Minimum Variance SMAReturn the value of a simple moving average with a period within the range min to max such that the variance of the same period is the smallest available.
Since the smallest variance is often the one with the smallest period, a penalty setting is introduced, and allows the indicator to return moving averages values with higher periods more often, with higher penalty values returning moving averages values with higher periods.
Because variances with smaller periods are more reactive than ones with higher periods, it is common for the indicator to return the value of an SMA of a higher period during more volatile market, this can be seen on the image below:
here variances from period 10 to 15 are plotted, a blueish color represents a higher period, note how they are the smallest ones when fluctuations are more volatile.
Indicator with min = 50, max = 200 and penalty = 0.5
In blue the indicator with penalty = 0, in red with penalty = 1, with both min = 50 and max = 200.
On The Script
The script minimize Var(i)/p with i ∈ (min,max) and p = i^penalty , this is done by computing the variance for each period i and keeping the smallest one currently in the loop, if we get a variance value smaller than the previously one found we calculate the value of an SMA with period i , as such the script deal with brute force optimization.
For our use case it is not possible to use the built-in sma and variance functions within a loop, as such we use cumulative forms for both functions.
在脚本中搜索"one一季度财报"
RenkoNow you can plot a "Renko" chart on any timeframe for free! As with my previous algorithm, you can plot the "Linear Break" chart on any timeframe for free!
I again decided to help TradingView programmers and wrote code that converts a standard candles / bars to a "Renko" chart. The built-in renko() and security() functions for constructing a "Renko" chart are working wrong. Do not try to write strategies based on the built-in renko() function! The developers write in the manual: "Please note that you cannot plot Renko bricks from Pine script exactly as they look. You can only get a series of numbers similar to OHLC values for Renko bars and use them in your algorithms". However, it is possible to build a "Renko" chart exactly like the "Renko" chart built into TradingView. Personally, I had enough Pine Script functionality.
For a complete understanding of how such a chart is built, you can read to Steve Nison's book "BEYOND JAPANESE CANDLES" and see the instructions for creating a "Renko" chart:
Rule 1: one white brick (or series) is built when the price rises above the base price by a fixed threshold value or more.
Rule 2: one black brick (or series) is built when the price falls below the base price by a fixed threshold or more.
Rule 3: if the rise or fall of the price is less than the minimum fixed value, then new bricks are not drawn.
Rule 4: if today's closing price is higher than the maximum of the last brick (white or black) by a threshold or more, move to the column to the right and build one or more white bricks of equal height. A new brick begins with the maximum of the previous brick.
Rule 5: if today's closing price is below the minimum of the last brick (white or black) by a threshold or more, move to the column to the right and build one or more black bricks of equal height. A new brick begins with the minimum of the previous brick.
Rule 6: if the price is below the maximum or above the minimum, then new bricks are not drawn on the chart.
So my algorithm can to plot Traditional Renko with a fixed box size. I want to note that such a "Renko" chart is slightly different from the "Renko" chart built into TradingView, because as a base price I use (by default) close of first candle. How the developers of TradingView calculate the base price I don’t know. Personally, I do as written in the book of Steve Neeson.
The algorithm is very complicated and I do not want to explain it in detail. I will explain very briefly. The first part of the get_renko () function — // creating lists — creates two lists that record how many green bricks should be and how many red bricks. The second part of the get_renko () function — // creating open and close series — creates open and close series to plot bricks. So, this is a white box - study it!
As you understand, one green candle can create a condition under which it will be necessary to plot, for example, 10 green bricks. So the smaller the box size you make, the smaller the portion of the chart you will see.
I stuffed all the logic into a wrapper in the form of the get_renko() function, which returns a tuple of OHLC values. And these series with the help of the plotcandle() annotation can be converted to the "Renko" chart. I also want to note that with a large number of candles on the chart, outrages about the buffer size uncertainty are heard from the TradingView blackbox. Because of it, in the annotation study() set the value of the max_bars_back parameter.
In general, use this script (for example, to write strategies)!
Time Range StatisticsA good amount of users requested a text box showing various price statistics, the following script returns various of these stats in a user-selected range, and include classical ones such as a central tendency measurement (mean), dispersion (normalized range) and percent change, but also include less common statistics such as average traded volume and number of gaps. The script also calculates the correlation between the closing price and another user-selected instrument.
The script is currently the longest one I ever made and took some efforts, as I wasn't satisfied with the statistics to be originally included. Big thx to Gael for the enormous feedback and the idea of the normalized range, to user @Cookiecrush for the feedback ( without ya I would have posted something bad you know umu ? ), and Lulidolce for the support, friendship is magic!
Selected Range
The setting Start determine the bar at which the range starts, while End determine at which bar the range end. To help you select these values, the current bar number (bar index) is displayed at the right of the indicator title in blue.
The setting evaluate to last bar will use a range starting at Start and ending at the last bar, as such you can use a full range by using Start = 0 and select evaluate to last bar
The range is highlighted by an area on the chart. By default Start = 9000 and End = 10000, you might not have this amount of data in your chart, as such use the displayed bar index to select Start and End, then set the settings as default.
Displayed Statistics
The statistics panel is displayed on the right side of the last bar, the panel has 3 sections, a title section who shows the symbol ticker, timeframe, and overall trends represented by a chart emoji, the overall trends are determined by comparing the number of higher highs with the number of lower low.
Below are displayed the date ranges with time format: year/month/day/hour:minute.
The second section shows the general statistics. The first one is the mean, also represented by the orange line in the chart, the blue line displayed represent the highest price value in the range, while the red one represents the lowest price value.
The second stat is the normalized range, and determine how spread is the price in the user-selected range, why not the standard deviation? Because the standard deviation might return results varying widely depending on the scale of the closing price, you could get measures such as 0.0156 or 16 or even 56 depending on the instrument, as such using a normalized range can be more appropriate as it lays in a range of (0,1). Lower values indicate a low degree of price variation. Note that I still want to find another measure in the future.
The percentage change (or relative change) indicates at which percentage the price has increased or decreased, and is calculated by subtracting the closing at bar Start with the price at bar End , divided by the price at bar End , the result is then multiplied by 100.
The average traded volume calculate the mean of the volume in the selected range, I used the same format used by the original volume indicator for clarity.
Finally, the last stats of the section is the number of gaps, this stat is by default hidden. An up gap is detected when the open price is superior to the previous high, while a down gap is detected when the open price is inferior to the previous low, this allow to only retain significant gaps.
The last section of the indicator panel shows the correlation between the closing price and another instrument, by default GOOG, this correlation is also calculated within the user-selected range. Positive values indicate a positive relationship, that is the two instruments tend to move in the same direction. Negative values indicate a negative relationship, both instruments tend to move in a direction opposite to each other. Values closer to 1 or -1 indicate a stronger relationship, while values closer to 0 indicate no relationship.
In Summary
The script shows various stats, each calculated within a user-selected range, in general one would be more interested in how these stats might evolve with time, but checking them in a custom range can be quite interesting.
Thx for reading. umu
Histogram - Price Action - Dy CalculatorThis script aims to help users of Price Action robot, for Smarttbot (brazilian site that automates Brazilian market (B3)).
You can use on any symbol.
The script will follow price action principles. It will calculate the absolute value of last candle and compare with actual candle. Colors are:
- Red - If the actual candle absolute value is higher than previous one, and the price is lower than last candle. It would be a short entry.
- Blue - If the actual candle absolute value is higher than previous one, and the price is higher than last candle. It would be a long entry.
- Black - The actual candle absolute value is lower than previous one, so there is no entry.
If there is a candle that is higher than previous one, and both high and low values are outside boundaries of previous one, it will calculate which boundary is bigger and will apply the collor accordingly.
eha Moving Averages StrategyMoving Average based strategies are very popular ones among both long-term investors and short-term traders as they can be tailored to any time frame. One of the main moving average strategies are crossovers. The very simple type is a price crossover , which is when the price crosses above or below a moving average to signal a potential change in trend.
Another strategy is to apply two moving averages to a chart: one longer (or slow) and one shorter (or fast). When the shorter-term MA crosses above the longer-term MA, it's a buy signal, as it indicates that the trend is shifting up (also known as “ Golden Cross ”). Meanwhile, when the shorter-term MA crosses below the longer-term MA, it's a sell signal, as it indicates that the trend is shifting down (which is also known as “ Dead/Death Cross ”).
This is a study to find a suitable trading strategy for 4-6 hour time frames. As you can see the performance is currently very poor. It has just generated almost 90 trades in a very long period from January 2017 to the time of publishing the study for the first time.
Moving averages work quite well in strong trending conditions but poorly in choppy or ranging conditions. Adjusting the time frame can correct this problem temporarily, although, at some point, these issues are likely to occur regardless of the time frame chosen for the moving average(s).
I am working on this basic strategy to make its performance better and I will update the post in the future. So keep in touch by following the post.
Why have I republished my study?
It sounds like TradingView stores and indexes scripts based on the title of the post rather than the actual title of the scripts and if one chose general terms as the title of the post, the TradingView script search engine may be unable to find it. So I decided to repost the strategy with a more searchable and unique prefix of " eha ".
Please provide me with your precious feedback.
Dual Purpose Pine Based CorrelationThis is my "Pine-based" correlation() function written in raw Pine Script. Other names applied to it are "Pearson Correlation", "Pearson's r", and one I can never remember being "Pearson Product-Moment Correlation Coefficient(PPMCC)". There is two basic ways to utilize this script. One is checking correlation with another asset such as the S&P 500 (provided as a default). The second is using it as a handy independent indicator correlated to time using Pine's bar_index variable. Also, this is in fact two separate correlation indicators with independent period adjustments, so I guess you could say this indicator has a dual purpose split personality. My intention was to take standard old correlation and apply a novel approach to it, and see what happens. Either way you use it, I hope you may find it most helpful enough to add to your daily TV tool belt.
You will notice I used the Pine built-in correlation() in combination with my custom function, so it shows they are precisely equal, even when the first two correlation() parameters are reversed on purpose or by accident. Additionally, there's an interesting technique to provide a visually appealing line with two overlapping plot()s combined together. I'm sure many members may find that plotting tactic useful when a bird's nest of plotting is occurring on the overlay pane in some scenarios. One more thing about correlation is it's always confined to +/-1.0 irregardless of time intervals or the asset(s) it is applied to, making it a unique oscillator.
As always, I have included advanced Pine programming techniques that conform to proper "Pine Etiquette". For those of you who are newcomers to Pine Script, this code release may also help you comprehend the "Power of Pine" by employing advanced programming techniques in Pine exhibiting code utilization in a most effective manner. One of the many tricks I applied here was providing floating point number safeties for _correlation(). While it cannot effectively use a floating point number, it won't error out in the event this should occur especially when applying "dominant cycle periods" to it, IF you might attempt this.
NOTICE: You may have observed there is a sqrt() custom function and you may be thinking... "Did he just sick and twistedly overwrite the Pine built-in sqrt() function?" The answer is... YES, I am and yes I did! One thing I noticed, is that it does provide slightly higher accuracy precision decimal places compared to the Pine built-in sqrt(). Be forewarned, "MY" sqrt() is technically speaking slower than snail snot compared to the native Pine sqrt(), so I wouldn't advise actually using it religiously in other scripts as a daily habit. It is seemingly doing quite well in combination with these simple calculations without being "sluggish". Lastly, of course you may always just delete the custom sqrt() function, via Pine Editor, and then the script will still operate flawlessly, yet more efficiently.
Features List Includes:
Dark Background - Easily disabled in indicator Settings->Style for "Light" charts or with Pine commenting
AND much, much more... You have the source!
The comments section below is solely just for commenting and other remarks, ideas, compliments, etc... regarding only this indicator, not others. When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I may implement more ideas when they present themselves as worthy additions. As always, "Like" it if you simply just like it with a proper thumbs up, and also return to my scripts list occasionally for additional postings. Have a profitable future everyone!
Pivots MTF [LucF]Pivots detected at higher timeframes are more significant because more market activity—or work—is required to produce them. This indicator displays pivots calculated on the higher timeframe of your choice.
Features
► Timeframe selection
— The higher timeframe (HTF) can be selected in 3 different ways:
• By steps (15 min., 60 min., 4H, 1D, 3D, 1W, 1M, 1Y). This setting is the default.
• As a multiple of the current chart's resolution, which can be fractional, so 3.5 will work.
• Fixed.
— The HTF used can be displayed near the last bar (default).
— Note that using the HTF is not mandatory. If it is disabled, the indicator will calculate on the chart's resolution.
— Non-repainting or repainting mode can be selected. This has no impact on the display of historical bars, but when no repainting is selected, pivot detection in the realtime bar will be delayed by one chart bar (not one bar at the HTF).
► Pivots
— Three color schemes are provided: green/red, aqua/pink and coral/violet (the default).
— Both the thickness and brightness of lines can be controlled separately for the hi and lo pivots.
— The visibility of the last hi/lo pivots can be enhanced.
— Prices can be displayed on pivot lines and the text's size and color can be adjusted.
— The number of bars required for the left/right pivot legs can be controlled (the default is 4).
— The source can be selected individually for hi and lo pivots (the default is hlc3 and low .
— The mean of the hi/lo pivot values of the last few thousand chart bars can be displayed. Pivots having lasted longer during the mean's period will weigh more in the calculation. The mean can be displayed in running mode and/or only showing its last level as a long horizontal line. I don't find it very useful; maybe others will.
► Markers and Alerts
— Markers can be configured on breaches of either the last hi/lo pivot levels, or the hi/lo mean. Crossovers and crossunders are controlled separately.
— Alerts can be configured using any of the marker combinations. As is usual for my indicators, only one alert is used. It will trigger on the markers that are active when you create your alert. Once your markers are set up the way you want, create your alert from the chart/timeframe you want the alert to run on, and be sure to use the “Once Per Bar Close” triggering condition. Use an alert message that will remind you of the combination of markers used when creating the alert. If you use multiple markers to trigger one alert, then having the indicator show those markers will be important to help you figure out which marker triggered the alert when it fired.
A quick look at the pattern of these markers will hopefully convince you that using them as entry/exit signals would be perilous, as they are prone to whipsaw. I have included them because some traders may use the markers as reminders.
Using Pivots
These pivots can be used in a few different ways:
— When using the high / low sources they will show extreme levels, breaches of which should be more significant.
— Another way to use them is with hlc3 (the average of the high , low and close ) for hi pivots and low for the lo pivots. This accounts for my personal mythology to the effect that drops typically reach previous lows more easily than rallies make newer highs.
— Using low for hi pivots and high for lo pivots (so backward) can be a useful way to set stops or to detect weakness in movements.
You will usually be better served by pivots if you consider them as denoting regions rather than precise levels. The flexibility in the display options of this indicator will help you adapt it to the way you use your pivots. To indicate areas rather than levels, for example, try using a brightness of 1 with a line thickness of 30. The cloud effect generated this way will show areas better than fine lines.
Realize that these pivot lines are positioned in the past, and so they are drawn after the fact because a given number of bars need to elapse before calculations determine a pivot has occurred. You will thus never see a pivot top, for example, identified on the realtime bar. To detect a pivot, it takes a number of bars corresponding to the dilation of the higher timeframe in the current one, multiplied by the number of bars you use for your pivots' right leg. Also note that the Pine native function used to detect pivots in this indicator considers a summit to be a top when the number of bars in each leg are lower or equal to that top. Bars in legs do not need to be progressively lower on each side of the pivot for a pivot to be detected.
If you program in Pine
— See the Pinecoders MTF Selection Framework for an explanation of the functions used in this script to provide the selection mechanism for the higher timeframe.
— This code uses the Pine Script Coding Conventions .
Thanks
— To the Pine coders asking questions in the Pine Script chat on TV ; your questions got me to write this indicator.
Center Of Linearity - A More Efficient Alternative To Elhers CGIntroduction
The center of gravity oscillator (CG) is one of the oscillators presented in Elhers book "cybernetic analysis for stocks and futures". This oscillator can be described as a bandpass filter centered around 0, its simplicity is ridiculous yet this indicator managed to get a pretty great popularity, this might be due to Elhers saying that he has substantial advantages over conventional oscillators used in technical analysis.
Today i propose a more efficient estimation of the center of gravity oscillator, this estimation will only use one convolution, while the original and other estimations use 2. I will also explain everything about the center of gravity oscillator, because even if its name can be imposing its actually super easy to understand.
The Center Of Gravity Oscillator
The CG oscillator is a bandpass filter, in short it filter high frequencies components as well as low frequency ones, this is why the oscillator is both smooth (no high frequencies) as well as detrended (no low frequencies), and therefore the oscillator focus exclusively on the cycles.
Its calculation is simple, its just a linearly weighted moving average minus a simple moving average wma - sma , this is not what is showcased in its book, but the result is just the same, the only thing that change is the scale, this is why some estimates have a weird scale that is not centered around 0, the output is technically the same but the scale isn't, however the scale of an oscillator isn't a big deal as long as the oscillator is centered around 0 and we don't plan to use it as input for overlay indicators.
If you are familiar with moving averages you'll know that the wma is more reactive than the sma, this is because more recent values have higher weights, and since subtracting a low-pass filter with another one conserve the smoothness while removing low-frequency components, we end up with a bandpass filter, yay!
Why "Center" Of Gravity ?
Elhers explain the idea behind this title with a pretty blurry analogy, so i'll try to give a visual explanation, we said earlier that the center of gravity was simply : wma - sma, ok lets look at their respective impulse responses,
Those are basically the weights of each filters, also called filter coefficients, lets denote the coefficients of the wma as a and the coefficients of the moving average as b . So whats the meaning behind center of gravity ? We basically want to "center" the weights of the wma, this can be done with a - b
The coefficients of the wma are therefore centered around 0, but actually there is more to that than a simple title explanation, basically a - b = c , where c are the coefficients of the center of gravity bandpass filter, therefore if we where to apply convolution to the price with c , we would get the center of gravity oscillator. Thats the thing with FIR filters, we can use convolution for describing a lot of FIR systems, and the difference between two impulse responses of two low-pass filters (here wma, sma) give us the coefficients of a bandpass filter.
The Center Of Linearity
At this point we could simply get the oscillator by using length/2 - i as coefficient, however in order to propose a more interesting variation i decided to go with a less efficient but more original approach, the center of linearity. Imagine two convolutions :
a = i*src and b = i*src
a only has a reversed index length-i , and is therefore describe a simple wma. Both convolutions give the following impulse responses :
Both are symmetrical to each others, and cross at a point, denoted center of linearity. The difference of each responses is :
Using it as coefficients would give us a bandpass filter who would look exactly like the Cg oscillator, this would be calculated as follows in our convolution :
i*src -i*src ) = i*(src -src )
Lets compare our estimate with the CG oscillator,
Conclusion
I this post i explained the calculation of the CG oscillator and proposed an efficient estimation of it by using an original approach. The CG oscillator isn't something complicated to use nor calculate, and is in fact closely related to the rolling covariance between the price and a linear function, so if you want to use the crosses between the center of gravity and 0 you can just use : correlation(close,bar_index,length) instead, thats basically the same.
The proposed indicator can also use other weightings instead of a linear one, each impulses responses would remain symmetrical.
Smart Envelope - Running Away From The TrendIntroduction
Envelopes indicators consist in displaying one upper and one lower extremity on the price chart. They are most of the time built by adding/subtracting a volatility estimator (rolling stdev, atr, range...etc) to a central tendency estimator (SMA, EMA, LSMA...etc) . Their interpretation is often subject to debate amongst technical analyst, some will use a support and resistance methodology, where price will start a downtrend once it cross the upper extremity, and a down trend once it cross the lower one. Others will prefer a breakout methodology, where price will reach higher highs once it cross the upper extremity, and lower lows when it cross the lower one. Because of price non stationarity its hard to select the best methodology, the support and resistance one will mostly work on ranging markets, while the breakout methodology mostly work on trending ones.
Therefore new methods where proposed, instead of using moving averages with a high lag, faster filters where used, such as the least squares moving average or zero lag exponential moving average, other band indicators where also created using adaptive filters, but improvements remain relatively low. The most difficult task would be to make extremities with the ability to return accurate support and resistances levels, and today i want to provide a new way to construct such extremities by using the recursive bands framework that allow extremely creative and efficient indicators.
The Main Idea
With classical bands indicators, the upper and lower extremity will still be correlated with the main trend, the problem behind such method is that we can't use a support and resistance methodology with trending markets, the fact that reversals exist tells us that our extremities will always be crossed by the main trend, here is an example :
Here the support is correlated with the main trend, in order for it to be accurate we must assume the trend will go on for ever, and will only detect higher lows, this is what we expect with the orange line, but we can see that a severe down trend totally destroy our plan.
In short we need to give some headroom to our extremities, and thus one extremity can't be correlated with the main trend.
The proposed Indicator
We want to minimize the correlation between the extremities, so if the upper extremity rise, the lower one must fall. This allow to give some headroom and allow the user to anticipate larger movements, this is how bands seeking to give support and resistances points should work.
The indicator has a length setting that control the wideness of the extremities, unlike other indicators low values such as 14 can still create really wide bands, take that into account.
length = 5. Lower length values allow for more motion from the extremities, but does not necessarily involve detecting shorter terms support and resistances levels. The factor setting is not that important, but it allow to return extremities with more motion when high, and really wide bands when below 1 and greater than 0.
Central Tendency Estimator
Something fun with the recursive band framework is that the bands are no longer based on the central tendency estimator but its the central tendency estimator who is based on the bands. The central tendency estimator can also provide support and resistances points with the price, like classical moving averages, altho its lack of motion is this time a downside.
Conclusion
Altho the extremities are more accurate than other band indicators, the problem remain the same, larger trend will always break the extremities and continue creating higher/lower highs/lows, at this point our stop loss would certainly be triggered. This is a huge downsides of contrarian strategy, we sure might anticipate reversals earlier, but we are exposed to larger price movements, therefore the risk is extreme.
But the proposed methodology might still prove useful to develop more robust support and resistances levels based on envelopes indicators.
Thanks for reading !
Visual RSI [LucF]Visual RSI offers a different way of looking at RSI by providing a composite representation of 9 different RSI-generated components. Instead of focusing on one line only, this approach blends multiple sources to provide the viewer with a larger context RSI-based picture.
For those who don’t want to read
• Green in bullish (>50) zone is the most bullish.
• Red in bullish zone doesn’t necessarily mean bearish—it just means bullish strength is weakening. It may be just a pause before a reprise or exhaustion signalling a reversal—impossible to tell.
• The same in inverse applies to the bearish zone (<50).
For those who want to understand
The nine components making up Visual RSI are:
• a current timeframe RSI
• a higher timeframe RSI
• the delta between these two RSI lines
• for each of these three basic components, two independent Bollinger band: one calculated for the bullish section of the scale (>50) and a separate one calculated for the lower bearish region.
Dual BBs
In my view, RSI’s position with regards to the centerline is much more important than its position in extreme areas. Why? Because the building block of RSI is the ratio of the averages of up/down moves during the RSI period. When the average of ups is greater, RSI is > 50. So while a rising signal starting from 20 let’s say, indicates that the rate of change is increasing, only when it crosses 50 can we say that sentiment balance has truly become bullish, and this information is more reliable than the signal being at a level corresponding to whatever estimate we make of what constitutes an extreme value. In my landscape, the general balance of a ratio provides more valuable information than the ratio’s exact value.
The idea behind the dual BBs is to provide independent tracking information for both halves of the indicator’s space, which I find more useful than the normal method of simply adding a multiple of the standard deviation on both sides of the mean. With dual BBs, the upper BB will never go lower than the indicator’s centerline, and the lower BB will never go higher. The upper BB focuses on upper-bound volatility when the signal is bearish, and the lower BB focuses on downside volatility when the signal is bearish.
The functions used to calculate the independent BBs are reusable on other signals if a centerline can be defined for them. A clamping percentage is implemented, so that when a BB line is hugging the centerline it clamps to it. This helps in providing earlier signals when they use the BB line states.
Providing context to RSI
What RSI measures indirectly is the balance in the rate of change—or the speed of price movement, but not its instant value, otherwise RSI would be even noisier. More precisely, RSI represents the relative strength of the up/down movement in the last n bars of RSI’s length, with 14 often used because that’s what Wilder proposed (Visual RSI’s defaults are 20 for the current timeframe and 40 for the higher timeframe). At every bar, a new value is added to the equation and an old value carrying equal weight is dropped, so a large dropped off value will have more impact on RSI’s value if the new bar’s move is small. This accounts for some of RSI’s speed in identifying exhaustion after important moves, but almost for some of its noise.
Visual RSI is the result of trying to drown RSI’s noise in the context of other informational streams, while simultaneously providing even faster information than RSI alone, by giving more visual weight to the delta between the current and higher timeframe RSI’s.
How to read Visual RSI
The default settings show all 9 basic components as green/red areas of intensities varying with their importance. The most intense colors are reserved for the delta RSI and the BBs have the lightest intensities. The individual lines of components are intentionally difficult to distinguish so that focus is first on the general picture, including the all-important six-state background, and then on the delta RSI.
One entry setup could be reversals in a larger trend context, so low pivots of the delta in a fully bullish context (a green background in the upper section of the indicator), and inversely, high pivots in a fully bearish context (a red background in the lower section of the indicator).
Please resist the common misconception, when interpreting RSI, that a reversal in the signal will necessarily lead to a reversal in price. Each trend has its rhythm. Only machine-generated price action can progress regularly. It’s normal for trends to take a breather for some time before they continue or reverse, as traders driving the trend experience emotional fatigue and gradual fear. RSI reversals merely signify that such a breather has occurred—nothing more. Only the larger context can provide information that can situate that pause and put more meaningful odds on it having more probability of continuing in one direction or the other. This is the reasoning behind the setup just described.
Features
• All components can be hidden, displayed as a simple line, a uniformly colored fill, or a green/red fill (the default).
• The background can be colored using 9 different methods, including 3 six-state methods using the rising/falling BB lines of the 3 basic components. These six states allow for bullish/bearish/neutral sentiment in both the upper and lower regions of the indicator. A bearish (dark red) background in the bullish (>50) section of the indicator represents decreasing bullishness. A bearish (slightly brighter red) in the bearish (<50) section of the indicator means incresingly bearish sentiment. The six-state backgrounds allow for neutral (no color) sentiment when no compelling signs can be found to conclude anything with meaningful odds. The default background uses the six-state method on the higher timeframe RSI’s BBs because I find it the most useful, as it represents the largest—and slowest—context sentiment among all the indicator’s components.
• A thin status bar in the top part of the indicator also allows selection of the same 9 methods to color it. The default is a triple-state system using the rising/falling characteristics of the current timeframe RSI’s BBs to provide a short-term counterbalance to the long-term background.
• Three different markers can be configured using approximately 70 permutations each, each filtered by 20 different filter permutations. When modification of the relevant parameters in the script’s Settings/Settings/Parameters section is added, possibilities are almost endless. If the generated signals are then fed into the PineCoders Engine and combined with the Engine’s own options, the permutations go up another order of magnitude, and changes to any setting can be instantly evaluated using the Engine’s backtesting results.
• Five simple filters can be combined. They are additive. They include volume-related conditions and a chandelier, which I find useful because both volume and volatility (the chandelier using highs/lows and ATR) are sensible complementary sources to RSI’s momentum information. The filter’s state can be shown as a thin line at the bottom of the indicator.
• Alerts can be configured using any of the marker/filter combinations mentioned. As usual, once your markers/filters are set up the way you want, create your alert from the chart/timeframe you want the alert to run on and be sure to use the “Once Per Bar Close” triggering condition. Use an alert message that will remind you of which combination of markers were used when creating the alert.
• A plot providing entry signals for the PineCoders Backtesting & Trading Engine is supplied. It will use whichever marker/filter configuration is active to generate signals.
• All higher timeframe information is non-repainting. Higher timeframe lines can be smoothed (the default). The selection of the higher timeframe can be made using 3 different methods:
1. By steps (if current timeframe <= 1 minute: 60 min, <= 60 min: 1D, <= 6H: 3D, <= 1D: 1W, <=1W: 1M, >1W: 12M)
2. By a user-defined multiple of the current timeframe
3. Using a fixed timeframe
Thanks to:
• Alex Orekhov aka @everget for the chandelier code.
• @RicardoSantos who through a small remark early on, unknowingly put me on the track of eliminating noise through visual crowding.
• The brilliant guys in the PineCoders Pro room for your knowledge, limitless creativity and constant companionship.
Forecasting - Drift MethodIntroduction
Nothing fancy in terms of code, take this post as an educational post where i provide information rather than an useful tool.
Time-Series Forecasting And The Drift Method
In time-series analysis one can use many many forecasting methods, some share similarities but they can all by classified in groups and sub-groups, the drift method is a forecasting method that unlike averages/naive methods does not have a constant (flat) forecast, instead the drift method can increase or decrease over time, this is why its a great method when it comes to forecasting linear trends.
Basically a drift forecast is like a linear extrapolation, first you take the first and last point of your data and draw a line between those points, extend this line into the future and you have a forecast, thats pretty much it.
One of the advantage of this method is first its simplicity, everyone could do it by hand without any mathematical calculations, then its ability to be non-conservative, conservative methods involve methods that fit the data very well such as linear/non-linear regression that best fit a curve to the data using the method of least-squares, those methods take into consideration all the data points, however the drift method only care about the first and last point.
Understanding Bias And Variance
In order to follow with the ability of methods to be non-conservative i want to introduce the concept of bias and variance, which are essentials in time-series analysis and machine learning.
First lets talk about training a model, when forecasting a time-series we can divide our data set in two, the first part being the training set and the second one the testing set. In the training set we fit a model to the training data, for example :
We use 200 data points, we split this set in two sets, the first one is for training which is in blue, and the other one for testing which is in green.
Basically the Bias is related to how well a forecasting model fit the training set, while the variance is related to how well the model fit the testing set. In our case we can see that the drift line does not fit the training set very well, it is then said to have high bias. If we check the testing set :
We can see that it does not fit the testing set very well, so the model is said to have high variance. It can be better to talk of bias and variance when using regression, but i think you get it. This is an important concept in machine learning, you'll often see the term "overfitting" which relate to a model fitting the training set really well, those models have a low to no bias, however when it comes to testing they don't fit well at all, they have high variance.
Conclusion On The Drift Method
The drift method is good at forecasting linear trends, and thats all...you see, when forecasting financial data you need models that are able to capture the complexity of the price structure as well as being robust to noise and outliers, the drift method isn't able to capture such complexity, its not a super smart method, same goes for linear regression. This is why more peoples are switching to more advanced models such a neural networks that can sometimes capture such complexity and return decent results.
So this method might not be the best but if you like lines then here you go.
Dollar Cost Average (Data Window Edition)Hi everyone
Hope you had a nice weekend and you're all excited for the week to come. At least I am (thanks to a few coffee but that still counts !!!)
This indicator is inspired from Dollar-Cost-Average-Cost-Basis
EDUCATIONAL POST
The educational post is coming a bit later this afternoon explaining how to use the indicator so I would advise to follow me so that you'll get updated in real-time :) (shameless self-advertising)
1 - What is Dollar-Cost Averaging (DCA)?
Dollar-Cost Averaging is a strategy that allows an investor to buy the same dollar amount of an investment on regular intervals. The purchases occur regardless of the asset's price.
I hope you're hungry because that one is a biggie and gave me a few headaches. Happy that it's getting out of my way finally and I can offer it
This indicator will analyse for the defined date range, how a dollar cost average (DCA) method would have performed vs investing all the hard earnt money at the beginning
2- What's on the menu today ?
Please check this screenshot to understand what you're supposed to see : CLICK ME I'M A SCREENSHOT (I'll repeat this URL one more time below as I noticed some don't read the information on my description and then will come pinging me saying "sir me no understand your indicator, itz buggy sir"
(yes I finally thought about a way to share screenshots on TradingView, took me 4 weeks, I'm slow to understand things apparently)
My indicator works with all asset classes and with the daily/weekly/monthly timeframes
As always, let's review quickly the different fields so that you'll understand how to use it (and I won't get spammed with questions in DM ^^)
- Use current resolution : if checked will use the resolution of the chart
- Timeframe used for DCA : different timeframe to be used if Use current resolution is unchecked
- Amount invested in your local currency : The amount in Fiat money that will be invested at each period selected above
- Starting Date
- Ending Date
- Select a candle level for the desired timeframe : If you want to use the open or close of the selected period above. Might make a diffence when the timeframe is weekly or monthly
3 - Specifications used
I got the idea from this website dcabtc.com and the result shown by this website and my indicator are very interesting in general and for your own trading
The formula used for the DCA calculation is that one : Investopedia Dollar Cost Average
4 - How to interpret the results
"But sir which results ??"...... those ones : CLICK ME I'M A SCREENSHOT :) (strike #2 with the screenshot)
It will draw all the plots and will give you some nice data to analyze in the Data Window section of TradingView
I'm not completely satisfied with the tool yet but the results are very closed to the dcabtc website mentioned above
If you're trading a very bullish asset class (who said crypto ?), it's very interesting to see what a DCA strategy could bring in term of performance. But DCA is not magic, there is a time component which is the day/week/month you'll start to invest (those who invested in crypto beginning of 2018 in altcoins know what I'm talking about and ..............will hate me for this joke)
5 - What's next ?
As said, the educational post is coming next but not only.
Will probably post a strategy tomorrow using this indicator so that you can compare what's performing best between your trading and a dollar cost average method
I'll publish as a protected source this time a more advanced version of that one including DCA forecasts
6 - Suggested alternative (but I'll you doing it)
If you don't want to have this panel in the bottom with the plots and analyze the results in the data window, you can always create an infopanel like shown here Risk-Reward-InfoPanel/ and display all the data there
Hope you'll like it, like me, love it, love me, tip me :)
____________________________________________________________
Feel free to hit the thumbs up as it shows me that I'm not doing this for nothing and will motivate to deliver more quality content in the future. (Meaning... a few likes only = no indicators = Dave enjoying the beach)
- I'm an offically approved PineEditor/LUA/MT4 approved mentor on codementor. You can request a coaching with me if you want and I'll teach you how to build kick-ass indicators and strategies
Jump on a 1 to 1 coaching with me
- You can also hire for a custom dev of your indicator/strategy/bot/chrome extension/python
sma-pivotsThis model is based on this script
I change it to sma model . the model run on pivots high or low that are base on SMA
I make two SMA one for high pivots and one for low pivots ( I put for now at same distance but you need to change it according to needs)
because asset can be in bull period or bear period when we have two separate distance of SMA we can find the correct combination if to buy more or less by changing either the sma pivot of the low end or the sma pivots of the high end using the length . also global we can use the lookbar of bar numbers
one sma to both pivots is bad as it not consider the market situation but separation to two one for sell and one for buy can give you a better flexible model for enter or exit
so its your job to find what length is best suited for exit and what for enter .
example when we have two different length how it work on 4 hour
TTM SQUEEZE with ALERT by NM// ######################################################################################
// This script was created because the original TTM Squeeze script
// did trigger when only one of the Bollinger Bands was
// in the Keltner channel. It now gives the option to use it as was
// or to force it to only give a signal when both BB are in the Keltner channels
//
// Furthermore an alert was added to fire when we are squeezing
// no matter which option your choose (original or strict)
//
// To create an alert, click on the alerts in the right column on your screen
// then click on the +button to add an alert.
// Select from the conditions "CTTV Squeeze" and "Once per bar close"
// Keep in mind that you set this alert for one instrument and one particular time frame
//
// If you would have any questions, contact me :
// TradingView : @Nico.Muselle
// ######################################################################################
How to start using this script ?
1. Add this script to your favorites
2. Click on the Indicator-button on the top bar of your chart
3. Click on Favorites and find CTTV TTM
Do also check out my other indicators :
Percentage change -
Power Moving Average Pro - (use Moving Averages of higher time frames on lower time frame charts) -
Power Moving Average - (use 1 moving average of a higher time frame on the current time frame) -
BitFinex Longs vs. Shorts -
Relative Strength Index Direction -
Reversal Candles -
EMADiff -
Improved Linear Regression Bull and Bear Power v02 -
Improved Linear Regression Bull and Bear Power v01 -
PS : Sorry about the messy chart - Bottom indicators show the TTM Squeeze, top one being the original posted here, bottom one being the more strict option.
Guerrilla AdvancedThis indicator was designed with people without Pro License in mind (Including many of my close friends).
Basically, you will get a combo of few different tools in one box, with ability to turn them on and off with a single check mark, also, you have total control over the input numbers that was used in calculations if you so want to, for example, sometimes when i see a massive bullish up trend, i reduce the short rally from 12 to 8 even 6 to get faster signal for selling the trend.
So, what will you get in this pack?
1- Ichimoko. Yes, you heard it right, although we have it in the default tools but hey, it will use one indicator slot and if you don't have a pro license, you will use that slot
2- Rally. This is an old yet very powerful system for getting buy or sell signals, basically, you get two lines and for making the life easier i draw a cloud between them. when the trend passes above the cloud and it was bellow it in past, right after the very first candle that gets above the cloud you can put the buy order, and vice versa, the moment a candle body enters the cloud, if you want an aggressive signal, you can sell, if not, you may want to wait to see if the candles drop bellow the cloud or not then decide.
3- Resistance Support Cloud. Most of us always heard about resistance and support "lines" but many of us don't know that, in each trend, the trend line itself is a resistance or support line, and when you are going in a bullish or bearish tunnel, the floor and roof of tunnels are again resistance and supports, using this part of the tool, just like rally, you get a cloud that shows you the resistance / support "zone"
4- William Fractals. To be honest, I got this part of the code from another source available around. Why? looking at those fractal indicators, you can easily eyeball the trend line or existence of a tunnel.
5- Different EMA lines. If you are one of those people that use EMA lines for their trading, have fun with them, there are few different standard ones and even a custom one that you can put your desired number for it.
Trench Cross ScalperThe original script was posted on ProRealCode by user Nicolas.
This indicator is an attempt of scalping strategy by crossing the mean high or low weigthed price over a short "n" period. This 2 lines represent the black "trench" on screenshots attached.
When signal line (blue one) crossing the buy trigger one (dotted green one) a buy signal should occur and vice-versa for a sell signal (when crossing the dotted red one). I add an option to draw the white signal line as the close price value of the high/low ones if they are respectively above or below the trench' buy or sell lines trigger.
The yellow green and red brick lines serve as stoploss.
The indicator can be use alone with no price chart as its values are derivated from it, of course if you dont mind about candlesticks informations.
I think enter/exit trades should occur very quickly, as it were designed for scalping trading purpose. I didn't have much time to test it for a long period, so here it is as a concept indicator, despite that, it does have sense.
Fibonacci WavesFirst of all, ignore all other lines in the example chart except the four FAT lines. The four fat lines are the ones that define the fibonacci price leves. The lines have different extension offset to the right. The shortest one is the end of the second wave ( or leg B ), the next one is the end of C, the one following that is the end of D and the final one is the end of the final leg E.
The two input parameters is the start of A and the end of A.
If the start of A is larger than then end of A, the calculated series is a downward trend, else it is an upward trend.
Calculation based on old EWT simple wave expansion by fibonacci sequence.
0.618, 1.618, 0.382
Based on this source:
www.ino.com
Best Regards,
/Hull, 2015.05.20.15:50 ( placera.se )
Every Hour 1st/Last FVG vTDL OVERVIEW - Shoutout to Micheal J. Huddleston aka ICT
This indicator identifies the first Fair Value Gap (FVG) that forms within each trading hour, providing traders with potential entry zones, reversal points, and unmitigated gap targets. Based on the concept that the first presented FVG of each hour represents a significant price delivery array where institutional order flow occurred.
The indicator detects FVGs on a lower timeframe (1-minute default) and displays them as boxes on your chart, tracking which gaps get filled and which remain open as potential draw-on-liquidity targets.
WHAT IS A FAIR VALUE GAP
A Fair Value Gap is a 3-candle price pattern representing an imbalance between buyers and sellers:
Bullish FVG: Forms when candle 3's low is above candle 1's high, leaving a gap
Bearish FVG: Forms when candle 3's high is below candle 1's low, leaving a gap
These gaps often act as magnets for price, which tends to return and "fill" the imbalance before continuing. They function as dynamic support and resistance zones.
KEY FEATURES
Detection Types
FVG: Standard fair value gap detection with volume imbalance expansion
Suspension FVG Blocks: Requires outside prints on both sides for more refined signals
Hourly Display Modes
First Only: Shows whichever FVG appears first each hour (bullish or bearish)
Show Both: Shows first bullish AND first bearish FVG independently each hour
Last FVG Tracking
Optionally display the last FVG of each hour
Useful for comparing how the hour developed
Can extend into the next hour for continued tracking
Breakaway Gap Detection
Gaps not traded into during their formation hour extend forward
Extended gaps display labels showing formation time and date
These unmitigated gaps become price targets and reversal zones
Gap Fill Modes
Touch Box: Marks filled when price enters the gap
Touch Midpoint: Marks filled when price reaches the 50 percent level
Fill Completely: Marks filled when price fills the entire gap with visual progress
HOW TO USE
Entry Points
The first FVG of each hour provides potential entry zones based on price reaction:
When price returns to an FVG and shows rejection, enter in the direction of rejection
The gap zone represents where institutional orders likely reside
Use the boundaries of the gap for stop loss placement
A clean rejection of the zone confirms it as valid support or resistance
Reversal Points
Unmitigated gaps that extend beyond their formation hour are high-probability reaction zones:
Extended boxes with labels indicate unfilled gaps
When price finally reaches these zones, expect a reaction
The longer a gap remains unfilled, the stronger the expected response
These zones act as magnets drawing price back to them
Price Targets
Use unmitigated gaps as draw-on-liquidity targets:
Look for extended boxes above or below current price
Price tends to seek out and fill imbalances
The midpoint line often serves as a minimum target
Multiple unfilled gaps in one direction suggest strong momentum potential
FRAMING DIRECTIONAL BIAS
The first presented FVG of each hour acts as a support or resistance zone. The direction of the FVG itself does not determine bias - it is how price reacts to that FVG that reveals the true market intention.
Reading Price Reaction
Price respects a bullish FVG as support and bounces higher = bullish bias confirmed
Price respects a bearish FVG as resistance and rejects lower = bearish bias confirmed
Price fails to hold a bullish FVG and breaks through = potential inversion, look for shorts
Price fails to hold a bearish FVG and breaks through = potential inversion, look for longs
Inversion Fair Value Gaps (IFVG)
When price trades through an FVG and closes beyond it, that gap can invert its role:
A bullish FVG that fails becomes resistance - use it as a short entry zone
A bearish FVG that fails becomes support - use it as a long entry zone
The inversion signals a shift in control from one side to the other
Watch for price to retest the inverted gap before continuing
Support and Resistance Framework
Think of each hourly first FVG as a key level:
Price above the FVG: the gap acts as potential support
Price below the FVG: the gap acts as potential resistance
Watch how price behaves when it returns to the gap zone
A clean rejection confirms the level; a break through signals inversion
SHORT-TERM SCALPING APPLICATION
These FVGs provide scalping opportunities each hour:
Identify the first FVG of the hour as your key level
Wait for price to trade away from it and return
Observe the reaction at the gap zone
Enter in the direction of the reaction with tight risk
Target the next FVG, midpoint, or nearby liquidity
Trade Management
Use the opposite side of the FVG box as your stop loss zone
The midpoint of the gap often provides first target or decision point
Scale out at nearby unmitigated gaps or key levels
If the gap inverts, flip your bias and look for entries in the new direction
MULTI-HOUR CONTEXT
If price consistently respects FVGs as support across hours = uptrend context
If price consistently respects FVGs as resistance across hours = downtrend context
If FVGs keep inverting = choppy or transitional market
Use higher timeframe direction to filter which reactions to trade
Compare first and last FVG of each hour to see how momentum developed
SESSION FILTERING
The indicator automatically excludes unreliable periods:
4 PM to 5 PM New York time (market close hours 16-17)
Weekend closed periods (Saturday and Sunday before 6 PM)
All timestamps use New York timezone for consistency with futures market hours.
SETTINGS GUIDE
Detection Settings
Detection Type: Choose between standard FVG or Suspension FVG Blocks
Lower Timeframe: 15 seconds, 1 minute, or 5 minutes for gap detection
Min FVG Size: Minimum gap size in ticks to filter noise
Display Settings
Hourly Display Mode: First Only shows one gap per hour; Show Both shows first bull and bear
Show First FVG: Toggle visibility of first FVG boxes
Show Last FVG: Toggle visibility of last FVG boxes
Show Midpoint Lines: Display the 50 percent level of each gap
Show Unfilled Breakaway Gaps: Extend boxes until price fills them
Show Only Today: Reduce clutter by hiding older hourly boxes
Gap Fill Detection Mode
Touch Box: Gap marked filled when price enters the zone
Touch Midpoint: Gap marked filled when price reaches 50 percent level
Fill Completely: Gap marked filled only when fully closed, shows visual fill progress
Recommended Settings by Style
Scalping: 1 minute LTF, 4 tick minimum, Show Both mode, Touch Box fill
Day Trading: 1 minute LTF, 4-8 tick minimum, First Only mode, Touch Midpoint fill
Swing Context: 5 minute LTF, Show Unfilled Gaps enabled, Fill Completely mode
COLOR CODING
Blue boxes: First bullish FVG of the hour
Red boxes: First bearish FVG of the hour
Green boxes: Last bullish FVG of the hour
Orange boxes: Last bearish FVG of the hour
Black midpoint lines: 50 percent level of each gap
Filled portion overlay: Shows visual progress in Fill Completely mode
All colors are fully customizable in the settings menu.
PRACTICAL TIPS
The first FVG of each hour is a hidden PD array - treat it as a significant level
Not every gap produces a tradeable reaction - wait for confirmation
Gaps that remain unfilled for multiple hours carry more weight
Use the Show Both mode to see both bullish and bearish opportunities each hour
When multiple gaps cluster in one zone, that area becomes even more significant
Inversions are powerful signals - a failed level often leads to acceleration
NOTES
Works on any instrument and timeframe
Best used on intraday charts (1 minute to 15 minute) viewing 1 minute LTF gaps
Combine with higher timeframe analysis for confluence
These are probability zones, not guarantees - always use proper risk management
The indicator handles HTF to LTF data fetching automatically
RSI Forecast Colorful [DiFlip]RSI Forecast Colorful
Introducing one of the most complete RSI indicators available — a highly customizable analytical tool that integrates advanced prediction capabilities. RSI Forecast Colorful is an evolution of the classic RSI, designed to anticipate potential future RSI movements using linear regression. Instead of simply reacting to historical data, this indicator provides a statistical projection of the RSI’s future behavior, offering a forward-looking view of market conditions.
⯁ Real-Time RSI Forecasting
For the first time, a public RSI indicator integrates linear regression (least squares method) to forecast the RSI’s future behavior. This innovative approach allows traders to anticipate market movements based on historical trends. By applying Linear Regression to the RSI, the indicator displays a projected trendline n periods ahead, helping traders make more informed buy or sell decisions.
⯁ Highly Customizable
The indicator is fully adaptable to any trading style. Dozens of parameters can be optimized to match your system. All 28 long and short entry conditions are selectable and configurable, allowing the construction of quantitative, statistical, and automated trading models. Full control over signals ensures precise alignment with your strategy.
⯁ Innovative and Science-Based
This is the first public RSI indicator to apply least-squares predictive modeling to RSI calculations. Technically, it incorporates machine-learning logic into a classic indicator. Using Linear Regression embeds strong statistical foundations into RSI forecasting, making this tool especially valuable for traders seeking quantitative and analytical advantages.
⯁ Scientific Foundation: Linear Regression
Linear regression is a fundamental statistical method that models the relationship between a dependent variable y and one or more independent variables x. The general formula for simple linear regression is:
y = β₀ + β₁x + ε
where:
y = predicted variable (e.g., future RSI value)
x = explanatory variable (e.g., bar index or time)
β₀ = intercept (value of y when x = 0)
β₁ = slope (rate of change of y relative to x)
ε = random error term
The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the RSI projection based on recent trends.
⯁ Least Squares Estimation
To minimize the error between predicted and observed values, we use the formulas:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Σ denotes summation; x̄ and ȳ are the means of x and y; and i ranges from 1 to n (number of observations). These equations produce the best linear unbiased estimator under the Gauss–Markov assumptions — constant variance (homoscedasticity) and a linear relationship between variables.
⯁ Linear Regression in Machine Learning
Linear regression is a foundational component of supervised learning. Its simplicity and precision in numerical prediction make it essential in AI, predictive algorithms, and time-series forecasting. Applying regression to RSI is akin to embedding artificial intelligence inside a classic indicator, adding a new analytical dimension.
⯁ Visual Interpretation
Imagine a time series of RSI values like this:
Time →
RSI →
The regression line smooths these historical values and projects itself n periods forward, creating a predictive trajectory. This projected RSI line can cross the actual RSI, generating sophisticated entry and exit signals. In summary, the RSI Forecast Colorful indicator provides both the current RSI and the forecasted RSI, allowing comparison between past and future trend behavior.
⯁ Summary of Scientific Concepts Used
Linear Regression: Models relationships between variables using a straight line.
Least Squares: Minimizes squared prediction errors for optimal fit.
Time-Series Forecasting: Predicts future values from historical patterns.
Supervised Learning: Predictive modeling based on known output values.
Statistical Smoothing: Reduces noise to highlight underlying trends.
⯁ Why This Indicator Is Revolutionary
Scientifically grounded: Built on statistical and mathematical theory.
First of its kind: The first public RSI with least-squares predictive modeling.
Intelligent: Incorporates machine-learning logic into RSI interpretation.
Forward-looking: Generates predictive, not just reactive, signals.
Customizable: Exceptionally flexible for any strategic framework.
⯁ Conclusion
By combining RSI and linear regression, the RSI Forecast Colorful allows traders to predict market momentum rather than simply follow it. It's not just another indicator: it's a scientific advancement in technical analysis technology. Offering 28 configurable entry conditions and advanced signals, this open-source indicator paves the way for innovative quantitative systems.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What Is RSI?
The RSI (Relative Strength Index) is a technical indicator developed by J. Welles Wilder. It measures the velocity and magnitude of recent price movements to identify overbought and oversold conditions. The RSI ranges from 0 to 100 and is commonly used to identify potential reversals and evaluate trend strength.
⯁ How RSI Works
RSI is calculated from average gains and losses over a set period (commonly 14 bars) and plotted on a 0–100 scale. It consists of three key zones:
Overbought: RSI above 70 may signal an overbought market.
Oversold: RSI below 30 may signal an oversold market.
Neutral Zone: RSI between 30 and 70, indicating no extreme condition.
These zones help identify potential price reversals and confirm trend strength.
⯁ Entry Conditions
All conditions below are fully customizable and allow detailed control over entry signal creation.
📈 BUY
🧲 Signal Validity: Signal remains valid for X bars.
🧲 Signal Logic: Configurable using AND or OR.
🧲 RSI > Upper
🧲 RSI < Upper
🧲 RSI > Lower
🧲 RSI < Lower
🧲 RSI > Middle
🧲 RSI < Middle
🧲 RSI > MA
🧲 RSI < MA
🧲 MA > Upper
🧲 MA < Upper
🧲 MA > Lower
🧲 MA < Lower
🧲 RSI (Crossover) Upper
🧲 RSI (Crossunder) Upper
🧲 RSI (Crossover) Lower
🧲 RSI (Crossunder) Lower
🧲 RSI (Crossover) Middle
🧲 RSI (Crossunder) Middle
🧲 RSI (Crossover) MA
🧲 RSI (Crossunder) MA
🧲 MA (Crossover)Upper
🧲 MA (Crossunder)Upper
🧲 MA (Crossover) Lower
🧲 MA (Crossunder) Lower
🧲 RSI Bullish Divergence
🧲 RSI Bearish Divergence
🔮 RSI (Crossover) Forecast MA
🔮 RSI (Crossunder) Forecast MA
📉 SELL
🧲 Signal Validity: Signal remains valid for X bars.
🧲 Signal Logic: Configurable using AND or OR.
🧲 RSI > Upper
🧲 RSI < Upper
🧲 RSI > Lower
🧲 RSI < Lower
🧲 RSI > Middle
🧲 RSI < Middle
🧲 RSI > MA
🧲 RSI < MA
🧲 MA > Upper
🧲 MA < Upper
🧲 MA > Lower
🧲 MA < Lower
🧲 RSI (Crossover) Upper
🧲 RSI (Crossunder) Upper
🧲 RSI (Crossover) Lower
🧲 RSI (Crossunder) Lower
🧲 RSI (Crossover) Middle
🧲 RSI (Crossunder) Middle
🧲 RSI (Crossover) MA
🧲 RSI (Crossunder) MA
🧲 MA (Crossover)Upper
🧲 MA (Crossunder)Upper
🧲 MA (Crossover) Lower
🧲 MA (Crossunder) Lower
🧲 RSI Bullish Divergence
🧲 RSI Bearish Divergence
🔮 RSI (Crossover) Forecast MA
🔮 RSI (Crossunder) Forecast MA
🤖 Automation
All BUY and SELL conditions can be automated using TradingView alerts. Every configurable condition can trigger alerts suitable for fully automated or semi-automated strategies.
⯁ Unique Features
Linear Regression Forecast
Signal Validity: Keep signals active for X bars
Signal Logic: AND/OR configuration
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Chart Labels: BUY/SELL markers above price
Automation & Alerts: BUY/SELL
Background Colors: bgcolor
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Linear Regression Forecast
Signal Validity: Keep signals active for X bars
Signal Logic: AND/OR configuration
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Chart Labels: BUY/SELL markers above price
Automation & Alerts: BUY/SELL
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Regime [CHE] Regime — Minimal HTF MACD histogram regime marker with a simple rising versus falling state.
Summary
Regime is a lightweight overlay that turns a higher-timeframe-style MACD histogram condition into a simple regime marker on your chart. It queries an imported core module to determine whether the histogram is rising and then paints a consistent marker color based on that boolean state. The output is intentionally minimal: no lines, no panels, no extra smoothing visuals, just a repeated marker that reflects the current regime. This makes it useful as a quick context filter for other signals rather than a standalone system.
Motivation: Why this design?
A common problem in discretionary and systematic workflows is clutter and over-interpretation. Many regime tools draw multiple plots, which can distract from price structure. This script reduces the regime idea to one stable question: is the MACD histogram rising under a given preset and smoothing length. The core logic is delegated to a shared module to keep the indicator thin and consistent across scripts that rely on the same definition.
What’s different vs. standard approaches?
Reference baseline: A standard MACD histogram plotted in a separate pane with manual interpretation.
Architecture differences:
Uses a shared library call for the regime decision, rather than re-implementing MACD logic locally.
Uses a single boolean output to drive marker color, rather than plotting histogram bars.
Uses fixed marker placement at the bottom of the chart for consistent visibility.
Practical effect:
You get a persistent “context layer” on price without dedicating a separate pane or reading histogram amplitude. The chart shows state, not magnitude.
How it works (technical)
1. The script imports `chervolino/CoreMACDHTF/2` and calls `core.is_hist_rising()` on each bar.
2. Inputs provide the source series, a preset string for MACD-style parameters, and a smoothing length used by the library function.
3. The library returns a boolean `rising` that represents whether the histogram is rising according to the library’s internal definition.
4. The script maps that boolean to a color: yellow when rising, blue otherwise.
5. A circle marker is plotted on every bar at the bottom of the chart, colored by the current regime state. Only the most recent five hundred bars are displayed to limit visual load.
Notes:
The exact internal calculation details of `core.is_hist_rising()` are not shown in this code. Any higher timeframe mechanics, security usage, or confirmation behavior are determined by the imported library. (Unknown)
Parameter Guide
Source — Selects the price series used by the library call — Default: close — Tips: Use close for consistency; alternate sources may shift regime changes.
Preset — Chooses parameter preset for the library’s MACD-style configuration — Default: 3,10,16 — Trade-offs: Faster presets tend to flip more often; slower presets tend to react later.
Smoothing Length — Controls smoothing used inside the library regime decision — Default: 21 — Bounds: minimum one — Trade-offs: Higher values typically reduce noise but can delay transitions. (Library behavior: Unknown)
Reading & Interpretation
Yellow markers indicate the library considers the histogram to be rising at that bar.
Blue markers indicate the library considers it not rising, which may include falling or flat conditions depending on the library definition. (Unknown)
Because markers repeat on every bar, focus on transitions from one color to the other as regime changes.
This tool is best read as context: it does not express strength, only direction of change as defined by the library.
Practical Workflows & Combinations
Trend following:
Use yellow as a condition to allow long-side entries and blue as a condition to allow short-side entries, then trigger entries with your primary setup such as structure breaks or pullback patterns. (Optional)
Exits and stops:
Consider tightening management after a color transition against your position direction, but do not treat a single flip as an exit signal without price-based confirmation. (Optional)
Multi-asset and multi-timeframe:
Keep `Source` consistent across assets.
Use the slower preset when instruments are noisy, and the faster preset when you need earlier context shifts. The best transferability depends on the imported library’s behavior. (Unknown)
Behavior, Constraints & Performance
Repaint and confirmation:
This script itself uses no forward-looking indexing and no explicit closed-bar gating. It evaluates on every bar update.
Any repaint or confirmation behavior may come from the imported library. If the library uses higher timeframe data, intrabar updates can change the state until the higher timeframe bar closes. (Unknown)
security and HTF:
Not visible here. The library name suggests HTF behavior, but the implementation is not shown. Treat this as potentially higher-timeframe-driven unless you confirm the library source. (Unknown)
Resources:
No loops, no arrays, no heavy objects. The plotting is one marker series with a five hundred bar display window.
Known limits:
This indicator does not convey histogram magnitude, divergence, or volatility context.
A binary regime can flip in choppy phases depending on preset and smoothing.
Sensible Defaults & Quick Tuning
Starting point:
Source: close
Preset: 3,10,16
Smoothing Length: 21
Tuning recipes:
Too many flips: choose the slower preset and increase smoothing length.
Too sluggish: choose the faster preset and reduce smoothing length.
Regime changes feel misaligned with your entries: keep the preset, switch the source back to close, and tune smoothing length in small steps.
What this indicator is—and isn’t
This is a minimal regime visualization and a context filter. It is not a complete trading system, not a risk model, and not a prediction engine. Use it together with price structure, execution rules, and position management. The regime definition depends on the imported library, so validate it against your market and timeframe before relying on it.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
MACD HTF Hardcoded
Global Liquidity Score
Global Liquidity Score – Simple Risk-On / Risk-Off Gauge
This indicator measures overall market liquidity conditions using a single, normalized score.
It takes several macro and crypto variables, standardizes each one (z-score), and combines them into one clear Liquidity Score Line.
You only follow one line (your pink/white line).
The background color shows the current liquidity regime.
⸻
What the indicator measures
The algorithm looks at four major liquidity sources:
1. USD Liquidity (tightening or easing)
• DXY (strong dollar = tighter global liquidity)
• US10Y yield (higher yields = liquidity drain)
2. Risk Sentiment (risk-on vs risk-off)
• VIX index (volatility)
• S&P 500 index (SPX)
3. Credit Market Strength
• High-yield ETFs: HYG, JNK
• Investment-grade corporate credit: LQD
Stronger credit = easier liquidity.
Weaker credit = tightening risk.
4. Internal Crypto Liquidity
• USDT dominance (higher = risk-off in crypto)
• Bitcoin price
• TOTAL2 (crypto market cap excluding BTC)
These are all converted into z-scores and combined into one metric:
Total Liquidity Score =
USD Block + Risk Block − Credit Block − 0.5 × Crypto Block
⸻
How to read the colors
The indicator uses background colors to show the liquidity regime:
Color Meaning
Dark Red Severe liquidity tightening / strong risk-off
Red Mild-to-moderate tightening
Green Liquidity easing / soft risk-on
Dark Green Strong easing, high liquidity / risk-on
Your pink/white line = the final liquidity score.
You only need to follow that single line.
⸻
How to interpret the score
📉 Positive score → Liquidity Tightening (Risk-Off)
• USD stronger
• Yields rising
• Volatility rising
• Credit markets weakening
• Crypto rotating to stablecoins
📈 Negative score → Liquidity Easing (Risk-On)
• USD weakening
• Yields falling
• Stocks rising
• Volatility low
• Credit markets strong
• Crypto beta assets outperform
⸻
What this indicator is NOT
This is not a price predictor.
It does not follow BTC directly.
It tells you liquidity conditions, not immediate price direction.
It answers the macro question:
“Is liquidity flowing INTO the market or OUT of the market?”
If liquidity is tightening (red), crypto rallies are harder to sustain.
If liquidity is easing (green), crypto rallies have more fuel.
Stochastic Hash Strat [Hash Capital Research]# Stochastic Hash Strategy by Hash Capital Research
## 🎯 What Is This Strategy?
The **Stochastic Slow Strategy** is a momentum-based trading system that identifies oversold and overbought market conditions to capture mean-reversion opportunities. Think of it as a "buy low, sell high" approach with smart mathematical filters that remove emotion from your trading decisions.
Unlike fast-moving indicators that generate excessive noise, this strategy uses **smoothed stochastic oscillators** to identify only the highest-probability setups when momentum truly shifts.
---
## 💡 Why This Strategy Works
Most traders fail because they:
- **Chase prices** after big moves (buying high, selling low)
- **Overtrade** in choppy, directionless markets
- **Exit too early** or hold losses too long
This strategy solves all three problems:
1. **Entry Discipline**: Only trades when the stochastic oscillator crosses in extreme zones (oversold for longs, overbought for shorts)
2. **Cooldown Filter**: Prevents revenge trading by forcing a waiting period after each trade
3. **Fixed Risk/Reward**: Pre-defined stop-loss and take-profit levels ensure consistent risk management
**The Math Behind It**: The stochastic oscillator measures where the current price sits relative to its recent high-low range. When it's below 25, the market is oversold (time to buy). When above 70, it's overbought (time to sell). The crossover with its moving average confirms momentum is shifting.
---
## 📊 Best Markets & Timeframes
### ⭐ OPTIMAL PERFORMANCE:
**Crude Oil (WTI) - 12H Timeframe**
- **Why it works**: Oil markets have predictable volatility patterns and respect technical levels
**AAVE/USD - 4H to 12H Timeframe**
- **Why it works**: DeFi tokens exhibit strong momentum cycles with clear extremes
### ✅ Also Works Well On:
- **BTC/USD** (12H, Daily) - Lower frequency but high win rate
- **ETH/USD** (8H, 12H) - Balanced volatility and liquidity
- **Gold (XAU/USD)** (Daily) - Classic mean-reversion asset
- **EUR/USD** (4H, 8H) - Lower volatility, requires patience
### ❌ Avoid Using On:
- Timeframes below 4H (too much noise)
- Low-liquidity altcoins (wide spreads kill performance)
- Strongly trending markets without pullbacks (Bitcoin in 2021)
- News-driven instruments during major events
---
## 🎛️ Understanding The Settings
### Core Stochastic Parameters
**Stochastic Length (Default: 16)**
- Controls the lookback period for price comparison
- Lower = faster reactions, more signals (10-14 for volatile markets)
- Higher = smoother signals, fewer trades (16-21 for stable markets)
- **Pro tip**: Use 10 for crypto 4H, 16 for commodities 12H
**Overbought Level (Default: 70)**
- Threshold for short entries
- Lower values (65-70) = more trades, earlier entries
- Higher values (75-80) = fewer but higher-conviction trades
- **Sweet spot**: 70 works for most assets
**Oversold Level (Default: 25)**
- Threshold for long entries
- Higher values (25-30) = more trades, earlier entries
- Lower values (15-20) = fewer but stronger bounce setups
- **Sweet spot**: 20-25 depending on market conditions
**Smooth K & Smooth D (Default: 7 & 3)**
- Additional smoothing to filter out whipsaws
- K=7 makes the indicator slower and more reliable
- D=3 is the signal line that confirms the trend
- **Don't change these unless you know what you're doing**
---
### Risk Management
**Stop Loss % (Default: 2.2%)**
- Automatically exits losing trades
- Should be 1.5x to 2x your average market volatility
- Too tight = death by a thousand cuts
- Too wide = uncontrolled losses
- **Calibration**: Check ATR indicator and set SL slightly above it
**Take Profit % (Default: 7%)**
- Automatically exits winning trades
- Should be 2.5x to 3x your stop loss (reward-to-risk ratio)
- This default gives 7% / 2.2% = 3.18:1 R:R
- **The golden rule**: Never have R:R below 2:1
---
### Trade Filters
**Bar Cooldown Filter (Default: ON, 3 bars)**
- **What it does**: Forces you to wait X bars after closing a trade before entering a new one
- **Why it matters**: Prevents emotional revenge trading and overtrading in choppy markets
- **Settings guide**:
- 3 bars = Standard (good for most cases)
- 5-7 bars = Conservative (oil, slow-moving assets)
- 1-2 bars = Aggressive (only for experienced traders)
**Exit on Opposite Extreme (Default: ON)**
- Closes your long when stochastic hits overbought (and vice versa)
- Acts as an early profit-taking mechanism
- **Leave this ON** unless you're testing other exit strategies
**Divergence Filter (Default: OFF)**
- Looks for price/momentum divergences for additional confirmation
- **When to enable**: Trending markets where you want fewer but higher-quality trades
- **Keep OFF for**: Mean-reverting markets (oil, forex, most of the time)
---
## 🚀 Quick Start Guide
### Step 1: Set Up in TradingView
1. Open TradingView and navigate to your chart
2. Click "Pine Editor" at the bottom
3. Copy and paste the strategy code
4. Click "Add to Chart"
5. The strategy will appear in a separate pane below your price chart
### Step 2: Choose Your Market
**If you're trading Crude Oil:**
- Timeframe: 12H
- Keep all default settings
- Watch for signals during London/NY overlap (8am-11am EST)
**If you're trading AAVE or crypto:**
- Timeframe: 4H or 12H
- Consider these adjustments:
- Stochastic Length: 10-14 (faster)
- Oversold: 20 (more aggressive)
- Take Profit: 8-10% (higher targets)
### Step 3: Wait for Your First Signal
**LONG Entry** (Green circle appears):
- Stochastic crosses up below oversold level (25)
- Price likely near recent lows
- System places limit order at take profit and stop loss
**SHORT Entry** (Red circle appears):
- Stochastic crosses down above overbought level (70)
- Price likely near recent highs
- System places limit order at take profit and stop loss
**EXIT** (Orange circle):
- Position closes either at stop, target, or opposite extreme
- Cooldown period begins
### Step 4: Let It Run
The biggest mistake? **Interfering with the system.**
- Don't close trades early because you're scared
- Don't skip signals because you "have a feeling"
- Don't increase position size after a big win
- Don't revenge trade after a loss
**Follow the system or don't use it at all.**
---
### Important Risks:
1. **Drawdown Pain**: You WILL experience losing streaks of 5-7 trades. This is mathematically normal.
2. **Whipsaw Markets**: Choppy, range-bound conditions can trigger multiple small losses.
3. **Gap Risk**: Overnight gaps can cause your actual fill to be worse than the stop loss.
4. **Slippage**: Real execution prices differ from backtested prices (factor in 0.1-0.2% slippage).
---
## 🔧 Optimization Guide
### When to Adjust Settings:
**Market Volatility Increased?**
- Widen stop loss by 0.5-1%
- Increase take profit proportionally
- Consider increasing cooldown to 5-7 bars
**Getting Too Few Signals?**
- Decrease stochastic length to 10-12
- Increase oversold to 30, decrease overbought to 65
- Reduce cooldown to 2 bars
**Getting Too Many Losses?**
- Increase stochastic length to 18-21 (slower, smoother)
- Enable divergence filter
- Increase cooldown to 5+ bars
- Verify you're on the right timeframe
### A/B Testing Method:
1. **Run default settings for 50 trades** on your chosen market
2. Document: Win rate, profit factor, max drawdown, emotional tolerance
3. **Change ONE variable** (e.g., oversold from 25 to 20)
4. Run another 50 trades
5. Compare results
6. Keep the better version
**Never change multiple settings at once** or you won't know what worked.
---
## 📚 Educational Resources
### Key Concepts to Learn:
**Stochastic Oscillator**
- Developed by George Lane in the 1950s
- Measures momentum by comparing closing price to price range
- Formula: %K = (Close - Low) / (High - Low) × 100
- Similar to RSI but more sensitive to price movements
**Mean Reversion vs. Trend Following**
- This is a **mean reversion** strategy (price returns to average)
- Works best in ranging markets with defined support/resistance
- Fails in strong trending markets (2017 Bitcoin, 2020 Tech stocks)
- Complement with trend filters for better results
**Risk:Reward Ratio**
- The cornerstone of profitable trading
- Winning 40% of trades with 3:1 R:R = profitable
- Winning 60% of trades with 1:1 R:R = breakeven (after fees)
- **This strategy aims for 45% win rate with 2.5-3:1 R:R**
### Recommended Reading:
- *"Trading Systems and Methods"* by Perry Kaufman (Chapter on Oscillators)
- *"Mean Reversion Trading Systems"* by Howard Bandy
- *"The New Trading for a Living"* by Dr. Alexander Elder
---
## 🛠️ Troubleshooting
### "I'm not seeing any signals!"
**Check:**
- Is your timeframe 4H or higher?
- Is the stochastic actually reaching extreme levels (check if your asset is stuck in middle range)?
- Is cooldown still active from a previous trade?
- Are you on a low-liquidity pair?
**Solution**: Switch to a more volatile asset or lower the overbought/oversold thresholds.
---
### "The strategy keeps losing money!"
**Check:**
- What's your win rate? (Below 35% is concerning)
- What's your profit factor? (Below 0.8 means serious issues)
- Are you trading during major news events?
- Is the market in a strong trend?
**Solution**:
1. Verify you're using recommended markets/timeframes
2. Increase cooldown period to avoid choppy markets
3. Reduce position size to 5% while you diagnose
4. Consider switching to daily timeframe for less noise
---
### "My stop losses keep getting hit!"
**Check:**
- Is your stop loss tighter than the average ATR?
- Are you trading during high-volatility sessions?
- Is slippage eating into your buffer?
**Solution**:
1. Calculate the 14-period ATR
2. Set stop loss to 1.5x the ATR value
3. Avoid trading right after market open or major news
4. Factor in 0.2% slippage for crypto, 0.1% for oil
---
## 💪 Pro Tips from the Trenches
### Psychological Discipline
**The Three Deadly Sins:**
1. **Skipping signals** - "This one doesn't feel right"
2. **Early exits** - "I'll just take profit here to be safe"
3. **Revenge trading** - "I need to make back that loss NOW"
**The Solution:** Treat your strategy like a business system. Would McDonald's skip making fries because the cashier "doesn't feel like it today"? No. Systems work because of consistency.
---
### Position Management
**Scaling In/Out** (Advanced)
- Enter 50% position at signal
- Add 50% if stochastic reaches 10 (oversold) or 90 (overbought)
- Exit 50% at 1.5x take profit, let the rest run
**This is NOT for beginners.** Master the basic system first.
---
### Market Awareness
**Oil Traders:**
- OPEC meetings = volatility spikes (avoid or widen stops)
- US inventory reports (Wed 10:30am EST) = avoid trading 2 hours before/after
- Summer driving season = different patterns than winter
**Crypto Traders:**
- Monday-Tuesday = typically lower volatility (fewer signals)
- Thursday-Sunday = higher volatility (more signals)
- Avoid trading during exchange maintenance windows
---
## ⚖️ Legal Disclaimer
This trading strategy is provided for **educational purposes only**.
- Past performance does not guarantee future results
- Trading involves substantial risk of loss
- Only trade with capital you can afford to lose
- No one associated with this strategy is a licensed financial advisor
- You are solely responsible for your trading decisions
**By using this strategy, you acknowledge that you understand and accept these risks.**
---
## 🙏 Acknowledgments
Strategy development inspired by:
- George Lane's original Stochastic Oscillator work
- Modern quantitative trading research
- Community feedback from hundreds of backtests
Built with ❤️ for retail traders who want systematic, disciplined approaches to the markets.
---
**Good luck, stay disciplined, and trade the system, not your emotions.**
RSI Ensemble Confidence [CHE]RSI Ensemble Confidence — Measures RSI agreement across multiple lengths and price sources
Summary
This indicator does not just show you one RSI — it shows you how strongly dozens of different RSI variants agree with each other right now.
The Confidence line (0–100) is the core idea:
- High Confidence → almost all RSIs see the same thing → clean, reliable situation
- Low Confidence → the RSIs contradict each other → the market is messy, RSI signals are questionable
How it works (exactly as you wanted it described)
1. Multiple RSIs instead of just one
The indicator builds a true ensemble:
- 4 lengths (default 8, 14, 21, 34)
- 6 price sources (Close, Open, High, Low, HL2, OHLC4 – individually switchable)
→ When everything is enabled, up to 24 different RSIs are calculated on every single bar.
These 24 opinions form a real “vote” about the current market state.
2. Mean and dispersion
From all active RSIs it calculates:
- rsiMean → the average opinion of the entire ensemble (orange line)
- rsiStd → how far the individual RSIs deviate from each other
Small rsiStd = they all lie close together → strong agreement
Large rsiStd = they are all over the place → contradiction
3. Confidence (0–100)
The standard deviation is compared to the user parameter “Max expected StdDev” (default 20):
- rsiStd = 0 → Confidence ≈ 100
- rsiStd = maxStd → Confidence ≈ 0
- Everything in between is scaled linearly
If only one RSI is active, Confidence is automatically set to ~80 for practicality.
What you see on the chart
1. Classic reference RSI – blue line (Close, length 14) → your familiar benchmark
2. Ensemble mean – orange line → the true consensus RSI
±1 StdDev band (optional) → shows dispersion directly:
- narrow band = clean, consistent setup
- wide band = the RSIs disagree → caution
3. Confidence line (aqua, 0–100) → your quality meter for any RSI signal
4. StdDev histogram (optional, fuchsia columns) → raw dispersion if you prefer the unscaled value
5. Background coloring
- Greenish ≥ 80 → high agreement
- Orange 60–80 → medium
- Reddish < 40 → strong disagreement
- Transparent below that
6. Two built-in alerts
- High Confidence (crossover 80)
- Low Confidence (crossunder 40)
Why this indicator is practically useful
1. Perfect filter for all RSI strategies
Only trade overbought/oversold, divergences, or failures when Confidence ≥ 70. Skip or reduce size when Confidence < 40.
2. Protection against overinterpretation
You immediately see whether a “beautiful” RSI hook is confirmed by the other 23 variants — or whether it’s just one outlier fooling you.
3. Excellent regime detector
Long periods of high Confidence = clean trends or clear overbought/oversold phases
Constantly low Confidence = choppy, noisy market → RSI becomes almost useless
4. Turns gut feeling into numbers
We all sometimes think “this setup somehow doesn’t feel right”. Now you have the exact number that says why.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
