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Waindrops [Makit0]█  OVERALL Plot waindrops (custom volume profiles) on user defined periods, for each period you get high and low, it slices each period in half to get independent vwap, volume profile and the volume traded per price at each half. It works on intraday charts only, up to 720m (12H). It can plot balanced or unbalanced waindrops, and volume profiles up to 24H sessions. As example you can setup unbalanced periods to get independent volume profiles for the overnight and cash sessions on the futures market, or 24H periods to get the full session volume profile of EURUSD The purpose of this indicator is twofold: 1 — from a Chartist point of view, to have an indicator which displays the volume in a more readable way 2 — from a Pine Coder point of view, to have an example of use for two very powerful tools on Pine Script:    • the recently updated drawing limit to 500 (from 50)    • the recently ability to use drawings arrays (lines and labels) If you are new to Pine Script and you are learning how to code, I hope you read all the code and comments on this indicator, all is designed for you, the variables and functions names, the sometimes too big explanations, the overall structure of the code, all is intended as an example on how to code in Pine Script a specific indicator from a very good specification in form of white paper If you wanna learn Pine Script form scratch just start HERE In case you have any kind of problem with Pine Script please use some of the awesome resources at our disposal: USRMAN , REFMAN , AWESOMENESS , MAGIC █  FEATURES Waindrops are a different way of seeing the volume and price plotted in a chart, its a volume profile indicator where you can see the volume of each price level plotted as a vertical histogram for each half of a custom period. By default the period is 60 so it plots an independent volume profile each 30m You can think of each waindrop as an user defined candlestick or bar with four key values:  • high of the period  • low of the period  • left vwap (volume weighted average price of the first half period)  • right vwap (volume weighted average price of the second half period) The waindrop can have 3 different colors (configurable by the user):  • GREEN: when the right vwap is higher than the left vwap (bullish sentiment )  • RED: when the right vwap is lower than the left vwap (bearish sentiment )  • BLUE: when the right vwap is equal than the left vwap ( neutral sentiment ) KEY FEATURES  • Help menu  • Custom periods  • Central bars  • Left/Right VWAPs  • Custom central bars and vwaps: color and pixels  • Highly configurable volume histogram: execution window, ticks, pixels, color, update frequency and fine tuning the neutral meaning  • Volume labels with custom size and color  • Tracking price dot to be able to see the current price when you hide your default candlesticks or bars █  SETTINGS Click here or set any impar period to see the HELP INFO : show the HELP INFO, if it is activated the indicator will not plot PERIOD SIZE (max 2880 min) : waindrop size in minutes, default 60, max 2880 to allow the first half of a 48H period as a full session volume profile BARS : show the central and vwap bars, default true    Central bars : show the central bars, default true    VWAP bars : show the left and right vwap bars, default true    Bars pixels : width of the bars in pixels, default 2    Bars color mode : bars color behavior    • BARS : gets the color from the 'Bars color' option on the settings panel    • HISTOGRAM : gets the color from the Bearish/Bullish/Neutral Histogram color options from the settings panel    Bars color : color for the central and vwap bars, default white HISTOGRAM show the volume histogram, default true    Execution window (x24H) : last 24H periods where the volume funcionality will be plotted, default 5    Ticks per bar (max 50) : width in ticks of each histogram bar, default 2    Updates per period : number of times the histogram will update    • ONE : update at the last bar of the period    • TWO : update at the last bar of each half period    • FOUR : slice the period in 4 quarters and updates at the last bar of each of them    • EACH BAR : updates at the close of each bar    Pixels per bar : width in pixels of each histogram bar, default 4    Neutral Treshold (ticks) : delta in ticks between left and right vwaps to identify a waindrop as neutral, default 0    Bearish Histogram color : histogram color when right vwap is lower than left vwap, default red    Bullish Histogram color : histogram color when right vwap is higher than left vwap, default green    Neutral Histogram color : histogram color when the delta between right and left vwaps is equal or lower than the Neutral treshold, default blue VOLUME LABELS : show volume labels    Volume labels color : color for the volume labels, default white    Volume Labels size : text size for the volume labels, choose between AUTO, TINY, SMALL, NORMAL or LARGE, default TINY TRACK PRICE : show a yellow ball tracking the last price, default true █  LIMITS This indicator only works on intraday charts (minutes only) up to 12H (720m), the lower chart timeframe you can use is 1m This indicator needs price, time and volume to work, it will not work on an index (there is no volume), the execution will not be allowed The histogram (volume profile) can be plotted on 24H sessions as limit but you can plot several 24H sessions █  ERRORS AND PERFORMANCE Depending on the choosed settings, the script performance will be highly affected and it will experience errors Two of the more common errors it can throw are:  • Calculation takes too long to execute  • Loop takes too long The indicator performance is highly related to the underlying volatility (tick wise), the script takes each candlestick or bar and for each tick in it stores the price and volume, if the ticker in your chart has thousands and thousands of ticks per bar the indicator will throw an error for sure, it can not calculate in time such amount of ticks. What all of that means? Simply put, this will throw error on the BITCOIN pair BTCUSD (high volatility with tick size 0.01) because it has too many ticks per bar, but lucky you it will work just fine on the futures contract BTC1! (tick size 5) because it has a lot less ticks per bar There are some options you can fine tune to boost the script performance, the more demanding option in terms of resources consumption is Updates per period , by default is maxed out so lowering this setting will improve the performance in a high way. If you wanna know more about how to improve the script performance, read the HELP INFO accessible from the settings panel █  HOW-TO SETUP The basic parameters to adjust are Period size , Ticks per bar and Pixels per bar  • Period size is the main setting, defines the waindrop size, to get a better looking histogram set bigger period and smaller chart timeframe  • Ticks per bar is the tricky one, adjust it differently for each underlying (ticker) volatility wise, for some you will need a low value, for others a high one.    To get a more accurate histogram set it as lower as you can (min value is 1)  • Pixels per bar allows you to adjust the width of each histogram bar, with it you can adjust the blank space between them or allow overlaping You must play with these three parameters until you obtain the desired histogram: smoother, sharper, etc... These are some of the different kind of charts you can setup thru the settings:  • Balanced Waindrops (default): charts with waindrops where the two halfs are of same size.    This is the default chart, just select a period (30m, 60m, 120m, 240m, pick your poison), adjust the histogram ticks and pixels and watch  • Unbalanced Waindrops: chart with waindrops where the two halfs are of different sizes.    Do you trade futures and want to plot a waindrop with the first half for the overnight session and the second half for the cash session? you got it;    just adjust the period to 1860 for any CME ticker (like ES1! for example) adjust the histogram ticks and pixels and watch  • Full Session Volume Profile: chart with waindrops where only the first half plots.    Do you use Volume profile to analize the market? Lucky you, now you can trick this one to plot it, just try a period of 780 on SPY, 2760 on ES1!, or 2880 on EURUSD    remember to adjust the histogram ticks and pixels for each underlying  • Only Bars: charts with only central and vwap bars plotted, simply deactivate the histogram and volume labels  • Only Histogram: charts with only the histogram plotted (volume profile charts), simply deactivate the bars and volume labels  • Only Volume: charts with only the raw volume numbers plotted, simply deactivate the bars and histogram If you wanna know more about custom full session periods for different asset classes, read the HELP INFO accessible from the settings panel EXAMPLES Full Session Volume Profile on MES 5m chart: Full Session Unbalanced Waindrop on MNQ 2m chart (left side Overnight session, right side Cash Session): The following examples will have the exact same charts but on four different tickers representing a futures contract, a forex pair, an etf and a stock. We are doing this to be able to see the different parameters we need for plotting the same kind of chart on different assets The chart composition is as follows:  • Left side: Volume Labels chart (period 10)  • Upper Right side: Waindrops (period 60)  • Lower Right side: Full Session Volume Profile The first example will specify the main parameters, the rest of the charts will have only the differences MES :  • Left: Period size: 10, Bars: uncheck, Histogram: uncheck, Execution window: 1, Ticks per bar: 2, Updates per period: EACH BAR,    Pixels per bar: 4, Volume labels: check, Track price: check  • Upper Right: Period size: 60, Bars: check, Bars color mode: HISTOGRAM, Histogram: check, Execution window: 2, Ticks per bar: 2,    Updates per period: EACH BAR, Pixels per bar: 4, Volume labels: uncheck, Track price: check  • Lower Right: Period size: 2760, Bars: uncheck, Histogram: check, Execution window: 1, Ticks per bar: 1, Updates per period: EACH BAR,    Pixels per bar: 2, Volume labels: uncheck, Track price: check EURUSD :  • Upper Right: Ticks per bar: 10  • Lower Right: Period size: 2880, Ticks per bar: 1, Pixels per bar: 1 SPY :  • Left: Ticks per bar: 3  • Upper Right: Ticks per bar: 5, Pixels per bar: 3  • Lower Right: Period size: 780, Ticks per bar: 2, Pixels per bar: 2 AAPL :  • Left: Ticks per bar: 2  • Upper Right: Ticks per bar: 6, Pixels per bar: 3  • Lower Right: Period size: 780, Ticks per bar: 1, Pixels per bar: 2 █  THANKS TO PineCoders for all they do, all the tools and help they provide and their involvement in making a better community scarf for the idea of coding a waindrops like indicator, I did not know something like that existed at all All the Pine Coders, Pine Pros and Pine Wizards, people who share their work and knowledge for the sake of it and helping others, I'm very grateful indeed I'm learning at each step of the way from you all, thanks for this awesome community; Opensource and shared knowledge: this is the way! (said with canned voice from inside my helmet :D) █  NOTE This description was formatted following THIS guidelines ═════════════════════════════════════════════════════════════════════════ I sincerely hope you enjoy reading and using this work as much as I enjoyed developing it :D GOOD LUCK AND HAPPY TRADING!
Pine Script®指标
由makit0提供
108
Delta Volume Columns Pro [LucF]█  OVERVIEW This indicator displays volume​​ delta information calculated with intrabar inspection on historical bars, and feed updates when running in realtime. It is designed to run in a pane and can display either stacked buy/sell volume​ columns or a signal line which can be calculated and displayed in many different ways. Five different models are offered to reveal different characteristics of the calculated volume​ delta information. Many options are offered to visualize the calculations, giving you much leeway in morphing the indicator's visuals to suit your needs. If you value delta volume​ information, I hope you will find the time required to master Delta Volume​ Columns Pro well worth the investment. I am confident that if you combine a proper understanding of the indicator's information with an intimate knowledge of the volume​ idiosyncrasies on the markets you trade, you can extract useful market intelligence using this tool. █  WARNINGS 1. The indicator only works on markets where volume​ information is available,   Please validate that your symbol's feed carries volume​ information before asking me why the indicator doesn't plot values. 2. When you refresh your chart or re-execute the script on the chart, the indicator will repaint because elapsed realtime bars will then recalculate as historical bars. 3. Because the indicator uses different modes of calculation on historical and realtime bars, it's critical that you understand the differences between them. Details are provided further down. 4. Calculations using intrabar inspection on historical bars can only be done from some chart timeframes. See further down for a list of supported timeframes.   If the chart's timeframe is not supported, no historical volume​ delta will display. █  CONCEPTS Chart bars Three different types of bars are used in charts:  1. Historical bars are bars that have already closed when the script executes on them.  2. The realtime bar is the current, incomplete bar where a script is running on an open market. There is only one active realtime bar on your chart at any given time.    The realtime bar is where alerts trigger.  3. Elapsed realtime bars are bars that were calculated when they were realtime bars but have since closed.    When a script re-executes on a chart because the browser tab is refreshed or some of its inputs are changed, elapsed realtime bars are recalculated as historical bars. Why does this indicator use two modes of calculation? Historical bars on TradingView charts contain OHLCV data only, which is insufficient to calculate volume​ delta on them with any level of precision. To mine more detailed information from those bars we look at intrabars , i.e., bars from a smaller timeframe (we call it the intrabar timeframe ) that are contained in one chart bar. If your chart Is running at 1D on a 24x7 market for example, most 1D chart bars will contain 24 underlying 1H bars in their dilation. On historical bars, this indicator looks at those intrabars to amass volume​ delta information. If the intrabar is up, its volume​ goes in the Buy bin, and inversely for the Sell bin. When price does not move on an intrabar, the polarity of the last known movement is used to determine in which bin its volume​ goes. In realtime, we have access to price and volume​ change for each update of the chart. Because a 1D chart bar can be updated tens of thousands of times during the day, volume​ delta calculations on those updates is much more precise. This precision, however, comes at a price:  — The script must be running on the chart for it to keep calculating in realtime.  — If you refresh your chart you will lose all accumulated realtime calculations on elapsed realtime bars, and the realtime bar.   Elapsed realtime bars will recalculate as historical bars, i.e., using intrabar inspection, and the realtime bar's calculations will reset.   When the script recalculates elapsed realtime bars as historical bars, the values on those bars will change, which means the script repaints in those conditions.  — When the indicator first calculates on a chart containing an incomplete realtime bar, it will count ALL the existing volume​ on the bar as Buy or Sell volume​,   depending on the polarity of the bar at that point. This will skew calculations for that first bar. Scripts have no access to the history of a realtime bar's previous updates,   and intrabar inspection cannot be used on realtime bars, so this is the only to go about this.  — Even if alerts only trigger upon confirmation of their conditions after the realtime bar closes, they are repainting alerts   because they would perhaps not have calculated the same way using intrabar inspection.  — On markets like stocks that often have different EOD​ and intraday feeds and volume​ information,   the volume's scale may not be the same for the realtime bar if your chart is at 1D, for example,   and the indicator is using an intraday timeframe to calculate on historical bars.  — Any chart timeframe can be used in realtime mode, but plots that include moving averages in their calculations may require many elapsed realtime bars before they can calculate.   You might prefer drastically reducing the periods of the moving averages, or using the volume​ columns mode, which displays instant values, instead of the line. Volume Delta Balances This indicator uses a variety of methods to evaluate five volume​ delta balances and derive other values from those balances. The five balances are: 1 — On Bar Balance : This is the only balance using instant values; it is simply the subtraction of the Sell volume​ from the Buy volume​ on the bar. 2 — Average Balance : Calculates a distinct EMA for both the Buy and Sell volumes, and subtracts the Sell EMA from the Buy EMA. 3 — Momentum Balance : Starts by calculating, separately for both Buy and Sell volumes, the difference between the same EMAs used in "Average Balance" and   an SMA of double the period used for the "Average Balance" EMAs. The difference for the Sell side is subtracted from the difference for the Buy side,   and an RSI of that value is calculated and brought over the −50/+50 scale. 4 — Relative Balance : The reference values used in the calculation are the Buy and Sell EMAs used in the "Average Balance".   From those, we calculate two intermediate values using how much the instant Buy and Sell volumes on the bar exceed their respective EMA — but with a twist.   If the bar's Buy volume​ does not exceed the EMA of Buy volume​, a zero value is used. The same goes for the Sell volume​ with the EMA of Sell volume​.   Once we have our two intermediate values for the Buy and Sell volumes exceeding their respective MA, we subtract them. The final "Relative Balance" value is an ALMA of that subtraction.   The rationale behind using zero values when the bar's Buy/Sell volume​ does not exceed its EMA is to only take into account the more significant volume​.   If both instant volume​ values exceed their MA, then the difference between the two is the signal's value.   The signal is called "relative" because the intermediate values are the difference between the instant Buy/Sell volumes and their respective MA.   This balance flatlines when the bar's Buy/Sell volumes do not exceed their EMAs, which makes it useful to spot areas where trader interest dwindles, such as consolidations.   The smaller the period of the final value's ALMA, the more easily you will see the balance flatline. These flat zones should be considered no-trade zones. 5 — Percent Balance : This balance is the ALMA of the ratio of the "On Bar Balance" value, i.e., the volume​ delta balance on the bar (which can be positive or negative),   over the total volume for that bar. From the balances and marker conditions, two more values are calculated: 1 — Marker Bias : It sums the up/down (+1/‒1) occurrences of the markers 1 to 4 over a period you define, so it ranges from −4 to +4, times the period.   Its calculation will depend on the modes used to calculate markers 3 and 4. 2 — Combined Balances : This is the sum of the bull/bear (+1/−1) states of each of the five balances, so it ranges from −5 to +5. █  FEATURES The indicator has two main modes of operation: Columns and Line . Columns • In Columns mode you can display stacked Buy/Sell volume​ columns. • The buy section always appears above the centerline, the sell section below. • The top and bottom sections can be colored independently using eight different methods. • The EMAs of the Buy/Sell values can be displayed (these are the same EMAs used to calculate the "Average Balance"). Line • Displays one of seven signals: the five balances or one of two complementary values, i.e., the "Marker Bias" or the "Combined Balances". • You can color the line and its fill using independent calculation modes to pack more information in the display.  You can thus appraise the state of 3 different values using the line itself, its color and the color of its fill. • A "Divergence Levels" feature will use the line to automatically draw expanding levels on divergence events. Default settings Using the indicator's default settings, this is the information displayed: • The line is calculated on the "Average Balance". • The line's color is determined by the bull/bear state of the "Percent Balance". • The line's fill gradient is determined by the advances/declines of the "Momentum Balance". • The orange divergence dots are calculated using discrepancies between the polarity of the "On Bar Balance" and the chart's bar. • The divergence levels are determined using the line's level when a divergence occurs. • The background's fill gradient is calculated on advances/declines of the "Marker Bias". • The chart bars are colored using advances/declines of the "Relative Balance". Divergences are shown in orange. • The intrabar timeframe is automatically determined from the chart's timeframe so that a minimum of 50 intrabars are used to calculate volume​ delta on historical bars. Alerts The configuration of the marker conditions explained further is what determines the conditions that will trigger alerts created from this script. Note that simply selecting the display of markers does not create alerts. To create an alert on this script, you must use ALT-A from the chart. You can create multiple alerts triggering on different conditions from this same script; simply configure the markers so they define the trigger conditions for each alert before creating the alert. The configuration of the script's inputs is saved with the alert, so from then on you can change them without affecting the alert. Alert messages will mention the marker(s) that triggered the specific alert event. Keep in mind, when creating alerts on small chart timeframes, that discrepancies between alert triggers and markers displayed on your chart are to be expected. This is because the alert and your chart are running two distinct instances of the indicator on different servers and different feeds. Also keep in mind that while alerts only trigger on confirmed conditions, they are calculated using realtime calculation mode, which entails that if you refresh your chart and elapsed realtime bars recalculate as historical bars using intrabar inspection, markers will not appear in the same places they appeared in realtime. So it's important to understand that even though the alert conditions are confirmed when they trigger, these alerts will repaint. Let's go through the sections of the script's inputs. Columns The size of the Buy/Sell columns always represents their respective importance on the bar, but the coloring mode for tops and bottoms is independent. The default setup uses a standard coloring mode where the Buy/Sell columns are always in the bull/bear color with a higher intensity for the winning side. Seven other coloring modes allow you to pack more information in the columns. When choosing to color the top columns using a bull/bear gradient on "Average Balance", for example, you will have bull/bear colored tops. In order for the color of the bottom columns to continue to show the instant bar balance, you can then choose the "On Bar Balance — Dual Solid Colors" coloring mode to make those bars the color of the winning side for that bar. You can display the averages of the Buy and Sell columns. If you do, its coloring is controlled through the "Line" and "Line fill" sections below. Line and Line fill You can select the calculation mode and the thickness of the line, and independent calculations to determine the line's color and fill. Zero Line The zero line can display dots when all five balances are bull/bear. Divergences You first select the detection mode. Divergences occur whenever the up/down direction of the signal does not match the up/down polarity of the bar. Divergences are used in three components of the indicator's visuals: the orange dot, colored chart bars, and to calculate the divergence levels on the line. The divergence levels are dynamic levels that automatically build from the line's values on divergence events. On consecutive divergences, the levels will expand, creating a channel. This implementation of the divergence levels corresponds to my view that divergences indicate anomalies, hesitations, points of uncertainty if you will. It precludes any attempt to identify a directional bias to divergences. Accordingly, the levels merely take note of divergence events and mark those points in time with levels. Traders then have a reference point from which they can evaluate further movement. The bull/bear/neutral colors used to plot the levels are also congruent with this view in that they are determined by the line's position relative to the levels, which is how I think divergences can be put to the most effective use. One of the coloring modes for the line's fill uses advances/declines in the line after divergence events. Background The background can show a bull/bear gradient on six different calculations. As with other gradients, you can adjust its brightness to make its importance proportional to how you use it in your analysis. Chart bars Chart bars can be colored using seven different methods. You have the option of emptying the body of bars where volume​ does not increase, as does my TLD indicator, and you can choose whether you want to show divergences. Intrabar Timeframe This is the intrabar timeframe that will be used to calculate volume​ delta using intrabar inspection on historical bars. You can choose between four modes. The three "Auto-steps" modes calculate, from the chart's timeframe, the intrabar timeframe where the said number of intrabars will make up the dilation of chart bars. Adjustments are made for non-24x7 markets. "Fixed" mode allows you to select the intrabar timeframe you want. Checking the "Show TF" box will display in the lower-right corner the intrabar timeframe used at any given moment. The proper selection of the intrabar timeframe is important. It must achieve maximal granularity to produce precise results while not unduly slowing down calculations, or worse, causing runtime errors. Note that historical depth will vary with the intrabar timeframe. The smaller the timeframe, the shallower historical plots you will be. Markers Markers appear when the required condition has been confirmed on a closed bar. The configuration of the markers when you create an alert is what determines when the alert will trigger. Five markers are available: • Balances Agreement : All five balances are either bullish​ or bearish​. • Double Bumps : A double bump is two consecutive up/down bars with +/‒ volume​​ delta, and rising Buy/Sell volume​ above its average. • Divergence confirmations : A divergence is confirmed up/down when the chosen balance is up/down on the previous bar when that bar was down/up, and this bar is up/down. • Balance Shifts : These are bull/bear transitions of the selected signal. • Marker Bias Shifts : Marker bias shifts occur when it crosses into bull/bear territory. Periods Allows control over the periods of the different moving averages used to calculate the balances. Volume​ Discrepancies Stock exchanges do not report the same volume​ for intraday and daily (or higher) resolutions. Other variations in how volume​ information is reported can also occur in other markets, namely Forex, where volume​ irregularities can even occur between different intraday timeframes. This will cause discrepancies between the total volume​ on the bar at the chart's timeframe, and the total volume​​ calculated by adding the volume​​ of the intrabars in that bar's dilation. This does not necessarily invalidate the volume​​ delta information calculated from intrabars, but it tells us that we are using partial volume​ data. A mechanism to detect chart vs intrabar timeframe volume​​ discrepancies is provided. It allows you to define a threshold percentage above which the background will indicate a difference has been detected. Other Settings You can control here the display of the gray dot reminder on realtime bars, and the display of error messages if you are using a chart timeframe that is not greater than the fixed intrabar timeframe, when you use that mode. Disabling the message can be useful if you only use realtime mode at chart timeframes that do not support intrabar inspection. █  RAMBLINGS On Volume​ Delta Volume​ is arguably the best complement to interpret price action, and I consider volume​ delta to be the most effective way of processing volume​ information. In periods of low-volatility price consolidations, volume​ will typically also be lower than normal, but slight imbalances in the trend of the buy/sell volume​ balance can sometimes help put early odds on the direction of the break from consolidation. Additionally, the progression of the volume​ imbalance can help determine the proximity of the breakout. I also find volume​ delta and the number of divergences very useful to evaluate the strength of trends. In trends, I am looking for "slow and steady", i.e., relatively low volatility​ and pauses where price action doesn't look like world affairs are being reassessed. In my personal mythology, this type of trend is often more resilient than high-volatility breakouts, especially when volume​ balance confirms the general agreement of traders signaled by the low-volatility usually accompanying this type of trend. The volume​ action on pauses will often help me decide between aggressively taking profits, tightening a stop or going for a longer-term movement. As for reversals, they generally occur in high-volatility areas where entering trades is more expensive and riskier. While the identification of counter-trend reversals fascinates many traders to no end, they represent poor opportunities in my view. Volume​ imbalances often precede reversals, but I prefer to use volume​ delta information to identify the areas following reversals where I can confirm them and make relatively low-cost entries with better odds. On "Buy/Sell" Volume Buying or selling volume​ are misnomers, as every unit of volume​ transacted is both bought and sold by two different traders. While this does not keep me from using the terms, there is no such thing as “buy only” or “sell only” volume​. Trader lingo is riddled with peculiarities. Divergences The divergence detection method used here relies on a difference between the direction of a signal and the polarity (up/down) of a chart bar. When using the default "On Bar Balance" to detect divergences, however, only the bar's volume​ delta is used. You may wonder how there can be divergences between buying/selling volume​ information and price movement on one bar. This will sometimes be due to the calculation's shortcomings, but divergences may also occur in instances where because of order book structure, it takes less volume​ to increase the price of an asset than it takes to decrease it. As usual, divergences are points of interest because they reveal imbalances, which may or may not become turning points. To your pattern-hungry brain, the divergences displayed by this indicator will — as they do on other indicators — appear to often indicate turnarounds. My opinion is that reality is generally quite sobering and I have no reliable information that would tend to prove otherwise. Exercise caution when using them. Consequently, I do not share the overwhelming enthusiasm of traders in identifying bullish​/bearish​ divergences. For me, the best course of action when a divergence occurs is to wait and see what happens from there. That is the rationale underlying how my divergence levels work; they take note of a signal's level when a divergence occurs, and it's the signal's behavior from that point on that determines if the post-divergence action is bullish​/bearish​. Superfluity In "The Bed of Procrustes", Nassim Nicholas Taleb writes: To bankrupt a fool, give him information . This indicator can display lots of information. While learning to use a new indicator inevitably requires an adaptation period where we put it through its paces and try out all its options, once you have become used to it and decide to adopt it, rigorously eliminate the components you don't use and configure the remaining ones so their visual prominence reflects their relative importance in your analysis. I tried to provide flexible options for traders to control this indicator's visuals for that exact reason — not for window dressing. █  LIMITATIONS • This script uses a special characteristic of the `security()` function allowing the inspection of intrabars — which is not officially supported by TradingView.  It has the advantage of permitting a more robust calculation of volume​ delta than other methods on historical bars, but also has its limits. • Intrabar inspection only works on some chart timeframes: 3, 5, 10, 15 and 30 minutes, 1, 2, 3, 4, 6, and 12 hours, 1 day, 1 week and 1 month.  The script’s code can be modified to run on other resolutions. • When the difference between the chart’s timeframe and the intrabar timeframe is too great, runtime errors will occur. The Auto-Steps selection mechanisms should avoid this. • All volume​ is not created equally. Its source, components, quality and reliability will vary considerably with sectors and instruments.  The higher the quality, the more reliably volume​ delta information can be used to guide your decisions.  You should make it your responsibility to understand the volume​ information provided in the data feeds you use. It will help you make the most of volume​ delta. █  NOTES For traders • The Data Window shows key values for the indicator. • While this indicator displays some of the same information calculated in my Delta Volume Columns ,  I have elected to make it a separate publication so that traders continue to have a simpler alternative available to them. Both code bases will continue to evolve separately. • All gradients used in this indicator determine their brightness intensities using advances/declines in the signal—not their relative position in a pre-determined scale. • Volume​ delta being relative, by nature, it is particularly well-suited to Forex markets, as it filters out quite elegantly the cyclical volume​ data characterizing the sector. If you are interested in volume​ delta, consider having a look at my other "Delta Volume" indicators: • Delta Volume Realtime Action displays realtime volume​ delta and tick information on the chart. • Delta Volume Candles builds volume​​ delta candles on the chart. • Delta Volume Columns is a simpler version of this indicator. For coders • I use the `f_c_gradientRelativePro()` from the PineCoders Color Gradient Framework to build my gradients.  This function has the advantage of allowing begin/end colors for both the bull and bear colors. It also allows us to define the number of steps allowed for each gradient.  I use this to modulate the gradients so they perform optimally on the combination of the signal used to calculate advances/declines,  but also the nature of the visual component the gradient applies to. I use fewer steps for choppy signals and when the gradient is used on discrete visual components  such as volume​ columns or chart bars. • I use the PineCoders Coding Conventions for Pine to write my scripts. • I used functions modified from the PineCoders MTF Selection Framework for the selection of timeframes. █  THANKS TO: — The devs from TradingView's Pine and other teams, and the PineCoders who collaborate with them. They are doing amazing work,  and much of what this indicator does could not be done without their recent improvements to Pine. — A guy called Kuan who commented on a Backtest Rookies presentation of their Volume Profile indicator using a `for` loop.  This indicator started from the intrabar inspection technique illustrated in Kuan's snippet. — theheirophant , my partner in the exploration of the sometimes weird abysses of `security()`’s behavior at intrabar timeframes. — midtownsk8rguy , my brilliant companion in mining the depths of Pine graphics.
Pine Script®指标
由LucF提供
125
Ultimate RSI [captainua]Ultimate RSI Overview This indicator combines multiple RSI calculations with volume analysis, divergence detection, and trend filtering to provide a comprehensive RSI-based trading system. The script calculates RSI using three different periods (6, 14, 24) and applies various smoothing methods to reduce noise while maintaining responsiveness. The combination of these features creates a multi-layered confirmation system that reduces false signals by requiring alignment across multiple indicators and timeframes. The script includes optimized configuration presets for instant setup: Scalping, Day Trading, Swing Trading, and Position Trading. Simply select a preset to instantly configure all settings for your trading style, or use Custom mode for full manual control. All settings include automatic input validation to prevent configuration errors and ensure optimal performance. Configuration Presets The script includes preset configurations optimized for different trading styles, allowing you to instantly configure the indicator for your preferred trading approach. Simply select a preset from the "Configuration Preset" dropdown menu: - Scalping: Optimized for fast-paced trading with shorter RSI periods (4, 7, 9) and minimal smoothing. Noise reduction is automatically disabled, and momentum confirmation is disabled to allow faster signal generation. Designed for quick entries and exits in volatile markets. - Day Trading: Balanced configuration for intraday trading with moderate RSI periods (6, 9, 14) and light smoothing. Momentum confirmation is enabled for better signal quality. Ideal for day trading strategies requiring timely but accurate signals. - Swing Trading: Configured for medium-term positions with standard RSI periods (14, 14, 21) and moderate smoothing. Provides smoother signals suitable for swing trading timeframes. All noise reduction features remain active. - Position Trading: Optimized for longer-term trades with extended RSI periods (24, 21, 28) and heavier smoothing. Filters are configured for highest-quality signals. Best for position traders holding trades over multiple days or weeks. - Custom: Full manual control over all settings. All input parameters are available for complete customization. This is the default mode and maintains full backward compatibility with previous versions. When a preset is selected, it automatically adjusts RSI periods, smoothing lengths, and filter settings to match the trading style. The preset configurations ensure optimal settings are applied instantly, eliminating the need for manual configuration. All settings can still be manually overridden if needed, providing flexibility while maintaining ease of use. Input Validation and Error Prevention The script includes comprehensive input validation to prevent configuration errors: - Cross-Input Validation: Smoothing lengths are automatically validated to ensure they are always less than their corresponding RSI period length. If you set a smoothing length greater than or equal to the RSI length, the script automatically adjusts it to (RSI Length - 1). This prevents logical errors and ensures valid configurations. - Input Range Validation: All numeric inputs have minimum and maximum value constraints enforced by TradingView's input system, preventing invalid parameter values. - Smart Defaults: Preset configurations use validated default values that are tested and optimized for each trading style. When switching between presets, all related settings are automatically updated to maintain consistency. Core Calculations Multi-Period RSI: The script calculates RSI using the standard Wilder's RSI formula: RSI = 100 - (100 / (1 + RS)), where RS = Average Gain / Average Loss over the specified period. Three separate RSI calculations run simultaneously: - RSI(6): Uses 6-period lookback for high sensitivity to recent price changes, useful for scalping and early signal detection - RSI(14): Standard 14-period RSI for balanced analysis, the most commonly used RSI period - RSI(24): Longer 24-period RSI for trend confirmation, provides smoother signals with less noise Each RSI can be smoothed using EMA, SMA, RMA (Wilder's smoothing), WMA, or Zero-Lag smoothing. Zero-Lag smoothing uses the formula: ZL-RSI = RSI + (RSI - RSI ) to reduce lag while maintaining signal quality. You can apply individual smoothing lengths to each RSI period, or use global smoothing where all three RSIs share the same smoothing length. Dynamic Overbought/Oversold Thresholds: Static thresholds (default 70/30) are adjusted based on market volatility using ATR. The formula: Dynamic OB = Base OB + (ATR × Volatility Multiplier × Base Percentage / 100), Dynamic OS = Base OS - (ATR × Volatility Multiplier × Base Percentage / 100). This adapts to volatile markets where traditional 70/30 levels may be too restrictive. During high volatility, the dynamic thresholds widen, and during low volatility, they narrow. The thresholds are clamped between 0-100 to remain within RSI bounds. The ATR is cached for performance optimization, updating on confirmed bars and real-time bars. Adaptive RSI Calculation: An adaptive RSI adjusts the standard RSI(14) based on current volatility relative to average volatility. The calculation: Adaptive Factor = (Current ATR / SMA of ATR over 20 periods) × Volatility Multiplier. If SMA of ATR is zero (edge case), the adaptive factor defaults to 0. The adaptive RSI = Base RSI × (1 + Adaptive Factor), clamped to 0-100. This makes the indicator more responsive during high volatility periods when traditional RSI may lag. The adaptive RSI is used for signal generation (buy/sell signals) but is not plotted on the chart. Overbought/Oversold Fill Zones: The script provides visual fill zones between the RSI line and the threshold lines when RSI is in overbought or oversold territory. The fill logic uses inclusive conditions: fills are shown when RSI is currently in the zone OR was in the zone on the previous bar. This ensures complete coverage of entry and exit boundaries. A minimum gap of 0.1 RSI points is maintained between the RSI plot and threshold line to ensure reliable polygon rendering in TradingView. The fill uses invisible plots at the threshold levels and the RSI value, with the fill color applied between them. You can select which RSI (6, 14, or 24) to use for the fill zones. Divergence Detection Regular Divergence: Bullish divergence: Price makes a lower low (current low < lowest low from previous lookback period) while RSI makes a higher low (current RSI > lowest RSI from previous lookback period). Bearish divergence: Price makes a higher high (current high > highest high from previous lookback period) while RSI makes a lower high (current RSI < highest RSI from previous lookback period). The script compares current price/RSI values to the lowest/highest values from the previous lookback period using ta.lowest() and ta.highest() functions with index to reference the previous period's extreme. Pivot-Based Divergence: An enhanced divergence detection method that uses actual pivot points instead of simple lowest/highest comparisons. This provides more accurate divergence detection by identifying significant pivot lows/highs in both price and RSI. The pivot-based method uses a tolerance-based approach with configurable constants: 1% tolerance for price comparisons (priceTolerancePercent = 0.01) and 1.0 RSI point absolute tolerance for RSI comparisons (pivotTolerance = 1.0). Minimum divergence threshold is 1.0 RSI point (minDivergenceThreshold = 1.0). It looks for two recent pivot points and compares them: for bullish divergence, price makes a lower low (at least 1% lower) while RSI makes a higher low (at least 1.0 point higher). This method reduces false divergences by requiring actual pivot points rather than just any low/high within a period. When enabled, pivot-based divergence replaces the traditional method for more accurate signal generation. Strong Divergence: Regular divergence is confirmed by an engulfing candle pattern. Bullish engulfing requires: (1) Previous candle is bearish (close < open ), (2) Current candle is bullish (close > open), (3) Current close > previous open, (4) Current open < previous close. Bearish engulfing is the inverse: previous bullish, current bearish, current close < previous open, current open > previous close. Strong divergence signals are marked with visual indicators (🐂 for bullish, 🐻 for bearish) and have separate alert conditions. Hidden Divergence: Continuation patterns that signal trend continuation rather than reversal. Bullish hidden divergence: Price makes a higher low (current low > lowest low from previous period) but RSI makes a lower low (current RSI < lowest RSI from previous period). Bearish hidden divergence: Price makes a lower high (current high < highest high from previous period) but RSI makes a higher high (current RSI > highest RSI from previous period). These patterns indicate the trend is likely to continue in the current direction. Volume Confirmation System Volume threshold filtering requires current volume to exceed the volume SMA multiplied by the threshold factor. The formula: Volume Confirmed = Volume > (Volume SMA × Threshold). If the threshold is set to 0.1 or lower, volume confirmation is effectively disabled (always returns true). This allows you to use the indicator without volume filtering if desired. Volume Climax is detected when volume exceeds: Volume SMA + (Volume StdDev × Multiplier). This indicates potential capitulation moments where extreme volume accompanies price movements. Volume Dry-Up is detected when volume falls below: Volume SMA - (Volume StdDev × Multiplier), indicating low participation periods that may produce unreliable signals. The volume SMA is cached for performance, updating on confirmed and real-time bars. Multi-RSI Synergy The script generates signals when multiple RSI periods align in overbought or oversold zones. This creates a confirmation system that reduces false signals. In "ALL" mode, all three RSIs (6, 14, 24) must be simultaneously above the overbought threshold OR all three must be below the oversold threshold. In "2-of-3" mode, any two of the three RSIs must align in the same direction. The script counts how many RSIs are in each zone: twoOfThreeOB = ((rsi6OB ? 1 : 0) + (rsi14OB ? 1 : 0) + (rsi24OB ? 1 : 0)) >= 2. Synergy signals require: (1) Multi-RSI alignment (ALL or 2-of-3), (2) Volume confirmation, (3) Reset condition satisfied (enough bars since last synergy signal), (4) Additional filters passed (RSI50, Trend, ADX, Volume Dry-Up avoidance). Separate reset conditions track buy and sell signals independently. The reset condition uses ta.barssince() to count bars since the last trigger, returning true if the condition never occurred (allowing first signal) or if enough bars have passed. Regression Forecasting The script uses historical RSI values to forecast future RSI direction using four methods. The forecast horizon is configurable (1-50 bars ahead). Historical data is collected into an array, and regression coefficients are calculated based on the selected method. Linear Regression: Calculates the least-squares fit line (y = mx + b) through the last N RSI values. The calculation: meanX = sumX / horizon, meanY = sumY / horizon, denominator = sumX² - horizon × meanX², m = (sumXY - horizon × meanX × meanY) / denominator, b = meanY - m × meanX. The forecast projects this line forward: forecast = b + m × i for i = 1 to horizon. Polynomial Regression: Fits a quadratic curve (y = ax² + bx + c) to capture non-linear trends. The system of equations is solved using Cramer's rule with a 3×3 determinant. If the determinant is too small (< 0.0001), the system falls back to linear regression. Coefficients are calculated by solving: n×c + sumX×b + sumX²×a = sumY, sumX×c + sumX²×b + sumX³×a = sumXY, sumX²×c + sumX³×b + sumX⁴×a = sumX²Y. Note: Due to the O(n³) computational complexity of polynomial regression, the forecast horizon is automatically limited to a maximum of 20 bars when using polynomial regression to maintain optimal performance. If you set a horizon greater than 20 bars with polynomial regression, it will be automatically capped at 20 bars. Exponential Smoothing: Applies exponential smoothing with adaptive alpha = 2/(horizon+1). The smoothing iterates from oldest to newest value: smoothed = alpha × series + (1 - alpha) × smoothed. Trend is calculated by comparing current smoothed value to an earlier smoothed value (at 60% of horizon): trend = (smoothed - earlierSmoothed) / (horizon - earlierIdx). Forecast: forecast = base + trend × i. Moving Average: Uses the difference between short MA (horizon/2) and long MA (horizon) to estimate trend direction. Trend = (maShort - maLong) / (longLen - shortLen). Forecast: forecast = maShort + trend × i. Confidence bands are calculated using RMSE (Root Mean Squared Error) of historical forecast accuracy. The error calculation compares historical values with forecast values: RMSE = sqrt(sumSquaredError / count). If insufficient data exists, it falls back to calculating standard deviation of recent RSI values. Confidence bands = forecast ± (RMSE × confidenceLevel). All forecast values and confidence bands are clamped to 0-100 to remain within RSI bounds. The regression functions include comprehensive safety checks: horizon validation (must not exceed array size), empty array handling, edge case handling for horizon=1 scenarios, division-by-zero protection, and bounds checking for all array access operations to prevent runtime errors. Strong Top/Bottom Detection Strong buy signals require three conditions: (1) RSI is at its lowest point within the bottom period: rsiVal <= ta.lowest(rsiVal, bottomPeriod), (2) RSI is below the oversold threshold minus a buffer: rsiVal < (oversoldThreshold - rsiTopBottomBuffer), where rsiTopBottomBuffer = 2.0 RSI points, (3) The absolute difference between current RSI and the lowest RSI exceeds the threshold value: abs(rsiVal - ta.lowest(rsiVal, bottomPeriod)) > threshold. This indicates a bounce from extreme levels with sufficient distance from the absolute low. Strong sell signals use the inverse logic: RSI at highest point, above overbought threshold + rsiTopBottomBuffer (2.0 RSI points), and difference from highest exceeds threshold. Both signals also require: volume confirmation, reset condition satisfied (separate reset for buy vs sell), and all additional filters passed (RSI50, Trend, ADX, Volume Dry-Up avoidance). The reset condition uses separate logic for buy and sell: resetCondBuy checks bars since isRSIAtBottom, resetCondSell checks bars since isRSIAtTop. This ensures buy signals reset based on bottom conditions and sell signals reset based on top conditions, preventing incorrect signal blocking. Filtering System RSI(50) Filter: Only allows buy signals when RSI(14) > 50 (bullish momentum) and sell signals when RSI(14) < 50 (bearish momentum). This filter ensures you're buying in uptrends and selling in downtrends from a momentum perspective. The filter is optional and can be disabled. Recommended to enable for noise reduction. Trend Filter: Uses a long-term EMA (default 200) to determine trend direction. Buy signals require price above EMA, sell signals require price below EMA. The EMA slope is calculated as: emaSlope = ema - ema . Optional EMA slope filter additionally requires the EMA to be rising (slope > 0) for buy signals or falling (slope < 0) for sell signals. This provides stronger trend confirmation by requiring both price position and EMA direction. ADX Filter: Uses the Directional Movement Index (calculated via ta.dmi()) to measure trend strength. Signals only fire when ADX exceeds the threshold (default 20), indicating a strong trend rather than choppy markets. The ADX calculation uses separate length and smoothing parameters. This filter helps avoid signals during sideways/consolidation periods. Volume Dry-Up Avoidance: Prevents signals during periods of extremely low volume relative to average. If volume dry-up is detected and the filter is enabled, signals are blocked. This helps avoid unreliable signals that occur during low participation periods. RSI Momentum Confirmation: Requires RSI to be accelerating in the signal direction before confirming signals. For buy signals, RSI must be consistently rising (recovering from oversold) over the lookback period. For sell signals, RSI must be consistently falling (declining from overbought) over the lookback period. The momentum check verifies that all consecutive changes are in the correct direction AND the cumulative change is significant. This filter ensures signals only fire when RSI momentum aligns with the signal direction, reducing false signals from weak momentum. Multi-Timeframe Confirmation: Requires higher timeframe RSI to align with the signal direction. For buy signals, current RSI must be below the higher timeframe RSI by at least the confirmation threshold. For sell signals, current RSI must be above the higher timeframe RSI by at least the confirmation threshold. This ensures signals align with the larger trend context, reducing counter-trend trades. The higher timeframe RSI is fetched using request.security() from the selected timeframe. All filters use the pattern: filterResult = not filterEnabled OR conditionMet. This means if a filter is disabled, it always passes (returns true). Filters can be combined, and all must pass for a signal to fire. RSI Centerline and Period Crossovers RSI(50) Centerline Crossovers: Detects when the selected RSI source crosses above or below the 50 centerline. Bullish crossover: ta.crossover(rsiSource, 50), bearish crossover: ta.crossunder(rsiSource, 50). You can select which RSI (6, 14, or 24) to use for these crossovers. These signals indicate momentum shifts from bearish to bullish (above 50) or bullish to bearish (below 50). RSI Period Crossovers: Detects when different RSI periods cross each other. Available pairs: RSI(6) × RSI(14), RSI(14) × RSI(24), or RSI(6) × RSI(24). Bullish crossover: fast RSI crosses above slow RSI (ta.crossover(rsiFast, rsiSlow)), indicating momentum acceleration. Bearish crossover: fast RSI crosses below slow RSI (ta.crossunder(rsiFast, rsiSlow)), indicating momentum deceleration. These crossovers can signal shifts in momentum before price moves. StochRSI Calculation Stochastic RSI applies the Stochastic oscillator formula to RSI values instead of price. The calculation: %K = ((RSI - Lowest RSI) / (Highest RSI - Lowest RSI)) × 100, where the lookback is the StochRSI length. If the range is zero, %K defaults to 50.0. %K is then smoothed using SMA with the %K smoothing length. %D is calculated as SMA of smoothed %K with the %D smoothing length. All values are clamped to 0-100. You can select which RSI (6, 14, or 24) to use as the source for StochRSI calculation. RSI Bollinger Bands Bollinger Bands are applied to RSI(14) instead of price. The calculation: Basis = SMA(RSI(14), BB Period), StdDev = stdev(RSI(14), BB Period), Upper = Basis + (StdDev × Deviation Multiplier), Lower = Basis - (StdDev × Deviation Multiplier). This creates dynamic zones around RSI that adapt to RSI volatility. When RSI touches or exceeds the bands, it indicates extreme conditions relative to recent RSI behavior. Noise Reduction System The script includes a comprehensive noise reduction system to filter false signals and improve accuracy. When enabled, signals must pass multiple quality checks: Signal Strength Requirement: RSI must be at least X points away from the centerline (50). For buy signals, RSI must be at least X points below 50. For sell signals, RSI must be at least X points above 50. This ensures signals only trigger when RSI is significantly in oversold/overbought territory, not just near neutral. Extreme Zone Requirement: RSI must be deep in the OB/OS zone. For buy signals, RSI must be at least X points below the oversold threshold. For sell signals, RSI must be at least X points above the overbought threshold. This ensures signals only fire in extreme conditions where reversals are more likely. Consecutive Bar Confirmation: The signal condition must persist for N consecutive bars before triggering. This reduces false signals from single-bar spikes or noise. The confirmation checks that the signal condition was true for all bars in the lookback period. Zone Persistence (Optional): Requires RSI to remain in the OB/OS zone for N consecutive bars, not just touch it. This ensures RSI is truly in an extreme state rather than just briefly touching the threshold. When enabled, this provides stricter filtering for higher-quality signals. RSI Slope Confirmation (Optional): Requires RSI to be moving in the expected signal direction. For buy signals, RSI should be rising (recovering from oversold). For sell signals, RSI should be falling (declining from overbought). This ensures momentum is aligned with the signal direction. The slope is calculated by comparing current RSI to RSI N bars ago. All noise reduction filters can be enabled/disabled independently, allowing you to customize the balance between signal frequency and accuracy. The default settings provide a good balance, but you can adjust them based on your trading style and market conditions. Alert System The script includes separate alert conditions for each signal type: buy/sell (adaptive RSI crossovers), divergence (regular, strong, hidden), crossovers (RSI50 centerline, RSI period crossovers), synergy signals, and trend breaks. Each alert type has its own alertcondition() declaration with a unique title and message. An optional cooldown system prevents alert spam by requiring a minimum number of bars between alerts of the same type. The cooldown check: canAlert = na(lastAlertBar) OR (bar_index - lastAlertBar >= cooldownBars). If the last alert bar is na (first alert), it always allows the alert. Each alert type maintains its own lastAlertBar variable, so cooldowns are independent per signal type. The default cooldown is 10 bars, which is recommended for noise reduction. Higher Timeframe RSI The script can display RSI from a higher timeframe using request.security(). This allows you to see the RSI context from a larger timeframe (e.g., daily RSI on an hourly chart). The higher timeframe RSI uses RSI(14) calculation from the selected timeframe. This provides context for the current timeframe's RSI position relative to the larger trend. RSI Pivot Trendlines The script can draw trendlines connecting pivot highs and lows on RSI(6). This feature helps visualize RSI trends and identify potential trend breaks. Pivot Detection: Pivots are detected using a configurable period. The script can require pivots to have minimum strength (RSI points difference from surrounding bars) to filter out weak pivots. Lower minPivotStrength values detect more pivots (more trendlines), while higher values detect only stronger pivots (fewer but more significant trendlines). Pivot confirmation is optional: when enabled, the script waits N bars to confirm the pivot remains the extreme, reducing repainting. Pivot confirmation functions (f_confirmPivotLow and f_confirmPivotHigh) are always called on every bar for consistency, as recommended by TradingView. When pivot bars are not available (na), safe default values are used, and the results are then used conditionally based on confirmation settings. This ensures consistent calculations and prevents calculation inconsistencies. Trendline Drawing: Uptrend lines connect confirmed pivot lows (green), and downtrend lines connect confirmed pivot highs (red). By default, only the most recent trendline is shown (old trendlines are deleted when new pivots are confirmed). This keeps the chart clean and uncluttered. If "Keep Historical Trendlines" is enabled, the script preserves up to N historical trendlines (configurable via "Max Trendlines to Keep", default 5). When historical trendlines are enabled, old trendlines are saved to arrays instead of being deleted, allowing you to see multiple trendlines simultaneously for better trend analysis. The arrays are automatically limited to prevent memory accumulation. Trend Break Detection: Signals are generated when RSI breaks above or below trendlines. Uptrend breaks (RSI crosses below uptrend line) generate buy signals. Downtrend breaks (RSI crosses above downtrend line) generate sell signals. Optional trend break confirmation requires the break to persist for N bars and optionally include volume confirmation. Trendline angle filtering can exclude flat/weak trendlines from generating signals (minTrendlineAngle > 0 filters out weak/flat trendlines). How Components Work Together The combination of multiple RSI periods provides confirmation across different timeframes, reducing false signals. RSI(6) catches early moves, RSI(14) provides balanced signals, and RSI(24) confirms longer-term trends. When all three align (synergy), it indicates strong consensus across timeframes. Volume confirmation ensures signals occur with sufficient market participation, filtering out low-volume false breakouts. Volume climax detection identifies potential reversal points, while volume dry-up avoidance prevents signals during unreliable low-volume periods. Trend filters align signals with the overall market direction. The EMA filter ensures you're trading with the trend, and the EMA slope filter adds an additional layer by requiring the trend to be strengthening (rising EMA for buys, falling EMA for sells). ADX filter ensures signals only fire during strong trends, avoiding choppy/consolidation periods. RSI(50) filter ensures momentum alignment with the trade direction. Momentum confirmation requires RSI to be accelerating in the signal direction, ensuring signals only fire when momentum is aligned. Multi-timeframe confirmation ensures signals align with higher timeframe trends, reducing counter-trend trades. Divergence detection identifies potential reversals before they occur, providing early warning signals. Pivot-based divergence provides more accurate detection by using actual pivot points. Hidden divergence identifies continuation patterns, useful for trend-following strategies. The noise reduction system combines multiple filters (signal strength, extreme zone, consecutive bars, zone persistence, RSI slope) to significantly reduce false signals. These filters work together to ensure only high-quality signals are generated. The synergy system requires alignment across all RSI periods for highest-quality signals, significantly reducing false positives. Regression forecasting provides forward-looking context, helping anticipate potential RSI direction changes. Pivot trendlines provide visual trend analysis and can generate signals when RSI breaks trendlines, indicating potential reversals or continuations. Reset conditions prevent signal spam by requiring a minimum number of bars between signals. Separate reset conditions for buy and sell signals ensure proper signal management. Usage Instructions Configuration Presets (Recommended): The script includes optimized preset configurations for instant setup. Simply select your trading style from the "Configuration Preset" dropdown: - Scalping Preset: RSI(4, 7, 9) with minimal smoothing. Noise reduction disabled, momentum confirmation disabled for fastest signals. - Day Trading Preset: RSI(6, 9, 14) with light smoothing. Momentum confirmation enabled for better signal quality. - Swing Trading Preset: RSI(14, 14, 21) with moderate smoothing. Balanced configuration for medium-term trades. - Position Trading Preset: RSI(24, 21, 28) with heavier smoothing. Optimized for longer-term positions with all filters active. - Custom Mode: Full manual control over all settings. Default behavior matches previous script versions. Presets automatically configure RSI periods, smoothing lengths, and filter settings. You can still manually adjust any setting after selecting a preset if needed. Getting Started: The easiest way to get started is to select a configuration preset matching your trading style (Scalping, Day Trading, Swing Trading, or Position Trading) from the "Configuration Preset" dropdown. This instantly configures all settings for optimal performance. Alternatively, use "Custom" mode for full manual control. The default configuration (Custom mode) shows RSI(6), RSI(14), and RSI(24) with their default smoothing. Overbought/oversold fill zones are enabled by default. Customizing RSI Periods: Adjust the RSI lengths (6, 14, 24) based on your trading timeframe. Shorter periods (6) for scalping, standard (14) for day trading, longer (24) for swing trading. You can disable any RSI period you don't need. Smoothing Selection: Choose smoothing method based on your needs. EMA provides balanced smoothing, RMA (Wilder's) is traditional, Zero-Lag reduces lag but may increase noise. Adjust smoothing lengths individually or use global smoothing for consistency. Note: Smoothing lengths are automatically validated to ensure they are always less than the corresponding RSI period length. If you set smoothing >= RSI length, it will be auto-adjusted to prevent invalid configurations. Dynamic OB/OS: The dynamic thresholds automatically adapt to volatility. Adjust the volatility multiplier and base percentage to fine-tune sensitivity. Higher values create wider thresholds in volatile markets. Volume Confirmation: Set volume threshold to 1.2 (default) for standard confirmation, higher for stricter filtering, or 0.1 to disable volume filtering entirely. Multi-RSI Synergy: Use "ALL" mode for highest-quality signals (all 3 RSIs must align), or "2-of-3" mode for more frequent signals. Adjust the reset period to control signal frequency. Filters: Enable filters gradually to find your preferred balance. Start with volume confirmation, then add trend filter, then ADX for strongest confirmation. RSI(50) filter is useful for momentum-based strategies and is recommended for noise reduction. Momentum confirmation and multi-timeframe confirmation add additional layers of accuracy but may reduce signal frequency. Noise Reduction: The noise reduction system is enabled by default with balanced settings. Adjust minSignalStrength (default 3.0) to control how far RSI must be from centerline. Increase requireConsecutiveBars (default 1) to require signals to persist longer. Enable requireZonePersistence and requireRsiSlope for stricter filtering (higher quality but fewer signals). Start with defaults and adjust based on your needs. Divergence: Enable divergence detection and adjust lookback periods. Strong divergence (with engulfing confirmation) provides higher-quality signals. Hidden divergence is useful for trend-following strategies. Enable pivot-based divergence for more accurate detection using actual pivot points instead of simple lowest/highest comparisons. Pivot-based divergence uses tolerance-based matching (1% for price, 1.0 RSI point for RSI) for better accuracy. Forecasting: Enable regression forecasting to see potential RSI direction. Linear regression is simplest, polynomial captures curves, exponential smoothing adapts to trends. Adjust horizon based on your trading timeframe. Confidence bands show forecast uncertainty - wider bands indicate less reliable forecasts. Pivot Trendlines: Enable pivot trendlines to visualize RSI trends and identify trend breaks. Adjust pivot detection period (default 5) - higher values detect fewer but stronger pivots. Enable pivot confirmation (default ON) to reduce repainting. Set minPivotStrength (default 1.0) to filter weak pivots - lower values detect more pivots (more trendlines), higher values detect only stronger pivots (fewer trendlines). Enable "Keep Historical Trendlines" to preserve multiple trendlines instead of just the most recent one. Set "Max Trendlines to Keep" (default 5) to control how many historical trendlines are preserved. Enable trend break confirmation for more reliable break signals. Adjust minTrendlineAngle (default 0.0) to filter flat trendlines - set to 0.1-0.5 to exclude weak trendlines. Alerts: Set up alerts for your preferred signal types. Enable cooldown to prevent alert spam. Each signal type has its own alert condition, so you can be selective about which signals trigger alerts. Visual Elements and Signal Markers The script uses various visual markers to indicate signals and conditions: - "sBottom" label (green): Strong bottom signal - RSI at extreme low with strong buy conditions - "sTop" label (red): Strong top signal - RSI at extreme high with strong sell conditions - "SyBuy" label (lime): Multi-RSI synergy buy signal - all RSIs aligned oversold - "SySell" label (red): Multi-RSI synergy sell signal - all RSIs aligned overbought - 🐂 emoji (green): Strong bullish divergence detected - 🐻 emoji (red): Strong bearish divergence detected - 🔆 emoji: Weak divergence signals (if enabled) - "H-Bull" label: Hidden bullish divergence - "H-Bear" label: Hidden bearish divergence - ⚡ marker (top of pane): Volume climax detected (extreme volume) - positioned at top for visibility - 💧 marker (top of pane): Volume dry-up detected (very low volume) - positioned at top for visibility - ↑ triangle (lime): Uptrend break signal - RSI breaks below uptrend line - ↓ triangle (red): Downtrend break signal - RSI breaks above downtrend line - Triangle up (lime): RSI(50) bullish crossover - Triangle down (red): RSI(50) bearish crossover - Circle markers: RSI period crossovers All markers are positioned at the RSI value where the signal occurs, using location.absolute for precise placement. Signal Priority and Interpretation Signals are generated independently and can occur simultaneously. Higher-priority signals generally indicate stronger setups: 1. Multi-RSI Synergy signals (SyBuy/SySell) - Highest priority: Requires alignment across all RSI periods plus volume and filter confirmation. These are the most reliable signals. 2. Strong Top/Bottom signals (sTop/sBottom) - High priority: Indicates extreme RSI levels with strong bounce conditions. Requires volume confirmation and all filters. 3. Divergence signals - Medium-High priority: Strong divergence (with engulfing) is more reliable than regular divergence. Hidden divergence indicates continuation rather than reversal. 4. Adaptive RSI crossovers - Medium priority: Buy when adaptive RSI crosses below dynamic oversold, sell when it crosses above dynamic overbought. These use volatility-adjusted RSI for more accurate signals. 5. RSI(50) centerline crossovers - Medium priority: Momentum shift signals. Less reliable alone but useful when combined with other confirmations. 6. RSI period crossovers - Lower priority: Early momentum shift indicators. Can provide early warning but may produce false signals in choppy markets. Best practice: Wait for multiple confirmations. For example, a synergy signal combined with divergence and volume climax provides the strongest setup. Chart Requirements For proper script functionality and compliance with TradingView requirements, ensure your chart displays: - Symbol name: The trading pair or instrument name should be visible - Timeframe: The chart timeframe should be clearly displayed - Script name: "Ultimate RSI " should be visible in the indicator title These elements help traders understand what they're viewing and ensure proper script identification. The script automatically includes this information in the indicator title and chart labels. Performance Considerations The script is optimized for performance: - ATR and Volume SMA are cached using var variables, updating only on confirmed and real-time bars to reduce redundant calculations - Forecast line arrays are dynamically managed: lines are reused when possible, and unused lines are deleted to prevent memory accumulation - Calculations use efficient Pine Script functions (ta.rsi, ta.ema, etc.) which are optimized by TradingView - Array operations are minimized where possible, with direct calculations preferred - Polynomial regression automatically caps the forecast horizon at 20 bars (POLYNOMIAL_MAX_HORIZON constant) to prevent performance degradation, as polynomial regression has O(n³) complexity. This safeguard ensures optimal performance even with large horizon settings - Pivot detection includes edge case handling to ensure reliable calculations even on early bars with limited historical data. Regression forecasting functions include comprehensive safety checks: horizon validation (must not exceed array size), empty array handling, edge case handling for horizon=1 scenarios, and division-by-zero protection in all mathematical operations The script should perform well on all timeframes. On very long historical data, forecast lines may accumulate if the horizon is large; consider reducing the forecast horizon if you experience performance issues. The polynomial regression performance safeguard automatically prevents performance issues for that specific regression type. Known Limitations and Considerations - Forecast lines are forward-looking projections and should not be used as definitive predictions. They provide context but are not guaranteed to be accurate. - Dynamic OB/OS thresholds can exceed 100 or go below 0 in extreme volatility scenarios, but are clamped to 0-100 range. This means in very volatile markets, the dynamic thresholds may not widen as much as the raw calculation suggests. - Volume confirmation requires sufficient historical volume data. On new instruments or very short timeframes, volume calculations may be less reliable. - Higher timeframe RSI uses request.security() which may have slight delays on some data feeds. - Regression forecasting requires at least N bars of history (where N = forecast horizon) before it can generate forecasts. Early bars will not show forecast lines. - StochRSI calculation requires the selected RSI source to have sufficient history. Very short RSI periods on new charts may produce less reliable StochRSI values initially. Practical Use Cases The indicator can be configured for different trading styles and timeframes: Swing Trading: Select the "Swing Trading" preset for instant optimal configuration. This preset uses RSI periods (14, 14, 21) with moderate smoothing. Alternatively, manually configure: Use RSI(24) with Multi-RSI Synergy in "ALL" mode, combined with trend filter (EMA 200) and ADX filter. This configuration provides high-probability setups with strong confirmation across multiple RSI periods. Day Trading: Select the "Day Trading" preset for instant optimal configuration. This preset uses RSI periods (6, 9, 14) with light smoothing and momentum confirmation enabled. Alternatively, manually configure: Use RSI(6) with Zero-Lag smoothing for fast signal detection. Enable volume confirmation with threshold 1.2-1.5 for reliable entries. Combine with RSI(50) filter to ensure momentum alignment. Strong top/bottom signals work well for day trading reversals. Trend Following: Enable trend filter (EMA) and EMA slope filter for strong trend confirmation. Use RSI(14) or RSI(24) with ADX filter to avoid choppy markets. Hidden divergence signals are useful for trend continuation entries. Reversal Trading: Focus on divergence detection (regular and strong) combined with strong top/bottom signals. Enable volume climax detection to identify capitulation moments. Use RSI(6) for early reversal signals, confirmed by RSI(14) and RSI(24). Forecasting and Planning: Enable regression forecasting with polynomial or exponential smoothing methods. Use forecast horizon of 10-20 bars for swing trading, 5-10 bars for day trading. Confidence bands help assess forecast reliability. Multi-Timeframe Analysis: Enable higher timeframe RSI to see context from larger timeframes. For example, use daily RSI on hourly charts to understand the larger trend context. This helps avoid counter-trend trades. Scalping: Select the "Scalping" preset for instant optimal configuration. This preset uses RSI periods (4, 7, 9) with minimal smoothing, disables noise reduction, and disables momentum confirmation for faster signals. Alternatively, manually configure: Use RSI(6) with minimal smoothing (or Zero-Lag) for ultra-fast signals. Disable most filters except volume confirmation. Use RSI period crossovers (RSI(6) × RSI(14)) for early momentum shifts. Set volume threshold to 1.0-1.2 for less restrictive filtering. Position Trading: Select the "Position Trading" preset for instant optimal configuration. This preset uses extended RSI periods (24, 21, 28) with heavier smoothing, optimized for longer-term trades. Alternatively, manually configure: Use RSI(24) with all filters enabled (Trend, ADX, RSI(50), Volume Dry-Up avoidance). Multi-RSI Synergy in "ALL" mode provides highest-quality signals. Practical Tips and Best Practices Getting Started: The fastest way to get started is to select a configuration preset that matches your trading style. Simply choose "Scalping", "Day Trading", "Swing Trading", or "Position Trading" from the "Configuration Preset" dropdown to instantly configure all settings optimally. For advanced users, use "Custom" mode for full manual control. The default configuration (Custom mode) is balanced and works well across different markets. After observing behavior, customize settings to match your trading style. Reducing Repainting: All signals are based on confirmed bars, minimizing repainting. The script uses confirmed bar data for all calculations to ensure backtesting accuracy. Signal Quality: Multi-RSI Synergy signals in "ALL" mode provide the highest-quality signals because they require alignment across all three RSI periods. These signals have lower frequency but higher reliability. For more frequent signals, use "2-of-3" mode. The noise reduction system further improves signal quality by requiring multiple confirmations (signal strength, extreme zone, consecutive bars, optional zone persistence and RSI slope). Adjust noise reduction settings to balance signal frequency vs. accuracy. Filter Combinations: Start with volume confirmation, then add trend filter for trend alignment, then ADX filter for trend strength. Combining all three filters significantly reduces false signals but also reduces signal frequency. Find your balance based on your risk tolerance. Volume Filtering: Set volume threshold to 0.1 or lower to effectively disable volume filtering if you trade instruments with unreliable volume data or want to test without volume confirmation. Standard confirmation uses 1.2-1.5 threshold. RSI Period Selection: RSI(6) is most sensitive and best for scalping or early signal detection. RSI(14) provides balanced signals suitable for day trading. RSI(24) is smoother and better for swing trading and trend confirmation. You can disable any RSI period you don't need to reduce visual clutter. Smoothing Methods: EMA provides balanced smoothing with moderate lag. RMA (Wilder's smoothing) is traditional and works well for RSI. Zero-Lag reduces lag but may increase noise. WMA gives more weight to recent values. Choose based on your preference for responsiveness vs. smoothness. Forecasting: Linear regression is simplest and works well for trending markets. Polynomial regression captures curves and works better in ranging markets. Exponential smoothing adapts to trends. Moving average method is most conservative. Use confidence bands to assess forecast reliability. Divergence: Strong divergence (with engulfing confirmation) is more reliable than regular divergence. Hidden divergence indicates continuation rather than reversal, useful for trend-following strategies. Pivot-based divergence provides more accurate detection by using actual pivot points instead of simple lowest/highest comparisons. Adjust lookback periods based on your timeframe: shorter for day trading, longer for swing trading. Pivot divergence period (default 5) controls the sensitivity of pivot detection. Dynamic Thresholds: Dynamic OB/OS thresholds automatically adapt to volatility. In volatile markets, thresholds widen; in calm markets, they narrow. Adjust the volatility multiplier and base percentage to fine-tune sensitivity. Higher values create wider thresholds in volatile markets. Alert Management: Enable alert cooldown (default 10 bars, recommended) to prevent alert spam. Each alert type has its own cooldown, so you can set different cooldowns for different signal types. For example, use shorter cooldown for synergy signals (high quality) and longer cooldown for crossovers (more frequent). The cooldown system works independently for each signal type, preventing spam while allowing different signal types to fire when appropriate. Technical Specifications - Pine Script Version: v6 - Indicator Type: Non-overlay (displays in separate panel below price chart) - Repainting Behavior: Minimal - all signals are based on confirmed bars, ensuring accurate backtesting results - Performance: Optimized with caching for ATR and volume calculations. Forecast arrays are dynamically managed to prevent memory accumulation. - Compatibility: Works on all timeframes (1 minute to 1 month) and all instruments (stocks, forex, crypto, futures, etc.) - Edge Case Handling: All calculations include safety checks for division by zero, NA values, and boundary conditions. Reset conditions and alert cooldowns handle edge cases where conditions never occurred or values are NA. - Reset Logic: Separate reset conditions for buy signals (based on bottom conditions) and sell signals (based on top conditions) ensure logical correctness. - Input Parameters: 60+ customizable parameters organized into logical groups for easy configuration. Configuration presets available for instant setup (Scalping, Day Trading, Swing Trading, Position Trading, Custom). - Noise Reduction: Comprehensive noise reduction system with multiple filters (signal strength, extreme zone, consecutive bars, zone persistence, RSI slope) to reduce false signals. - Pivot-Based Divergence: Enhanced divergence detection using actual pivot points for improved accuracy. - Momentum Confirmation: RSI momentum filter ensures signals only fire when RSI is accelerating in the signal direction. - Multi-Timeframe Confirmation: Optional higher timeframe RSI alignment for trend confirmation. - Enhanced Pivot Trendlines: Trendline drawing with strength requirements, confirmation, and trend break detection. Technical Notes - All RSI values are clamped to 0-100 range to ensure valid oscillator values - ATR and Volume SMA are cached for performance, updating on confirmed and real-time bars - Reset conditions handle edge cases: if a condition never occurred, reset returns true (allows first signal) - Alert cooldown handles na values: if no previous alert, cooldown allows the alert - Forecast arrays are dynamically sized based on horizon, with unused lines cleaned up - Fill logic uses a minimum gap (0.1) to ensure reliable polygon rendering in TradingView - All calculations include safety checks for division by zero and boundary conditions. Regression functions validate that horizon doesn't exceed array size, and all array access operations include bounds checking to prevent out-of-bounds errors - The script uses separate reset conditions for buy signals (based on bottom conditions) and sell signals (based on top conditions) for logical correctness - Background coloring uses a fallback system: dynamic color takes priority, then RSI(6) heatmap, then monotone if both are disabled - Noise reduction filters are applied after accuracy filters, providing multiple layers of signal quality control - Pivot trendlines use strength requirements to filter weak pivots, reducing noise in trendline drawing. Historical trendlines are stored in arrays and automatically limited to prevent memory accumulation when "Keep Historical Trendlines" is enabled - Volume climax and dry-up markers are positioned at the top of the pane for better visibility - All calculations are optimized with conditional execution - features only calculate when enabled (performance optimization) - Input Validation: Automatic cross-input validation ensures smoothing lengths are always less than RSI period lengths, preventing configuration errors - Configuration Presets: Four optimized preset configurations (Scalping, Day Trading, Swing Trading, Position Trading) for instant setup, plus Custom mode for full manual control - Constants Management: Magic numbers extracted to documented constants for improved maintainability and easier tuning (pivot tolerance, divergence thresholds, fill gap, etc.) - TradingView Function Consistency: All TradingView functions (ta.crossover, ta.crossunder, ta.atr, ta.lowest, ta.highest, ta.lowestbars, ta.highestbars, etc.) and custom functions that depend on historical results (f_consecutiveBarConfirmation, f_rsiSlopeConfirmation, f_rsiZonePersistence, f_applyAllFilters, f_rsiMomentum, f_forecast, f_confirmPivotLow, f_confirmPivotHigh) are called on every bar for consistency, as recommended by TradingView. Results are then used conditionally when needed. This ensures consistent calculations and prevents calculation inconsistencies.
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Hellenic EMA Matrix - PremiumHellenic EMA Matrix - Alpha Omega Premium Complete User Guide Table of Contents Introduction Indicator Philosophy Mathematical Constants EMA Types Settings Trading Signals Visualization Usage Strategies FAQ Introduction Hellenic EMA Matrix is a premium indicator based on mathematical constants of nature: Phi (Phi - Golden Ratio), Pi (Pi), e (Euler's number). The indicator uses these universal constants to create dynamic EMAs that adapt to the natural rhythms of the market. Key Features: 6 EMA types based on mathematical constants Premium visualization with Neon Glow and Gradient Clouds Automatic Fast/Mid/Slow EMA sorting STRONG signals for powerful trends Pulsing Ribbon Bar for instant trend assessment Works on all timeframes (M1 - MN) Indicator Philosophy Why Mathematical Constants? Traditional EMAs use arbitrary periods (9, 21, 50, 200). Hellenic Matrix goes further, using universal mathematical constants found in nature: Phi (1.618) - Golden Ratio: galaxy spirals, seashells, human body proportions Pi (3.14159) - Pi: circles, waves, cycles e (2.71828) - Natural logarithm base: exponential growth, radioactive decay Markets are also a natural system composed of millions of participants. Using mathematical constants allows tuning into the natural rhythms of market cycles. Mathematical Constants Phi (Phi) - Golden Ratio Phi = 1.618033988749895 Properties: Phi² = Phi + 1 = 2.618 Phi³ = 4.236 Phi⁴ = 6.854 Application: Ideal for trending movements and Fibonacci corrections Pi (Pi) - Pi Number Pi = 3.141592653589793 Properties: 2Pi = 6.283 (full circle) 3Pi = 9.425 4Pi = 12.566 Application: Excellent for cyclical markets and wave structures e (Euler) - Euler's Number e = 2.718281828459045 Properties: e² = 7.389 e³ = 20.085 e⁴ = 54.598 Application: Suitable for exponential movements and volatile markets EMA Types 1. Phi (Phi) - Golden Ratio EMA Description: EMA based on the golden ratio Period Formula: Period = Phi^n × Base Multiplier Parameters: Phi Power Level (1-8): Power of Phi Phi¹ = 1.618 → ~16 period (with Base=10) Phi² = 2.618 → ~26 period Phi³ = 4.236 → ~42 period (recommended) Phi⁴ = 6.854 → ~69 period Recommendations: Phi² or Phi³ for day trading Phi⁴ or Phi⁵ for swing trading Works excellently as Fast EMA 2. Pi (Pi) - Circular EMA Description: EMA based on Pi for cyclical movements Period Formula: Period = Pi × Multiple × Base Multiplier Parameters: Pi Multiple (1-10): Pi multiplier 1Pi = 3.14 → ~31 period (with Base=10) 2Pi = 6.28 → ~63 period (recommended) 3Pi = 9.42 → ~94 period Recommendations: 2Pi ideal as Mid or Slow EMA Excellently identifies cycles and waves Use on volatile markets (crypto, forex) 3. e (Euler) - Natural EMA Description: EMA based on natural logarithm Period Formula: Period = e^n × Base Multiplier Parameters: e Power Level (1-6): Power of e e¹ = 2.718 → ~27 period (with Base=10) e² = 7.389 → ~74 period (recommended) e³ = 20.085 → ~201 period Recommendations: e² works excellently as Slow EMA Ideal for stocks and indices Filters noise well on lower timeframes 4. Delta (Delta) - Adaptive EMA Description: Adaptive EMA that changes period based on volatility Period Formula: Period = Base Period × (1 + (Volatility - 1) × Factor) Parameters: Delta Base Period (5-200): Base period (default 20) Delta Volatility Sensitivity (0.5-5.0): Volatility sensitivity (default 2.0) How it works: During low volatility → period decreases → EMA reacts faster During high volatility → period increases → EMA smooths noise Recommendations: Works excellently on news and sharp movements Use as Fast EMA for quick adaptation Sensitivity 2.0-3.0 for crypto, 1.0-2.0 for stocks 5. Sigma (Sigma) - Composite EMA Description: Composite EMA combining multiple active EMAs Composition Methods: Weighted Average (default): Sigma = (Phi + Pi + e + Delta) / 4 Simple average of all active EMAs Geometric Mean: Sigma = fourth_root(Phi × Pi × e × Delta) Geometric mean (more conservative) Harmonic Mean: Sigma = 4 / (1/Phi + 1/Pi + 1/e + 1/Delta) Harmonic mean (more weight to smaller values) Recommendations: Enable for additional confirmation Use as Mid EMA Weighted Average - most universal method 6. Lambda (Lambda) - Wave EMA Description: Wave EMA with sinusoidal period modulation Period Formula: Period = Base Period × (1 + Amplitude × sin(2Pi × bar / Frequency)) Parameters: Lambda Base Period (10-200): Base period Lambda Wave Amplitude (0.1-2.0): Wave amplitude Lambda Wave Frequency (10-200): Wave frequency in bars How it works: Period pulsates sinusoidally Creates wave effect following market cycles Recommendations: Experimental EMA for advanced users Works well on cyclical markets Frequency = 50 for day trading, 100+ for swing Settings Matrix Core Settings Base Multiplier (1-100) Multiplies all EMA periods Base = 1: Very fast EMAs (Phi³ = 4, 2Pi = 6, e² = 7) Base = 10: Standard (Phi³ = 42, 2Pi = 63, e² = 74) Base = 20: Slow EMAs (Phi³ = 85, 2Pi = 126, e² = 148) Recommendations by timeframe: M1-M5: Base = 5-10 M15-H1: Base = 10-15 (recommended) H4-D1: Base = 15-25 W1-MN: Base = 25-50 Matrix Source Data source selection for EMA calculation: close - closing price (standard) open - opening price high - high low - low hl2 - (high + low) / 2 hlc3 - (high + low + close) / 3 ohlc4 - (open + high + low + close) / 4 When to change: hlc3 or ohlc4 for smoother signals high for aggressive longs low for aggressive shorts Manual EMA Selection Critically important setting! Determines which EMAs are used for signal generation. Use Manual Fast/Slow/Mid Selection Enabled (default): You select EMAs manually Disabled: Automatic selection by periods Fast EMA Fast EMA - reacts first to price changes Recommendations: Phi Golden (recommended) - universal choice Delta Adaptive - for volatile markets Must be fastest (smallest period) Slow EMA Slow EMA - determines main trend Recommendations: Pi Circular (recommended) - excellent trend filter e Natural - for smoother trend Must be slowest (largest period) Mid EMA Mid EMA - additional signal filter Recommendations: e Natural (recommended) - excellent middle level Pi Circular - alternative None - for more frequent signals (only 2 EMAs) IMPORTANT: The indicator automatically sorts selected EMAs by their actual periods: Fast = EMA with smallest period Mid = EMA with middle period Slow = EMA with largest period Therefore, you can select any combination - the indicator will arrange them correctly! Premium Visualization Neon Glow Enable Neon Glow for EMAs - adds glowing effect around EMA lines Glow Strength: Light - subtle glow Medium (recommended) - optimal balance Strong - bright glow (may be too bright) Effect: 2 glow layers around each EMA for 3D effect Gradient Clouds Enable Gradient Clouds - fills space between EMAs with gradient Parameters: Cloud Transparency (85-98): Cloud transparency 95-97 (recommended) Higher = more transparent Dynamic Cloud Intensity - automatically changes transparency based on EMA distance Cloud Colors: Phi-Pi Cloud: Blue - when Pi above Phi (bullish) Gold - when Phi above Pi (bearish) Pi-e Cloud: Green - when e above Pi (bullish) Blue - when Pi above e (bearish) 2 layers for volumetric effect Pulsing Ribbon Bar Enable Pulsing Indicator Bar - pulsing strip at bottom/top of chart Parameters: Ribbon Position: Top / Bottom (recommended) Pulse Speed: Slow / Medium (recommended) / Fast Symbols and colors: Green filled square - STRONG BULLISH Pink filled square - STRONG BEARISH Blue hollow square - Bullish (regular) Red hollow square - Bearish (regular) Purple rectangle - Neutral Effect: Pulsation with sinusoid for living market feel Signal Bar Highlights Enable Signal Bar Highlights - highlights bars with signals Parameters: Highlight Transparency (88-96): Highlight transparency Highlight Style: Light Fill (recommended) - bar background fill Thin Line - bar outline only Highlights: Golden Cross - green Death Cross - pink STRONG BUY - green STRONG SELL - pink Show Greek Labels Shows Greek alphabet letters on last bar: Phi - Phi EMA (gold) Pi - Pi EMA (blue) e - Euler EMA (green) Delta - Delta EMA (purple) Sigma - Sigma EMA (pink) When to use: For education or presentations Show Old Background Old background style (not recommended): Green background - STRONG BULLISH Pink background - STRONG BEARISH Blue background - Bullish Red background - Bearish Not recommended - use new Gradient Clouds and Pulsing Bar Info Table Show Info Table - table with indicator information Parameters: Position: Top Left / Top Right (recommended) / Bottom Left / Bottom Right Size: Tiny / Small (recommended) / Normal / Large Table contents: EMA list - periods and current values of all active EMAs Effects - active visual effects TREND - current trend state: STRONG UP - strong bullish STRONG DOWN - strong bearish Bullish - regular bullish Bearish - regular bearish Neutral - neutral Momentum % - percentage deviation of price from Fast EMA Setup - current Fast/Slow/Mid configuration Trading Signals Show Golden/Death Cross Golden Cross - Fast EMA crosses Slow EMA from below (bullish signal) Death Cross - Fast EMA crosses Slow EMA from above (bearish signal) Symbols: Yellow dot "GC" below - Golden Cross Dark red dot "DC" above - Death Cross Show STRONG Signals STRONG BUY and STRONG SELL - the most powerful indicator signals Conditions for STRONG BULLISH: EMA Alignment: Fast > Mid > Slow (all EMAs aligned) Trend: Fast > Slow (clear uptrend) Distance: EMAs separated by minimum 0.15% Price Position: Price above Fast EMA Fast Slope: Fast EMA rising Slow Slope: Slow EMA rising Mid Trending: Mid EMA also rising (if enabled) Conditions for STRONG BEARISH: Same but in reverse Visual display: Green label "STRONG BUY" below bar Pink label "STRONG SELL" above bar Difference from Golden/Death Cross: Golden/Death Cross = crossing moment (1 bar) STRONG signal = sustained trend (lasts several bars) IMPORTANT: After fixes, STRONG signals now: Work on all timeframes (M1 to MN) Don't break on small retracements Work with any Fast/Mid/Slow combination Automatically adapt thanks to EMA sorting Show Stop Loss/Take Profit Automatic SL/TP level calculation on STRONG signal Parameters: Stop Loss (ATR) (0.5-5.0): ATR multiplier for stop loss 1.5 (recommended) - standard 1.0 - tight stop 2.0-3.0 - wide stop Take Profit R:R (1.0-5.0): Risk/reward ratio 2.0 (recommended) - standard (risk 1.5 ATR, profit 3.0 ATR) 1.5 - conservative 3.0-5.0 - aggressive Formulas: LONG: Stop Loss = Entry - (ATR × Stop Loss ATR) Take Profit = Entry + (ATR × Stop Loss ATR × Take Profit R:R) SHORT: Stop Loss = Entry + (ATR × Stop Loss ATR) Take Profit = Entry - (ATR × Stop Loss ATR × Take Profit R:R) Visualization: Red X - Stop Loss Green X - Take Profit Levels remain active while STRONG signal persists Trading Signals Signal Types 1. Golden Cross Description: Fast EMA crosses Slow EMA from below Signal: Beginning of bullish trend How to trade: ENTRY: On bar close with Golden Cross STOP: Below local low or below Slow EMA TARGET: Next resistance level or 2:1 R:R Strengths: Simple and clear Works well on trending markets Clear entry point Weaknesses: Lags (signal after movement starts) Many false signals in ranging markets May be late on fast moves Optimal timeframes: H1, H4, D1 2. Death Cross Description: Fast EMA crosses Slow EMA from above Signal: Beginning of bearish trend How to trade: ENTRY: On bar close with Death Cross STOP: Above local high or above Slow EMA TARGET: Next support level or 2:1 R:R Application: Mirror of Golden Cross 3. STRONG BUY Description: All EMAs aligned + trend + all EMAs rising Signal: Powerful bullish trend How to trade: ENTRY: On bar close with STRONG BUY or on pullback to Fast EMA STOP: Below Fast EMA or automatic SL (if enabled) TARGET: Automatic TP (if enabled) or by levels TRAILING: Follow Fast EMA Entry strategies: Aggressive: Enter immediately on signal Conservative: Wait for pullback to Fast EMA, then enter on bounce Pyramiding: Add positions on pullbacks to Mid EMA Position management: Hold while STRONG signal active Exit on STRONG SELL or Death Cross appearance Move stop behind Fast EMA Strengths: Most reliable indicator signal Doesn't break on pullbacks Catches large moves Works on all timeframes Weaknesses: Appears less frequently than other signals Requires confirmation (multiple conditions) Optimal timeframes: All (M5 - D1) 4. STRONG SELL Description: All EMAs aligned down + downtrend + all EMAs falling Signal: Powerful bearish trend How to trade: Mirror of STRONG BUY Visual Signals Pulsing Ribbon Bar Quick market assessment at a glance: Symbol Color State Filled square Green STRONG BULLISH Filled square Pink STRONG BEARISH Hollow square Blue Bullish Hollow square Red Bearish Rectangle Purple Neutral Pulsation: Sinusoidal, creates living effect Signal Bar Highlights Bars with signals are highlighted: Green highlight: STRONG BUY or Golden Cross Pink highlight: STRONG SELL or Death Cross Gradient Clouds Colored space between EMAs shows trend strength: Wide clouds - strong trend Narrow clouds - weak trend or consolidation Color change - trend change Info Table Quick reference in corner: TREND: Current state (STRONG UP, Bullish, Neutral, Bearish, STRONG DOWN) Momentum %: Movement strength Effects: Active visual effects Setup: Fast/Slow/Mid configuration Usage Strategies Strategy 1: "Golden Trailing" Idea: Follow STRONG signals using Fast EMA as trailing stop Settings: Fast: Phi Golden (Phi³) Mid: Pi Circular (2Pi) Slow: e Natural (e²) Base Multiplier: 10 Timeframe: H1, H4 Entry rules: Wait for STRONG BUY Enter on bar close or on pullback to Fast EMA Stop below Fast EMA Management: Hold position while STRONG signal active Move stop behind Fast EMA daily Exit on STRONG SELL or Death Cross Take Profit: Partially close at +2R Trail remainder until exit signal For whom: Swing traders, trend followers Pros: Catches large moves Simple rules Emotionally comfortable Cons: Requires patience Possible extended drawdowns on pullbacks Strategy 2: "Scalping Bounces" Idea: Scalp bounces from Fast EMA during STRONG trend Settings: Fast: Delta Adaptive (Base 15, Sensitivity 2.0) Mid: Phi Golden (Phi²) Slow: Pi Circular (2Pi) Base Multiplier: 5 Timeframe: M5, M15 Entry rules: STRONG signal must be active Wait for price pullback to Fast EMA Enter on bounce (candle closes above/below Fast EMA) Stop behind local extreme (15-20 pips) Take Profit: +1.5R or to Mid EMA Or to next level For whom: Active day traders Pros: Many signals Clear entry point Quick profits Cons: Requires constant monitoring Not all bounces work Requires discipline for frequent trading Strategy 3: "Triple Filter" Idea: Enter only when all 3 EMAs and price perfectly aligned Settings: Fast: Phi Golden (Phi³) Mid: e Natural (e²) Slow: Pi Circular (3Pi) Base Multiplier: 15 Timeframe: H4, D1 Entry rules (LONG): STRONG BUY active Price above all three EMAs Fast > Mid > Slow (all aligned) All EMAs rising (slope up) Gradient Clouds wide and bright Entry: On bar close meeting all conditions Or on next pullback to Fast EMA Stop: Below Mid EMA or -1.5 ATR Take Profit: First target: +3R Second target: next major level Trailing: Mid EMA For whom: Conservative swing traders, investors Pros: Very reliable signals Minimum false entries Large profit potential Cons: Rare signals (2-5 per month) Requires patience Strategy 4: "Adaptive Scalper" Idea: Use only Delta Adaptive EMA for quick volatility reaction Settings: Fast: Delta Adaptive (Base 10, Sensitivity 3.0) Mid: None Slow: Delta Adaptive (Base 30, Sensitivity 2.0) Base Multiplier: 3 Timeframe: M1, M5 Feature: Two different Delta EMAs with different settings Entry rules: Golden Cross between two Delta EMAs Both Delta EMAs must be rising/falling Enter on next bar Stop: 10-15 pips or below Slow Delta EMA Take Profit: +1R to +2R Or Death Cross For whom: Scalpers on cryptocurrencies and forex Pros: Instant volatility adaptation Many signals on volatile markets Quick results Cons: Much noise on calm markets Requires fast execution High commissions may eat profits Strategy 5: "Cyclical Trader" Idea: Use Pi and Lambda for trading cyclical markets Settings: Fast: Pi Circular (1Pi) Mid: Lambda Wave (Base 30, Amplitude 0.5, Frequency 50) Slow: Pi Circular (3Pi) Base Multiplier: 10 Timeframe: H1, H4 Entry rules: STRONG signal active Lambda Wave EMA synchronized with trend Enter on bounce from Lambda Wave For whom: Traders of cyclical assets (some altcoins, commodities) Pros: Catches cyclical movements Lambda Wave provides additional entry points Cons: More complex to configure Not for all markets Lambda Wave may give false signals Strategy 6: "Multi-Timeframe Confirmation" Idea: Use multiple timeframes for confirmation Scheme: Higher TF (D1): Determine trend direction (STRONG signal) Middle TF (H4): Wait for STRONG signal in same direction Lower TF (M15): Look for entry point (Golden Cross or bounce from Fast EMA) Settings for all TFs: Fast: Phi Golden (Phi³) Mid: e Natural (e²) Slow: Pi Circular (2Pi) Base Multiplier: 10 Rules: All 3 TFs must show one trend Entry on lower TF Stop by lower TF Target by higher TF For whom: Serious traders and investors Pros: Maximum reliability Large profit targets Minimum false signals Cons: Rare setups Requires analysis of multiple charts Experience needed Practical Tips DOs Use STRONG signals as primary - they're most reliable Let signals develop - don't exit on first pullback Use trailing stop - follow Fast EMA Combine with levels - S/R, Fibonacci, volumes Test on demo before real Adjust Base Multiplier for your timeframe Enable visual effects - they help see the picture Use Info Table - quick situation assessment Watch Pulsing Bar - instant state indicator Trust auto-sorting of Fast/Mid/Slow DON'Ts Don't trade against STRONG signal - trend is your friend Don't ignore Mid EMA - it adds reliability Don't use too small Base Multiplier on higher TFs Don't enter on Golden Cross in range - check for trend Don't change settings during open position Don't forget risk management - 1-2% per trade Don't trade all signals in row - choose best ones Don't use indicator in isolation - combine with Price Action Don't set too tight stops - let trade breathe Don't over-optimize - simplicity = reliability Optimal Settings by Asset US Stocks (SPY, AAPL, TSLA) Recommendation: Fast: Phi Golden (Phi³) Mid: e Natural (e²) Slow: Pi Circular (2Pi) Base: 10-15 Timeframe: H4, D1 Features: Use on daily for swing STRONG signals very reliable Works well on trending stocks Forex (EUR/USD, GBP/USD) Recommendation: Fast: Delta Adaptive (Base 15, Sens 2.0) Mid: Phi Golden (Phi²) Slow: Pi Circular (2Pi) Base: 8-12 Timeframe: M15, H1, H4 Features: Delta Adaptive works excellently on news Many signals on M15-H1 Consider spreads Cryptocurrencies (BTC, ETH, altcoins) Recommendation: Fast: Delta Adaptive (Base 10, Sens 3.0) Mid: Pi Circular (2Pi) Slow: e Natural (e²) Base: 5-10 Timeframe: M5, M15, H1 Features: High volatility - adaptation needed STRONG signals can last days Be careful with scalping on M1-M5 Commodities (Gold, Oil) Recommendation: Fast: Pi Circular (1Pi) Mid: Phi Golden (Phi³) Slow: Pi Circular (3Pi) Base: 12-18 Timeframe: H4, D1 Features: Pi works excellently on cyclical commodities Gold responds especially well to Phi Oil volatile - use wide stops Indices (S&P500, Nasdaq, DAX) Recommendation: Fast: Phi Golden (Phi³) Mid: e Natural (e²) Slow: Pi Circular (2Pi) Base: 15-20 Timeframe: H4, D1, W1 Features: Very trending instruments STRONG signals last weeks Good for position trading Alerts The indicator supports 6 alert types: 1. Golden Cross Message: "Hellenic Matrix: GOLDEN CROSS - Fast EMA crossed above Slow EMA - Bullish trend starting!" When: Fast EMA crosses Slow EMA from below 2. Death Cross Message: "Hellenic Matrix: DEATH CROSS - Fast EMA crossed below Slow EMA - Bearish trend starting!" When: Fast EMA crosses Slow EMA from above 3. STRONG BULLISH Message: "Hellenic Matrix: STRONG BULLISH SIGNAL - All EMAs aligned for powerful uptrend!" When: All conditions for STRONG BUY met (first bar) 4. STRONG BEARISH Message: "Hellenic Matrix: STRONG BEARISH SIGNAL - All EMAs aligned for powerful downtrend!" When: All conditions for STRONG SELL met (first bar) 5. Bullish Ribbon Message: "Hellenic Matrix: BULLISH RIBBON - EMAs aligned for uptrend" When: EMAs aligned bullish + price above Fast EMA (less strict condition) 6. Bearish Ribbon Message: "Hellenic Matrix: BEARISH RIBBON - EMAs aligned for downtrend" When: EMAs aligned bearish + price below Fast EMA (less strict condition) How to Set Up Alerts: Open indicator on chart Click on three dots next to indicator name Select "Create Alert" In "Condition" field select needed alert: Golden Cross Death Cross STRONG BULLISH STRONG BEARISH Bullish Ribbon Bearish Ribbon Configure notification method: Pop-up in browser Email SMS (in Premium accounts) Push notifications in mobile app Webhook (for automation) Select frequency: Once Per Bar Close (recommended) - once on bar close Once Per Bar - during bar formation Only Once - only first time Click "Create" Tip: Create separate alerts for different timeframes and instruments FAQ 1. Why don't STRONG signals appear? Possible reasons: Incorrect Fast/Mid/Slow order Solution: Indicator automatically sorts EMAs by periods, but ensure selected EMAs have different periods Base Multiplier too large Solution: Reduce Base to 5-10 on lower timeframes Market in range Solution: STRONG signals appear only in trends - this is normal Too strict EMA settings Solution: Try classic combination: Phi³ / Pi×2 / e² with Base=10 Mid EMA too close to Fast or Slow Solution: Select Mid EMA with period between Fast and Slow 2. How often should STRONG signals appear? Normal frequency: M1-M5: 5-15 signals per day (very active markets) M15-H1: 2-8 signals per day H4: 3-10 signals per week D1: 2-5 signals per month W1: 2-6 signals per year If too many signals - market very volatile or Base too small If too few signals - market in range or Base too large 4. What are the best settings for beginners? Universal "out of the box" settings: Matrix Core: Base Multiplier: 10 Source: close Phi Golden: Enabled, Power = 3 Pi Circular: Enabled, Multiple = 2 e Natural: Enabled, Power = 2 Delta Adaptive: Enabled, Base = 20, Sensitivity = 2.0 Manual Selection: Fast: Phi Golden Mid: e Natural Slow: Pi Circular Visualization: Gradient Clouds: ON Neon Glow: ON (Medium) Pulsing Bar: ON (Medium) Signal Highlights: ON (Light Fill) Table: ON (Top Right, Small) Signals: Golden/Death Cross: ON STRONG Signals: ON Stop Loss: OFF (while learning) Timeframe for learning: H1 or H4 5. Can I use only one EMA? No, minimum 2 EMAs (Fast and Slow) for signal generation. Mid EMA is optional: With Mid EMA = more reliable but rarer signals Without Mid EMA = more signals but less strict filtering Recommendation: Start with 3 EMAs (Fast/Mid/Slow), then experiment 6. Does the indicator work on cryptocurrencies? Yes, works excellently! Especially good on: Bitcoin (BTC) Ethereum (ETH) Major altcoins (SOL, BNB, XRP) Recommended settings for crypto: Fast: Delta Adaptive (Base 10-15, Sensitivity 2.5-3.0) Mid: Pi Circular (2Pi) Slow: e Natural (e²) Base: 5-10 Timeframe: M15, H1, H4 Crypto market features: High volatility → use Delta Adaptive 24/7 trading → set alerts Sharp movements → wide stops 7. Can I trade only with this indicator? Technically yes, but NOT recommended. Best approach - combine with: Price Action - support/resistance levels, candle patterns Volume - movement strength confirmation Fibonacci - retracement and extension levels RSI/MACD - divergences and overbought/oversold Fundamental analysis - news, company reports Hellenic Matrix: Excellently determines trend and its strength Provides clear entry/exit points Doesn't consider fundamentals Doesn't see major levels 8. Why do Gradient Clouds change color? Color depends on EMA order: Phi-Pi Cloud: Blue - Pi EMA above Phi EMA (bullish alignment) Gold - Phi EMA above Pi EMA (bearish alignment) Pi-e Cloud: Green - e EMA above Pi EMA (bullish alignment) Blue - Pi EMA above e EMA (bearish alignment) Color change = EMA order change = possible trend change 9. What is Momentum % in the table? Momentum % = percentage deviation of price from Fast EMA Formula: Momentum = ((Close - Fast EMA) / Fast EMA) × 100 Interpretation: +0.5% to +2% - normal bullish momentum +2% to +5% - strong bullish momentum +5% and above - overheating (correction possible) -0.5% to -2% - normal bearish momentum -2% to -5% - strong bearish momentum -5% and below - oversold (bounce possible) Usage: Monitor momentum during STRONG signals Large momentum = don't enter (wait for pullback) Small momentum = good entry point 10. How to configure for scalping? Settings for scalping (M1-M5): Base Multiplier: 3-5 Source: close or hlc3 (smoother) Fast: Delta Adaptive (Base 8-12, Sensitivity 3.0) Mid: None (for more signals) Slow: Phi Golden (Phi²) or Pi Circular (1Pi) Visualization: - Gradient Clouds: ON (helps see strength) - Neon Glow: OFF (doesn't clutter chart) - Pulsing Bar: ON (quick assessment) - Signal Highlights: ON Signals: - Golden/Death Cross: ON - STRONG Signals: ON - Stop Loss: ON (1.0-1.5 ATR, R:R 1.5-2.0) Scalping rules: Trade only STRONG signals Enter on bounce from Fast EMA Tight stops (10-20 pips) Quick take profit (+1R to +2R) Don't hold through news 11. How to configure for long-term investing? Settings for investing (D1-W1): Base Multiplier: 20-30 Source: close Fast: Phi Golden (Phi³ or Phi⁴) Mid: e Natural (e²) Slow: Pi Circular (3Pi or 4Pi) Visualization: - Gradient Clouds: ON - Neon Glow: ON (Medium) - Everything else - to taste Signals: - Golden/Death Cross: ON - STRONG Signals: ON - Stop Loss: OFF (use percentage stop) Investing rules: Enter only on STRONG signals Hold while STRONG active (weeks/months) Stop below Slow EMA or -10% Take profit: by company targets or +50-100% Ignore short-term pullbacks 12. What if indicator slows down chart? Indicator is optimized, but if it slows: Disable unnecessary visual effects: Neon Glow: OFF (saves 8 plots) Gradient Clouds: ON but low quality Lambda Wave EMA: OFF (if not using) Reduce number of active EMAs: Sigma Composite: OFF Lambda Wave: OFF Leave only Phi, Pi, e, Delta Simplify settings: Pulsing Bar: OFF Greek Labels: OFF Info Table: smaller size 13. Can I use on different timeframes simultaneously? Yes! Multi-timeframe analysis is very powerful: Classic scheme: Higher TF (D1, W1) - determine global trend Wait for STRONG signal This is our trading direction Middle TF (H4, H1) - look for confirmation STRONG signal in same direction Precise entry zone Lower TF (M15, M5) - entry point Golden Cross or bounce from Fast EMA Precise stop loss Example: W1: STRONG BUY active (global uptrend) H4: STRONG BUY appeared (confirmation) M15: Wait for Golden Cross or bounce from Fast EMA → ENTRY Advantages: Maximum reliability Clear timeframe hierarchy Large targets 14. How does indicator work on news? Delta Adaptive EMA adapts excellently to news: Before news: Low volatility → Delta EMA becomes fast → pulls to price During news: Sharp volatility spike → Delta EMA slows → filters noise After news: Volatility normalizes → Delta EMA returns to normal Recommendations: Don't trade at news release moment (spreads widen) Wait for STRONG signal after news (2-5 bars) Use Delta Adaptive as Fast EMA for quick reaction Widen stops by 50-100% during important news Advanced Techniques Technique 1: "Divergences with EMA" Idea: Look for discrepancies between price and Fast EMA Bullish divergence: Price makes lower low Fast EMA makes higher low = Possible reversal up Bearish divergence: Price makes higher high Fast EMA makes lower high = Possible reversal down How to trade: Find divergence Wait for STRONG signal in divergence direction Enter on confirmation Technique 2: "EMA Tunnel" Idea: Use space between Fast and Slow EMA as "tunnel" Rules: Wide tunnel - strong trend, hold position Narrow tunnel - weak trend or consolidation, caution Tunnel narrowing - trend weakening, prepare to exit Tunnel widening - trend strengthening, can add Visually: Gradient Clouds show this automatically! Trading: Enter on STRONG signal (tunnel starts widening) Hold while tunnel wide Exit when tunnel starts narrowing Technique 3: "Wave Analysis with Lambda" Idea: Lambda Wave EMA creates sinusoid matching market cycles Setup: Lambda Base Period: 30 Lambda Wave Amplitude: 0.5 Lambda Wave Frequency: 50 (adjusted to asset cycle) How to find correct Frequency: Look at historical cycles (distance between local highs) Average distance = your Frequency Example: if highs every 40-60 bars, set Frequency = 50 Trading: Enter when Lambda Wave at bottom of sinusoid (growth potential) Exit when Lambda Wave at top (fall potential) Combine with STRONG signals Technique 4: "Cluster Analysis" Idea: When all EMAs gather in narrow cluster = powerful breakout soon Cluster signs: All EMAs (Phi, Pi, e, Delta) within 0.5-1% of each other Gradient Clouds almost invisible Price jumping around all EMAs Trading: Identify cluster (all EMAs close) Determine breakout direction (where more volume, higher TFs direction) Wait for breakout and STRONG signal Enter on confirmation Target = cluster size × 3-5 This is very powerful technique for big moves! Technique 5: "Sigma as Dynamic Level" Idea: Sigma Composite EMA = average of all EMAs = magnetic level Usage: Enable Sigma Composite (Weighted Average) Sigma works as dynamic support/resistance Price often returns to Sigma before trend continuation Trading: In trend: Enter on bounces from Sigma In range: Fade moves from Sigma (trade return to Sigma) On breakout: Sigma becomes support/resistance Risk Management Basic Rules 1. Position Size Conservative: 1% of capital per trade Moderate: 2% of capital per trade (recommended) Aggressive: 3-5% (only for experienced) Calculation formula: Lot Size = (Capital × Risk%) / (Stop in pips × Pip value) 2. Risk/Reward Ratio Minimum: 1:1.5 Standard: 1:2 (recommended) Optimal: 1:3 Aggressive: 1:5+ 3. Maximum Drawdown Daily: -3% to -5% Weekly: -7% to -10% Monthly: -15% to -20% Upon reaching limit → STOP trading until end of period Position Management Strategies 1. Fixed Stop Method: Stop below/above Fast EMA or local extreme DON'T move stop against position Can move to breakeven For whom: Beginners, conservative traders 2. Trailing by Fast EMA Method: Each day (or bar) move stop to Fast EMA level Position closes when price breaks Fast EMA Advantages: Stay in trend as long as possible Automatically exit on reversal For whom: Trend followers, swing traders 3. Partial Exit Method: 50% of position close at +2R 50% hold with trailing by Mid EMA or Slow EMA Advantages: Lock profit Leave position for big move Psychologically comfortable For whom: Universal method (recommended) 4. Pyramiding Method: First entry on STRONG signal (50% of planned position) Add 25% on pullback to Fast EMA Add another 25% on pullback to Mid EMA Overall stop below Slow EMA Advantages: Average entry price Reduce risk Increase profit in strong trends Caution: Works only in trends In range leads to losses For whom: Experienced traders Trading Psychology Correct Mindset 1. Indicator is a tool, not holy grail Indicator shows probability, not guarantee There will be losing trades - this is normal Important is series statistics, not one trade 2. Trust the system If STRONG signal appeared - enter Don't search for "perfect" moment Follow trading plan 3. Patience STRONG signals don't appear every day Better miss signal than enter against trend Quality over quantity 4. Discipline Always set stop loss Don't move stop against position Don't increase risk after losses Beginner Mistakes 1. "I know better than indicator" Indicator says STRONG BUY, but you think "too high, will wait for pullback" Result: miss profitable move Solution: Trust signals or don't use indicator 2. "Will reverse now for sure" Trading against STRONG trend Result: stops, stops, stops Solution: Trend is your friend, trade with trend 3. "Will hold a bit more" Don't exit when STRONG signal disappears Greed eats profit Solution: If signal gone - exit! 4. "I'll recover" After losses double risk Result: huge losses Solution: Fixed % risk ALWAYS 5. "I don't like this signal" Skip signals because of "feeling" Result: inconsistency, no statistics Solution: Trade ALL signals or clearly define filters Trading Journal What to Record For each trade: 1. Entry/exit date and time 2. Instrument and timeframe 3. Signal type Golden Cross STRONG BUY STRONG SELL Death Cross 4. Indicator settings Fast/Mid/Slow EMA Base Multiplier Other parameters 5. Chart screenshot Entry moment Exit moment 6. Trade parameters Position size Stop loss Take Profit R:R 7. Result Profit/Loss in $ Profit/Loss in % Profit/Loss in R 8. Notes What was right What was wrong Emotions during trade Lessons Journal Analysis Analyze weekly: 1. Win Rate Win Rate = (Profitable trades / All trades) × 100% Good: 50-60% Excellent: 60-70% Exceptional: 70%+ 2. Average R Average R = Sum of all R / Number of trades Good: +0.5R Excellent: +1.0R Exceptional: +1.5R+ 3. Profit Factor Profit Factor = Total profit / Total losses Good: 1.5+ Excellent: 2.0+ Exceptional: 3.0+ 4. Maximum Drawdown Track consecutive losses If more than 5 in row - stop, check system 5. Best/Worst Trades What was common in best trades? (do more) What was common in worst trades? (avoid) Pre-Trade Checklist Technical Analysis STRONG signal active (BUY or SELL) All EMAs properly aligned (Fast > Mid > Slow or reverse) Price on correct side of Fast EMA Gradient Clouds confirm trend Pulsing Bar shows STRONG state Momentum % in normal range (not overheated) No close strong levels against direction Higher timeframe doesn't contradict Risk Management Position size calculated (1-2% risk) Stop loss set Take profit calculated (minimum 1:2) R:R satisfactory Daily/weekly risk limit not exceeded No other open correlated positions Fundamental Analysis No important news in coming hours Market session appropriate (liquidity) No contradicting fundamentals Understand why asset is moving Psychology Calm and thinking clearly No emotions from previous trades Ready to accept loss at stop Following trading plan Not revenging market for past losses If at least one point is NO - think twice before entering! Learning Roadmap Week 1: Familiarization Goals: Install and configure indicator Study all EMA types Understand visualization Tasks: Add indicator to chart Test all Fast/Mid/Slow settings Play with Base Multiplier on different timeframes Observe Gradient Clouds and Pulsing Bar Study Info Table Result: Comfort with indicator interface Week 2: Signals Goals: Learn to recognize all signal types Understand difference between Golden Cross and STRONG Tasks: Find 10 Golden Cross examples in history Find 10 STRONG BUY examples in history Compare their results (which worked better) Set up alerts Get 5 real alerts Result: Understanding signals Week 3: Demo Trading Goals: Start trading signals on demo account Gather statistics Tasks: Open demo account Trade ONLY STRONG signals Keep journal (minimum 20 trades) Don't change indicator settings Strictly follow stop losses Result: 20+ documented trades Week 4: Analysis Goals: Analyze demo trading results Optimize approach Tasks: Calculate win rate and average R Find patterns in profitable trades Find patterns in losing trades Adjust approach (not indicator!) Write trading plan Result: Trading plan on 1 page Month 2: Improvement Goals: Deepen understanding Add additional techniques Tasks: Study multi-timeframe analysis Test combinations with Price Action Try advanced techniques (divergences, tunnels) Continue demo trading (minimum 50 trades) Achieve stable profitability on demo Result: Win rate 55%+ and Profit Factor 1.5+ Month 3: Real Trading Goals: Transition to real account Maintain discipline Tasks: Open small real account Trade minimum lots Strictly follow trading plan DON'T increase risk Focus on process, not profit Result: Psychological comfort on real Month 4+: Scaling Goals: Increase account Become consistently profitable Tasks: With 60%+ win rate can increase risk to 2% Upon doubling account can add capital Continue keeping journal Periodically review and improve strategy Share experience with community Result: Stable profitability month after month Additional Resources Recommended Reading Technical Analysis: "Technical Analysis of Financial Markets" - John Murphy "Trading in the Zone" - Mark Douglas (psychology) "Market Wizards" - Jack Schwager (trader interviews) EMA and Moving Averages: "Moving Averages 101" - Steve Burns Articles on Investopedia about EMA Risk Management: "The Mathematics of Money Management" - Ralph Vince "Trade Your Way to Financial Freedom" - Van K. Tharp Trading Journals: Edgewonk (paid, very powerful) Tradervue (free version + premium) Excel/Google Sheets (free) Screeners: TradingView Stock Screener Finviz (stocks) CoinMarketCap (crypto) Conclusion Hellenic EMA Matrix is a powerful tool based on universal mathematical constants of nature. The indicator combines: Mathematical elegance - Phi, Pi, e instead of arbitrary numbers Premium visualization - Neon Glow, Gradient Clouds, Pulsing Bar Reliable signals - STRONG BUY/SELL work on all timeframes Flexibility - 6 EMA types, adaptation to any trading style Automation - auto-sorting EMAs, SL/TP calculation, alerts Key Success Principles: Simplicity - start with basic settings (Phi/Pi/e, Base=10) Discipline - follow STRONG signals strictly Patience - wait for quality setups Risk Management - 1-2% per trade, ALWAYS Journal - document every trade Learning - constantly improve skills Remember: Indicator shows probability, not guarantee Important is series statistics, not one trade Psychology more important than technique Quality more important than quantity Process more important than result Acknowledgments Thank you for using Hellenic EMA Matrix - Alpha Omega Premium! The indicator was created with love for mathematics, markets, and beautiful visualization. Wishing you profitable trading! Guide Version: 1.0 Date: 2025 Compatibility: Pine Script v6, TradingView "In the simplicity of mathematical constants lies the complexity of market movements"
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Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM): Phase Coherence Detection Through Complex-Plane Oscillator Analysis Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge. The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions. What Makes This Original Complex-Plane Phasor Framework This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation. From these components, the system extracts: Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°) Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory). Coherence Index Calculation The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ). The CI measures what happens when you sum all these vectors: Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ) Coherence Index : CI = |R| / N Where |R| is the magnitude of the resultant vector and N is the number of active oscillators. The CI ranges from 0 to 1: CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference 0 < CI < 1 : Partial alignment—some clustering with some scatter This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss. Dominant Phase and Direction Detection Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points: Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ)) This gives the "average direction" of all oscillator phases, mapped to -180° to +180°: +90° to -90° (right half-plane): Bullish phase dominance +90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging. Entanglement Matrix and Pairwise Coherence While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates: E(i,j) = |cos(φᵢ - φⱼ)| This represents the phase agreement between oscillators i and j: E = 1.0 : Oscillators are in-phase (0° or 360° apart) E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal) E between 0 and 1 : Varying degrees of alignment The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered. The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently. Phase-Lock Tolerance Mechanism A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators: For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180° Max Spread = maximum Δφ across all pairs If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band. This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals. Multi-Layer Visual Architecture QRFM includes six visual components that represent the same underlying mathematics from different perspectives: Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it. Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition. Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier. Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers. Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down. Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%). Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match. Core Components and How They Work Together 1. Oscillator Normalization Engine The foundation is creating a common measurement scale. QRFM supports eight oscillators: RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to Stochastic %K : Normalized from using (80, 20) anchors CCI : Divided by 200 (typical extreme level), clamped to Williams %R : Normalized from using (-20, -80) anchors MFI : Normalized from using (80, 20) anchors ROC : Divided by 10, clamped to TSI : Divided by 50, clamped to Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI. 2. Analytic Signal Construction For each active oscillator at each bar, the system constructs the analytic signal: In-Phase (I) : The normalized oscillator value itself Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation) This creates a 2D representation: (I, Q). The phase is extracted as: φ = atan2(Q, I) × (180 / π) This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through." The amplitude is extracted as: A = √(I² + Q²) This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state). 3. Coherence Calculation Pipeline For each bar (or every Nth bar if phase sample rate > 1 for performance): Step 1 : Extract phase φₙ for each of the N active oscillators Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180) Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ) Step 4 : Calculate magnitude: |R| = √ Step 5 : Normalize by count: CI_raw = |R| / N Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window) The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability. The dominant phase is calculated as: φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π) This is the angle of the resultant vector R in the complex plane. 4. Entanglement Matrix Construction For all unique pairs of oscillators (i, j) where i < j: Step 1 : Get phases φᵢ and φⱼ Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians) Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)| Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j) The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric. For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity. 5. Phase-Lock Detection Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ| Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ Step 3 : Find maximum: max_spread = max(Δφ) across all pairs Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance) If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter. 6. Signal Generation Logic Signals are generated through multi-layer confirmation: Long Ignition Signal : CI crosses above ignition threshold (e.g., 0.80) AND dominant phase is in bullish range (-90° < φ_dom < +90°) AND phase_locked = true AND entangled_pairs >= minimum threshold (e.g., 4) Short Ignition Signal : CI crosses above ignition threshold AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°) AND phase_locked = true AND entangled_pairs >= minimum threshold Collapse Signal : CI at bar minus CI at current bar > collapse threshold (e.g., 0.55) AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state) These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers. Calculation Methodology Phase 1: Oscillator Computation and Normalization On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions: RSI: ta.rsi(close, length) MACD: ta.macd() returning histogram component Stochastic: ta.stoch() smoothed with ta.sma() CCI: ta.cci(close, length) Williams %R: ta.wpr(length) MFI: ta.mfi(hlc3, length) ROC: ta.roc(close, length) TSI: ta.tsi(close, short, long) Each raw value is then passed through a normalization function: normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1 This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish. For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to . Phase 2: Phasor Extraction For each normalized oscillator value val: I = val (in-phase component) Q = val - val (quadrature component, first difference) Phase calculation: phi_rad = atan2(Q, I) phi_deg = phi_rad × (180 / π) Amplitude calculation: A = √(I² + Q²) These values are stored in arrays: osc_phases and osc_amps for each oscillator n. Phase 3: Complex Summation and Coherence Initialize accumulators: sum_cos = 0 sum_sin = 0 For each oscillator n = 0 to N-1: phi_rad = osc_phases × (π / 180) sum_cos += cos(phi_rad) sum_sin += sin(phi_rad) Resultant magnitude: resultant_mag = √(sum_cos² + sum_sin²) Coherence Index (raw): CI_raw = resultant_mag / N Smoothed CI: CI = SMA(CI_raw, smoothing_window) Dominant phase: phi_dom_rad = atan2(sum_sin, sum_cos) phi_dom_deg = phi_dom_rad × (180 / π) Phase 4: Entanglement Matrix Population For i = 0 to N-2: For j = i+1 to N-1: phi_i = osc_phases × (π / 180) phi_j = osc_phases × (π / 180) delta_phi = phi_i - phi_j E = |cos(delta_phi)| matrix_index_ij = i × N + j matrix_index_ji = j × N + i entangle_matrix = E entangle_matrix = E if E >= threshold: entangled_pairs += 1 The matrix uses flat array storage with index mapping: index(row, col) = row × N + col. Phase 5: Phase-Lock Check max_spread = 0 For i = 0 to N-2: For j = i+1 to N-1: delta = |osc_phases - osc_phases | if delta > 180: delta = 360 - delta max_spread = max(max_spread, delta) phase_locked = (max_spread < tolerance) Phase 6: Signal Evaluation Ignition Long : ignition_long = (CI crosses above threshold) AND (phi_dom > -90 AND phi_dom < 90) AND phase_locked AND (entangled_pairs >= minimum) Ignition Short : ignition_short = (CI crosses above threshold) AND (phi_dom < -90 OR phi_dom > 90) AND phase_locked AND (entangled_pairs >= minimum) Collapse : CI_prev = CI collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6) All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true. Phase 7: Field Strength and Visualization Metrics Average Amplitude : avg_amp = (Σ osc_amps ) / N Field Strength : field_strength = CI × avg_amp Collapse Risk (for dashboard): collapse_risk = (CI - CI) / max(CI , 0.1) collapse_risk_pct = clamp(collapse_risk × 100, 0, 100) Quantum State Classification : if (CI > threshold AND phase_locked): state = "Ignition" else if (CI > 0.6): state = "Coherent" else if (collapse): state = "Collapse" else: state = "Chaos" Phase 8: Visual Rendering Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement: radius = amplitude × grid_center × 0.8 x = radius × cos(phase × π/180) y = radius × sin(phase × π/180) col = center + x (mapped to grid coordinates) row = center - y Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient. Entanglement Web : Render matrix as table cell with background color opacity = E(i,j). Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI). All visual components render only on the last bar (barstate.islast) to minimize computational overhead. How to Use This Indicator Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction. Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools. Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot. Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence. Understanding the Circular Orbit Plot The orbit plot is a polar grid showing oscillator vectors in real-time: Center point : Neutral (zero phase and amplitude) Each vector : A line from center to a point on the grid Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south) Vector length : The oscillator's amplitude (short = weak signal, long = strong signal) Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.) What to watch : Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning. Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime. Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends. Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals. Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold. Reading Dashboard Metrics The dashboard provides numerical confirmation of what the orbit plot shows visually: CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries). Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral. Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment. Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals. Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide). State : Real-time classification: 🚀 IGNITION: CI just crossed threshold with phase-lock ⚡ COHERENT: CI is high and stable 💥 COLLAPSE: CI has dropped sharply 🌀 CHAOS: Low CI, scattered phases Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown. Interpreting Signals Long Ignition (Blue Triangle Below Price) : Occurs when CI crosses above threshold (e.g., 0.80) Dominant phase is in bullish range (-90° to +90°) All oscillators are phase-locked (within tolerance) Minimum entangled pairs requirement met Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw. Short Ignition (Red Triangle Above Price) : Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°) Interpretation : Coherent bearish alignment has formed. High-probability short entry. Collapse (Circles Above and Below Price) : CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window CI was previously above 0.6 (collapsing from coherent state) Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning. Phase-Time Heat Map Patterns Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left). Pattern: Horizontal Color Bands If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime. Pattern: Vertical Color Bands If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots. Pattern: Rainbow Chaos If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation. Pattern: Color Transition If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway. Entanglement Web Analysis Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators. Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well. Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature. Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself. How to use : Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal). Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation). Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals. Trading Workflow Step 1: Monitor Coherence Level Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait. Step 2: Detect Coherence Building When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare. Step 3: Confirm Phase Direction Check the dominant phase angle and the orbit plot quadrant where clustering is occurring: Clustering in right half (0° to ±90°): Bullish bias forming Clustering in left half (±90° to 180°): Bearish bias forming Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇). Step 4: Wait for Signal Confirmation Do not enter based on rising CI alone. Wait for the full ignition signal: CI crosses above threshold Phase-lock indicator shows 🔒 YES Entangled pairs count >= minimum Directional triangle appears on chart This ensures all layers have aligned. Step 5: Execute Entry Long : Blue triangle below price appears → enter long Short : Red triangle above price appears → enter short Step 6: Position Management Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer). Monitoring : Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact. Check dashboard collapse risk. If it rises above 50%, prepare for exit. Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking. Exit Triggers : Collapse signal fires (circles appear) Dominant phase flips to opposite half-plane CI drops below 40% (coherence lost) Price hits your profit target or trailing stop Step 7: Post-Exit Analysis After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside. Best Practices Use Price Structure as Context QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example: Long ignition near a major support level after a pullback: high-probability bounce Long ignition in the middle of a range with no structure: lower probability Multi-Timeframe Confirmation Open QRFM on two timeframes simultaneously: Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime. Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias. This prevents counter-trend trades and increases win rate. Distinguish Between Regime Types High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings. Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish. Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside. Adjust Parameters to Instrument and Timeframe Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10). Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14). Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness. Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction. Use Entanglement Count as Conviction Filter The minimum entangled pairs setting controls signal strictness: Low (1-2) : More signals, lower quality (acceptable if you have other confirmation) Medium (3-5) : Balanced (recommended for most traders) High (6+) : Very strict, fewer signals, highest quality Adjust based on your trade frequency preference and risk tolerance. Monitor Oscillator Contribution Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example: On low-volume instruments, MFI may be unreliable → disable MFI On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable Respect the Collapse Signal Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice: If in profit: Take partial or full profit on collapse If at breakeven/small loss: Exit immediately If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown Collapses do not guarantee immediate reversals—they signal uncertainty . Combine with Volume Analysis If your instrument has reliable volume: Ignitions with expanding volume: Higher conviction Ignitions with declining volume: Weaker, possibly false Collapses with volume spikes: Strong reversal signal Collapses with low volume: May just be consolidation Volume is not built into QRFM (except via MFI), so add it as external confirmation. Observe the Phase Spiral The spiral provides a quick visual cue for rotation consistency: Tight, smooth spiral : Ensemble is rotating coherently (trending) Loose, erratic spiral : Phase is jumping around (ranging or transitional) If the spiral tightens, coherence is building. If it loosens, coherence is dissolving. Do Not Overtrade Low-Coherence Periods When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times: Reduce position size Widen stops Wait for coherence to return QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside." Use Alerts Strategically Set alerts for: Long Ignition Short Ignition Collapse Phase Lock (optional) Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify: Orbit plot shows clustering Dashboard confirms all conditions Price structure supports the trade Do not blindly trade alerts—use them as prompts for analysis. Ideal Market Conditions Best Performance Instruments : Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto) Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets) Timeframes : 15-minute to 4-hour: Optimal balance of noise reduction and responsiveness 1-hour to daily: Slower, higher-conviction signals; good for swing trading 5-minute: Acceptable for scalping if parameters are tightened and you accept more noise Market Regimes : Trending markets with periodic retracements (where oscillators cycle through phases predictably) Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion) Rotational markets with clear swings (oscillators phase-lock at turning points) Volatility : Moderate to high volatility (oscillators have room to move through their ranges) Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses) Challenging Conditions Instruments : Very low liquidity markets (erratic price action creates unstable oscillator phases) Heavily news-driven instruments (fundamentals may override technical coherence) Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence) Market Regimes : Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire) Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes) Gap-driven markets (large overnight gaps create phase discontinuities) Timeframes : Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading Special Cases : During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside. In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through. Adaptive Behavior QRFM is designed to self-adapt to poor conditions: When coherence is genuinely absent, CI remains low and signals do not fire When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades. Parameter Optimization by Trading Style Scalping (5-15 Minute Charts) Goal : Maximum responsiveness, accept higher noise Oscillator Lengths : RSI: 7-10 MACD: 8/17/6 Stochastic: 8-10, smooth 2-3 CCI: 14-16 Others: 8-12 Coherence Settings : CI Smoothing Window: 2-3 bars (fast reaction) Phase Sample Rate: 1 (every bar) Ignition Threshold: 0.65-0.75 (lower for more signals) Collapse Threshold: 0.40-0.50 (earlier exit warnings) Confirmation : Phase Lock Tolerance: 40-50° (looser, easier to achieve) Min Entangled Pairs: 2-3 (fewer oscillators required) Visuals : Orbit Plot + Dashboard only (reduce screen clutter for fast decisions) Disable heavy visuals (heat map, web) for performance Alerts : Enable all ignition and collapse alerts Set to "Once per bar close" Day Trading (15-Minute to 1-Hour Charts) Goal : Balance between responsiveness and reliability Oscillator Lengths : RSI: 14 (standard) MACD: 12/26/9 (standard) Stochastic: 14, smooth 3 CCI: 20 Others: 10-14 Coherence Settings : CI Smoothing Window: 3-5 bars (balanced) Phase Sample Rate: 2-3 Ignition Threshold: 0.75-0.85 (moderate selectivity) Collapse Threshold: 0.50-0.55 (balanced exit timing) Confirmation : Phase Lock Tolerance: 30-40° (moderate tightness) Min Entangled Pairs: 4-5 (reasonable confirmation) Visuals : Orbit Plot + Dashboard + Heat Map or Web (choose one) Field Cloud for regime backdrop Alerts : Ignition and collapse alerts Optional phase-lock alert for advance warning Swing Trading (4-Hour to Daily Charts) Goal : High-conviction signals, minimal noise, fewer trades Oscillator Lengths : RSI: 14-21 MACD: 12/26/9 or 19/39/9 (longer variant) Stochastic: 14-21, smooth 3-5 CCI: 20-30 Others: 14-20 Coherence Settings : CI Smoothing Window: 5-10 bars (very smooth) Phase Sample Rate: 3-5 Ignition Threshold: 0.80-0.90 (high bar for entry) Collapse Threshold: 0.55-0.65 (only significant breakdowns) Confirmation : Phase Lock Tolerance: 20-30° (tight clustering required) Min Entangled Pairs: 5-7 (strong confirmation) Visuals : All modules enabled (you have time to analyze) Heat Map for multi-bar pattern recognition Web for deep confirmation analysis Alerts : Ignition and collapse Review manually before entering (no rush) Position/Long-Term Trading (Daily to Weekly Charts) Goal : Rare, very high-conviction regime shifts Oscillator Lengths : RSI: 21-30 MACD: 19/39/9 or 26/52/12 Stochastic: 21, smooth 5 CCI: 30-50 Others: 20-30 Coherence Settings : CI Smoothing Window: 10-14 bars Phase Sample Rate: 5 (every 5th bar to reduce computation) Ignition Threshold: 0.85-0.95 (only extreme alignment) Collapse Threshold: 0.60-0.70 (major regime breaks only) Confirmation : Phase Lock Tolerance: 15-25° (very tight) Min Entangled Pairs: 6+ (broad consensus required) Visuals : Dashboard + Orbit Plot for quick checks Heat Map to study historical coherence patterns Web to verify deep entanglement Alerts : Ignition only (collapses are less critical on long timeframes) Manual review with fundamental analysis overlay Performance Optimization (Low-End Systems) If you experience lag or slow rendering: Reduce Visual Load : Orbit Grid Size: 8-10 (instead of 12+) Heat Map Time Bins: 5-8 (instead of 10+) Disable Web Matrix entirely if not needed Disable Field Cloud and Phase Spiral Reduce Calculation Frequency : Phase Sample Rate: 5-10 (calculate every 5-10 bars) Max History Depth: 100-200 (instead of 500+) Disable Unused Oscillators : If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops. Simplify Dashboard : Choose "Small" dashboard size Reduce number of metrics displayed These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness. Important Disclaimers This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty. No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics. Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades. Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries. Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside. Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose. Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital. No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes. Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness. This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning. Technical Notes Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation. Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary. Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed). Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically. Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations. Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise. Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)). Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared). Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals. Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross). Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red). No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests. Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies. — Dskyz, Engineering precision. Trading coherence.
Pine Script®指标
由DskyzInvestments提供
8
Volume Based Sampling [BackQuant]Volume Based Sampling What this does This indicator converts the usual time-based stream of candles into an event-based stream of “synthetic” bars that are created only when enough trading activity has occurred . You choose the activity definition: Volume bars : create a new synthetic bar whenever the cumulative number of shares/contracts traded reaches a threshold. Dollar bars : create a new synthetic bar whenever the cumulative traded dollar value (price × volume) reaches a threshold. The script then keeps an internal ledger of these synthetic opens, highs, lows, closes, and volumes, and can display them as candles, plot a moving average calculated over the synthetic closes, mark each time a new sample is formed, and optionally overlay the native time-bars for comparison. Why event-based sampling matters Markets do not release information on a clock: activity clusters during news, opens/closes, and liquidity shocks. Event-based bars normalize for that heteroskedastic arrival of information: during active periods you get more bars (finer resolution); during quiet periods you get fewer bars (coarser resolution). Research shows this can reduce microstructure pathologies and produce series that are closer to i.i.d. and more suitable for statistical modeling and ML. In particular: Volume and dollar bars are a common event-time alternative to time bars in quantitative research and are discussed extensively in Advances in Financial Machine Learning (AFML). These bars aim to homogenize information flow by sampling on traded size or value rather than elapsed seconds. The Volume Clock perspective models market activity in “volume time,” showing that many intraday phenomena (volatility, liquidity shocks) are better explained when time is measured by traded volume instead of seconds. Related market microstructure work on flow toxicity and liquidity highlights that the risk dealers face is tied to information intensity of order flow, again arguing for activity-based clocks. How the indicator works (plain English) Choose your bucket type Volume : accumulate volume until it meets a threshold. Dollar Bars : accumulate close × volume until it meets a dollar threshold. Pick the threshold rule Dynamic threshold : by default, the script computes a rolling statistic (mean or median) of recent activity to set the next bucket size. This adapts bar size to changing conditions (e.g., busier sessions produce more frequent synthetic bars). Fixed threshold : optionally override with a constant target (e.g., exactly 100,000 contracts per synthetic bar, or $5,000,000 per dollar bar). Build the synthetic bar While a bucket fills, the script tracks: o_s: first price of the bucket (synthetic open) h_s: running maximum price (synthetic high) l_s: running minimum price (synthetic low) c_s: last price seen (synthetic close) v_s: cumulative native volume inside the bucket d_samples: number of native bars consumed to complete the bucket (a proxy for “how fast” the threshold filled) Emit a new sample Once the bucket meets/exceeds the threshold, a new synthetic bar is finalized and stored. If overflow occurs (e.g., a single native bar pushes you past the threshold by a lot), the code will emit multiple synthetic samples to account for the extra activity. Maintain a rolling history efficiently A ring buffer can overwrite the oldest samples when you hit your Max Stored Samples cap, keeping memory usage stable. Compute synthetic-space statistics The script computes an SMA over the last N synthetic closes and basic descriptors like average bars per synthetic sample, mean and standard deviation of synthetic returns, and more. These are all in event time , not clock time. Inputs and options you will actually use Data Settings Sampling Method : Volume or Dollar Bars. Rolling Lookback : window used to estimate the dynamic threshold from recent activity. Filter : Mean or Median for the dynamic threshold. Median is more robust to spikes. Use Fixed? / Fixed Threshold : override dynamic sizing with a constant target. Max Stored Samples : cap on synthetic history to keep performance snappy. Use Ring Buffer : turn on to recycle storage when at capacity. Indicator Settings SMA over last N samples : moving average in synthetic space . Because its index is sample count, not minutes, it adapts naturally: more updates in busy regimes, fewer in quiet regimes. Visuals Show Synthetic Bars : plot the synthetic OHLC candles. Candle Color Mode : Green/Red: directional close vs open Volume Intensity: opacity scales with synthetic size Neutral: single color Adaptive: graded by how large the bucket was relative to threshold Mark new samples : drop a small marker whenever a new synthetic bar prints. Comparison & Research Show Time Bars : overlay the native time-based candles to visually compare how the two sampling schemes differ. How to read it, step by step Turn on “Synthetic Bars” and optionally overlay “Time Bars.” You will see that during high-activity bursts, synthetic bars print much faster than time bars. Watch the synthetic SMA . Crosses in synthetic space can be more meaningful because each update represents a roughly comparable amount of traded information. Use the “Avg Bars per Sample” in the info table as a regime signal. Falling average bars per sample means activity is clustering, often coincident with higher realized volatility. Try Dollar Bars when price varies a lot but share count does not; they normalize by dollar risk taken in each sample. Volume Bars are ideal when share count is a better proxy for information flow in your instrument. Quant finance background and citations Event time vs. clock time : Easley, López de Prado, and O’Hara advocate measuring intraday phenomena on a volume clock to better align sampling with information arrival. This framing helps explain volatility bursts and liquidity droughts and motivates volume-based bars. Flow toxicity and dealer risk : The same authors show how adverse selection risk changes with the intensity and informativeness of order flow, further supporting activity-based clocks for modeling and risk management. AFML framework : In Advances in Financial Machine Learning , event-driven bars such as volume, dollar, and imbalance bars are presented as superior sampling units for many ML tasks, yielding more stationary features and fewer microstructure distortions than fixed time bars. ( Alpaca ) Practical use cases 1) Regime-aware moving averages The synthetic SMA in event time is not fooled by quiet periods: if nothing of consequence trades, it barely updates. This can make trend filters less sensitive to calendar drift and more sensitive to true participation. 2) Breakout logic on “equal-information” samples The script exposes simple alerts such as breakout above/below the synthetic SMA . Because each bar approximates a constant amount of activity, breakouts are conditioned on comparable informational mass, not arbitrary time buckets. 3) Volatility-adaptive backtests If you use synthetic bars as your base data stream, most signal rules become self-paced : entry and exit opportunities accelerate in fast markets and slow down in quiet regimes, which often improves the realism of slippage and fill modeling in research pipelines (pair this indicator with strategy code downstream). 4) Regime diagnostics Avg Bars per Sample trending down: activity is dense; expect larger realized ranges. Return StdDev (synthetic) rising: noise or trend acceleration in event time; re-tune risk. Interpreting the info panel Method : your sampling choice and current threshold. Total Samples : how many synthetic bars have been formed. Current Vol/Dollar : how much of the next bucket is already filled. Bars in Bucket : native bars consumed so far in the current bucket. Avg Bars/Sample : lower means higher trading intensity. Avg Return / Return StdDev : return stats computed over synthetic closes . Research directions you can build from here Imbalance and run bars Extend beyond pure volume or dollar thresholds to imbalance bars that trigger on directional order flow imbalance (e.g., buy volume minus sell volume), as discussed in the AFML ecosystem. These often further homogenize distributional properties used in ML. alpaca.markets Volume-time indicators Re-compute classical indicators (RSI, MACD, Bollinger) on the synthetic stream. The premise is that signals are updated by traded information , not seconds, which may stabilize indicator behavior in heteroskedastic regimes. Liquidity and toxicity overlays Combine synthetic bars with proxies of flow toxicity to anticipate spread widening or volatility clustering. For instance, tag synthetic bars that surpass multiples of the threshold and test whether subsequent realized volatility is elevated. Dollar-risk parity sampling for portfolios Use dollar bars to align samples across assets by notional risk, enabling cleaner cross-asset features and comparability in multi-asset models (e.g., correlation studies, regime clustering). AFML discusses the benefits of event-driven sampling for cross-sectional ML feature engineering. Microstructure feature set Compute duration in native bars per synthetic sample , range per sample , and volume multiple of threshold as inputs to state classifiers or regime HMMs . These features are inherently activity-aware and often predictive of short-horizon volatility and trend persistence per the event-time literature. ( Alpaca ) Tips for clean usage Start with dynamic thresholds using Median over a sensible lookback to avoid outlier distortion, then move to Fixed thresholds when you know your instrument’s typical activity scale. Compare time bars vs synthetic bars side by side to develop intuition for how your market “breathes” in activity time. Keep Max Stored Samples reasonable for performance; the ring buffer avoids memory creep while preserving a rolling window of research-grade data.
Pine Script®指标
由BackQuant提供
Screener based on Profitunity strategy for multiple timeframes Screener based on Profitunity strategy by Bill Williams for multiple timeframes (max 5, including chart timeframe) and customizable symbol list. The screener analyzes the Alligator and Awesome Oscillator indicators, Divergent bars and high volume bars. The maximum allowed number of requests (symbols and timeframes) is limited to 40 requests, for example, for 10 symbols by 4 requests of different timeframes. Therefore, the indicator automatically limits the number of displayed symbols depending on the number of timeframes for each symbol, if there are more symbols than are displayed in the screener table, then the ordinal numbers are displayed to the left of the symbols, in this case you can display the next group of symbols by increasing the value by 1 in the "Show tickers from" field, if the "Group" field is enabled, or specify the symbol number by 1 more than the last symbol in the screener table. 👀 When timeframe filtering is applied, the screener table displays only the columns of those timeframes for which the filtering value is selected, which allows displaying more symbols. For each timeframe, in the "TIMEFRAMES > Prev" field, you can enable the display of data for the previous bar relative to the last (current) one, if the market is open for the requested symbol. In the "TIMEFRAMES > Y" field, you can enable filtering depending on the location of the last five bars relative to the Alligator indicator lines, which are designated by special symbols in the screener table: ⬆️ — if the Alligator is open upwards (Lips > Teeth > Jaw) and none of the bars is closed below the Lips line; ↗️ — if one of the bars, except for the penultimate one, is closed below Lips, or two bars, except for the last one, are closed below Lips, or the Alligator is open upwards only below four bars, but none of the bars is closed below Lips; ⬇️ — if the Alligator is open downwards (Lips < Teeth < Jaw), but none of the bars is closed above Lips; ↘️ — if one of the bars, except the penultimate one, is closed above the Lips, or two bars, except the last one, are closed above the Lips, or the Alligator is open down only above four bars, but none of the bars are closed above the Lips; ➡️ — in other cases, including when the Alligator lines intersect and one of the bars is closed behind the Lips line or two bars intersect one of the Alligator lines. In the "TIMEFRAMES > Show bar change value for TF" field, you can add a column to the right of the selected timeframe column with the percentage change between the closing price of the last bar (current) and the closing price of the previous bar ((close – previous close) / previous close * 100). Depending on the percentage value, the background color of the screener table cell will change: dark red if <= -3%; red if <= -2%, light red if <= -0.5%; dark green if >= 3%; green if >= 2%; light green if >= 0.5%. For each timeframe, the screener table displays the symbol of the latest (current) bar, depending on the closing price relative to the bar's midpoint ((high + low) / 2) and its location relative to the Alligator indicator lines: ⎾ — the bar's closing price is above its midpoint; ⎿ — the bar's closing price is below its midpoint; ├ — the bar's closing price is equal to its midpoint; 🟢 — Bullish Divergent bar, i.e. the bar's closing price is above its midpoint, the bar's high is below all Alligator lines, the bar's low is below the previous bar's low; 🔴 — Bearish Divergent bar, i.e. the bar's closing price is below its midpoint, the bar's low is above all Alligator lines, the bar's high is above the previous bar's high. When filtering is enabled in the "TIMEFRAMES > Filtering by Divergent bar" field, the data in the screener table cells will be displayed only for those timeframes that have a Divergent bar. A high bar volume signal is also displayed — 📶/📶² if the bar volume is greater than 40%/70% of the average volume value calculated using a simple moving average (SMA) in the 140 bar interval from the last bar. In the indicator settings in the "SYMBOL LIST" field, each ticker (for example: OANDA:SPX500USD) must be on a separate line. If the market is closed, then the data for requested symbols will be limited to the time of the last (current) bar on the chart, for example, if the current symbol was traded yesterday, and the requested symbol is traded today, when requesting data for an hourly timeframe, the last bar will be for yesterday, if the timeframe of the current chart is not higher than 1 day. Therefore, by default, a warning will be displayed on the chart instead of the screener table that if the market is open, you must wait for the screener to load (after the first price change on the current chart), or if the highest timeframe in the screener is 1 day, you will be prompted to change the timeframe on the current chart to 1 week, if the screener requests data for the timeframe of 1 week, you will be prompted to change the timeframe on the current chart to 1 month, or switch to another symbol on the current chart for which the market is open (for example: BINANCE:BTCUSDT), or disable the warning in the field "SYMBOL LIST > Do not display screener if market is close". The number of the last columns with the color of the AO indicator that will be displayed in the screener table for each timeframe is specified in the indicator settings in the "AWESOME OSCILLATOR > Number of columns" field. For each timeframe, the direction of the trend between the price of the highest and lowest bars in the specified range of bars from the last bar is displayed — ↑ if the trend is up (the highest bar is to the right of the lowest), or ↓ if the trend is down (the lowest bar is to the right of the highest). If there is a divergence on the AO indicator in the specified interval, the symbol ∇ is also displayed. The average volume value is also calculated in the specified interval using a simple moving average (SMA). The number of bars is set in the indicator settings in the "INTERVAL FOR HIGHEST AND LOWEST BARS > Bars count" field. In the indicator settings in the "STYLE" field you can change the position of the screener table relative to the chart window, the background color, the color and size of the text. *** Скринер на основе стратегии Profitunity Билла Вильямса для нескольких таймфреймов (максимум 5, включая таймфрейм графика) и настраиваемого списка символов. Скринер анализирует индикаторы Alligator и Awesome Oscillator, Дивергентные бары и бары с высоким объемом. Максимально допустимое количество запросов (символы и таймфреймы) ограничено 40 запросами, например, для 10 символов по 4 запроса разных таймфреймов. Поэтому в индикаторе автоматически ограничивается количество отображаемых символов в зависимости от количества таймфреймов для каждого символа, если символов больше чем отображено в таблице скринера, то слева от символов отображаются порядковые номера, в таком случае можно отобразить следующую группу символов, увеличив значение на 1 в настройках индикатора поле "Show tickers from", если включено поле "Group", или указать номер символа на 1 больше, чем последний символ в таблице скринера. 👀 Когда применяется фильтрация по таймфрейму, в таблице скринера отображаются только столбцы тех таймфреймов, для которых выбрано значение фильтрации, что позволяет отображать большее количество символов. Для каждого таймфрейма в настройках индикатора в поле "TIMEFRAMES > Prev" можно включить отображение данных для предыдущего бара относительно последнего (текущего), если для запрашиваемого символа рынок открыт. В поле "TIMEFRAMES > Y" можно включить фильтрацию, в зависимости от расположения последних пяти баров относительно линий индикатора Alligator, которые обозначаются специальными символами в таблице скринера: ⬆️ — если Alligator открыт вверх (Lips > Teeth > Jaw) и ни один из баров не закрыт ниже линии Lips; ↗️ — если один из баров, кроме предпоследнего, закрыт ниже Lips, или два бара, кроме последнего, закрыты ниже Lips, или Alligator открыт вверх только ниже четырех баров, но ни один из баров не закрыт ниже Lips; ⬇️ — если Alligator открыт вниз (Lips < Teeth < Jaw), но ни один из баров не закрыт выше Lips; ↘️ — если один из баров, кроме предпоследнего, закрыт выше Lips, или два бара, кроме последнего, закрыты выше Lips, или Alligator открыт вниз только выше четырех баров, но ни один из баров не закрыт выше Lips; ➡️ — в остальных случаях, в то числе когда линии Alligator пересекаются и один из баров закрыт за линией Lips или два бара пересекают одну из линий Alligator. В поле "TIMEFRAMES > Show bar change value for TF" можно добавить справа от выбранного столбца таймфрейма столбец с процентным изменением между ценой закрытия последнего бара (текущего) и ценой закрытия предыдущего бара ((close – previous close) / previous close * 100). В зависимости от величины процента будет меняться цвет фона ячейки таблицы скринера: темно-красный, если <= -3%; красный, если <= -2%, светло-красный, если <= -0.5%; темно-зеленый, если >= 3%; зеленый, если >= 2%; светло-зеленый, если >= 0.5%. Для каждого таймфрейма в таблице скринера отображается символ последнего (текущего) бара, в зависимости от цены закрытия относительно середины бара ((high + low) / 2) и расположения относительно линий индикатора Alligator: ⎾ — цена закрытия бара выше его середины; ⎿ — цена закрытия бара ниже его середины; ├ — цена закрытия бара равна его середине; 🟢 — Бычий Дивергентный бар, т.е. цена закрытия бара выше его середины, максимум бара ниже всех линий Alligator, минимум бара ниже минимума предыдущего бара; 🔴 — Медвежий Дивергентный бар, т.е. цена закрытия бара ниже его середины, минимум бара выше всех линий Alligator, максимум бара выше максимума предыдущего бара. При включении фильтрации в поле "TIMEFRAMES > Filtering by Divergent bar" данные в ячейках таблицы скринера будут отображаться только для тех таймфреймов, где есть Дивергентный бар. Также отображается сигнал высокого объема бара — 📶/📶², если объем бара больше чем на 40%/70% среднего значения объема, рассчитанного с помощью простой скользящей средней (SMA) в интервале 140 баров от последнего бара. В настройках индикатора в поле "SYMBOL LIST" каждый тикер (например: OANDA:SPX500USD) должен быть на отдельной строке. Если рынок закрыт, то данные для запрашиваемых символов будут ограничены временем последнего (текущего) бара на графике, например, если текущий символ торговался последний день вчера, а запрашиваемый символ торгуется сегодня, при запросе данных для часового таймфрейма, последний бар будет за вчерашний день, если таймфрейм текущего графика не выше 1 дня. Поэтому по умолчанию на графике будет отображаться предупреждение вместо таблицы скринера о том, что если рынок открыт, то необходимо дождаться загрузки скринера (после первого изменения цены на текущем графике), или если в скринере самый высокий таймфрейм 1 день, то будет предложено изменить на текущем графике таймфрейм на 1 неделю, если в скринере запрашиваются данные для таймфрейма 1 неделя, то будет предложено изменить на текущем графике таймфрейм на 1 месяц, или же переключиться на другой символ на текущем графике, для которого рынок открыт (например: BINANCE:BTCUSDT), или отключить предупреждение в поле "SYMBOL LIST > Do not display screener if market is close". Количество последних столбцов с цветом индикатора AO, которые будут отображены в таблице скринера для каждого таймфрейма, указывается в настройках индикатора в поле "AWESOME OSCILLATOR > Number of columns". Для каждого таймфрейма отображается направление тренда между ценой самого высокого и самого низкого баров в указанном интервале баров от последнего бара — ↑, если тренд направлен вверх (самый высокий бар справа от самого низкого), или ↓, если тренд направлен вниз (самый низкий бар справа от самого высокого). Если есть дивергенция на индикаторе AO в указанном интервале, то также отображается символ — ∇. В указанном интервале также рассчитывается среднее значение объема с помощью простой скользящей средней (SMA). Количество баров устанавливается в настройках индикатора в поле "INTERVAL FOR HIGHEST AND LOWEST BARS > Bars count". В настройках индикатора в поле "STYLE" можно изменить положение таблицы скринера относительно окна графика, цвет фона, цвет и размер текста.
Pine Script®指标
由grigorykov提供
Percentage price changeThis indicator marks bars whose values increase or decrease by an amount greater than or equal to the value of the specified parameter as a percentage. Bars that meet the condition are marked with labels, boxes and colors. In addition to the standard method of calculating the percentage change at the closing price of the current and previous bars, the indicator allows you to choose non-standard calculation methods (at the prices of opening and closing the current bar, as well as at the prices of the maximum at the minimum of the current bar). You can choose to display the percentage changes of individual bars as well as a series of bars. You can select the number of bars in a series of bars. You can also apply filters by the direction of the bars in the series or by the percentage of individual bars in the series. It is important to remember that in version 5 of Pine Script™, the maximum possible number of labels and the maximum possible number of boxes cannot exceed 500! There are several main parameters that can be changed in section PARAMETERS FOR CALCULATION: 1. 'Bars count' - The number of bars for which the percentage rise or fall is calculated. 2. ‘Percentage change’ - sets the price change as a percentage. Bars with a price range above or equal to the specified value will be marked on the chart. 3. ‘First and second points of calculation’ - the first and second points for calculating the percentage change. Here you can set several different values for the calculation: - 'Cl.pr., Close' - Closing price of the previous bar and closing price of the current bar (or a series of bars) (these values are used for the standard calculation of the percentage change on the chart). - 'Open, Close' - Opening and closing prices of the current bar (or a series of bars). - 'High|Low' - Highest and lowest price of the current bar (or a series of bars). - 'Cl.pr.|High|Low' - Highest or lowest price of the current bar (or a series of bars) (depending on whether the bar is going up or down) or closing price of the previous bar for first point (one of these values is automatically selected, which gives a larger result, depending on whether there is a gap between these values). Highest or lowest price of the current bar for second point. In the LIMITS section, you can set the following parameters. 1. ‘Only for the last bar’ - If this option is selected, the indicator will be applied only for the last bar (or series of bars). 2. 'Only bars in one direction' - A condition that takes into account sequences from the selected number of bars going in only one direction. If at least one bar has a different direction from the other bars, then such a sequence will not be taken into account. This only works if the 'Bars count' is > 1. 3. "Cut off higher values" - This field cuts off higher values. Bars with a price range above or equal to the specified value will not be marked on the chart. This can be used in some cases to make the chart less loaded with data and more visual. Of course, you can also use this option however you want. 4. ‘Min percent in series of bars’ - If the value 'Number of bars' is > 1, then a series of bars is taken into account, in which the percentage change of individual bars is greater than or equal to the set value. In the DATE RANGE section, you can set the limits of the time and date range in which the calculation will be performed. In some cases, this can be used in order not to exceed the limit on the number of labels or boxes, which cannot exceed 500. Of course, you can also use this option however you want. By default, the date range is unlimited. 'Timezone offset, hours' - It is used only for the correct display of the limits of the date range in the parameter table. In the PRICE INCREASE LABELS and PRICE REDUCTION LABELS section, you can define the design of labels bars and boxes, such as colors, shapes, sizes, and location. You can set the colors of the bars separately on the Style tab. On the Style tab, you can also turn on/off the display of frames, labels and color markings of bars. The PARAMETER TABLE section is designed to adjust the display of the table for a more visual display of the selected values of all parameters on the Arguments tab. Depending on which values have been set and which parameters have been enabled or disabled, the table will change its appearance, display or hide some rows. A single line 'Total found' will be displayed all the time. It shows the count of bars that meet the condition and count of labels or boxes used in the diagram. Since the bars are labeled with labels or boxes, their number cannot exceed 500 for Pine script version 5. 1. 'Pos.' - sets the main position of the table on the screen. 2. 'X off.', 'Y off.' - You can set the offset of the table along the X and Y axes. This option can be useful to avoid overlapping multiple tables if you want to use two or more instances of this indicator on your chart. The minimum value is -30, the maximum is 30. Positive values shift the table to the right on the X axis and up on the Y axis. Negative values shift the table to the left on the X axis and down on the Y axis. 3. 'Font color' - The font color in the table. 'Warn. font color', 'Warn. backgr. color' - The font and background colors in the 'Total found' row in the table. If the number of labels or boxes exceeds 500, the font and background will be colored in these colors. 4. ‘Font size’ – Sets the font size in the table. 5. 'Show hours and minutes in date/time range' - changes the date and time format of time range from {yyyy.MM.dd HH:mm} to {yyyy.MM.dd}. 6. 'View all params' - used to display all parameters, even those duplicated in the main line of the indicator. 7. ‘Title’ – If desired, you can make a header for the table. The last row of the table shows the number of bars found that meet the conditions. Since these bars are marked with labels (in the case of one bar) or boxes (in the case of series of bars), the limit that can be marked on the chart is 500. Exceeding this value will be displayed in the table and additionally highlighted in red font. This will signal that not all bars found are displayed on the chart. On the Style tab, you can turn the table display on/off.
Pine Script®指标
由Bondar提供
3
CandleAnalysisLibrary "CandleAnalysis" A collection of frequently used candle analysis functions in my scripts. isBullish(barsBack)   Checks if a specific bar is bullish.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar is bullish, otherwise returns false. isBearish(barsBack)   Checks if a specific bar is bearish.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar is bearish, otherwise returns false. isBE(barsBack)   Checks if a specific bar is break even.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar is break even, otherwise returns false. getBodySize(barsBack, inPriceChg)   Calculates a specific candle's body size.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).      inPriceChg (bool) : (bool) True to return the body size as a price change value. The default is false (in points).   Returns: The candle's body size in points. getTopWickSize(barsBack, inPriceChg)   Calculates a specific candle's top wick size.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).      inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).   Returns: The candle's top wick size in points. getBottomWickSize(barsBack, inPriceChg)   Calculates a specific candle's bottom wick size.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).      inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).   Returns: The candle's bottom wick size in points. getBodyPercent(barsBack)   Calculates a specific candle's body size as a percentage of its entire size including its wicks.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: The candle's body size percentage. isHammer(fib, bullish, barsBack)   Checks if a specific bar is a hammer candle based on a given fibonacci level.   Parameters:      fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.      bullish (bool) : (bool) True if the candle must to be green. The default is false.      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar matches the requirements of a hammer candle, otherwise returns false. isShootingStar(fib, bearish, barsBack)   Checks if a specific bar is a shooting star candle based on a given fibonacci level.   Parameters:      fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.      bearish (bool) : (bool) True if the candle must to be red. The default is false.      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar matches the requirements of a shooting star candle, otherwise returns false. isDoji(wickSize, bodySize, barsBack)   Checks if a specific bar is a doji candle based on a given wick and body size.   Parameters:      wickSize (float) : (float) The maximum top wick size compared to the bottom and vice versa. The default is 1.5.      bodySize (float) : (bool) The maximum body size as a percentage compared to the entire candle size. The default is 5.      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar matches the requirements of a doji candle. isBullishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)   Checks if a specific bar is a bullish engulfing candle.   Parameters:      gapTolerance (int)      rejectionWickSize (int) : (int) The maximum top wick size compared to the body as a percentage. The default is 10.      engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar matches the requirements of a bullish engulfing candle. isBearishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)   Checks if a specific bar is a bearish engulfing candle.   Parameters:      gapTolerance (int)      rejectionWickSize (int) : (int) The maximum bottom wick size compared to the body as a percentage. The default is 10.      engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar matches the requirements of a bearish engulfing candle.
Pine Script®库
由ActiveQuants提供
MarcosLibraryLibrary "MarcosLibrary" A colection of frequently used functions in my scripts. bullFibRet(priceLow, priceHigh, fibLevel)   Calculates a bullish fibonacci retracement value.   Parameters:      priceLow (float) : (float) The lowest price point.      priceHigh (float) : (float) The highest price point.      fibLevel (float) : (float) The fibonacci level to calculate.   Returns: The fibonacci value of the given retracement level. bearFibRet(priceLow, priceHigh, fibLevel)   Calculates a bearish fibonacci retracement value.   Parameters:      priceLow (float) : (float) The lowest price point.      priceHigh (float) : (float) The highest price point.      fibLevel (float) : (float) The fibonacci level to calculate.   Returns: The fibonacci value of the given retracement level. bullFibExt(priceLow, priceHigh, thirdPivot, fibLevel)   Calculates a bullish fibonacci extension value.   Parameters:      priceLow (float) : (float) The lowest price point.      priceHigh (float) : (float) The highest price point.      thirdPivot (float) : (float) The third price point.      fibLevel (float) : (float) The fibonacci level to calculate.   Returns: The fibonacci value of the given extension level. bearFibExt(priceLow, priceHigh, thirdPivot, fibLevel)   Calculates a bearish fibonacci extension value.   Parameters:      priceLow (float) : (float) The lowest price point.      priceHigh (float) : (float) The highest price point.      thirdPivot (float) : (float) The third price point.      fibLevel (float) : (float) The fibonacci level to calculate.   Returns: The fibonacci value of the given extension level. isBullish(barsBack)   Checks if a specific bar is bullish.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar is bullish, otherwise returns false. isBearish(barsBack)   Checks if a specific bar is bearish.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar is bearish, otherwise returns false. isBE(barsBack)   Checks if a specific bar is break even.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar is break even, otherwise returns false. getBodySize(barsBack, inPriceChg)   Calculates a specific candle's body size.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).      inPriceChg (bool) : (bool) True to return the body size as a price change value. The default is false (in points).   Returns: The candle's body size in points. getTopWickSize(barsBack, inPriceChg)   Calculates a specific candle's top wick size.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).      inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).   Returns: The candle's top wick size in points. getBottomWickSize(barsBack, inPriceChg)   Calculates a specific candle's bottom wick size.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).      inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).   Returns: The candle's bottom wick size in points. getBodyPercent(barsBack)   Calculates a specific candle's body size as a percentage of its entire size including its wicks.   Parameters:      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: The candle's body size percentage. isHammer(fib, bullish, barsBack)   Checks if a specific bar is a hammer candle based on a given fibonacci level.   Parameters:      fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.      bullish (bool) : (bool) True if the candle must to be green. The default is false.      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar matches the requirements of a hammer candle, otherwise returns false. isShootingStar(fib, bearish, barsBack)   Checks if a specific bar is a shooting star candle based on a given fibonacci level.   Parameters:      fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.      bearish (bool) : (bool) True if the candle must to be red. The default is false.      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar matches the requirements of a shooting star candle, otherwise returns false. isDoji(wickSize, bodySize, barsBack)   Checks if a specific bar is a doji candle based on a given wick and body size.   Parameters:      wickSize (float) : (float) The maximum top wick size compared to the bottom and vice versa. The default is 1.5.      bodySize (float) : (bool) The maximum body size as a percentage compared to the entire candle size. The default is 5.      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar matches the requirements of a doji candle. isBullishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)   Checks if a specific bar is a bullish engulfing candle.   Parameters:      gapTolerance (int)      rejectionWickSize (int) : (int) The maximum top wick size compared to the body as a percentage. The default is 10.      engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar matches the requirements of a bullish engulfing candle. isBearishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)   Checks if a specific bar is a bearish engulfing candle.   Parameters:      gapTolerance (int)      rejectionWickSize (int) : (int) The maximum bottom wick size compared to the body as a percentage. The default is 10.      engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.      barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).   Returns: True if the bar matches the requirements of a bearish engulfing candle.
Pine Script®库
由ActiveQuants提供
Higher-timeframe requests█   OVERVIEW This publication focuses on enhancing awareness of the best practices for accessing higher-timeframe (HTF) data via the request.security() function. Some "traditional" approaches, such as what we explored in our previous `security()` revisited publication, have shown limitations in their ability to retrieve non-repainting HTF data. The fundamental technique outlined in this script is currently the most effective in preventing repainting when requesting data from a higher timeframe. For detailed information about why it works, see this section in the Pine Script™ User Manual . █   CONCEPTS Understanding repainting Repainting is a behavior that occurs when a script's calculations or outputs behave differently after restarting it. There are several types of repainting behavior, not all of which are inherently useless or misleading. The most prevalent form of repainting occurs when a script's calculations or outputs exhibit different behaviors on historical and realtime bars. When a script calculates across historical data, it only needs to execute once per bar, as those values are confirmed and not subject to change. After each historical execution, the script commits the states of its calculations for later access. On a realtime, unconfirmed bar, values are fluid . They are subject to change on each new tick from the data provider until the bar closes. A script's code can execute on each tick in a realtime bar, meaning its calculations and outputs are subject to realtime fluctuations, just like the underlying data it uses. Each time a script executes on an unconfirmed bar, it first reverts applicable values to their last committed states, a process referred to as rollback . It only commits the new values from a realtime bar after the bar closes. See the User Manual's Execution model page to learn more. In essence, a script can repaint when it calculates on realtime bars due to fluctuations before a bar's confirmation, which it cannot reproduce on historical data. A common strategy to avoid repainting when necessary involves forcing only confirmed values on realtime bars, which remain unchanged until each bar's conclusion. Repainting in higher-timeframe (HTF) requests When working with a script that retrieves data from higher timeframes with request.security() , it's crucial to understand the differences in how such requests behave on historical and realtime bars . The request.security() function executes all code required by its `expression` argument using data from the specified context (symbol, timeframe, or modifiers) rather than on the chart's data. As when executing code in the chart's context, request.security() only returns new historical values when a bar closes in the requested context. However, the values it returns on realtime HTF bars can also update before confirmation, akin to the rollback and recalculation process that scripts perform in the chart's context on the open bar. Similar to how scripts operate in the chart's context, request.security() only confirms new values after a realtime bar closes in its specified context. Once a script's execution cycle restarts, what were previously realtime bars become historical bars, meaning the request.security() call will only return confirmed values from the HTF on those bars. Therefore, if the requested data fluctuates across an open HTF bar, the script will repaint those values after it restarts. This behavior is not a bug; it's simply the default behavior of request.security() . In some cases, having the latest information from an unconfirmed HTF bar is precisely what a script needs. However, in many other cases, traders will require confirmed, stable values that do not fluctuate across an open HTF bar. Below, we explain the most reliable approach to achieve such a result. Achieving consistent timing on all bars One can retrieve non-fluctuating values with consistent timing across historical and realtime feeds by exclusively using request.security() to fetch the data from confirmed HTF bars. The best way to achieve this result is offsetting the `expression` argument by at least one bar (e.g., `close [1 ]`) and using barmerge.lookahead_on as the `lookahead` argument. We discourage the use of barmerge.lookahead_on alone since it prompts the function to look toward future values of HTF bars across historical data, which is heavily misleading. However, when paired with a requested `expression` that includes a one-bar historical offset, the "future" data the function retrieves is not from the future. Instead, it represents the last confirmed bar's values at the start of each HTF bar, thus preventing the results on realtime bars from fluctuating before confirmation from the timeframe. For example, this line of code uses a request.security() call with barmerge.lookahead_on to request the close price from the "1D" timeframe, offset by one bar with the history-referencing operator [ ] . This line will return the daily price with consistent timing across all bars: float htfClose = request.security(syminfo.tickerid, "1D", close , lookahead = barmerge.lookahead_on) Note that:  • This technique only works as intended for higher-timeframe requests .  • When designing a script to work specifically with HTFs, we recommend including conditions to prevent request.security() from accessing timeframes equal to or lower than the chart's timeframe, especially if you intend to publish it. In this script, we included an if structure that raises a runtime error when the requested timeframe is too small.  • A necessary trade-off with this approach is that the script must wait for an HTF bar's confirmation to retrieve new data on realtime bars, thus delaying its availability until the open of the subsequent HTF bar. The time elapsed during such a delay varies with each market, but it's typically relatively small. 👉 Failing to offset the function's `expression` argument while using barmerge.lookahead_on will produce historical results with lookahead bias , as it will look to the future states of historical HTF bars, retrieving values before the times at which they're available in the feed. See the `lookahead` and Future leak with `request.security()` sections in the Pine Script™ User Manual for more information. Evolving practices The fundamental technique outlined in this publication is currently the only reliable approach to requesting non-repainting HTF data with request.security() . It is the superior approach because it avoids the pitfalls of other methods, such as the one introduced in the `security()` revisited publication. That publication proposed using a custom `f_security()` function, which applied offsets to the `expression` and the requested result based on historical and realtime bar states. At that time, we explored techniques that didn't carry the risk of lookahead bias if misused (i.e., removing the historical offset on the `expression` while using lookahead), as requests that look ahead to the future on historical bars exhibit dangerously misleading behavior. Despite these efforts, we've unfortunately found that the bar state method employed by `f_security()` can produce inaccurate results with inconsistent timing in some scenarios, undermining its credibility as a universal non-repainting technique. As such, we've deprecated that approach, and the Pine Script™ User Manual no longer recommends it. █   METHOD VARIANTS In this script, all non-repainting requests employ the same underlying technique to avoid repainting. However, we've applied variants to cater to specific use cases, as outlined below: Variant 1 Variant 1, which the script displays using a lime plot, demonstrates a non-repainting HTF request in its simplest form, aligning with the concept explained in the "Achieving consistent timing" section above. It uses barmerge.lookahead_on and offsets the `expression` argument in request.security() by one bar to retrieve the value from the last confirmed HTF bar. For detailed information about why this works, see the Avoiding Repainting section of the User Manual's Other timeframes and data page. Variant 2 Variant 2 ( fuchsia ) introduces a custom function, `htfSecurity()`, which wraps the request.security() function to facilitate convenient repainting control. By specifying a value for its `repaint` parameter, users can determine whether to allow repainting HTF data. When the `repaint` value is `false`, the function applies lookahead and a one-bar offset to request the last confirmed value from the specified `timeframe`. When the value is `true`, the function requests the `expression` using the default behavior of request.security() , meaning the results can fluctuate across chart bars within realtime HTF bars and repaint when the script restarts. Note that:  • This function exclusively handles HTF requests. If the requested timeframe is not higher than the chart's, it will raise a runtime error .  • We prefer this approach since it provides optional repainting control. Sometimes, a script's calculations need to respond immediately to realtime HTF changes, which `repaint = true` allows. In other cases, such as when issuing alerts, triggering strategy commands, and more, one will typically need stable values that do not repaint, in which case `repaint = false` will produce the desired behavior. Variant 3 Variant 3 ( white ) builds upon the same fundamental non-repainting approach used by the first two. The difference in this variant is that it applies repainting control to tuples , which one cannot pass as the `expression` argument in our `htfSecurity()` function. Tuples are handy for consolidating `request.*()` calls when a script requires several values from the same context, as one can request a single tuple from the context rather than executing multiple separate request.security() calls. This variant applies the internal logic of our `htfSecurity()` function in the script's global scope to request a tuple containing open and `srcInput` values from a higher timeframe with repainting control. Historically, Pine Script™ did not allow the history-referencing operator [ ] when requesting tuples unless the tuple came from a function call, which limited this technique. However, updates to Pine over time have lifted this restriction, allowing us to pass tuples with historical offsets directly as the `expression` in request.security() . By offsetting all items in a tuple `expression` by one bar and using barmerge.lookahead_on , we effectively retrieve a tuple of stable, non-repainting HTF values. Since we cannot encapsulate this method within the `htfSecurity()` function and must execute the calculations in the global scope, the script's "Repainting" input directly controls the global `offset` and `lookahead` values to ensure it behaves as intended. Variant 4 (Control) Variant 4, which the script displays as a translucent orange plot, uses a default request.security() call, providing a reference point to compare the difference between a repainting request and the non-repainting variants outlined above. Whenever the script restarts its execution cycle, realtime bars become historical bars, and the request.security() call here will repaint the results on those bars. █   Inputs Repainting The "Repainting" input (`repaintInput` variable) controls whether Variant 2 and Variant 3 are allowed to use fluctuating values from an unconfirmed HTF bar. If its value is `false` (default), these requests will only retrieve stable values from the last confirmed HTF bar. Source The "Source" input (`srcInput` variable) determines the series the script will use in the `expression` for all HTF data requests. Its default value is close . HTF Selection This script features two ways to specify the higher timeframe for all its data requests, which users can control with the "HTF Selection" input (`tfTypeInput` variable):  1) If its value is "Fixed TF", the script uses the timeframe value specified by the "Fixed Higher Timeframe" input (`fixedTfInput` variable). The script will raise a runtime error if the selected timeframe is not larger than the chart's.  2) If the input's value is "Multiple of chart TF", the script multiplies the value of the "Timeframe Multiple" input (`tfMultInput` variable) by the chart's timeframe.in_seconds() value, then converts the result to a valid timeframe string via timeframe.from_seconds() . Timeframe Display This script features the option to display an "information box", i.e., a single-cell table that shows the higher timeframe the script is currently using. Users can toggle the display and determine the table's size, location, and color scheme via the inputs in the "Timeframe Display" group. █   Outputs This script produces the following outputs:  • It plots the results from all four of the above variants for visual comparison.  • It highlights the chart's background gray whenever a new bar starts on the higher timeframe, signifying when confirmations occur in the requested context.  • To demarcate which bars the script considers historical or realtime bars, it plots squares with contrasting colors corresponding to bar states at the bottom of the chart pane.  • It displays the higher timeframe string in a single-cell table with a user-specified size, location, and color scheme. Look first. Then leap.
Pine Script®指标
由PineCoders提供
14
ULTIMATE ORDER FLOW SYSTEM🔥 ULTIMATE ORDER FLOW SYSTEM Overview This comprehensive order flow analysis tool combines **Volume Profile**, **Cumulative Delta**, and **Large Order Detection** to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react. 📊 Core Components & Methodology 🔥 ULTIMATE ORDER FLOW SYSTEM Overview This comprehensive order flow analysis tool combines Volume Profile, Cumulative Delta, and Large Order Detection to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react. ________________________________________ 📊 Core Components & Methodology 1. Volume Profile Analysis The script constructs a horizontal volume profile by: • Dividing the price range into configurable rows (default: 20) • Accumulating volume at each price level over a lookback period (default: 50 bars) • Separating buy volume (green bars close > open) from sell volume (red bars) • Identifying three critical levels: o POC (Point of Control): Price level with highest traded volume - acts as a strong magnet o VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone o HVN (High Volume Nodes): Resistance zones where institutions accumulated positions o LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance. ________________________________________ 2. Cumulative Delta (Order Flow) Tracks the running total of buying vs selling pressure: • Bar Delta: Difference between buy and sell volume per candle • Cumulative Delta: Sum of all bar deltas - shows net directional pressure • Delta Moving Average: Smoothed delta (20-period) to identify trend • Delta Divergences: o Bullish: Price makes lower low, but delta makes higher low (absorption at bottom) o Bearish: Price makes higher high, but delta makes lower high (exhaustion at top) How It Works: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations. ________________________________________ 3. Large Order Detection Identifies institutional-sized orders in real-time: • Compares current bar volume to 20-period moving average • Flags orders exceeding 2.5x average volume (configurable multiplier) • Distinguishes bullish (green circles below) vs bearish (red circles above) large orders Rationale: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals. ________________________________________ 🎯 Trading Signal Logic Combined Setup Criteria The script generates SHORT and LONG signals when multiple conditions align: SHORT Signal Requirements: 1. Price reaches an HVN resistance zone (within 0.2%) 2. Large sell order detected (volume spike + red candle) 3. Cumulative delta is bearish OR bearish divergence present 4. 10-bar cooldown between signals (prevents overtrading) LONG Signal Requirements: 1. Price reaches an HVN support zone 2. Large buy order detected (volume spike + green candle) 3. Cumulative delta is bullish OR bullish divergence present 4. 10-bar cooldown enforced ________________________________________ 🔧 Customization Options Setting - Purpose - Recommendation Volume Profile Rows - Granularity of level detection - 20 (balanced) Lookback Period - Historical data analyzed - 50 bars (intraday), 200 (swing) Large Order Multiplier - Sensitivity to volume spikes - 2.5x (standard), 3.5x (conservative) HVN Threshold - Resistance zone detection - 1.3 (default) LVN Threshold - Target zone identification - 0.6 (default) Divergence Lookback - Pivot detection period - 5 bars (responsive) ________________________________________ 📈 Dashboard Indicators The real-time panel displays: • POC: Current Point of Control price • Location: Whether price is at HVN resistance • Orders: Current large buy/sell activity • Cumulative Δ: Net order flow value + trend direction • Divergence: Active bullish/bearish divergences • Bar Strength: % of candle volume that's directional (>65% = strong) • SETUP: Current trade signal (LONG/SHORT/WAIT) ________________________________________ 🎨 Visual System • Yellow POC Line: Highest volume level - primary pivot • Blue Value Area Box: Fair value zone (VAH to VAL) • Red HVN Zones: Resistance/support from institutional accumulation • Green LVN Zones: Low-liquidity targets for quick moves • Volume Bars: Green (buy pressure) vs Red (sell pressure) distribution • Triangles: LONG (green up) and SHORT (red down) entry signals • Diamonds: Divergence warnings (cyan=bullish, fuchsia=bearish) ________________________________________ 💡 How This Script Is Unique Unlike standalone volume profile or delta indicators, this script: 1. Synthesizes three complementary methods - volume structure, order flow momentum, and liquidity detection 2. Requires multi-factor confirmation - signals only trigger when price, volume, and delta align at key zones 3. Adapts to market regime - delta filters ensure you're trading with the dominant order flow direction 4. Provides context, not just signals - the dashboard helps you understand why a setup is forming ________________________________________ ⚙️ Best Practices Timeframes: • 5-15 min: Scalping (use 30-50 bar lookback) • 1-4 hour: Swing trading (use 100-200 bar lookback) Risk Management: • Enter on signal candle close • Stop loss: Beyond nearest HVN/LVN zone • Target 1: Next LVN level • Target 2: Opposite value area boundary Filters: • Avoid signals during major news events • Require bar delta strength >65% for aggressive entries • Wait for delta MA cross confirmation in ranging markets ________________________________________ 🚨 Alerts Available • Long Setup Trigger • Short Setup Trigger • Bullish/Bearish Divergence Detection • Large Buy/Sell Order Execution ________________________________________ 📚 Educational Context This methodology is based on principles used by professional order flow traders: • Market Profile Theory: Volume distribution reveals fair value • Tape Reading: Large orders show institutional intent • Auction Theory: Price seeks areas of liquidity imbalance (LVN zones) The script automates pattern recognition that discretionary traders spend years learning to identify manually. ________________________________________ ⚠️ Disclaimer This indicator is a trading tool, not a trading system. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results. ________________________________________ Version: 6 (Pine Script) Type: Overlay + Separate Pane (Delta Panel) Resource Usage: Moderate (500 bars history, 500 lines/boxes) ________________________________________ For questions or support, please comment below. If you find this script valuable, please boost and favorite! 🚀 1. Volume Profile Analysis The script constructs a horizontal volume profile by: - Dividing the price range into configurable rows (default: 20) - Accumulating volume at each price level over a lookback period (default: 50 bars) - Separating buy volume (green bars close > open) from sell volume (red bars) - Identifying three critical levels: - POC (Point of Control): Price level with highest traded volume - acts as a strong magnet - VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone - HVN (High Volume Nodes): Resistance zones where institutions accumulated positions - LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance. --- 2. Cumulative Delta (Order Flow) Tracks the running total of buying vs selling pressure: - **Bar Delta**: Difference between buy and sell volume per candle - **Cumulative Delta**: Sum of all bar deltas - shows net directional pressure - **Delta Moving Average**: Smoothed delta (20-period) to identify trend - **Delta Divergences**: - **Bullish**: Price makes lower low, but delta makes higher low (absorption at bottom) - **Bearish**: Price makes higher high, but delta makes lower high (exhaustion at top) **How It Works**: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations. --- ### 3. **Large Order Detection** Identifies **institutional-sized orders** in real-time: - Compares current bar volume to 20-period moving average - Flags orders exceeding 2.5x average volume (configurable multiplier) - Distinguishes bullish (green circles below) vs bearish (red circles above) large orders **Rationale**: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals. --- ## 🎯 Trading Signal Logic ### Combined Setup Criteria The script generates **SHORT** and **LONG** signals when multiple conditions align: **SHORT Signal Requirements:** 1. Price reaches an HVN resistance zone (within 0.2%) 2. Large sell order detected (volume spike + red candle) 3. Cumulative delta is bearish OR bearish divergence present 4. 10-bar cooldown between signals (prevents overtrading) **LONG Signal Requirements:** 1. Price reaches an HVN support zone 2. Large buy order detected (volume spike + green candle) 3. Cumulative delta is bullish OR bullish divergence present 4. 10-bar cooldown enforced --- ## 🔧 Customization Options | Setting | Purpose | Recommendation | |---------|---------|----------------| | **Volume Profile Rows** | Granularity of level detection | 20 (balanced) | | **Lookback Period** | Historical data analyzed | 50 bars (intraday), 200 (swing) | | **Large Order Multiplier** | Sensitivity to volume spikes | 2.5x (standard), 3.5x (conservative) | | **HVN Threshold** | Resistance zone detection | 1.3 (default) | | **LVN Threshold** | Target zone identification | 0.6 (default) | | **Divergence Lookback** | Pivot detection period | 5 bars (responsive) | --- ## 📈 Dashboard Indicators The real-time panel displays: - **POC**: Current Point of Control price - **Location**: Whether price is at HVN resistance - **Orders**: Current large buy/sell activity - **Cumulative Δ**: Net order flow value + trend direction - **Divergence**: Active bullish/bearish divergences - **Bar Strength**: % of candle volume that's directional (>65% = strong) - **SETUP**: Current trade signal (LONG/SHORT/WAIT) --- ## 🎨 Visual System - **Yellow POC Line**: Highest volume level - primary pivot - **Blue Value Area Box**: Fair value zone (VAH to VAL) - **Red HVN Zones**: Resistance/support from institutional accumulation - **Green LVN Zones**: Low-liquidity targets for quick moves - **Volume Bars**: Green (buy pressure) vs Red (sell pressure) distribution - **Triangles**: LONG (green up) and SHORT (red down) entry signals - **Diamonds**: Divergence warnings (cyan=bullish, fuchsia=bearish) --- ## 💡 How This Script Is Unique Unlike standalone volume profile or delta indicators, this script: 1. **Synthesizes three complementary methods** - volume structure, order flow momentum, and liquidity detection 2. **Requires multi-factor confirmation** - signals only trigger when price, volume, and delta align at key zones 3. **Adapts to market regime** - delta filters ensure you're trading with the dominant order flow direction 4. **Provides context, not just signals** - the dashboard helps you understand *why* a setup is forming --- ## ⚙️ Best Practices **Timeframes:** - 5-15 min: Scalping (use 30-50 bar lookback) - 1-4 hour: Swing trading (use 100-200 bar lookback) **Risk Management:** - Enter on signal candle close - Stop loss: Beyond nearest HVN/LVN zone - Target 1: Next LVN level - Target 2: Opposite value area boundary **Filters:** - Avoid signals during major news events - Require bar delta strength >65% for aggressive entries - Wait for delta MA cross confirmation in ranging markets --- ## 🚨 Alerts Available - Long Setup Trigger - Short Setup Trigger - Bullish/Bearish Divergence Detection - Large Buy/Sell Order Execution --- ## 📚 Educational Context This methodology is based on principles used by professional order flow traders: - **Market Profile Theory**: Volume distribution reveals fair value - **Tape Reading**: Large orders show institutional intent - **Auction Theory**: Price seeks areas of liquidity imbalance (LVN zones) The script automates pattern recognition that discretionary traders spend years learning to identify manually. --- ## ⚠️ Disclaimer This indicator is a **trading tool, not a trading system**. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results. --- **Version**: 6 (Pine Script) **Type**: Overlay + Separate Pane (Delta Panel) **Resource Usage**: Moderate (500 bars history, 500 lines/boxes) --- *For questions or support, please comment below. If you find this script valuable, please boost and favorite!* 🚀
Pine Script®指标
由harshivsymposium提供
Mars Signals - Ultimate Institutional Suite v3.0(Joker)Comprehensive Trading Manual Mars Signals – Ultimate Institutional Suite v3.0 (Joker) ## Chapter 1 – Philosophy & System Architecture This script is not a simple “buy/sell” indicator. Mars Signals – UIS v3.0 (Joker) is designed as an institutional-style analytical assistant that layers several methodologies into a single, coherent framework. The system is built on four core pillars: 1. Smart Money Concepts (SMC) - Detection of Order Blocks (professional demand/supply zones). - Detection of Fair Value Gaps (FVGs) (price imbalances). 2. Smart DCA Strategy - Combination of RSI and Bollinger Bands - Identifies statistically discounted zones for scaling into spot positions or exiting shorts. 3. Volume Profile (Visible Range Simulation) - Distribution of volume by price, not by time. - Identification of POC (Point of Control) and high-/low-volume areas. 4. Wyckoff Helper – Spring - Detection of bear traps, liquidity grabs, and sharp bullish reversals. All four pillars feed into a Confluence Engine (Scoring System). The final output is presented in the Dashboard, with a clear, human-readable signal: - STRONG LONG 🚀 - WEAK LONG ↗ - NEUTRAL / WAIT - WEAK SHORT ↘ - STRONG SHORT 🩸 This allows the trader to see *how many* and *which* layers of the system support a bullish or bearish bias at any given time. ## Chapter 2 – Settings Overview ### 2.1 General & Dashboard Group - Show Dashboard Panel (`show_dash`) Turns the dashboard table in the corner of the chart ON/OFF. - Show Signal Recommendation (`show_rec`) - If enabled, the textual signal (STRONG LONG, WEAK SHORT, etc.) is displayed. - If disabled, you only see feature status (ON/OFF) and the current price. - Dashboard Position (`dash_pos`) Determines where the dashboard appears on the chart: - `Top Right` - `Bottom Right` - `Top Left` ### 2.2 Smart Money (SMC) Group - Enable SMC Strategy (`show_smc`) Globally enables or disables the Order Block and FVG logic. - Order Block Pivot Lookback (`ob_period`) Main parameter for detecting key pivot highs/lows (swing points). - Default value: 5 - Concept: A bar is considered a pivot low if its low is lower than the lows of the previous 5 and the next 5 bars. Similarly, a pivot high has a high higher than the previous 5 and the next 5 bars. These pivots are used as anchors for Order Blocks. - Increasing `ob_period`: - Fewer levels. - But levels tend to be more significant and reliable. - In highly volatile markets (major news, war events, FOMC, etc.), using values 7–10 is recommended to filter out weak levels. - Show Fair Value Gaps (`show_fvg`) Enables/disables the drawing of FVG zones (imbalances). - Bullish OB Color (`c_ob_bull`) - Color of Bullish Order Blocks (Demand Zones). - Default: semi-transparent green (transparency ≈ 80). - Bearish OB Color (`c_ob_bear`) - Color of Bearish Order Blocks (Supply Zones). - Default: semi-transparent red. - Bullish FVG Color (`c_fvg_bull`) - Color of Bullish FVG (upward imbalance), typically yellow. - Bearish FVG Color (`c_fvg_bear`) - Color of Bearish FVG (downward imbalance), typically purple. ### 2.3 Smart DCA Strategy Group - Enable DCA Zones (`show_dca`) Enables the Smart DCA logic and visual labels. - RSI Length (`rsi_len`) Lookback period for RSI (default: 14). - Shorter → more sensitive, more noise. - Longer → fewer signals, higher reliability. - Bollinger Bands Length (`bb_len`) Moving average period for Bollinger Bands (default: 20). - BB Multiplier (`bb_mult`) Standard deviation multiplier for Bollinger Bands (default: 2.0). - For extremely volatile markets, values like 2.5–3.0 can be used so that only extreme deviations trigger a DCA signal. ### 2.4 Volume Profile (Visible Range Sim) Group - Show Volume Profile (`show_vp`) Enables the simulated Volume Profile bars on the right side of the chart. - Volume Lookback Bars (`vp_lookback`) Number of bars used to compute the Volume Profile (default: 150). - Higher values → broader historical context, heavier computation. - Row Count (`vp_rows`) Number of vertical price segments (rows) to divide the total price range into (default: 30). - Width (%) (`vp_width`) Relative width of each volume bar as a percentage. In the code, bar widths are scaled relative to the row with the maximum volume. > Technical note: Volume Profile calculations are executed only on the last bar (`barstate.islast`) to keep the script performant even on higher timeframes. ### 2.5 Wyckoff Helper Group - Show Wyckoff Events (`show_wyc`) Enables detection and plotting of Wyckoff Spring events. - Volume MA Length (`vol_ma_len`) Length of the moving average on volume. A bar is considered to have Ultra Volume if its volume is more than 2× the volume MA. ## Chapter 3 – Smart Money Strategy (Order Blocks & FVG) ### 3.1 What Is an Order Block? An Order Block (OB) represents the footprint of large institutional orders: - Bullish Order Block (Demand Zone) The last selling region (bearish candle/cluster) before a strong upward move. - Bearish Order Block (Supply Zone) The last buying region (bullish candle/cluster) before a strong downward move. Institutions and large players place heavy orders in these regions. Typical price behavior: - Price moves away from the zone. - Later returns to the same zone to fill unfilled orders. - Then continues the larger trend. In the script: - If `pl` (pivot low) forms → a Bullish OB is created. - If `ph` (pivot high) forms → a Bearish OB is created. The box is drawn: - From `bar_index ` to `bar_index`. - Between `low ` and `high `. - `extend=extend.right` extends the OB into the future, so it acts as a dynamic support/resistance zone. - Only the last 4 OB boxes are kept to avoid clutter. ### 3.2 Order Block Color Guide - Semi-transparent Green (`c_ob_bull`) - Represents a Bullish Order Block (Demand Zone). - Interpretation: a price region with a high probability of bullish reaction. - Semi-transparent Red (`c_ob_bear`) - Represents a Bearish Order Block (Supply Zone). - Interpretation: a price region with a high probability of bearish reaction. Overlap (Multiple OBs in the Same Area) When two or more Order Blocks overlap: - The shared area appears visually denser/stronger. - This suggests higher order density. - Such zones can be treated as high-priority levels for entries, exits, and stop-loss placement. ### 3.3 Demand/Supply Logic in the Scoring Engine is_in_demand = low <= ta.lowest(low, 20) is_in_supply = high >= ta.highest(high, 20) - If current price is near the lowest lows of the last 20 bars, it is considered in a Demand Zone → positive impact on score. - If current price is near the highest highs of the last 20 bars, it is considered in a Supply Zone → negative impact on score. This logic complements Order Blocks and helps the Dashboard distinguish whether: - Market is currently in a statistically cheap (long-friendly) area, or - In a statistically expensive (short-friendly) area. ### 3.4 Fair Value Gaps (FVG) #### Concept When the market moves aggressively: - Some price levels are skipped and never traded. - A gap between wicks/shadows of consecutive candles appears. - These regions are called Fair Value Gaps (FVGs) or Imbalances. The market generally “dislikes” imbalance and often: - Returns to these zones in the future. - Fills the gap (rebalance). - Then resumes its dominant direction. #### Implementation in the Code Bullish FVG (Yellow) fvg_bull_cond = show_smc and show_fvg and low > high and close > high if fvg_bull_cond box.new(bar_index , high , bar_index, low, ...) Core condition: `low > high ` → the current low is above the high of two bars ago; the space between them is an untraded gap. Bearish FVG (Purple) fvg_bear_cond = show_smc and show_fvg and high < low and close < low if fvg_bear_cond box.new(bar_index , low , bar_index, high, ...) Core condition: `high < low ` → the current high is below the low of two bars ago; again a price gap exists. #### FVG Color Guide - Transparent Yellow (`c_fvg_bull`) – Bullish FVG Often acts like a magnet for price: - Price tends to retrace into this zone, - Fill the imbalance, - And then continue higher. - Transparent Purple (`c_fvg_bear`) – Bearish FVG Price tends to: - Retrace upward into the purple area, - Fill the imbalance, - And then resume downward movement. #### Trading with FVGs - FVGs are *not* standalone entry signals. They are best used as: - Targets (take-profit zones), or - Reaction areas where you expect a pause or reversal. Examples: - If you are long, a bearish FVG above is often an excellent take-profit zone. - If you are short, a bullish FVG below is often a good cover/exit zone. ### 3.5 Core SMC Trading Templates #### Reversal Long 1. Price trades down into a green Order Block (Demand Zone). 2. A bullish confirmation candle (Close > Open) forms inside or just above the OB. 3. If this zone is close to or aligned with a bullish FVG (yellow), the signal is reinforced. 4. Entry: - At the close of the confirmation candle, or - Using a limit order near the upper boundary of the OB. 5. Stop-loss: - Slightly below the OB. - If the OB is broken decisively and price consolidates below it, the zone loses validity. 6. Targets: - The next FVG, - Or the next red Order Block (Supply Zone) above. #### Reversal Short The mirror scenario: - Price rallies into a red Order Block (Supply). - A bearish confirmation candle forms (Close < Open). - FVG/premium structure above can act as a confluence. - Stop-loss goes above the OB. - Targets: lower FVGs or subsequent green OBs below. ## Chapter 4 – Smart DCA Strategy (RSI + Bollinger Bands) ### 4.1 Smart DCA Concept - Classic DCA = buying at fixed time intervals regardless of price. - Smart DCA = scaling in only when: - Price is statistically cheaper than usual, and - The market is in a clear oversold condition. Code logic: rsi_val = ta.rsi(close, rsi_len) = ta.bb(close, bb_len, bb_mult) dca_buy = show_dca and rsi_val < 30 and close < bb_lower dca_sell = show_dca and rsi_val > 70 and close > bb_upper Conditions: - DCA Buy – Smart Scale-In Zone - RSI < 30 → oversold. - Close < lower Bollinger Band → price has broken below its typical volatility envelope. - DCA Sell – Overbought/Distribution Zone - RSI > 70 → overbought. - Close > upper Bollinger Band → price is extended far above the mean. ### 4.2 Visual Representation on the Chart - Green “DCA” Label Below Candle - Shape: `labelup`. - Color: lime background, white text. - Meaning: statistically attractive level for laddered spot entries or short exits. - Red “SELL” Label Above Candle - Warning that the market is in an extended, overbought condition. - Suitable for profit-taking on longs or considering short entries (with proper confluence and risk management). - Light Green Background (`bgcolor`) - When `dca_buy` is true, the candle background turns very light green (high transparency). - This helps visually identify DCA Zones across the chart at a glance. ### 4.3 Practical Use in Trading #### Spot Trading Used to build a better average entry price: - Every time a DCA label appears, allocate a fixed portion of capital (e.g., 2–5%). - Combining DCA signals with: - Green OBs (Demand Zones), and/or - The Volume Profile POC makes the zone structurally more important. #### Futures Trading - Longs - Use DCA Buy signals as low-risk zones for opening or adding to longs when: - Price is inside a green OB, or - The Dashboard already leans LONG. - Shorts - Use DCA Sell signals as: - Exit zones for longs, or - Areas to initiate shorts with stops above structural highs. ## Chapter 5 – Volume Profile (Visible Range Simulation) ### 5.1 Concept Traditional volume (histogram under the chart) shows volume over time. Volume Profile shows volume by price level: - At which prices has the highest trading activity occurred? - Where did buyers and sellers agree the most (High Volume Nodes – HVNs)? - Where did price move quickly due to low participation (Low Volume Nodes – LVNs)? ### 5.2 Implementation in the Script Executed only when `show_vp` is enabled and on the last bar: 1. The last `vp_lookback` bars (default 150) are processed. 2. The minimum low and maximum high over this window define the price range. 3. This price range is divided into `vp_rows` segments (e.g., 30 rows). 4. For each row: - All bars are scanned. - If the mid-price `(high + low ) / 2` falls inside a row, that bar’s volume is added to the row total. 5. The row with the greatest volume is stored as `max_vol_idx` (the POC row). 6. For each row, a volume box is drawn on the right side of the chart. ### 5.3 Color Scheme - Semi-transparent Orange - The row with the maximum volume – the Point of Control (POC). - Represents the strongest support/resistance level from a volume perspective. - Semi-transparent Blue - Other volume rows. - The taller the bar → the higher the volume → the stronger the interest at that price band. ### 5.4 Trading Applications - If price is above POC and retraces back into it: → POC often acts as support, suitable for long setups. - If price is below POC and rallies into it: → POC often acts as resistance, suitable for short setups or profit-taking. HVNs (Tall Blue Bars) - Represent areas of equilibrium where the market has spent time and traded heavily. - Price tends to consolidate here before choosing a direction. LVNs (Short or Nearly Empty Bars) - Represent low participation zones. - Price often moves quickly through these areas – useful for targeting fast moves. ## Chapter 6 – Wyckoff Helper – Spring ### 6.1 Spring Concept In the Wyckoff framework: - A Spring is a false break of support. - The market briefly trades below a well-defined support level, triggers stop losses, then sharply reverses upward as institutional buyers absorb liquidity. This movement: - Clears out weak hands (retail sellers). - Provides large players with liquidity to enter long positions. - Often initiates a new uptrend. ### 6.2 Code Logic Conditions for a Spring: 1. The current low is lower than the lowest low of the previous 50 bars → apparent break of a long-standing support. 2. The bar closes bullish (Close > Open) → the breakdown was rejected. 3. Volume is significantly elevated: → `volume > 2 × volume_MA` (Ultra Volume). When all conditions are met and `show_wyc` is enabled: - A pink diamond is plotted below the bar, - With the label “Spring” – one of the strongest long signals in this system. ### 6.3 Trading Use - After a valid Spring, markets frequently enter a meaningful bullish phase. - The highest quality setups occur when: - The Spring forms inside a green Order Block, and - Near or on the Volume Profile POC. Entries: - At the close of the Spring bar, or - On the first pullback into the mid-range of the Spring candle. Stop-loss: - Slightly below the Spring’s lowest point (wick low plus a small buffer). ## Chapter 7 – Confluence Engine & Dashboard ### 7.1 Scoring Logic For each bar, the script: 1. Resets `score` to 0. 2. Adjusts the score based on different signals. SMC Contribution if show_smc if is_in_demand score += 1 if is_in_supply score -= 1 - Being in Demand → `+1` - Being in Supply → `-1` DCA Contribution if show_dca if dca_buy score += 2 if dca_sell score -= 2 - DCA Buy → `+2` (strong, statistically driven long signal) - DCA Sell → `-2` Wyckoff Spring Contribution if show_wyc if wyc_spring score += 2 - Spring → `+2` (entry of strong money) ### 7.2 Mapping Score to Dashboard Signal - score ≥ 2 → STRONG LONG 🚀 Multiple bullish conditions aligned. - score = 1 → WEAK LONG ↗ Some bullish bias, but only one layer clearly positive. - score = 0 → NEUTRAL / WAIT Rough balance between buying and selling forces; staying flat is usually preferable. - score = -1 → WEAK SHORT ↘ Mild bearish bias, suited for cautious or short-term plays. - score ≤ -2 → STRONG SHORT 🩸 Convergence of several bearish signals. ### 7.3 Dashboard Structure The dashboard is a two-column table: - Row 0 - Column 0: `"Mars Signals"` – black background, white text. - Column 1: `"UIS v3.0"` – black background, yellow text. - Row 1 - Column 0: `"Price:"` (light grey background). - Column 1: current closing price (`close`) with a semi-transparent blue background. - Row 2 - Column 0: `"SMC:"` - Column 1: - `"ON"` (green) if `show_smc = true` - `"OFF"` (grey) otherwise. - Row 3 - Column 0: `"DCA:"` - Column 1: - `"ON"` (green) if `show_dca = true` - `"OFF"` (grey) otherwise. - Row 4 - Column 0: `"Signal:"` - Column 1: signal text (`status_txt`) with background color `status_col` (green, red, teal, maroon, etc.) - If `show_rec = false`, these cells are cleared. ## Chapter 8 – Visual Legend (Colors, Shapes & Actions) For quick reading inside TradingView, the visual elements are described line by line instead of a table. Chart Element: Green Box Color / Shape: Transparent green rectangle Core Meaning: Bullish Order Block (Demand Zone) Suggested Trader Response: Look for longs, Smart DCA adds, closing or reducing shorts. Chart Element: Red Box Color / Shape: Transparent red rectangle Core Meaning: Bearish Order Block (Supply Zone) Suggested Trader Response: Look for shorts, or take profit on existing longs. Chart Element: Yellow Area Color / Shape: Transparent yellow zone Core Meaning: Bullish FVG / upside imbalance Suggested Trader Response: Short take-profit zone or expected rebalance area. Chart Element: Purple Area Color / Shape: Transparent purple zone Core Meaning: Bearish FVG / downside imbalance Suggested Trader Response: Long take-profit zone or temporary supply region. Chart Element: Green "DCA" Label Color / Shape: Green label with white text, plotted below the candle Core Meaning: Smart ladder-in buy zone, DCA buy opportunity Suggested Trader Response: Spot DCA entry, partial short exit. Chart Element: Red "SELL" Label Color / Shape: Red label with white text, plotted above the candle Core Meaning: Overbought / distribution zone Suggested Trader Response: Take profit on longs, consider initiating shorts. Chart Element: Light Green Background (bgcolor) Color / Shape: Very transparent light-green background behind bars Core Meaning: Active DCA Buy zone Suggested Trader Response: Treat as a discount zone on the chart. Chart Element: Orange Bar on Right Color / Shape: Transparent orange horizontal bar in the volume profile Core Meaning: POC – price with highest traded volume Suggested Trader Response: Strong support or resistance; key reference level. Chart Element: Blue Bars on Right Color / Shape: Transparent blue horizontal bars in the volume profile Core Meaning: Other volume levels, showing high-volume and low-volume nodes Suggested Trader Response: Use to identify balance zones (HVN) and fast-move corridors (LVN). Chart Element: Pink "Spring" Diamond Color / Shape: Pink diamond with white text below the candle Core Meaning: Wyckoff Spring – liquidity grab and potential major bullish reversal Suggested Trader Response: One of the strongest long signals in the suite; look for high-quality long setups with tight risk. Chart Element: STRONG LONG in Dashboard Color / Shape: Green background, white text in the Signal row Core Meaning: Multiple bullish layers in confluence Suggested Trader Response: Consider initiating or increasing longs with strict risk management. Chart Element: STRONG SHORT in Dashboard Color / Shape: Red background, white text in the Signal row Core Meaning: Multiple bearish layers in confluence Suggested Trader Response: Consider initiating or increasing shorts with a logical, well-placed stop. ## Chapter 9 – Timeframe-Based Trading Playbook ### 9.1 Timeframe Selection - Scalping - Timeframes: 1M, 5M, 15M - Objective: fast intraday moves (minutes to a few hours). - Recommendation: focus on SMC + Wyckoff. Smart DCA on very low timeframes may introduce excessive noise. - Day Trading - Timeframes: 15M, 1H, 4H - Provides a good balance between signal quality and frequency. - Recommendation: use the full stack – SMC + DCA + Volume Profile + Wyckoff + Dashboard. - Swing Trading & Position Investing - Timeframes: Daily, Weekly - Emphasis on Smart DCA + Volume Profile. - SMC and Wyckoff are used mainly to fine-tune swing entries within larger trends. ### 9.2 Scenario A – Scalping Long Example: 5-Minute Chart 1. Price is declining into a green OB (Bullish Demand). 2. A candle with a long lower wick and bullish close (Pin Bar / Rejection) forms inside the OB. 3. A Spring diamond appears below the same candle → very strong confluence. 4. The Dashboard shows at least WEAK LONG ↗, ideally STRONG LONG 🚀. 5. Entry: - On the close of the confirmation candle, or - On the first pullback into the mid-range of that candle. 6. Stop-loss: - Slightly below the OB. 7. Targets: - Nearby bearish FVG above, and/or - The next red OB. ### 9.3 Scenario B – Day-Trading Short Recommended Timeframes: 1H or 4H 1. The market completes a strong impulsive move upward. 2. Price enters a red Order Block (Supply). 3. In the same zone, a purple FVG appears or remains unfilled. 4. On a lower timeframe (e.g., 15M), RSI enters overbought territory and a DCA Sell signal appears. 5. The main timeframe Dashboard (1H) shows WEAK SHORT ↘ or STRONG SHORT 🩸. Trade Plan - Open a short near the upper boundary of the red OB. - Place the stop above the OB or above the last swing high. - Targets: - A yellow FVG lower on the chart, and/or - The next green OB (Demand) below. ### 9.4 Scenario C – Swing / Investment with Smart DCA Timeframes: Daily / Weekly 1. On the daily or weekly chart, each time a green “DCA” label appears: - Allocate a fixed fraction of your capital (e.g., 3–5%) to that asset. 2. Check whether this DCA zone aligns with the orange POC of the Volume Profile: - If yes → the quality of the entry zone is significantly higher. 3. If the DCA signal sits inside a daily green OB, the probability of a medium-term bottom increases. 4. Always build the position laddered, never all-in at a single price. Exits for investors: - Near weekly red OBs or large purple FVG zones. - Ideally via partial profit-taking rather than closing 100% at once. ### 9.5 Case Study 1 – BTCUSDT (15-Minute) - Context: Price has sold off down towards 65,000 USD. - A green OB had previously formed at that level. - Near the lower boundary of this OB, a partially filled yellow FVG is present. - As price returns to this region, a Spring appears. - The Dashboard shifts from NEUTRAL / WAIT to WEAK LONG ↗. Plan - Enter a long near the OB low. - Place stop below the Spring low. - First target: a purple FVG around 66,200. - Second (optional) target: the first red OB above that level. ### 9.6 Case Study 2 – Meme Coin (PEPE – 4H) - After a strong pump, price enters a corrective phase. - On the 4H chart, RSI drops below 30; price breaks below the lower Bollinger Band → a DCA label prints. - The Volume Profile shows the POC at approximately the same level. - The Dashboard displays STRONG LONG 🚀. Plan - Execute laddered buys in the combined DCA + POC zone. - Place a protective stop below the last significant swing low. - Target: an expected 20–30% upside move towards the next red OB or purple FVG. ## Chapter 10 – Risk Management, Psychology & Advanced Tuning ### 10.1 Risk Management No signal, regardless of its strength, replaces risk control. Recommendations: - In futures, do not expose more than 1–3% of account equity to risk per trade. - Adjust leverage to the volatility of the instrument (lower leverage for highly volatile altcoins). - Place stop-losses in zones where the idea is clearly invalidated: - Below/above the relevant Order Block or Spring, not randomly in the middle of the structure. ### 10.2 Market-Specific Parameter Tuning - Calmer Markets (e.g., major FX pairs) - `ob_period`: 3–5. - `bb_mult`: 2.0 is usually sufficient. - Highly Volatile Markets (Crypto, news-driven assets) - `ob_period`: 7–10 to highlight only the most robust OBs. - `bb_mult`: 2.5–3.0 so that only extreme deviations trigger DCA. - `vol_ma_len`: increase (e.g., to ~30) so that Spring triggers only on truly exceptional volume spikes. ### 10.3 Trading Psychology - STRONG LONG 🚀 does not mean “risk-free”. It means the probability of a successful long, given the model’s logic, is higher than average. - Treat Mars Signals as a confirmation and context system, not a full replacement for your own decision-making. - Example of disciplined thinking: - The Dashboard prints STRONG LONG, - But price is simultaneously testing a multi-month macro resistance or a major negative news event is imminent, - In such cases, trade smaller, widen stops appropriately, or skip the trade. ## Chapter 11 – Technical Notes & FAQ ### 11.1 Does the Script Repaint? - Order Blocks and Springs are based on completed pivot structures and confirmed candles. - Until a pivot is confirmed, an OB does not exist; after confirmation, behavior is stable under classic SMC assumptions. - The script is designed to be structurally consistent rather than repainting signals arbitrarily. ### 11.2 Computational Load of Volume Profile - On the last bar, the script processes up to `vp_lookback` bars × `vp_rows` rows. - On very low timeframes with heavy zooming, this can become demanding. - If you experience performance issues: - Reduce `vp_lookback` or `vp_rows`, or - Temporarily disable Volume Profile (`show_vp = false`). ### 11.3 Multi-Timeframe Behavior - This version of the script is not internally multi-timeframe. All logic (OB, DCA, Spring, Volume Profile) is computed on the active timeframe only. - Practical workflow: - Analyze overall structure and key zones on higher timeframes (4H / Daily). - Use lower timeframes (15M / 1H) with the same tool for timing entries and exits. ## Conclusion Mars Signals – Ultimate Institutional Suite v3.0 (Joker) is a multi-layer trading framework that unifies: - Price structure (Order Blocks & FVG), - Statistical behavior (Smart DCA via RSI + Bollinger), - Volume distribution by price (Volume Profile with POC, HVN, LVN), - Liquidity events (Wyckoff Spring), into a single, coherent system driven by a transparent Confluence Scoring Engine. The final output is presented in clear, actionable language: > STRONG LONG / WEAK LONG / NEUTRAL / WEAK SHORT / STRONG SHORT The system is designed to support professional decision-making, not to replace it. Used together with strict risk management and disciplined execution, Mars Signals – UIS v3.0 (Joker) can serve as a central reference manual and operational guide for your trading workflow, from scalping to swing and investment positioning.
Pine Script®指标
由MarsSignals提供
lower_tfLibrary "lower_tf" █ OVERVIEW This library is an enhanced (opinionated) version of the library originally developed by PineCoders contained in lower_tf . It is a Pine Script® programming tool for advanced lower-timeframe selection and intra-bar analysis. █ CONCEPTS Lower Timeframe Analysis Lower timeframe analysis refers to the analysis of price action and market microstructure using data from timeframes shorter than the current chart period. This technique allows traders and analysts to gain deeper insights into market dynamics, volume distribution, and the price movements occurring within each bar on the chart. In Pine Script®, the request.security_lower_tf() function allows this analysis by accessing intrabar data. The library provides a comprehensive set of functions for accurate mapping of lower timeframes, dynamic precision control, and optimized historical coverage using request.security_lower_tf(). █ IMPROVEMENTS The original library implemented ten precision levels. This enhanced version extends that to twelve levels, adding two ultra-high-precision options: Coverage-Based Precision (Original 5 levels): 1. "Covering most chart bars (least precise)" 2. "Covering some chart bars (less precise)" 3. "Covering fewer chart bars (more precise)" 4. "Covering few chart bars (very precise)" 5. "Covering the least chart bars (most precise)" Intrabar-Count-Based Precision (Expanded from 5 to 7 levels): 6. "~12 intrabars per chart bar" 7. "~24 intrabars per chart bar" 8. "~50 intrabars per chart bar" 9. "~100 intrabars per chart bar" 10. "~250 intrabars per chart bar" 11. "~500 intrabars per chart bar" ← NEW 12. "~1000 intrabars per chart bar" ← NEW The key enhancements in this version include: 1. Extended Precision Range: Adds two ultra-high-precision levels (~500 and ~1000 intrabars) for advanced microstructure analysis requiring maximum granularity. 2. Market-Agnostic Implementation: Eliminates the distinction between crypto/forex and traditional markets, removing the mktFactor variable in favor of a unified, predictable approach across all asset classes. 3. Explicit Precision Mapping: Completely refactors the timeframe selection logic using native Pine Script® timeframe properties ( timeframe.isseconds , timeframe.isminutes , timeframe.isdaily , timeframe.isweekly , timeframe.ismonthly ) and explicit multiplier-based lookup tables. The original library used minute-based calculations with market-dependent conditionals that produced inconsistent results. This version provides deterministic, predictable mappings for every chart timeframe, ensuring consistent precision behavior regardless of asset type or market hours. An example of the differences can be seen side-by-side in the chart below, where the original library is on the left and the enhanced version is on the right: █ USAGE EXAMPLE // This Pine Script® code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // © andre_007 //@version=6 indicator("lower_tf Example") import andre_007/lower_tf/1 as LTF import PineCoders/Time/5 as PCtime //#region ———————————————————— Example code // ————— Constants color WHITE = color.white color GRAY = color.gray string LTF1 = "Covering most chart bars (least precise)" string LTF2 = "Covering some chart bars (less precise)" string LTF3 = "Covering less chart bars (more precise)" string LTF4 = "Covering few chart bars (very precise)" string LTF5 = "Covering the least chart bars (most precise)" string LTF6 = "~12 intrabars per chart bar" string LTF7 = "~24 intrabars per chart bar" string LTF8 = "~50 intrabars per chart bar" string LTF9 = "~100 intrabars per chart bar" string LTF10 = "~250 intrabars per chart bar" string LTF11 = "~500 intrabars per chart bar" string LTF12 = "~1000 intrabars per chart bar" string TT_LTF = "This selection determines the approximate number of intrabars analyzed per chart bar. Higher numbers of intrabars produce more granular data at the cost of less historical bar coverage, because the maximum number of available intrabars is 200K. \n\nThe first five options set the lower timeframe based on a specified relative level of chart bar coverage. The last five options set the lower timeframe based on an approximate number of intrabars per chart bar." string TAB_TXT = "Uses intrabars at the {0} timeframe.\nAvg intrabars per chart bar: {1,number,#.#}\nChart bars covered: {2} of {3} ({4,number,#.##}%)" string ERR_TXT = "No intrabar information exists at the {1}{0}{1} timeframe." // ————— Inputs string ltfModeInput = input.string(LTF3, "Intrabar precision", options = , tooltip = TT_LTF) bool showInfoBoxInput = input.bool(true, "Show information box ") string infoBoxSizeInput = input.string("normal", "Size ", inline = "01", options = ) string infoBoxYPosInput = input.string("bottom", "↕", inline = "01", options = ) string infoBoxXPosInput = input.string("right", "↔", inline = "01", options = ) color infoBoxColorInput = input.color(GRAY, "", inline = "01") color infoBoxTxtColorInput = input.color(WHITE, "T", inline = "01") // ————— Calculations // @variable A "string" representing the lower timeframe for the data request. // NOTE: // This line is a good example where using `var` in the declaration can improve a script's performance. // By using `var` here, the script calls `ltf()` only once, on the dataset's first bar, instead of redundantly // evaluating unchanging strings on every bar. We only need one evaluation of this function because the selected // timeframe does not change across bars in this script. var string ltfString = LTF.ltf(ltfModeInput, LTF1, LTF2, LTF3, LTF4, LTF5, LTF6, LTF7, LTF8, LTF9, LTF10, LTF11, LTF12) // @variable An array containing all intrabar `close` prices from the `ltfString` timeframe for the current chart bar. array intrabarCloses = request.security_lower_tf(syminfo.tickerid, ltfString, close) // Calculate the intrabar stats. = LTF.ltfStats(intrabarCloses) int chartBars = bar_index + 1 // ————— Visuals // Plot the `avgIntrabars` and `intrabars` series in all display locations. plot(avgIntrabars, "Average intrabars", color.silver, 6) plot(intrabars, "Intrabars", color.blue, 2) // Plot the `chartBarsCovered` and `chartBars` values in the Data Window and the script's status line. plot(chartBarsCovered, "Chart bars covered", display = display.data_window + display.status_line) plot(chartBars, "Chart bars total", display = display.data_window + display.status_line) // Information box logic. if showInfoBoxInput // @variable A single-cell table that displays intrabar information. var table infoBox = table.new(infoBoxYPosInput + "_" + infoBoxXPosInput, 1, 1) // @variable The span of the `ltfString` timeframe formatted as a number of automatically selected time units. string formattedLtf = PCtime.formattedNoOfPeriods(timeframe.in_seconds(ltfString) * 1000) // @variable A "string" containing the formatted text to display in the `infoBox`. string txt = str.format( TAB_TXT, formattedLtf, avgIntrabars, chartBarsCovered, chartBars, chartBarsCovered / chartBars * 100, "'" ) // Initialize the `infoBox` cell on the first bar. if barstate.isfirst table.cell( infoBox, 0, 0, txt, text_color = infoBoxTxtColorInput, text_size = infoBoxSizeInput, bgcolor = infoBoxColorInput ) // Update the cell's text on the latest bar. else if barstate.islast table.cell_set_text(infoBox, 0, 0, txt) // Raise a runtime error if no intrabar data is available. if ta.cum(intrabars) == 0 and barstate.islast runtime.error(str.format(ERR_TXT, ltfString, "'")) //#endregion █ EXPORTED FUNCTIONS ltf(userSelection, choice1, choice2, ...) Returns the optimal lower timeframe string based on user selection and current chart timeframe. Dynamically calculates precision to balance granularity with historical coverage within the 200K intrabar limit. ltfStats(intrabarValues) Analyzes an intrabar array returned by request.security_lower_tf() and returns statistics: number of intrabars in current bar, total chart bars covered, and average intrabars per bar. █ CREDITS AND LICENSING Original Concept : PineCoders Team Original Lower TF Library : License : Mozilla Public License 2.0
Pine Script®库
由andre_007提供
1
Price Action Brooks ProPrice Action Brooks Pro (PABP) - Professional Trading Indicator ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 OVERVIEW Price Action Brooks Pro (PABP) is a professional-grade TradingView indicator developed based on Al Brooks' Price Action trading methodology. It integrates decades of Al Brooks' trading experience and price action analysis techniques into a comprehensive technical analysis tool, helping traders accurately interpret market structure and identify trading opportunities. • Applicable Markets: Stocks, Futures, Forex, Cryptocurrencies • Timeframes: 1-minute to Daily (5-minute chart recommended) • Theoretical Foundation: Al Brooks Price Action Trading Method ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 CORE FEATURES ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1️⃣ INTELLIGENT GAP DETECTION SYSTEM Automatically identifies and marks three critical types of gaps in the market. TRADITIONAL GAP • Detects complete price gaps between bars • Upward gap: Current bar's low > Previous bar's high • Downward gap: Current bar's high < Previous bar's low • Hollow border design - doesn't obscure price action • Color coding: Upward gaps (light green), Downward gaps (light pink) • Adjustable border: 1-5 pixel width options TAIL GAP • Detects price gaps between bar wicks/shadows • Analyzes across 3 bars for precision • Identifies hidden market structure BODY GAP • Focuses only on gaps between bar bodies (open/close) • Filters out wick noise • Disabled by default, enable as needed Trading Significance: • Gaps signal strong momentum • Gap fills provide trading opportunities • Consecutive gaps indicate trend continuation ✓ Independent alert system for all gap types ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2️⃣ RTH BAR COUNT (Trading Session Counter) Intelligent counting system designed for US stock intraday trading. FEATURES • RTH Only Display: Regular Trading Hours (09:30-15:00 EST) • 5-Minute Chart Optimized: Displays every 3 bars (15-minute intervals) • Daily Auto-Reset: Counting starts from 1 each trading day SMART COLOR CODING • 🔴 Red (Bars 18 & 48): Critical turning moments (1.5h & 4h) • 🔵 Sky Blue (Multiples of 12): Hourly markers (12, 24, 36...) • 🟢 Light Green (Bar 6): Half-hour marker (30 minutes) • ⚫ Gray (Others): Regular 15-minute interval markers Al Brooks Time Theory: • Bar 18 (90 min): First 90 minutes determine daily trend • Bar 48 (4 hours): Important afternoon turning point • Hourly markers: Track institutional trading rhythm ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3️⃣ FOUR-LINE EMA SYSTEM Professional-grade configurable moving average system. DEFAULT CONFIGURATION • EMA 20: Short-term trend (Al Brooks' most important MA) • EMA 50: Medium-short term reference • EMA 100: Medium-long term confirmation • EMA 200: Long-term trend and bull/bear dividing line FLEXIBLE CUSTOMIZATION Each EMA can be independently configured: • On/Off toggle • Data source selection (close/high/low/open, etc.) • Custom period length • Offset adjustment • Color and transparency COLOR SCHEME • EMA 20: Dark brown, opaque (most important) • EMA 50/100/200: Blue-purple gradient, 70% transparent TRADING APPLICATIONS • Bullish Alignment: Price > 20 > 50 > 100 > 200 • Bearish Alignment: 200 > 100 > 50 > 20 > Price • EMA Confluence: All within <1% = major move precursor Al Brooks Quote: "The EMA 20 is the most important moving average. Almost all trading decisions should reference it." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 4️⃣ PREVIOUS VALUES (Key Prior Price Levels) Automatically marks important price levels that often act as support/resistance. THREE INDEPENDENT CONFIGURATIONS Each group configurable for: • Timeframe (1D/60min/15min, etc.) • Price source (close/high/low/open/CurrentOpen, etc.) • Line style and color • Display duration (Today/TimeFrame/All) SMART OPEN PRICE LABELS ⭐ • Auto-displays "Open" label when CurrentOpen selected • Label color matches line color • Customizable label size TYPICAL SETUP • 1st Line: Previous close (Support/Resistance) • 2nd Line: Previous high (Breakout target) • 3rd Line: Previous low (Support level) Al Brooks Magnet Price Theory: • Previous open: Price frequently tests opening price • Previous high/low: Strongest support/resistance • Breakout confirmation: Breaking prior levels = trend continuation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 5️⃣ INSIDE & OUTSIDE BAR PATTERN RECOGNITION Automatically detects core candlestick patterns from Al Brooks' theory. ii PATTERN (Consecutive Inside Bars) • Current bar contained within previous bar • Two or more consecutive • Labels: ii, iii, iiii (auto-accumulates) • High-probability breakout setup • Stop loss: Outside both bars Trading Significance: "Inside bars are one of the most reliable breakout setups, especially three or more consecutive inside bars." - Al Brooks OO PATTERN (Consecutive Outside Bars) • Current bar engulfs previous bar • Two or more consecutive • Labels: oo, ooo (auto-accumulates) • Indicates indecision or volatility increase ioi PATTERN (Inside-Outside-Inside) • Three-bar combination: Inside → Outside → Inside • Auto-detected and labeled • Tug-of-war pattern • Breakout direction often very strong SMART LABEL SYSTEM • Auto-accumulation counting • Dynamic label updates • Customizable size and color • Positioned above bars ✓ Independent alerts for all patterns ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 USE CASES INTRADAY TRADING ✓ Bar Count (timing rhythm) ✓ Traditional Gap (strong signals) ✓ EMA 20 + 50 (quick trend) ✓ ii/ioi Patterns (breakout points) SWING TRADING ✓ Previous Values (key levels) ✓ EMA 20 + 50 + 100 (trend analysis) ✓ Gaps (trend confirmation) ✓ iii Patterns (entry timing) TREND FOLLOWING ✓ All four EMAs (alignment analysis) ✓ Gaps (continuation signals) ✓ Previous Values (targets) BREAKOUT TRADING ✓ iii Pattern (high-reliability setup) ✓ Previous Values (targets) ✓ EMA 20 (trend direction) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎨 DESIGN FEATURES PROFESSIONAL COLOR SCHEME • Gaps: Hollow borders + light colors • Bar Count: Smart multi-color coding • EMAs: Gradient colors + transparency hierarchy • Previous Values: Customizable + smart labels CLEAR VISUAL HIERARCHY • Important elements: Opaque (EMA 20, bar count) • Reference elements: Semi-transparent (other EMAs, gaps) • Hollow design: Doesn't obscure price action USER-FRIENDLY INTERFACE • Clear functional grouping • Inline layout saves space • All colors and sizes customizable ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📚 AL BROOKS THEORY CORE READING PRICE ACTION "Don't try to predict the market, read what the market is telling you." PABP converts core concepts into visual tools: • Trend Assessment: EMA system • Time Rhythm: Bar Count • Market Structure: Gap analysis • Trade Setups: Inside/Outside Bars • Support/Resistance: Previous Values PROBABILITY THINKING • ii pattern: Medium probability • iii pattern: High probability • iii + EMA 20 support: Very high probability ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ TECHNICAL SPECIFICATIONS • Pine Script Version: v6 • Maximum Objects: 500 lines, 500 labels, 500 boxes • Alert Functions: 8 independent alerts • Supported Timeframes: All (5-min recommended for Bar Count) • Compatibility: All TradingView plans, Mobile & Desktop ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 RECOMMENDED INITIAL SETTINGS GAPS • Traditional Gap: ✓ • Tail Gap: ✓ • Border Width: 2 BAR COUNT • Use Bar Count: ✓ • Label Size: Normal EMA • EMA 20: ✓ • EMA 50: ✓ • EMA 100: ✓ • EMA 200: ✓ PREVIOUS VALUES • 1st: close (Previous close) • 2nd: high (Previous high) • 3rd: low (Previous low) INSIDE & OUTSIDE BAR • All patterns: ✓ • Label Size: Large ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🌟 WHY CHOOSE PABP? ✅ Solid Theoretical Foundation Based on Al Brooks' decades of trading experience ✅ Complete Professional Features Systematizes complex price action analysis ✅ Highly Customizable Every feature adjustable to personal style ✅ Excellent Performance Optimized code ensures smooth experience ✅ Continuous Updates Constantly improving based on feedback ✅ Suitable for All Levels Benefits beginners to professionals ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📖 RECOMMENDED LEARNING Al Brooks Books: • "Trading Price Action Trends" • "Trading Price Action Trading Ranges" • "Trading Price Action Reversals" Learning Path: 1. Understand basic candlestick patterns 2. Learn EMA applications 3. Master market structure analysis 4. Develop trading system 5. Continuous practice and optimization ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ RISK DISCLOSURE IMPORTANT NOTICE: • For educational and informational purposes only • Does not constitute investment advice • Past performance doesn't guarantee future results • Trading involves risk and may result in capital loss • Trade according to your risk tolerance • Test thoroughly in demo account first RESPONSIBLE TRADING: • Always use stop losses • Control position sizes reasonably • Don't overtrade • Continuous learning and improvement • Keep trading journal ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📜 COPYRIGHT Price Action Brooks Pro (PABP) Author: © JimmC98 License: Mozilla Public License 2.0 Pine Script Version: v6 Acknowledgments: Thanks to Dr. Al Brooks for his contributions to price action trading. This indicator is developed based on his theories. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Experience professional-grade price action analysis now! "The best traders read price action, not indicators. But when indicators help you read price action better, use them." - Al Brooks
Pine Script®指标
由JimmC98提供
1
Custom Buy/Sell Pattern BuilderAre you tired of using trading indicators that only let you follow fixed, pre-designed rules? Do you wish you could build your own “Buy” or “Sell” signals, experiment with your own ideas, or see instantly if your unique pattern works—without learning coding or hiring a developer? The Custom Buy/Sell Pattern Builder is designed for YOU. This TradingView indicator lets ANY trader—even a complete beginner—define exactly what kind of price and volume conditions should create a BUY or SELL label on any chart, in any market, at any timeframe. You don’t need to know programming. You don’t need to know the definition of a hammer, doji, volume spike, or Engulfing pattern. With a few clicks and easy dropdown choices, you can: Make your own rules for buying or selling Choose how many candles your pattern should look at Decide if you want the biggest body, the lowest volume, the biggest movement, or any combination you can imagine The result? You’ll see clear “BUY” or “SELL” labels automatically show up on your chart whenever the exact rule YOU built matches current price action. No more guessing. No more forced strategies. Just pure control and visual feedback! Why Is This Powerful? Traditional indicators (like MACD, RSI, or even classic candlestick scanners) work the same for everyone—and only as their inventors defined. But every trader, and every market, is unique. What if you could say: “Show me a ‘SELL’ every time the newest candle is bigger than the one before, but with LESS volume, while the bar before that had an even smaller body—but more volume than all others?” With this tool, it’s EASY! You simply pick which candle you want to compare (most recent, previous, etc), what to compare (body or volume—body means the candle’s “thickness”, from open to close), choose “greater than”, “less than”, or “equal to”, and set a multiplier if you want (like “half as much”, “twice as big”, etc). After this, if any bar on the chart fits all your rules, it will mark it as a BUY or SELL, depending on your selection. This means— Beginners can start experimenting with their intuition or small ideas, without tech hurdles Experienced traders can visualize and fine-tune any possible logic, before they commit to backtesting or automating a real strategy Every “what if” or “I wonder” setup is just 2–3 clicks away How Does It Work? Simple Steps 1. Choose Your Signal Type “Buy” or “Sell” This tells the indicator whether to mark the qualifying bars with a green “BUY” or red “SELL” label 2. Pick How Many Candles To Use “Pattern Candle Count” input (2, 3, or 4) Example: If you use 4, the pattern will be applied to the most recent 4 candles at every step 3. Define Your Pattern With Inputs For each candle (from newest “0” to oldest “3”), you can set: Body Condition (example: “is this candle’s body bigger/smaller/equal to another?”) Pick which candle to compare against Pick “>”, “<”, “>=”, “<=”, or “=” Set a multiplier if needed (like “0.5” to mean “half as big as” or “2” for “twice as big as”) Volume Condition (exact same choices, but based on trading volume—not the candle’s price body) For example: “Candle0 Body > Candle2 Body” means “the latest candle’s real-body (open–close) is bigger than the one two bars ago.” “Candle1 Volume <= Candle2 Volume” means “the previous candle’s volume is less than or equal to the volume of the bar two periods ago.” You can leave a comparison blank if you don’t want to use it for a particular candle. What Happens After You Set Your Rules? Every bar on your chart is checked for your logic: If ALL body AND volume conditions are true (for each candle you specified), AND The signal side (“Buy” or “Sell”) matches your dropdown, Then a green “BUY” or red “SELL” label will show right on the bar, so you can visually spot exactly where your logic works! Practical Example: Suppose you want an entry setup that is: “Sell whenever the newest candle’s body is bigger than two bars ago, body before that is bigger than three bars ago, AND the newest candle’s volume is less than or equal to two bars ago, AND the candle three bars ago’s volume is less than or equal to half the candle two bars ago’s volume.” You’d set: Pattern Candle Count: 4 Side: Sell Candle0 Body Ref#: 2, Op: >, Mult: 1 Candle1 Body Ref#: 3, Op: >, Mult: 1 Candle0 Vol Ref#: 2, Op: <=, Mult: 1 Candle3 Vol Ref#: 2, Op: <=, Mult: 0.5 And the script will find all “SELL” bars on your chart matching these conditions. Inputs Section: What Does Each Setting Do? Let’s break down each input in the indicator’s Settings one by one, so even if you’re new, you’ll understand exactly how to use it! 1. Pattern Candle Count (2–4) What is it? This sets how many candles in a row you want your rule to look at. Example: “4” means your rules are based on the most recent candle and the 3 before it. “2” means you are only comparing the current and previous candles. Tip: Beginners often use 4 to spot stronger patterns, but you can experiment! 2. Signal Side What is it? Choose “Buy” or “Sell”. The word you pick here decides which colored label (green for Buy, red for Sell) appears if your pattern matches. Example: Want to spot where “Sell” is likely? Pick “Sell”. Change to “Buy” if you want bullish signals instead. 3. Body & Volume Comparison Settings (per Candle) For each candle (#0 is newest/current, #3 is oldest in your pattern window): Body Comparison Candle# Body Ref# Choose which other candle you want to compare this one’s body to. “0” = newest, “1” = previous, “2” = two bars ago, “3” = three bars ago Candle# Body Op (Operator; >, <, >=, <=, =) How do you want to compare? “>” means “greater than” (is bigger than) “<” means “less than” (is smaller than) “=” means “equal to” Candle# Body Mult (Multiplier) If you want relative comparisons. For example, with Mult=1: “Candle0 body > Candle2 body x 1” means just “0 is larger than 2.” “Candle0 body > Candle2 body x 2” means “0 is more than double 2.” Volume Comparison Candle# Vol Ref# / Op / Mult Exact same logic as body, but works on the “Volume” of each candle (how much was traded during that bar). How to Set Up a Rule (Step by Step Example) Say you want to mark a Sell every time: The most recent candle’s real body is BIGGER than the candle 2 bars ago; The previous candle’s body is also BIGGER than the candle 3 bars ago; The current candle’s volume is LESS than or equal to the volume of candle 2; The previous candle’s volume is LESS than or equal to candle 2’s volume; The candle 3 bars ago’s volume is LESS than or equal to HALF candle 2’s volume. You’d set: Pattern Candle Count: 4 Side: "Sell" Candle0 Body Ref#: 2, Op: “>”, Mult: 1 Candle1 Body Ref#: 3, Op: “>”, Mult: 1 Candle0 Vol Ref#: 2, Op: “<=”, Mult: 1 Candle1 Vol Ref#: 2, Op: “<=”, Mult: 1 Candle3 Vol Ref#: 2, Op: “<=”, Mult: 0.5 All other comparisons (operators) can be left blank if you don’t want to use them! When these rules are met, a bright red “SELL” label will appear right above the bar matching all your conditions. Practical Tips & FAQ for Beginners What does “body” mean? It’s the “true range” of the candle: the difference between open and close. This ignores wicks for simple setups. What does “volume” mean? This is the total trading activity during that candle/bar. Many traders believe that patterns with different volume “meaning” (such as low-volume up bars, or high-volume down bars) signal a meaningful change. What if nothing shows on chart? It just means your current rules are rarely or never matched! Try making your comparisons simpler (maybe just 2-body and 2-volume conditions to start). You can always hit “Reset Settings” to go back to default. Can I use this for both buying and selling? YES! You can detect both bullish (Buy) and bearish (Sell) custom conditions; just switch “Signal Side.” Do I need to know coding? Not at all! Everything is in simple input panels. Creative Use Cases, Example Recipes & Troubleshooting Creative Ways to Use Spotting Reversals Example: Buy when: the newest candle body is LARGER than the previous 3 bars, but ALL volumes are lower than their neighbors. Why? Sometimes, a big candle with surprisingly low volume after a sequence of small bars can signal a reversal. Finding Exhaustion Moves Example: Sell when: the current bar body is twice as big as two bars ago, but volume is half. Why? A very big candle with very little volume compared to similar bars may show the move is “running out of steam.” Custom “Breakout + Confirmation” Patterns Example: Buy when: Candle 0’s body is greater than Candle 2’s by at least 1.5x, Candle 0’s volume is greater than Candle 1 and Candle 2, Candle 1’s volume is less than Candle 0. Why? This could catch strong breakouts but filter out noisy moves. Multi-bar Bias/Squeeze Filter Use “Pattern Candle Count: 4” Set all 4 volume conditions to “<” and each reference to the previous candle. Now, a BUY or SELL only marks when each bar is “dryer”/less active than the last — a classic squeeze or low-volatility buildup. Troubleshooting Guide “I don’t see any Buy/Sell label; is something broken?” Most likely, your rules are too strict or rare! Try using only two comparisons and leave other “Op” inputs blank as a test. Double-check you have enough candles on the chart: you need at least as many bars as your pattern count. “Why does a label appear but not where I expect?” Remember, the script checks your rules for every NEW candle. The candle “0” is always the most recent, then “1” is one bar back, etc. Check the color and type chosen: “Signal Side” must be “Buy” for green, “Sell” for red. “What if I want a more complex pattern?” Stack conditions! You can demand the body/volume of each candle in your window meet a different rule or all follow the same rule in sequence. Mini Glossary — For Newcomers Candle/Bar: Each bar on the chart, shows price movement during a fixed time (e.g., one minute, one hour, one day). Body: The colored (or filled) part of the candle — the open-to-close price range. Volume: How much of the asset was actually traded that candle/bar. Reference Index: When you pick “2” as a reference, it means “the candle two bars ago in the pattern window.” Operator (“Op”): The math symbol used to compare (>, <, =, etc). Signal Side: Whether you want to highlight bullish (“Buy”) or bearish (“Sell”) bars. Tips for Getting More Value Start Simple—try just one or two conditions at first. See what lights up. Slowly add more logic as you get comfortable. Watch the chart live as you change settings. The labels update instantly—this makes strategy design fast and visual! Try flipping your ideas: If a certain pattern doesn’t work for buys, try reversing the direction for possible “sell” setups. Remember: There is NO wrong idea. This indicator is only limited by your creativity—it’s a “strategy playground.” Example Quick-Start Recipes Classic Sell: 4 candles, side = Sell Candle0 Body > Candle2; Candle1 Body > Candle3 Candle0 Vol <= Candle2; Candle1 Vol <= Candle2; Candle3 Vol <= Candle2 × 0.5 Simple Buy After Pause: 3 candles, side = Buy Candle0 Body > Candle1; Candle0 Vol > Candle1 All other Ops blank Low-Volume Pullback for Entry: 4 candles, side = Buy Candle0 Body > Candle2 Candle0 Vol < Candle1; Candle1 Vol < Candle2; Candle2 Vol < Candle3 Final Words Think of this as your “pattern lab.” No code, no guesswork—just experiment, see what the market actually gives, and design your own visual rulebook. If you’re stuck, reset the script to defaults—it’s always safe to start again! If you want more ready-made “recipes” for different strategies/styles, just ask and I’ll send some more setups for you. Happy building—and may your edge always be YOUR edge!
Pine Script®指标
由cnagda3提供
MSFA_LibraryLibrary "MSFA_library" TODO: add library description here getDecimals()   Calculates how many decimals are on the quote price of the current market   Returns: The current decimal places on the market quote price getPipSize(multiplier)   Calculates the pip size of the current market   Parameters:      multiplier (int) : The mintick point multiplier (1 by default, 10 for FX/Crypto/CFD but can be used to override when certain markets require)   Returns: The pip size for the current market truncate(number, decimalPlaces)   Truncates (cuts) excess decimal places   Parameters:      number (float) : The number to truncate      decimalPlaces (simple float) : (default=2) The number of decimal places to truncate to   Returns: The given number truncated to the given decimalPlaces toWhole(number)   Converts pips into whole numbers   Parameters:      number (float) : The pip number to convert into a whole number   Returns: The converted number toPips(number)   Converts whole numbers back into pips   Parameters:      number (float) : The whole number to convert into pips   Returns: The converted number getPctChange(value1, value2, lookback)   Gets the percentage change between 2 float values over a given lookback period   Parameters:      value1 (float) : The first value to reference      value2 (float) : The second value to reference      lookback (int) : The lookback period to analyze   Returns: The percent change over the two values and lookback period random(minRange, maxRange)   Wichmann–Hill Pseudo-Random Number Generator   Parameters:      minRange (float) : The smallest possible number (default: 0)      maxRange (float) : The largest possible number (default: 1)   Returns: A random number between minRange and maxRange bullFib(priceLow, priceHigh, fibRatio)   Calculates a bullish fibonacci value   Parameters:      priceLow (float) : The lowest price point      priceHigh (float) : The highest price point      fibRatio (float) : The fibonacci % ratio to calculate   Returns: The fibonacci value of the given ratio between the two price points bearFib(priceLow, priceHigh, fibRatio)   Calculates a bearish fibonacci value   Parameters:      priceLow (float) : The lowest price point      priceHigh (float) : The highest price point      fibRatio (float) : The fibonacci % ratio to calculate   Returns: The fibonacci value of the given ratio between the two price points getMA(length, maType)   Gets a Moving Average based on type (! MUST BE CALLED ON EVERY TICK TO BE ACCURATE, don't place in scopes)   Parameters:      length (simple int) : The MA period      maType (string) : The type of MA   Returns: A moving average with the given parameters barsAboveMA(lookback, ma)   Counts how many candles are above the MA   Parameters:      lookback (int) : The lookback period to look back over      ma (float) : The moving average to check   Returns: The bar count of how many recent bars are above the MA barsBelowMA(lookback, ma)   Counts how many candles are below the MA   Parameters:      lookback (int) : The lookback period to look back over      ma (float) : The moving average to reference   Returns: The bar count of how many recent bars are below the EMA barsCrossedMA(lookback, ma)   Counts how many times the EMA was crossed recently (based on closing prices)   Parameters:      lookback (int) : The lookback period to look back over      ma (float) : The moving average to reference   Returns: The bar count of how many times price recently crossed the EMA (based on closing prices) getPullbackBarCount(lookback, direction)   Counts how many green & red bars have printed recently (ie. pullback count)   Parameters:      lookback (int) : The lookback period to look back over      direction (int) : The color of the bar to count (1 = Green, -1 = Red)   Returns: The bar count of how many candles have retraced over the given lookback & direction getBodySize()   Gets the current candle's body size (in POINTS, divide by 10 to get pips)   Returns: The current candle's body size in POINTS getTopWickSize()   Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)   Returns: The current candle's top wick size in POINTS getBottomWickSize()   Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)   Returns: The current candle's bottom wick size in POINTS getBodyPercent()   Gets the current candle's body size as a percentage of its entire size including its wicks   Returns: The current candle's body size percentage isHammer(fib, colorMatch)   Checks if the current bar is a hammer candle based on the given parameters   Parameters:      fib (float) : (default=0.382) The fib to base candle body on      colorMatch (bool) : (default=false) Does the candle need to be green? (true/false)   Returns: A boolean - true if the current bar matches the requirements of a hammer candle isStar(fib, colorMatch)   Checks if the current bar is a shooting star candle based on the given parameters   Parameters:      fib (float) : (default=0.382) The fib to base candle body on      colorMatch (bool) : (default=false) Does the candle need to be red? (true/false)   Returns: A boolean - true if the current bar matches the requirements of a shooting star candle isDoji(wickSize, bodySize)   Checks if the current bar is a doji candle based on the given parameters   Parameters:      wickSize (float) : (default=2) The maximum top wick size compared to the bottom (and vice versa)      bodySize (float) : (default=0.05) The maximum body size as a percentage compared to the entire candle size   Returns: A boolean - true if the current bar matches the requirements of a doji candle isBullishEC(allowance, rejectionWickSize, engulfWick)   Checks if the current bar is a bullish engulfing candle   Parameters:      allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)      rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage      engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?   Returns: A boolean - true if the current bar matches the requirements of a bullish engulfing candle isBearishEC(allowance, rejectionWickSize, engulfWick)   Checks if the current bar is a bearish engulfing candle   Parameters:      allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)      rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage      engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?   Returns: A boolean - true if the current bar matches the requirements of a bearish engulfing candle isInsideBar()   Detects inside bars   Returns: Returns true if the current bar is an inside bar isOutsideBar()   Detects outside bars   Returns: Returns true if the current bar is an outside bar barInSession(sess, useFilter)   Determines if the current price bar falls inside the specified session   Parameters:      sess (simple string) : The session to check      useFilter (bool) : (default=true) Whether or not to actually use this filter   Returns: A boolean - true if the current bar falls within the given time session barOutSession(sess, useFilter)   Determines if the current price bar falls outside the specified session   Parameters:      sess (simple string) : The session to check      useFilter (bool) : (default=true) Whether or not to actually use this filter   Returns: A boolean - true if the current bar falls outside the given time session dateFilter(startTime, endTime)   Determines if this bar's time falls within date filter range   Parameters:      startTime (int) : The UNIX date timestamp to begin searching from      endTime (int) : the UNIX date timestamp to stop searching from   Returns: A boolean - true if the current bar falls within the given dates dayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)   Checks if the current bar's day is in the list of given days to analyze   Parameters:      monday (bool) : Should the script analyze this day? (true/false)      tuesday (bool) : Should the script analyze this day? (true/false)      wednesday (bool) : Should the script analyze this day? (true/false)      thursday (bool) : Should the script analyze this day? (true/false)      friday (bool) : Should the script analyze this day? (true/false)      saturday (bool) : Should the script analyze this day? (true/false)      sunday (bool) : Should the script analyze this day? (true/false)   Returns: A boolean - true if the current bar's day is one of the given days atrFilter(atrValue, maxSize)   Parameters:      atrValue (float)      maxSize (float) tradeCount()   Calculate total trade count   Returns: Total closed trade count isLong()   Check if we're currently in a long trade   Returns: True if our position size is positive isShort()   Check if we're currently in a short trade   Returns: True if our position size is negative isFlat()   Check if we're currentlyflat   Returns: True if our position size is zero wonTrade()   Check if this bar falls after a winning trade   Returns: True if we just won a trade lostTrade()   Check if this bar falls after a losing trade   Returns: True if we just lost a trade maxDrawdownRealized()   Gets the max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).   Returns: The max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized). totalPipReturn()   Gets the total amount of pips won/lost (as a whole number)   Returns: Total amount of pips won/lost (as a whole number) longWinCount()   Count how many winning long trades we've had   Returns: Long win count shortWinCount()   Count how many winning short trades we've had   Returns: Short win count longLossCount()   Count how many losing long trades we've had   Returns: Long loss count shortLossCount()   Count how many losing short trades we've had   Returns: Short loss count breakEvenCount(allowanceTicks)   Count how many break-even trades we've had   Parameters:      allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)   Returns: Break-even count longCount()   Count how many long trades we've taken   Returns: Long trade count shortCount()   Count how many short trades we've taken   Returns: Short trade count longWinPercent()   Calculate win rate of long trades   Returns: Long win rate (0-100) shortWinPercent()   Calculate win rate of short trades   Returns: Short win rate (0-100) breakEvenPercent(allowanceTicks)   Calculate break even rate of all trades   Parameters:      allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)   Returns: Break-even win rate (0-100) averageRR()   Calculate average risk:reward   Returns: Average winning trade divided by average losing trade unitsToLots(units)   (Forex) Convert the given unit count to lots (multiples of 100,000)   Parameters:      units (float) : The units to convert into lots   Returns: Units converted to nearest lot size (as float) skipTradeMonteCarlo(chance, debug)   Checks to see if trade should be skipped to emulate rudimentary Monte Carlo simulation   Parameters:      chance (float) : The chance to skip a trade (0-1 or 0-100, function will normalize to 0-1)      debug (bool) : Whether or not to display a label informing of the trade skip   Returns: True if the trade is skipped, false if it's not skipped (idea being to include this function in entry condition validation checks) fillCell(tableID, column, row, title, value, bgcolor, txtcolor, tooltip)   This updates the given table's cell with the given values   Parameters:      tableID (table) : The table ID to update      column (int) : The column to update      row (int) : The row to update      title (string) : The title of this cell      value (string) : The value of this cell      bgcolor (color) : The background color of this cell      txtcolor (color) : The text color of this cell      tooltip (string)   Returns: Nothing.
Pine Script®库
由hphuc0212提供
GEEKSDOBYTE IFVG w/ Buy/Sell Signals1. Inputs & Configuration Swing Lookback (swingLen) Controls how many bars on each side are checked to mark a swing high or swing low (default = 5). Booleans to Toggle Plotting showSwings – Show small triangle markers at swing highs/lows showFVG – Show Fair Value Gap zones showSignals – Show “BUY”/“SELL” labels when price inverts an FVG showDDLine – Show a yellow “DD” line at the close of the inversion bar showCE – Show an orange dashed “CE” line at the midpoint of the gap area 2. Swing High / Low Detection isSwingHigh = ta.pivothigh(high, swingLen, swingLen) Marks a bar as a swing high if its high is higher than the highs of the previous swingLen bars and the next swingLen bars. isSwingLow = ta.pivotlow(low, swingLen, swingLen) Marks a bar as a swing low if its low is lower than the lows of the previous and next swingLen bars. Plotting If showSwings is true, small red downward triangles appear above swing highs, and green upward triangles below swing lows. 3. Fair Value Gap (3‐Bar) Identification A Fair Value Gap (FVG) is defined here using a simple three‐bar logic (sometimes called an “inefficiency” in price): Bullish FVG (bullFVG) Checks if, two bars ago, the low of that bar (low ) is strictly greater than the current bar’s high (high). In other words: bullFVG = low > high Bearish FVG (bearFVG) Checks if, two bars ago, the high of that bar (high ) is strictly less than the current bar’s low (low). In other words: bearFVG = high < low When either condition is true, it identifies a three‐bar “gap” or unfilled imbalance in the market. 4. Drawing FVG Zones If showFVG is enabled, each time a bullish or bearish FVG is detected: Bullish FVG Zone Draws a semi‐transparent green box from the bar two bars ago (where the gap began) at low up to the current bar’s high. Bearish FVG Zone Draws a semi‐transparent red box from the bar two bars ago at high down to the current bar’s low. These colored boxes visually highlight the “fair value imbalance” area on the chart. 5. Inversion (Fill) Detection & Entry Signals An inversion is defined as the price “closing through” that previously drawn FVG: Bullish Inversion (bullInversion) Occurs when a bullish FVG was identified on bar-2 (bullFVG), and on the current bar the close is greater than that old bar-2 low: bullInversion = bullFVG and close > low Bearish Inversion (bearInversion) Occurs when a bearish FVG was identified on bar-2 (bearFVG), and on the current bar the close is lower than that old bar-2 high: bearInversion = bearFVG and close < high When an inversion is true, the indicator optionally draws two lines and a label (depending on input toggles): Draw “DD” Line (yellow, solid) Plots a horizontal yellow line from the current bar’s close price extending five bars forward (bar_index + 5). This is often referred to as a “Demand/Daily Demand” line, marking where price inverted the gap. Draw “CE” Line (orange, dashed) Calculates the midpoint (ce) of the original FVG zone. For a bullish inversion: ce = (low + high) / 2 For a bearish inversion: ce = (high + low) / 2 Plots a horizontal dashed orange line at that midpoint for five bars forward. Plot Label (“BUY” / “SELL”) If showSignals is true, a green “BUY” label is placed at the low of the current bar when a bullish inversion occurs. Likewise, a red “SELL” label at the high of the current bar when a bearish inversion happens. 6. Putting It All Together Swing Markers (Optional): Visually confirm recent swing highs and swing lows with small triangles. FVG Zones (Optional): Highlight areas where price left a 3-bar gap (bullish in green, bearish in red). Inversion Confirmation: Wait for price to close beyond the old FVG boundary. Once that happens, draw the yellow “DD” line at the close, the orange dashed “CE” line at the zone’s midpoint, and place a “BUY” or “SELL” label exactly on that bar. User Controls: All of the above elements can be individually toggled on/off (showSwings, showFVG, showSignals, showDDLine, showCE). In Practice A bullish FVG forms whenever a strong drop leaves a gap in liquidity (three bars ago low > current high). When price later “fills” that gap by closing above the old low, the script signals a potential long entry (BUY), draws a demand line at the closing price, and marks the midpoint of that gap. Conversely, a bearish FVG marks a potential short zone (three bars ago high < current low). When price closes below that gap’s high, it signals a SELL, with similar lines drawn. By combining these elements, the indicator helps users visually identify inefficiencies (FVGs), confirm when price inverts/fills them, and place straightforward buy/sell labels alongside reference lines for trade management.
Pine Script®指标
由RayenGeeksdoByte提供
MirPapa_Library_ICTLibrary "MirPapa_Library_ICT" GetHTFoffsetToLTFoffset(_offset, _chartTf, _htfTf)   GetHTFoffsetToLTFoffset @description Adjust an HTF offset to an LTF offset by calculating the ratio of timeframes.   Parameters:      _offset (int) : int The HTF bar offset (0 means current HTF bar).      _chartTf (string) : string The current chart’s timeframe (e.g., "5", "15", "1D").      _htfTf (string) : string The High Time Frame string (e.g., "60", "1D"). @return int The corresponding LTF bar index. Returns 0 if the result is negative. IsConditionState(_type, _isBull, _level, _open, _close, _open1, _close1, _low1, _low2, _low3, _low4, _high1, _high2, _high3, _high4)   IsConditionState @description Evaluate a condition state based on type for COB, FVG, or FOB. Overloaded: first signature handles COB, second handles FVG/FOB.   Parameters:      _type (string) : string Condition type ("cob", "fvg", "fob").      _isBull (bool) : bool Direction flag: true for bullish, false for bearish.      _level (int) : int Swing level (only used for COB).      _open (float) : float Current bar open price (only for COB).      _close (float) : float Current bar close price (only for COB).      _open1 (float) : float Previous bar open price (only for COB).      _close1 (float) : float Previous bar close price (only for COB).      _low1 (float) : float Low 1 bar ago (only for COB).      _low2 (float) : float Low 2 bars ago (only for COB).      _low3 (float) : float Low 3 bars ago (only for COB).      _low4 (float) : float Low 4 bars ago (only for COB).      _high1 (float) : float High 1 bar ago (only for COB).      _high2 (float) : float High 2 bars ago (only for COB).      _high3 (float) : float High 3 bars ago (only for COB).      _high4 (float) : float High 4 bars ago (only for COB). @return bool True if the specified condition is met, false otherwise. IsConditionState(_type, _isBull, _pricePrev, _priceNow)   IsConditionState @description Evaluate FVG or FOB condition based on price movement.   Parameters:      _type (string) : string Condition type ("fvg", "fob").      _isBull (bool) : bool Direction flag: true for bullish, false for bearish.      _pricePrev (float) : float Previous price (for FVG/FOB).      _priceNow (float) : float Current price (for FVG/FOB). @return bool True if the specified condition is met, false otherwise. IsSwingHighLow(_isBull, _level, _open, _close, _open1, _close1, _low1, _low2, _low3, _low4, _high1, _high2, _high3, _high4)   IsSwingHighLow @description Public wrapper for isSwingHighLow.   Parameters:      _isBull (bool) : bool Direction flag: true for bullish, false for bearish.      _level (int) : int Swing level (1 or 2).      _open (float) : float Current bar open price.      _close (float) : float Current bar close price.      _open1 (float) : float Previous bar open price.      _close1 (float) : float Previous bar close price.      _low1 (float) : float Low 1 bar ago.      _low2 (float) : float Low 2 bars ago.      _low3 (float) : float Low 3 bars ago.      _low4 (float) : float Low 4 bars ago.      _high1 (float) : float High 1 bar ago.      _high2 (float) : float High 2 bars ago.      _high3 (float) : float High 3 bars ago.      _high4 (float) : float High 4 bars ago. @return bool True if swing condition is met, false otherwise. AddBox(_left, _right, _top, _bot, _xloc, _colorBG, _colorBD)   AddBox @description Draw a rectangular box on the chart with specified coordinates and colors.   Parameters:      _left (int) : int Left bar index for the box.      _right (int) : int Right bar index for the box.      _top (float) : float Top price coordinate for the box.      _bot (float) : float Bottom price coordinate for the box.      _xloc (string) : string X-axis location type (e.g., xloc.bar_index).      _colorBG (color) : color Background color for the box.      _colorBD (color) : color Border color for the box. @return box Returns the created box object. Addline(_x, _y, _xloc, _color, _width)   Addline @description Draw a vertical or horizontal line at specified coordinates.   Parameters:      _x (int) : int X-coordinate for start (bar index).      _y (int) : float Y-coordinate for start (price).      _xloc (string) : string X-axis location type (e.g., xloc.bar_index).      _color (color) : color Line color.      _width (int) : int Line width. @return line Returns the created line object. Addline(_x, _y, _xloc, _color, _width)   Parameters:      _x (int)      _y (float)      _xloc (string)      _color (color)      _width (int) Addline(_x1, _y1, _x2, _y2, _xloc, _color, _width)   Parameters:      _x1 (int)      _y1 (int)      _x2 (int)      _y2 (int)      _xloc (string)      _color (color)      _width (int) Addline(_x1, _y1, _x2, _y2, _xloc, _color, _width)   Parameters:      _x1 (int)      _y1 (int)      _x2 (int)      _y2 (float)      _xloc (string)      _color (color)      _width (int) Addline(_x1, _y1, _x2, _y2, _xloc, _color, _width)   Parameters:      _x1 (int)      _y1 (float)      _x2 (int)      _y2 (int)      _xloc (string)      _color (color)      _width (int) Addline(_x1, _y1, _x2, _y2, _xloc, _color, _width)   Parameters:      _x1 (int)      _y1 (float)      _x2 (int)      _y2 (float)      _xloc (string)      _color (color)      _width (int) AddlineMid(_type, _left, _right, _top, _bot, _xloc, _color, _width)   AddlineMid @description Draw a midline between top and bottom for FVG or FOB types.   Parameters:      _type (string) : string Type identifier: "fvg" or "fob".      _left (int) : int Left bar index for midline start.      _right (int) : int Right bar index for midline end.      _top (float) : float Top price of the region.      _bot (float) : float Bottom price of the region.      _xloc (string) : string X-axis location type (e.g., xloc.bar_index).      _color (color) : color Line color.      _width (int) : int Line width. @return line or na Returns the created line or na if type is not recognized. GetHtfFromLabel(_label)   GetHtfFromLabel @description Convert a Korean HTF label into a Pine Script timeframe string via handler library.   Parameters:      _label (string) : string The Korean label (e.g., "5분", "1시간"). @return string Returns the corresponding Pine Script timeframe (e.g., "5", "60"). IsChartTFcomparisonHTF(_chartTf, _htfTf)   IsChartTFcomparisonHTF @description Determine whether a given HTF is greater than or equal to the current chart timeframe.   Parameters:      _chartTf (string) : string Current chart timeframe (e.g., "5", "15", "1D").      _htfTf (string) : string HTF timeframe (e.g., "60", "1D"). @return bool True if HTF ≥ chartTF, false otherwise. CreateBoxData(_type, _isBull, _useLine, _top, _bot, _xloc, _colorBG, _colorBD, _offset, _htfTf, htfBarIdx, _basePoint)   CreateBoxData @description Create and draw a box and optional midline for given type and parameters. Returns success flag and BoxData.   Parameters:      _type (string) : string Type identifier: "fvg", "fob", "cob", or "sweep".      _isBull (bool) : bool Direction flag: true for bullish, false for bearish.      _useLine (bool) : bool Whether to draw a midline inside the box.      _top (float) : float Top price of the box region.      _bot (float) : float Bottom price of the box region.      _xloc (string) : string X-axis location type (e.g., xloc.bar_index).      _colorBG (color) : color Background color for the box.      _colorBD (color) : color Border color for the box.      _offset (int) : int HTF bar offset (0 means current HTF bar).      _htfTf (string) : string HTF timeframe string (e.g., "60", "1D").      htfBarIdx (int) : int HTF bar_index (passed from HTF request).      _basePoint (float) : float Base point for breakout checks. @return tuple(bool, BoxData) Returns a boolean indicating success and the created BoxData struct. ProcessBoxDatas(_datas, _useMidLine, _closeCount, _colorClose)   ProcessBoxDatas @description Process an array of BoxData structs: extend, record volume, update stage, and finalize boxes.   Parameters:      _datas (array) : array Array of BoxData objects to process.      _useMidLine (bool) : bool Whether to update the midline endpoint.      _closeCount (int) : int Number of touches required to close the box.      _colorClose (color) : color Color to apply when a box closes. @return void No return value; updates are in-place. BoxData   Fields:      _isActive (series bool)      _isBull (series bool)      _box (series box)      _line (series line)      _basePoint (series float)      _boxTop (series float)      _boxBot (series float)      _stage (series int)      _isStay (series bool)      _volBuy (series float)      _volSell (series float)      _result (series string) LineData   Fields:      _isActive (series bool)      _isBull (series bool)      _line (series line)      _basePoint (series float)      _stage (series int)      _isStay (series bool)      _result (series string)
Pine Script®库
由goodia提供
LinearRegressionLibrary "LinearRegression" Calculates a variety of linear regression and deviation types, with optional emphasis weighting. Additionally, multiple of slope and Pearson’s R calculations. calcSlope(_src, _len, _condition)   Calculates the slope of a linear regression over the specified length.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The length of the lookback period for the linear regression.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.   Returns: (float) The slope of the linear regression. calcReg(_src, _len, _condition)   Calculates a basic linear regression, returning y1, y2, slope, and average.   Parameters:      _src (float) : (float) The source data series.      _len (int) : (int) The length of the lookback period.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: (float ) An array of 4 values: . calcRegStandard(_src, _len, _emphasis, _condition)   Calculates an Standard linear regression with optional emphasis.   Parameters:      _src (float) : (series float) The source data series.      _len (int) : (int) The length of the lookback period.      _emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: (float ) . calcRegRidge(_src, _len, lambda, _emphasis, _condition)   Calculates a ridge regression with optional emphasis.   Parameters:      _src (float) : (float) The source data series.      _len (int) : (int) The length of the lookback period.      lambda (float) : (float) The ridge regularization parameter.      _emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: (float ) . calcRegLasso(_src, _len, lambda, _emphasis, _condition)   Calculates a Lasso regression with optional emphasis.   Parameters:      _src (float) : (float) The source data series.      _len (int) : (int) The length of the lookback period.      lambda (float) : (float) The Lasso regularization parameter.      _emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: (float ) . calcElasticNetLinReg(_src, _len, lambda1, lambda2, _emphasis, _condition)   Calculates an Elastic Net regression with optional emphasis.   Parameters:      _src (float) : (float) The source data series.      _len (int) : (int) The length of the lookback period.      lambda1 (float) : (float) L1 regularization parameter (Lasso).      lambda2 (float) : (float) L2 regularization parameter (Ridge).      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: (float ) . calcRegHuber(_src, _len, delta, iterations, _emphasis, _condition)   Calculates a Huber regression using Iteratively Reweighted Least Squares (IRLS).   Parameters:      _src (float) : (float) The source data series.      _len (int) : (int) The length of the lookback period.      delta (float) : (float) Huber threshold parameter.      iterations (int) : (int) Number of IRLS iterations.      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: (float ) . calcRegLAD(_src, _len, iterations, _emphasis, _condition)   Calculates a Least Absolute Deviations (LAD) regression via IRLS.   Parameters:      _src (float) : (float) The source data series.      _len (int) : (int) The length of the lookback period.      iterations (int) : (int) Number of IRLS iterations for LAD.      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: (float ) . calcRegBayesian(_src, _len, priorMean, priorSpan, sigma, _emphasis, _condition)   Calculates a Bayesian linear regression with optional emphasis.   Parameters:      _src (float) : (float) The source data series.      _len (int) : (int) The length of the lookback period.      priorMean (float) : (float) The prior mean for the slope.      priorSpan (float) : (float) The prior variance (or span) for the slope.      sigma (float) : (float) The assumed standard deviation of residuals.      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: (float ) . calcRFromLinReg(_src, _len, _slope, _average, _y1, _condition)   Calculates the Pearson correlation coefficient (R) based on linear regression parameters.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The length of the lookback period.      _slope (float) : (float) The slope of the linear regression.      _average (float) : (float) The average value of the source data series.      _y1 (float) : (float) The starting point (y-intercept of the oldest bar) for the linear regression.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.   Returns: (float) The Pearson correlation coefficient (R) adjusted for the direction of the slope. calcRFromSource(_src, _len, _condition)   Calculates the correlation coefficient (R) using a specified length and source data.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The length of the lookback period.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.   Returns: (float) The correlation coefficient (R). calcSlopeLengthZero(_src, _len, _minLen, _step, _condition)   Identifies the length at which the slope is flattest (closest to zero).   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The maximum lookback length to consider (minimum of 2).      _minLen (int) : (int) The minimum length to start from (cannot exceed the max length).      _step (int) : (int) The increment step for lengths.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.   Returns: (int) The length at which the slope is flattest. calcSlopeLengthHighest(_src, _len, _minLen, _step, _condition)   Identifies the length at which the slope is highest.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The maximum lookback length (minimum of 2).      _minLen (int) : (int) The minimum length to start from.      _step (int) : (int) The step for incrementing lengths.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.   Returns: (int) The length at which the slope is highest. calcSlopeLengthLowest(_src, _len, _minLen, _step, _condition)   Identifies the length at which the slope is lowest.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The maximum lookback length (minimum of 2).      _minLen (int) : (int) The minimum length to start from.      _step (int) : (int) The step for incrementing lengths.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.   Returns: (int) The length at which the slope is lowest. calcSlopeLengthAbsolute(_src, _len, _minLen, _step, _condition)   Identifies the length at which the absolute slope value is highest.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The maximum lookback length (minimum of 2).      _minLen (int) : (int) The minimum length to start from.      _step (int) : (int) The step for incrementing lengths.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.   Returns: (int) The length at which the absolute slope value is highest. calcRLengthZero(_src, _len, _minLen, _step, _condition)   Identifies the length with the lowest absolute R value.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The maximum lookback length (minimum of 2).      _minLen (int) : (int) The minimum length to start from.      _step (int) : (int) The step for incrementing lengths.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.   Returns: (int) The length with the lowest absolute R value. calcRLengthHighest(_src, _len, _minLen, _step, _condition)   Identifies the length with the highest R value.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The maximum lookback length (minimum of 2).      _minLen (int) : (int) The minimum length to start from.      _step (int) : (int) The step for incrementing lengths.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.   Returns: (int) The length with the highest R value. calcRLengthLowest(_src, _len, _minLen, _step, _condition)   Identifies the length with the lowest R value.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The maximum lookback length (minimum of 2).      _minLen (int) : (int) The minimum length to start from.      _step (int) : (int) The step for incrementing lengths.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.   Returns: (int) The length with the lowest R value. calcRLengthAbsolute(_src, _len, _minLen, _step, _condition)   Identifies the length with the highest absolute R value.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The maximum lookback length (minimum of 2).      _minLen (int) : (int) The minimum length to start from.      _step (int) : (int) The step for incrementing lengths.      _condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.   Returns: (int) The length with the highest absolute R value. calcDevReverse(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)   Calculates the regressive linear deviation in reverse order, with optional emphasis on recent data.   Parameters:      _src (float) : (float) The source data.      _len (int) : (int) The length of the lookback period.      _slope (float) : (float) The slope of the linear regression.      _y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.      _inputDev (float) : (float) The input deviation multiplier.      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: A 2-element tuple: . calcDevForward(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)   Calculates the progressive linear deviation in forward order (oldest to most recent bar), with optional emphasis.   Parameters:      _src (float) : (float) The source data array, where _src is oldest and _src is most recent.      _len (int) : (int) The length of the lookback period.      _slope (float) : (float) The slope of the linear regression.      _y1 (float) : (float) The y-intercept of the linear regression (value at the most recent bar, adjusted by slope).      _inputDev (float) : (float) The input deviation multiplier.      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: A 2-element tuple: . calcDevBalanced(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)   Calculates the balanced linear deviation with optional emphasis on recent or older data.   Parameters:      _src (float) : (float) Source data array, where _src is the most recent and _src is the oldest.      _len (int) : (int) The length of the lookback period.      _slope (float) : (float) The slope of the linear regression.      _y1 (float) : (float) The y-intercept of the linear regression (value at the oldest bar).      _inputDev (float) : (float) The input deviation multiplier.      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: A 2-element tuple: . calcDevMean(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)   Calculates the mean absolute deviation from a forward-applied linear trend (oldest to most recent), with optional emphasis.   Parameters:      _src (float) : (float) The source data array, where _src is the most recent and _src is the oldest.      _len (int) : (int) The length of the lookback period.      _slope (float) : (float) The slope of the linear regression.      _y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.      _inputDev (float) : (float) The input deviation multiplier.      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: A 2-element tuple: . calcDevMedian(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)   Calculates the median absolute deviation with optional emphasis on recent data.   Parameters:      _src (float) : (float) The source data array (index 0 = oldest, index _len - 1 = most recent).      _len (int) : (int) The length of the lookback period.      _slope (float) : (float) The slope of the linear regression.      _y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.      _inputDev (float) : (float) The deviation multiplier.      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: calcDevPercent(_y1, _inputDev, _condition)   Calculates the percent deviation from a given value and a specified percentage.   Parameters:      _y1 (float) : (float) The base value from which to calculate deviation.      _inputDev (float) : (float) The deviation percentage.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: A 2-element tuple: . calcDevFitted(_len, _slope, _y1, _emphasis, _condition)   Calculates the weighted fitted deviation based on high and low series data, showing max deviation, with optional emphasis.   Parameters:      _len (int) : (int) The length of the lookback period.      _slope (float) : (float) The slope of the linear regression.      _y1 (float) : (float) The Y-intercept (oldest bar) of the linear regression.      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: A 2-element tuple: . calcDevATR(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)   Calculates an ATR-style deviation with optional emphasis on recent data.   Parameters:      _src (float) : (float) The source data (typically close).      _len (int) : (int) The length of the lookback period.      _slope (float) : (float) The slope of the linear regression.      _y1 (float) : (float) The Y-intercept (oldest bar) of the linear regression.      _inputDev (float) : (float) The input deviation multiplier.      _emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.      _condition (bool) : (bool) Flag to enable calculation (true = calculate).   Returns: A 2-element tuple: . calcPricePositionPercent(_top, _bot, _src)   Calculates the percent position of a price within a linear regression channel. Top=100%, Bottom=0%.   Parameters:      _top (float) : (float) The top (positive) deviation, corresponding to 100%.      _bot (float) : (float) The bottom (negative) deviation, corresponding to 0%.      _src (float) : (float) The source price.   Returns: (float) The percent position within the channel. plotLinReg(_len, _y1, _y2, _slope, _devTop, _devBot, _scaleTypeLog, _lineWidth, _extendLines, _channelStyle, _colorFill, _colUpLine, _colDnLine, _colUpFill, _colDnFill)   Plots the linear regression line and its deviations, with configurable styles and fill.   Parameters:      _len (int) : (int) The lookback period for the linear regression.      _y1 (float) : (float) The starting y-value of the regression line.      _y2 (float) : (float) The ending y-value of the regression line.      _slope (float) : (float) The slope of the regression line (used to determine line color).      _devTop (float) : (float) The top deviation to add to the line.      _devBot (float) : (float) The bottom deviation to subtract from the line.      _scaleTypeLog (bool) : (bool) Use a log scale if true; otherwise, linear scale.      _lineWidth (int) : (int) The width of the plotted lines.      _extendLines (string) : (string) How lines should extend (none, left, right, both).      _channelStyle (string) : (string) The style of the channel lines (solid, dashed, dotted).      _colorFill (bool) : (bool) Whether to fill the space between the top and bottom deviation lines.      _colUpLine (color) : (color) Line color when slope is positive.      _colDnLine (color) : (color) Line color when slope is negative.      _colUpFill (color) : (color) Fill color when slope is positive.      _colDnFill (color) : (color) Fill color when slope is negative.
Pine Script®库
由TanHef提供
2
Exposure Oscillator (Cumulative 0 to ±100%) Exposure Oscillator (Cumulative 0 to ±100%) This Pine Script indicator plots an "Exposure Oscillator" on the chart, which tracks the cumulative market exposure from a range of technical buy and sell signals. The exposure is measured on a scale from -100% (maximum short exposure) to +100% (maximum long exposure), helping traders assess the strength of their position in the market. It provides an intuitive visual cue to aid decision-making for trend-following strategies. Buy Signals (Increase Exposure Score by +10%) Buy Signal 1 (Cross Above 21 EMA): This signal is triggered when the price crosses above the 21-period Exponential Moving Average (EMA), where the current bar closes above the EMA21, and the previous bar closed below the EMA21. This indicates a potential upward price movement as the market shifts into a bullish trend. buySignal1 = ta.crossover(close, ema21) Buy Signal 2 (Trending Above 21 EMA): This signal is triggered when the price closes above the 21-period EMA for each of the last 5 bars, indicating a sustained bullish trend. It confirms that the price is consistently above the EMA21 for a significant period. buySignal2 = ta.barssince(close <= ema21) > 5 Buy Signal 3 (Living Above 21 EMA): This signal is triggered when the price has closed above the 21-period EMA for each of the last 15 bars, demonstrating a strong, prolonged uptrend. buySignal3 = ta.barssince(close <= ema21) > 15 Buy Signal 4 (Cross Above 50 SMA): This signal is triggered when the price crosses above the 50-period Simple Moving Average (SMA), where the current bar closes above the 50 SMA, and the previous bar closed below it. It indicates a shift toward bullish momentum. buySignal4 = ta.crossover(close, sma50) Buy Signal 5 (Cross Above 200 SMA): This signal is triggered when the price crosses above the 200-period Simple Moving Average (SMA), where the current bar closes above the 200 SMA, and the previous bar closed below it. This suggests a long-term bullish trend. buySignal5 = ta.crossover(close, sma200) Buy Signal 6 (Low Above 50 SMA): This signal is true when the lowest price of the current bar is above the 50-period SMA, indicating strong bullish pressure as the price maintains itself above the moving average. buySignal6 = low > sma50 Buy Signal 7 (Accumulation Day): An accumulation day occurs when the closing price is in the upper half of the daily range (greater than 50%) and the volume is larger than the previous bar's volume, suggesting buying pressure and accumulation. buySignal7 = (close - low) / (high - low) > 0.5 and volume > volume Buy Signal 8 (Higher High): This signal occurs when the current bar’s high exceeds the highest high of the previous 14 bars, indicating a breakout or strong upward momentum. buySignal8 = high > ta.highest(high, 14) Buy Signal 9 (Key Reversal Bar): This signal is generated when the stock opens below the low of the previous bar but rallies to close above the previous bar’s high, signaling a potential reversal from bearish to bullish. buySignal9 = open < low and close > high Buy Signal 10 (Distribution Day Fall Off): This signal is triggered when a distribution day (a day with high volume and a close near the low of the range) "falls off" the rolling 25-bar period, indicating the end of a bearish trend or selling pressure. buySignal10 = ta.barssince(close < sma50 and close < sma50) > 25 Sell Signals (Decrease Exposure Score by -10%) Sell Signal 1 (Cross Below 21 EMA): This signal is triggered when the price crosses below the 21-period Exponential Moving Average (EMA), where the current bar closes below the EMA21, and the previous bar closed above it. It suggests that the market may be shifting from a bullish trend to a bearish trend. sellSignal1 = ta.crossunder(close, ema21) Sell Signal 2 (Trending Below 21 EMA): This signal is triggered when the price closes below the 21-period EMA for each of the last 5 bars, indicating a sustained bearish trend. sellSignal2 = ta.barssince(close >= ema21) > 5 Sell Signal 3 (Living Below 21 EMA): This signal is triggered when the price has closed below the 21-period EMA for each of the last 15 bars, suggesting a strong downtrend. sellSignal3 = ta.barssince(close >= ema21) > 15 Sell Signal 4 (Cross Below 50 SMA): This signal is triggered when the price crosses below the 50-period Simple Moving Average (SMA), where the current bar closes below the 50 SMA, and the previous bar closed above it. It indicates the start of a bearish trend. sellSignal4 = ta.crossunder(close, sma50) Sell Signal 5 (Cross Below 200 SMA): This signal is triggered when the price crosses below the 200-period Simple Moving Average (SMA), where the current bar closes below the 200 SMA, and the previous bar closed above it. It indicates a long-term bearish trend. sellSignal5 = ta.crossunder(close, sma200) Sell Signal 6 (High Below 50 SMA): This signal is true when the highest price of the current bar is below the 50-period SMA, indicating weak bullishness or a potential bearish reversal. sellSignal6 = high < sma50 Sell Signal 7 (Distribution Day): A distribution day is identified when the closing range of a bar is less than 50% and the volume is larger than the previous bar's volume, suggesting that selling pressure is increasing. sellSignal7 = (close - low) / (high - low) < 0.5 and volume > volume Sell Signal 8 (Lower Low): This signal occurs when the current bar's low is less than the lowest low of the previous 14 bars, indicating a breakdown or strong downward momentum. sellSignal8 = low < ta.lowest(low, 14) Sell Signal 9 (Downside Reversal Bar): A downside reversal bar occurs when the stock opens above the previous bar's high but falls to close below the previous bar’s low, signaling a reversal from bullish to bearish. sellSignal9 = open > high and close < low Sell Signal 10 (Distribution Cluster): This signal is triggered when a distribution day occurs three times in the rolling 7-bar period, indicating significant selling pressure. sellSignal10 = ta.valuewhen((close < low) and volume > volume , 1, 7) >= 3 Theme Mode: Users can select the theme mode (Auto, Dark, or Light) to match the chart's background or to manually choose a light or dark theme for the oscillator's appearance. Exposure Score Calculation: The script calculates a cumulative exposure score based on a series of buy and sell signals. Buy signals increase the exposure score, while sell signals decrease it. Each signal impacts the score by ±10%. Signal Conditions: The buy and sell signals are derived from multiple conditions, including crossovers with moving averages (EMA21, SMA50, SMA200), trend behavior, and price/volume analysis. Oscillator Visualization: The exposure score is visualized as a line on the chart, changing color based on whether the exposure is positive (long position) or negative (short position). It is limited to the range of -100% to +100%. Position Type: The indicator also indicates the position type based on the exposure score, labeling it as "Long," "Short," or "Neutral." Horizontal Lines: Reference lines at 0%, 100%, and -100% visually mark neutral, increasing long, and increasing short exposure levels. Exposure Table: A table displays the current exposure level (in percentage) and position type ("Long," "Short," or "Neutral"), updated dynamically based on the oscillator’s value. Inputs: Theme Mode: Choose "Auto" to use the default chart theme, or manually select "Dark" or "Light." Usage: This oscillator is designed to help traders track market sentiment, gauge exposure levels, and manage risk. It can be used for long-term trend-following strategies or short-term trades based on moving average crossovers and volume analysis. The oscillator operates in conjunction with the chart’s price action and provides a visual representation of the market’s current trend strength and exposure. Important Considerations: Risk Management: While the exposure score provides valuable insight, it should be combined with other risk management tools and analysis for optimal trading decisions. Signal Sensitivity: The accuracy and effectiveness of the signals depend on market conditions and may require adjustments based on the user’s trading strategy or timeframe. Disclaimer: This script is for educational purposes only. Trading involves significant risk, and users should carefully evaluate all market conditions and apply appropriate risk management strategies before using this tool in live trading environments.
Pine Script®指标
由starshiptrade提供
JordanSwindenLibraryLibrary "JordanSwindenLibrary" TODO: add library description here getDecimals()   Calculates how many decimals are on the quote price of the current market   Returns: The current decimal places on the market quote price getPipSize(multiplier)   Calculates the pip size of the current market   Parameters:      multiplier (int) : The mintick point multiplier (1 by default, 10 for FX/Crypto/CFD but can be used to override when certain markets require)   Returns: The pip size for the current market truncate(number, decimalPlaces)   Truncates (cuts) excess decimal places   Parameters:      number (float) : The number to truncate      decimalPlaces (simple float) : (default=2) The number of decimal places to truncate to   Returns: The given number truncated to the given decimalPlaces toWhole(number)   Converts pips into whole numbers   Parameters:      number (float) : The pip number to convert into a whole number   Returns: The converted number toPips(number)   Converts whole numbers back into pips   Parameters:      number (float) : The whole number to convert into pips   Returns: The converted number getPctChange(value1, value2, lookback)   Gets the percentage change between 2 float values over a given lookback period   Parameters:      value1 (float) : The first value to reference      value2 (float) : The second value to reference      lookback (int) : The lookback period to analyze   Returns: The percent change over the two values and lookback period random(minRange, maxRange)   Wichmann–Hill Pseudo-Random Number Generator   Parameters:      minRange (float) : The smallest possible number (default: 0)      maxRange (float) : The largest possible number (default: 1)   Returns: A random number between minRange and maxRange bullFib(priceLow, priceHigh, fibRatio)   Calculates a bullish fibonacci value   Parameters:      priceLow (float) : The lowest price point      priceHigh (float) : The highest price point      fibRatio (float) : The fibonacci % ratio to calculate   Returns: The fibonacci value of the given ratio between the two price points bearFib(priceLow, priceHigh, fibRatio)   Calculates a bearish fibonacci value   Parameters:      priceLow (float) : The lowest price point      priceHigh (float) : The highest price point      fibRatio (float) : The fibonacci % ratio to calculate   Returns: The fibonacci value of the given ratio between the two price points getMA(length, maType)   Gets a Moving Average based on type (! MUST BE CALLED ON EVERY TICK TO BE ACCURATE, don't place in scopes)   Parameters:      length (simple int) : The MA period      maType (string) : The type of MA   Returns: A moving average with the given parameters barsAboveMA(lookback, ma)   Counts how many candles are above the MA   Parameters:      lookback (int) : The lookback period to look back over      ma (float) : The moving average to check   Returns: The bar count of how many recent bars are above the MA barsBelowMA(lookback, ma)   Counts how many candles are below the MA   Parameters:      lookback (int) : The lookback period to look back over      ma (float) : The moving average to reference   Returns: The bar count of how many recent bars are below the EMA barsCrossedMA(lookback, ma)   Counts how many times the EMA was crossed recently (based on closing prices)   Parameters:      lookback (int) : The lookback period to look back over      ma (float) : The moving average to reference   Returns: The bar count of how many times price recently crossed the EMA (based on closing prices) getPullbackBarCount(lookback, direction)   Counts how many green & red bars have printed recently (ie. pullback count)   Parameters:      lookback (int) : The lookback period to look back over      direction (int) : The color of the bar to count (1 = Green, -1 = Red)   Returns: The bar count of how many candles have retraced over the given lookback & direction getBodySize()   Gets the current candle's body size (in POINTS, divide by 10 to get pips)   Returns: The current candle's body size in POINTS getTopWickSize()   Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)   Returns: The current candle's top wick size in POINTS getBottomWickSize()   Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)   Returns: The current candle's bottom wick size in POINTS getBodyPercent()   Gets the current candle's body size as a percentage of its entire size including its wicks   Returns: The current candle's body size percentage isHammer(fib, colorMatch)   Checks if the current bar is a hammer candle based on the given parameters   Parameters:      fib (float) : (default=0.382) The fib to base candle body on      colorMatch (bool) : (default=false) Does the candle need to be green? (true/false)   Returns: A boolean - true if the current bar matches the requirements of a hammer candle isStar(fib, colorMatch)   Checks if the current bar is a shooting star candle based on the given parameters   Parameters:      fib (float) : (default=0.382) The fib to base candle body on      colorMatch (bool) : (default=false) Does the candle need to be red? (true/false)   Returns: A boolean - true if the current bar matches the requirements of a shooting star candle isDoji(wickSize, bodySize)   Checks if the current bar is a doji candle based on the given parameters   Parameters:      wickSize (float) : (default=2) The maximum top wick size compared to the bottom (and vice versa)      bodySize (float) : (default=0.05) The maximum body size as a percentage compared to the entire candle size   Returns: A boolean - true if the current bar matches the requirements of a doji candle isBullishEC(allowance, rejectionWickSize, engulfWick)   Checks if the current bar is a bullish engulfing candle   Parameters:      allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)      rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage      engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?   Returns: A boolean - true if the current bar matches the requirements of a bullish engulfing candle isBearishEC(allowance, rejectionWickSize, engulfWick)   Checks if the current bar is a bearish engulfing candle   Parameters:      allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)      rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage      engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?   Returns: A boolean - true if the current bar matches the requirements of a bearish engulfing candle isInsideBar()   Detects inside bars   Returns: Returns true if the current bar is an inside bar isOutsideBar()   Detects outside bars   Returns: Returns true if the current bar is an outside bar barInSession(sess, useFilter)   Determines if the current price bar falls inside the specified session   Parameters:      sess (simple string) : The session to check      useFilter (bool) : (default=true) Whether or not to actually use this filter   Returns: A boolean - true if the current bar falls within the given time session barOutSession(sess, useFilter)   Determines if the current price bar falls outside the specified session   Parameters:      sess (simple string) : The session to check      useFilter (bool) : (default=true) Whether or not to actually use this filter   Returns: A boolean - true if the current bar falls outside the given time session dateFilter(startTime, endTime)   Determines if this bar's time falls within date filter range   Parameters:      startTime (int) : The UNIX date timestamp to begin searching from      endTime (int) : the UNIX date timestamp to stop searching from   Returns: A boolean - true if the current bar falls within the given dates dayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)   Checks if the current bar's day is in the list of given days to analyze   Parameters:      monday (bool) : Should the script analyze this day? (true/false)      tuesday (bool) : Should the script analyze this day? (true/false)      wednesday (bool) : Should the script analyze this day? (true/false)      thursday (bool) : Should the script analyze this day? (true/false)      friday (bool) : Should the script analyze this day? (true/false)      saturday (bool) : Should the script analyze this day? (true/false)      sunday (bool) : Should the script analyze this day? (true/false)   Returns: A boolean - true if the current bar's day is one of the given days atrFilter(atrValue, maxSize)   Parameters:      atrValue (float)      maxSize (float) tradeCount()   Calculate total trade count   Returns: Total closed trade count isLong()   Check if we're currently in a long trade   Returns: True if our position size is positive isShort()   Check if we're currently in a short trade   Returns: True if our position size is negative isFlat()   Check if we're currentlyflat   Returns: True if our position size is zero wonTrade()   Check if this bar falls after a winning trade   Returns: True if we just won a trade lostTrade()   Check if this bar falls after a losing trade   Returns: True if we just lost a trade maxDrawdownRealized()   Gets the max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).   Returns: The max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized). totalPipReturn()   Gets the total amount of pips won/lost (as a whole number)   Returns: Total amount of pips won/lost (as a whole number) longWinCount()   Count how many winning long trades we've had   Returns: Long win count shortWinCount()   Count how many winning short trades we've had   Returns: Short win count longLossCount()   Count how many losing long trades we've had   Returns: Long loss count shortLossCount()   Count how many losing short trades we've had   Returns: Short loss count breakEvenCount(allowanceTicks)   Count how many break-even trades we've had   Parameters:      allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)   Returns: Break-even count longCount()   Count how many long trades we've taken   Returns: Long trade count shortCount()   Count how many short trades we've taken   Returns: Short trade count longWinPercent()   Calculate win rate of long trades   Returns: Long win rate (0-100) shortWinPercent()   Calculate win rate of short trades   Returns: Short win rate (0-100) breakEvenPercent(allowanceTicks)   Calculate break even rate of all trades   Parameters:      allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)   Returns: Break-even win rate (0-100) averageRR()   Calculate average risk:reward   Returns: Average winning trade divided by average losing trade unitsToLots(units)   (Forex) Convert the given unit count to lots (multiples of 100,000)   Parameters:      units (float) : The units to convert into lots   Returns: Units converted to nearest lot size (as float) getFxPositionSize(balance, risk, stopLossPips, fxRate, lots)   (Forex) Calculate fixed-fractional position size based on given parameters   Parameters:      balance (float) : The account balance      risk (float) : The % risk (whole number)      stopLossPips (float) : Pip distance to base risk on      fxRate (float) : The conversion currency rate (more info below in library documentation)      lots (bool) : Whether or not to return the position size in lots rather than units (true by default)   Returns: Units/lots to enter into "qty=" parameter of strategy entry function EXAMPLE USAGE: string conversionCurrencyPair = (strategy.account_currency == syminfo.currency ? syminfo.tickerid : strategy.account_currency + syminfo.currency) float fx_rate = request.security(conversionCurrencyPair, timeframe.period, close ) if (longCondition) strategy.entry("Long", strategy.long, qty=zen.getFxPositionSize(strategy.equity, 1, stopLossPipsWholeNumber, fx_rate, true)) skipTradeMonteCarlo(chance, debug)   Checks to see if trade should be skipped to emulate rudimentary Monte Carlo simulation   Parameters:      chance (float) : The chance to skip a trade (0-1 or 0-100, function will normalize to 0-1)      debug (bool) : Whether or not to display a label informing of the trade skip   Returns: True if the trade is skipped, false if it's not skipped (idea being to include this function in entry condition validation checks) fillCell(tableID, column, row, title, value, bgcolor, txtcolor, tooltip)   This updates the given table's cell with the given values   Parameters:      tableID (table) : The table ID to update      column (int) : The column to update      row (int) : The row to update      title (string) : The title of this cell      value (string) : The value of this cell      bgcolor (color) : The background color of this cell      txtcolor (color) : The text color of this cell      tooltip (string)   Returns: Nothing.
Pine Script®库
由jordanswinden提供
Auto Volume Spread Analysis (VSA) [TANHEF]Auto Volume Spread Analysis (visible volume and spread bars auto-scaled): Understanding Market Intentions through the Interpretation of Volume and Price Movements. All the sections below contain the same descriptions as my other indicator "Volume Spread Analysis" with the exception of 'Auto Scaling'. █ Auto-Scaling This indicator auto-scales spread bars to match the visible volume bars, unlike the previous "Volume Spread Analysis " version which limited the number of visible spread bars to a fixed count. The auto-scaling feature allows for easier navigation through historical data, enabling both more historical spread bars to be viewed and more historical VSA pattern labels being displayed without requiring using the bar replay tool. Please note that this indicator’s auto-scaling feature recalculates the visible bars on the chart, causing the indicator to reload whenever the chart is moved. Auto-scaled spread bars have two display options (set via 'Spread Bars Method' setting): Lines: a bar lookback limit of 500 bars. Polylines: no bar lookback limit as only plotted on visible bars on chart, which uses multiple polylines are used. █ Simple Explanation: The Volume Spread Analysis (VSA) indicator is a comprehensive tool that helps traders identify key market patterns and trends based on volume and spread data. This indicator highlights significant VSA patterns and provides insights into market behavior through color-coded volume/spread bars and identification of bars indicating strength, weakness, and neutrality between buyers and sellers. It also includes powerful volume and spread forecasting capabilities. █ Laws of Volume Spread Analysis (VSA): The origin of VSA begins with Richard Wyckoff, a pivotal figure in its development. Wyckoff made significant contributions to trading theory, including the formulation of three basic laws: The Law of Supply and Demand: This fundamental law states that supply and demand balance each other over time. High demand and low supply lead to rising prices until demand falls to a level where supply can meet it. Conversely, low demand and high supply cause prices to fall until demand increases enough to absorb the excess supply. The Law of Cause and Effect: This law assumes that a 'cause' will result in an 'effect' proportional to the 'cause'. A strong 'cause' will lead to a strong trend (effect), while a weak 'cause' will lead to a weak trend. The Law of Effort vs. Result: This law asserts that the result should reflect the effort exerted. In trading terms, a large volume should result in a significant price move (spread). If the spread is small, the volume should also be small. Any deviation from this pattern is considered an anomaly. █ Volume and Spread Analysis Bars: Display: Volume and spread bars that consist of color coded levels, with the spread bars scaled to match the volume bars. A displayable table (Legend) of bar colors and levels can give context and clarify to each volume/spread bar. Calculation: Levels are calculated using multipliers applied to moving averages to represent key levels based on historical data: low, normal, high, ultra. This method smooths out short-term fluctuations and focuses on longer-term trends. Low Level: Indicates reduced volatility and market interest. Normal Level: Reflects typical market activity and volatility. High Level: Indicates increased activity and volatility. Ultra Level: Identifies extreme levels of activity and volatility. This illustrates the appearance of Volume and Spread bars when scaled and plotted together: █ Forecasting Capabilities: Display: Forecasted volume and spread levels using predictive models. Calculation: Volume and Spread prediction calculations differ as volume is linear and spread is non-linear. Volume Forecast (Linear Forecasting): Predicts future volume based on current volume rate and bar time till close. Spread Forecast (Non-Linear Dynamic Forecasting): Predicts future spread using a dynamic multiplier, less near midpoint (consolidation) and more near low or high (trending), reflecting non-linear expansion. Moving Averages: In forecasting, moving averages utilize forecasted levels instead of actual levels to ensure the correct level is forecasted (low, normal, high, or ultra). The following compares forecasted volume with actual resulting volume, highlighting the power of early identifying increased volume through forecasted levels: █ VSA Patterns: Criteria and descriptions for each VSA pattern are available as tooltips beside them within the indicator’s settings. These tooltips provide explanations of potential developments based on the volume and spread data. Signs of Strength (🟢): Patterns indicating strong buying pressure and potential market upturns. Down Thrust Selling Climax No Effort ➤ Bearish Result Bearish Effort ➤ No Result Inverse Down Thrust Failed Selling Climax Bull Outside Reversal End of Falling Market (Bag Holder) Pseudo Down Thrust No Supply Signs of Weakness (🔴): Patterns indicating strong selling pressure and potential market downturns. Up Thrust Buying Climax No Effort ➤ Bullish Result Bullish Effort ➤ No Result Inverse Up Thrust Failed Buying Climax Bear Outside Reversal End of Rising Market (Bag Seller) Pseudo Up Thrust No Demand Neutral Patterns (🔵): Patterns indicating market indecision and potential for continuation or reversal. Quiet Doji Balanced Doji Strong Doji Quiet Spinning Top Balanced Spinning Top Strong Spinning Top Quiet High Wave Balanced High Wave Strong High Wave Consolidation Bar Patterns (🟡): Common candlestick patterns that offer insights into market sentiment. These are required in some VSA patterns and can also be displayed independently. Bull Pin Bar Bear Pin Bar Doji Spinning Top High Wave Consolidation This demonstrates the acronym and descriptive options for displaying bar patterns, with the ability to hover over text to reveal the descriptive text along with what type of pattern: █ Alerts: VSA Pattern Alerts: Notifications for identified VSA patterns at bar close. Volume and Spread Alerts: Alerts for confirmed and forecasted volume/spread levels (Low, High, Ultra). Forecasted Volume and Spread Alerts: Alerts for forecasted volume/spread levels (High, Ultra) include a minimum percent time elapsed input to reduce false early signals by ensuring sufficient bar time has passed. █ Inputs and Settings: Indicator Bar Color: Select color schemes for bars (Normal, Detail, Levels). Indicator Moving Average Color: Select schemes for bars (Fill, Lines, None). Price Bar Colors: Options to color price bars based on VSA patterns and volume levels. Legend: Display a table of bar colors and levels for context and clarity of volume/spread bars. Forecast: Configure forecast display and prediction details for volume and spread. Average Multipliers: Define multipliers for different levels (Low, High, Ultra) to refine the analysis. Moving Average: Set volume and spread moving average settings. VSA: Select the VSA patterns to be calculated and displayed (Strength, Weakness, Neutral). Bar Patterns: Criteria for bar patterns used in VSA (Doji, Bull Pin Bar, Bear Pin Bar, Spinning Top, Consolidation, High Wave). Colors: Set exact colors used for indicator bars, indicator moving averages, and price bars. More Display Options: Specify how VSA pattern text is displayed (Acronym, Descriptive), positioning, and sizes. Alerts: Configure alerts for VSA patterns, volume, and spread levels, including forecasted levels. █ Usage: The Volume Spread Analysis indicator is a helpful tool for leveraging volume spread analysis to make informed trading decisions. It offers comprehensive visual and textual cues on the chart, making it easier to identify market conditions, potential reversals, and continuations. Whether analyzing historical data or forecasting future trends, this indicator provides insights into the underlying factors driving market movements.
Pine Script®指标
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