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Trend Correlation HeatmapHello everyone! I am excited to release my trend correlation heatmap, or trend heatmap for short. Per usual, I think its important to explain the theory before we get into the use of the indicator, so let's get into the theory! The theory: So what is a correlation? Correlation is the relationship one variable has to another. Correlations are the basis of everything I do as a quantitative trader. From the correlation between the same variables (i.e. autocorrelation), the correlation between other variables (i.e. VIX and SPY, SPY High and SPY Low, DXY and ES1! close, etc.) and, as well, the correlation between price and time (time series correlation). This may sound very familiar to you, especially if you are a user, observer or follower of my ideas and/or indicators. Ninety-five percent of my indicators are a function of one of those three things. Whether it be a time series based indicator (i.e.my time series indicator), whether it be autocorrelation (my autoregressive cloud indicator or my autocorrelation oscillator) or whether it be regressive in nature (i.e. my SPY Volume weighted close, or even my expected move which uses averages in lieu of regressive approaches but is foundational in regression principles. Or even my VIX oscillator which relies on the premise of correlations between tickers.) So correlation is extremely important to me and while its true I am more of a regression trader than anything, I would argue that I am more of a correlation trader, because correlations are the backbone of how I develop math models of stocks. What I am trying to stress here is the importance of correlations. They really truly are foundational to any type of quantitative analysis for stocks. And as such, understanding the current relationship a stock has to time is pivotal for any meaningful analysis to be conducted. So what is correlation to time and what does it tell us? Correlation to time, otherwise known and commonly referred to as "Time Series", is the relationship a ticker's price has to the passing of time. It is displayed in the traditional Pearson Correlation Coefficient or R value and can be any value from -1 (strong negative relationship, i.e. a strong downtrend) to + 1 (i.e. a strong positive relationship, i.e. a strong uptrend). The higher or lower the value the stronger the up or downtrend is. As such, correlation to time tells us two very important things. These are: a) The direction of the stock; and b) The strength of the trend. Let's take a look at an example: Above we have a chart of QQQ. We can see a trendline that seems to fit well. The questions we ask as traders are: 1. What is the likelihood QQQ breaks down from this trendline? 2. What is the likelihood QQQ continues up? 3. What is the likelihood QQQ does a false breakdown? There are numerous mathematical approaches we can take to answer these questions. For example, 1 and 2 can be answered by use of a Cumulative Distribution Density analysis (CDDA) or even a linear or loglinear regression analysis and 3 can be answered, more or less, with a linear regression analysis and standard error ascertainment, or even just a general comparison using a data science approach (such as cosine similarity or Manhattan distance). But, the reality is, all 3 of these questions can be visualized, at least in some way, by simply looking at the correlation to time. Let's look at this chart again, this time with the correlation heatmap applied: If we look at the indicator we can see some pivotal things. These are: 1. We have 4, very strong uptrends that span both higher AND lower timeframes. We have a strong uptrend of 0.96 on the 5 minute, 50 candle period. We have a strong uptrend at the 300 candle lookback period on the 1 minute, we have a strong uptrend on the 100 day lookback on the daily timeframe period and we have a strong uptrend on the 5 minute on the 500 candle lookback period. 2. By comparison, we have 3 downtrends, all of which have correlations less than the 4 uptrends. All of the downtrends have a correlation above -0.8 (which we would want lower than -0.8 to be very strong), and all of the uptrends are greater than + 0.80. 3. We can also see that the uptrends are not confined to the smaller timeframes. We have multiple uptrends on multiple timeframes and both short term (50 to 100 candles) and long term (up to 500 candles). 4. The overall trend is strengthening to the upside manifested by a positive Max Change and a Positive Min change (to be discussed later more in-depth). With this, we can see that QQQ is actually very strong and likely will continue at least some upside. If we let this play out: We continued up, had one test and then bounced. Now, I want to specify, this indicator is not a panacea for all trading. And in relation to the 3 questions posed, they are best answered, at least quantitatively, not only by correlation but also by the aforementioned methods (CDDA, etc.) but correlation will help you get a feel for the strength or weakness present with a stock. What are some tangible applications of the indicator? For me, this indicator is used in many ways. Let me outline some ways I generally apply this indicator in my day and swing trading: 1. Gauging the strength of the stock: The indictor tells you the most prevalent behavior of the stock. Are there more downtrends than uptrends present? Are the downtrends present on the larger timeframes vs uptrends on the shorter indicating a possible bullish reversal? or vice versa? Are the trends strengthening or weakening? All of these things can be visualized with the indicator. 2. Setting parameters for other indicators: If you trade EMAs or SMAs, you may have a "one size fits all" approach. However, its actually better to adjust your EMA or SMA length to the actual trend itself. Take a look at this: This is QQQ on the 1 hour with the 200 EMA with 200 standard deviation bands added. If we look at the heatmap, we can see, yes indeed 200 has a fairly strong uptrend correlation of 0.70. But the strongest hourly uptrend is actually at 400 candles, with a correlation of 0.91. So what happens if we change the EMA length and standard deviation to 400? This: The exact areas are circled and colour coded. You can see, the 400 offers more of a better reference point of supports and resistances as well as a better overall trend fit. And this is why I never advocate for getting married to a specific EMA. If you are an EMA 200 lover or 21 or 51, know that these are not always the best depending on the trend and situation. Components of the indicator: Ah okay, now for the boring stuff. Let's go over the functionality of the indicator. I tried to keep it simple, so it is pretty straight forward. If we open the menu here are our options: We have the ability to toggle whichever timeframes we want. We also have the ability to toggle on or off the legend that displays the colour codes and the Max and Min highest change. Max and Min highest change: The max and min highest change simply display the change in correlation over the previous 14 candles. An increasing Max change means that the Max trend is strengthening. If we see an increasing Max change and an increasing Min change (the Min correlation is moving up), this means the stock is bullish. Why? Because the min (i.e. ideally a big negative number) is going up closer to the positives. Therefore, the downtrend is weakening. If we see both the Max and Min declining (red), that means the uptrend is weakening and downtrend is strengthening. Here are some examples: Final Thoughts: And that is the indicator and the theory behind the indicator. In a nutshell, to summarize, the indicator simply tracks the correlation of a ticker to time on multiple timeframes. This will allow you to make judgements about strength, sentiment and also help you adjust which tools and timeframes you are using to perform your analyses. As well, to make the indicator more user friendly, I tried to make the colours distinctively different. I was going to do different shades but it was a little difficult to visualize. As such, I have included a toggle-able legend with a breakdown of the colour codes! That's it my friends, I hope you find it useful! Safe trades and leave your questions, comments and feedback below!
Pine Script®指标
由Steversteves提供
18
Moving Average Filters Add-on w/ Expanded Source Types [Loxx]Moving Average Filters Add-on w/ Expanded Source Types is a conglomeration of specialized and traditional moving averages that will be used in most of indicators that I publish moving forward. There are 39 moving averages included in this indicator as well as expanded source types including traditional Heiken Ashi and Better Heiken Ashi candles. You can read about the expanded source types clicking here . About half of these moving averages are closed source on other trading platforms. This indicator serves as a reference point for future public/private, open/closed source indicators that I publish to TradingView. Information about these moving averages was gleaned from various forex and trading forums and platforms as well as TASC publications and other assorted research publications. ________________________________________________________________ Included moving averages ADXvma - Average Directional Volatility Moving Average Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator. The ADXvma has the SMA in Chande's CMO replaced with an EMA, it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated. A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA. The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move. Ahrens Moving Average Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows. Alexander Moving Average - ALXMA This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile. Double Exponential Moving Average - DEMA The Double Exponential Moving Average (DEMA) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag. Double Smoothed Exponential Moving Average - DSEMA The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA. It's also considered a leading indicator compared to the EMA, and is best utilized whenever smoothness and speed of reaction to market changes are required. Exponential Moving Average - EMA The EMA places more significance on recent data points and moves closer to price than the SMA (Simple Moving Average). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA. Fast Exponential Moving Average - FEMA An Exponential Moving Average with a short look-back period. Fractal Adaptive Moving Average - FRAMA The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry. Hull Moving Average - HMA Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. IE/2 - Early T3 by Tim Tilson The IE/2 is a Moving Average that uses Linear Regression slope in its calculation to help with smoothing. It's a worthy Moving Average on it's own, even though it is the precursor and very early version of the famous "T3 Indicator". Integral of Linear Regression Slope - ILRS A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA (Simple Moving Average) of length N, which is actually the midpoint of the linear regression line as it moves across the data. Instantaneous Trendline The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading. Laguerre Filter The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation. Adjusting the Alpha coefficient is used to increase or decrease its lag and it's smoothness. Leader Exponential Moving Average The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter. Linear Regression Value - LSMA (Least Squares Moving Average) LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down. Linear Weighted Moving Average - LWMA LWMA reacts to price quicker than the SMA and EMA. Although it's similar to the Simple Moving Average, the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion. McGinley Dynamic John McGinley created this Moving Average to track price better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets. McNicholl EMA Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws. Non lag moving average The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals. Parabolic Weighted Moving Average The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average. The Linear Weighted Moving Average calculates the average by assigning different weight to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator. Recursive Moving Trendline Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrows price. Simple Moving Average - SMA The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA. Sine Weighted Moving Average The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average). Smoothed Moving Average - SMMA The Smoothed Moving Average is similar to the Simple Moving Average (SMA), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen a an accurate yet laggy Moving Average. Smoother The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA (Smoothed Moving Average). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm. Super Smoother The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a a Two pole Butterworth filter combined with a 2-bar SMA (Simple Moving Average) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence. Three pole Ehlers Butterworth The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA. They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing. Three pole Ehlers smoother The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth. Triangular Moving Average - TMA The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data. The TMA and Sine Weighted Moving Average Filter are almost identical at times. Triple Exponential Moving Average - TEMA The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, it's signals are considered very noisy and should only be used in extremely fast-paced trading conditions. Two pole Ehlers Butterworth The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded. Two pole Ehlers smoother A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers. Volume Weighted EMA - VEMA Utilizing tick volume in MT4 (or real volume in MT5), this EMA will use the Volume reading in its decision to plot its moves. The more Volume it detects on a move, the more authority (confirmation) it has. And this EMA uses those Volume readings to plot its movements. Studies show that tick volume and real volume have a very strong correlation, so using this filter in MT4 or MT5 produces very similar results and readings. Zero Lag DEMA - Zero Lag Double Exponential Moving Average John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence. Zero Lag Moving Average The Zero Lag Moving Average is described by its creator, John Ehlers, as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average. Zero Lag TEMA - Zero Lag Triple Exponential Moving Average Just like the Zero Lag DEMA, this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators. ________________________________________________________________ What are Heiken Ashi "better" candles? The "better formula" was proposed in an article/memo by BNP-Paribas (In Warrants & Zertifikate, No. 8, August 2004 (a monthly German magazine published by BNP Paribas, Frankfurt), there is an article by Sebastian Schmidt about further development (smoothing) of Heikin-Ashi chart.) They proposed to use the following: (Open+Close)/2+(((Close-Open)/( High-Low ))*ABS((Close-Open)/2)) instead of using : haClose = (O+H+L+C)/4 According to that document the HA representation using their proposed formula is better than the traditional formula. What are traditional Heiken-Ashi candles? The Heikin-Ashi technique averages price data to create a Japanese candlestick chart that filters out market noise. Heikin-Ashi charts, developed by Munehisa Homma in the 1700s, share some characteristics with standard candlestick charts but differ based on the values used to create each candle. Instead of using the open, high, low, and close like standard candlestick charts, the Heikin-Ashi technique uses a modified formula based on two-period averages. This gives the chart a smoother appearance, making it easier to spots trends and reversals, but also obscures gaps and some price data. Expanded generic source types: Close = close Open = open High = high Low = low Median = hl2 Typical = hlc3 Weighted = hlcc4 Average = ohlc4 Average Median Body = (open+close)/2 Trend Biased = (see code, too complex to explain here) Trend Biased (extreme) = (see code, too complex to explain here) Included: -Toggle bar color on/off -Toggle signal line on/off
Pine Script®指标
由loxx提供
7
[blackcat] L2 Ehlers Fisherized Deviation Scaled OscillatorLevel: 2 Background John F. Ehlers introuced Fisherized Deviation Scaled Oscillator in Oct, 2018. Function In “Probability—Probably A Good Thing To Know,” John Ehlers introduces a procedure for measuring an indicator’s probability distribution to determine if it can be used as part of a reversion-to-the-mean trading strategy. Dr. Ehlers demonstrates this method with several of his existing indicators and presents a new indicator that he calls a deviation-scaled oscillator with Fisher transform. It charts the probability density of an oscillator to evaluate its applicability to swing trading. Key Signal FisherFilt --> Ehlers Fisherized Deviation Scaled Oscillator fast line Trigger --> Ehlers Fisherized Deviation Scaled Oscillator slow line Pros and Cons 100% John F. Ehlers definition translation, even variable names are the same. This help readers who would like to use pine to read his book. Remarks The 91th script for Blackcat1402 John F. Ehlers Week publication. Readme In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts. The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works. Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element. Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level. Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated. Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop. Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Pine Script®指标
由blackcat1402提供
[blackcat] L2 Swing Oscillator Swing MeterLevel: 2 Background Swing trading is a type of trading aimed at making short to medium term profits from a trading pair over a period of a few days to several weeks. Swing traders mainly use technical analysis to look for trading opportunities. In addition to analyzing price trends and patterns, these traders can also use fundamental analysis. Function L2 Swing Oscillator Swing Meter is an oscillator based on breakouts. Another important feature of it is the swing meter, which confirms the top or bottom's confidence level with different color candles. The higher of the candles stack up, the higher confidence level is indicated. Key Signal absolutebot ---> absolute bottom with very high confidence level ltbot ---> long term bottom with high confidence level mtbot ---> middle term bottom with moderate confidence level stbot ---> short term bottom with low confidence level absolutetop ---> absolute top with very high confidence level lttop ---> long term top with high confidence level mttop ---> middle term top with moderate confidence level sttop ---> short term top with low confidence level fastline ---> oscillator fast line slowline ---> oscillator slow line Pros and Cons Pros: 1. reconfigurable swing oscillator based on breakouts 2. swing meter can confirm/validate the bottom and top signal Cons: 1. not appliable with trading pairs without volume information 2. small time frame may not trigger swing meter function Remarks This is a simple but very comprehensive technical indicator Readme In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts. The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works. Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element. Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level. Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated. Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop. Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Pine Script®指标
由blackcat1402提供
4
RSI ADX Bollinger Analysis High-level purpose and design philosophy This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management. ________________________________________ What each indicator contributes (component-by-component) RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side. ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates. Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move. Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy. 4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results. 5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results. These exercises teach both statistical thinking and the specific failure modes of the mashup. ________________________________________ Limitations, failure modes and caveats (explicit & teachable) • ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions. • Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof. • RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns. • Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios. Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent. ________________________________________ Originality & mashup justification (text you can paste) This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength. ________________________________________ TradingView publication guidance & compliance checklist To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code): 1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter). 2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each. 3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.” 4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size). 5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest). 6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits. 7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes. 8. Trademark clause: If you used trademark symbols, remove or provide registration proof. 9. Risk disclaimer: Add the copy-ready disclaimer below. This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning. ________________________________________ Copy-ready short publication description (paste into TradingView) Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity. ________________________________________ Copy-ready risk & misuse disclaimer (paste into description or help file) This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls. ________________________________________ Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
Pine Script®指标
由aiTrendview-Charting-System提供
Tzotchev Trend Measure [EdgeTools]Are you still measuring trend strength with moving averages? Here is a better variant at scientific level: Tzotchev Trend Measure: A Statistical Approach to Trend Following The Tzotchev Trend Measure represents a sophisticated advancement in quantitative trend analysis, moving beyond traditional moving average-based indicators toward a statistically rigorous framework for measuring trend strength. This indicator implements the methodology developed by Tzotchev et al. (2015) in their seminal J.P. Morgan research paper "Designing robust trend-following system: Behind the scenes of trend-following," which introduced a probabilistic approach to trend measurement that has since become a cornerstone of institutional trading strategies. Mathematical Foundation and Statistical Theory The core innovation of the Tzotchev Trend Measure lies in its transformation of price momentum into a probability-based metric through the application of statistical hypothesis testing principles. The indicator employs the fundamental formula ST = 2 × Φ(√T × r̄T / σ̂T) - 1, where ST represents the trend strength score bounded between -1 and +1, Φ(x) denotes the normal cumulative distribution function, T represents the lookback period in trading days, r̄T is the average logarithmic return over the specified period, and σ̂T represents the estimated daily return volatility. This formulation transforms what is essentially a t-statistic into a probabilistic trend measure, testing the null hypothesis that the mean return equals zero against the alternative hypothesis of non-zero mean return. The use of logarithmic returns rather than simple returns provides several statistical advantages, including symmetry properties where log(P₁/P₀) = -log(P₀/P₁), additivity characteristics that allow for proper compounding analysis, and improved validity of normal distribution assumptions that underpin the statistical framework. The implementation utilizes the Abramowitz and Stegun (1964) approximation for the normal cumulative distribution function, achieving accuracy within ±1.5 × 10⁻⁷ for all input values. This approximation employs Horner's method for polynomial evaluation to ensure numerical stability, particularly important when processing large datasets or extreme market conditions. Comparative Analysis with Traditional Trend Measurement Methods The Tzotchev Trend Measure demonstrates significant theoretical and empirical advantages over conventional trend analysis techniques. Traditional moving average-based systems, including simple moving averages (SMA), exponential moving averages (EMA), and their derivatives such as MACD, suffer from several fundamental limitations that the Tzotchev methodology addresses systematically. Moving average systems exhibit inherent lag bias, as documented by Kaufman (2013) in "Trading Systems and Methods," where he demonstrates that moving averages inevitably lag price movements by approximately half their period length. This lag creates delayed signal generation that reduces profitability in trending markets and increases false signal frequency during consolidation periods. In contrast, the Tzotchev measure eliminates lag bias by directly analyzing the statistical properties of return distributions rather than smoothing price levels. The volatility normalization inherent in the Tzotchev formula addresses a critical weakness in traditional momentum indicators. As shown by Bollinger (2001) in "Bollinger on Bollinger Bands," momentum oscillators like RSI and Stochastic fail to account for changing volatility regimes, leading to inconsistent signal interpretation across different market conditions. The Tzotchev measure's incorporation of return volatility in the denominator ensures that trend strength assessments remain consistent regardless of the underlying volatility environment. Empirical studies by Hurst, Ooi, and Pedersen (2013) in "Demystifying Managed Futures" demonstrate that traditional trend-following indicators suffer from significant drawdowns during whipsaw markets, with Sharpe ratios frequently below 0.5 during challenging periods. The authors attribute these poor performance characteristics to the binary nature of most trend signals and their inability to quantify signal confidence. The Tzotchev measure addresses this limitation by providing continuous probability-based outputs that allow for more sophisticated risk management and position sizing strategies. The statistical foundation of the Tzotchev approach provides superior robustness compared to technical indicators that lack theoretical grounding. Fama and French (1988) in "Permanent and Temporary Components of Stock Prices" established that price movements contain both permanent and temporary components, with traditional moving averages unable to distinguish between these elements effectively. The Tzotchev methodology's hypothesis testing framework specifically tests for the presence of permanent trend components while filtering out temporary noise, providing a more theoretically sound approach to trend identification. Research by Moskowitz, Ooi, and Pedersen (2012) in "Time Series Momentum in the Cross Section of Asset Returns" found that traditional momentum indicators exhibit significant variation in effectiveness across asset classes and time periods. Their study of multiple asset classes over decades revealed that simple price-based momentum measures often fail to capture persistent trends in fixed income and commodity markets. The Tzotchev measure's normalization by volatility and its probabilistic interpretation provide consistent performance across diverse asset classes, as demonstrated in the original J.P. Morgan research. Comparative performance studies conducted by AQR Capital Management (Asness, Moskowitz, and Pedersen, 2013) in "Value and Momentum Everywhere" show that volatility-adjusted momentum measures significantly outperform traditional price momentum across international equity, bond, commodity, and currency markets. The study documents Sharpe ratio improvements of 0.2 to 0.4 when incorporating volatility normalization, consistent with the theoretical advantages of the Tzotchev approach. The regime detection capabilities of the Tzotchev measure provide additional advantages over binary trend classification systems. Research by Ang and Bekaert (2002) in "Regime Switches in Interest Rates" demonstrates that financial markets exhibit distinct regime characteristics that traditional indicators fail to capture adequately. The Tzotchev measure's five-tier classification system (Strong Bull, Weak Bull, Neutral, Weak Bear, Strong Bear) provides more nuanced market state identification than simple trend/no-trend binary systems. Statistical testing by Jegadeesh and Titman (2001) in "Profitability of Momentum Strategies" revealed that traditional momentum indicators suffer from significant parameter instability, with optimal lookback periods varying substantially across market conditions and asset classes. The Tzotchev measure's statistical framework provides more stable parameter selection through its grounding in hypothesis testing theory, reducing the need for frequent parameter optimization that can lead to overfitting. Advanced Noise Filtering and Market Regime Detection A significant enhancement over the original Tzotchev methodology is the incorporation of a multi-factor noise filtering system designed to reduce false signals during sideways market conditions. The filtering mechanism employs four distinct approaches: adaptive thresholding based on current market regime strength, volatility-based filtering utilizing ATR percentile analysis, trend strength confirmation through momentum alignment, and a comprehensive multi-factor approach that combines all methodologies. The adaptive filtering system analyzes market microstructure through price change relative to average true range, calculates volatility percentiles over rolling windows, and assesses trend alignment across multiple timeframes using exponential moving averages of varying periods. This approach addresses one of the primary limitations identified in traditional trend-following systems, namely their tendency to generate excessive false signals during periods of low volatility or sideways price action. The regime detection component classifies market conditions into five distinct categories: Strong Bull (ST > 0.3), Weak Bull (0.1 < ST ≤ 0.3), Neutral (-0.1 ≤ ST ≤ 0.1), Weak Bear (-0.3 ≤ ST < -0.1), and Strong Bear (ST < -0.3). This classification system provides traders with clear, quantitative definitions of market regimes that can inform position sizing, risk management, and strategy selection decisions. Professional Implementation and Trading Applications The indicator incorporates three distinct trading profiles designed to accommodate different investment approaches and risk tolerances. The Conservative profile employs longer lookback periods (63 days), higher signal thresholds (0.2), and reduced filter sensitivity (0.5) to minimize false signals and focus on major trend changes. The Balanced profile utilizes standard academic parameters with moderate settings across all dimensions. The Aggressive profile implements shorter lookback periods (14 days), lower signal thresholds (-0.1), and increased filter sensitivity (1.5) to capture shorter-term trend movements. Signal generation occurs through threshold crossover analysis, where long signals are generated when the trend measure crosses above the specified threshold and short signals when it crosses below. The implementation includes sophisticated signal confirmation mechanisms that consider trend alignment across multiple timeframes and momentum strength percentiles to reduce the likelihood of false breakouts. The alert system provides real-time notifications for trend threshold crossovers, strong regime changes, and signal generation events, with configurable frequency controls to prevent notification spam. Alert messages are standardized to ensure consistency across different market conditions and timeframes. Performance Optimization and Computational Efficiency The implementation incorporates several performance optimization features designed to handle large datasets efficiently. The maximum bars back parameter allows users to control historical calculation depth, with default settings optimized for most trading applications while providing flexibility for extended historical analysis. The system includes automatic performance monitoring that generates warnings when computational limits are approached. Error handling mechanisms protect against division by zero conditions, infinite values, and other numerical instabilities that can occur during extreme market conditions. The finite value checking system ensures data integrity throughout the calculation process, with fallback mechanisms that maintain indicator functionality even when encountering corrupted or missing price data. Timeframe validation provides warnings when the indicator is applied to unsuitable timeframes, as the Tzotchev methodology was specifically designed for daily and higher timeframe analysis. This validation helps prevent misapplication of the indicator in contexts where its statistical assumptions may not hold. Visual Design and User Interface The indicator features eight professional color schemes designed for different trading environments and user preferences. The EdgeTools theme provides an institutional blue and steel color palette suitable for professional trading environments. The Gold theme offers warm colors optimized for commodities trading. The Behavioral theme incorporates psychology-based color contrasts that align with behavioral finance principles. The Quant theme provides neutral colors suitable for analytical applications. Additional specialized themes include Ocean, Fire, Matrix, and Arctic variations, each optimized for specific visual preferences and trading contexts. All color schemes include automatic dark and light mode optimization to ensure optimal readability across different chart backgrounds and trading platforms. The information table provides real-time display of key metrics including current trend measure value, market regime classification, signal strength, Z-score, average returns, volatility measures, filter threshold levels, and filter effectiveness percentages. This comprehensive dashboard allows traders to monitor all relevant indicator components simultaneously. Theoretical Implications and Research Context The Tzotchev Trend Measure addresses several theoretical limitations inherent in traditional technical analysis approaches. Unlike moving average-based systems that rely on price level comparisons, this methodology grounds trend analysis in statistical hypothesis testing, providing a more robust theoretical foundation for trading decisions. The probabilistic interpretation of trend strength offers significant advantages over binary trend classification systems. Rather than simply indicating whether a trend exists, the measure quantifies the statistical confidence level associated with the trend assessment, allowing for more nuanced risk management and position sizing decisions. The incorporation of volatility normalization addresses the well-documented problem of volatility clustering in financial time series, ensuring that trend strength assessments remain consistent across different market volatility regimes. This normalization is particularly important for portfolio management applications where consistent risk metrics across different assets and time periods are essential. Practical Applications and Trading Strategy Integration The Tzotchev Trend Measure can be effectively integrated into various trading strategies and portfolio management frameworks. For trend-following strategies, the indicator provides clear entry and exit signals with quantified confidence levels. For mean reversion strategies, extreme readings can signal potential turning points. For portfolio allocation, the regime classification system can inform dynamic asset allocation decisions. The indicator's statistical foundation makes it particularly suitable for quantitative trading strategies where systematic, rules-based approaches are preferred over discretionary decision-making. The standardized output range facilitates easy integration with position sizing algorithms and risk management systems. Risk management applications benefit from the indicator's ability to quantify trend strength and provide early warning signals of potential trend changes. The multi-timeframe analysis capability allows for the construction of robust risk management frameworks that consider both short-term tactical and long-term strategic market conditions. Implementation Guide and Parameter Configuration The practical application of the Tzotchev Trend Measure requires careful parameter configuration to optimize performance for specific trading objectives and market conditions. This section provides comprehensive guidance for parameter selection and indicator customization. Core Calculation Parameters The Lookback Period parameter controls the statistical window used for trend calculation and represents the most critical setting for the indicator. Default values range from 14 to 63 trading days, with shorter periods (14-21 days) providing more sensitive trend detection suitable for short-term trading strategies, while longer periods (42-63 days) offer more stable trend identification appropriate for position trading and long-term investment strategies. The parameter directly influences the statistical significance of trend measurements, with longer periods requiring stronger underlying trends to generate significant signals but providing greater reliability in trend identification. The Price Source parameter determines which price series is used for return calculations. The default close price provides standard trend analysis, while alternative selections such as high-low midpoint ((high + low) / 2) can reduce noise in volatile markets, and volume-weighted average price (VWAP) offers superior trend identification in institutional trading environments where volume concentration matters significantly. The Signal Threshold parameter establishes the minimum trend strength required for signal generation, with values ranging from -0.5 to 0.5. Conservative threshold settings (0.2 to 0.3) reduce false signals but may miss early trend opportunities, while aggressive settings (-0.1 to 0.1) provide earlier signal generation at the cost of increased false positive rates. The optimal threshold depends on the trader's risk tolerance and the volatility characteristics of the traded instrument. Trading Profile Configuration The Trading Profile system provides pre-configured parameter sets optimized for different trading approaches. The Conservative profile employs a 63-day lookback period with a 0.2 signal threshold and 0.5 noise sensitivity, designed for long-term position traders seeking high-probability trend signals with minimal false positives. The Balanced profile uses a 21-day lookback with 0.05 signal threshold and 1.0 noise sensitivity, suitable for swing traders requiring moderate signal frequency with acceptable noise levels. The Aggressive profile implements a 14-day lookback with -0.1 signal threshold and 1.5 noise sensitivity, optimized for day traders and scalpers requiring frequent signal generation despite higher noise levels. Advanced Noise Filtering System The noise filtering mechanism addresses the challenge of false signals during sideways market conditions through four distinct methodologies. The Adaptive filter adjusts thresholds based on current trend strength, increasing sensitivity during strong trending periods while raising thresholds during consolidation phases. The Volatility-based filter utilizes Average True Range (ATR) percentile analysis to suppress signals during abnormally volatile conditions that typically generate false trend indications. The Trend Strength filter requires alignment between multiple momentum indicators before confirming signals, reducing the probability of false breakouts from consolidation patterns. The Multi-factor approach combines all filtering methodologies using weighted scoring to provide the most robust noise reduction while maintaining signal responsiveness during genuine trend initiations. The Noise Sensitivity parameter controls the aggressiveness of the filtering system, with lower values (0.5-1.0) providing conservative filtering suitable for volatile instruments, while higher values (1.5-2.0) allow more signals through but may increase false positive rates during choppy market conditions. Visual Customization and Display Options The Color Scheme parameter offers eight professional visualization options designed for different analytical preferences and market conditions. The EdgeTools scheme provides high contrast visualization optimized for trend strength differentiation, while the Gold scheme offers warm tones suitable for commodity analysis. The Behavioral scheme uses psychological color associations to enhance decision-making speed, and the Quant scheme provides neutral colors appropriate for quantitative analysis environments. The Ocean, Fire, Matrix, and Arctic schemes offer additional aesthetic options while maintaining analytical functionality. Each scheme includes optimized colors for both light and dark chart backgrounds, ensuring visibility across different trading platform configurations. The Show Glow Effects parameter enhances plot visibility through multiple layered lines with progressive transparency, particularly useful when analyzing multiple timeframes simultaneously or when working with dense price data that might obscure trend signals. Performance Optimization Settings The Maximum Bars Back parameter controls the historical data depth available for calculations, with values ranging from 5,000 to 50,000 bars. Higher values enable analysis of longer-term trend patterns but may impact indicator loading speed on slower systems or when applied to multiple instruments simultaneously. The optimal setting depends on the intended analysis timeframe and available computational resources. The Calculate on Every Tick parameter determines whether the indicator updates with every price change or only at bar close. Real-time calculation provides immediate signal updates suitable for scalping and day trading strategies, while bar-close calculation reduces computational overhead and eliminates signal flickering during bar formation, preferred for swing trading and position management applications. Alert System Configuration The Alert Frequency parameter controls notification generation, with options for all signals, bar close only, or once per bar. High-frequency trading strategies benefit from all signals mode, while position traders typically prefer bar close alerts to avoid premature position entries based on intrabar fluctuations. The alert system generates four distinct notification types: Long Signal alerts when the trend measure crosses above the positive signal threshold, Short Signal alerts for negative threshold crossings, Bull Regime alerts when entering strong bullish conditions, and Bear Regime alerts for strong bearish regime identification. Table Display and Information Management The information table provides real-time statistical metrics including current trend value, regime classification, signal status, and filter effectiveness measurements. The table position can be customized for optimal screen real estate utilization, and individual metrics can be toggled based on analytical requirements. The Language parameter supports both English and German display options for international users, while maintaining consistent calculation methodology regardless of display language selection. Risk Management Integration Effective risk management integration requires coordination between the trend measure signals and position sizing algorithms. Strong trend readings (above 0.5 or below -0.5) support larger position sizes due to higher probability of trend continuation, while neutral readings (between -0.2 and 0.2) suggest reduced position sizes or range-trading strategies. The regime classification system provides additional risk management context, with Strong Bull and Strong Bear regimes supporting trend-following strategies, while Neutral regimes indicate potential for mean reversion approaches. The filter effectiveness metric helps traders assess current market conditions and adjust strategy parameters accordingly. Timeframe Considerations and Multi-Timeframe Analysis The indicator's effectiveness varies across different timeframes, with higher timeframes (daily, weekly) providing more reliable trend identification but slower signal generation, while lower timeframes (hourly, 15-minute) offer faster signals with increased noise levels. Multi-timeframe analysis combining trend alignment across multiple periods significantly improves signal quality and reduces false positive rates. For optimal results, traders should consider trend alignment between the primary trading timeframe and at least one higher timeframe before entering positions. Divergences between timeframes often signal potential trend reversals or consolidation periods requiring strategy adjustment. Conclusion The Tzotchev Trend Measure represents a significant advancement in technical analysis methodology, combining rigorous statistical foundations with practical trading applications. Its implementation of the J.P. Morgan research methodology provides institutional-quality trend analysis capabilities previously available only to sophisticated quantitative trading firms. The comprehensive parameter configuration options enable customization for diverse trading styles and market conditions, while the advanced noise filtering and regime detection capabilities provide superior signal quality compared to traditional trend-following indicators. Proper parameter selection and understanding of the indicator's statistical foundation are essential for achieving optimal trading results and effective risk management. References Abramowitz, M. and Stegun, I.A. (1964). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Washington: National Bureau of Standards. Ang, A. and Bekaert, G. (2002). Regime Switches in Interest Rates. Journal of Business and Economic Statistics, 20(2), 163-182. Asness, C.S., Moskowitz, T.J., and Pedersen, L.H. (2013). Value and Momentum Everywhere. Journal of Finance, 68(3), 929-985. Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill. Fama, E.F. and French, K.R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273. Hurst, B., Ooi, Y.H., and Pedersen, L.H. (2013). Demystifying Managed Futures. Journal of Investment Management, 11(3), 42-58. Jegadeesh, N. and Titman, S. (2001). Profitability of Momentum Strategies: An Evaluation of Alternative Explanations. Journal of Finance, 56(2), 699-720. Kaufman, P.J. (2013). Trading Systems and Methods. 5th Edition. Hoboken: John Wiley & Sons. Moskowitz, T.J., Ooi, Y.H., and Pedersen, L.H. (2012). Time Series Momentum. Journal of Financial Economics, 104(2), 228-250. Tzotchev, D., Lo, A.W., and Hasanhodzic, J. (2015). Designing robust trend-following system: Behind the scenes of trend-following. J.P. Morgan Quantitative Research, Asset Management Division.
Pine Script®指标
由EdgeTools提供
Multi Timeframe Indian Stocks TrendsThis script, "Multi Timeframe Indian Stocks Trends," is designed for swing trading in the Indian stock market, with a specific focus on Nifty50. It provides a comprehensive view of trends across multiple timeframes: 1-hour, 4-hour, Daily, Weekly, and Monthly. Key Features: Multi-Timeframe Analysis: Gain insights into trends across 1H, 4H, D, W, and M timeframes, helping you make informed swing trading decisions. Trend Calculation Methods: Choose between two popular trend calculation methods: Supertrend: A widely used indicator that identifies trend direction and provides potential entry and exit points. EMA (Exponential Moving Average): Utilizes the relationship between a fast and slow EMA to determine trend direction. Customizable Trend Table: A clear and concise table displays the trend direction for each selected timeframe, making it easy to grasp the overall market sentiment. Nifty50 Reference: The script is tailored for Indian stocks and includes a reference to Nifty50, allowing you to gauge the broader market trend. Visual Customization: Adjust the colors of the trend table, background, and text to suit your preferences. Adjustable Settings: Fine-tune the parameters for Supertrend (ATR Length, Factor) and EMA (Fast EMA, Slow EMA) to optimize the indicator for your trading style. This script is ideal for traders who want to: Identify swing trading opportunities in Indian stocks. Confirm trends across various timeframes. Utilize either Supertrend or EMA for trend analysis. Have a quick and clear overview of market trends. By providing a multi-timeframe perspective and customizable trend analysis, this script empowers traders to make more confident and well-informed swing trading decisions in the Indian stock market.
Pine Script®指标
由mudraminer提供
AMF PG Strategy_v2The AMF PG Strategy (Praetorian Guard) is an advanced trading system designed to seamlessly adapt to market conditions. Its unique structure balances precise entries with intelligent protection, giving traders confidence in both trending and volatility environments. Key points include: Adaptive Core (AMF Engine) – A dynamic framework that automatically adjusts for clearer long- and short-term opportunities and generates a robust tracking line. Praetorian Guard – A built-in protective shield that activates in extreme conditions and helps stabilize performance when markets become turbulent. Versatility – Effective across multiple timeframes, from scalping to swing trading, without constant parameter adjustments. Clarity – Clear visual signals and color-coded monitoring for instant decision-making. This strategy is designed for traders who want more than just entries and exits; it offers a command center for disciplined, adaptable, and resilient trading. Disclaimer: It should be noted that no strategy is guaranteed. This strategy does not provide buy-sell-hold advice. Responsibility rests with the user. Version 2: Bugs overlooked in Version 1 have been corrected and improvements have been made.
Pine Script®策略
由blntduman提供
EMA Cross Suite (8/20/50/200) GOLDEN/DEATH by Carlos Chavez📜 Short Description (max 160 characters) “Advanced EMA crossover system with FAST, MID, GOLDEN, and DEATH signals. Includes alerts, optimized visuals, and full customization.” 📄 Full Description (Paste in the box) 📌 Overview The Embilletados • EMA Cross Suite is a professional trading indicator designed for intraday traders, scalpers, and swing traders. It provides clear crossover signals using 4 EMAs combined with optimized visualization and built-in alerts to help you catch opportunities faster. ✨ Key Features: 🔹 4 configurable EMAs → 8, 20, 50, and 200. 🔹 Instant visual signals with colored labels: FAST CROSS (8/20) → Quick momentum shifts. MID CROSS (20/50) → Trend confirmation signals. GOLDEN CROSS (50/200) → Strong bullish trend signals. DEATH CROSS (50/200) → Strong bearish trend signals. 🔹 Built-in alerts → Get notified instantly for all crossover events. 🔹 Optimized visualization → Clean and easy-to-read interface. 🔹 Highly customizable → Enable/disable signals, labels, colors, and alerts according to your strategy. 📊 Recommended Timeframes: 10-minute charts → Best for intraday setups. 1-hour charts → Ideal for swing trading and trend confirmation. 🚀 How to Use: Add the indicator to your chart. Set up alerts for the desired crossovers: FAST, MID, GOLDEN, or DEATH. Trade confidently using clear visual confirmations and real-time notifications. 🌟 Perfect for: ✅ Intraday traders ✅ Scalpers ✅ Swing traders ✅ Trend-following strategies
Pine Script®指标
由Carlostradercr提供
6
AMF PG Strategy AMF Command Center Strategy (Praetorian Guard) The AMF PG Strategy (Praetorian Guard) is an advanced trading system built to adapt seamlessly across market conditions. Its unique structure balances precision entries with intelligent protection, giving traders confidence in both trending and volatile environments. Key highlights include: Adaptive Core (AMF Engine) – A dynamic framework that automatically adjusts and generates a powerful tracking line for clearer long and short opportunities. Praetorian Guard – A built-in protective shield that activates in extreme conditions, helping stabilize performance when markets become turbulent. Versatility – Effective across multiple timeframes, from scalping to swing trading, without constant parameter adjustments. Clarity – Clean visual signals and color-coded tracking for instant decision-making. This strategy was designed for traders who want more than just entries and exits — it offers a command center for disciplined, adaptive, and resilient trading.
Pine Script®策略
由blntduman提供
Artharjan ADXArtharjan ADX (AADX) by Rrahul Desai @Artharjan 📌 Overview The Artharjan ADX (AADX) is an advanced implementation of the Average Directional Index (ADX) with customizable moving averages, momentum thresholds, and visually intuitive grading of bullish and bearish strength. Unlike the standard ADX indicator that only shows trend strength, AADX adds graded bullish/bearish conditions, alerts, smoothed DI signals, histogram visualizations, and background color fills to help traders quickly interpret market conditions. It is designed for traders who want early detection of trend strength, clean visual cues, and automated alert triggers for both bullish and bearish momentum setups. ⚙️ Key Features 🔹 Customizable Calculations DI Length (default 13) – controls sensitivity of directional indicators. +/- DI Smoothing – smooths DI signals with user-selected MA. Multiple Moving Average Types – SMA, EMA, WMA, RMA, VWMA, ALMA, Hull, SWMA, SMMA, TMA. ADX Smoothing – define how smooth/fast the ADX reacts. 🔹 Flexible Display Toggle between line plots or histogram view. Adjustable plot thickness. Option to plot averages of ADX, +DI, -DI for confirmation. Configurable background fills: ADX above/below momentum threshold. ADX rising/falling color shading. Trend-grade based color intensity. 🔹 Momentum & Thresholds Momentum Level (default 25) → defines “strong trend” zone. Crossover Threshold (default 15) → helps detect early DI crossovers. Color-coded histogram bars for +DI vs -DI difference: Above/below zero. Rising/falling momentum. 🔹 Bullish & Bearish Grading System The indicator assigns grades from 1 to 5 for both bullish and bearish setups, based on DI and ADX conditions: Bullish Grades Grade 1 → Very Weak Bullish Grade 2 → Weak Bullish Grade 3 → Moderate Bullish Grade 4 → Strong Bullish Grade 5 → Very Strong Bullish Bearish Grades Grade 1 → Very Weak Bearish Grade 2 → Weak Bearish Grade 3 → Moderate Bearish Grade 4 → Strong Bearish Grade 5 → Very Strong Bearish Labels are automatically plotted above bars to indicate the active grade. 🔹 Alerts Bullish Alert → when +DI crosses above its average below the threshold OR bullish conditions are met. Bearish Alert → when -DI crosses above its average below the threshold OR bearish conditions are met. These alerts make it possible to automate trading signals for scalping, intraday, and swing trading. 📊 Use Cases Trend Strength Measurement Spot when markets shift from range-bound to trending. Confirm the reliability of breakouts with strong ADX readings. Bullish vs Bearish Control Compare +DI vs -DI strength to gauge trend direction. Identify trend reversals early with DI slope changes. Momentum Confirmation Use ADX rising + DI grades to validate trade entries. Filter false breakouts with weak ADX. Trade Grading System Enter aggressively on Grade 4–5 signals. Stay cautious on Grade 1–2 signals. Automated Alerts & Screening Combine AADX alerts with strategy rules. Build scanners to highlight strong ADX setups across multiple stocks. 🎯 Trader’s Advantage More powerful than standard ADX → Adds slope, grading, alerts, and visualization. Adaptable to any style → Works for intraday scalping, swing trading, and positional analysis. Visual clarity → Color fills, histograms, and labels simplify decision-making. Customizable smoothing → Adjusts to fast or slow markets. ✅ Closing Note The Artharjan ADX (AADX) transforms the traditional ADX into a complete trend and momentum analyzer. It helps traders detect, confirm, and act on directional strength with clarity and confidence. With Thanks, Rrahul Desai @Artharjan
Pine Script®指标
由rsdesai005提供
EMA20 Cross Strategy with countertrades and signalsEMA20 Cross Strategy Documentation Overview The EMA20 Cross Strategy with Counter-Trades and Instant Signals is a Pine Script (version 6) trading strategy designed for the TradingView platform. It implements an Exponential Moving Average (EMA) crossover system to generate buy and sell signals, with optional trend filtering, session-based trading, instant signal processing, and visual/statistical feedback. The strategy supports counter-trades (closing opposing positions before entering new ones) and operates with a fixed trade size in EUR. Features EMA Crossover Mechanism: Uses a short-term EMA (configurable length, default: 1) and a long-term EMA (default: 20) to detect crossovers. A buy signal is generated when the short EMA crosses above the long EMA. A sell signal is generated when the short EMA crosses below the long EMA. Instant Signals: If enabled (useInstantSignals), signals are based on the current price crossing the short EMA, rather than waiting for the candle close. This allows faster trade execution but may increase sensitivity to price fluctuations. Trend Filter: Optionally filters trades based on the trend direction (useTrendFilter). Long trades are allowed only when the short EMA (or price, for instant signals) is above the long EMA. Short trades are allowed only when the short EMA (or price) is below the long EMA. Session Filter: Restricts trading to specific market hours (sessionStart, default: 09:00–17:00) if enabled (useSessionFilter). Ensures trades occur only during active market sessions, reducing exposure to low-liquidity periods. Customizable Timeframe: The EMA calculations can use a higher timeframe (e.g., 5m, 15m, 1H, 4H, 1D, default: 1H) via request.security. This allows the strategy to base signals on longer-term trends while operating on a shorter-term chart. Trade Management: Fixed trade size of €100,000 per trade (tradeAmount), with a maximum quantity cap (maxQty = 10,000) to prevent oversized trades. Counter-trades: Closes short positions before entering a long position and vice versa. Trades are executed with a minimum quantity of 1 to ensure valid orders. Visualization: EMA Lines: The short EMA is colored based on the last signal (green for buy, red for sell, gray for neutral), and the long EMA is orange. Signal Markers: Displays buy/sell signals as arrows (triangles) above/below candles if enabled (showSignalShapes). Background/Candle Coloring: Optionally colors the chart background or candles green (bullish) or red (bearish) based on the trend (useColoredBars). Statistics Display: If enabled (useStats), a label on the chart shows: Total closed trades Open trades Win rate (%) Number of winning/losing trades Profit factor (gross profit / gross loss) Net profit Maximum drawdown Configuration Inputs EMA Short Length (emaLength): Length of the short-term EMA (default: 1). Trend EMA Length (trendLength): Length of the long-term EMA (default: 20). Enable Trend Filter (useTrendFilter): Toggles trend-based filtering (default: true). Color Candles (useColoredBars): Colors candles instead of the background (default: true). Enable Session Filter (useSessionFilter): Restricts trading to specified hours (default: false). Trading Session (sessionStart): Defines trading hours (default: 09:00–17:00). Show Statistics (useStats): Displays performance stats on the chart (default: true). Show Signal Arrows (showSignalShapes): Displays buy/sell signals as arrows (default: true). Use Instant Signals (useInstantSignals): Generates signals based on live price action (default: false). EMA Timeframe (emaTimeframe): Timeframe for EMA calculations (options: 5m, 15m, 1H, 4H, 1D; default: 1H). Strategy Logic Signal Generation: Standard Mode: Signals are based on EMA crossovers (short EMA crossing long EMA) at candle close. Instant Mode: Signals are based on the current price crossing the short EMA, enabling faster reactions. Trade Execution: On a buy signal, closes any short position and opens a long position. On a sell signal, closes any long position and opens a short position. Position size is calculated as the minimum of €100,000 or available equity, divided by the current price, capped at 10,000 units. Filters: Trend Filter: Ensures trades align with the trend direction (if enabled). Session Filter: Restricts trades to user-defined market hours (if enabled). Visual Feedback EMA Lines: Provide a clear view of the short and long EMAs, with the short EMA’s color reflecting the latest signal. Signal Arrows: Large green triangles (buy) below candles or red triangles (sell) above candles for easy signal identification. Chart Coloring: Highlights bullish (green) or bearish (red) trends via background or candle colors. Statistics Label: Displays key performance metrics in a label above the chart for quick reference. Usage Notes Initial Capital: €100,000 (configurable via initial_capital). Currency: EUR (set via currency). Order Processing: Orders are processed at candle close (process_orders_on_close=true) unless instant signals are enabled. Dynamic Requests: Allows dynamic timeframe adjustments for EMA calculations (dynamic_requests=true). Platform: Designed for TradingView, compatible with any market supported by the platform (e.g., stocks, forex, crypto). Example Use Case Scenario: Trading on a 5-minute chart with a 1-hour EMA timeframe, trend filter enabled, and session filter set to 09:00–17:00. Behavior: The strategy will: Calculate EMAs on the 1-hour timeframe. Generate buy signals when the short EMA crosses above the long EMA (and price is above the long EMA). Generate sell signals when the short EMA crosses below the long EMA (and price is below the long EMA). Execute trades only during 09:00–17:00. Display green/red candles and performance stats on the chart. Limitations Instant Signals: May lead to more frequent signals, increasing the risk of false positives in volatile markets. Fixed Trade Size: Does not adjust dynamically based on market conditions beyond equity and max quantity limits. Session Filter: Simplified and may not account for complex session rules or holidays. Statistics: Displayed on-chart, which may clutter the view in smaller charts. Customization Adjust emaLength and trendLength to suit different market conditions (e.g., shorter for scalping, longer for swing trading). Toggle useInstantSignals for faster or more stable signal generation. Modify sessionStart to align with specific market hours. Disable useStats or showSignalShapes for a cleaner chart. This strategy is versatile for both manual and automated trading, offering flexibility for various markets and trading styles while providing clear visual and statistical feedback.
Pine Script®策略
由osterhansi_提供
Vagas-dctang(8~13)Overview The Vegas Tunnel EMA 8-13 is a refined technical analysis indicator that utilizes two key exponential moving averages (8-period and 13-period EMAs) to create a dynamic tunnel system for identifying trend direction and potential support/resistance zones. This indicator is specifically designed to help traders visualize price action within the context of short-term trend dynamics. Key Features ✅ Dual EMA Tunnel System: Creates a visual tunnel between 8 EMA (fast) and 13 EMA (slow) to identify trend channels ✅ Dynamic Support Detection: The tunnel acts as dynamic support during uptrends and resistance during downtrends ✅ Trend Confirmation: Price position relative to the tunnel helps confirm the current market trend ✅ Entry/Exit Signals: Tunnel crossovers and price interactions provide clear trading signals ✅ Multi-Timeframe Compatible: Works effectively across various timeframes from scalping to swing trading How It Works The Vegas Tunnel EMA 8-13 operates on the principle that shorter-period EMAs react more quickly to price changes, creating a responsive tunnel system: Bullish Tunnel: When 8 EMA > 13 EMA, the tunnel indicates an upward trend with potential support zones Bearish Tunnel: When 8 EMA < 13 EMA, the tunnel indicates a downward trend with potential resistance zones Tunnel Width: The distance between EMAs indicates trend strength and volatility Price Interaction: Bounces off the tunnel boundaries suggest trend continuation, while breaks may signal reversals Trading Applications Trend Following: Use tunnel direction to align trades with the prevailing trend Support/Resistance Trading: Enter long positions when price bounces off tunnel support, short when rejected at resistance Breakout Strategy: Trade tunnel breaks as potential trend continuation or reversal signals Risk Management: Use tunnel boundaries as dynamic stop-loss levels Advantages Over Traditional Moving Averages Reduced Noise: The tunnel system filters out minor price fluctuations Visual Clarity: Easy identification of trend channels and key levels Faster Response: 8-13 period combination provides quicker signals than longer-term systems Versatile Application: Suitable for various trading styles and market conditions Best Practices Combine with volume analysis for stronger signal confirmation Consider higher timeframe tunnel direction for context Use proper risk management with position sizing Backtest on your preferred instruments and timeframes This indicator is ideal for traders seeking a clean, effective tool for trend analysis and dynamic support/resistance identification in fast-moving markets.
Pine Script®指标
由tangdixi提供
1
Smart Structure Breaks & Order BlocksOverview (What it does) The indicator “Smart Structure Breaks & Order Blocks” detects market structure using swing highs and lows, identifies Break of Structure (BOS) events, and automatically draws order blocks (OBs) from the origin candle. These zones extend to the right and change color/outline when mitigated or invalidated. By formalizing and automating part of discretionary analysis, it provides consistent zone recognition. Main Components Swing Detection: ta.pivothigh/ta.pivotlow identify confirmed swing points. BOS Detection: Determines if the recent swing high/low is broken by close (strict mode) or crossover. OB Creation: After a BOS, the opposite candle (bearish for bullish BOS, bullish for bearish BOS) is used to generate an order block zone. Zone Management: Limits the number of zones, extends them to the right, and tracks tagged (mitigated) or invalidated states. Input Parameters Left/Right Pivot (default 6/6): Number of bars required on each side to confirm a swing. Higher values = smoother swings. Max Zones (default 4): Maximum zones stored per direction (bull/bear). Oldest zones are overwritten. Zone Confirmation Lookback (default 3): Ensures OB origin candle validity by checking recent highs/lows. Show Swing Points (default ON): Displays triangles on swing highs/lows. Require close for BOS? (default ON): Strict BOS (close required) vs loose BOS (line crossover). Use candle body for zones (default OFF): Zones drawn from candle body (ON) or wick (OFF). Signal Definition & Logic Swing Updates: Latest confirmed pivots update lastHighLevel / lastLowLevel. BOS (Break of Structure): 　Bullish – close breaks last swing high. 　Bearish – close breaks last swing low. 　Only one valid BOS per swing (avoids duplicates). OB Detection: 　Bullish BOS → previous bearish candle with lowest low forms the OB. 　Bearish BOS → previous bullish candle with highest high forms the OB. 　Zones: Bull = green, Bear = red, semi-transparent, extended to the right. Zone States: 　Mitigated: Price touches the zone → border highlighted. 　Invalidated: 　　Bull zone → close below → turns red. 　　Bear zone → close above → turns green. Chart Appearance Swing High: red triangle above bar Swing Low: green triangle below bar Bull OB: green zone (border highlighted on touch) Bear OB: red zone (border highlighted on touch) Invalid Zones: Bull zones turn reddish, Bear zones turn greenish Practical Use (Trading Assistance) Trend Following Entries: Buy pullbacks into green OBs in uptrends, sell rallies into red OBs in downtrends. Focus on First Touch: First mitigation after BOS often has higher reaction probability. Confluence: Combine with higher timeframe trend, volume, session levels, key price levels (previous highs/lows, VWAP, etc.). Stops/Targets: 　Bull – stop below zone, partial take profit at swing high or resistance. 　Bear – stop above zone, partial take profit at swing low or support. Parameter Tuning (per market/timeframe) Pivot (6/6 → 4/4/8/8): Lower for scalping (3–5), medium for day trading (5–8), higher for swing trading (8–14). Increase to reduce noise. Strict Break: ON to reduce false breaks in ranging markets; OFF for earlier signals. Body Zones: ON for assets with long wicks, OFF for cleaner OBs in liquid instruments. Zone Confirmation (default 3): Increase for stricter OB origin, fewer zones. Max Zones (default 4 → 6–10): Increase for higher volatility, decrease to avoid clutter. Strengths Standardizes BOS and OB detection that is usually subjective. Tracks mitigation and invalidation automatically. Adaptable: allows body/wick zone switching for different instruments. Limitations Pivot-based: Signals appear only after pivots confirm (slight lag). Zones reflect past balance: Can fail after new events (news, earnings, macro data). Range-heavy markets: More false BOS; consider stricter settings. Backtesting: This script is for drawing/visual aid; trading rules must be defined separately. Workflow Example Identify higher timeframe trend (4H/Daily). On lower TF (15–60m), wait for BOS and new OB. Enter on first mitigation with confirmation candle. Stop beyond zone; targets based on R multiples and swing points. FAQ Q: Why are zones invalidated quickly? A: Flow reversal after BOS. Adjust pivots higher, enable Strict mode, or switch to Body zones to reduce noise. Q: What does “tagged” mean? A: Price touched the zone once = mitigated. Implies some orders in that zone may have been filled. Q: Body or Wick zones? A: Wick zones are fine in clean markets. For volatile pairs with long wicks, body zones provide more realistic areas. Customization Tips (Code perspective) Zone storage: Currently ring buffer ((idx+1) % zoneLimit). Could prioritize keeping unmitigated zones. Automated testing: Add strategy.entry/exit for rule-based backtests. Multi-timeframe: Use request.security() for higher timeframe swings/BOS. Visualization: Add labels for BOS bars, tag zones with IDs, count touches. Summary This indicator formalizes the cycle Swing → BOS → OB creation → Mitigation/Invalidation, providing consistent structure analysis and zone tracking. By tuning sensitivity and strictness, and combining with higher timeframe context, it enhances pullback/continuation trading setups. Always combine with proper risk management.
Pine Script®指标
由PakunFX提供
ADX Tide ZonesADX Tide Zones – Adaptive Momentum & Trend Strength Framework Overview ADX Tide Zones – Professional is a dynamic trend-strength visualizer designed for traders who want to interpret momentum with precision and context. By combining the Average Directional Index (ADX) with adaptive threshold logic, the indicator segments price action into distinct “tide zones” that reflect varying levels of market strength: Calm, Rising, Strong, and Falling Tides. These zones transform raw ADX readings into an interpretable framework that highlights when markets are consolidating, building momentum, trending strongly, or losing strength. Unlike standard ADX readings, which can be difficult to interpret in real time, ADX Tide Zones translate momentum shifts into a continuous, color-coded system that traders can instantly read. Whether applied to scalping, intraday, or swing trading, the indicator offers a consistent methodology for identifying actionable opportunities across assets and timeframes. How It Works The foundation of ADX Tide Zones lies in momentum analysis via the ADX. By measuring the strength (not direction) of a trend, ADX provides an objective read on when markets are gaining or losing energy. ADX Tide Zones enhances this by applying threshold logic to classify ADX values into four distinct states: Calm Tide : Low ADX values indicate sideways or consolidating conditions. Rising Tide : ADX increases past a threshold, signaling momentum building. Strong Tide : ADX remains elevated, confirming robust and sustained trend strength. Falling Tide : ADX declines after strength, hinting at exhaustion or early reversal setups. These states are displayed on the chart through adaptive visualizations (zones, bar colors, or overlays), offering real-time clarity on when to expect expansion, continuation, or contraction in price action. Interpretation Trend Analysis : By mapping transitions between tides, traders can instantly gauge whether markets are in accumulation, expansion, or exhaustion phases. Rising/Strong Tides reinforce trend continuation, while Falling Tides highlight weakening conditions. Volatility & Risk Assessment : Shifts between Calm → Rising Tide often precede volatility expansions. Falling Tides can signal a period of compression or corrective moves, warning traders to manage risk proactively. Market Context : The indicator does not dictate direction; instead, it overlays strength on top of price action, allowing traders to combine it with directional tools such as moving averages, order blocks, or liquidity zones for confirmation. Strategy Integration ADX Tide Zones adapts seamlessly to a wide range of trading strategies by translating momentum dynamics into actionable frameworks: Trend Following : Traders can align with dominant flows by entering positions when the indicator confirms a Rising Tide or Strong Tide. These conditions signal persistent directional strength, making them ideal for continuation setups. Combining directional bias with ADX confirmation reduces the risk of trading against prevailing momentum. Breakout Trading : When the market transitions from Calm Tide into a Rising Tide, it often precedes a volatility expansion. This shift highlights breakout conditions where accumulation gives way to impulsive price movement. Traders can use this transition as a timing tool to catch early entries into new momentum phases. Exhaustion Reversals : Strong Tide phases don’t last forever—when they begin to fade into Falling Tide, it can mark trend fatigue or liquidity exhaustion. This offers contrarian traders an early edge in spotting overextended moves and positioning for corrective pullbacks or full reversals. Multi-Timeframe Analysis : By overlaying higher timeframe tide zones on intraday or scalping charts, traders can filter noise and trade in alignment with larger flows. For example, combining a daily Rising Tide bias with a 15-minute breakout confirmation can significantly improve entry precision while reducing exposure to false signals. Advanced Techniques For traders seeking an extra edge, ADX Tide Zones can be pushed further with advanced methods: Volume & Liquidity Confirmation : Pair the tide transitions with volume spikes, order flow, or liquidity sweep tools. When directional strength confirmed by the ADX coincides with institutional activity, it validates setups and increases probability of follow-through. Cross-Asset Synchronization : Momentum rarely exists in isolation. Monitoring tide shifts across correlated instruments (e.g., majors vs. USD, or indices vs. risk assets) can uncover synchronized volatility events. These correlations help traders identify whether a move is isolated noise or part of a broader systemic trend. Threshold Optimization : The sensitivity of ADX Tide Zones can be fine-tuned for different trading objectives. Lower thresholds heighten responsiveness, capturing micro-moves suitable for scalpers. Higher thresholds filter minor fluctuations, isolating major structural swings that align with swing or position trading. Contextual Trade Management : Instead of using static stops or targets, traders can adapt risk management dynamically by tracking tide progression. For example, a trade initiated during Rising Tide may remain valid as long as conditions sustain, but partial profits or tighter stops can be applied once the zone shifts to Calm Tide. Inputs & Customization ADX Length : Define the lookback period for ADX calculation. Threshold Levels : Adjust sensitivity for Calm, Rising, Strong, and Falling Tides. Zone Visualization : Choose between bar coloring, background shading, or overlays. Color Customization : Configure bullish, bearish, neutral, and tide-specific colors. Multi-Timeframe Options : Enable tide readings from higher timeframes for confirmation. Why Use ADX Tide Zones ADX Tide Zones turns the complexity of momentum analysis into a visual system that highlights when markets are gearing up for moves, trending with conviction, or running out of steam. By combining adaptive ADX interpretation with customizable thresholds, traders can: Anticipate breakouts before volatility expands. Confirm the strength behind price trends. Spot exhaustion phases early to secure profits or prepare for reversals. Adapt strategies seamlessly between scalping, intraday, and swing trading. With its balance of simplicity and depth, ADX Tide Zones provides a structured lens for reading market momentum, equipping traders with the clarity needed to execute with discipline and confidence.
Pine Script®指标
由BOSWaves提供
ZLEMA Trend Index 2.0ZTI — ZLEMA Trend Index 2.0 (0–1000) Overview Price Mapped ZTI v2.0 - Enhanced Zero-Lag Trend Index. This indicator is a significant upgrade to the original ZTI v1.0, featuring enhanced resolution from 0-100 to 0-1000 levels for dramatically improved price action accuracy. The Price Mapped ZTI uses direct price-to-level mapping to eliminate statistical noise and provide true proportional representation of market movements. Key Innovation: Instead of statistical normalization, this version maps current price position within a user-defined lookback period directly to the ZTI scale, ensuring perfect correlation with actual price movements. I believe this is the best way to capture trends instead of directly on the charts using a plethora of indicators which introduces bad signals resulting in drawdowns. The RSI-like ZTI overbought and oversold lines filter valid trends by slicing through the current trading zone. Unlike RSI that can introduce false signals, the ZTI levels 1 to 1000 is faithfully mapped to the lowest to highest price in the current trading zone (lookback period in days) which can be changed in the settings. The ZTI line will never go off the beyond the ZTI levels in case of extreme trend continuation as the trading zone is constantly updated to reflect only the most recent bars based on lookback days. Core Features ✅ 10x Higher Resolution - 0-1000 scale provides granular movement detection ✅ Adjustable Trading Zone - Customizable lookback period from 1-50 days ✅ Price-Proportional Mapping - Direct correlation between price position and ZTI level ✅ Zero Statistical Lag - No rolling averages or standard deviation calculations ✅ Multi-Strategy Adaptability - Single parameter adjustment for different trading styles Trading Zone Optimization 📊 Lookback Period Strategies Short-term (1-3 days): Ultra-responsive to recent price action Perfect for scalping and day trading Tight range produces more sensitive signals Medium-term (7-14 days): Balanced view of recent trading range Ideal for swing trading Captures meaningful support/resistance levels Long-term (21-30 days): Broader market context Excellent for position trading Smooths out short-term market noise ⚡ Market Condition Adaptation Volatile Markets: Use shorter lookback (3-5 days) for tighter ranges Trending Markets: Use longer lookback (14-21 days) for broader context Ranging Markets: Use medium lookback (7-10 days) for clear boundaries 🎯 Timeframe Optimization 1-minute charts: 1-2 day lookback 5-minute charts: 2-5 day lookback Hourly charts: 7-14 day lookback Daily charts: 21-50 day lookback Trading Applications Scalping Setup (2-day lookback): Super tight range for quick reversals ZTI 800+ = immediate short opportunity ZTI 200- = immediate long opportunity Swing Trading Setup (10-day lookback): Meaningful swing levels captured ZTI extremes = high-probability reversal zones More stable signals, reduced whipsaws Advanced Usage 🔧 Real-Time Adaptability Trending days: Increase to 14+ days for broader perspective Range-bound days: Decrease to 3 days for tighter signals High volatility: Shorter lookback for responsiveness Low volatility: Longer lookback to avoid false signals 💡 Multi-Timeframe Approach Entry signals: Use 7-day ZTI on main timeframe Trend confirmation: Use 21-day ZTI on higher timeframe Exit timing: Use 3-day ZTI for precise exits 🌐 Session Optimization Asian session: Shorter lookback (3-5 days) for range-bound conditions London/NY session: Longer lookback (7-14 days) for trending conditions How It Works The indicator maps the current price position within the specified lookback period directly to a 0-1000 scale and plots it using ZLEMA (Zero Lag Exponential Moving Average) which has the least lag of the available popular moving averages: Price at recent high = ZTI at 1000 Price at recent low = ZTI at 1 Price at mid-range = ZTI at 500 This creates perfect proportional representation where every price movement translates directly to corresponding ZTI movement, eliminating the false signals common in traditional oscillators. This single, versatile indicator adapts to any market condition, timeframe, or trading style through one simple parameter adjustment, making it an essential tool for traders at every level. Credits ZLEMA techniques widely attributed to John Ehlers. Disclaimer This tool is for educational purposes only and is not financial advice. Backtest and forward‑test before live use, and always manage risk. Please note that I set this as closed source to prevent source code cloning by others, repackaging and republishing which results in multiple confusing choices of the same indicator.
Pine Script®指标
由Coinbank-MMXXV提供
1
ORB with Golden Zone FIB targets, Any Timeframe by TenAMTraderDescription: This indicator is designed to help traders identify key price levels using Fibonacci extensions and retracements based on the Opening Range Breakout (ORB). The levels are visualized as “Golden Zones”, which can serve as potential targets for trades. Features: Customizable ORB Timeframe: By default, the ORB is set from 9:30 AM to 9:45 AM EST, but any timeframe can be configured in the settings to fit your trading style. Golden Zones as Targets: Fibonacci levels are intended to be used as potential profit-taking zones or areas to monitor for reversals, providing a structured framework for intraday and swing trading. Adjustable Chart Settings: Color-coded levels make it easy to interpret at a glance, and all lines can be customized for personal preference. Versatile Application: The indicator works across any timeframe, enabling traders to analyze both intraday and multi-day price action. How to Use: Ensure Regular Trading Hours (RTH) is enabled on your chart for accurate level calculation. Observe price action near Golden Zones: a confirmed breakout may indicate continuation, while a pullback could signal a reversal opportunity. Use the Golden Zones as reference targets for managing risk and planning exits. Adjust the ORB timeframe and display settings to match your preferred trading style. Legal Disclosure: This indicator is provided for educational purposes only and is not financial advice. Trading carries a substantial risk of loss. Users should always perform their own analysis and consult a licensed financial professional before making any trading decisions. Past performance is not indicative of future results.
Pine Script®指标
由TenAM_Trader提供
Swing Z | Zillennial Technologies Inc.Swing Z by Zillennial Technologies Inc. is an advanced algorithmic framework built specifically for cryptocurrency markets. It integrates multiple layers of technical analysis into a single decision-support tool, generating buy and sell signals only when several independent confirmations align. Core Concept Swing Z fuses trend structure, momentum oscillators, volatility signals, and price action tools to capture high-probability trading opportunities in volatile crypto environments. Trend Structure (EMA 9, 21, 50, 200) Short-term EMAs (9 & 21) detect immediate momentum shifts. Longer-term EMAs (50 & 200) define the broader trend and dynamic support/resistance. Momentum & Confirmation Layer RSI measures relative strength and market conditions. MACD crossovers confirm momentum shifts and trend continuations. Volatility & Market Pressure TTM Squeeze highlights compression zones likely to precede breakouts. Volume analysis confirms conviction behind directional moves. VWAP (Volume Weighted Average Price) establishes intraday value zones and institutional benchmarks. Price Action Filters Fibonacci retracements are integrated to identify key reversal and continuation levels. Signals are produced only when multiple conditions agree, reducing noise and improving reliability in fast-moving crypto markets. Features Tailored for cryptocurrency trading across major pairs (BTC, ETH, and altcoins). Works effectively on swing and trend-based timeframes (1H–1D). Combines trend, momentum, volatility, and price action into a single framework. Generates clear Buy/Sell markers and integrates with TradingView alerts. How to Use Apply to a clean chart for the clearest visualization. Use Swing Z as a swing trading tool, aligning entries with both trend structure and momentum confirmation. Combine with your own stop-loss, take-profit, and position sizing rules. Avoid application on non-standard chart types such as Renko, Heikin Ashi, or Point & Figure, which may distort results. Disclaimer Swing Z is designed as a decision-support tool, not financial advice. All backtesting should use realistic risk, commission, and slippage assumptions. Past results do not guarantee future performance. Signals do not repaint but may adjust as new data develops in real-time. Why Swing Z is original & useful: Swing Z unifies EMA trend structure, RSI, MACD, TTM Squeeze, VWAP, Fibonacci retracements, and volume analysis into a single algorithmic framework. This multi-confirmation approach improves accuracy by requiring consensus across trend, momentum, volatility, and price action — a design made specifically for the challenges and volatility of cryptocurrency markets.
Pine Script®指标
由ericc2c45提供
Swing Z – Crypto Trading Algorithm | Zillennial Technologies IncSwing Z by Zillennial Technologies Inc. is an advanced algorithmic framework built specifically for cryptocurrency markets. It integrates multiple layers of technical analysis into a single decision-support tool, generating buy and sell signals only when several independent confirmations align. Core Concept Swing Z fuses trend structure, momentum oscillators, volatility signals, and price action tools to capture high-probability trading opportunities in volatile crypto environments. Trend Structure (EMA 9, 21, 50, 200) Short-term EMAs (9 & 21) detect immediate momentum shifts. Longer-term EMAs (50 & 200) define the broader trend and dynamic support/resistance. Momentum & Confirmation Layer RSI measures relative strength and market conditions. MACD crossovers confirm momentum shifts and trend continuations. Volatility & Market Pressure TTM Squeeze highlights compression zones likely to precede breakouts. Volume analysis confirms conviction behind directional moves. VWAP (Volume Weighted Average Price) establishes intraday value zones and institutional benchmarks. Price Action Filters Fibonacci retracements are integrated to identify key reversal and continuation levels. Signals are produced only when multiple conditions agree, reducing noise and improving reliability in fast-moving crypto markets. Features Tailored for cryptocurrency trading across major pairs (BTC, ETH, and altcoins). Works effectively on swing and trend-based timeframes (1H–1D). Combines trend, momentum, volatility, and price action into a single framework. Generates clear Buy/Sell markers and integrates with TradingView alerts. How to Use Apply to a clean chart for the clearest visualization. Use Swing Z as a swing trading tool, aligning entries with both trend structure and momentum confirmation. Combine with your own stop-loss, take-profit, and position sizing rules. Avoid application on non-standard chart types such as Renko, Heikin Ashi, or Point & Figure, which may distort results. Disclaimer Swing Z is designed as a decision-support tool, not financial advice. All backtesting should use realistic risk, commission, and slippage assumptions. Past results do not guarantee future performance. Signals do not repaint but may adjust as new data develops in real-time. Why Swing Z is original & useful: Swing Z unifies EMA trend structure, RSI, MACD, TTM Squeeze, VWAP, Fibonacci retracements, and volume analysis into a single algorithmic framework. This multi-confirmation approach improves accuracy by requiring consensus across trend, momentum, volatility, and price action — a design made specifically for the challenges and volatility of cryptocurrency markets.
Pine Script®指标
由ericc2c45提供
Persistence# Persistence ## What it does Measures **price change persistence**, defined as the percentage of bars within a lookback window that closed higher than the prior close. A high value means the instrument has been closing up frequently, which can indicate durable momentum. This mirrors Stockbee’s idea: *select stocks with high price change persistence*, and then combine **momentum plus persistence**. ## Can be used for scanning in PineScreener ## Calculation * `isUp` is true when `close > close `. * `countUp` counts true instances over the last `len` bars. * `pctUp = 100 * countUp / len`, bounded between 0 and 100. * A 50% level is a natural baseline. Above 50% suggests more up closes than down closes in the window. ## Inputs * **Lookback bars (`len`)**: default 252 for roughly one trading year on a daily chart. On weekly charts use something like 52, on monthly charts use 12. ## How to use 1. **Screen for persistence** Sort a watchlist by the plotted value, higher is better. Many momentum traders start looking above 58 to 65 percent, then layer a trend filter. 2. **Combine with momentum** Examples, pick tickers with: * `pctUp > 60`, and price above a rising EMA50 or EMA100. * `pctUp rising` and weekly ROC positive. 3. **Switch timeframe to change the horizon** * Daily chart with `len = 252` approximates one year. * Weekly chart with `len = 52` approximates one year. * Monthly chart with `len = 12` approximates one year. ## TC2000 equivalence Stockbee’s TC2000 expression: ``` CountTrue(c > c1, 252) ``` ## Interpretation guide * **70 to 90**: very strong persistence; often trend leaders, check for extensions and risk controls. * **60 to 70**: constructive persistence; good hunting ground for swing setups that also pass momentum filters. * **50**: neutral baseline; around random up vs down frequency. * **Below 50**: persistent weakness; consider only for mean reversion or short strategies. ## Practical tips * **Event effects**: ex-dividend gaps can reduce persistence on high yield names. Earnings gaps can swing the value sharply. * **Survivorship bias**: when backtesting on curated lists, persistence can look cleaner than in live scans. * **Liquidity**: thin names may show noisy persistence due to erratic prints. ## Reference to Stockbee * “One way to select stocks for swing trading is to find those with high price change persistence.” * “Persistence can be calculated on a daily, monthly, or weekly timeframe.” * TC2000 function: `CountTrue(c > c1, 252)` * Example noted in the tweet: CVNA had very high one-year price persistence at the time of that post. * Takeaway: **look for momentum plus persistence**, not persistence alone.
Pine Script®指标
由BB_9791提供
XAUUSD Buy/Sell Alerts with SL & TPThis custom TradingView indicator identifies high-probability buy and sell signals on XAUUSD using EMA crossovers combined with RSI confirmation. Designed for precision entries, it automatically calculates optimal Stop Loss (SL) and Take Profit (TP) levels based on user-defined pip distances. Key Features: Fast and Slow EMA crossover for trend direction RSI filter for momentum confirmation Dynamic SL and TP levels to manage risk and reward Visual buy/sell signals plotted on chart Real-time alerts with detailed messages including entry price, SL, and TP Suitable for multiple timeframes and trading styles Perfect for traders seeking clear signals with built-in risk management for scalping or swing trading XAUUSD.
Pine Script®指标
由alexandrossolomou1提供
Smart Money Precision Structure [BullByte]Smart Money Precision Structure Advanced Market Structure Analysis Using Institutional Order Flow Concepts --- OVERVIEW Smart Money Precision Structure (SMPS) is a comprehensive market analysis indicator that combines six analytical frameworks to identify high-probability market structure patterns. The indicator uses multi-dimensional scoring algorithms to evaluate market conditions through institutional order flow concepts, providing traders with professional-grade market analysis. --- PURPOSE AND ORIGINALITY Why This Indicator Was Developed • Addresses the gap between retail and institutional analysis methods • Consolidates multiple analysis techniques that professionals use separately • Automates complex market structure evaluation into actionable insights • Eliminates the need for multiple indicators by providing comprehensive analysis What Makes SMPS Original • Six-Layer Confluence System - Unique combination of market regime, structure, volume flow, momentum, price action, and adaptive filtering • Institutional Pattern Recognition - Identifies smart money accumulation and distribution patterns • Adaptive Intelligence - Parameters automatically adjust based on detected market conditions • Real-Time Market Scoring - Proprietary algorithm rates market quality from 0-100% • Structure Break Detection - Advanced pivot analysis identifies trend reversals early --- HOW IT WORKS - TECHNICAL METHODOLOGY 1. Market Regime Analysis Engine The indicator evaluates five core market dimensions: • Volatility Score - Measures current volatility against 50-period historical baseline • Trend Score - Analyzes alignment between 8, 21, and 50-period EMAs • Momentum Score - Combines RSI divergence with MACD signal alignment • Structure Score - Evaluates pivot point formation clarity • Efficiency Score - Calculates directional movement efficiency ratio These scores combine to classify markets into five regimes: • TRENDING - Strong directional movement with aligned indicators • RANGING - Sideways movement with mixed directional signals • VOLATILE - Elevated volatility with unpredictable price swings • QUIET - Low volatility consolidation periods • TRANSITIONAL - Market shifting between different regimes 2. Market Structure Analysis Advanced pivot point analysis identifies: • Higher Highs and Higher Lows for bullish structure • Lower Highs and Lower Lows for bearish structure • Structure breaks when established patterns fail • Dynamic support and resistance from recent pivot points • Key level proximity detection using ATR-based buffers 3. Volume Flow Decoding Institutional activity detection through: • Volume surge identification when volume exceeds 2x average • Buy versus sell pressure analysis using price-volume correlation • Flow strength measurement through directional volume consistency • Divergence detection between volume and price movements • Institutional threshold alerts when unusual volume patterns emerge 4. Multi-Period Momentum Synthesis Weighted momentum calculation across four timeframes: • 1-period momentum weighted at 40% • 3-period momentum weighted at 30% • 5-period momentum weighted at 20% • 8-period momentum weighted at 10% Result smoothed with 6-period EMA for noise reduction. 5. Price Action Quality Assessment Each bar evaluated for: • Range quality relative to 20-period average • Body-to-range ratio for directional conviction • Wick analysis for rejection pattern identification • Pattern recognition including engulfing and hammer formations • Sequential price movement analysis 6. Adaptive Parameter System Parameters automatically adjust based on detected regime: • Trending markets reduce sensitivity and confirmation requirements • Volatile markets increase filtering and require additional confirmations • Ranging markets maintain neutral settings • Transitional markets use moderate adjustments --- COMPLETE SETTINGS GUIDE Section 1: Core Analysis Settings Analysis Sensitivity (0.3-2.0) • Default: 1.0 • Lower values require stronger price movements • Higher values detect more subtle patterns • Scalpers use 0.8-1.2, swing traders use 1.5-2.0 Noise Reduction Level (2-7) • Default: 4 • Controls filtering of false patterns • Higher values reduce pattern frequency • Increase in volatile markets Minimum Move % (0.05-0.50) • Default: 0.15% • Sets minimum price movement threshold • Adjust based on instrument volatility • Forex: 0.05-0.10%, Stocks: 0.15-0.25%, Crypto: 0.20-0.50% High Confirmation Mode • Default: True (Enabled) • Requires all technical conditions to align • Reduces frequency but increases reliability • Disable for more aggressive pattern detection Section 2: Market Regime Detection Enable Regime Analysis • Default: True (Enabled) • Activates market environment evaluation • Essential for adaptive features • Keep enabled for best results Regime Analysis Period (20-100) • Default: 50 bars • Determines regime calculation lookback • Shorter for responsive, longer for stable • Scalping: 20-30, Swing: 75-100 Minimum Market Clarity (0.2-0.8) • Default: 0.4 • Quality threshold for pattern generation • Higher values require clearer conditions • Lower for more patterns, higher for quality Adaptive Parameter Adjustment • Default: True (Enabled) • Enables automatic parameter optimization • Adjusts based on market regime • Highly recommended to keep enabled Section 3: Market Structure Analysis Enable Structure Validation • Default: True (Enabled) • Validates patterns against support/resistance • Confirms trend structure alignment • Essential for reliability Structure Analysis Period (15-50) • Default: 30 bars • Period for structure pattern analysis • Affects support/resistance calculation • Match to your trading timeframe Minimum Structure Alignment (0.3-0.8) • Default: 0.5 • Required structure score for valid patterns • Higher values need stronger structure • Balance with desired frequency Section 4: Analysis Configuration Minimum Strength Level (3-5) • Default: 4 • Minimum confirmations for pattern display • 5 = Maximum reliability, 3 = More patterns • Beginners should use 4-5 Required Technical Confirmations (4-6) • Default: 5 • Number of aligned technical factors • Higher = fewer but better patterns • Works with High Confirmation Mode Pattern Separation (3-20 bars) • Default: 8 bars • Minimum bars between patterns • Prevents clustering and overtrading • Increase for cleaner charts Section 5: Technical Filters Momentum Validation • Default: True (Enabled) • Requires momentum alignment • Filters counter-trend patterns • Essential for trend following Volume Confluence Analysis • Default: True (Enabled) • Requires volume confirmation • Identifies institutional participation • Critical for reliability Trend Direction Filter • Default: True (Enabled) • Only shows patterns with trend • Reduces counter-trend signals • Disable for reversal hunting Section 6: Volume Flow Analysis Institutional Activity Threshold (1.2-3.5) • Default: 2.0 • Multiplier for unusual volume detection • Lower finds more institutional activity • Stock: 2.0-2.5, Forex: 1.5-2.0, Crypto: 2.5-3.5 Volume Surge Multiplier (1.8-4.5) • Default: 2.5 • Defines significant volume increases • Adjust per instrument characteristics • Higher for stocks, lower for forex Volume Flow Period (12-35) • Default: 18 bars • Smoothing for volume analysis • Shorter = responsive, longer = smooth • Match to timeframe used Section 7: Analysis Frequency Control Maximum Analysis Points Per Hour (1-5) • Default: 3 • Limits pattern frequency • Prevents overtrading • Scalpers: 4-5, Swing traders: 1-2 Section 8: Target Level Configuration Target Calculation Method • Default: Market Adaptive • Three modes available: - Fixed: Uses set point distances - Dynamic: ATR-based calculations - Market Adaptive: Structure-based levels Minimum Target/Risk Ratio (1.0-3.0) • Default: 1.5 • Minimum acceptable reward vs risk • Higher filters lower probability setups • Professional standard: 1.5-2.0 Fixed Mode Settings: • Fixed Target Distance: 50 points default • Fixed Invalidation Distance: 30 points default • Use for consistent instruments Dynamic Mode Settings: • Dynamic Target Multiplier: 1.8x ATR default • Dynamic Invalidation Multiplier: 1.0x ATR default • Adapts to volatility automatically Market Adaptive Settings: • Use Structure Levels: True (default) • Structure Level Buffer: 0.1% default • Places levels at actual support/resistance Section 9: Visual Display Settings Color Theme Options • Professional (Teal/Red) - Bullish: Teal (#26a69a) - Bearish: Red (#ef5350) - Neutral: Gray (#78909c) - Best for: Traditional traders, clean appearance • Dark (Neon Green/Pink) - Bullish: Neon Green (#00ff88) - Bearish: Hot Pink (#ff0044) - Neutral: Dark Gray (#333333) - Best for: Dark theme users, high contrast • Light (Green/Red Classic) - Bullish: Green (#4caf50) - Bearish: Red (#f44336) - Neutral: Light Gray (#9e9e9e) - Best for: Light backgrounds, traditional colors • Vibrant (Cyan/Magenta) - Bullish: Cyan (#00ffff) - Bearish: Magenta (#ff00ff) - Neutral: Medium Gray (#888888) - Best for: High visibility, modern appearance Dashboard Position • Options: Top Left, Top Right, Bottom Left, Bottom Right, Middle Left, Middle Right • Default: Top Right • Choose based on chart layout preference Dashboard Size • Full: Complete information display (desktop) • Mobile: Compact view for small screens • Default: Full Analysis Display Style • Arrows : Simple directional markers • Labels : Detailed text information • Zones : Colored areas showing pattern regions • Default: Labels (most informative) Display Options: • Display Analysis Strength: Shows star rating • Display Target Levels: Shows target/invalidation lines • Display Market Regime: Shows regime in pattern labels --- HOW TO USE SMPS - DETAILED GUIDE Understanding the Dashboard Top Row - Header • SMPS Dashboard title • VALUE column: Current readings • STATUS column: Condition assessments Market Regime Row • Shows: TRENDING, RANGING, VOLATILE, QUIET, or TRANSITIONAL • Color coding: Green = Favorable, Red = Caution • Status: FAVORABLE or CAUTION trading conditions Market Score Row • Percentage from 0-100% • Above 60% = Strong conditions • 40-60% = Moderate conditions • Below 40% = Weak conditions Structure Row • Direction: BULLISH, BEARISH, or NEUTRAL • Status: INTACT or BREAK • Orange BREAK indicates structure failure Volume Flow Row • Direction: BUYING or SELLING • Intensity: STRONG or WEAK • Color indicates dominant pressure Momentum Row • Numerical momentum value • Positive = Upward pressure • Negative = Downward pressure Volume Status Row • INST = Institutional activity detected • HIGH = Above average volume • NORM = Normal volume levels Adaptive Mode Row • ACTIVE = Parameters adjusting • STATIC = Fixed parameters • Shows required confirmations Analysis Level Row • Minimum strength level setting • Pattern separation in bars Market State Row • Current analysis: BULLISH, BEARISH, NEUTRAL • Shows analysis price level when active T:R Ratio Row • Current target to risk ratio • GOOD = Meets minimum requirement • LOW = Below minimum threshold Strength Row • BULL or BEAR dominance • Numerical strength value 0-100 Price Row • Current price • Percentage change Last Analysis Row • Previous pattern direction • Bars since last pattern Reading Pattern Signals Bullish Structure Pattern • Upward triangle or "Bullish Structure" label • Star rating shows strength (★★★★★ = strongest) • Green line = potential target level • Red dashed line = invalidation level • Appears below price bars Bearish Structure Pattern • Downward triangle or "Bearish Structure" label • Star rating indicates reliability • Green line = potential target level • Red dashed line = invalidation level • Appears above price bars Pattern Strength Interpretation • ★★★★★ = 6 confirmations (exceptional) • ★★★★☆ = 5 confirmations (strong) • ★★★☆☆ = 4 confirmations (moderate) • ★★☆☆☆ = 3 confirmations (minimum) • Below minimum = filtered out Visual Elements on Chart Lines and Levels: • Gray Line = 21 EMA trend reference • Green Stepline = Dynamic support level • Red Stepline = Dynamic resistance level • Green Solid Line = Active target level • Red Dashed Line = Active invalidation level Pattern Markers: • Triangles = Arrow display mode • Text Labels = Label display mode • Colored Boxes = Zone display mode Target Completion Labels: • "Target" = Price reached target level • "Invalid" = Pattern invalidated by price --- RECOMMENDED USAGE BY TIMEFRAME 1-Minute Charts (Scalping) • Sensitivity: 0.8-1.2 • Noise Reduction: 3-4 • Pattern Separation: 3-5 bars • High Confirmation: Optional • Best for: Quick intraday moves 5-Minute Charts (Precision Intraday) • Sensitivity: 1.0 (default) • Noise Reduction: 4 (default) • Pattern Separation: 8 bars • High Confirmation: Enabled • Best for: Day trading 15-Minute Charts (Short Swing) • Sensitivity: 1.0-1.5 • Noise Reduction: 4-5 • Pattern Separation: 10-12 bars • High Confirmation: Enabled • Best for: Intraday swings 30-Minute to 1-Hour (Position Trading) • Sensitivity: 1.5-2.0 • Noise Reduction: 5-7 • Pattern Separation: 15-20 bars • Regime Period: 75-100 • Best for: Multi-day positions Daily Charts (Swing Trading) • Sensitivity: 1.8-2.0 • Noise Reduction: 6-7 • Pattern Separation: 20 bars • All filters enabled • Best for: Long-term analysis --- MARKET-SPECIFIC SETTINGS Forex Pairs • Minimum Move: 0.05-0.10% • Institutional Threshold: 1.5-2.0 • Volume Surge: 1.8-2.2 • Target Mode: Dynamic or Market Adaptive Stock Indices (ES, NQ, YM) • Minimum Move: 0.10-0.15% • Institutional Threshold: 2.0-2.5 • Volume Surge: 2.5-3.0 • Target Mode: Market Adaptive Individual Stocks • Minimum Move: 0.15-0.25% • Institutional Threshold: 2.0-2.5 • Volume Surge: 2.5-3.5 • Target Mode: Dynamic Cryptocurrency • Minimum Move: 0.20-0.50% • Institutional Threshold: 2.5-3.5 • Volume Surge: 3.0-4.5 • Target Mode: Dynamic • Increase noise reduction --- PRACTICAL APPLICATION EXAMPLES Example 1: Strong Trending Market Dashboard Reading: • Market Regime: TRENDING • Market Score: 75% • Structure: BULLISH, INTACT • Volume Flow: BUYING, STRONG • Momentum: +0.45 Interpretation: • Strong uptrend environment • Institutional buying present • Look for bullish patterns as continuation • Higher probability of success • Consider using lower sensitivity Example 2: Range-Bound Conditions Dashboard Reading: • Market Regime: RANGING • Market Score: 35% • Structure: NEUTRAL • Volume Flow: SELLING, WEAK • Momentum: -0.05 Interpretation: • No clear direction • Low opportunity environment • Patterns are less reliable • Consider waiting for regime change • Or switch to a range-trading approach Example 3: Structure Break Alert Dashboard Reading: • Previous: BULLISH structure • Current: Structure BREAK • Volume: INST flag active • Momentum: Shifting negative Interpretation: • Trend reversal potentially beginning • Institutional participation detected • Watch for bearish pattern confirmation • Adjust bias accordingly • Increase caution on long positions Example 4: Volatile Market Dashboard Reading: • Market Regime: VOLATILE • Market Score: 45% • Adaptive Mode: ACTIVE • Confirmations: Increased to 6 Interpretation: • Choppy conditions • Parameters auto-adjusted • Fewer but higher quality patterns • Wider stops may be needed • Consider reducing position size Below are a few chart examples of the Smart Money Precision Structure (SMPS) indicator in action. • Example 1 – Bullish Structure Detection on SOLUSD 5m • Example 2 – Bearish Structure Detected with Strong Confluence on SOLUSD 5m --- TROUBLESHOOTING GUIDE No Patterns Appearing Check these settings: • High Confirmation Mode may be too restrictive • Minimum Strength Level may be too high • Market Clarity threshold may be too high • Regime filter may be blocking patterns • Try increasing sensitivity Too Many Patterns Adjust these settings: • Enable High Confirmation Mode • Increase Minimum Strength Level to 5 • Increase Pattern Separation • Reduce Sensitivity below 1.0 • Enable all technical filters Dashboard Shows "CAUTION" This indicates: • Market conditions are unfavorable • Regime is RANGING or QUIET • Market score is low • Consider waiting for better conditions • Or adjust expectations accordingly Patterns Not Reaching Targets Consider: • Market may be choppy • Volatility may have changed • Try Dynamic target mode • Reduce target/risk ratio requirement • Check if regime is VOLATILE --- ALERTS CONFIGURATION Alert Message Format Alerts include: • Pattern type (Bullish/Bearish) • Strength rating • Market regime • Analysis price level • Target and invalidation levels • Strength percentage • Target/Risk ratio • Educational disclaimer Setting Up Alerts • Click Alert button on TradingView • Select SMPS indicator • Choose alert frequency • Customize message if desired • Alerts fire on pattern detection --- DATA WINDOW INFORMATION The Data Window displays: • Market Regime Score (0-100) • Market Structure Bias (-1 to +1) • Bullish Strength (0-100) • Bearish Strength (0-100) • Bull Target/Risk Ratio • Bear Target/Risk Ratio • Relative Volume • Momentum Value • Volume Flow Strength • Bull Confirmations Count • Bear Confirmations Count --- BEST PRACTICES AND TIPS For Beginners • Start with default settings • Use High Confirmation Mode • Focus on TRENDING regime only • Paper trade first • Learn one timeframe thoroughly For Intermediate Users • Experiment with sensitivity settings • Try different target modes • Use multiple timeframes • Combine with price action analysis • Track pattern success rate For Advanced Users • Customize per instrument • Create setting templates • Use regime information for bias • Combine with other indicators • Develop systematic rules --- IMPORTANT DISCLAIMERS • This indicator is for educational and informational purposes only • Not financial advice or a trading system • Past performance does not guarantee future results • Trading involves substantial risk of loss • Always use appropriate risk management • Verify patterns with additional analysis • The author is not a registered investment advisor • No liability accepted for trading losses --- VERSION NOTES Version 1.0.0 - Initial Release • Six-layer confluence system • Adaptive parameter technology • Institutional volume detection • Market regime classification • Structure break identification • Real-time dashboard • Multiple display modes • Comprehensive settings ## My Final Thoughts Smart Money Precision Structure represents an advanced approach to market analysis, bringing institutional-grade techniques to retail traders through intelligent automation and multi-dimensional evaluation. By combining six analytical frameworks with adaptive parameter adjustment, SMPS provides comprehensive market intelligence that single indicators cannot achieve. The indicator serves as an educational tool for understanding how professional traders analyze markets, while providing practical pattern detection for those seeking to improve their technical analysis. Remember that all trading involves risk, and this tool should be used as part of a complete analysis approach, not as a standalone trading system. - BullByte
Pine Script®指标
由BullByte提供
6
Smart Money Trades Pro [BOSWaves]Smart Money Trades Pro – Advanced Market Structure & Liquidity Visualizer Overview Smart Money Trades Pro is a comprehensive trading tool designed for traders seeking an in-depth understanding of market structure, liquidity dynamics, and institutional flow. The indicator systematically identifies key market turning points, including break of structure (BOS) and change of character (CHoCH) events, and overlays these with adaptive visualizations to highlight high-probability trade setups. By integrating ATR-based risk zones, progressive take-profit levels, and real-time trade analytics, Smart Money Trades Pro transforms complex price action into an interpretable framework suitable for multiple trading styles, including scalping, intraday, and swing trading. Unlike traditional static indicators, Smart Money Trades Pro adapts continuously to market conditions. It evaluates swing highs and lows over a configurable lookback period, then determines structural breaks using customizable confirmation methods (candle body or wick). The resulting signals are augmented with dynamic entry, stop-loss, and target levels, allowing traders to analyze potential trade opportunities with both precision and context. The indicator’s design ensures that each visual element—trend-colored candles, signal markers, and risk/reward boxes—reflects real-time market conditions, offering an actionable interpretation of institutional activity. How It Works The indicator’s foundation is built upon market structure analysis. By calculating pivot highs and lows over a specified period, Smart Money Trades Pro identifies potential points of liquidity accumulation and exhaustion. When price breaks a pivot high or low, the indicator evaluates whether this constitutes a BOS or a CHoCH, signaling trend continuation or reversal. These events are marked on the chart with distinct visual cues, allowing traders to quickly discern shifts in market sentiment without manually analyzing historical price action. Once a structural break is confirmed, the indicator automatically determines entry levels, stop-loss placements, and progressive take-profit zones (TP1, TP2, TP3). These calculations are based on ATR-derived volatility, ensuring that targets scale with current market conditions. Risk and reward zones are plotted as shaded boxes, providing a clear visual representation of potential profit relative to risk for each trade setup. This system allows traders to maintain discipline and consistency, with dynamic trade management baked directly into the visualization. Trend direction is further reinforced by color-coded candles, which reflect the prevailing market bias. Bullish trends are represented by one color, bearish trends by another, and neutral conditions are displayed in muted tones. This continuous visual feedback simplifies the process of trend assessment and helps confirm the validity of trade setups alongside BOS and CHoCH markers. Signals and Breakouts Smart Money Trades Pro includes structured visual signals to indicate actionable price movements: Bullish Break Signals – Triangular markers below the candle appear when a swing high is broken, suggesting potential long opportunities. Bearish Break Signals – Triangular markers above the candle appear when a swing low is broken, indicating potential short setups. Change of Character (CHoCH) – Special markers highlight trend reversals, showing where momentum shifts from bullish to bearish or vice versa. These markers are strategically spaced to prevent overlap and remain clear during high-volatility periods. Traders can use them in combination with trend-colored candles, risk/reward zones, and ATR-based targets to assess the strength and reliability of each setup. The integrated table provides live trade information, including entry price, stop-loss level, take-profit levels, risk/reward ratio, and trade direction, ensuring that trade decisions are informed and data-driven. Interpretation Trend Analysis : The indicator’s trend coloring, combined with BOS and CHoCH detection, provides an immediate view of market direction. Rising structures indicate bullish momentum, while falling structures signal bearish momentum. CHoCH markers highlight potential trend reversals or significant liquidity sweeps. Volatility and Risk Assessment : ATR-based calculations determine stop-loss distances and target levels, giving a quantitative measure of risk relative to market volatility. Wide ATR readings indicate periods of high price fluctuation, whereas narrow readings suggest consolidation and reduced risk exposure. Market Structure Insights : By monitoring swing highs and lows alongside break confirmations, traders can identify where institutional players are likely active. Areas with multiple structural breaks or overlapping targets can indicate liquidity hotspots, potential reversal zones, or areas of market congestion. Trade Management : The built-in trade zones allow traders to visualize entry, risk, and reward simultaneously. Progressive targets (TP1, TP2, TP3) reflect incremental profit-taking strategies, while dynamic stop-loss levels help preserve capital during adverse moves. Strategy Integration Smart Money Trades Pro supports a range of trading approaches: Trend Following : Enter trades in the direction of confirmed BOS while using CHoCH markers and trend-colored candles to validate momentum. Pullback Entries : Use failed breakout retests or minor reversals toward broken structure levels for lower-risk entries. Mean Reversion : In consolidated zones with narrow ATR and repeated BOS/CHoCH activity, anticipate reversals or short-term corrective moves. Multi-Timeframe Confirmation : Overlay signals on higher or lower timeframes to filter noise and improve trade accuracy. Stop-loss levels should be placed just beyond the opposing structural point, while take-profit targets can be scaled using the ATR-based zones. Progressive targets allow for partial exits or scaling out of trades while maintaining exposure to larger moves. Advanced Techniques Traders seeking greater precision can combine Smart Money Trades Pro with volume, momentum, or volatility indicators to validate signals. Observing sequences of BOS and CHoCH markers across multiple timeframes provides insight into liquidity accumulation and depletion trends. Tracking the expansion or contraction of ATR-based zones helps anticipate shifts in volatility, enabling better timing for entries and exits. Customizing the structure period and confirmation type allows the indicator to adapt to different asset classes and timeframes. Shorter periods increase sensitivity to smaller swings, while longer periods filter noise and emphasize higher-probability structural breaks. By integrating these features, the indicator offers a robust statistical framework for disciplined, data-driven trading decisions. Inputs and Customization Structure Detection Period : Defines the lookback window for pivot high and low calculation. Break Confirmation : Choose whether to confirm breaks using candle body or wick. Display CHoCH : Toggle visibility of change-of-character markers. Color Trend Bars : Enable color-coding of candles based on market structure direction. Show Info Table : Display trade dashboard showing entry, stop-loss, take-profits, risk/reward, and bias. Table Position : Choose from top-left, top-right, bottom-left, or bottom-right placement. Color Customization : Configure bullish, bearish, neutral, risk, reward, and text colors for enhanced visual clarity. Why Use Smart Money Trades Pro Smart Money Trades Pro transforms complex market behavior into an actionable visual framework. By combining market structure analysis, liquidity tracking, ATR-based risk/reward mapping, and a dynamic trade dashboard, it provides a multidimensional view of the market. Traders can focus on execution, interpret trends, and evaluate overextensions or reversals without relying on guesswork. The indicator is suitable for scalping, intraday, and swing strategies, offering a comprehensive system for understanding and trading alongside institutional participants.
Pine Script®指标
由BOSWaves提供
10