G-Channels - Efficient Calculation Of Upper/Lower ExtremitiesIntroduction
Channels indicators are widely used in technical analysis, they provide lot of information. In general, technical indicators giving upper/lower extremities are calculated by adding/subtracting a volatility component to a central tendency estimator. This is the case with Bollinger bands, using the rolling standard deviation as volatility estimator and the simple moving average as central tendency estimator, or the Keltner channels using the exponential moving average and the average true range.
Lots and lots and lots (i can go on) of those indicators have been made, they only really need a central tendency estimator, which can be obtained from pretty much any filter, however i find interesting to focus on the efficiency of those indicators, therefore i propose a super efficient channel indicator using recursion. The average resulting from the upper/lower extremity of the indicator provide a new efficient filter similar to the average highest/lowest.
The calculation - How Does It Works
Efficiency is often associated to recursion, this would allow us to use past output values as input, so how does the indicator is calculated? Lets look at the upper band calculation :
a := max(src,nz(a(1))) - nz(a(1) - b(1))/length
src is the closing price, a is upper extremity, b is the lower one. Here we only need 3 values, the previous values of a and b and the closing price. Basically a := max(src,nz(a(1))) mean :
if the closing price is greater than the precedent value of a then output the closing price, else output the precedent value of a
therefore a will never be inferior to its precedent value, this is useful for getting the maximum price value in our dataset however its not useful to make an upper band, therefore we subtract this to a correction factor defined as the difference between a and b , this force the upper band to have lower values thus acting like a band without loosing its "upper" property, a similar process is done with the lower band.
Of course we could only use 2 values for making the indicator, thus ending with :
a := max(src,nz(a(1))) - nz(abs(close - a(1))/length
In fact this implementation is the same as the one proposed in my paper "Recursive Bands - A New Indicator For Technical Analysis", its also what i used for making the indicator "Adaptive Trailing Stop", this would be more efficient but i used the difference between the upper and lower extremities for a reason.
The Central tendency Estimator
This is the reason why i didn't implemented a more efficient version. Basically this central tendency estimator is just the average between the upper and lower extremities, it behave like the average of the highest/lowest over length period, its central plot in the Donchian channel indicator. Below is a comparison of both with length = 100 :
But why is our average so "boxy"? The extremities are not boxy, so why the average is sometimes equal to its previous value? Explain!
Its super easy to understand, imagine two lines, if their absolute change is the same and they follow an opposite direction, then their average is constant.
the average of the green and red line is the orange line. If both lines follow the same direction then their average will also follow this direction.
When both extremities follow the same direction, the average will also do the same, when both follow an opposite direction then the average will be equal to its precedent value, this is also due to the fact that both extremities are based on the same correction factor (a-b) , else the average wouldn't act that way, now you understand why i made this choice.
Conclusion
I proposed an efficient implementation of a channel indicator that provide an interesting central tendency estimator. This simple implementation would allow for tons of interesting concepts, some of my indicators use a similar approach and allow for great outputs, you'll see them soon enough. I hope this indicator find its use in the community, remember to ask before using this indicator in a script you want to publish.
Thanks for reading !
If you want to discuss about anime stuff send me a pm but don't do it in the commend section.
ค้นหาในสคริปต์สำหรับ "Trailing stop"
Peterbolic SARThe Peterbolic SAR indicator is based on Peter Brandt's 3 Day Trailing Stop Rule. The yellow triangles indicate setup candles, and the green and red triangles represent trigger candles to buy and sell, respectively.
Sawcruhteez asked me to create the code for this SAR. Gabriel Harber came up with the name for the SAR. Peter Brandt gave his permission to use his name.
For more information, see Sawcruhteez Streamz: Live Coaching Sessionz with Gabriel Harber - Trading Peterbolic SAR
and Peter Brandt's original description of the 3DTSR
4 JMA Crossover Strategy (ps4)This is a PS4 update to my previous 4 JMA strategy that received many likes. In this and several recent strategies I use a simplified strategy setup, featuring trailing stops with very tiny increments. This is done intentionally in order to boost performance to the limit, so that to pinpoint that limit. Strategies with performance of about 90% or above are regarded as viable. Incorporating various overhead factors such as transaction costs, broker's spread, slippage, etc. at this stage creates too much 'noise' with the end result of losing the sight of the forest behind the trees.)) In practice, I disable the 'Use Strategy Setup' option and fine-tune parameters the way I want.
Tested security: EURUSD . Tested TF: 3m
Scaled Normalized Vector Strategy, ver.4.1This modification of the Scaled Normalized Vector Strategy uses trailing stops and is optimized for lower TFs.
Kaufman Adaptive BandsIntroduction
Bands are quite efficient in technical analysis, they can provide support and resistance levels, provide breakouts points, trailing stop loss/take profits positions and can show the current market volatility to the user. Most of the time bands are made from a central tendency estimator like a moving average plus/minus a volatility indicator. Therefore bands can be made out of pretty much everything thus allowing for any kind of flavors.
So i propose a band indicator made from a Kaufman adaptive moving average using an estimate of the standard deviation.
Construction
The Kaufman moving average is an exponential averager using the efficiency ratio as smoothing variable, length control the period of kama and in order to provide more smoothness a power parameter has been introduced, higher values of power will return smoother results.
The volatility indicator is made from a biased estimation of the standard deviation by using the square root of the mean of the square minus the square of the mean method, except that we use kama instead of a mean.
The bands are made by adding/subtracting this volatility indicator with kama.
How To Use
The ability of the indicator to adapt to the current market state is what makes him a great tool for avoiding major exposition during ranging market, therefore the indicator will have a greater motion during trending market, or more simply the bands will move during trending markets while staying "flat" during ranging ones. Therefore the indicator might be more suited to breakouts, even if some cases will return what where turning points, this is particularly true during ranging markets.
Of course the efficiency ratio is not an "unbiased" trend metric indicator, it can consider high volatility markets as trending markets. Its one of his downsides.
High values of power will create smoother bands.
When using a low power parameter use an higher mult. In general using a low power value will make the bands move more freely as well as making them closer to each others.
Conclusion
At least the indicator is really nice to the eyes when using high power values, its ability to adapt to the market is a great addition to other more classical bands indicators, i also introduced a volatility estimator based on kama, some might have used the following estimation : kama(abs(price - kama)) which would have created a slower result. A trailing stop might be made from it if i see request about such addition.
If you are curious here are some more images of the indicator performing on different markets. Thanks for reading !
Renko Plot StrategyThis strategy lets you plot Renko open and close values, based on your preferred Renko size brick, on normal candle chart. You can use it on any timeframe, define your preferred brick size and trailing stop.
Modified Gann HiLo ActivatorIntroduction
The gann hilo activator is a trend indicator developed by Robert Krausz published into W. D. Gann Treasure Discovered: Simple Trading Plans for Stocks & Commodities . This indicator crate a trailing stop aiming to show the direction of the trend.
This indicator is fairly easy to compute and dont require lot of skills to understand. First we calculate the simple moving average of both price high and price low, when the close price is higher than the moving average of the price high the indicator return the moving average of the price low, else the indicator return the moving average of the price high if the close price is lower than the moving average of the price low.
My indicator add a different calculation method in order to avoid whipsaw trades as well as adding significance to the moving average length. A Median method has been added to provide more robustness.
The Indicator
The indicator is a simple trailing stop aiming to show the direction of the trend. The indicator use a different source instead of the price high/low for its calculation. The first method is the "SMA" method which like the classic hilo indicator use a simple moving average for the calculation of the indicator.
Sma Method with length = 25
The "Median" use a moving median instead of a simple moving average, this provide more robustness.
Median Method with length = 25
The shape is less curved and the indicator can sometimes avoid whipsaw with high's length periods.
Mult Parameter
The mult parameter is a parameter set to be lower or equal to 1 and greater or equal to 0. High values allow the indicator to be far from the price thus avoiding whipsaw trades, lower ones lower the distance from the price. A mult parameter of 0.1 approximate the original hilo indicator.
In blue the indicator with mult = 0.1 and in radical red the original hilo activator.
Conclusion
The modifications allow more control over the indicator as well as adding more robustness while the original one is destined to fail when market price is more complex.
Thanks for reading :)
For any questions/suggestions feel free to pm me
Fisher Transform Multi-Timeframe Backtest (No Trailing)This is the Backtester without Trailing Stops
Credits to mortdiggiddy
Chandelier Exit V2 by fr3762 KIVANÇChandelier Exit Version 2 with two lines Long Stop and Short Stop
There is a Chandelier exit for long positions and one for short positions. The Chandelier Exit (long) hangs three ATR values below the 22-period high. This means it rises and falls as the period high and the ATR value changes. The Chandelier Exit for short positions is placed three ATR values above the 22-period low. The spreadsheet examples show sample calculations for both.
According to the theory, traders should exit long positions at either the highest high since entry minus 3 ATRs .
Similarly traders should exit short positions at either the lowest low since entry plus 3 ATRs .
Developed by Charles Le Beau and featured in Alexander Elder's books, the Chandelier Exit sets a trailing stop-loss based on the Average True Range (ATR). The indicator is designed to keep traders in a trend and prevent an early exit as long as the trend extends. Typically, the Chandelier Exit will be above prices during a downtrend and below prices during an uptrend.
The author, Chuck LeBeau explains: It lets "... profits run in the direction of a trend while still offering some protection against any reversal in trend."
The exit stop is placed at a multiple of average true ranges from the highest high or highest close since the entry of the trade.
Chandelier Exit will rise instantly whenever new highs are reached. As the highs get higher the stop moves up but it never moves downward.
The Chandelier Exit is mostly used to set a trailing stop-loss during a trend. Trends sometimes extend further than we anticipate and the Chandelier Exit can help traders ride the trend a little longer. Even though it is mostly used for stop-losses, the Chandelier Exit can also be used as a trend tool. A break above the Chandelier Exit (long) signals strength, while a break below the Chandelier Exit (short) signals weakness. Once a new trend begins, chartists can then use the corresponding Chandelier Exit to help define this trend.
Developer: Charles Le Beau
Here's the link to a complete list of all my indicators:
tr.tradingview.com
Şimdiye kadar paylaştığım indikatörlerin tam listesi için: tr.tradingview.com
Chandelier Exit by fr3762 KIVANÇChandelier Exit
Developed by Charles Le Beau and featured in Alexander Elder's books, the Chandelier Exit sets a trailing stop-loss based on the Average True Range (ATR). The indicator is designed to keep traders in a trend and prevent an early exit as long as the trend extends. Typically, the Chandelier Exit will be above prices during a downtrend and below prices during an uptrend.
The author, Chuck LeBeau explains: It lets "... profits run in the direction of a trend while still offering some protection against any reversal in trend."
According to the theory, traders should exit long positions at either the highest high since entry minus 3 ATRs .
Similarly traders should exit short positions at either the lowest low since entry plus 3 ATRs .
The exit stop is placed at a multiple of average true ranges from the highest high or highest close since the entry of the trade.
Chandelier Exit will rise instantly whenever new highs are reached. As the highs get higher the stop moves up but it never moves downward.
The Chandelier Exit is mostly used to set a trailing stop-loss during a trend. Trends sometimes extend further than we anticipate and the Chandelier Exit can help traders ride the trend a little longer. Even though it is mostly used for stop-losses, the Chandelier Exit can also be used as a trend tool. A break above the Chandelier Exit (long) signals strength, while a break below the Chandelier Exit (short) signals weakness. Once a new trend begins, chartists can then use the corresponding Chandelier Exit to help define this trend.
Developer: Charles Le Beau
Average True Range Trailing Stops
Choices of Alerts supported (mainly for free members with only one alert):
Long crossover : to inform when a long position is available
Short crossover: to inform when a long position is available
Long/Short crossover : to inform when any position is available
DayLow - Chart the Moving Average of the DAILY LOW PriceThis is a moving average of the Daily LOW Price over a short period of time (i.e. 3 day low moving average, etc...) Great for tracking trailing stops for a stock on an up swing.
Moving Average Cross and/or Bbands botHello TradingView and world!
This is one of our latest concepts for an actual bot builder. This script comes with a bunch of features that we're hoping will alleviate a lot of the stress and confusion around using and building strategies here on TV. Especially if the end-goal is to automate the strategies using Autoview.
This is a combination of 2 strategies, and gives you full control of each component within the script.
The 2 strategies are:
2 Moving Averages == if close is greater than moving average and moving average 1 is greater than moving average 2
Bolling Bands == if close is less than lower or greater than upper
Features / Settings included :
- Ability to change settings from a commodity market (default) to an altcoin or forex market.
- Backtest time period selector component
- Heiken Ashi Candles on/off
- Moving Average Strategy on/off
- Bollinger Bands Strategy on/off
- Both Moving Average settings can be adjusted
- Bollinger Bands length and multiplier can be adjusted.
- Pyramiding Greater Than, Equal To, or Less Than
- Trailing Stop with the ability to set a price in which the Trailing Stop activate
- Take Profit on/off and editable
- Stop Loss on/off and editable
- Margin Call on/off dependent on Leverage which is editable
- If pyramiding is used, the strategy will calculate and display your average on the chart
- Profit and Loss visuals added to the chart
You can watch a video here on how all the settings can be used and work together.
www.youtube.com
You can learn more about Autoview here:
autoview.with.pink
Get your invite and join us in slack here:
slack.with.pink
Average True Range Reversed Strategy Average True Range Trailing Stops Strategy, by Sylvain Vervoort
The related article is copyrighted material from Stocks & Commodities Jun 2009
Please, use it only for learning or paper trading. Do not for real trading.
JC_MacD_RSI_Candle_Strat_public//
// Author : Jacques CRETINON
// Last Version : V1.0 11-22-2016
//
// Risk disclaimer : Do not use this script in production environment. We assume no liability or responsibility for any damage to you, your computer, or your other property, due to the use of this script.
//
// Purpose of this script :
// 1- use same pine code for strategy or study script (with simple modifications)
// 2- be able to send alerts : enterlong, entershort, exitlong, exitshort, stoplosslong, stoplossshort, takeprofitlong, takeprofitshort in a study script like a strategy script should do
// 3- do not repaint (I HOPE)
//
// RoadMap :
// 1- manage : Trailing Stop Loss and Trailing Stop Loss offset
//
// I use this script :
// 1- with default value for XAUUSD, current chart resolution : 1mn, large timeframe : 15mn.
// 2- That's why I hard code MACD5 (5mn average), MACD15 (15mn average), MACD60 (1h average) ...
// 3- MACD, RSI (1mn and 15mn) and Candles info are my inputs to take any decisions
//
// I do not publish my enterLong, enterShort, exitLong and exitShort conditions (lines 204 to 207 are sample !) as they are not as perfect as I'd like. Fell free to use your own conditions :)
//
// Please, report me any bug, fell free to discuss and share. English is not my natural language, so be clement ;) Happy safe trading :)
Strategy Code Example - Risk Management*** THIS IS JUST AN EXAMPLE OF STRATEGY RISK MANAGEMENT CODE IMPLEMENTATION ***
For my own future reference, and for anyone else who needs it.
Pine script strategy code can be confusing and awkward, so I finally sat down and had a little think about it and put something together that actually works (i think...)
Code is commented where I felt might be necessary (pretty much everything..) and covers:
Take Profit
Stop Loss
Trailing Stop
Trailing Stop Offset
...and details how to handle the input values for these in a way that allows them to be disabled if set to 0, without breaking the strategy.exit functionality or requiring a silly amount of statement nesting.
Also shows how to use functions (or variables/series) to execute trade entries and exits.
Cheers!
CapnsSurferThis is a simple RMA Trend that may help you decide for SL or TP. Similar to CapnsBands this uses Donchian Channels.. but remember. Your Trade Your Money
Howto Read Capns Surfer - I will write more later
First of all this is NOT a BUY or SELL indicator. However with this you can define sweet spots for ENTRIES, or TRAILING STOPS and recognize the trend.
Sweetspots
Ichimoku-Hausky Trading systemThis is a indicator with some parts of the ichimoku and EMA. It's my first script so i have used other peoples script (Chris Moody and DavidR) as reference cause I really have no idea myself on how to script with pinescript.
Hope that is okay!
I use 20M timeframe but it should work with any timeframe! I have not tested this system much so I would really appreciate feedback and tips for better entries, settings etc..
Tenken-sen: green line
Kijun-sen: blue line
EMA: Purple
Rules:
Buy:
IF price crosses or bounce above Kijun-sen
THEN see if market has closed above EMA
IF Market has closed above EMA
THEN see if EMA is above Kijun-sen
IF EMA is above Kijun-sen
THEN buy and set trailing stop 5 pips below EMA
Sell:
IF price crosses or bounce below Kijun-sen
THEN see if market has closed below EMA
IF Market has closed below EMA
THEN see if EMA is below Kijun-sen
IF EMA is below Kijun-sen
THEN sell and set trailing stop 5 pips above EMA
QQEThe Metastock version of Quantative Qualitative Estimation with two trailing stop lines and more options
Yellow line can be hidden if its too many signals and expirement with the Slow/Fast Trailing stop lines.
SuperTrend BFThe SuperTrend overlay by Olivier Seban provides an excellent 'trailing stop' that can be used with any bar length for bullish or bearish moves. My preferred timeframe is weekly for capturing huge (Super) moves. For instance applying it to AAPL, this baby would have us reeling in a fivebagger over the course of three years. Patience and holding your nerve are key to trend following and I like to think of SuperTrend as a great big visual 'crutch' right there on the chart.
Essentially this is an average true range trailing stop, of which there are several versions available (eg see the Sylvain Vervoort version programmed by H Potter). SuperTrend differs by referring the stop back from the middle of the bar (High+Low)/2. This is similar to using the Vervoort with a tweak to the number of ATR's considered. At the end of the day its a matter of preference and what works best for you.
MESA Adaptive Ehlers Flow | AlphaNattMESA Adaptive Ehlers Flow | AlphaNatt
An advanced adaptive indicator based on John Ehlers' MESA (Maximum Entropy Spectrum Analysis) algorithm that automatically adjusts to market cycles in real-time, providing superior trend identification with minimal lag across all market conditions.
🎯 What Makes This Indicator Revolutionary?
Unlike traditional moving averages with fixed parameters, this indicator uses Hilbert Transform mathematics to detect the dominant market cycle and adapts its responsiveness accordingly:
Automatically detects market cycles using advanced signal processing
MAMA (MESA Adaptive Moving Average) adapts from fast to slow based on cycle phase
FAMA (Following Adaptive Moving Average) provides confirmation signals
Dynamic volatility bands that expand and contract with cycle detection
Zero manual optimization required - the indicator tunes itself
📊 Core Components
1. MESA Adaptive Moving Average (MAMA)
The MAMA is the crown jewel of adaptive indicators. It uses the Hilbert Transform to measure the market's dominant cycle and adjusts its smoothing factor in real-time:
During trending phases: Responds quickly to capture moves
During choppy phases: Smooths heavily to filter noise
Transition is automatic and seamless based on price action
Parameters:
Fast Limit: Maximum responsiveness (default: 0.5) - how fast the indicator can adapt
Slow Limit: Minimum responsiveness (default: 0.05) - maximum smoothing during consolidation
2. Following Adaptive Moving Average (FAMA)
The FAMA is a slower version of MAMA that follows the primary signal. The relationship between MAMA and FAMA provides powerful trend confirmation:
MAMA > FAMA: Bullish trend in progress
MAMA < FAMA: Bearish trend in progress
Crossovers signal potential trend changes
3. Hilbert Transform Cycle Detection
The indicator employs sophisticated DSP (Digital Signal Processing) techniques:
Detects the dominant cycle period (1.5 to 50 bars)
Measures phase relationships in the price data
Calculates adaptive alpha values based on cycle dynamics
Continuously updates as market character changes
⚡ Key Features
Adaptive Alpha Calculation
The indicator's "intelligence" comes from its adaptive alpha:
Alpha dynamically adjusts between Fast Limit and Slow Limit based on the rate of phase change in the market cycle. Rapid phase changes trigger faster adaptation, while stable cycles maintain smoother response.
Dynamic Volatility Bands
Unlike static bands, these adapt to both ATR volatility AND the current cycle state:
Bands widen when the indicator detects fast adaptation (trending)
Bands narrow during slow adaptation (consolidation)
Band Multiplier controls overall width (default: 1.5)
Provides context-aware support and resistance
Intelligent Color Coding
Cyan: Bullish regime (MAMA > FAMA and price > MAMA)
Magenta: Bearish regime (MAMA < FAMA and price < MAMA)
Gray: Neutral/transitional state
📈 Trading Strategies
Trend Following Strategy
The MESA indicator excels at identifying and riding strong trends while automatically reducing sensitivity during choppy periods.
Entry Signals:
Long: MAMA crosses above FAMA with price closing above MAMA
Short: MAMA crosses below FAMA with price closing below MAMA
Exit/Management:
Exit longs when MAMA crosses below FAMA
Exit shorts when MAMA crosses above FAMA
Use dynamic bands as trailing stop references
Mean Reversion Strategy
When price extends beyond the dynamic bands during established trends, look for bounces back toward the MAMA line.
Setup Conditions:
Strong trend confirmed by MAMA/FAMA alignment
Price touches or exceeds outer band
Enter on first sign of reversal toward MAMA
Target: Return to MAMA line or opposite band
Cycle-Based Swing Trading
The indicator's cycle detection makes it ideal for swing trading:
Enter on MAMA/FAMA crossovers
Hold through the detected cycle period
Exit on counter-crossover or band extremes
Works exceptionally well on 4H to Daily timeframes
🔬 Technical Background
The Hilbert Transform
The Hilbert Transform is a mathematical operation used in signal processing to extract instantaneous phase and frequency information from a signal. In trading applications:
Separates trend from cycle components
Identifies the dominant market cycle without curve-fitting
Provides leading indicators of trend changes
MESA Algorithm Components
Smoothing: 4-bar weighted moving average for noise reduction
Detrending: Removes linear price trend to isolate cycles
InPhase & Quadrature: Orthogonal components for phase measurement
Homodyne Discriminator: Calculates instantaneous period
Adaptive Alpha: Converts period to smoothing factor
MAMA/FAMA: Final adaptive moving averages
⚙️ Optimization Guide
Fast Limit (0.1 - 0.9)
Higher values (0.5-0.9): More responsive, better for volatile markets and lower timeframes
Lower values (0.1-0.3): Smoother response, better for stable markets and higher timeframes
Default 0.5: Balanced for most applications
Slow Limit (0.01 - 0.1)
Higher values (0.05-0.1): Less smoothing during consolidation, more signals
Lower values (0.01-0.03): Heavy smoothing during chop, fewer but cleaner signals
Default 0.05: Good noise filtering while maintaining responsiveness
Band Multiplier (0.5 - 3.0)
Adjust based on instrument volatility
Backtest to find optimal value for your specific market
1.5 works well for most forex and equity indices
Consider higher values (2.0-2.5) for cryptocurrencies
🎨 Visual Interpretation
The gradient visualization shows probability zones around the MESA line:
MESA line: The adaptive trend center
Band expansion: Indicates strong cycle detection and trending
Band contraction: Indicates consolidation or ranging market
Color intensity: Shows confidence in trend direction
💡 Best Practices
Let it adapt: Give the indicator 50+ bars to properly calibrate to the market
Combine timeframes: Use higher timeframe MESA for trend bias, lower for entries
Respect the bands: Price rarely stays outside bands for extended periods
Watch for compression: Narrow bands often precede explosive moves
Volume confirmation: Combine with volume for higher probability setups
📊 Optimal Timeframes
15m - 1H: Day trading with Fast Limit 0.6-0.8
4H - Daily: Swing trading with Fast Limit 0.4-0.6 (recommended)
Weekly: Position trading with Fast Limit 0.2-0.4
⚠️ Important Considerations
The indicator needs time to "learn" the market - avoid trading the first 50 bars after applying
Extreme gap events can temporarily disrupt cycle calculations
Works best in markets with detectable cyclical behavior
Less effective during news events or extreme volatility spikes
Consider the detected cycle period for position holding times
🔍 What Makes MESA Superior?
Compared to traditional indicators:
vs. Fixed MAs: Automatically adjusts to market conditions instead of using one-size-fits-all parameters
vs. Other Adaptive MAs: Uses true DSP mathematics rather than simple volatility adjustments
vs. Manual Optimization: Continuously re-optimizes itself in real-time
vs. Lagging Indicators: Hilbert Transform provides earlier trend change detection
🎓 Understanding Adaptation
The magic of MESA is that it solves the eternal dilemma of technical analysis: be fast and get whipsawed in chop, or be smooth and miss the early move. MESA does both by detecting when to be fast and when to be smooth.
Adaptation in Action:
Strong trend starts → MESA quickly detects phase change → Fast Limit kicks in → Early entry
Trend continues → Phase stabilizes → MESA maintains moderate speed → Smooth ride
Consolidation begins → Phase changes slow → Slow Limit engages → Whipsaw avoidance
🚀 Advanced Applications
Multi-timeframe confluence: Use MESA on 3 timeframes for high-probability setups
Divergence detection: Watch for MAMA/price divergences at band extremes
Cycle period analysis: The internal period calculation can guide position duration
Band squeeze trading: Narrow bands + MAMA/FAMA cross = high-probability breakout
Created by AlphaNatt - Based on John Ehlers' MESA research. For educational purposes. Always practice proper risk management. Not financial advice. Always DYOR.
Arnaud Legoux Gaussian Flow | AlphaNattArnaud Legoux Gaussian Flow | AlphaNatt
A sophisticated trend-following and mean-reversion indicator that combines the power of the Arnaud Legoux Moving Average (ALMA) with advanced Gaussian distribution analysis to identify high-probability trading opportunities.
🎯 What Makes This Indicator Unique?
This indicator goes beyond traditional moving averages by incorporating Gaussian mathematics at multiple levels:
ALMA uses Gaussian distribution for superior price smoothing with minimal lag
Dynamic envelopes based on Gaussian probability zones
Multi-layer gradient visualization showing probability density
Adaptive envelope modes that respond to market conditions
📊 Core Components
1. Arnaud Legoux Moving Average (ALMA)
The ALMA is a highly responsive moving average that uses Gaussian distribution to weight price data. Unlike simple moving averages, ALMA can be fine-tuned to balance responsiveness and smoothness through three key parameters:
ALMA Period: Controls the lookback window (default: 21)
Gaussian Offset: Shifts the Gaussian curve to adjust lag vs. responsiveness (default: 0.85)
Gaussian Sigma: Controls the width of the Gaussian distribution (default: 6.0)
2. Gaussian Envelope System
The indicator features three envelope calculation modes:
Fixed Mode: Uses ATR-based fixed width for consistent envelope sizing
Adaptive Mode: Dynamically adjusts based on price acceleration and volatility
Hybrid Mode: Combines ATR and standard deviation for balanced adaptation
The envelopes represent statistical probability zones. Price moving beyond these zones suggests potential mean reversion opportunities.
3. Momentum-Adjusted Envelopes
The envelope width automatically expands during strong trends and contracts during consolidation, providing context-aware support and resistance levels.
⚡ Key Features
Multi-Layer Gradient Visualization
The indicator displays 10 gradient layers between the ALMA and envelope boundaries, creating a visual "heat map" of probability density. This helps traders quickly assess:
Distance from the mean
Potential support/resistance strength
Overbought/oversold conditions in context
Dynamic Color Coding
Cyan gradient: Price below ALMA (bullish zone)
Magenta gradient: Price above ALMA (bearish zone)
The ALMA line itself changes color based on price position
Trend Regime Detection
The indicator automatically identifies market regimes:
Strong Uptrend: Trend strength > 0.5% with price above ALMA
Strong Downtrend: Trend strength < -0.5% with price below ALMA
Weak trends and ranging conditions
📈 Trading Strategies
Mean Reversion Strategy
Look for price entering the extreme Gaussian zones (beyond 95% of envelope width) when trend strength is moderate. These represent statistical extremes where mean reversion is probable.
Signals:
Long: Price in lower Gaussian zone with trend strength > -0.5%
Short: Price in upper Gaussian zone with trend strength < 0.5%
Trend Continuation Strategy
Enter when price crosses the ALMA during confirmed strong trend conditions, riding momentum while using the envelope as a trailing stop reference.
Signals:
Long: Price crosses above ALMA during strong uptrend
Short: Price crosses below ALMA during strong downtrend
🎨 Visualization Guide
The gradient layers create a "probability cloud" around the ALMA:
Darker shades (near ALMA): High probability zone - price tends to stay here
Lighter shades (near envelope edges): Lower probability - potential reversal zones
Price at envelope extremes: Statistical outliers - strongest mean reversion setups
⚙️ Customization Options
ALMA Parameters
Adjust period for different timeframes (lower for day trading, higher for swing trading)
Modify offset to tune responsiveness vs. smoothness
Change sigma to control distribution width
Envelope Configuration
Choose envelope mode based on market characteristics
Adjust multiplier to match instrument volatility
Modify gradient depth for visual preference (5-15 layers)
Signal Enhancement
Momentum Length: Lookback for trend strength calculation
Signal Smoothing: Additional EMA smoothing to reduce noise
🔔 Built-in Alerts
The indicator includes six pre-configured alert conditions:
ALMA Trend Long - Price crosses above ALMA in strong uptrend
ALMA Trend Short - Price crosses below ALMA in strong downtrend
Mean Reversion Long - Price enters lower Gaussian zone
Mean Reversion Short - Price enters upper Gaussian zone
Strong Uptrend Detected - Momentum confirms strong bullish regime
Strong Downtrend Detected - Momentum confirms strong bearish regime
💡 Best Practices
Use on clean, liquid markets with consistent volatility
Combine with volume analysis for confirmation
Adjust envelope multiplier based on backtesting for your specific instrument
Higher timeframes (4H+) generally provide more reliable signals
Use adaptive mode for trending markets, hybrid for mixed conditions
⚠️ Important Notes
This indicator works best in markets with normal price distribution
Extreme news events can invalidate Gaussian assumptions temporarily
Always use proper risk management - no indicator is perfect
Backtest parameters on your specific instrument and timeframe
🔬 Technical Background
The Arnaud Legoux Moving Average was developed to solve the classic dilemma of moving averages: the trade-off between lag and noise. By applying Gaussian distribution weighting, ALMA achieves superior smoothing while maintaining responsiveness to price changes.
The envelope system extends this concept by creating probability zones based on volatility and momentum, effectively mapping where price is "likely" vs "unlikely" to be found based on statistical principles.
Created by AlphaNatt - For educational purposes. Always practice proper risk management. Not financial advice. Always DYOR.
