LineGetPriceOnLogScaleLibrary "LineGetPriceOnLogScale"
This library provides a way to calculate the y-coordinate of a line on a specified bar when the chart scale is Log.
The built-in `line.get_price()` function only works with linear scale and gives incorrect results when the chart is in Log scale.
The library only works with `bar_index` values and `xloc.bar_index`-based lines, `time`-based lines will cause errors to appear.
coordGetPriceLog(x1, y1, x2, y2, xi) Calculates the y-coordinate on the specified bar on the logarithmic scale.
Only coordinates based on bar index are applicable, bar time will throw an error.
Parameters:
x1 : First X coordinate of a line, index of the bar where the line starts.
y1 : First Y coordinate of a line, price on the price scale.
x2 : Second X coordinate of a line, index of the bar where the line ends.
y2 : Second Y coordinate of a line, price on the price scale.
xi : Index of the bar for which the price should be calculated.
Returns: Price of the line on the bar specified in `xi`, on the logarithmic scale.
lineGetPriceLog(_line, xi) Calculates the y-coordinate on the specified bar for the logarithmic scale. Takes a line.
Only lines drawn based on `xloc.bar_index` are applicable, `xloc.bar_time` will throw and error.
Parameters:
_line : The line for which the price is calculated.
xi : Index of the bar for which the bar should calculate the price.
Returns: Price of the line on the bar specified in `xi`, on the logarithmic scale.
在脚本中搜索"bar"
[CP]Pivot Boss Candlestick Scanner - No Repainting This indicator is based on the high probability candlestick patterns described in the ’Secrets of a Pivot Boss’ book.
The indicator does not suffer from repainting.
I have kept this indicator open source, so that you can take this indicator and design a complete trading system around it.
Although the patterns have some statistical edge in the markets, blindly using them as Buy/Sell Indicators will certainly result in a heavy loss.
I like some of these setups more than others, and I have listed them in the order of my likeness.
The first one I like the most, the last one, I like the least.
The patterns are universal and work well in both intraday, daily and even larger timeframes.
Signals in the example charts are manually marked by,
Hammer - profitable short signal
Rocket - profitable long signal
X - unprofitable long or short signal
GENERAL USER INPUTS:
These settings exist as the indicator uses ‘Labels’ to mark the patterns and Pine Script limits a maximum of 500 labels on a chart.
If you want to go back in the past and check how the indicator was doing, set the Start and End dates both and check the ’Use the date range above to mark the Candlestick Setups?’ option.
EXTREME REVERSAL SETUP:
This is by far my favorite setup in the lot. Classic Mean Reversion setup.
The logic, as explained in the book, goes like this,
1. The first bar of the pattern is about two times larger than the average size of the candles in the lookback period.
2. The body of the first bar of the pattern should encompass more than 50 percent of the bar’s total range, but usually not more than 85 percent.
3. The second bar of the pattern opposes the first.
The setup works extremely well in high beta stocks like Vedanta VEDL.
Feel free to play with the settings in order to better align this pattern with your favorite stock.
Check out the examples below,
No indicator is perfect, failed patterns are marked with an X.
OUTSIDE REVERSAL SETUP:
My second favorite setup, it is quite good at catching intraday trends.
Here’s the logic,
1. The engulfing bar of a bullish outside reversal setup has a low that is below the prior bar’s low and a close that is above the prior bar’s high. Reverse the conditions for bearish outside reversal.
2. The engulfing bar is usually 5 to 25 percent larger than the size of the average bar in the lookback period.
Settings for this pattern simply reflect these conditions. Feel free to modify them as you wish.
The pattern is pretty powerful and will sometimes help you catch literally all the highs and lows of the market, as shown in the examples of Vedanta VEDL and RELIANCE stocks below.
As usual, this pattern is not PERFECT either.
DOJI REVERSAL SETUP:
Doji candles signify market indecision and this pattern tries to profit off these market conditions.
Logic:
1. The open and close price of the doji should fall within 10 percent of each other, as measured by the total range of the candlestick.
2. For a bullish doji, the high of the doji candlestick should be below the ten-period simple moving average. Vice-versa for bearish.
3. For a bullish doji setup, one of the two bars following the doji must close above the high of the doji. Vice-versa for bearish.
Feel free to modify the settings and optimize according to the stock you are trading.
Don't optimize too much :)
This pattern works brilliantly well on larger intraday timeframes, like 15m/30m/60m.
This pattern also has a higher propensity to give false indications than the two described above.
Doji reversal typically helps to catch larger trend reversals. Check out the examples below from RELIANCE and NIFTY charts,
Note that the RELIANCE chart below is the same as shown for the Outside Reversal Setup above, notice the confluence of Outside
Reversal and Doji Reversal on the 31st August.
Confluence of patterns usually increases the probability of success.
RELIANCE 15m Chart - Pattern can catch nice trends on higher timeframes
NIFTY 15m Chart
WICK REVERSAL SETUP:
This pattern tries to capture candlesticks with large wick sizes, as they often indicate trend reversal when coupled with significant support and resistance levels.
Logic:
1. The body is used to determine the size of the reversal wick. A wick that is between 2.5 to 3.5 times larger than the size of the body is ideal.
2. For a bullish reversal wick to exist, the close of the bar should fall within the top 35 percent of the overall range of the candle.
3. For a bearish reversal wick to exist, the close of the bar should fall within the bottom 35 percent of the overall range of the candle.
This pattern must always be coupled with important support resistance levels, else there will be a lot of false signals.
The chart below is the same NIFTY chart as above with the Wick Reversal candles marked as well.
You can see that there are a lot of false signals, but the price also indicates ’pausing’ at important levels by printing a wick reversal setup.
You can use this information to your advantage when riding a trend.
FINAL WORDS:
Settings for various patterns simply reflect the logic described.
You will probably need to tweak and optimize the pattern settings for the stock that you are trading.
Higher Beta/Higher Volatility stocks are a great choice for these patterns.
Using these patterns at critical support and resistance levels will result in dramatically high accuracy.
Be creative and try to develop a proper system around this indicator, with rules for position sizing, stop loss etc.
You do not have to trade all the patterns. Even trading just one pattern with a proper system is good enough.
DO NOT USE THIS INDICATOR AS A BUY/SELL SYSTEM, YOU WILL LOSE MONEY.
Feel free to drop any feedback in the comments section below, or if you have any unique candlestick patterns that you would like me to code.
Cyclic Smoothed RSI with Motive-Corrective Wave Indicator
This indicator uses the cyclic smoothed Relative Strength Index (cRSI) instead of the traditional Relative Strength Index (RSI). See below for more info on the benefits to the cRSI.
My key contributions
1) A Weighted Moving Average (WMA) to track the general trend of the cRSI signal. This is very helpful in determining when the equity switches from bullish to bearish, which can be used to determine buy/sell points. This is then is used to color the region between the upper and lower cRSI bands (green above, red below).
2) An attempt to detect the motive (impulse) and corrective and waves. Corrective waves are indicated A, B, C, D, E, F, G. F and G waves are not technically Elliot Waves, but the way I detect waves it is really hard to always get it right. Once and a while you could actually see G and F a second time. Motive waves are identified as s (strong) and w (weak). Strong waves have a peak above the cRSI upper band and weak waves have a peak below the upper band.
3) My own divergence indicator for bull, hidden bull, bear, and hidden bear. I was not able to replicate the TradingView style of drawing a line from peak to peak, but for this indicator I think in the end it makes the chart cleaner.
There is a latency issue with an indicator that is based on moving averages. That means they tend to trigger right after key events. Perfect timing is not possible strictly with these indicators, but they do work very well "on average." However, my implementation has minimal latency as peaks (tops/bottoms) only require one bar to detect.
As a bit of an Easter Egg, this code can be tweaked and run as a strategy to get buy/sell signals. I use this code for both my indicator and for trading strategy. Just copy and past it into a new strategy script and just change it from study to a strategy, something like this:
strategy("cRSI + Waves Strategy with VWMA overlay", overlay=overlay)
The buy/sell code is at the end and just needs to be uncommented. I make no promises or guarantees about how good it is as a strategy, but it gives you some code and ideas to work with.
Tuning
1) Volume Weighted Moving Average (VWMA): This is a “hidden strategy” feature implemented that will display the high-low bands of the VWMA on the price chart if run the code using “overlay = true”.
- If the equity does not have volume, then the VWMA will not show up. Uncheck this box and it will use the regular WMA (no volume).
- defines how far back the WMA averages price.
2) cRSI (Black line in the indicator)
- Increase to length that amount of time a band (upper/lower) stays high/low after a peak. Reduce the value to shorten the time. Just increment it up/down to see the effect.
- defines how far back the SMA averages the cRSI. This affects the purple line in the indicator.
- defines how many bars back the peak detector looks to determine if a peak has occurred. For example, a top is detected like this: current-bar down relative to the 1-bar-back, 1-bar-back up relative to 2-bars-back (look back = 1), c) 2-bars-back up relative to 3-bars-back (lookback = 2), and d) 3-bars-back up relative to 4-bars-back (lookback = 3). I hope that makes sense. There are only 2 options for this setting: 2 or 3 bars. 2 bars will be able to detect small peaks but create more “false” peaks that may not be meaningful. 3 bars will be more robust but can miss short duration peaks.
3) Waves
- The check boxes are self explanatory for which labels they turn on and off on the plot.
4) Divergence Indicators
- The check boxes are self explanatory for which labels they turn on and off on the plot.
Hints
- The most common parameter to change is the . Different stocks will have different levels of strength in their peaks. A setting of 2 may generate too many corrective waves.
- Different times scales will give you different wave counts. This is to be expected. A counter impulse wave inside a corrective wave may actually go above the cRSI WMA on a smaller time frame. You may need to increase it one or two levels to see large waves.
- Just because you see divergence (bear or hidden bear) does not mean a price is going to go down. Often price continues to rise through bears, so take note and that is normal. Bulls are usually pretty good indicators especially if you see them on C,E,G waves.
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cyclic smoothed RSI (cRSI) indicator
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The “core” code for the cyclic smoothed RSI (cRSI) indicator was written by Lars von Theinen and is subject to the terms of the Mozilla Public License 2.0 at mozilla.org Copyright (C) 2017 CC BY, whentotrade / Lars von Thienen. For more details on the cRSI Indicator:
The cyclic smoothed RSI indicator is an enhancement of the classic RSI, adding
1) additional smoothing according to the market vibration,
2) adaptive upper and lower bands according to the cyclic memory and
3) using the current dominant cycle length as input for the indicator.
It is much more responsive to market moves than the basic RSI. The indicator uses the dominant cycle as input to optimize signal, smoothing, and cyclic memory. To get more in-depth information on the cyclic-smoothed RSI indicator, please read Decoding The Hidden Market Rhythm - Part 1: Dynamic Cycles (2017), Chapter 4: "Fine-tuning technical indicators." You need to derive the dominant cycle as input parameter for the cycle length as described in chapter 4.
Hope this helps and good luck.
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
Multi SMA EMA WMA HMA BB (4x5 MAs Bollinger Bands) Adv MTF - RRBMulti SMA EMA WMA HMA 4x5 Moving Averages with Bollinger Bands Advanced MTF by RagingRocketBull 2019
Version 1.0
This indicator shows multiple MAs of any type SMA EMA WMA HMA etc with BB and MTF support, can show MAs as dynamically moving levels.
There are 4 MA groups + 1 BB group, a total of 4 TFs * 5 MAs = 20 MAs. You can assign any type/timeframe combo to a group, for example:
- EMAs 12,26,50,100,200 x H1, H4, D1, W1 (4 TFs x 5 MAs x 1 type)
- EMAs 8,10,13,21,30,50,55,100,200,400 x M15, H1 (2 TFs x 10 MAs x 1 type)
- D1 EMAs and SMAs 8,10,12,26,30,50,55,100,200,400 (1 TF x 10 MAs x 2 types)
- H1 WMAs 7,77,89,167,231; H4 HMAs 12,26,50,100,200; D1 EMAs 89,144,169,233,377; W1 SMAs 12,26,50,100,200 (4 TFs x 5 MAs x 4 types)
- +1 extra MA type/timeframe for BB
There are several versions: Simple, MTF, Pro MTF, Advanced MTF and Ultimate MTF. This is the Advanced MTF version. The Differences are listed below. All versions have BB
- Simple: you have 2 groups of MAs that can be assigned any type (5+5)
- MTF: +2 custom Timeframes for each group (2x5 MTF) +1 TF for BB, TF XY smoothing
- Pro MTF: 4 custom Timeframes for each group (4x3 MTF), 1 TF for BB, MA levels and show max bars back options
- Advanced MTF: +2 extra MAs/group (4x5 MTF), custom Ticker/Symbols, Timeframe <>= filter, Remove Duplicates Option
- Ultimate MTF: +individual settings for each MA, custom Ticker/Symbols
Features:
- 4x5 = 20 MAs of any type
- 4x MTF groups with XY step line smoothing
- +1 extra TF/type for BB MAs
- 4x5 = 20 MA levels with adjustable group offsets, indents and shift
- supports any existing type of MA: SMA, EMA, WMA, Hull Moving Average (HMA)
- custom tickers/symbols for each group - you can compare MAs of the same symbol across exchanges
- show max bars back option
- show/hide both groups of MAs/levels/BB and individual MAs
- timeframe filter: show only MAs/Levels with TFs <>= Current TF
- hide MAs/Levels with duplicate TFs
- support for custom TFs that are not available in free accounts: 2D, 3D etc
- support for timeframes in H: H, 2H, 4H etc
Notes:
- Uses timeframe textbox instead of input resolution dropdown to allow for 240 120 and other custom TFs
- Uses symbol textbox instead of input symbol to avoid establishing multiple dummy security connections to the current ticker - otherwise empty symbols will prevent script from running
- Possible reasons for missing MAs on a chart:
- there may not be enough bars in history to start plotting it. For example, W1 EMA200 needs at least 200 bars on a weekly chart.
- price << default Y smoothing step 5. For charts with low/fractional prices (i.e. 0.00002 << 5) adjust X Y smoothing as needed (set Y = 0.0000001) or disable it completely (set X,Y to 0,0)
- TradingView Replay Mode UI and Pinescript security calls are limited to TFs >= D (D,2D,W,MN...) for free accounts
- attempting to plot any TF < D1 in Replay Mode will only result in straight lines, but all TFs will work properly in history and real-time modes. This is not a bug.
- Max Bars Back (num_bars) is limited to 5000 for free accounts (10000 for paid), will show error when exceeded. To plot on all available history set to 0 (default)
- Slow load/redraw times. This indicator becomes slower, its UI less responsive when:
- Pinescript Node.js graphics library is too slow and inefficient at plotting bars/objects in a browser window. Code optimization doesn't help much - the graphics engine is the main reason for general slowness.
- the chart has a long history (10000+ bars) in a browser's cache (you have scrolled back a couple of screens in a max zoom mode).
- Reload the page/Load a fresh chart and then apply the indicator or
- Switch to another Timeframe (old TF history will still remain in cache and that TF will be slow)
- in max possible zoom mode around 4500 bars can fit on 1 screen - this also slows down responsiveness. Reset Zoom level
- initial load and redraw times after a param change in UI also depend on TF. For example:
D1/W1 - 2 sec, H1/H4 - 5-6 sec, M30 - 10 sec, M15/M5 - 4 sec, M1 - 5 sec.
M30 usually has the longest history (up to 16000 bars) and W1 - the shortest (1000 bars).
- when indicator uses more MAs (plots) and timeframes it will redraw slower. Seems that up to 5 Timeframes is acceptable, but 6+ Timeframes can become very slow.
- show_last=last_bars plot limit doesn't affect load/redraw times, so it was removed from MA plot
- Max Bars Back (num_bars) default/custom set UI value doesn't seem to affect load/redraw times
- In max zoom mode all dynamic levels disappear (they behave like text)
1. based on 3EmaBB, uses plot*, barssince and security functions
2. you can't set certain constants from input due to Pinescript limitations - change the code as needed, recompile and use as a private version
3. Levels = trackprice implementation
4. Show Max Bars Back = show_last implementation
5. swma has a fixed length = 4, alma and linreg have additional offset and smoothing params
6. Smoothing is applied by default for visual aesthetics on MTF. To use exact ma mtf values (lines with stair stepping) - disable it
Good Luck! You can explore, modify/reuse the code to build your own indicators.
The Zone Trades v1.0The Zone is mention in New Trading Dimensions by Bill Williams,PhD.
The Zone is used for Entry Signal
Green Zone are painting Green Bars when Awesome Oscillator (AO) and Accelerater/Decelerator (AC) are both increasing.
Red Zone are painting Red Bars when Awesome Oscillator (AO) and Accelerater/Decelerator (AC) are both decreasing.
Gray Zone are painting Gray Bars AO and AC in difference changing
Gray Zone are indicate the indecision between bulls and bears.
Bill Williams, PhD. mention that Green Zone or Red Zone usually happen 6-8 bars Continuously.
The First Bar that change to be Green or Red color is the Signal Bar.
Entry Signal is the second bar in the same color as the Signal bar happen with Volume
Price go higher the high of previous Green Bar is Buy Signal. Entry Buy (Long) and place Stop at 1 tick lower the Low of previous bar.
Price go ;ower the Low of previous Red Bars is Sell Signal. Entry Sell (Short) and place Stop at 1 tick higher the High of previous bar.
Do not Entry if Green Bars or Red Bars completed 5 bars continuously.
The Zone Trades v1.0The Zone v.1.0
The Zone is mention in New Trading Dimensions by Bill Williams,PhD. The Zone is used for Entry Signal of Both Long and Short side.
Green Zone are painting Green Bars when Awesome Oscillator (AO) and Accelerater/Decelerator (AC) are both increasing.
Red Zone are painting Red Bars when Awesome Oscillator (AO) and Accelerater/Decelerator (AC) are both decreasing.
Gray Zone are painting Gray Bars AO and AC in difference changing. Gray Zone are indicate the indecision between bulls and bears.
Bill Williams, PhD. mention that Green Zone or Red Zone usually happen 6-8 bars Continuously.
The First Bar that change to be Green or Red color is the Signal Bar.
Entry Signal is the second bar in the same color as the Signal bar happen with Volume
Price go higher the high of previous Green Bar is Buy Signal. Entry Buy (Long) and place Stop at 1 tick lower the Low of previous bar.
Price go ;ower the Low of previous Red Bars is Sell Signal. Entry Sell (Short) and place Stop at 1 tick higher the High of previous bar.
Do not Entry if Green Bars or Red Bars completed 5 bars continuously.
Indicator: Relative Volume Indicator & Freedom Of MovementRelative Volume Indicator
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RVI is a support-resistance technical indicator developed by Melvin E. Dickover. Unlike many conventional support and resistance indicators, the Relative Volume Indicator takes into account price-volume behavior in order to detect the supply and demand pools. These pools are marked by "Defended Price Lines" (DPLs), also introduced by the author.
RVI is usually plotted as a histogram; its bars are highlighted (black, by default) when the volume is unusually large. According to the author, this happens if the indicator value exceeds 2.0, thus signifying that a possible DPL is present.
DPLs are horizontal lines that run across the chart at levels defined by following conditions:
* Overlapping bars: If the indicator spike (i.e., indicator is above 2.0 or a custom value)
corresponds to a price bar overlapping the previous one, the previous close can be used as the
DPL value.
* Very large bars: If the indicator spike corresponds to a price bar of a large size, use its
close price as the DPL value.
* Gapping bars: If the indicator spike corresponds to a price bar gapping from the previous bar,
the DPL value will depend on the gap size. Small gaps can be ignored: the author suggests using
the previous close as the DPL value. When the gap is big, the close of the latter bar is used
instead.
* Clustering spikes: If the indicator spikes come in clusters, use the extreme close or open
price of the bar corresponding to the last or next to last spike in cluster.
DPLs can be used as support and resistance levels. In order confirm and refine them, RVI is used along with the FreedomOfMovement indicator discussed next.
Freedom of Movement Indicator
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FOM is a support-resistance technical indicator, also by Melvin E. Dickover. FOM is the ratio of relative effect (relative price change) to the relative effort (normalized volume), expressed in standard deviations. This value is plotted as a histogram; its bars are highlighted (black, by default( when this ratio is unusually high. These highlighted bars, or "spikes", define the positioning of the DPLs.
Suggestions for placing DPLs are the same as for the Relative Volume Indicator discussed above.
Note that clustering spikes provide the strongest DPLs while isolated spikes can be used to confirm and refine those provided by the Relative Volume Indicator. Coincidence of spikes of the two indicator can be considered a sign of greater strength of the DPL.
More info:
S&C magazine, April 2014.
I am still trying these on various instruments to understand the workings more. Don't forget to share what you learn -- any use cases / ideal scenarios / gotchas, would love to hear them all.
X Trade Planlets you define up to 10 fully manual price levels and ranges—each with its own toggle, two prices (for a band/box), an optional note, and a color. The tool draws lines that start at the first bar of a chosen anchor timeframe (e.g., Daily) and extend to the right, mirroring the “fresh start-of-session” look. If two prices are entered, the area between them is shaded using the same color at 60% transparency, so the line and box fill are visually consistent.
Key Features
10 explicit categories (Cat 1 … Cat 10)
Each category includes:
Enable/disable toggle
Price 1 (line) and Price 2 (optional, defines box top/bottom)
Note (optional): label shows note only; hidden automatically if blank
Color: used for the line, box border, and box fill (with 60% transparency)
Anchor-aware drawing
Lines and boxes begin at the new bar of your selected Anchor Timeframe (e.g., D/W/H4), producing clean, session-style extensions.
Clean visuals
Line width is standardized at 1 for a crisp, unobtrusive look
Labels are aligned to the right of current bars and inherit user label styling options (size, text color, background)
No historical dependence
The indicator does not compute or display historical pivots, opens, or derived levels. Everything is user-defined.
Inputs (Per Category)
Cat N (toggle): Show/hide the category
Price 1: Primary level; a horizontal line is drawn when set
Price 2 (optional): When set with Price 1, a box is drawn between the two values
Note (optional): Free-text label; shown only if non-empty
Color: Applies to line, box border, and box fill (fill uses 60% transparency)
Global Inputs
Anchor Timeframe: Timeframe whose new bar defines the start (anchor) of all lines/boxes
Extend Right (bars): Number of bars to extend into the future
Labels (on/off) and label style options (size, text color, background)
How It Works
On the first bar and on each new bar of the anchor timeframe, the indicator captures the current bar index as the anchor for each category.
For each enabled category:
If Price 1 is set, the script draws a horizontal line from the anchor to extend_len bars into the future.
If Price 2 is also set, a box spanning Price 1 ↔ Price 2 is drawn from the anchor to the same future point.
If a Note is provided, a right-side label is rendered at the level (or box midpoint). If the note is empty, no label is shown.
Visual objects are refreshed every bar to ensure alignment with current settings.
Common Use Cases
Scenario planning & playbooks: Define “watch zones” (e.g., Look Above & Fail) and keep them consistent across sessions.
Manual S/R & liquidity areas: Mark hand-picked levels/ranges you care about, without auto-calculated clutter.
Session-like anchoring: Start-of-day/week anchoring to mimic institutional levels that reset each period.
Trade management: Color-coded bands for entries, invalidation, and targets with clear notes
EMA 50/200/100 [NevoxCore]⯁ OVERVIEW
EMA 50/200/100 is a clean EMA trio for trend mapping.
It highlights the classic 50/200 bias, keeps a constant EMA-100 anchor in white, plots cross dots, and can mark the first pullback back to a target EMA within an ATR tolerance.
Solid bias bar coloring (Nevox pink/orange or classic green/red) and compact visuals make it fast and reliable with no repainting.
⯁ HOW IT WORKS
Calculates Fast EMA 50, Slow EMA 200, and an always-on EMA 100 (white).
Bias = Fast vs. Slow: Fast > Slow → long regime; Fast < Slow → short regime.
Cross dots appear at confirmed 50/200 crosses (once per bar close).
First Pullback: after a cross, the script arms a window and marks the first return to the chosen EMA (100 or Fast) within ATR × tolerance.
Bar coloring is solid by regime (pink/orange by default, classic green/red when enabled).
No lookahead; signals confirm on bar close.
⯁ KEY FEATURES
• EMA 50/200 with EMA-100 anchor (always visible, white)
• Cross Up/Down dots (style-configurable)
• First Pullback marker (toggle) with ATR tolerance & window
• Solid bias bar coloring (Nevox or classic)
• Optional bias fill between Fast/Slow
• Minimal 1-cell HUD (OFF by default)
• Ready-made alerts with clean prefixes
⯁ SETTINGS (quick)
Visual: Classic colors toggle; Bias Fill (ON); Fill Transparency (85); Bar Color (solid, ON; auto-disabled when Classic is ON).
Core: Source = Close; EMA Fast = 50; EMA Slow = 200.
Pullback: Show marker (ON); Target EMA = EMA 100; Tolerance × ATR = 0.5; Max Bars After Cross = 40; ATR Length = 14.
HUD: Mini HUD OFF; Position selector.
Status Line: OFF by default (optional EMA values).
⯁ ALERTS (built-in)
• Cross Up (Fast above Slow) — confirmed at bar close
• Cross Down (Fast below Slow) — confirmed at bar close
• First Pullback LONG — first return to target after long cross
• First Pullback SHORT — first return to target after short cross
Prefix: EMA and message includes {{ticker}} {{interval}} @ {{close}}.
Suggested: set TradingView alerts to Once Per Bar Close.
⯁ HOW TO USE
• Read trend quickly: 50 above 200 with a rising 100 = healthy long bias.
• Use the First Pullback to time entries after a cross (default target = EMA 100).
• Tune Tolerance × ATR by symbol/TF; 0.3–0.7 is a good start.
• Keep charts clean: bias fill + barcolor ON; switch to Classic for green/red if preferred.
⯁ WHY IT’S DIFFERENT
It preserves the classic 50/200 logic but adds a consistent EMA-100 anchor, a single, one-shot pullback detector, and clean bias bars — all in a lightweight overlay with no repaint tricks.
⯁ DISCLAIMER
Backtest and paper-trade before using live. Not financial advice. Performance depends on market, timeframe, and parameters.
Breaout and followthroughThis indicator is designed to identify and highlight a single, powerful entry signal at the beginning of a new trend. It filters for high-volatility breakout bars that show strong directional conviction, helping traders catch the initial momentum of a potential move. It will only paint one bullish or bearish signal after a trend change is detected, preventing repeat signals during a sustained move.
Core Concept
The indicator combines four key concepts to generate high-probability signals:
Trend Direction: It first establishes the overall trend (bullish or bearish) using a configurable Exponential or Simple Moving Average (EMA/SMA).
Volatility Expansion: It looks for bars with a larger-than-average range by comparing the bar's size to the Average True Range (ATR). This helps identify moments of increased market interest.
Closing Strength (IBS): It uses the Internal Bar Strength (IBS) to measure directional conviction. A high IBS (closing near the top) suggests bullish strength, while a low IBS (closing near the bottom) suggests bearish pressure.
Breakout Confirmation: As an optional but powerful filter, it can confirm the signal by ensuring the bar is breaking above the high or below the low of a user-defined number of previous bars.
A signal is only generated on the first bar that meets all these criteria after the price crosses the trend-defining moving average, making it ideal for capturing the start of a new swing.
Features
Bullish Signals (Green): Highlights the first bar in an uptrend that is larger than the ATR, closes with a high IBS (>70), and optionally breaks out above the recent highs.
Bearish Signals (Red): Highlights the first bar in a downtrend that is larger than the ATR, closes with a low IBS (<30), and optionally breaks out below the recent lows.
"First Signal Only" Logic: The script is hard-coded to show only the initial signal in a new trend, filtering out noise and redundant signals.
Fully Customizable Trend Filter:
Choose between EMA or SMA for trend definition.
Set the MA length (default is a short-term 7-period MA).
Option to show or hide the moving average on the chart.
Optional Breakout Filter:
Enable or disable the requirement for the signal bar to break the high/low of previous bars.
Customize the lookback period for the breakout confirmation.
How to Use
This indicator can be used as a primary signal for a trend-following or momentum-based trading system.
Look for a Green Bar (Bullish Signal): This suggests the start of a potential uptrend. Consider it a signal for a long entry. A logical stop-loss could be placed below the low of the highlighted signal bar.
Look for a Red Bar (Bearish Signal): This suggests the start of a potential downtrend. Consider it a signal for a short entry. A logical stop-loss could be placed above the high of the highlighted signal bar.
Adjust Settings: Use the settings menu to configure the indicator to your preferred market and timeframe. A longer Trend MA Length will result in fewer, more long-term signals, while a shorter length will be more responsive.
As with any tool, this indicator is best used in conjunction with other forms of analysis, such as market structure, support/resistance levels, and proper risk management.
BOCS Channel Scalper Strategy - Automated Mean Reversion System# BOCS Channel Scalper Strategy - Automated Mean Reversion System
## WHAT THIS STRATEGY DOES:
This is an automated mean reversion trading strategy that identifies consolidation channels through volatility analysis and executes scalp trades when price enters entry zones near channel boundaries. Unlike breakout strategies, this system assumes price will revert to the channel mean, taking profits as price bounces back from extremes. Position sizing is fully customizable with three methods: fixed contracts, percentage of equity, or fixed dollar amount. Stop losses are placed just outside channel boundaries with take profits calculated either as fixed points or as a percentage of channel range.
## KEY DIFFERENCE FROM ORIGINAL BOCS:
**This strategy is designed for traders seeking higher trade frequency.** The original BOCS indicator trades breakouts OUTSIDE channels, waiting for price to escape consolidation before entering. This scalper version trades mean reversion INSIDE channels, entering when price reaches channel extremes and betting on a bounce back to center. The result is significantly more trading opportunities:
- **Original BOCS**: 1-3 signals per channel (only on breakout)
- **Scalper Version**: 5-15+ signals per channel (every touch of entry zones)
- **Trade Style**: Mean reversion vs trend following
- **Hold Time**: Seconds to minutes vs minutes to hours
- **Best Markets**: Ranging/choppy conditions vs trending breakouts
This makes the scalper ideal for active day traders who want continuous opportunities within consolidation zones rather than waiting for breakout confirmation. However, increased trade frequency also means higher commission costs and requires tighter risk management.
## TECHNICAL METHODOLOGY:
### Price Normalization Process:
The strategy normalizes price data to create consistent volatility measurements across different instruments and price levels. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). Current close price is normalized using: (close - lowest_low) / (highest_high - lowest_low), producing values between 0 and 1 for standardized volatility analysis.
### Volatility Detection:
A 14-period standard deviation is applied to the normalized price series to measure price deviation from the mean. Higher standard deviation values indicate volatility expansion; lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() to identify when volatility peaks and troughs occur over the detection period (default 14 bars).
### Channel Formation Logic:
When volatility crosses from a high level to a low level (ta.crossover(upper, lower)), a consolidation phase begins. The strategy tracks the highest and lowest prices during this period, which become the channel boundaries. Minimum duration of 10+ bars is required to filter out brief volatility spikes. Channels are rendered as box objects with defined upper and lower boundaries, with colored zones indicating entry areas.
### Entry Signal Generation:
The strategy uses immediate touch-based entry logic. Entry zones are defined as a percentage from channel edges (default 20%):
- **Long Entry Zone**: Bottom 20% of channel (bottomBound + channelRange × 0.2)
- **Short Entry Zone**: Top 20% of channel (topBound - channelRange × 0.2)
Long signals trigger when candle low touches or enters the long entry zone. Short signals trigger when candle high touches or enters the short entry zone. This captures mean reversion opportunities as price reaches channel extremes.
### Cooldown Filter:
An optional cooldown period (measured in bars) prevents signal spam by enforcing minimum spacing between consecutive signals. If cooldown is set to 3 bars, no new long signal will fire until 3 bars after the previous long signal. Long and short cooldowns are tracked independently, allowing both directions to signal within the same period.
### ATR Volatility Filter:
The strategy includes a multi-timeframe ATR filter to avoid trading during low-volatility conditions. Using request.security(), it fetches ATR values from a specified timeframe (e.g., 1-minute ATR while trading on 5-minute charts). The filter compares current ATR to a user-defined minimum threshold:
- If ATR ≥ threshold: Trading enabled
- If ATR < threshold: No signals fire
This prevents entries during dead zones where mean reversion is unreliable due to insufficient price movement.
### Take Profit Calculation:
Two TP methods are available:
**Fixed Points Mode**:
- Long TP = Entry + (TP_Ticks × syminfo.mintick)
- Short TP = Entry - (TP_Ticks × syminfo.mintick)
**Channel Percentage Mode**:
- Long TP = Entry + (ChannelRange × TP_Percent)
- Short TP = Entry - (ChannelRange × TP_Percent)
Default 50% targets the channel midline, a natural mean reversion target. Larger percentages aim for opposite channel edge.
### Stop Loss Placement:
Stop losses are placed just outside the channel boundary by a user-defined tick offset:
- Long SL = ChannelBottom - (SL_Offset_Ticks × syminfo.mintick)
- Short SL = ChannelTop + (SL_Offset_Ticks × syminfo.mintick)
This logic assumes channel breaks invalidate the mean reversion thesis. If price breaks through, the range is no longer valid and position exits.
### Trade Execution Logic:
When entry conditions are met (price in zone, cooldown satisfied, ATR filter passed, no existing position):
1. Calculate entry price at zone boundary
2. Calculate TP and SL based on selected method
3. Execute strategy.entry() with calculated position size
4. Place strategy.exit() with TP limit and SL stop orders
5. Update info table with active trade details
The strategy enforces one position at a time by checking strategy.position_size == 0 before entry.
### Channel Breakout Management:
Channels are removed when price closes more than 10 ticks outside boundaries. This tolerance prevents premature channel deletion from minor breaks or wicks, allowing the mean reversion setup to persist through small boundary violations.
### Position Sizing System:
Three methods calculate position size:
**Fixed Contracts**:
- Uses exact contract quantity specified in settings
- Best for futures traders (e.g., "trade 2 NQ contracts")
**Percentage of Equity**:
- position_size = (strategy.equity × equity_pct / 100) / close
- Dynamically scales with account growth
**Cash Amount**:
- position_size = cash_amount / close
- Maintains consistent dollar exposure regardless of price
## INPUT PARAMETERS:
### Position Sizing:
- **Position Size Type**: Choose Fixed Contracts, % of Equity, or Cash Amount
- **Number of Contracts**: Fixed quantity per trade (1-1000)
- **% of Equity**: Percentage of account to allocate (1-100%)
- **Cash Amount**: Dollar value per position ($100+)
### Channel Settings:
- **Nested Channels**: Allow multiple overlapping channels vs single channel
- **Normalization Length**: Lookback for high/low calculation (1-500, default 100)
- **Box Detection Length**: Period for volatility detection (1-100, default 14)
### Scalping Settings:
- **Enable Long Scalps**: Toggle long entries on/off
- **Enable Short Scalps**: Toggle short entries on/off
- **Entry Zone % from Edge**: Size of entry zone (5-50%, default 20%)
- **SL Offset (Ticks)**: Distance beyond channel for stop (1+, default 5)
- **Cooldown Period (Bars)**: Minimum spacing between signals (0 = no cooldown)
### ATR Filter:
- **Enable ATR Filter**: Toggle volatility filter on/off
- **ATR Timeframe**: Source timeframe for ATR (1, 5, 15, 60 min, etc.)
- **ATR Length**: Smoothing period (1-100, default 14)
- **Min ATR Value**: Threshold for trade enablement (0.1+, default 10.0)
### Take Profit Settings:
- **TP Method**: Choose Fixed Points or % of Channel
- **TP Fixed (Ticks)**: Static distance in ticks (1+, default 30)
- **TP % of Channel**: Dynamic target as channel percentage (10-100%, default 50%)
### Appearance:
- **Show Entry Zones**: Toggle zone labels on channels
- **Show Info Table**: Display real-time strategy status
- **Table Position**: Corner placement (Top Left/Right, Bottom Left/Right)
- **Color Settings**: Customize long/short/TP/SL colors
## VISUAL INDICATORS:
- **Channel boxes** with semi-transparent fill showing consolidation zones
- **Colored entry zones** labeled "LONG ZONE ▲" and "SHORT ZONE ▼"
- **Entry signal arrows** below/above bars marking long/short entries
- **Active TP/SL lines** with emoji labels (⊕ Entry, 🎯 TP, 🛑 SL)
- **Info table** showing position status, channel state, last signal, entry/TP/SL prices, and ATR status
## HOW TO USE:
### For 1-3 Minute Scalping (NQ/ES):
- ATR Timeframe: "1" (1-minute)
- ATR Min Value: 10.0 (for NQ), adjust per instrument
- Entry Zone %: 20-25%
- TP Method: Fixed Points, 20-40 ticks
- SL Offset: 5-10 ticks
- Cooldown: 2-3 bars
- Position Size: 1-2 contracts
### For 5-15 Minute Day Trading:
- ATR Timeframe: "5" or match chart
- ATR Min Value: Adjust to instrument (test 8-15 for NQ)
- Entry Zone %: 20-30%
- TP Method: % of Channel, 40-60%
- SL Offset: 5-10 ticks
- Cooldown: 3-5 bars
- Position Size: Fixed contracts or 5-10% equity
### For 30-60 Minute Swing Scalping:
- ATR Timeframe: "15" or "30"
- ATR Min Value: Lower threshold for broader market
- Entry Zone %: 25-35%
- TP Method: % of Channel, 50-70%
- SL Offset: 10-15 ticks
- Cooldown: 5+ bars or disable
- Position Size: % of equity recommended
## BACKTEST CONSIDERATIONS:
- Strategy performs best in ranging, mean-reverting markets
- Strong trending markets produce more stop losses as price breaks channels
- ATR filter significantly reduces trade count but improves quality during low volatility
- Cooldown period trades signal quantity for signal quality
- Commission and slippage materially impact sub-5-minute timeframe performance
- Shorter timeframes require tighter entry zones (15-20%) to catch quick reversions
- % of Channel TP adapts better to varying channel sizes than fixed points
- Fixed contract sizing recommended for consistent risk per trade in futures
**Backtesting Parameters Used**: This strategy was developed and tested using realistic commission and slippage values to provide accurate performance expectations. Recommended settings: Commission of $1.40 per side (typical for NQ futures through discount brokers), slippage of 2 ticks to account for execution delays on fast-moving scalp entries. These values reflect real-world trading costs that active scalpers will encounter. Backtest results without proper cost simulation will significantly overstate profitability.
## COMPATIBLE MARKETS:
Works on any instrument with price data including stock indices (NQ, ES, YM, RTY), individual stocks, forex pairs (EUR/USD, GBP/USD), cryptocurrency (BTC, ETH), and commodities. Volume-based features require data feed with volume information but are optional for core functionality.
## KNOWN LIMITATIONS:
- Immediate touch entry can fire multiple times in choppy zones without adequate cooldown
- Channel deletion at 10-tick breaks may be too aggressive or lenient depending on instrument tick size
- ATR filter from lower timeframes requires higher-tier TradingView subscription (request.security limitation)
- Mean reversion logic fails in strong breakout scenarios leading to stop loss hits
- Position sizing via % of equity or cash amount calculates based on close price, may differ from actual fill price
- No partial closing capability - full position exits at TP or SL only
- Strategy does not account for gap openings or overnight holds
## RISK DISCLOSURE:
Trading involves substantial risk of loss. Past performance does not guarantee future results. This strategy is for educational purposes and backtesting only. Mean reversion strategies can experience extended drawdowns during trending markets. Stop losses may not fill at intended levels during extreme volatility or gaps. Thoroughly test on historical data and paper trade before risking real capital. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions. Automated trading systems can malfunction - monitor all live positions actively.
## ACKNOWLEDGMENT & CREDITS:
This strategy is built upon the channel detection methodology created by **AlgoAlpha** in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns. The core channel formation logic using normalized price standard deviation is AlgoAlpha's original contribution to the TradingView community.
Enhancements to the original concept include: mean reversion entry logic (vs breakout), immediate touch-based signals, multi-timeframe ATR volatility filtering, flexible position sizing (fixed/percentage/cash), cooldown period filtering, dual TP methods (fixed points vs channel percentage), automated strategy execution with exit management, and real-time position monitoring table.
BOCS AdaptiveBOCS Adaptive Strategy - Automated Volatility Breakout System
WHAT THIS STRATEGY DOES:
This is an automated trading strategy that detects consolidation patterns through volatility analysis and executes trades when price breaks out of these channels. Take-profit and stop-loss levels are calculated dynamically using Average True Range (ATR) to adapt to current market volatility. The strategy closes positions partially at the first profit target and exits the remainder at the second target or stop loss.
TECHNICAL METHODOLOGY:
Price Normalization Process:
The strategy begins by normalizing price to create a consistent measurement scale. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). The current close price is then normalized using the formula: (close - lowest_low) / (highest_high - lowest_low). This produces values between 0 and 1, allowing volatility analysis to work consistently across different instruments and price levels.
Volatility Detection:
A 14-period standard deviation is applied to the normalized price series. Standard deviation measures how much prices deviate from their average - higher values indicate volatility expansion, lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() functions to track when volatility reaches peaks and troughs over the detection length period (default 14 bars).
Channel Formation Logic:
When volatility crosses from a high level to a low level, this signals the beginning of a consolidation phase. The strategy records this moment using ta.crossover(upper, lower) and begins tracking the highest and lowest prices during the consolidation. These become the channel boundaries. The duration between the crossover and current bar must exceed 10 bars minimum to avoid false channels from brief volatility spikes. Channels are drawn using box objects with the recorded high/low boundaries.
Breakout Signal Generation:
Two detection modes are available:
Strong Closes Mode (default): Breakout occurs when the candle body midpoint math.avg(close, open) exceeds the channel boundary. This filters out wick-only breaks.
Any Touch Mode: Breakout occurs when the close price exceeds the boundary.
When price closes above the upper channel boundary, a bullish breakout signal generates. When price closes below the lower boundary, a bearish breakout signal generates. The channel is then removed from the chart.
ATR-Based Risk Management:
The strategy uses request.security() to fetch ATR values from a specified timeframe, which can differ from the chart timeframe. For example, on a 5-minute chart, you can use 1-minute ATR for more responsive calculations. The ATR is calculated using ta.atr(length) with a user-defined period (default 14).
Exit levels are calculated at the moment of breakout:
Long Entry Price = Upper channel boundary
Long TP1 = Entry + (ATR × TP1 Multiplier)
Long TP2 = Entry + (ATR × TP2 Multiplier)
Long SL = Entry - (ATR × SL Multiplier)
For short trades, the calculation inverts:
Short Entry Price = Lower channel boundary
Short TP1 = Entry - (ATR × TP1 Multiplier)
Short TP2 = Entry - (ATR × TP2 Multiplier)
Short SL = Entry + (ATR × SL Multiplier)
Trade Execution Logic:
When a breakout occurs, the strategy checks if trading hours filter is satisfied (if enabled) and if position size equals zero (no existing position). If volume confirmation is enabled, it also verifies that current volume exceeds 1.2 times the 20-period simple moving average.
If all conditions are met:
strategy.entry() opens a position using the user-defined number of contracts
strategy.exit() immediately places a stop loss order
The code monitors price against TP1 and TP2 levels on each bar
When price reaches TP1, strategy.close() closes the specified number of contracts (e.g., if you enter with 3 contracts and set TP1 close to 1, it closes 1 contract). When price reaches TP2, it closes all remaining contracts. If stop loss is hit first, the entire position exits via the strategy.exit() order.
Volume Analysis System:
The strategy uses ta.requestUpAndDownVolume(timeframe) to fetch up volume, down volume, and volume delta from a specified timeframe. Three display modes are available:
Volume Mode: Shows total volume as bars scaled relative to the 20-period average
Comparison Mode: Shows up volume and down volume as separate bars above/below the channel midline
Delta Mode: Shows net volume delta (up volume - down volume) as bars, positive values above midline, negative below
The volume confirmation logic compares breakout bar volume to the 20-period SMA. If volume ÷ average > 1.2, the breakout is classified as "confirmed." When volume confirmation is enabled in settings, only confirmed breakouts generate trades.
INPUT PARAMETERS:
Strategy Settings:
Number of Contracts: Fixed quantity to trade per signal (1-1000)
Require Volume Confirmation: Toggle to only trade signals with volume >120% of average
TP1 Close Contracts: Exact number of contracts to close at first target (1-1000)
Use Trading Hours Filter: Toggle to restrict trading to specified session
Trading Hours: Session input in HHMM-HHMM format (e.g., "0930-1600")
Main Settings:
Normalization Length: Lookback bars for high/low calculation (1-500, default 100)
Box Detection Length: Period for volatility peak/trough detection (1-100, default 14)
Strong Closes Only: Toggle between body midpoint vs close price for breakout detection
Nested Channels: Allow multiple overlapping channels vs single channel at a time
ATR TP/SL Settings:
ATR Timeframe: Source timeframe for ATR calculation (1, 5, 15, 60, etc.)
ATR Length: Smoothing period for ATR (1-100, default 14)
Take Profit 1 Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 2.0)
Take Profit 2 Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 3.0)
Stop Loss Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 1.0)
Enable Take Profit 2: Toggle second profit target on/off
VISUAL INDICATORS:
Channel boxes with semi-transparent fill showing consolidation zones
Green/red colored zones at channel boundaries indicating breakout areas
Volume bars displayed within channels using selected mode
TP/SL lines with labels showing both price level and distance in points
Entry signals marked with up/down triangles at breakout price
Strategy status table showing position, contracts, P&L, ATR values, and volume confirmation status
HOW TO USE:
For 2-Minute Scalping:
Set ATR Timeframe to "1" (1-minute), ATR Length to 12, TP1 Multiplier to 2.0, TP2 Multiplier to 3.0, SL Multiplier to 1.5. Enable volume confirmation and strong closes only. Use trading hours filter to avoid low-volume periods.
For 5-15 Minute Day Trading:
Set ATR Timeframe to match chart or use 5-minute, ATR Length to 14, TP1 Multiplier to 2.0, TP2 Multiplier to 3.5, SL Multiplier to 1.2. Volume confirmation recommended but optional.
For Hourly+ Swing Trading:
Set ATR Timeframe to 15-30 minute, ATR Length to 14-21, TP1 Multiplier to 2.5, TP2 Multiplier to 4.0, SL Multiplier to 1.5. Volume confirmation optional, nested channels can be enabled for multiple setups.
BACKTEST CONSIDERATIONS:
Strategy performs best during trending or volatility expansion phases
Consolidation-heavy or choppy markets produce more false signals
Shorter timeframes require wider stop loss multipliers due to noise
Commission and slippage significantly impact performance on sub-5-minute charts
Volume confirmation generally improves win rate but reduces trade frequency
ATR multipliers should be optimized for specific instrument characteristics
COMPATIBLE MARKETS:
Works on any instrument with price and volume data including forex pairs, stock indices, individual stocks, cryptocurrency, commodities, and futures contracts. Requires TradingView data feed that includes volume for volume confirmation features to function.
KNOWN LIMITATIONS:
Stop losses execute via strategy.exit() and may not fill at exact levels during gaps or extreme volatility
request.security() on lower timeframes requires higher-tier TradingView subscription
False breakouts inherent to breakout strategies cannot be completely eliminated
Performance varies significantly based on market regime (trending vs ranging)
Partial closing logic requires sufficient position size relative to TP1 close contracts setting
RISK DISCLOSURE:
Trading involves substantial risk of loss. Past performance of this or any strategy does not guarantee future results. This strategy is provided for educational purposes and automated backtesting. Thoroughly test on historical data and paper trade before risking real capital. Market conditions change and strategies that worked historically may fail in the future. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions.
ACKNOWLEDGMENT & CREDITS:
This strategy is built upon the channel detection methodology created by AlgoAlpha in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns and sharing this innovative technique with the TradingView community. The enhancements added to the original concept include automated trade execution, multi-timeframe ATR-based risk management, partial position closing by contract count, volume confirmation filtering, and real-time position monitoring.
EMP Probabilistic [CHE]Part 1 — For Traders (Practical Overview, no formulas)
What this tool does
EMP Probabilistic \ turns raw price action into a clean, probability-aware map. It builds two adaptive bands around the session open of a higher timeframe you choose (called the S-timeframe) and highlights a robust median threshold. At a glance you know:
Where price has recently tended to stay,
Whether current momentum sits above or below the median, and
A live Long vs. Short probability based on recent outcomes.
Why it improves decisions
Objective context in any regime: The nonparametric band comes straight from recent market behavior, without assuming a particular distribution.
Volatility-aware risk lens: The parametric band adapts to current volatility, helping you judge stretch and room for continuation or snap-back.
No lookahead: All stats update only after an S-bar is finished. That means the panel reflects information you truly had at that time.
How to read the chart
Orange band = empirical, distribution-free range derived from recent session returns (nonparametric).
Teal band = volatility-scaled range around the session open (parametric).
Median dots: green when close is above the median threshold, red when below.
Info panel: shows the active S-timeframe, window sizes, live coverage for both bands, the internal width parameter and volatility estimate, plus a one-line summary.
Probability label: “Long XX% • Short YY%” — a simple read on the recent balance of up vs. down S-bars.
How to use it (quick start)
1. Choose S-timeframe with Auto, Multiplier, or Manual. “Auto” scales your chart TF up to a sensible higher step.
2. Set alpha to control how tight the inner band should be. A typical value gives you a comfortable center zone without cutting off healthy trends.
3. Trade the context:
Trend-following: Prefer longs when price holds above the median; prefer shorts when it stays below.
Mean-reversion: Fade moves near the outer edges during ranges; look for reversion back toward the median.
Breakout filter: Require closes that push and hold beyond the volatility band for momentum plays; avoid noise when price chops inside the middle of the orange band.
Risk management made practical
Size positions relative to the teal band width to keep risk consistent across instruments and regimes.
For stops, many traders set them just beyond the opposite orange bound or use a fraction of the teal band.
Watch the panel’s coverage readouts and Brier score; when they deteriorate, the market may be shifting — reduce size or demand stronger confirmation.
Suggested presets
Scalping (Crypto/FX): Auto S-TF, alpha around a fifth, calibration window near two hundred, RS volatility, metrics window near two hundred.
Intraday Futures: Multiplier 3–5× your chart TF; similar alpha and window sizes; RS volatility is a solid default.
Swing/Equities: S-TF at least daily; test both RS and GK volatility modes; keep windows on the larger side for stability.
What makes it different
Two complementary lenses: a distribution-free read of recent behavior and a volatility-scaled read for risk and stretch.
Self-calibrating width: the parametric band quietly nudges its internal multiplier so actual coverage tracks your target.
Clean UX: grouped inputs, tooltips, an info panel that tells you what’s going on, and a simple median bias you can act on.
Repainting & timing
The logic updates only when the S-bar closes. On lower-timeframe charts you’ll see intrabar flips of the dot color — that’s just live price moving around. For strict signals, confirm on S-bar close.
Friendly note (not financial advice)
Use this as a context engine. It won’t predict the future, but it will keep you on the right side of probability and volatility more often, which is exactly where consistency starts.
Part 2 — Under the Hood (Conceptual, no formulas)
Data and timeframe design
The script works on a higher S-timeframe you select. It fetches the open, high, low, close, and time of that S-bar. Internally, it only updates its rolling windows after an S-bar has finished. It then pushes the previous S-bar’s statistics into its arrays. That design removes lookahead and keeps the metrics out-of-sample relative to the current S-bar.
Nonparametric band (distribution-free)
The orange band comes from the empirical distribution of recent session-level close-minus-open moves. The script keeps a rolling window, sorts a safe copy, and reads three key points: a lower bound, a median, and an upper bound. Because it’s based purely on observed outcomes, it adapts naturally to skew, fat tails, and regime shifts without assuming any particular shape. The orange range shows “where price has tended to live” lately on the chosen S-timeframe.
Parametric band (volatility-scaled)
The teal band models log-space variability around the session open using one of two well-known OHLC volatility estimators: Rogers–Satchell or Garman–Klass. Each estimator contributes a per-bar variance figure; the script averages these across the rolling window to form a current volatility scale. It then builds a symmetric band around the session open in price space. This gives you a volatility-aware notion of stretch that complements the distribution-free orange band.
Self-calibration of band width
The teal band has an internal width multiplier. After each completed S-bar the script checks whether the realized move stayed inside that band. If the band was too tight, the multiplier is nudged upward; if it was too loose, it’s eased downward. A simple learning rate governs how quickly it adapts. Over time this keeps the realized inside-coverage close to the target implied by your alpha setting, without you having to hand-tune anything.
Long/Short probability and calibration quality
The Long vs. Short probability is a transparent statistic: it’s just the recent fraction of up sessions in the rolling window. It is not a complex model — and that’s the point. You get an honest, intuitive read on directional tendency.
To monitor how well this simple probability lines up with reality, the script tracks a Brier-style score over a separate metrics window. Lower is better: it means your recent probability read has matched outcomes more closely.
Coverage tracking for both bands
The panel reports coverage for the orange band (nonparametric) and the teal band (parametric). These are rolling averages of how often recent S-bar moves landed inside each band. Watching these two numbers tells you whether market behavior still aligns with the recent distribution and with the current volatility model.
Why it doesn’t repaint
Because the arrays update only when an S-bar closes and only push the previous bar’s stats, the panel and metrics reflect information you had at the time. Intrabar visuals can change while a bar is forming — that’s expected — but the decision framework itself is anchored to completed S-bars.
Performance and practicality
The heaviest step is sorting a copy of the window for the nonparametric band. With typical window sizes this stays responsive on TradingView. The volatility estimators and rolling averages are lightweight. Inputs are grouped with clear tooltips so you can tune without hunting.
Limitations and good practice
In thin or gappy markets the bands can jump; consider a larger window or a higher S-timeframe.
During violent regime shifts, shorten the window and increase the learning rate slightly so the teal band catches up faster — but don’t overdo it, or you’ll chase noise.
The Long/Short probability is intentionally simple; it’s a context indicator, not a standalone signal factory. Combine it with structure, volume, or your execution rules.
Takeaway
Under the hood, the script blends empirical behavior and volatility scaling, then self-calibrates so the teal band’s real-world coverage stays near your target. You get clarity, consistency, and a dashboard that tells you when its own assumptions are holding up — exactly what you need to trade with confidence.
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.
Best regards and happy trading
Chervolino
Trend Score HTF (Raw Data) Pine Screener📘 Trend Score HTF (Raw Data) Pine Screener — Indicator Guide
This indicator tracks price action using a custom cumulative Trend Score (TS) system. It helps you visualize trend momentum, detect early reversals, confirm direction changes, and screen for entries across large watchlists like SPX500 using TradingView’s Pine Script Screener (beta).
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🔧 What This Indicator Does
• Assigns a +1 or -1 score when price breaks the previous high or low
• Accumulates these scores into a real-time tsScore
• Detects early warnings (primed flips) and trend changes (confirmed flips)
• Supports alerts and labels for visual and automated trading
• Designed to work inside the Pine Screener so you can filter hundreds of tickers live
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⚙️ Recommended Settings (for Beginners)
When adding the indicator to your chart:
Go to the “Inputs” tab at the top of the settings panel.
Then:
• Uncheck “Confirm flips on bar close”
• Check “Accumulate TS Across Flips? (ON = non-reset, OFF = reset)”
This setup allows you to see trend changes immediately without waiting for bar closes and lets the trend score build continuously over time, making it easier to follow long trends.
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🧠 Core Logic
Start Date
Select a meaningful historical start date — for example: 2020-01-01. This provides long-term context for trend score calculation.
Per-Bar Delta (Δ) Calculation
The indicator scores each bar based on breakout behavior:
If the bar breaks only the previous high, Δ = +1
If it breaks only the previous low, Δ = -1
If it breaks both the high and low, Δ = 0
If it breaks neither, Δ = 0
This filters out wide-range or indecisive candles during volatility.
Cumulative Trend Score
Each bar’s delta is added to the running tsScore.
When it rises, bullish pressure is building.
When it falls, bearish pressure is increasing.
Trend Flip Logic
A bullish flip happens when tsScore rises by +3 from the lowest recent point.
A bearish flip happens when tsScore falls by -3 from the highest recent point.
These flips update the active trend direction between bullish and bearish.
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⚠️ What Is a “Primed” Flip?
A primed flip is a signal that the current trend is about to flip — just one point away.
A primed bullish flip means the trend is currently bearish, but the tsScore only needs +1 more to flip. If the next bar breaks the previous high (without breaking the low), it will trigger a bullish flip.
A primed bearish flip means the trend is currently bullish, but the tsScore only needs -1 more to flip. If the next bar breaks the previous low (without breaking the high), it will trigger a bearish flip.
Primed flips are plotted one bar ahead of the current bar. They act like forecasts and give you a head start.
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✅ What Is a “Confirmed” Flip?
A confirmed flip is the first bar of a new trend direction.
A confirmed bullish flip appears when a bearish trend officially flips into a new bullish trend.
A confirmed bearish flip appears when a bullish trend officially flips into a new bearish trend.
These signals are reliable and great for entries, trend filters, or reversals.
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🖼 Visual Cues
The trend score (tsScore) line shows the accumulated trend strength.
A Δ histogram shows the daily price contribution: +1 for breaking highs, -1 for breaking lows, 0 otherwise.
A green background means the chart is in a bullish trend.
A red background means the chart is in a bearish trend.
A ⬆ label signals a primed bullish flip is possible on the next bar.
A ⬇ label signals a primed bearish flip is possible on the next bar.
A ✅ means a bullish flip just confirmed.
A ❌ means a bearish flip just confirmed.
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🔔 Alerts You Can Use
The indicator includes these built-in alerts:
• Primed Bullish Flip — watch for possible bullish reversal tomorrow
• Primed Bearish Flip — watch for possible bearish reversal tomorrow
• Bullish Confirmed — official entry into new uptrend
• Bearish Confirmed — official entry into new downtrend
You can set these alerts in TradingView to monitor across your chart or watchlist.
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📈 How to Use in TradingView Pine Screener
Step 1: Create your own watchlist — for example, SPX500
Step 2: Favorite this indicator so it shows up in the screener
Step 3: Go to TradingView → Products → Screeners → Pine (Beta)
Step 4: Select this indicator and choose a condition, like “Bullish Confirmed”
Step 5: Click Scan
You’ll instantly see stocks that just flipped trends or are close to doing so.
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⏰ When to Use the Screener
Use this screener after market close or before the next open to avoid intraday noise.
During the day, if a candle breaks both the high and low, the delta becomes 0, which may cancel a flip or primed signal.
Results during regular trading hours can change frequently. For best results, scan during stable periods like pre-market or after-hours.
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🧪 Real-World Examples
SWK
NVR
WMT
UNH
Each of these examples shows clean, structured trend transitions detected in advance or confirmed with precision.
PLTR: complicated case primed for bullish (but we don't when it will flip)
⚠️ Risk Disclaimer & Trend Context
A confirmed bullish signal does not guarantee an immediate price increase. Price may continue to consolidate or even pull back after a bullish flip.
Likewise, a primed bullish signal does not always lead to confirmation. It simply means the conditions are close — but if the next bar breaks both the high and low, or breaks only the low, the flip will be canceled.
On the other side, a confirmed bearish signal does not mean the market will crash. If the overall trend is bullish (for example, tsScore has been rising for weeks), then a bearish flip may just represent a short-term pullback — not a trend reversal.
You always need to consider the overall market structure. If the long-term trend is bullish, it’s usually smarter to wait for bullish confirmation signals. Bearish flips in that context are often just dips — not opportunities to short.
This indicator gives you context, not predictions. It’s a tool for alignment — not absolute outcomes. Use it to follow structure, not fight it.
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator
Purpose
This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns.
What a martingale is
A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged:
Lose one leg → increase next position size
Lose again → increase again
Win → reset to the base size
The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops.
What it plots
Equity – simulated portfolio equity including compounding
Buy & Hold – equity from holding the chart symbol for context
Optional helpers – last trade outcome, current streak length, current allocation fraction
Optional diagnostics – daily portfolio return, rolling drawdown, metrics table
Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands
Model assumptions
Bar-close execution with no slippage or commissions
Shorting allowed and frictionless
No margin interest, borrow fees, or position limits
No intrabar moves or gaps within a bar (returns are close-to-close)
Sizing applies to equity fraction only and is capped by your setting
All results are hypothetical and for education only.
How the simulator applies it
1) Directional signal
You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts.
2) Sizing after losses and wins
Position size is a fraction of equity:
Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity
Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double
Reset after win – return to the initial allocation
Max allocation cap – hard ceiling to prevent runaway growth
At a high level the size after k consecutive losses is
alloc(k) = min( cap , base × factor^k ) .
In practice the simulator changes size only when a leg ends and its PnL is known.
3) Equity update
Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds:
eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) .
This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled.
Why traders experiment with martingale sizing
Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn
Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests
Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live
Why martingale is dangerous
Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic:
Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N.
Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible.
No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels.
Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest.
Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs.
Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected.
The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty.
Interpreting losing streaks with numbers
A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check:
If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare.
If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap.
This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions
Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests..
Using the simulator productively
Parameter studies
Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond.
Initial allocation – lower base reduces volatility and drawdowns across the board
Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive
Max cap – the most important brake; many users keep it between 20 and 50 percent
Signal selection
Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each.
Diagnostics to watch
Use the built-in metrics to quantify risk:
Max Drawdown – worst peak-to-trough equity loss
Sharpe and Sortino – volatility and downside-adjusted return
VaR 95 percent and CVaR – tail risk measures from the realized distribution
Alpha and Beta – relationship to your chosen benchmark
If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see
Monte Carlo exploration
When enabled, the forecast draws many synthetic paths from your realized daily returns:
Choose a horizon and a number of runs
Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path
Use the table to read the expected return over the horizon and the tail outcomes
Remember it is a sketch based on your recent distribution, not a predictor
Concrete examples
Example A: Modest martingale
Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing.
Example B: Aggressive martingale
Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk.
Strengths
Bar-by-bar, transparent computation of equity from stance and size
Explicit handling of wins, losses, streaks, and caps
Portable signal inputs so you can A–B test ideas quickly
Risk diagnostics and forward uncertainty visualization in one place
Example, Rolling Max Drawdown
Limitations and important notes
Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs.
No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled.
Signals are evaluated on closes. Real execution and fills will differ.
Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes.
All results are hypothetical. Use this as an educational tool, not a production risk engine.
Practical tips
Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples.
Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg.
Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear.
Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off.
If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop.
Settings recap
Backtest start date and initial capital
Initial allocation, increase-after-loss factor, max allocation cap
Signal source selector
Trading days per year and risk-free rate
Benchmark symbol for Alpha and Beta
UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown
Monte Carlo controls for enable, runs, horizon, and result table
Final thoughts
A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
