RSI Median DeviationRSI Median Deviation – Adaptive Statistical RSI for High-Probability Extremes
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder in 1978 to measure the magnitude of recent price changes and identify potential overbought or oversold conditions. It calculates the ratio of upward to downward price movements over a specified period, scaled to 0-100. However, standard RSI often relies on fixed thresholds like 70/30, which can produce unreliable signals in varying market regimes due to their lack of adaptability to the actual distribution of RSI values.
This indicator was developed because I needed a reliable tool for spotting intermediate high-probability bottoms and tops. Instead of arbitrary horizontal lines, it uses the RSI’s own historical median as a dynamic centerline and measures how far the current RSI deviates from that median over a chosen lookback period. The main signals are triggered only at 2 standard deviation (2σ) extremes — statistically rare events that occur roughly 5 % of the time under a normal distribution. I selected 2σ because it is extreme enough to be meaningful yet frequent enough for practical trading. For oversold signals I further require RSI to be below 42, a filter that significantly improved results in my mean-reversion tests (enter on oversold, exit on the first bar the condition is no longer true).
The combination of percentile median + standard deviation bands is deliberate: the median is far more robust to outliers than a simple average, while the SD bands automatically adjust to the current volatility of the RSI itself, producing adaptive envelopes that work equally well in ranging and trending markets.
Underlying Concepts and Calculations
Base RSI: RSI = 100 − (100 / (1 + RS)), RS = average gain / average loss (default length 10).
Percentile Median: 50th percentile of the last "N" RSI values (default 28 = 4 weeks)
→ dynamic, outlier-resistant centerline.
Standard Deviation Bands: rolling stdev of RSI (default length 27 = = 4 weeks (almost))
→ bands = median ± 1σ / 2σ.
Optional Dynamic MA Envelopes: user-selectable moving average (TEMA, WMA, etc., default WMA length 37) for additional momentum context.
Trend Bias Coloring
Independent of the statistical extremes, the RSI line itself is colored green when above the user-defined Long Threshold (default 60) and red when below the Short Threshold (default 47). This provides an instant bullish/bearish bias overlay similar to classic RSI usage, without interfering with the main 2σ extreme signals.
Extremes are highlighted with background color (green for oversold 2σ + RSI<42, magenta for overbought 2σ) and small diamond markers for ultra-extremes (RSI <25 or >85).
Originality and Development Rationale
The indicator was built and refined through extensive testing on dozens of assets including major cryptocurrencies:
(BTC, ETH, SOL, SUI, BNB, XRP, TRX, DOGE, LINK, PAXG, CVX, HYPE, VIRTUAL and many more),
the Magnificent 7 stocks,, QQQ, SPX, and gold.
Default parameters were chosen to deliver consistent profitability in simple mean-reversion setups while maximizing Sortino ratio and minimizing maximum drawdown across this broad universe — ensuring the settings are robust and not overfitted to any single instrument or timeframe.
How to Use It
Ideal for swing / position trading on the 1h to daily charts (the same defaults work).
Oversold (high-probability long): RSI crosses below lower 2σ band AND RSI < 42
→ green background
→ enter long, exit the first bar the condition disappears.
Overbought (high-probability short): RSI crosses above upper 2σ band
→ magenta background
→ enter short, exit on opposite signal or at median. (Shorts were not tested, it's only an idea)
Use the green/red RSI line coloring for quick trend context and to avoid fighting strong momentum.
Always confirm with price action and manage risk appropriately.
This indicator is not a standalone trading system.
Disclaimer: This is not financial advice. Backtests are based on past results and are not indicative of future performance.
Oscillators
Rahul Prakash's BUY/SELL signal for momentum tradeBuy or Sell signal with just on one confirmation candle.
Show a Buy singal then wait for the confirmation candle, is a strong Buy signal.
Show a Sell singal then wait for the confirmation candle, is a strong Sell signal.
You can use as a free version and earn money. Please are taking lots of price for this type of indicator.
VCAI Stochastic RSI+VCAI Stoch RSI+ is a cleaned-up Stochastic RSI built with V-Core colours for faster, clearer momentum reads and more reliable OB/OS signals.
What it shows:
Purple %K line → bearish momentum strengthening
Yellow %D line → bullish momentum building and smoothing
Soft purple/yellow background bands → OB/OS exhaustion zones, not just raw 80/20 triggers
Midline at 50 → balance point where momentum shifts between bull- and bear-side control
Optional HTF mode → run Stoch RSI from any timeframe while viewing it on your current chart
How to read it:
Both lines rising out of OS → early bullish shift; pullbacks that hold direction favour continuation
Both lines falling from OB → early bearish shift; bounces into the purple OB zone can become fade setups
Lines stacked and moving together → strong, cleaner momentum
Lines crossing repeatedly → low-conviction, choppy conditions
OB/OS shading highlights exhaustion so you focus on moves with context, not every 80/20 tick
Why it’s different:
Classic Stoch RSI is hyper-sensitive and mostly noise.
VCAI Stoch RSI+ applies V-Core’s colour-driven regime logic, controlled OB/OS shading, and optional HTF smoothing so you see momentum structure instead of clutter — making it easier to judge when momentum is genuinely shifting and when it’s just another wiggle.
VCAI RSI Divergence +VCAI RSI Divergence+ is an RSI that shows trend, momentum, and divergence using V-CoresAI colour logic instead of a single white line.
What it shows:
Yellow RSI line → bullish momentum (RSI above its MA; buy-side pressure in control)
Purple RSI line → bearish momentum (RSI below its MA; sell-side pressure in control)
Thin blue line → fast RSI moving average that drives the colour flips
Dashed 70/30 lines → classic OB/OS zones
Background bands → soft purple in OB, soft yellow in OS to mark exhaustion areas
How to read it:
Yellow & rising → momentum shifting bullish; pullbacks into yellow OS band can be accumulation zones
Purple & falling → momentum shifting bearish; pushes into purple OB band can be distribution/sell zones
Hard colour flips (yellow ↔ purple) mark trend regime changes, not minor RSI noise
Divergence mode (on/off)
The divergence engine scans RSI and price pivot structure:
Bullish divergence (yellow) → price lower low + RSI higher low
Bearish divergence (purple) → price higher high + RSI lower high
Lines and tags appear only where a meaningful disagreement between price and RSI exists, giving early context for potential reversals or fade setups.
Together, the momentum colours + optional divergence mapping give a far clearer market read than a standard RSI, with zero clutter and no guesswork.
Estrategia Visual PRO: Momentum EditionIndicador con estrategia propia basado en cruce de emas editables son sombreado de tendencia del precio y niveles de soporte y resistencias donde el precio tiene reaccion, tambien cuenta con filtro de rsi donde colorea las velas segun la fuerza del rsi, colores editables y cuando el precio pierde fuerza
This indicator, with its own strategy based on editable EMA crossovers, features price trend shading and support and resistance levels where the price reacts. It also includes an RSI filter that colors the candles according to the strength of the RSI, with editable colors, and alerts you when the price loses strength.
Alloyz Traders_RSI by Sagar BRSI for Intraday purpose with moving average and volume weightage price added in RSI.
RSI Pivot Breaks█ OVERVIEW
RSI Pivot Breaks is an RSI-based indicator that detects breakout events on oscillator-based pivot levels (RSI or MA RSI).
The tool automatically plots pivot levels, tracks their breakouts, highlights momentum shifts, and generates alerts for key events (pivot breaks and OB/OS crosses).
The indicator is designed primarily for momentum strategies — pivot breakouts often precede directional price moves, making RSI Pivot Breaks a powerful tool for identifying accelerations and changes in strength.
█ CONCEPTS
The indicator analyzes local RSI extremes and transforms them into dynamic support/resistance levels.
When RSI or MA RSI breaks the last pivot, it signals a shift in momentum balance, often leading to an impulse move.
Key concepts:
- pivot highs/lows detected on RSI or MA RSI,
- pivot lines extend forward until broken,
- pivot filters restrict pivot detection to specific RSI zones,
- OB/OS levels provide contextual momentum thresholds.
█ FEATURES
Pivot Detection & Breakouts
- Detection of pivot highs and lows on RSI or MA RSI.
- Pivot filters allow you to limit pivot detection to specific RSI ranges (e.g., only bullish pivots below 50 or bearish pivots above 50).
- Pivot lines update automatically after breakout.
Background highlights:
- green on pivot-high breakouts,
- red on pivot-low breakouts.
RSI & MA RSI
- Dynamic RSI colors based on momentum direction.
- Optional MA RSI line (SMA/EMA/RMA/WMA) usable as a smoother pivot source.
OB / OS Zones
- Fully adjustable overbought/oversold levels.
- Dedicated OB/OS colors.
- Optional gradient backgrounds.
Highlights
- Instant identification of moments when RSI breaks a key pivot level.
Alerts:
- pivot high breakouts.
- pivot low breakouts.
- OB crosses.
- OS crosses.
█ HOW TO USE
Add the indicator:
Indicators → RSI Pivot Breaks.
RSI Settings
- RSI Length – core RSI period.
- RSI MA Length & Type – MA RSI smoothing parameters.
Pivot Settings
- Pivot Left / Pivot Right – number of bars required to form a pivot and also the number of bars of delay before the pivot becomes confirmed.
(Higher values produce more reliable but slower pivots.)
Pivot Filters
- Minimum/maximum allowed RSI levels for pivot Highs and Lows.
- Examples:
- detect only pivot Highs at low RSI values.
- ignore pivots during extreme momentum.
- allow only mid-range pivot detection depending on strategy.
Visualization
- Toggles for RSI and MA RSI visibility.
- Optional gradients.
- Full color and transparency customization.
OB/OS Levels
- Adjustable thresholds depending on instrument volatility and strategy style.
█ SIGNAL INTERPRETATION
BUY
- RSI breaks the latest pivot high.
- RSI crosses upward out of OS.
- Context example: pivot lows forming a rising sequence.
SELL
- RSI breaks the latest pivot low.
- RSI drops downward from OB.
- Context example: pivot highs forming a declining sequence.
Trend / Momentum
- Pivot breakouts indicate acceleration or continuation of momentum.
- MA-based pivots provide smoother and more stable momentum structure.
█ APPLICATIONS
- Momentum Trading – pivot breaks as early acceleration signals.
- Scalping & Intraday – fast RSI pivots react quickly to short-term shifts.
- Swing Trading – smoother pivots using MA RSI for higher-timeframe structure.
- Divergence Detection – pivot behavior helps reveal divergence patterns, e.g.:
- RSI pivots rising while price is falling → potential early momentum reversal.
- Custom Filtering – pivot filters allow, for example:
- blocking bullish signals near OB.
- blocking bearish signals near OS.
- detecting pivots only above/below mid-range during strong trends,
depending entirely on strategy design.
█ NOTES
- Pivot detection includes natural delay equal to the Left/Right parameters.
- Pivot filters significantly change the character of signals, allowing fine-tuning of aggressiveness for any strategy.
VCAI MACD LiteVCAI MACD Lite is a clean, modern version of the classic MACD oscillator, rebuilt with selectable EMA/SMA types and a 2-tone histogram using VCAI’s visual style.
It keeps the indicator lightweight and easy to read while giving clearer momentum shifts through rising/falling histogram colour changes.
What it does
Calculates MACD using your choice of EMA or SMA
Plots signal line and histogram with 2-tone VCAI colours
Highlights changes in momentum strength as histogram bars rise or fade
Works on any market and timeframe
How to use it
Expanding yellow bars reflect strengthening upside momentum; dim yellow shows fading strength.
Darker and lighter VCAI purple tones show momentum behaviour below zero, helping you see when bearish pressure is increasing or weakening.
Part of the VCAI Lite Series — clean, minimal tools.
RSI Multi Levels kiawosch [TradingFinder] 7-14-42 Consolidation🔵 Introduction
The Relative Strength Index or RSI is a tool used to measure the speed and intensity of price movement, oscillating between zero and one hundred. It is commonly applied to identify strength or weakness in market momentum across different time intervals. Despite its simple formula and wide usage, the behavior of RSI within specific ranges often provides more precise information than traditional overbought and oversold levels.
The Multi RSI layout displays three RSI values with periods 7, 14 and 42. The seven period RSI plays the primary role in short term analysis. When this value enters predefined ranges, it shows highly consistent and interpretable behavior that can signal trend continuation, corrections or the start of a range structure. The other two values, RSI 14 and RSI 42, help reveal higher timeframe momentum and provide context for the depth and quality of price movement.
Three potential zones are defined, each representing a behavioral range. The position zones forms the basis for signal interpretation :
High Potential : 78 to 85 & 22 to 15
Mid Potential : 70 to 78 & 30 to 22
Low Potential : 58 to 62 & 42 to 38
These zones highlight areas where RSI reacts in specific ways to price movement. Entering the High Potential range usually aligns with new highs or lows in price and often precedes continuation after a correction. In contrast, reactions inside the Mid Potential range frequently appear during clean ranges or channel structures. This approach focuses on momentum quality and structural behavior rather than classic overbought and oversold thresholds.
In summary, the logic behind the signals follows three principles :
Trend continuation, When RSI 7 enters the High Potential zone and price prints a new high or low, continuation after a correction becomes the most likely outcome.
Reversal or slowdown, When RSI exits the High Potential zone while price is reaching a previous high or low, the probability of a short term reversal increases.
Range behavior, In clean ranges or channel structures, RSI 7 typically reacts inside the Mid Potential zone and produces consistent swing responses.
🔵 How to Use
This method is based on observing the repeating behavior of RSI within momentum zones and identifying moments when price continues after a shallow correction or, conversely, when signs of slowing and reversal appear. RSI 7 plays the main role since it gives the most sensitive response to short term price changes. Its entry into or exit from a potential zone, combined with the position of price relative to recent highs and lows, forms the core of the signal logic. RSI 14 and RSI 42 provide higher timeframe confirmation and help evaluate the broader strength or weakness behind each movement.
🟣 Trend continuation after entering the High Potential zone
When RSI 7 reaches the High Potential zone while price forms a new high or low, the probability of continuation becomes very high. The typical sequence includes a short correction in price and a retreat of RSI toward the Mid Potential zone. As long as price structure remains intact and RSI turns upward again, continuation becomes the most likely scenario. As shown in the charts, price often expands strongly after this type of correction and breaks the previous high.
🟣 Reversal or slowdown after exiting the High Potential zone
If RSI 7 enters the High Potential zone but then exits while price is interacting with a previous high or low, conditions for a short term reversal appear. This behavior is clear in the charts, where price hits a supply or demand area and RSI can no longer return to the upper zone. The drop in RSI reflects weakening momentum and, when accompanied by a confirming candle, increases the chance of a reversal or at least a temporary pause.
🟣 Strong reversal after hitting the Mid Potential zone during deeper corrections
Sometimes price enters a deeper corrective phase and RSI 7 moves into or through the Mid Potential zone. When this occurs near a previous low, it can mark the start of a significant reversal. The charts show this pattern clearly, where RSI turns upward while price reacts to support. If the other RSI values show relative alignment, the probability of a strong rebound increases. This signal is often seen after fast declines and can mark the beginning of a recovery wave.
🟣 Range structure and repetitive reactions inside the Mid Potential zone
When price enters a clean range or channel, the behavior of RSI 7 changes completely. In such conditions, RSI repeatedly reacts inside the Mid Potential zone. Each time price touches the upper or lower boundary of the range, RSI approaches the upper or lower part of this zone as well. The result is a sequence of predictable swing reactions, perfectly suitable for mean reversion strategies. Breakouts in these environments also tend to show higher failure rates.
🟣 Sharp reactions and fast reversals at extreme levels (RSI near 90 or below 10)
Although this approach is not based on classic overbought and oversold logic, extremely high or low RSI readings such as ninety often produce strong immediate reactions in price. These conditions usually occur after sudden spikes or emotional breakouts. As visible in the charts, RSI collapses quickly after reaching such extremes and price often reverses sharply. While not a core signal, these moments add meaningful context to momentum interpretation.
🔵 Settings
RSI Setting : This section allows enabling or disabling the three RSI values, adjusting their calculation length and customizing their colors. It is designed to help separate short, medium and longer term momentum visually on the chart.
Zones Setting : This section controls the display of momentum zones and the color applied to each area. Adjusting these colors or toggling them on and off helps the trader visually track the intensity and structure of momentum.
Levels Setting : This section allows editing the numeric boundaries of the levels or showing and hiding each one individually. These levels form the visual framework for interpreting RSI behavior within the defined momentum zones.
🔵 Conclusion
Examining RSI behavior across different momentum zones shows that entering these ranges creates relatively consistent patterns in price movement. Reaching the High Potential zone often corresponds to later stages of a trend, where price has the strength to continue after a brief correction and structure remains intact. In contrast, reactions within the Mid Potential zone occur more frequently when the market transitions into a range or a limited movement phase, where repetitive oscillations dominate.
Overall, observing RSI inside these zones helps distinguish between trending movement, corrective phases and range conditions with greater clarity. Entry or exit from each zone provides insight into the underlying strength or weakness of momentum and reveals where the market is positioned within its movement cycle. This perspective, based on momentum regions rather than traditional values alone, offers a more refined understanding of price behavior and highlights the likely direction of the next move.
macd rsi tunTitle:
Quantum Flow - Clean Momentum & Pattern Signals
Description:
A minimalist trend signal indicator designed purely for practical trading.
How it works:
Core Logic: Combines Momentum crossovers with Engulfing Candle patterns to identify potential reversals.
Clean Display: No messy lines. It only displays simple text signals ("多" for Long, "空" for Short) at key pivot points.
Filtering: Includes an optional RSI filter to improve signal probability and reduce noise.
Extras: Supports Bar Coloring and fully functional Alerts.
Designed specifically for traders who prefer a clean, uncluttered chart.
Note: This is not financial advice. Please test thoroughly in a demo account before live use.
TDI Fibonacci Volatility Bands Candle Coloring [cryptalent]"This is an advanced Traders Dynamic Index (TDI) candle coloring system, designed for traders seeking precise dynamic analysis. Unlike traditional TDI, which typically relies on a 50 midline with a single standard deviation band (±1 SD), this indicator innovatively incorporates Fibonacci golden ratio multiples (1.618, 2.618, 3.618 times standard deviation) to create multi-layered dynamic bands. It precisely divides the RSI fast line (green line) position into five distinct strength zones, instantly reflecting them on the candle colors, allowing you to grasp market sentiment in real-time without switching to a sub-chart.
Core Calculation Logic:
RSI Period (default 20), Band Length (default 50), and Fast MA Smoothing Period (default 1) are all adjustable.
The midline is the Simple Moving Average (SMA) of RSI, with upper and lower bands calculated by multiplying Fibonacci multiples with Standard Deviation (STDEV), generating three dynamic band sets: 1.618, 2.618, and 3.618.
Traders can quickly identify the following scenarios:
Extreme Overbought Zone (Strong Bullish, Red): Fast line exceeds custom threshold (default 82) and breaks above the specified band (default 2.618). This often signals overheating, potentially a profit-taking point or reversal short entry, especially at trend tops.
Extreme Oversold Zone (Strong Bearish, Green): Fast line drops below custom threshold (default 28) and breaks below the specified band (default 2.618). This is a potential strong rebound starting point, ideal for bottom-fishing or long entries.
Medium Bullish Zone (Yellow): Fast line surpasses medium threshold (default 66) and stands above the specified band (default 1.618), indicating bullish dominance in trend continuation.
Medium Bearish Zone (Orange): Fast line falls below medium threshold (default 33) and breaks below the specified band (default 1.618), signaling bearish control in segment transitions.
Neutral Zone (No Color Change): Fast line within custom upper and lower limits (default 34~65), retaining original candle colors to avoid noise interference during consolidation.
Color priority logic flows from strong to weak (Extreme > Medium > Neutral), ensuring no conflicts. All parameters are highly customizable, including thresholds, band selections (1.618/2.618/3.618/Midline/None), color schemes, and even optional semi-transparent background coloring (default off, transparency 90%) for enhanced visual layering.
Applicable Scenarios:
Intraday Trading: Capture extreme color shifts as entry/exit signals.
Swing Trading: Use medium colors to confirm trend extensions.
Long-Term Trend Following: Filter noise in neutral zones to focus on major trends.
Supports various markets like forex, stocks, and cryptocurrencies. After installation, adjust parameters in settings to match your strategy, and combine with other indicators like moving averages or support/resistance for improved accuracy.
If you're a TDI enthusiast, this will make your trading more intuitive and efficient!
Open Interest Z-Score [BackQuant]Open Interest Z-Score
A standardized pressure gauge for futures positioning that turns multi venue open interest into a Z score, so you can see how extreme current positioning is relative to its own history and where leverage is stretched, decompressing, or quietly re loading.
What this is
This indicator builds a single synthetic open interest series by aggregating futures OI across major derivatives venues, then standardises that aggregated OI into a rolling Z score. Instead of looking at raw OI or a simple change, you get a normalized signal that says "how many standard deviations away from normal is positioning right now", with optional smoothing, reference bands, and divergence detection against price.
You can render the Z score in several plotting modes:
Line for a clean, classic oscillator.
Colored line that encodes both sign and momentum of OI Z.
Oscillator histogram that makes impulses and compressions obvious.
The script also includes:
Aggregated open interest across Binance, Bybit, OKX, Bitget, Kraken, HTX, and Deribit, using multiple contract suffixes where applicable.
Choice of OI units, either coin based or converted to USD notional.
Standard deviation reference lines and adaptive extreme bands.
A flexible smoothing layer with multiple moving average types.
Automatic detection of regular and hidden divergences between price and OI Z.
Alerts for zero line and ±2 sigma crosses.
Aggregated open interest source
At the core is the same multi venue OI aggregation engine as in the OI RSI tool, adapted from NoveltyTrade's work and extended for this use case. The indicator:
Anchors on the current chart symbol and its base currency.
Loops over a set of exchanges, gated by user toggles:
Binance.
Bybit.
OKX.
Bitget.
Kraken.
HTX.
Deribit.
For each exchange, loops over several contract suffixes such as USDT.P, USD.P, USDC.P, USD.PM to cover the common perp and margin styles.
Requests OI candles for each exchange plus suffix pair into a small custom OI type that carries open, high, low and close of open interest.
Converts each OI stream into a common unit via the sw method:
In COIN mode, OI is normalized relative to the coin.
In USD mode, OI is scaled by price to approximate notional.
Exchange specific scaling factors are applied where needed to match contract multipliers.
Accumulates all valid OI candles into a single combined OI "candle" by summing open, high, low and close across venues.
The result is oiClose , a synthetic close for aggregated OI that represents cross venue positioning. If there is no valid OI data for the symbol after this process, the script throws a clear runtime error so you know the market is unsupported rather than quietly plotting nonsense.
How the Z score is computed
Once the aggregated OI close is available, the indicator computes a rolling Z score over a configurable lookback:
Define subject as the aggregated OI close.
Compute a rolling mean of this subject with EMA over Z Score Lookback Period .
Compute a rolling standard deviation over the same length.
Subtract the mean from the current OI and divide by the standard deviation.
This gives a raw Z score:
oi_z_raw = (subject − mean) ÷ stdDev .
Instead of plotting this raw value directly, the script passes it through a smoothing layer:
You pick a Smoothing Type and Smoothing Period .
Choices include SMA, HMA, EMA, WMA, DEMA, RMA, linear regression, ALMA, TEMA, and T3.
The helper ma function applies the chosen smoother to the raw Z score.
The result is oi_z , a smoothed Z score of aggregated open interest. A separate EMA with EMA Period is then applied on oi_z to create a signal line ma that can be used for crossovers and trend reads.
Plotting modes
The Plotting Type input controls how this Z score is rendered:
1) Line
In line mode:
The smoothed OI Z score is plotted as a single line using Base Line Color .
The EMA overlay is optionally plotted if Show EMA is enabled.
This is the cleanest view when you want to treat OI Z like a standard oscillator, watching for zero line crosses, swings, and divergences.
2) Colored Line
Colored line mode adds conditional color logic to the Z score:
If the Z score is above zero and rising, it is bright green, representing positive and strengthening positioning pressure.
If the Z score is above zero and falling, it shifts to a cooler cyan, representing positive but weakening pressure.
If the Z score is below zero and falling, it is bright red, representing negative and strengthening pressure (growing net de risking or shorting).
If the Z score is below zero and rising, it is dark red, representing negative but recovering pressure.
This mapping makes it easy to see not only whether OI is above or below its historical mean, but also whether that deviation is intensifying or fading.
3) Oscillator
Oscillator mode turns the Z score into a histogram:
The smoothed Z score is plotted as vertical columns around zero.
Column colors use the same conditional palette as colored line mode, based on sign and change direction.
The histogram base is zero, so bars extend up into positive Z and down into negative Z.
Oscillator mode is useful when you care about impulses in positioning, for example sharp jumps into positive Z that coincide with fast builds in leverage, or deep spikes into negative Z that show aggressive flushes.
4) None
If you only want reference lines, extreme bands, divergences, or alerts without the base oscillator, you can set plotting to None and keep the rest of the tooling active.
The EMA overlay respects plotting mode and only appears when a visible Z score line or histogram is present.
Reference lines and standard deviation levels
The Select Reference Lines input offers two styles:
Standard Deviation Levels
Plots small markers at zero.
Draws thin horizontal lines at +1, +2, −1 and −2 Z.
Acts like a classic Z score ladder, zero as mean, ±1 as normal band, ±2 as outer band.
This mode is ideal if you want a textbook statistical framing, using ±1 and ±2 sigma as standard levels for "normal" versus "extended" positioning.
Extreme Bands
Extreme bands build on the same ±1 and ±2 lines, then add:
Upper outer band between +3 and +4 Z.
Lower outer band between −3 and −4 Z.
Dynamic fill colors inside these bands:
If the Z score is positive, the upper band fill turns red with an alpha that scales with the magnitude of |Z|, capped at a chosen max strength. Stronger deviations towards +4 produce more opaque red fills.
If the Z score is negative, the lower band fill turns green with the same adaptive alpha logic, highlighting deep negative deviations.
Opposite side bands remain a faint neutral white when not in use, so they still provide structural context without shouting.
This creates a visual "danger zone" for position crowding. When the Z score enters these outer bands, open interest is many standard deviations away from its mean and you are dealing with rare but highly loaded positioning states.
Z score as a positioning pressure gauge
Because this is a Z score of aggregated open interest, it measures how unusual current positioning is relative to its own recent history, not just whether OI is rising or falling:
Z near zero means total OI is roughly in line with normal conditions for your lookback window.
Positive Z means OI is above its recent mean. The further above zero, the more "crowded" or extended positioning is.
Negative Z means OI is below its recent mean. Deep negatives often mark post flush environments where leverage has been cleared and the market is under positioned.
The smoothing options help control how much noise you want in the signal:
Short Z score lookback and short smoothing will react quickly, suited for short term traders watching intraday positioning shocks.
Longer Z score lookback with smoother MA types (EMA, RMA, T3) give a slower, more structural view of where the crowd sits over days to weeks.
Divergences between price and OI Z
The indicator includes automatic divergence detection on the Z score versus price, using pivot highs and lows:
You configure Pivot Lookback Left and Pivot Lookback Right to control swing sensitivity.
Pivots are detected on the OI Z series.
For each eligible pivot, the script compares OI Z and price at the last two pivots.
It looks for four patterns:
Regular Bullish – price makes a lower low, OI Z makes a higher low. This can indicate selling exhaustion in positioning even as price washes out. These are marked with a line and a label "ℝ" below the oscillator, in the bullish color.
Hidden Bullish – price makes a higher low, OI Z makes a lower low. This suggests continuation potential where price holds up while positioning resets. Marked with "ℍ" in the bullish color.
Regular Bearish – price makes a higher high, OI Z makes a lower high. This is a classic warning sign of trend exhaustion, where price pushes higher while OI Z fails to confirm. Marked with "ℝ" in the bearish color.
Hidden Bearish – price makes a lower high, OI Z makes a higher high. This is often seen in pullbacks within downtrends, where price retraces but positioning stretches again in the direction of the prevailing move. Marked with "ℍ" in the bearish color.
Each divergence type can be toggled globally via Show Detected Divergences . Internally, the script restricts how far back it will connect pivots, so you do not get stray signals linking very old structures to current bars.
Trading applications
Crowding and squeeze risk
Z scores are a natural way to talk about crowding:
High positive Z in aggregated OI means the market is running high leverage compared to its own norm. If price is also extended, the risk of a squeeze or sharp unwind rises.
Deep negative Z means leverage has been cleaned out. While it can be painful to sit through, this environment often sets up cleaner new trends, since there is less one sided positioning to unwind.
The extreme bands at ±3 to ±4 highlight the rare states where crowding is most intense. You can treat these events as regime markers rather than day to day noise.
Trend confirmation and fade selection
Combine Z score with price and trend:
Bull trends with positive and rising Z are supported by fresh leverage, usually more persistent.
Bull trends with flat or falling Z while price keeps grinding up can be more fragile. Divergences and extreme bands can help identify which edges you do not want to fade and which you might.
In downtrends, deep negative Z that stays pinned can mean persistent de risking. Once the Z score starts to mean revert back toward zero, it can mark the early stages of stabilization.
Event and liquidation context
Around major events, you often see:
Rapid spikes in Z as traders rush to position.
Reversal and overshoot as liquidations and forced de risking clear the book.
A move from positive extremes through zero into negative extremes as the market transitions from crowded to under exposed.
The Z score makes that path obvious, especially in oscillator mode, where you see a block of high positive bars before the crash, then a slab of deep negative bars after the flush.
Settings overview
Z Score group
Plotting Type – None, Line, Colored Line, Oscillator.
Z Score Lookback Period – window used for mean and standard deviation on aggregated OI.
Smoothing Type – SMA, HMA, EMA, WMA, DEMA, RMA, linear regression, ALMA, TEMA or T3.
Smoothing Period – length for the selected moving average on the raw Z score.
Moving Average group
Show EMA – toggle EMA overlay on Z score.
EMA Period – EMA length for the signal line.
EMA Color – color of the EMA line.
Thresholds and Reference Lines group
Select Reference Lines – None, Standard Deviation Levels, Extreme Bands.
Standard deviation lines at 0, ±1, ±2 appear in both modes.
Extreme bands add filled zones at ±3 to ±4 with adaptive opacity tied to |Z|.
Extra Plotting and UI
Base Line Color – default color for the simple line mode.
Line Width – thickness of the oscillator line.
Positive Color – positive or bullish condition color.
Negative Color – negative or bearish condition color.
Divergences group
Show Detected Divergences – master toggle for divergence plotting.
Pivot Lookback Left and Pivot Lookback Right – how many bars left and right to define a pivot, controlling divergence sensitivity.
Open Interest Source group
OI Units – COIN or USD.
Exchange toggles for Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Internally, all enabled exchanges and contract suffixes are aggregated into one synthetic OI series.
Alerts included
The indicator defines alert conditions for several key events:
OI Z Score Positive – Z crosses above zero, aggregated OI moves from below mean to above mean.
OI Z Score Negative – Z crosses below zero, aggregated OI moves from above mean to below mean.
OI Z Score Enters +2σ – Z enters the +2 band and above, marking extended positive positioning.
OI Z Score Enters −2σ – Z enters the −2 band and below, marking extended negative positioning.
Tie these into your strategy to be notified when leverage moves from normal to extended states.
Notes
This indicator does not rely on price based oscillators. It is a statistical lens on cross venue open interest, which makes it a complementary tool rather than a replacement for your existing price or volume signals. Use it to:
Quantify how unusual current futures positioning is compared to recent history.
Identify crowded leverage phases that can fuel squeezes.
Spot structural divergences between price and positioning.
Frame risk and opportunity around events and regime shifts.
It is not a complete trading system. Combine it with your own entries, exits and risk rules to get the most out of what the Z score is telling you about positioning pressure under the hood of the market.
Bollinger Bands + VWAP + 4-State MACD BackgroundBollinger Bands + VWAP + 4-State MACD Background
An all-in-one technical analysis indicator combining three proven tools with an intelligent momentum-based background visualization system.
📊 FEATURES
Bollinger Bands
Standard Bollinger Bands implementation with full customization options:
Adjustable period length (default: 20)
Multiple moving average types: SMA, EMA, SMMA (RMA), WMA, VWMA
Configurable standard deviation multiplier (default: 2.0)
Visual fill between bands to highlight volatility zones
Offset capability for forward/backward display
Session VWAP (Volume Weighted Average Price)
Automatically resets at the start of each trading session:
Calculates true volume-weighted average price
Resets daily to provide fresh reference levels
Customizable source input (default: HLC3)
Adjustable line appearance (color and width)
Can be toggled on/off as needed
4-State MACD Background System
This is the unique feature of this indicator. The chart background dynamically changes based on MACD momentum analysis, providing instant visual feedback on trend strength and direction:
🟢 Strong Bullish (Bright Green)
MACD line is above signal line
Histogram is growing (momentum accelerating upward)
Indicates strong upward momentum
🟢 Weak Bullish (Pale Green)
MACD line is above signal line
Histogram is shrinking (momentum decelerating)
Early warning signal that uptrend may be weakening
🔴 Strong Bearish (Bright Red)
MACD line is below signal line
Histogram is falling (momentum accelerating downward)
Indicates strong downward momentum
🔴 Weak Bearish (Pale Red)
MACD line is below signal line
Histogram is rising (momentum decelerating)
Early warning signal that downtrend may be weakening
🎯 HOW TO USE
For Trend Trading:
Strong colored backgrounds indicate confirmed momentum in that direction - consider staying with the trend
Weak colored backgrounds signal potential momentum exhaustion - watch for possible reversals
Use VWAP as a dynamic support/resistance level
Bollinger Band breakouts combined with strong MACD backgrounds can confirm trend strength
Price above VWAP + strong bullish background = bullish bias
Price below VWAP + strong bearish background = bearish bias
For Mean Reversion:
Price touching upper/lower Bollinger Bands with weak MACD background may suggest potential reversal
VWAP acts as a mean reversion anchor during range-bound sessions
Background color shifts from strong to weak often precede price direction changes
Look for price return to VWAP when extended beyond bands with weakening momentum
Signal Confirmation:
Strongest signals occur when multiple indicators align:
BB breakout + MACD strong color + price above/below VWAP
Price rejection at BB bands + MACD color weakening
VWAP support/resistance hold + MACD color change
⚙️ SETTINGS
All components are fully customizable through organized input groups:
Bollinger Bands Group:
Period length
Moving average type (SMA/EMA/SMMA/WMA/VWMA)
Source (close/open/high/low/etc.)
Standard deviation multiplier
Offset
VWAP Group:
Toggle show/hide
Source calculation method
Line color
Line width
MACD Group:
Toggle background on/off
Fast length (default: 12)
Slow length (default: 26)
Signal length (default: 9)
Source
Four separate color settings for each momentum state
All colors include transparency controls
💡 EDUCATIONAL VALUE
This indicator teaches important concepts:
How volatility (Bollinger Bands) relates to price movement
The importance of volume-weighted pricing (VWAP)
Momentum analysis through MACD
How combining multiple timeframes and indicators can provide confluence
The difference between trend strength and trend direction
⚠️ IMPORTANT NOTES
This indicator is for educational and informational purposes only
No indicator is perfect - always use proper risk management
Past performance does not guarantee future results
Combine with your own analysis and risk tolerance
Test thoroughly on historical data before live trading
This is not financial advice - use at your own risk
🔧 TECHNICAL DETAILS
Pine Script Version 6
Overlay indicator (displays on price chart)
All calculations use standard, well-documented formulas
Minimal lag due to efficient coding
Compatible with all timeframes and instruments
No repainting - all signals are confirmed on bar close
📝 CHANGELOG
Version 1.0
Initial release
Bollinger Bands with multiple MA types
Session VWAP with daily reset
4-state MACD background system
Full customization options
Developed for traders who want multiple confirmation signals in a clean, organized format without cluttering their charts with separate indicator panels.
Exhaustion IndicatorThe ScalpSQZ indicator is designed to identify four critical market states using volatility structure, momentum behavior, and exhaustion conditions. It enhances scalping precision by visually marking transitions between consolidation, squeeze conditions, and momentum reversals through color-coded candles.
1. Squeeze Conditions (Orange Candles)
Orange candles highlight volatility compression, detected when Bollinger Bands contract inside the Keltner Channels. This structure signals that market volatility is tightening and a significant expansion move is likely to follow. The squeeze represents a pre-breakout environment and serves as the earliest warning of a potential directional shift.
2. Consolidation Conditions (Yellow Candles)
Yellow candles identify phases of low directional momentum. These conditions occur when RSI remains near neutral values, MACD histogram activity is minimal, and the Rate of Change stays muted. This combination indicates that the market is balanced and non-trending, often preceding a volatility spike or a new trend. Consolidation helps traders avoid low-probability entries during indecisive price action.
3. Momentum Exhaustion — Overbought Fade (White Candles)
White candles signal potential top-side exhaustion. This occurs when RSI enters overbought territory while the MACD histogram begins to weaken compared to the previous bar. This condition does not necessarily call a reversal but warns that bullish momentum is deteriorating and upside continuation may be limited. It is particularly useful for identifying trend fatigue and tightening stop-loss placement.
4. Momentum Exhaustion — Oversold Fade (Purple Candles)
Purple candles identify bottom-side exhaustion and appear when RSI reaches oversold levels, MACD momentum begins improving, and the current close shows buyer defense relative to the previous low. This condition suggests selling pressure is diminishing and a potential reversal or relief bounce may be forming. Purple candles serve as an early indication of bearish trend exhaustion.
Color Priority System
The indicator follows a fixed hierarchy to ensure clarity:
Squeeze (orange) has the highest priority, followed by consolidation (yellow). Exhaustion signals (white for tops, purple for bottoms) apply only when no squeeze or consolidation conditions are active. This structure ensures that the most critical market states are always highlighted first.
Purpose and Application
ScalpSQZ helps traders identify optimal environments for breakouts, anticipate trend exhaustion, and avoid low-quality trades during choppy or low-momentum conditions. It is suitable for scalping, day trading, and swing trading across any asset class or timeframe.
FluxPulse Momentum [JOAT]FluxPulse Momentum - Adaptive Multi-Component Oscillator
FluxPulse Momentum is a composite oscillator that blends three distinct momentum components into a single, smoothed signal line. Rather than relying on a single indicator, it synthesizes adaptive RSI, normalized rate of change, and a Kaufman-style efficiency ratio to provide a multi-dimensional view of momentum.
What This Indicator Does
Combines RSI, Rate of Change (ROC), and Efficiency Ratio into one weighted composite
Applies EMA smoothing to reduce noise while preserving responsiveness
Displays overbought/oversold zones with optional background highlighting
Generates buy/sell signals when the oscillator crosses its signal line in favorable zones
Provides a real-time dashboard showing current state, momentum direction, and efficiency
Core Components
Adaptive RSI (50% weight) — Standard RSI calculation normalized around the 50 level
Normalized ROC (30% weight) — Rate of change scaled relative to its recent maximum range
Efficiency Ratio (20% weight) — Measures directional movement efficiency, inspired by Kaufman's adaptive concepts
The final composite is smoothed twice using EMA to create both a fast line and a signal line.
Signal Logic
// Buy signal: crossover in lower half
buySignal = ta.crossover(qmo, qmoSmooth) and qmo < 50
// Sell signal: crossunder in upper half
sellSignal = ta.crossunder(qmo, qmoSmooth) and qmo > 50
Signals are generated only when the oscillator is positioned favorably—buy signals occur below the 50 midline, sell signals occur above it.
Dashboard Information
The on-chart table displays:
Current oscillator value with gradient coloring
Momentum state (Overbought, Oversold, Bullish, Bearish, Neutral)
Momentum direction and acceleration
Efficiency ratio percentage
Active signal status
Inputs Overview
RSI Length — Period for RSI calculation (default: 14)
ROC Length — Period for rate of change (default: 10)
Smoothing Length — EMA smoothing period (default: 3)
Overbought/Oversold Levels — Threshold levels for zone detection
Await Bar Confirmation — Wait for bar close before triggering alerts
How to Use It
Watch for crossovers between the main line and signal line
Use overbought/oversold zones to identify potential reversal areas
Monitor the histogram for momentum acceleration or deceleration
Combine with price action analysis for confirmation
Alerts
Buy Signal — Bullish crossover in the lower zone
Sell Signal — Bearish crossunder in the upper zone
Overbought/Oversold Crosses — Level threshold crossings
This indicator is provided for educational purposes. It does not constitute financial advice. Always conduct your own analysis before making trading decisions.
— Made with passion by officialjackofalltrades
RSI Swing Indicator (Win-Rate + Forecast Line + Range Row)What the script does:
It’s essentially an enhanced RSI tool that doesn’t just show the raw RSI line. Instead, it adds forecasting, trade statistics, and range detection so you can see how reliable RSI signals have been historically and what they might mean going forward.
The main components
RSI Calculation
- Uses your chosen source (close, hl2, etc.) and length (default 7).
- Plots the RSI line (orange).
Forecasting
- Projects RSI into the future using slope extrapolation.
- Plots a forecast line (blue) and shows whether RSI is likely to become overbought, oversold, or stay neutral.
Trade Statistics
- Tracks how many long and short trades would have been profitable based on RSI bias.
- Calculates Win‑Rate (percentage of profitable trades) and Average Return (average gain/loss per trade).
- This gives you a statistical edge: are longs or shorts historically working better?
Bias & Conflict Detection
- Defines current bias (Bullish, Bearish, Neutral).
- Flags Conflict when the forecast disagrees with the current bias (e.g., RSI bullish now but forecast bearish).
- Helps you avoid trading against weakening momentum.
Range Detection
- Checks if RSI slope is flat and values are between mid‑bounds (40–60).
- Calculates Range Probability (how often range conditions occur).
- Adds a Range row to the table so you know when the market is likely sideways instead of trending.
Table Display
- Summarizes everything in a neat table: Forecast, Win‑Rates, Avg Returns, Prob Bias, Conflict, Range Prob, and Range status.
- Color‑coded so you can instantly see what’s favorable (green), risky (red), or neutral (yellow/orange).
How to use it
- Trend trading: Look for Profitable Bias with forecast alignment.
- Range trading: When both win‑rates are weak and Range row says Range Likely, fade extremes (buy low RSI, sell high RSI).
- Risk management: Avoid trades when Conflict is flagged.
- Forecasting: Use the projected RSI to anticipate overbought/oversold zones before they happen.
In short:
The script is like a “smart RSI dashboard”. It takes the basic RSI, adds forecasting, tracks how well past trades worked, and tells you whether the market is trending or ranging. This way, you’re not just reacting to RSI — you’re trading with context, probabilities, and forward‑looking signals.
PEG RSI [Auto EPS Growth]The PEG RSI is a hybrid indicator that combines fundamental valuation with technical momentum. It applies the Relative Strength Index (RSI) directly to the Price/Earnings-to-Growth (PEG) Ratio.
Unlike traditional PEG indicators that require manual input for growth rates, this script automatically calculates the Compound Annual Growth Rate (CAGR) of Earnings Per Share (EPS) based on historical data.
Key Features
- Auto-Calculated Growth: Uses historical TTM Earnings Per Share (EPS) to calculate the CAGR over a user-defined period (Default: 4 years).
- Dynamic Valuation: Converts the static PEG ratio into an oscillator (RSI) to identify relative valuation extremes.
- Trend & Momentum: Visualizes the momentum of the PEG ratio relative to its own history.
Educational Case Study
This indicator is designed for educational purposes and research. Instead of relying on fixed overbought or oversold levels, users are encouraged to study the correlation between the PEG RSI and price action independently.
- Observe how the price reacts when the PEG RSI reaches upper or lower extremes.
- Different stocks may respect different RSI zones based on their growth stability.
- Use this tool to analyze how market valuation momentum shifts over time.
Settings:
- Years for CAGR Growth: Timeframe to calculate EPS growth (Default: 4 years).
- RSI Length: Lookback period for the RSI calculation (Default: 14).
Note: This indicator works best on stocks with a consistent history of earnings. It requires financial data to function (will not work on assets without EPS like Crypto or Forex).
Squeeze Momentum OmniViewSqueeze Momentum OmniView+ is an enhanced and modernized version of the classic Squeeze Momentum Indicator by LazyBear, rebuilt from the ground up in Pine Script v6.
This upgraded edition introduces OmniView color-mapping, adaptive histogram scaling, extreme detection, heat-zone alerts, and dynamic fire/ice icons, all fully synchronized with your selected visualization mode.
Key Features
1. OmniView Color Engine (Exact Price-State Matching)
Reproduces the full OmniView color logic (aqua → yellow → red), tracking market compression, expansion, and directional strength using a seamless multi-gradient system.
2. Dual Histogram Modes
Choose how the histogram is normalized:
Price-State Mode: Colors reflect price position within its recent range.
Self-Normalized Mode: Colors adapt to the histogram’s own momentum curve.
Both modes automatically adjust alerts, extremes, and icons.
3. Enhanced Squeeze Logic
The script includes the classic squeeze states (ON / OFF / Neutral) with clean visual dots and improved logic for precise state transitions.
4. Adaptive Extreme Detection (Upper & Lower Extremes)
Detects when price or momentum sets new highs/lows according to the active mode.
Automatically draws 🔥 fire labels near upper extremes and ❄️ ice labels near lower extremes, with:
Adaptive or fixed offsets
Customizable sizes
Optional dimming on momentum fade
Icon colors matching the histogram
5. Full Alert Suite
Includes alerts for:
New Upper / Lower Extremes
Heat-Zone Crossings (25%, 50%, 75%)
Momentum Turning Up / Down
Zero-Line Crossovers
Squeeze ON / OFF
All alert conditions adapt dynamically to the mode selected.
6. Clean, modern, and fully customizable
Every visual element—colors, transparency, icon sizing, offsets, squeeze dots, fades—can be adjusted from the settings panel.
What This Indicator Helps You See
Momentum acceleration and deceleration
Market compression/expansion phases
Heat levels in the current price context
Momentum extremes that often signal turning points
Trend continuation or exhaustion patterns
High-precision squeeze entries with visual clarity
Designed For
Traders looking for a more intelligent version of Squeeze Momentum with:
Better visual clarity
Stronger adaptive behavior
More actionable alerts
More information per bar without clutter
A special thanks to LazyBear, the original author of the Squeeze Momentum engine.
This script is not affiliated with or endorsed by him, but it extends his outstanding contribution to the TradingView community.
MACD Momentum Pro MACD Momentum Pro is an enhanced version of the classic MACD designed to help traders identify momentum strength with far greater clarity.
In addition to the traditional MACD line, Signal line, and histogram, this tool introduces two new momentum-intensity alerts:
• Strong Green – bullish momentum accelerating above the zero line
• Strong Red – bearish momentum accelerating below the zero line
These conditions allow traders to quickly spot when market pressure is truly strengthening, reducing noise and improving decision-making in trending environments.
The indicator also includes real-time alerts for:
• MACD/Signal crosses (bullish & bearish)
• MACD zero-line crosses
• Shifts between rising/falling histogram states
All moving averages (EMA or SMA) are fully customizable, and the visual histogram automatically adapts color to reflect momentum transitions.
Whether you are trading breakouts, trend reversals, or momentum continuation setups, this upgraded MACD version provides a clearer, more actionable view of market strength—while keeping the original MACD logic intact.
AKP Momentum TableThe table give at one glance the RSI,ADX and Relative Strength values on the 15 min,125 min, Daily,Weekly and Monthly timeframes to help identify the stocks with strong momentum securities. The Table is movable at various parts of the screen from a drop down menu and the values of RSI,ADX and RS period can also be changes.Enjoy!
CEF (Chaos Theory Regime Oscillator)Chaos Theory Regime Oscillator
This script is open to the community.
What is it?
The CEF (Chaos Entropy Fusion) Oscillator is a next-generation "Regime Analysis" tool designed to replace traditional, static momentum indicators like RSI or MACD. Unlike standard oscillators that only look at price changes, CEF analyzes the "character" of the market using concepts from Chaos Theory and Information Theory.
It combines advanced mathematical engines (Hurst Exponent, Entropy, VHF) to determine whether a price movement is a real trend or just random noise. It uses a novel "Adaptive Normalization" technique to solve scaling problems common in advanced indicators, ensuring the oscillator remains sensitive yet stable across all assets (Crypto, Forex, Stocks).
What It Promises:
Intelligent Filtering: Filters out false signals in sideways (volatile) markets using the Hurst Base to measure trend continuity.
Dynamic Adaptation: Automatically adapts to volatility. Thanks to trend memory, it doesn't get stuck at the top during uptrends or at the bottom during downtrends.
No Repainting: All signals are confirmed at the close of the bar. They don't repaint or disappear.
What It Doesn't Promise:
Magic Wand: It's a powerful analytical tool, not a crystal ball. It determines the regime, but risk management is up to the investor.
Late-Free Holy Grail: It deliberately uses advanced correction algorithms (WMA/SMA) to provide stability and filter out noise. Speed is sacrificed for accuracy.
Which Concepts Are Used for Which Purpose?
CEF is built on proven mathematical concepts while creating a unique "Fusion" mechanism. These are not used in their standard forms, but are remixed to create a consensus engine:
Hurst Exponent: Used to measure the "memory" of the time series. Tells the oscillator whether there is a probability of the trend continuing or reversing to the mean.
Vertical Horizontal Filter (VHF): Determines whether the market is in a trend phase or a congestion phase.
Shannon Entropy: Measures the "irregularity" or "unpredictability" of market data to adjust signal sensitivity.
Adaptive Normalization (Key Innovation): Instead of fixed limits, the oscillator dynamically scales itself based on recent historical performance, solving the "flat line" problem seen in other advanced scripts.
Original Methodology and Community Contribution
This algorithm is a custom synthesis of public domain mathematical theories. The author's unique contribution lies in the "Adaptive Normalization Logic" and the custom weighting of Chaos components to filter momentum.
Why Public Domain? Standard indicators (RSI, MACD) were developed for the markets of the 1970s. Modern markets require modern mathematics. This script is presented to the community to demonstrate how Regime Analysis can improve trading decisions compared to static tools.
What Problems Does It Solve?
Problem 1: The "Stagnant Market" Trap
CEF Solution: While the RSI gives false signals in a sideways market, CEF's Hurst/VHF filter suppresses the signal, essentially making the histogram "off" (or weak) during noise.
Problem 2: The "Overbought" Fallacy
CEF Solution: In a strong trend (Pump/Dump), traditional oscillators get stuck at 100 or 0. CEF uses "Trend Memory" to understand that an overbought price is not a reversal signal but a sign of trend strength, and keeps the signal green/red instead of reversing it prematurely. Problem 3: Visual Confusion
CEF Solution: Instead of multiple lines, it presents a single, color-coded histogram featuring only prominent "Smart Circles" at high-probability reversal points.
Automation Ready: Custom Alerts
CEF is designed for both manual trading and automation.
Smart Buy/Sell Circles: Visual signals that only appear when trend filters are aligned with momentum reversals.
Deviation Labels: Automatically detects and labels structural divergences between price and entropy.
Disclaimer: This indicator is for educational purposes only. Past performance does not guarantee future results. Always practice appropriate risk management.
Bästa Bob Multi-RSI 😎👊✅ RSI 7 → Fast impulse indicator
• Shows micro-movements
• Reacts instantly to liquidity sweeps
• Perfect for entry timing
✅ RSI 14 → Macro momentum indicator
• Captures the real trend
• Filters out noise
• Confirms larger market movements
When both are in sync → you get true market direction plus perfect timing.
👉 How to Use RSI 7 + RSI 14
1️⃣ Entry Signals (the best method)
BUY when:
• RSI 7 turns up from oversold
• RSI 14 is also sloping upward or gets crossed by RSI 7 from below
→ Extremely accurate right after a liquidity sweep.
SELL when:
• RSI 7 turns down from overbought
• RSI 14 is sloping downward or gets crossed by RSI 7 from above
→ Works insanely well for fakeouts and FVG entries.
2️⃣ Trend Filter
• When RSI 14 stays above 50 → market is bullish
• When RSI 14 stays below 50 → bearish
RSI 7 is then used only for timing entries.
3️⃣ A++ Setups (your favorite ones 😉🔥)
The best signals appear when:
✔ RSI 7 crosses RSI 14 at the same time as:
• a liquidity sweep happens
• price taps into an FVG or Order Block
• volume reacts
• your trend filter (EMA, HTF) supports the move
This combo is criminally effective when scalping BTC, NAS100, and XAUUSD.
Adaptive Genesis Engine [AGE]ADAPTIVE GENESIS ENGINE (AGE)
Pure Signal Evolution Through Genetic Algorithms
Where Darwin Meets Technical Analysis
🧬 WHAT YOU'RE GETTING - THE PURE INDICATOR
This is a technical analysis indicator - it generates signals, visualizes probability, and shows you the evolutionary process in real-time. This is NOT a strategy with automatic execution - it's a sophisticated signal generation system that you control .
What This Indicator Does:
Generates Long/Short entry signals with probability scores (35-88% range)
Evolves a population of up to 12 competing strategies using genetic algorithms
Validates strategies through walk-forward optimization (train/test cycles)
Visualizes signal quality through premium gradient clouds and confidence halos
Displays comprehensive metrics via enhanced dashboard
Provides alerts for entries and exits
Works on any timeframe, any instrument, any broker
What This Indicator Does NOT Do:
Execute trades automatically
Manage positions or calculate position sizes
Place orders on your behalf
Make trading decisions for you
This is pure signal intelligence. AGE tells you when and how confident it is. You decide whether and how much to trade.
🔬 THE SCIENCE: GENETIC ALGORITHMS MEET TECHNICAL ANALYSIS
What Makes This Different - The Evolutionary Foundation
Most indicators are static - they use the same parameters forever, regardless of market conditions. AGE is alive . It maintains a population of competing strategies that evolve, adapt, and improve through natural selection principles:
Birth: New strategies spawn through crossover breeding (combining DNA from fit parents) plus random mutation for exploration
Life: Each strategy trades virtually via shadow portfolios, accumulating wins/losses, tracking drawdown, and building performance history
Selection: Strategies are ranked by comprehensive fitness scoring (win rate, expectancy, drawdown control, signal efficiency)
Death: Weak strategies are culled periodically, with elite performers (top 2 by default) protected from removal
Evolution: The gene pool continuously improves as successful traits propagate and unsuccessful ones die out
This is not curve-fitting. Each new strategy must prove itself on out-of-sample data through walk-forward validation before being trusted for live signals.
🧪 THE DNA: WHAT EVOLVES
Every strategy carries a 10-gene chromosome controlling how it interprets market data:
Signal Sensitivity Genes
Entropy Sensitivity (0.5-2.0): Weight given to market order/disorder calculations. Low values = conservative, require strong directional clarity. High values = aggressive, act on weaker order signals.
Momentum Sensitivity (0.5-2.0): Weight given to RSI/ROC/MACD composite. Controls responsiveness to momentum shifts vs. mean-reversion setups.
Structure Sensitivity (0.5-2.0): Weight given to support/resistance positioning. Determines how much price location within swing range matters.
Probability Adjustment Genes
Probability Boost (-0.10 to +0.10): Inherent bias toward aggressive (+) or conservative (-) entries. Acts as personality trait - some strategies naturally optimistic, others pessimistic.
Trend Strength Requirement (0.3-0.8): Minimum trend conviction needed before signaling. Higher values = only trades strong trends, lower values = acts in weak/sideways markets.
Volume Filter (0.5-1.5): Strictness of volume confirmation. Higher values = requires strong volume, lower values = volume less important.
Risk Management Genes
ATR Multiplier (1.5-4.0): Base volatility scaling for all price levels. Controls whether strategy uses tight or wide stops/targets relative to ATR.
Stop Multiplier (1.0-2.5): Stop loss tightness. Lower values = aggressive profit protection, higher values = more breathing room.
Target Multiplier (1.5-4.0): Profit target ambition. Lower values = quick scalping exits, higher values = swing trading holds.
Adaptation Gene
Regime Adaptation (0.0-1.0): How much strategy adjusts behavior based on detected market regime (trending/volatile/choppy). Higher values = more reactive to regime changes.
The Magic: AGE doesn't just try random combinations. Through tournament selection and fitness-weighted crossover, successful gene combinations spread through the population while unsuccessful ones fade away. Over 50-100 bars, you'll see the population converge toward genes that work for YOUR instrument and timeframe.
📊 THE SIGNAL ENGINE: THREE-LAYER SYNTHESIS
Before any strategy generates a signal, AGE calculates probability through multi-indicator confluence:
Layer 1 - Market Entropy (Information Theory)
Measures whether price movements exhibit directional order or random walk characteristics:
The Math:
Shannon Entropy = -Σ(p × log(p))
Market Order = 1 - (Entropy / 0.693)
What It Means:
High entropy = choppy, random market → low confidence signals
Low entropy = directional market → high confidence signals
Direction determined by up-move vs down-move dominance over lookback period (default: 20 bars)
Signal Output: -1.0 to +1.0 (bearish order to bullish order)
Layer 2 - Momentum Synthesis
Combines three momentum indicators into single composite score:
Components:
RSI (40% weight): Normalized to -1/+1 scale using (RSI-50)/50
Rate of Change (30% weight): Percentage change over lookback (default: 14 bars), clamped to ±1
MACD Histogram (30% weight): Fast(12) - Slow(26), normalized by ATR
Why This Matters: RSI catches mean-reversion opportunities, ROC catches raw momentum, MACD catches momentum divergence. Weighting favors RSI for reliability while keeping other perspectives.
Signal Output: -1.0 to +1.0 (strong bearish to strong bullish)
Layer 3 - Structure Analysis
Evaluates price position within swing range (default: 50-bar lookback):
Position Classification:
Bottom 20% of range = Support Zone → bullish bounce potential
Top 20% of range = Resistance Zone → bearish rejection potential
Middle 60% = Neutral Zone → breakout/breakdown monitoring
Signal Logic:
At support + bullish candle = +0.7 (strong buy setup)
At resistance + bearish candle = -0.7 (strong sell setup)
Breaking above range highs = +0.5 (breakout confirmation)
Breaking below range lows = -0.5 (breakdown confirmation)
Consolidation within range = ±0.3 (weak directional bias)
Signal Output: -1.0 to +1.0 (bearish structure to bullish structure)
Confluence Voting System
Each layer casts a vote (Long/Short/Neutral). The system requires minimum 2-of-3 agreement (configurable 1-3) before generating a signal:
Examples:
Entropy: Bullish, Momentum: Bullish, Structure: Neutral → Signal generated (2 long votes)
Entropy: Bearish, Momentum: Neutral, Structure: Neutral → No signal (only 1 short vote)
All three bullish → Signal generated with +5% probability bonus
This is the key to quality. Single indicators give too many false signals. Triple confirmation dramatically improves accuracy.
📈 PROBABILITY CALCULATION: HOW CONFIDENCE IS MEASURED
Base Probability:
Raw_Prob = 50% + (Average_Signal_Strength × 25%)
Then AGE applies strategic adjustments:
Trend Alignment:
Signal with trend: +4%
Signal against strong trend: -8%
Weak/no trend: no adjustment
Regime Adaptation:
Trending market (efficiency >50%, moderate vol): +3%
Volatile market (vol ratio >1.5x): -5%
Choppy market (low efficiency): -2%
Volume Confirmation:
Volume > 70% of 20-bar SMA: no change
Volume below threshold: -3%
Volatility State (DVS Ratio):
High vol (>1.8x baseline): -4% (reduce confidence in chaos)
Low vol (<0.7x baseline): -2% (markets can whipsaw in compression)
Moderate elevated vol (1.0-1.3x): +2% (trending conditions emerging)
Confluence Bonus:
All 3 indicators agree: +5%
2 of 3 agree: +2%
Strategy Gene Adjustment:
Probability Boost gene: -10% to +10%
Regime Adaptation gene: scales regime adjustments by 0-100%
Final Probability: Clamped between 35% (minimum) and 88% (maximum)
Why These Ranges?
Below 35% = too uncertain, better not to signal
Above 88% = unrealistic, creates overconfidence
Sweet spot: 65-80% for quality entries
🔄 THE SHADOW PORTFOLIO SYSTEM: HOW STRATEGIES COMPETE
Each active strategy maintains a virtual trading account that executes in parallel with real-time data:
Shadow Trading Mechanics
Entry Logic:
Calculate signal direction, probability, and confluence using strategy's unique DNA
Check if signal meets quality gate:
Probability ≥ configured minimum threshold (default: 65%)
Confluence ≥ configured minimum (default: 2 of 3)
Direction is not zero (must be long or short, not neutral)
Verify signal persistence:
Base requirement: 2 bars (configurable 1-5)
Adapts based on probability: high-prob signals (75%+) enter 1 bar faster, low-prob signals need 1 bar more
Adjusts for regime: trending markets reduce persistence by 1, volatile markets add 1
Apply additional filters:
Trend strength must exceed strategy's requirement gene
Regime filter: if volatile market detected, probability must be 72%+ to override
Volume confirmation required (volume > 70% of average)
If all conditions met for required persistence bars, enter shadow position at current close price
Position Management:
Entry Price: Recorded at close of entry bar
Stop Loss: ATR-based distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit: ATR-based distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Position: +1 (long) or -1 (short), only one at a time per strategy
Exit Logic:
Check if price hit stop (on low) or target (on high) on current bar
Record trade outcome in R-multiples (profit/loss normalized by ATR)
Update performance metrics:
Total trades counter incremented
Wins counter (if profit > 0)
Cumulative P&L updated
Peak equity tracked (for drawdown calculation)
Maximum drawdown from peak recorded
Enter cooldown period (default: 8 bars, configurable 3-20) before next entry allowed
Reset signal age counter to zero
Walk-Forward Tracking:
During position lifecycle, trades are categorized:
Training Phase (first 250 bars): Trade counted toward training metrics
Testing Phase (next 75 bars): Trade counted toward testing metrics (out-of-sample)
Live Phase (after WFO period): Trade counted toward overall metrics
Why Shadow Portfolios?
No lookahead bias (uses only data available at the bar)
Realistic execution simulation (entry on close, stop/target checks on high/low)
Independent performance tracking for true fitness comparison
Allows safe experimentation without risking capital
Each strategy learns from its own experience
🏆 FITNESS SCORING: HOW STRATEGIES ARE RANKED
Fitness is not just win rate. AGE uses a comprehensive multi-factor scoring system:
Core Metrics (Minimum 3 trades required)
Win Rate (30% of fitness):
WinRate = Wins / TotalTrades
Normalized directly (0.0-1.0 scale)
Total P&L (30% of fitness):
Normalized_PnL = (PnL + 300) / 600
Clamped 0.0-1.0. Assumes P&L range of -300R to +300R for normalization scale.
Expectancy (25% of fitness):
Expectancy = Total_PnL / Total_Trades
Normalized_Expectancy = (Expectancy + 30) / 60
Clamped 0.0-1.0. Rewards consistency of profit per trade.
Drawdown Control (15% of fitness):
Normalized_DD = 1 - (Max_Drawdown / 15)
Clamped 0.0-1.0. Penalizes strategies that suffer large equity retracements from peak.
Sample Size Adjustment
Quality Factor:
<50 trades: 1.0 (full weight, small sample)
50-100 trades: 0.95 (slight penalty for medium sample)
100 trades: 0.85 (larger penalty for large sample)
Why penalize more trades? Prevents strategies from gaming the system by taking hundreds of tiny trades to inflate statistics. Favors quality over quantity.
Bonus Adjustments
Walk-Forward Validation Bonus:
if (WFO_Validated):
Fitness += (WFO_Efficiency - 0.5) × 0.1
Strategies proven on out-of-sample data receive up to +10% fitness boost based on test/train efficiency ratio.
Signal Efficiency Bonus (if diagnostics enabled):
if (Signals_Evaluated > 10):
Pass_Rate = Signals_Passed / Signals_Evaluated
Fitness += (Pass_Rate - 0.1) × 0.05
Rewards strategies that generate high-quality signals passing the quality gate, not just profitable trades.
Final Fitness: Clamped at 0.0 minimum (prevents negative fitness values)
Result: Elite strategies typically achieve 0.50-0.75 fitness. Anything above 0.60 is excellent. Below 0.30 is prime candidate for culling.
🔬 WALK-FORWARD OPTIMIZATION: ANTI-OVERFITTING PROTECTION
This is what separates AGE from curve-fitted garbage indicators.
The Three-Phase Process
Every new strategy undergoes a rigorous validation lifecycle:
Phase 1 - Training Window (First 250 bars, configurable 100-500):
Strategy trades normally via shadow portfolio
All trades count toward training performance metrics
System learns which gene combinations produce profitable patterns
Tracks independently: Training_Trades, Training_Wins, Training_PnL
Phase 2 - Testing Window (Next 75 bars, configurable 30-200):
Strategy continues trading without any parameter changes
Trades now count toward testing performance metrics (separate tracking)
This is out-of-sample data - strategy has never seen these bars during "optimization"
Tracks independently: Testing_Trades, Testing_Wins, Testing_PnL
Phase 3 - Validation Check:
Minimum_Trades = 5 (configurable 3-15)
IF (Train_Trades >= Minimum AND Test_Trades >= Minimum):
WR_Efficiency = Test_WinRate / Train_WinRate
Expectancy_Efficiency = Test_Expectancy / Train_Expectancy
WFO_Efficiency = (WR_Efficiency + Expectancy_Efficiency) / 2
IF (WFO_Efficiency >= 0.55): // configurable 0.3-0.9
Strategy.Validated = TRUE
Strategy receives fitness bonus
ELSE:
Strategy receives 30% fitness penalty
ELSE:
Validation deferred (insufficient trades in one or both periods)
What Validation Means
Validated Strategy (Green "✓ VAL" in dashboard):
Performed at least 55% as well on unseen data compared to training data
Gets fitness bonus: +(efficiency - 0.5) × 0.1
Receives priority during tournament selection for breeding
More likely to be chosen as active trading strategy
Unvalidated Strategy (Orange "○ TRAIN" in dashboard):
Failed to maintain performance on test data (likely curve-fitted to training period)
Receives 30% fitness penalty (0.7x multiplier)
Makes strategy prime candidate for culling
Can still trade but with lower selection probability
Insufficient Data (continues collecting):
Hasn't completed both training and testing periods yet
OR hasn't achieved minimum trade count in both periods
Validation check deferred until requirements met
Why 55% Efficiency Threshold?
If a strategy earned 10R during training but only 5.5R during testing, it still proved an edge exists beyond random luck. Requiring 100% efficiency would be unrealistic - market conditions change between periods. But requiring >50% ensures the strategy didn't completely degrade on fresh data.
The Protection: Strategies that work great on historical data but fail on new data are automatically identified and penalized. This prevents the population from being polluted by overfitted strategies that would fail in live trading.
🌊 DYNAMIC VOLATILITY SCALING (DVS): ADAPTIVE STOP/TARGET PLACEMENT
AGE doesn't use fixed stop distances. It adapts to current volatility conditions in real-time.
Four Volatility Measurement Methods
1. ATR Ratio (Simple Method):
Current_Vol = ATR(14) / Close
Baseline_Vol = SMA(Current_Vol, 100)
Ratio = Current_Vol / Baseline_Vol
Basic comparison of current ATR to 100-bar moving average baseline.
2. Parkinson (High-Low Range Based):
For each bar: HL = log(High / Low)
Parkinson_Vol = sqrt(Σ(HL²) / (4 × Period × log(2)))
More stable than close-to-close volatility. Captures intraday range expansion without overnight gap noise.
3. Garman-Klass (OHLC Based):
HL_Term = 0.5 × ²
CO_Term = (2×log(2) - 1) × ²
GK_Vol = sqrt(Σ(HL_Term - CO_Term) / Period)
Most sophisticated estimator. Incorporates all four price points (open, high, low, close) plus gap information.
4. Ensemble Method (Default - Median of All Three):
Ratio_1 = ATR_Current / ATR_Baseline
Ratio_2 = Parkinson_Current / Parkinson_Baseline
Ratio_3 = GK_Current / GK_Baseline
DVS_Ratio = Median(Ratio_1, Ratio_2, Ratio_3)
Why Ensemble?
Takes median to avoid outliers and false spikes
If ATR jumps but range-based methods stay calm, median prevents overreaction
If one method fails, other two compensate
Most robust approach across different market conditions
Sensitivity Scaling
Scaled_Ratio = (Raw_Ratio) ^ Sensitivity
Sensitivity 0.3: Cube root - heavily dampens volatility impact
Sensitivity 0.5: Square root - moderate dampening
Sensitivity 0.7 (Default): Balanced response to volatility changes
Sensitivity 1.0: Linear - full 1:1 volatility impact
Sensitivity 1.5: Exponential - amplified response to volatility spikes
Safety Clamps: Final DVS Ratio always clamped between 0.5x and 2.5x baseline to prevent extreme position sizing or stop placement errors.
How DVS Affects Shadow Trading
Every strategy's stop and target distances are multiplied by the current DVS ratio:
Stop Loss Distance:
Stop_Distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit Distance:
Target_Distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Example Scenario:
ATR = 10 points
Strategy's ATR_Mult gene = 2.5
Strategy's Stop_Mult gene = 1.5
Strategy's Target_Mult gene = 2.5
DVS_Ratio = 1.4 (40% above baseline volatility - market heating up)
Stop = 10 × 2.5 × 1.5 × 1.4 = 52.5 points (vs. 37.5 in normal vol)
Target = 10 × 2.5 × 2.5 × 1.4 = 87.5 points (vs. 62.5 in normal vol)
Result:
During volatility spikes: Stops automatically widen to avoid noise-based exits, targets extend for bigger moves
During calm periods: Stops tighten for better risk/reward, targets compress for realistic profit-taking
Strategies adapt risk management to match current market behavior
🧬 THE EVOLUTIONARY CYCLE: SPAWN, COMPETE, CULL
Initialization (Bar 1)
AGE begins with 4 seed strategies (if evolution enabled):
Seed Strategy #0 (Balanced):
All sensitivities at 1.0 (neutral)
Zero probability boost
Moderate trend requirement (0.4)
Standard ATR/stop/target multiples (2.5/1.5/2.5)
Mid-level regime adaptation (0.5)
Seed Strategy #1 (Momentum-Focused):
Lower entropy sensitivity (0.7), higher momentum (1.5)
Slight probability boost (+0.03)
Higher trend requirement (0.5)
Tighter stops (1.3), wider targets (3.0)
Seed Strategy #2 (Entropy-Driven):
Higher entropy sensitivity (1.5), lower momentum (0.8)
Slight probability penalty (-0.02)
More trend tolerant (0.6)
Wider stops (1.8), standard targets (2.5)
Seed Strategy #3 (Structure-Based):
Balanced entropy/momentum (0.8/0.9), high structure (1.4)
Slight probability boost (+0.02)
Lower trend requirement (0.35)
Moderate risk parameters (1.6/2.8)
All seeds start with WFO validation bypassed if WFO is disabled, or must validate if enabled.
Spawning New Strategies
Timing (Adaptive):
Historical phase: Every 30 bars (configurable 10-100)
Live phase: Every 200 bars (configurable 100-500)
Automatically switches to live timing when barstate.isrealtime triggers
Conditions:
Current population < max population limit (default: 8, configurable 4-12)
At least 2 active strategies exist (need parents)
Available slot in population array
Selection Process:
Run tournament selection 3 times with different seeds
Each tournament: randomly sample active strategies, pick highest fitness
Best from 3 tournaments becomes Parent 1
Repeat independently for Parent 2
Ensures fit parents but maintains diversity
Crossover Breeding:
For each of 10 genes:
Parent1_Fitness = fitness
Parent2_Fitness = fitness
Weight1 = Parent1_Fitness / (Parent1_Fitness + Parent2_Fitness)
Gene1 = parent1's value
Gene2 = parent2's value
Child_Gene = Weight1 × Gene1 + (1 - Weight1) × Gene2
Fitness-weighted crossover ensures fitter parent contributes more genetic material.
Mutation:
For each gene in child:
IF (random < mutation_rate):
Gene_Range = GENE_MAX - GENE_MIN
Noise = (random - 0.5) × 2 × mutation_strength × Gene_Range
Mutated_Gene = Clamp(Child_Gene + Noise, GENE_MIN, GENE_MAX)
Historical mutation rate: 20% (aggressive exploration)
Live mutation rate: 8% (conservative stability)
Mutation strength: 12% of gene range (configurable 5-25%)
Initialization of New Strategy:
Unique ID assigned (total_spawned counter)
Parent ID recorded
Generation = max(parent generations) + 1
Birth bar recorded (for age tracking)
All performance metrics zeroed
Shadow portfolio reset
WFO validation flag set to false (must prove itself)
Result: New strategy with hybrid DNA enters population, begins trading in next bar.
Competition (Every Bar)
All active strategies:
Calculate their signal based on unique DNA
Check quality gate with their thresholds
Manage shadow positions (entries/exits)
Update performance metrics
Recalculate fitness score
Track WFO validation progress
Strategies compete indirectly through fitness ranking - no direct interaction.
Culling Weak Strategies
Timing (Adaptive):
Historical phase: Every 60 bars (configurable 20-200, should be 2x spawn interval)
Live phase: Every 400 bars (configurable 200-1000, should be 2x spawn interval)
Minimum Adaptation Score (MAS):
Initial MAS = 0.10
MAS decays: MAS × 0.995 every cull cycle
Minimum MAS = 0.03 (floor)
MAS represents the "survival threshold" - strategies below this fitness level are vulnerable.
Culling Conditions (ALL must be true):
Population > minimum population (default: 3, configurable 2-4)
At least one strategy has fitness < MAS
Strategy's age > culling interval (prevents premature culling of new strategies)
Strategy is not in top N elite (default: 2, configurable 1-3)
Culling Process:
Find worst strategy:
For each active strategy:
IF (age > cull_interval):
Fitness = base_fitness
IF (not WFO_validated AND WFO_enabled):
Fitness × 0.7 // 30% penalty for unvalidated
IF (Fitness < MAS AND Fitness < worst_fitness_found):
worst_strategy = this_strategy
worst_fitness = Fitness
IF (worst_strategy found):
Count elite strategies with fitness > worst_fitness
IF (elite_count >= elite_preservation_count):
Deactivate worst_strategy (set active flag = false)
Increment total_culled counter
Elite Protection:
Even if a strategy's fitness falls below MAS, it survives if fewer than N strategies are better. This prevents culling when population is generally weak.
Result: Weak strategies removed from population, freeing slots for new spawns. Gene pool improves over time.
Selection for Display (Every Bar)
AGE chooses one strategy to display signals:
Best fitness = -1
Selected = none
For each active strategy:
Fitness = base_fitness
IF (WFO_validated):
Fitness × 1.3 // 30% bonus for validated strategies
IF (Fitness > best_fitness):
best_fitness = Fitness
selected_strategy = this_strategy
Display selected strategy's signals on chart
Result: Only the highest-fitness (optionally validated-boosted) strategy's signals appear as chart markers. Other strategies trade invisibly in shadow portfolios.
🎨 PREMIUM VISUALIZATION SYSTEM
AGE includes sophisticated visual feedback that standard indicators lack:
1. Gradient Probability Cloud (Optional, Default: ON)
Multi-layer gradient showing signal buildup 2-3 bars before entry:
Activation Conditions:
Signal persistence > 0 (same directional signal held for multiple bars)
Signal probability ≥ minimum threshold (65% by default)
Signal hasn't yet executed (still in "forming" state)
Visual Construction:
7 gradient layers by default (configurable 3-15)
Each layer is a line-fill pair (top line, bottom line, filled between)
Layer spacing: 0.3 to 1.0 × ATR above/below price
Outer layers = faint, inner layers = bright
Color transitions from base to intense based on layer position
Transparency scales with probability (high prob = more opaque)
Color Selection:
Long signals: Gradient from theme.gradient_bull_mid to theme.gradient_bull_strong
Short signals: Gradient from theme.gradient_bear_mid to theme.gradient_bear_strong
Base transparency: 92%, reduces by up to 8% for high-probability setups
Dynamic Behavior:
Cloud grows/shrinks as signal persistence increases/decreases
Redraws every bar while signal is forming
Disappears when signal executes or invalidates
Performance Note: Computationally expensive due to linefill objects. Disable or reduce layers if chart performance degrades.
2. Population Fitness Ribbon (Optional, Default: ON)
Histogram showing fitness distribution across active strategies:
Activation: Only draws on last bar (barstate.islast) to avoid historical clutter
Visual Construction:
10 histogram layers by default (configurable 5-20)
Plots 50 bars back from current bar
Positioned below price at: lowest_low(100) - 1.5×ATR (doesn't interfere with price action)
Each layer represents a fitness threshold (evenly spaced min to max fitness)
Layer Logic:
For layer_num from 0 to ribbon_layers:
Fitness_threshold = min_fitness + (max_fitness - min_fitness) × (layer / layers)
Count strategies with fitness ≥ threshold
Height = ATR × 0.15 × (count / total_active)
Y_position = base_level + ATR × 0.2 × layer
Color = Gradient from weak to strong based on layer position
Line_width = Scaled by height (taller = thicker)
Visual Feedback:
Tall, bright ribbon = healthy population, many fit strategies at high fitness levels
Short, dim ribbon = weak population, few strategies achieving good fitness
Ribbon compression (layers close together) = population converging to similar fitness
Ribbon spread = diverse fitness range, active selection pressure
Use Case: Quick visual health check without opening dashboard. Ribbon growing upward over time = population improving.
3. Confidence Halo (Optional, Default: ON)
Circular polyline around entry signals showing probability strength:
Activation: Draws when new position opens (shadow_position changes from 0 to ±1)
Visual Construction:
20-segment polyline forming approximate circle
Center: Low - 0.5×ATR (long) or High + 0.5×ATR (short)
Radius: 0.3×ATR (low confidence) to 1.0×ATR (elite confidence)
Scales with: (probability - min_probability) / (1.0 - min_probability)
Color Coding:
Elite (85%+): Cyan (theme.conf_elite), large radius, minimal transparency (40%)
Strong (75-85%): Strong green (theme.conf_strong), medium radius, moderate transparency (50%)
Good (65-75%): Good green (theme.conf_good), smaller radius, more transparent (60%)
Moderate (<65%): Moderate green (theme.conf_moderate), tiny radius, very transparent (70%)
Technical Detail:
Uses chart.point array with index-based positioning
5-bar horizontal spread for circular appearance (±5 bars from entry)
Curved=false (Pine Script polyline limitation)
Fill color matches line color but more transparent (88% vs line's transparency)
Purpose: Instant visual probability assessment. No need to check dashboard - halo size/brightness tells the story.
4. Evolution Event Markers (Optional, Default: ON)
Visual indicators of genetic algorithm activity:
Spawn Markers (Diamond, Cyan):
Plots when total_spawned increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.spawn_marker (cyan/bright blue)
Size: tiny
Indicates new strategy just entered population
Cull Markers (X-Cross, Red):
Plots when total_culled increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.cull_marker (red/pink)
Size: tiny
Indicates weak strategy just removed from population
What It Tells You:
Frequent spawning early = population building, active exploration
Frequent culling early = high selection pressure, weak strategies dying fast
Balanced spawn/cull = healthy evolutionary churn
No markers for long periods = stable population (evolution plateaued or optimal genes found)
5. Entry/Exit Markers
Clear visual signals for selected strategy's trades:
Long Entry (Triangle Up, Green):
Plots when selected strategy opens long position (position changes 0 → +1)
Location: below bar (location.belowbar)
Color: theme.long_primary (green/cyan depending on theme)
Transparency: Scales with probability:
Elite (85%+): 0% (fully opaque)
Strong (75-85%): 10%
Good (65-75%): 20%
Acceptable (55-65%): 35%
Size: small
Short Entry (Triangle Down, Red):
Plots when selected strategy opens short position (position changes 0 → -1)
Location: above bar (location.abovebar)
Color: theme.short_primary (red/pink depending on theme)
Transparency: Same scaling as long entries
Size: small
Exit (X-Cross, Orange):
Plots when selected strategy closes position (position changes ±1 → 0)
Location: absolute (at actual exit price if stop/target lines enabled)
Color: theme.exit_color (orange/yellow depending on theme)
Transparency: 0% (fully opaque)
Size: tiny
Result: Clean, probability-scaled markers that don't clutter chart but convey essential information.
6. Stop Loss & Take Profit Lines (Optional, Default: ON)
Visual representation of shadow portfolio risk levels:
Stop Loss Line:
Plots when selected strategy has active position
Level: shadow_stop value from selected strategy
Color: theme.short_primary with 60% transparency (red/pink, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Take Profit Line:
Plots when selected strategy has active position
Level: shadow_target value from selected strategy
Color: theme.long_primary with 60% transparency (green, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Purpose:
Shows where shadow portfolio would exit for stop/target
Helps visualize strategy's risk/reward ratio
Useful for manual traders to set similar levels
Disable for cleaner chart (recommended for presentations)
7. Dynamic Trend EMA
Gradient-colored trend line that visualizes trend strength:
Calculation:
EMA(close, trend_length) - default 50 period (configurable 20-100)
Slope calculated over 10 bars: (current_ema - ema ) / ema × 100
Color Logic:
Trend_direction:
Slope > 0.1% = Bullish (1)
Slope < -0.1% = Bearish (-1)
Otherwise = Neutral (0)
Trend_strength = abs(slope)
Color = Gradient between:
- Neutral color (gray/purple)
- Strong bullish (bright green) if direction = 1
- Strong bearish (bright red) if direction = -1
Gradient factor = trend_strength (0 to 1+ scale)
Visual Behavior:
Faint gray/purple = weak/no trend (choppy conditions)
Light green/red = emerging trend (low strength)
Bright green/red = strong trend (high conviction)
Color intensity = trend strength magnitude
Transparency: 50% (subtle, doesn't overpower price action)
Purpose: Subconscious awareness of trend state without checking dashboard or indicators.
8. Regime Background Tinting (Subtle)
Ultra-low opacity background color indicating detected market regime:
Regime Detection:
Efficiency = directional_movement / total_range (over trend_length bars)
Vol_ratio = current_volatility / average_volatility
IF (efficiency > 0.5 AND vol_ratio < 1.3):
Regime = Trending (1)
ELSE IF (vol_ratio > 1.5):
Regime = Volatile (2)
ELSE:
Regime = Choppy (0)
Background Colors:
Trending: theme.regime_trending (dark green, 92-93% transparency)
Volatile: theme.regime_volatile (dark red, 93% transparency)
Choppy: No tint (normal background)
Purpose:
Subliminal regime awareness
Helps explain why signals are/aren't generating
Trending = ideal conditions for AGE
Volatile = fewer signals, higher thresholds applied
Choppy = mixed signals, lower confidence
Important: Extremely subtle by design. Not meant to be obvious, just subconscious context.
📊 ENHANCED DASHBOARD
Comprehensive real-time metrics in single organized panel (top-right position):
Dashboard Structure (5 columns × 14 rows)
Header Row:
Column 0: "🧬 AGE PRO" + phase indicator (🔴 LIVE or ⏪ HIST)
Column 1: "POPULATION"
Column 2: "PERFORMANCE"
Column 3: "CURRENT SIGNAL"
Column 4: "ACTIVE STRATEGY"
Column 0: Market State
Regime (📈 TREND / 🌊 CHAOS / ➖ CHOP)
DVS Ratio (current volatility scaling factor, format: #.##)
Trend Direction (▲ BULL / ▼ BEAR / ➖ FLAT with color coding)
Trend Strength (0-100 scale, format: #.##)
Column 1: Population Metrics
Active strategies (count / max_population)
Validated strategies (WFO passed / active total)
Current generation number
Total spawned (all-time strategy births)
Total culled (all-time strategy deaths)
Column 2: Aggregate Performance
Total trades across all active strategies
Aggregate win rate (%) - color-coded:
Green (>55%)
Orange (45-55%)
Red (<45%)
Total P&L in R-multiples - color-coded by positive/negative
Best fitness score in population (format: #.###)
MAS - Minimum Adaptation Score (cull threshold, format: #.###)
Column 3: Current Signal Status
Status indicator:
"▲ LONG" (green) if selected strategy in long position
"▼ SHORT" (red) if selected strategy in short position
"⏳ FORMING" (orange) if signal persisting but not yet executed
"○ WAITING" (gray) if no active signal
Confidence percentage (0-100%, format: #.#%)
Quality assessment:
"🔥 ELITE" (cyan) for 85%+ probability
"✓ STRONG" (bright green) for 75-85%
"○ GOOD" (green) for 65-75%
"- LOW" (dim) for <65%
Confluence score (X/3 format)
Signal age:
"X bars" if signal forming
"IN TRADE" if position active
"---" if no signal
Column 4: Selected Strategy Details
Strategy ID number (#X format)
Validation status:
"✓ VAL" (green) if WFO validated
"○ TRAIN" (orange) if still in training/testing phase
Generation number (GX format)
Personal fitness score (format: #.### with color coding)
Trade count
P&L and win rate (format: #.#R (##%) with color coding)
Color Scheme:
Panel background: theme.panel_bg (dark, low opacity)
Panel headers: theme.panel_header (slightly lighter)
Primary text: theme.text_primary (bright, high contrast)
Secondary text: theme.text_secondary (dim, lower contrast)
Positive metrics: theme.metric_positive (green)
Warning metrics: theme.metric_warning (orange)
Negative metrics: theme.metric_negative (red)
Special markers: theme.validated_marker, theme.spawn_marker
Update Frequency: Only on barstate.islast (current bar) to minimize CPU usage
Purpose:
Quick overview of entire system state
No need to check multiple indicators
Trading decisions informed by population health, regime state, and signal quality
Transparency into what AGE is thinking
🔍 DIAGNOSTICS PANEL (Optional, Default: OFF)
Detailed signal quality tracking for optimization and debugging:
Panel Structure (3 columns × 8 rows)
Position: Bottom-right corner (doesn't interfere with main dashboard)
Header Row:
Column 0: "🔍 DIAGNOSTICS"
Column 1: "COUNT"
Column 2: "%"
Metrics Tracked (for selected strategy only):
Total Evaluated:
Every signal that passed initial calculation (direction ≠ 0)
Represents total opportunities considered
✓ Passed:
Signals that passed quality gate and executed
Green color coding
Percentage of evaluated signals
Rejection Breakdown:
⨯ Probability:
Rejected because probability < minimum threshold
Most common rejection reason typically
⨯ Confluence:
Rejected because confluence < minimum required (e.g., only 1 of 3 indicators agreed)
⨯ Trend:
Rejected because signal opposed strong trend
Indicates counter-trend protection working
⨯ Regime:
Rejected because volatile regime detected and probability wasn't high enough to override
Shows regime filter in action
⨯ Volume:
Rejected because volume < 70% of 20-bar average
Indicates volume confirmation requirement
Color Coding:
Passed count: Green (success metric)
Rejection counts: Red (failure metrics)
Percentages: Gray (neutral, informational)
Performance Cost: Slight CPU overhead for tracking counters. Disable when not actively optimizing settings.
How to Use Diagnostics
Scenario 1: Too Few Signals
Evaluated: 200
Passed: 10 (5%)
⨯ Probability: 120 (60%)
⨯ Confluence: 40 (20%)
⨯ Others: 30 (15%)
Diagnosis: Probability threshold too high for this strategy's DNA.
Solution: Lower min probability from 65% to 60%, or allow strategy more time to evolve better DNA.
Scenario 2: Too Many False Signals
Evaluated: 200
Passed: 80 (40%)
Strategy win rate: 45%
Diagnosis: Quality gate too loose, letting low-quality signals through.
Solution: Raise min probability to 70%, or increase min confluence to 3 (all indicators must agree).
Scenario 3: Regime-Specific Issues
⨯ Regime: 90 (45% of rejections)
Diagnosis: Frequent volatile regime detection blocking otherwise good signals.
Solution: Either accept fewer trades during chaos (recommended), or disable regime filter if you want signals regardless of market state.
Optimization Workflow:
Enable diagnostics
Run 200+ bars
Analyze rejection patterns
Adjust settings based on data
Re-run and compare pass rate
Disable diagnostics when satisfied
⚙️ CONFIGURATION GUIDE
🧬 Evolution Engine Settings
Enable AGE Evolution (Default: ON):
ON: Full genetic algorithm (recommended for best results)
OFF: Uses only 4 seed strategies, no spawning/culling (static population for comparison testing)
Max Population (4-12, Default: 8):
Higher = more diversity, more exploration, slower performance
Lower = faster computation, less exploration, risk of premature convergence
Sweet spot: 6-8 for most use cases
4 = minimum for meaningful evolution
12 = maximum before diminishing returns
Min Population (2-4, Default: 3):
Safety floor - system never culls below this count
Prevents population extinction during harsh selection
Should be at least half of max population
Elite Preservation (1-3, Default: 2):
Top N performers completely immune to culling
Ensures best genes always survive
1 = minimal protection, aggressive selection
2 = balanced (recommended)
3 = conservative, slower gene pool turnover
Historical: Spawn Interval (10-100, Default: 30):
Bars between spawning new strategies during historical data
Lower = faster evolution, more exploration
Higher = slower evolution, more evaluation time per strategy
30 bars = ~1-2 hours on 15min chart
Historical: Cull Interval (20-200, Default: 60):
Bars between culling weak strategies during historical data
Should be 2x spawn interval for balanced churn
Lower = aggressive selection pressure
Higher = patient evaluation
Live: Spawn Interval (100-500, Default: 200):
Bars between spawning during live trading
Much slower than historical for stability
Prevents population chaos during live trading
200 bars = ~1.5 trading days on 15min chart
Live: Cull Interval (200-1000, Default: 400):
Bars between culling during live trading
Should be 2x live spawn interval
Conservative removal during live trading
Historical: Mutation Rate (0.05-0.40, Default: 0.20):
Probability each gene mutates during breeding (20% = 2 out of 10 genes on average)
Higher = more exploration, slower convergence
Lower = more exploitation, faster convergence but risk of local optima
20% balances exploration vs exploitation
Live: Mutation Rate (0.02-0.20, Default: 0.08):
Mutation rate during live trading
Much lower for stability (don't want population to suddenly degrade)
8% = mostly inherits parent genes with small tweaks
Mutation Strength (0.05-0.25, Default: 0.12):
How much genes change when mutated (% of gene's total range)
0.05 = tiny nudges (fine-tuning)
0.12 = moderate jumps (recommended)
0.25 = large leaps (aggressive exploration)
Example: If gene range is 0.5-2.0, 12% strength = ±0.18 possible change
📈 Signal Quality Settings
Min Signal Probability (0.55-0.80, Default: 0.65):
Quality gate threshold - signals below this never generate
0.55-0.60 = More signals, accept lower confidence (higher risk)
0.65 = Institutional-grade balance (recommended)
0.70-0.75 = Fewer but higher-quality signals (conservative)
0.80+ = Very selective, very few signals (ultra-conservative)
Min Confluence Score (1-3, Default: 2):
Required indicator agreement before signal generates
1 = Any single indicator can trigger (not recommended - too many false signals)
2 = Requires 2 of 3 indicators agree (RECOMMENDED for balance)
3 = All 3 must agree (very selective, few signals, high quality)
Base Persistence Bars (1-5, Default: 2):
Base bars signal must persist before entry
System adapts automatically:
High probability signals (75%+) enter 1 bar faster
Low probability signals (<68%) need 1 bar more
Trending regime: -1 bar (faster entries)
Volatile regime: +1 bar (more confirmation)
1 = Immediate entry after quality gate (responsive but prone to whipsaw)
2 = Balanced confirmation (recommended)
3-5 = Patient confirmation (slower but more reliable)
Cooldown After Trade (3-20, Default: 8):
Bars to wait after exit before next entry allowed
Prevents overtrading and revenge trading
3 = Minimal cooldown (active trading)
8 = Balanced (recommended)
15-20 = Conservative (position trading)
Entropy Length (10-50, Default: 20):
Lookback period for market order/disorder calculation
Lower = more responsive to regime changes (noisy)
Higher = more stable regime detection (laggy)
20 = works across most timeframes
Momentum Length (5-30, Default: 14):
Period for RSI/ROC calculations
14 = standard (RSI default)
Lower = more signals, less reliable
Higher = fewer signals, more reliable
Structure Length (20-100, Default: 50):
Lookback for support/resistance swing range
20 = short-term swings (day trading)
50 = medium-term structure (recommended)
100 = major structure (position trading)
Trend EMA Length (20-100, Default: 50):
EMA period for trend detection and direction bias
20 = short-term trend (responsive)
50 = medium-term trend (recommended)
100 = long-term trend (position trading)
ATR Period (5-30, Default: 14):
Period for volatility measurement
14 = standard ATR
Lower = more responsive to vol changes
Higher = smoother vol calculation
📊 Volatility Scaling (DVS) Settings
Enable DVS (Default: ON):
Dynamic volatility scaling for adaptive stop/target placement
Highly recommended to leave ON
OFF only for testing fixed-distance stops
DVS Method (Default: Ensemble):
ATR Ratio: Simple, fast, single-method (good for beginners)
Parkinson: High-low range based (good for intraday)
Garman-Klass: OHLC based (sophisticated, considers gaps)
Ensemble: Median of all three (RECOMMENDED - most robust)
DVS Memory (20-200, Default: 100):
Lookback for baseline volatility comparison
20 = very responsive to vol changes (can overreact)
100 = balanced adaptation (recommended)
200 = slow, stable baseline (minimizes false vol signals)
DVS Sensitivity (0.3-1.5, Default: 0.7):
How much volatility affects scaling (power-law exponent)
0.3 = Conservative, heavily dampens vol impact (cube root)
0.5 = Moderate dampening (square root)
0.7 = Balanced response (recommended)
1.0 = Linear, full 1:1 vol response
1.5 = Aggressive, amplified response (exponential)
🔬 Walk-Forward Optimization Settings
Enable WFO (Default: ON):
Out-of-sample validation to prevent overfitting
Highly recommended to leave ON
OFF only for testing or if you want unvalidated strategies
Training Window (100-500, Default: 250):
Bars for in-sample optimization
100 = fast validation, less data (risky)
250 = balanced (recommended) - about 1-2 months on daily, 1-2 weeks on 15min
500 = patient validation, more data (conservative)
Testing Window (30-200, Default: 75):
Bars for out-of-sample validation
Should be ~30% of training window
30 = minimal test (fast validation)
75 = balanced (recommended)
200 = extensive test (very conservative)
Min Trades for Validation (3-15, Default: 5):
Required trades in BOTH training AND testing periods
3 = minimal sample (risky, fast validation)
5 = balanced (recommended)
10+ = conservative (slow validation, high confidence)
WFO Efficiency Threshold (0.3-0.9, Default: 0.55):
Minimum test/train performance ratio required
0.30 = Very loose (test must be 30% as good as training)
0.55 = Balanced (recommended) - test must be 55% as good
0.70+ = Strict (test must closely match training)
Higher = fewer validated strategies, lower risk of overfitting
🎨 Premium Visuals Settings
Visual Theme:
Neon Genesis: Cyberpunk aesthetic (cyan/magenta/purple)
Carbon Fiber: Industrial look (blue/red/gray)
Quantum Blue: Quantum computing (blue/purple/pink)
Aurora: Northern lights (teal/orange/purple)
⚡ Gradient Probability Cloud (Default: ON):
Multi-layer gradient showing signal buildup
Turn OFF if chart lags or for cleaner look
Cloud Gradient Layers (3-15, Default: 7):
More layers = smoother gradient, more CPU intensive
Fewer layers = faster, blockier appearance
🎗️ Population Fitness Ribbon (Default: ON):
Histogram showing fitness distribution
Turn OFF for cleaner chart
Ribbon Layers (5-20, Default: 10):
More layers = finer fitness detail
Fewer layers = simpler histogram
⭕ Signal Confidence Halo (Default: ON):
Circular indicator around entry signals
Size/brightness scales with probability
Minimal performance cost
🔬 Evolution Event Markers (Default: ON):
Diamond (spawn) and X (cull) markers
Shows genetic algorithm activity
Minimal performance cost
🎯 Stop/Target Lines (Default: ON):
Shows shadow portfolio stop/target levels
Turn OFF for cleaner chart (recommended for screenshots/presentations)
📊 Enhanced Dashboard (Default: ON):
Comprehensive metrics panel
Should stay ON unless you want zero overlays
🔍 Diagnostics Panel (Default: OFF):
Detailed signal rejection tracking
Turn ON when optimizing settings
Turn OFF during normal use (slight performance cost)
📈 USAGE WORKFLOW - HOW TO USE THIS INDICATOR
Phase 1: Initial Setup & Learning
Add AGE to your chart
Recommended timeframes: 15min, 30min, 1H (best signal-to-noise ratio)
Works on: 5min (day trading), 4H (swing trading), Daily (position trading)
Load 1000+ bars for sufficient evolution history
Let the population evolve (100+ bars minimum)
First 50 bars: Random exploration, poor results expected
Bars 50-150: Population converging, fitness improving
Bars 150+: Stable performance, validated strategies emerging
Watch the dashboard metrics
Population should grow toward max capacity
Generation number should advance regularly
Validated strategies counter should increase
Best fitness should trend upward toward 0.50-0.70 range
Observe evolution markers
Diamond markers (cyan) = new strategies spawning
X markers (red) = weak strategies being culled
Frequent early activity = healthy evolution
Activity slowing = population stabilizing
Be patient. Evolution takes time. Don't judge performance before 150+ bars.
Phase 2: Signal Observation
Watch signals form
Gradient cloud builds up 2-3 bars before entry
Cloud brightness = probability strength
Cloud thickness = signal persistence
Check signal quality
Look at confidence halo size when entry marker appears
Large bright halo = elite setup (85%+)
Medium halo = strong setup (75-85%)
Small halo = good setup (65-75%)
Verify market conditions
Check trend EMA color (green = uptrend, red = downtrend, gray = choppy)
Check background tint (green = trending, red = volatile, clear = choppy)
Trending background + aligned signal = ideal conditions
Review dashboard signal status
Current Signal column shows:
Status (Long/Short/Forming/Waiting)
Confidence % (actual probability value)
Quality assessment (Elite/Strong/Good)
Confluence score (2/3 or 3/3 preferred)
Only signals meeting ALL quality gates appear on chart. If you're not seeing signals, population is either still learning or market conditions aren't suitable.
Phase 3: Manual Trading Execution
When Long Signal Fires:
Verify confidence level (dashboard or halo size)
Confirm trend alignment (EMA sloping up, green color)
Check regime (preferably trending or choppy, avoid volatile)
Enter long manually on your broker platform
Set stop loss at displayed stop line level (if lines enabled), or use your own risk management
Set take profit at displayed target line level, or trail manually
Monitor position - exit if X marker appears (signal reversal)
When Short Signal Fires:
Same verification process
Confirm downtrend (EMA sloping down, red color)
Enter short manually
Use displayed stop/target levels or your own
AGE tells you WHEN and HOW CONFIDENT. You decide WHETHER and HOW MUCH.
Phase 4: Set Up Alerts (Never Miss a Signal)
Right-click on indicator name in legend
Select "Add Alert"
Choose condition:
"AGE Long" = Long entry signal fired
"AGE Short" = Short entry signal fired
"AGE Exit" = Position reversal/exit signal
Set notification method:
Sound alert (popup on chart)
Email notification
Webhook to phone/trading platform
Mobile app push notification
Name the alert (e.g., "AGE BTCUSD 15min Long")
Save alert
Recommended: Set alerts for both long and short, enable mobile push notifications. You'll get alerted in real-time even if not watching charts.
Phase 5: Monitor Population Health
Weekly Review:
Check dashboard Population column:
Active count should be near max (6-8 of 8)
Validated count should be >50% of active
Generation should be advancing (1-2 per week typical)
Check dashboard Performance column:
Aggregate win rate should be >50% (target: 55-65%)
Total P&L should be positive (may fluctuate)
Best fitness should be >0.50 (target: 0.55-0.70)
MAS should be declining slowly (normal adaptation)
Check Active Strategy column:
Selected strategy should be validated (✓ VAL)
Personal fitness should match best fitness
Trade count should be accumulating
Win rate should be >50%
Warning Signs:
Zero validated strategies after 300+ bars = settings too strict or market unsuitable
Best fitness stuck <0.30 = population struggling, consider parameter adjustment
No spawning/culling for 200+ bars = evolution stalled (may be optimal or need reset)
Aggregate win rate <45% sustained = system not working on this instrument/timeframe
Health Check Pass:
50%+ strategies validated
Best fitness >0.50
Aggregate win rate >52%
Regular spawn/cull activity
Selected strategy validated
Phase 6: Optimization (If Needed)
Enable Diagnostics Panel (bottom-right) for data-driven tuning:
Problem: Too Few Signals
Evaluated: 200
Passed: 8 (4%)
⨯ Probability: 140 (70%)
Solutions:
Lower min probability: 65% → 60% or 55%
Reduce min confluence: 2 → 1
Lower base persistence: 2 → 1
Increase mutation rate temporarily to explore new genes
Check if regime filter is blocking signals (⨯ Regime high?)
Problem: Too Many False Signals
Evaluated: 200
Passed: 90 (45%)
Win rate: 42%
Solutions:
Raise min probability: 65% → 70% or 75%
Increase min confluence: 2 → 3
Raise base persistence: 2 → 3
Enable WFO if disabled (validates strategies before use)
Check if volume filter is being ignored (⨯ Volume low?)
Problem: Counter-Trend Losses
⨯ Trend: 5 (only 5% rejected)
Losses often occur against trend
Solutions:
System should already filter trend opposition
May need stronger trend requirement
Consider only taking signals aligned with higher timeframe trend
Use longer trend EMA (50 → 100)
Problem: Volatile Market Whipsaws
⨯ Regime: 100 (50% rejected by volatile regime)
Still getting stopped out frequently
Solutions:
System is correctly blocking volatile signals
Losses happening because vol filter isn't strict enough
Consider not trading during volatile periods (respect the regime)
Or disable regime filter and accept higher risk
Optimization Workflow:
Enable diagnostics
Run 200+ bars with current settings
Analyze rejection patterns and win rate
Make ONE change at a time (scientific method)
Re-run 200+ bars and compare results
Keep change if improvement, revert if worse
Disable diagnostics when satisfied
Never change multiple parameters at once - you won't know what worked.
Phase 7: Multi-Instrument Deployment
AGE learns independently on each chart:
Recommended Strategy:
Deploy AGE on 3-5 different instruments
Different asset classes ideal (e.g., ES futures, EURUSD, BTCUSD, SPY, Gold)
Each learns optimal strategies for that instrument's personality
Take signals from all 5 charts
Natural diversification reduces overall risk
Why This Works:
When one market is choppy, others may be trending
Different instruments respond to different news/catalysts
Portfolio-level win rate more stable than single-instrument
Evolution explores different parameter spaces on each chart
Setup:
Same settings across all charts (or customize if preferred)
Set alerts for all
Take every validated signal across all instruments
Position size based on total account (don't overleverage any single signal)
⚠️ REALISTIC EXPECTATIONS - CRITICAL READING
What AGE Can Do
✅ Generate probability-weighted signals using genetic algorithms
✅ Evolve strategies in real-time through natural selection
✅ Validate strategies on out-of-sample data (walk-forward optimization)
✅ Adapt to changing market conditions automatically over time
✅ Provide comprehensive metrics on population health and signal quality
✅ Work on any instrument, any timeframe, any broker
✅ Improve over time as weak strategies are culled and fit strategies breed
What AGE Cannot Do
❌ Win every trade (typical win rate: 55-65% at best)
❌ Predict the future with certainty (markets are probabilistic, not deterministic)
❌ Work perfectly from bar 1 (needs 100-150 bars to learn and stabilize)
❌ Guarantee profits under all market conditions
❌ Replace your trading discipline and risk management
❌ Execute trades automatically (this is an indicator, not a strategy)
❌ Prevent all losses (drawdowns are normal and expected)
❌ Adapt instantly to regime changes (re-learning takes 50-100 bars)
Performance Realities
Typical Performance After Evolution Stabilizes (150+ bars):
Win Rate: 55-65% (excellent for trend-following systems)
Profit Factor: 1.5-2.5 (realistic for validated strategies)
Signal Frequency: 5-15 signals per 100 bars (quality over quantity)
Drawdown Periods: 20-40% of time in equity retracement (normal trading reality)
Max Consecutive Losses: 5-8 losses possible even with 60% win rate (probability says this is normal)
Evolution Timeline:
Bars 0-50: Random exploration, learning phase - poor results expected, don't judge yet
Bars 50-150: Population converging, fitness climbing - results improving
Bars 150-300: Stable performance, most strategies validated - consistent results
Bars 300+: Mature population, optimal genes dominant - best results
Market Condition Dependency:
Trending Markets: AGE excels - clear directional moves, high-probability setups
Choppy Markets: AGE struggles - fewer signals generated, lower win rate
Volatile Markets: AGE cautious - higher rejection rate, wider stops, fewer trades
Market Regime Changes:
When market shifts from trending to choppy overnight
Validated strategies can become temporarily invalidated
AGE will adapt through evolution, but not instantly
Expect 50-100 bar re-learning period after major regime shifts
Fitness may temporarily drop then recover
This is NOT a holy grail. It's a sophisticated signal generator that learns and adapts using genetic algorithms. Your success depends on:
Patience during learning periods (don't abandon after 3 losses)
Proper position sizing (risk 0.5-2% per trade, not 10%)
Following signals consistently (cherry-picking defeats statistical edge)
Not abandoning system prematurely (give it 200+ bars minimum)
Understanding probability (60% win rate means 40% of trades WILL lose)
Respecting market conditions (trending = trade more, choppy = trade less)
Managing emotions (AGE is emotionless, you need to be too)
Expected Drawdowns:
Single-strategy max DD: 10-20% of equity (normal)
Portfolio across multiple instruments: 5-15% (diversification helps)
Losing streaks: 3-5 consecutive losses expected periodically
No indicator eliminates risk. AGE manages risk through:
Quality gates (rejecting low-probability signals)
Confluence requirements (multi-indicator confirmation)
Persistence requirements (no knee-jerk reactions)
Regime awareness (reduced trading in chaos)
Walk-forward validation (preventing overfitting)
But it cannot prevent all losses. That's inherent to trading.
🔧 TECHNICAL SPECIFICATIONS
Platform: TradingView Pine Script v5
Indicator Type: Overlay indicator (plots on price chart)
Execution Type: Signals only - no automatic order placement
Computational Load:
Moderate to High (genetic algorithms + shadow portfolios)
8 strategies × shadow portfolio simulation = significant computation
Premium visuals add additional load (gradient cloud, fitness ribbon)
TradingView Resource Limits (Built-in Caps):
Max Bars Back: 500 (sufficient for WFO and evolution)
Max Labels: 100 (plenty for entry/exit markers)
Max Lines: 150 (adequate for stop/target lines)
Max Boxes: 50 (not heavily used)
Max Polylines: 100 (confidence halos)
Recommended Chart Settings:
Timeframe: 15min to 1H (optimal signal/noise balance)
5min: Works but noisier, more signals
4H/Daily: Works but fewer signals
Bars Loaded: 1000+ (ensures sufficient evolution history)
Replay Mode: Excellent for testing without risk
Performance Optimization Tips:
Disable gradient cloud if chart lags (most CPU intensive visual)
Disable fitness ribbon if still laggy
Reduce cloud layers from 7 to 3
Reduce ribbon layers from 10 to 5
Turn off diagnostics panel unless actively tuning
Close other heavy indicators to free resources
Browser/Platform Compatibility:
Works on all modern browsers (Chrome, Firefox, Safari, Edge)
Mobile app supported (full functionality on phone/tablet)
Desktop app supported (best performance)
Web version supported (may be slower on older computers)
Data Requirements:
Real-time or delayed data both work
No special data feeds required
Works with TradingView's standard data
Historical + live data seamlessly integrated
🎓 THEORETICAL FOUNDATIONS
AGE synthesizes advanced concepts from multiple disciplines:
Evolutionary Computation
Genetic Algorithms (Holland, 1975): Population-based optimization through natural selection metaphor
Tournament Selection: Fitness-based parent selection with diversity preservation
Crossover Operators: Fitness-weighted gene recombination from two parents
Mutation Operators: Random gene perturbation for exploration of new parameter space
Elitism: Preservation of top N performers to prevent loss of best solutions
Adaptive Parameters: Different mutation rates for historical vs. live phases
Technical Analysis
Support/Resistance: Price structure within swing ranges
Trend Following: EMA-based directional bias
Momentum Analysis: RSI, ROC, MACD composite indicators
Volatility Analysis: ATR-based risk scaling
Volume Confirmation: Trade activity validation
Information Theory
Shannon Entropy (1948): Quantification of market order vs. disorder
Signal-to-Noise Ratio: Directional information vs. random walk
Information Content: How much "information" a price move contains
Statistics & Probability
Walk-Forward Analysis: Rolling in-sample/out-of-sample optimization
Out-of-Sample Validation: Testing on unseen data to prevent overfitting
Monte Carlo Principles: Shadow portfolio simulation with realistic execution
Expectancy Theory: Win rate × avg win - loss rate × avg loss
Probability Distributions: Signal confidence quantification
Risk Management
ATR-Based Stops: Volatility-normalized risk per trade
Volatility Regime Detection: Market state classification (trending/choppy/volatile)
Drawdown Control: Peak-to-trough equity measurement
R-Multiple Normalization: Performance measurement in risk units
Machine Learning Concepts
Online Learning: Continuous adaptation as new data arrives
Fitness Functions: Multi-objective optimization (win rate + expectancy + drawdown)
Exploration vs. Exploitation: Balance between trying new strategies and using proven ones
Overfitting Prevention: Walk-forward validation as regularization
Novel Contribution:
AGE is the first TradingView indicator to apply genetic algorithms to real-time indicator parameter optimization while maintaining strict anti-overfitting controls through walk-forward validation.
Most "adaptive" indicators simply recalibrate lookback periods or thresholds. AGE evolves entirely new strategies through competitive selection - it's not parameter tuning, it's Darwinian evolution of trading logic itself.
The combination of:
Genetic algorithm population management
Shadow portfolio simulation for realistic fitness evaluation
Walk-forward validation to prevent overfitting
Multi-indicator confluence for signal quality
Dynamic volatility scaling for adaptive risk
...creates a system that genuinely learns and improves over time while avoiding the curse of curve-fitting that plagues most optimization approaches.
🏗️ DEVELOPMENT NOTES
This project represents months of intensive development, facing significant technical challenges:
Challenge 1: Making Genetics Actually Work
Early versions spawned garbage strategies that polluted the gene pool:
Random gene combinations produced nonsensical parameter sets
Weak strategies survived too long, dragging down population
No clear convergence toward optimal solutions
Solution:
Comprehensive fitness scoring (4 factors: win rate, P&L, expectancy, drawdown)
Elite preservation (top 2 always protected)
Walk-forward validation (unproven strategies penalized 30%)
Tournament selection (fitness-weighted breeding)
Adaptive culling (MAS decay creates increasing selection pressure)
Challenge 2: Balancing Evolution Speed vs. Stability
Too fast = population chaos, no convergence. Too slow = can't adapt to regime changes.
Solution:
Dual-phase timing: Fast evolution during historical (30/60 bar intervals), slow during live (200/400 bar intervals)
Adaptive mutation rates: 20% historical, 8% live
Spawn/cull ratio: Always 2:1 to prevent population collapse
Challenge 3: Shadow Portfolio Accuracy
Needed realistic trade simulation without lookahead bias:
Can't peek at future bars for exits
Must track multiple portfolios simultaneously
Stop/target checks must use bar's high/low correctly
Solution:
Entry on close (realistic)
Exit checks on current bar's high/low (realistic)
Independent position tracking per strategy
Cooldown periods to prevent unrealistic rapid re-entry
ATR-normalized P&L (R-multiples) for fair comparison across volatility regimes
Challenge 4: Pine Script Compilation Limits
Hit TradingView's execution limits multiple times:
Too many array operations
Too many variables
Too complex conditional logic
Solution:
Optimized data structures (single DNA array instead of 8 separate arrays)
Minimal visual overlays (only essential plots)
Efficient fitness calculations (vectorized where possible)
Strategic use of barstate.islast to minimize dashboard updates
Challenge 5: Walk-Forward Implementation
Standard WFO is difficult in Pine Script:
Can't easily "roll forward" through historical data
Can't re-optimize strategies mid-stream
Must work in real-time streaming environment
Solution:
Age-based phase detection (first 250 bars = training, next 75 = testing)
Separate metric tracking for train vs. test
Efficiency calculation at fixed interval (after test period completes)
Validation flag persists for strategy lifetime
Challenge 6: Signal Quality Control
Early versions generated too many signals with poor win rates:
Single indicators produced excessive noise
No trend alignment
No regime awareness
Instant entries on single-bar spikes
Solution:
Three-layer confluence system (entropy + momentum + structure)
Minimum 2-of-3 agreement requirement
Trend alignment checks (penalty for counter-trend)
Regime-based probability adjustments
Persistence requirements (signals must hold multiple bars)
Volume confirmation
Quality gate (probability + confluence thresholds)
The Result
A system that:
Truly evolves (not just parameter sweeps)
Truly validates (out-of-sample testing)
Truly adapts (ongoing competition and breeding)
Stays within TradingView's platform constraints
Provides institutional-quality signals
Maintains transparency (full metrics dashboard)
Development time: 3+ months of iterative refinement
Lines of code: ~1500 (highly optimized)
Test instruments: ES, NQ, EURUSD, BTCUSD, SPY, AAPL
Test timeframes: 5min, 15min, 1H, Daily
🎯 FINAL WORDS
The Adaptive Genesis Engine is not just another indicator - it's a living system that learns, adapts, and improves through the same principles that drive biological evolution. Every bar it observes adds to its experience. Every strategy it spawns explores new parameter combinations. Every strategy it culls removes weakness from the gene pool.
This is evolution in action on your charts.
You're not getting a static formula locked in time. You're getting a system that thinks , that competes , that survives through natural selection. The strongest strategies rise to the top. The weakest die. The gene pool improves generation after generation.
AGE doesn't claim to predict the future - it adapts to whatever the future brings. When markets shift from trending to choppy, from calm to volatile, from bullish to bearish - AGE evolves new strategies suited to the new regime.
Use it on any instrument. Any timeframe. Any market condition. AGE will adapt.
This indicator gives you the pure signal intelligence. How you choose to act on it - position sizing, risk management, execution discipline - that's your responsibility. AGE tells you when and how confident . You decide whether and how much .
Trust the process. Respect the evolution. Let Darwin work.
"In markets, as in nature, it is not the strongest strategies that survive, nor the most intelligent - but those most responsive to change."
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
— Happy Holiday's
