Get started

Supertrend

Quant Flow Supertrend [Quantum Edge]The Quant Flow Supertrend indicator / Strategy is a machine learning trading indicator built to help traders identify trend direction, trend strength, and high-interest rejection areas on the chart. By combining K-Nearest Neighbors classification with Supertrend logic, it transforms traditional trend-following analysis into a smarter, more adaptive trading strategy. The result is a clearer view of bullish and bearish market conditions, stronger confirmation for trend trades, and visual rejection signals that can help traders time entries, exits, and risk management more effectively. How to Trade the Quant flow supertrend Indicator The indicator is designed to do more than a standard Supertrend. Instead of relying only on ATR-based trend shifts, it applies a machine learning model to evaluate whether the current market environment resembles past bullish or bearish conditions. This makes it useful for traders who want a trend indicator, machine learning indicator, and price action confirmation tool in one script. At its core, the indicator helps traders stay aligned with the dominant move while also highlighting points where price may be rejecting a key trend level. This makes it suitable for trend-following strategies, pullback entries, and momentum confirmation. Trend Direction and Market Bias The main trend signal comes from the interaction between the KNN engine and the Supertrend baseline. The machine learning model studies RSI and ATR-related volatility across a historical search window, then classifies the most likely trend state based on similar past market behavior. When the machine learning output agrees with the Supertrend direction, the indicator displays a colored horizon on the chart. This gives traders a fast way to read bias: A bullish horizon suggests buyers are in control and price is trading in a higher-probability uptrend environment. A bearish horizon suggests sellers are in control and price is trading in a higher-probability downtrend environment. A weaker or less convincing visual state can suggest trend fatigue, indecision, or a market entering consolidation. This structure makes the tool useful as both a trend confirmation indicator and a market regime filter. 3D Rejection Orbs for Entry and Exit Clues One of the standout features of this trading indicator is the 3D Rejection Orbs, which appear when price reacts sharply around the Supertrend level and leaves behind a meaningful wick. These signals are designed to highlight moments where the market appears to reject continuation in one direction and respond strongly at the trend baseline. The size of each orb changes dynamically based on relative volume. A label attached to the orb displays the exact volume of the rejection candle. These signals can help traders spot potential pullback entries, defensive exits, or local exhaustion areas. In bullish conditions, traders may interpret rejection orbs near support as signs that buyers are stepping back in. In bearish conditions, rejection orbs near resistance can suggest renewed selling pressure. While these signals are not meant to be used in isolation, they can be powerful when combined with broader trend direction and market structure. Confidence-Based Candle Coloring The indicator also includes Liquid Smooth gradient candle coloring to visualize machine learning confidence. This is more than cosmetic. It provides an immediate read on whether the current trend has strong conviction or is beginning to lose momentum. Brighter and more vibrant colors suggest stronger confidence from the ML engine. More muted tones can indicate weakening momentum or a lower-confidence trend phase. Smooth transitions help traders avoid overreacting to small shifts in market noise. This feature can be especially helpful for traders who want a more intuitive read on whether a trend still has strength behind it. Why This Machine Learning Trading Indicator Stands Out Unlike a standard Supertrend indicator, the quant flow uses historical pattern recognition to filter trend signals. Traditional indicators can react too quickly in choppy conditions or lag during important transitions. By adding a KNN classifier, this script attempts to distinguish between meaningful directional moves and weaker, lower-quality fluctuations. That makes it valuable for traders looking for: A machine learning trading strategy framework A trend-following indicator with added intelligence A tool for combining volatility analysis, RSI behavior, and price rejection signals A visual system for reading trend strength, market bias, and possible reversal reactions How the it Works The machine learning component scans the current market using RSI and ATR-based volatility as its main features. It then compares the current state to previous bars inside the selected Search Window and finds the closest historical matches using the chosen number of K-Neighbors. From there, the indicator estimates whether current conditions more closely resemble prior bullish or bearish setups. This output is then filtered through a confidence buffer so that only stronger directional probabilities are allowed to influence the trend state. By requiring both machine learning confirmation and Supertrend alignment, the indicator reduces weak flips and improves the readability of the chart. In practice, this can help traders avoid some of the noise that often affects standalone trend indicators. Key Features Traders Can Use Machine Learning Trend Classification The KNN engine brings adaptive behavior to the script by evaluating whether the present setup resembles bullish or bearish conditions from the past. This adds a statistical layer to trend analysis and can improve decision-making when markets are not moving cleanly. Supertrend-Based Structure The Supertrend component acts as the structural backbone of the indicator. It creates the trend baseline that price interacts with and helps define where rejection signals and directional alignment matter most. Volume-Aware Rejection Signals The 3D Rejection Orbs are designed to call attention to candles that show strong rejection behavior near the trend level. Since orb size is tied to relative volume, higher-interest reactions stand out more clearly on the chart. Confidence Gradients The smooth candle and horizon gradients help traders judge the strength of the current move at a glance. This can be useful for managing trades, avoiding low-conviction environments, and reading the quality of a breakout or pullback. Real-Time Dashboard The built-in dashboard gives traders a compact summary of the current market state, including direction, machine learning confidence, and relative volatility. This is useful for fast chart analysis and for confirming whether a setup matches the broader environment. Indicator Settings Explained SETTINGS Machine Learning Settings K-Neighbors: Sets how many historical neighbors the KNN algorithm uses to classify the current trend direction. Lower values can make the model more reactive, while higher values may smooth the output and focus on broader similarity. Search Window: Defines how many past bars are scanned to find similar historical conditions. A larger search window provides more pattern history, while a smaller one focuses the model on more recent behavior. Supertrend Settings ATR Length: Controls the lookback period for the Average True Range calculation. This affects how the Supertrend adapts to market volatility. Factor: Sets the ATR multiplier used to place the Supertrend line above or below price. Higher values generally create a wider, slower trend baseline, while lower values make it more responsive. Noise Filter Settings Smooth Price Input: Applies HMA smoothing to the price source used in the machine learning features. This can reduce market noise and create cleaner classifications. ML Confidence Buffer (%): Defines how far above or below the midpoint probability the ML signal must move before a trend change is accepted. This is useful for preventing choppy signal flips. Rejection Signal Settings Show 3D Rejection Orbs: Turns the volume-based rejection bubbles on or off. Min Wick-to-Body Multiplier: Sets the minimum wick-to-body ratio required for a candle to qualify as a rejection signal. Min Bubble Gap: Defines the minimum spacing in bars between consecutive rejection orb signals, helping reduce clutter. Visual & Dashboard Settings Liquid Smoothness: Controls the EMA smoothing applied to machine learning confidence for the candle and horizon gradients. Vibrancy: Adjusts the intensity of the visual gradients for traders who want more or less pronounced coloring. Show Dashboard: Toggles the on-chart statistics panel showing trend direction, ML confidence, and relative volatility. Best Ways to Use This Trading Strategy Indicator Trend-Following Confirmation Traders can use the horizon direction and confidence coloring to confirm whether a trend is strong enough to trade. This is especially useful for filtering breakout trades or staying in trend positions longer. Pullback Entries When price pulls back toward the Supertrend level and forms a rejection orb, traders may use that area as a potential continuation setup. This approach can be effective when the broader trend remains intact and the machine learning confidence stays supportive. Trade Management The gradient candle colors can help traders gauge whether trend conviction is strengthening or fading. This can support decisions around holding, scaling out, or tightening stops. Sideways Market Filtering Because the machine learning confidence can weaken in indecisive conditions, the indicator can also help traders avoid low-quality environments where standard trend indicators often get chopped up. Is Quant flow Supertrend a trend indicator or a trading strategy? It can be used as both. At its core, it is a trend indicator, but many traders can build a full trading strategy around it by combining trend direction, rejection orb signals, and confidence gradients with their own entry and risk rules. What are the 3D Rejection Orbs used for? The 3D Rejection Orbs highlight candles that reject the Supertrend area with meaningful wick structure and relative volume. Traders can use them as potential clues for pullback entries, exits, or exhaustion points. Who is this indicator best for? This trading indicator can be useful for trend traders, swing traders, and active chart users who want more than a basic Supertrend. It is especially appealing to traders interested in machine learning indicators, trend strength analysis, and volume-based rejection signals. .
Pine Script® indicator
by Prolific-Prophets
Signal Engine Quantum EdgeSignal Engine — Quantum Edge Capital Signal Engine is a fully automated SuperTrend-based strategy built for precision trend detection and backtestable execution. Powered by a dual ATR calculation engine and adaptive trend bands, it identifies the exact moment a trend flips — entering long on bullish reversals and short on bearish reversals with zero ambiguity. How It Works The strategy constructs dynamic upper and lower ATR bands around a source price (hl2 by default). As price holds above the lower band, the system remains in an uptrend — the band trails price upward and never retraces. The moment price closes below the trailing band, trend flips bearish and a sell signal is generated. The inverse logic applies on the long side. This ratcheting mechanism filters out noise while staying locked to momentum. Key Features Dual ATR Mode — toggle between standard ATR (ta.atr) and a smoothed SMA-of-True-Range calculation for different market conditions Adaptive Trend Bands — upper and lower bands that only move in the direction of the trend, preventing whipsaw flips Buy/Sell Signal Labels — optional labels plotted directly on the chart at confirmed trend change bars Trend Highlight Zones — optional green/red fill between price and the active trend band for instant visual bias confirmation Bar Coloring — bars color green or red based on which signal fired most recently, keeping trend state front and center Date Range Backtesting — configurable From/To date window to isolate and test any historical period with precision Strategy Entries — auto-executes BUY (long) and SELL (short) entries directly in TradingView's strategy engine for full P&L reporting Inputs Setting Description ATR Period Lookback length for ATR volatility calculation Source Price input for band calculation (default: hl2) ATR Multiplier Band width multiplier — lower = tighter/more signals, higher = wider/stronger signals Change ATR Method Toggle between standard ATR and SMA-of-True-Range Show Buy/Sell Signals Display optional Buy/Sell text labels on the chart Highlighter On/Off Toggle trend fill zones between price and band Bar Coloring On/Off Toggle green/red bar coloring based on active trend Date Range From/To date window for backtesting a specific period Best Used On ES, NQ, GC, SI, SPY, QQQ — performs best on the 5-minute through daily timeframes. Use alongside HTF structure, liquidity sweeps, and SMT divergence for confirmation before taking strategy entries. Treat the trend flip signal as the bias confirmation, not a standalone entry trigger. Built by Quantum Edge Capital. For educational and informational purposes only. Not financial advice.
Pine Script® strategy
by Prolific-Prophets
Ultimate Supertrend [Quantum Edge]Here is a clean, professional TradingView description for your Quant SuperTrend indicator: Quant SuperTrend — Quantum Edge Capital Quant SuperTrend is a dynamic trend-following indicator built on an ATR-based trailing stop engine. It continuously adapts to market volatility to identify high-probability trend shifts in real time — keeping you on the right side of price action without the noise. How It Works The indicator calculates an ATR trailing stop that tightens and expands based on current volatility. When price crosses above the trailing stop, a Buy signal is generated. When price crosses below, a Sell signal fires. Bar coloring reinforces trend state — green bars during uptrends, red bars during downtrends — giving you an instant visual read of market bias at a glance. Key Features ATR Trailing Stop Engine — volatility-adaptive stop level that moves with price to lock in trend direction Buy/Sell Signal Labels — clearly plotted above/below bars at confirmed crossover points Gradient Bar Coloring — green during bullish trend, red during bearish trend Heikin Ashi Mode — optional toggle to calculate signals from Heikin Ashi candles for smoother, noise-reduced entries Built-in Alerts — pre-configured UT Long and UT Short alert conditions ready to fire to any webhook, SMS, or email Inputs Setting Description Key Value Sensitivity multiplier — lower = more signals, higher = fewer/stronger signals ATR Period Lookback length for ATR volatility calculation Heikin Ashi Candles Toggle to use HA close price as the signal source Best Used On ES, NQ, GC, SI, SPY, QQQ — optimized for intraday and swing timeframes. Combine with HTF structure, liquidity levels, and SMT confirmation for highest-quality entries aligned with the God's Plan framework. Built by Quantum Edge Capital. For educational and informational purposes only. Not financial advice.
Pine Script® indicator
by Prolific-Prophets
ML Supertrend [Quantum Edge]The Quant Flow Supertrend indicator / Strategy is a machine learning trading indicator built to help traders identify trend direction, trend strength, and high-interest rejection areas on the chart. By combining K-Nearest Neighbors classification with Supertrend logic, it transforms traditional trend-following analysis into a smarter, more adaptive trading strategy. The result is a clearer view of bullish and bearish market conditions, stronger confirmation for trend trades, and visual rejection signals that can help traders time entries, exits, and risk management more effectively. How to Trade the Quant flow supertrend Indicator The indicator is designed to do more than a standard Supertrend. Instead of relying only on ATR-based trend shifts, it applies a machine learning model to evaluate whether the current market environment resembles past bullish or bearish conditions. This makes it useful for traders who want a trend indicator, machine learning indicator, and price action confirmation tool in one script. At its core, the indicator helps traders stay aligned with the dominant move while also highlighting points where price may be rejecting a key trend level. This makes it suitable for trend-following strategies, pullback entries, and momentum confirmation. Trend Direction and Market Bias The main trend signal comes from the interaction between the KNN engine and the Supertrend baseline. The machine learning model studies RSI and ATR-related volatility across a historical search window, then classifies the most likely trend state based on similar past market behavior. When the machine learning output agrees with the Supertrend direction, the indicator displays a colored horizon on the chart. This gives traders a fast way to read bias: A bullish horizon suggests buyers are in control and price is trading in a higher-probability uptrend environment. A bearish horizon suggests sellers are in control and price is trading in a higher-probability downtrend environment. A weaker or less convincing visual state can suggest trend fatigue, indecision, or a market entering consolidation. This structure makes the tool useful as both a trend confirmation indicator and a market regime filter. 3D Rejection Orbs for Entry and Exit Clues One of the standout features of this trading indicator is the 3D Rejection Orbs, which appear when price reacts sharply around the Supertrend level and leaves behind a meaningful wick. These signals are designed to highlight moments where the market appears to reject continuation in one direction and respond strongly at the trend baseline. The size of each orb changes dynamically based on relative volume. A label attached to the orb displays the exact volume of the rejection candle. These signals can help traders spot potential pullback entries, defensive exits, or local exhaustion areas. In bullish conditions, traders may interpret rejection orbs near support as signs that buyers are stepping back in. In bearish conditions, rejection orbs near resistance can suggest renewed selling pressure. While these signals are not meant to be used in isolation, they can be powerful when combined with broader trend direction and market structure. Confidence-Based Candle Coloring The indicator also includes Liquid Smooth gradient candle coloring to visualize machine learning confidence. This is more than cosmetic. It provides an immediate read on whether the current trend has strong conviction or is beginning to lose momentum. Brighter and more vibrant colors suggest stronger confidence from the ML engine. More muted tones can indicate weakening momentum or a lower-confidence trend phase. Smooth transitions help traders avoid overreacting to small shifts in market noise. This feature can be especially helpful for traders who want a more intuitive read on whether a trend still has strength behind it. Why This Machine Learning Trading Indicator Stands Out Unlike a standard Supertrend indicator, the quant flow uses historical pattern recognition to filter trend signals. Traditional indicators can react too quickly in choppy conditions or lag during important transitions. By adding a KNN classifier, this script attempts to distinguish between meaningful directional moves and weaker, lower-quality fluctuations. That makes it valuable for traders looking for: A machine learning trading strategy framework A trend-following indicator with added intelligence A tool for combining volatility analysis, RSI behavior, and price rejection signals A visual system for reading trend strength, market bias, and possible reversal reactions How the it Works The machine learning component scans the current market using RSI and ATR-based volatility as its main features. It then compares the current state to previous bars inside the selected Search Window and finds the closest historical matches using the chosen number of K-Neighbors. From there, the indicator estimates whether current conditions more closely resemble prior bullish or bearish setups. This output is then filtered through a confidence buffer so that only stronger directional probabilities are allowed to influence the trend state. By requiring both machine learning confirmation and Supertrend alignment, the indicator reduces weak flips and improves the readability of the chart. In practice, this can help traders avoid some of the noise that often affects standalone trend indicators. Key Features Traders Can Use Machine Learning Trend Classification The KNN engine brings adaptive behavior to the script by evaluating whether the present setup resembles bullish or bearish conditions from the past. This adds a statistical layer to trend analysis and can improve decision-making when markets are not moving cleanly. Supertrend-Based Structure The Supertrend component acts as the structural backbone of the indicator. It creates the trend baseline that price interacts with and helps define where rejection signals and directional alignment matter most. Volume-Aware Rejection Signals The 3D Rejection Orbs are designed to call attention to candles that show strong rejection behavior near the trend level. Since orb size is tied to relative volume, higher-interest reactions stand out more clearly on the chart. Confidence Gradients The smooth candle and horizon gradients help traders judge the strength of the current move at a glance. This can be useful for managing trades, avoiding low-conviction environments, and reading the quality of a breakout or pullback. Real-Time Dashboard The built-in dashboard gives traders a compact summary of the current market state, including direction, machine learning confidence, and relative volatility. This is useful for fast chart analysis and for confirming whether a setup matches the broader environment. Indicator Settings Explained SETTINGS Machine Learning Settings K-Neighbors: Sets how many historical neighbors the KNN algorithm uses to classify the current trend direction. Lower values can make the model more reactive, while higher values may smooth the output and focus on broader similarity. Search Window: Defines how many past bars are scanned to find similar historical conditions. A larger search window provides more pattern history, while a smaller one focuses the model on more recent behavior. Supertrend Settings ATR Length: Controls the lookback period for the Average True Range calculation. This affects how the Supertrend adapts to market volatility. Factor: Sets the ATR multiplier used to place the Supertrend line above or below price. Higher values generally create a wider, slower trend baseline, while lower values make it more responsive. Noise Filter Settings Smooth Price Input: Applies HMA smoothing to the price source used in the machine learning features. This can reduce market noise and create cleaner classifications. ML Confidence Buffer (%): Defines how far above or below the midpoint probability the ML signal must move before a trend change is accepted. This is useful for preventing choppy signal flips. Rejection Signal Settings Show 3D Rejection Orbs: Turns the volume-based rejection bubbles on or off. Min Wick-to-Body Multiplier: Sets the minimum wick-to-body ratio required for a candle to qualify as a rejection signal. Min Bubble Gap: Defines the minimum spacing in bars between consecutive rejection orb signals, helping reduce clutter. Visual & Dashboard Settings Liquid Smoothness: Controls the EMA smoothing applied to machine learning confidence for the candle and horizon gradients. Vibrancy: Adjusts the intensity of the visual gradients for traders who want more or less pronounced coloring. Show Dashboard: Toggles the on-chart statistics panel showing trend direction, ML confidence, and relative volatility. Best Ways to Use This Trading Strategy Indicator Trend-Following Confirmation Traders can use the horizon direction and confidence coloring to confirm whether a trend is strong enough to trade. This is especially useful for filtering breakout trades or staying in trend positions longer. Pullback Entries When price pulls back toward the Supertrend level and forms a rejection orb, traders may use that area as a potential continuation setup. This approach can be effective when the broader trend remains intact and the machine learning confidence stays supportive. Trade Management The gradient candle colors can help traders gauge whether trend conviction is strengthening or fading. This can support decisions around holding, scaling out, or tightening stops. Sideways Market Filtering Because the machine learning confidence can weaken in indecisive conditions, the indicator can also help traders avoid low-quality environments where standard trend indicators often get chopped up. Is Quant flow Supertrend a trend indicator or a trading strategy? It can be used as both. At its core, it is a trend indicator, but many traders can build a full trading strategy around it by combining trend direction, rejection orb signals, and confidence gradients with their own entry and risk rules. What are the 3D Rejection Orbs used for? The 3D Rejection Orbs highlight candles that reject the Supertrend area with meaningful wick structure and relative volume. Traders can use them as potential clues for pullback entries, exits, or exhaustion points. Who is this indicator best for? This trading indicator can be useful for trend traders, swing traders, and active chart users who want more than a basic Supertrend. It is especially appealing to traders interested in machine learning indicators, trend strength analysis, and volume-based rejection signals.
Pine Script® indicator
by Prolific-Prophets
Adaptive Trend Intelligence + SMC + RVOL + ML - FloAlgoThis indicator combines an Adaptive SuperTrend with Smart Money Concepts (SMC) market structure, Relative Volume (RVOL) filtering, and an online Machine Learning model to produce high-confidence trend-following signals. How It Works Adaptive SuperTrend — A SuperTrend band whose ATR multiplier scales automatically based on the short/long volatility ratio. In quiet markets the band tightens; in expansions it widens. An optional noise filter requires price to hold on the new side for N bars before a flip is accepted, eliminating whipsaws. SMC Market Structure Engine — Uses a Stochastic Momentum Oscillator to detect overbought/oversold pivots and build an alternating High/Low swing chain. From those swings it tracks Dow-Theory labels (HH, HL, LH, LL), draws a zigzag, plots S/R zones, and detects BOS (Break of Structure) when price closes beyond the previous major swing confirming trend continuation, and CHoCH (Change of Character) when price closes beyond the prior opposing major swing signaling a trend flip. Both events require an established trend direction and fire only against the correct structural level, preventing false signals on internal corrections. RVOL Filter — Computes directional buy/sell volume from candle structure and ranks it against a rolling percentile. Signals are suppressed unless the directional volume percentile clears a configurable threshold, keeping entries to high-participation moves only. Online ML Model — A logistic regression model with L2 regularisation trained incrementally on every confirmed SuperTrend flip. It learns 17 features per signal including candle shape, volume, momentum, ATR slope, RSI, Bollinger position, RVOL, and SMC bias, then resolves each trade when the next flip occurs. Probability is displayed in the info table and can gate signals via a minimum confidence threshold. Visual Elements SuperTrend line with bull/bear fill ▲ / ▼ signal arrows and labels BOS / CHoCH labels at structure breaks HH / HL / LH / LL Dow labels at each pivot Zigzag lines connecting momentum pivots S/R zone boxes, colour-coded and fading on break Info table showing Signal, Trend, ML Confidence, RVOL, Momentum, Volatility, Quality, MS Bias, and last Structure event Key Settings ATR Length — lookback for ATR calculation ATR Multiplier — base band width Adaptive Multiplier — auto-scales multiplier with volatility ratio Noise Filter (bars) — bars price must hold before flip is confirmed RVOL Lookback — rolling window for volume percentile ranking RVOL Min Percentile % — minimum directional volume percentile to allow a signal Min ML Probability % — minimum ML model confidence to allow a signal Stochastic Length — sensitivity of the momentum pivot oscillator Overbought / Oversold — stochastic zone thresholds for pivot detection Filter Signals by MS — gate signals to align with SMC trend direction Max S/R Zones per Side — maximum supply/demand boxes kept on chart
Pine Script® indicator
by FloAlgo
Contrarian Level Strength PRO Contrarian Level Strength PRO is a discretionary trading assistant designed to analyze how price approaches manually defined support and resistance levels. The indicator focuses on the structure, strength and context of price movement before the level is reached, helping traders evaluate whether a contrarian reaction is statistically more favorable or whether momentum is strong enough to avoid fading the move. The script does not generate automatic buy/sell signals. Instead, it provides contextual information intended to support discretionary execution. Core concepts used internally: * ATR-based volatility normalization * Relative arrival speed calculation * Volume expansion and contraction analysis * Compression and overextension filters * Liquidity sweep detection * False breakout recognition * Multi-timeframe EMA directional context * Supertrend filtering * Historical level quality analysis * Contrarian probability scoring Main features: * Multi-symbol manual level profiles * Weighted support/resistance levels * Arrival strength score from 1 to 100 * Long vs Short probability estimation * Liquidity sweep detection * Fake breakout analysis * ATR-based target and stop projections * Technical trade management assistance * Level invalidation logic * Temporary contextual labels * Dashboard with statistical tracking * Supertrend directional filter * Multi-timeframe directional bias Typical interpretation: * Low arrival strength + rejection/sweep = possible contrarian opportunity * Strong breakout momentum = avoid fading the move * Fresh levels generally provide higher reaction probability than heavily tested levels The indicator is designed for traders using discretionary price action and liquidity-based execution models rather than fully automated systems. Why manual levels? The script intentionally uses trader-defined levels because many institutional liquidity reactions occur around discretionary market structure areas that are difficult to standardize algorithmically. English translation of interface labels: * “Forza arrivo” = Arrival strength * “Livello attivo” = Active level * “Probabilità” = Probability * “Qualità livello” = Level quality * “Pre-avviso” = Pre-alert * “Stato trade” = Trade status * “Proteggi trade” = Protect trade * “Livello invalidato” = Level invalidated Recommended usage: * Define important support/resistance zones manually * Wait for price approach * Evaluate arrival strength and reaction quality * Avoid fading extremely strong momentum * Use confirmation logic before execution This script is intended as a decision-support tool and should not be considered financial advice.
Pine Script® indicator
by marinobortoluzzi
1
XAUUSD ML Supertrend [MatsukazeAlgo]🇬🇧 ENGLISH A Gold-optimized version of the Machine Learning Supertrend. The original engine — SuperTrend foundation with three adaptive learning layers (Global Optimizer, Micro-Batch Processor, and Regime Grid) — is preserved. Four Gold-specific layers are added: session filtering, DXY bias, psychological level TP boost, and a Session-Aware Regime Grid that replaces trend-strength axes with Asia / London / NY session identifiers. Concepts Machine Learning SuperTrend — The original indicator fires entry signals when a volatility band flips direction (Reversal mode) or when price pushes to a new extreme within a trend (Breakout mode). What makes it adaptive is the background simulation: every signal opens a simulated trade, and the results continuously feed three learning systems that adjust the underlying parameters. The longer it runs, the more the engine reflects the current market's character. Three Adaptive Layers — The Global Optimizer monitors rolling win rate, Sortino ratio, and profit factor to propose parameter changes. The Micro-Batch Processor groups results into mini-batches for faster short-term adjustments. The Regime Grid is a 2D memory map that remembers what settings worked under similar conditions (trend strength × volatility) and biases proposals accordingly. These three layers run in parallel, reinforcing each other. Session-Aware Regime Grid — On Gold, the relevant "conditions" are not just trend strength and volatility — they are which session is active. Asia builds range. London breaks it. NY follows through or reverses. This version replaces the volatility axis of the Regime Grid with a session axis (Asia = 0.15, London = 0.5, NY = 0.85). The ML engine now learns optimal parameters per session rather than per generic market regime. Asia settings become distinct from London settings over time. DXY Bias — Gold and the US Dollar Index move inversely. When DXY is weakening (below its EMA), bullish signals are permitted. When DXY is strengthening, bearish signals are permitted. Signals that fight the macro Gold/Dollar relationship are filtered out before they reach the chart. Psychological Level TP Boost — Gold respects $50 and $100 round numbers as institutional order clusters. When an entry signal occurs near one of these levels, the simulated trade target is extended by a configurable ATR bonus. This tells the adaptive engine that psychological level entries have more room, producing more accurate learning near round numbers. How It Works 1. SuperTrend bands are calculated using the configured lookback, smoothing, and band width. 2. Signals fire in Reversal mode (band flip with trend exhaustion) or Breakout mode (new extreme within trend). 3. Session filter blocks signals during excluded sessions. Asia is excluded by default. 4. DXY filter blocks signals that oppose the Dollar trend. 5. Each signal opens a background simulated trade. Outcome is scored and fed to the three adaptive layers. 6. Session-aware Regime Grid maps performance by session, not just volatility × trend strength. 7. Psych level entries get extended TP in simulation, improving learning accuracy near round numbers. 8. Dashboard shows current session, DXY state, signal mode, and live performance metrics. Gold-Specific Features Session Filter — Individual toggles for Asia / London / NY. Asia is OFF by default. Gold's Asia session is dominated by thin liquidity and stop runs that produce unreliable signals. London and NY carry institutional volume. DXY Bias — Bullish signals only when DXY is below its EMA. Bearish signals only when DXY is above it. Configurable EMA period. Psychological Level TP Boost — When entry is within the configured proximity of a $25, $50, or $100 round number, the simulated TP is extended by the configured ATR bonus. The ML engine learns that these entries have more follow-through, adjusting parameters accordingly. Session-Aware Regime Grid — Replaces trend-strength as the X-axis with session identity. The engine builds separate parameter memory for Asia, London, and NY. Over time, it discovers that Asia requires different band widths than London. Dashboard — Shows current session, DXY state, signal mode, active parameters, and simulated win rates per session. Disabled by default. Session Background — Optional coloured background per session (Asia=rose, London=teal, NY=sky). OFF by default. Alerts All original alert types are preserved: Long Signal, Short Signal. These fire only for session-allowed, DXY-confirmed signals. Input Reference Gold Settings — Session Filter: master toggle with individual Asia/London/NY toggles. DXY Bias: enable/disable with DXY symbol and trend EMA period. Psych Level TP Boost: enable/disable with interval ($25/$50/$100), proximity ($), and ATR bonus multiplier. Session-Aware Regime Grid: toggle to use session as Regime Grid X-axis. Dashboard: show/hide. Session Background: show/hide. Signal Mode (①) — Signal Type (Reversal/Breakout), Require Fresh Pivot, Signal Spacing. Volatility Envelope (②) — Lookback Window, Smoothing Period, Band Width (most impactful setting), Price Basis, True Range Mode. Momentum Filter (③) — RSI length and hot/cold zone memory. Flow Analysis (④) — Volume sample depth and surge threshold. Adaptive Engine (⑤–⑥) — Learning rate, batch size, Regime Grid resolution, Reactivity / Master Dial. Conclusion XAUUSD ML Supertrend adds Gold's three-session structure to one of the most powerful adaptive trend indicators on TradingView. The machine learning engine no longer treats Asia, London, and NY the same — it learns them separately. DXY alignment removes signals that fight the macro Gold/Dollar relationship. Psychological level awareness improves simulation accuracy near the round numbers that Gold consistently respects. The original engine by Zimord is preserved in full. The Gold additions layer on top without touching the core learning architecture. --- Based on Machine Learning Supertrend by Zimord . This version adds session filtering (Asia/London/NY), DXY bias filter, psychological level TP boost, session-aware Regime Grid, and MatsukazeAlgo session palette. --- 🇯🇵 日本語 Machine Learning Supertrendのゴールド最適化版です。オリジナルエンジン（SuperTrend基盤 + グローバルオプティマイザー、マイクロバッチプロセッサー、レジームグリッドの3層学習）を完全保持。セッションフィルター、DXYバイアス、心理的価格帯TP延長、セッション対応レジームグリッドの4つのゴールド専用レイヤーを追加。 コンセプト 機械学習スーパートレンド — オリジナルはボラティリティバンドの反転（Reversalモード）または新高値/安値（Breakoutモード）でシグナルを発火。バックグラウンドシミュレーションが全シグナルをトレースし、3つの学習システムに結果を供給して継続的にパラメータを調整。稼働時間が長いほど、現在の市場特性を反映した設定になる。 3つの適応レイヤー — グローバルオプティマイザーがローリング勝率・ソルティノ比率・プロフィットファクターを監視。マイクロバッチプロセッサーが結果をミニバッチに分類して素早い短期調整を実施。レジームグリッドが類似条件下で効果的だった設定を記憶してプロポーザルにバイアスをかける。 セッション対応レジームグリッド — ゴールドで重要な「条件」はトレンド強度とボラティリティだけでない。どのセッションが動いているかが決定的。東京はレンジ形成、ロンドンはブレイク、NYは継続または反転。このバージョンではレジームグリッドのX軸をボラティリティからセッション（Asia=0.15、London=0.5、NY=0.85）に置き換え。MLエンジンが汎用的な市場レジームではなくセッションごとに最適パラメータを学習。 DXYバイアス — ゴールドとドル指数は逆相関。DXYがEMAを下回る時のみ強気シグナルを許可。マクロなゴールド/ドル関係に逆らうシグナルをフィルター。 心理的価格帯TP延長 — ゴールドは$50/$100のラウンドナンバーを機関投資家の注文クラスターとしてリスペクト。シグナルがこれらの価格帯付近で発生した場合、シミュレーションTPをATRボーナス分延長。適応エンジンが心理的価格帯エントリーの余地を正確に学習。 ゴールド専用機能 セッションフィルター — Asia/London/NYの個別トグル。Asiaはデフォルトでオフ。薄商いと流動性スイープが多いアジアを除外することで、信頼性の高いシグナルのみを許可。 DXYバイアス — DXYがEMA以下の場合のみ強気シグナル、EMA以上の場合のみ弱気シグナル。設定可能なEMA期間。 心理的価格帯TP延長 — $25/$50/$100のラウンドナンバー付近のエントリーでシミュレーションTPをATRボーナス分延長。MLエンジンの学習精度を向上。 セッション対応レジームグリッド — ボラティリティ軸をセッション識別子に置き換え。エンジンがAsia、London、NYそれぞれのパラメータ記憶を構築。 ダッシュボード — 現在セッション、DXY状態、シグナルモード、アクティブパラメータ、セッション別シミュレーション勝率を表示。 入力パラメータ ゴールド設定 — セッションフィルター（Asia/London/NY個別トグル）、DXYバイアス（シンボル + EMA期間）、心理的価格帯TP延長（間隔/近接距離/ATRボーナス）、セッション対応レジームグリッド、ダッシュボード、セッション背景。 シグナルモード（①） — シグナルタイプ（Reversal/Breakout）、Fresh Pivot必須、シグナル間隔。 ボラティリティエンベロープ（②） — ルックバック、スムージング期間、バンド幅（最重要設定）、価格ベース、True Rangeモード。 モメンタムフィルター（③） — RSI長さ、ホット/コールドゾーンメモリ。 フロー分析（④） — ボリュームサンプル深さ、サージ閾値。 適応エンジン（⑤–⑥） — 学習率、バッチサイズ、レジームグリッド解像度、Reactivity / Master Dial。 まとめ XAUUSD ML Supertrendは、TradingViewで最も強力な適応型トレンドインジケーターの一つにゴールドの3セッション構造を追加します。機械学習エンジンが東京、ロンドン、NYを同一視せず、それぞれ個別に学習します。DXYアライメントがマクロなゴールド/ドル関係に逆らうシグナルを除去。心理的価格帯の認識がゴールドが一貫してリスペクトするラウンドナンバー付近のシミュレーション精度を向上させます。 Zimordによるオリジナルエンジンは完全保持。ゴールドの追加機能はコア学習アーキテクチャに触れることなくレイヤーとして追加されています。 --- Based on Machine Learning Supertrend by Zimord . セッションフィルター（Asia/London/NY）、DXYバイアスフィルター、心理的価格帯TP延長、セッション対応レジームグリッド、MatsukazeAlgoセッションパレットを追加。
Pine Script® indicator
by MatsukazeAlgo
2
SuperTrend Logistic Regression | Flux ChartsGENERAL OVERVIEW The SuperTrend Logistic Regression indicator combines the classic SuperTrend trend-following tool with a self-training logistic regression model that assigns a probability percentage to every SuperTrend flip. Each time the SuperTrend changes direction, the indicator evaluates the market conditions at the flip across 14 features spanning candle structure, trend context, and technical indicators, then outputs a probability score between 0% and 100% representing how similar the current setup is to past flips that resolved profitably on the same chart. The model trains itself in real time using past SuperTrend signals as labeled examples. Each historical flip becomes a training example: the features captured at the flip are paired with the outcome at the next opposite flip, producing a continuously growing dataset that the model uses to refine its weights. The probability displayed on each new flip reflects what the model has learned about this specific instrument and timeframe, not a universal assumption about what makes a good signal. screenshot: Full chart showing SuperTrend line with multiple flips and probability labels 🔹What is the purpose of the indicator? The indicator addresses a common problem with SuperTrend: not every flip leads to a sustained trend. Many flips occur during choppy or transitional conditions and reverse quickly, producing losing signals. By scoring each flip with a probability, traders get a quantitative sense of how much confidence the model has in that specific signal based on similar past setups. The indicator does not change the SuperTrend calculation itself, so every flip is still detected and visualized. The probability score adds a filtering layer that helps traders separate high-confidence flips from low-confidence ones. 🔹What is the theory behind the indicator? The indicator is built on the idea that market behavior around trend reversals is not random. Certain combinations of candle structure, volatility conditions, volume patterns, and prior trend context tend to precede trends that follow through, while different combinations tend to precede trends that reverse quickly. Logistic regression is a statistical method well-suited to learning these relationships. Given a set of input features and historical outcomes, it produces a set of weights that map feature combinations to probability estimates. In this indicator, each SuperTrend flip becomes a data point. The features at the flip are recorded, and the outcome is determined at the next opposite flip. If price moved in the signal's direction (higher for bull, lower for bear), the signal is labeled as a win. Otherwise, it is labeled as a loss. The model continuously retrains on this growing dataset, adjusting weights so that feature patterns historically associated with wins produce higher probabilities, and feature patterns associated with losses produce lower probabilities. SUPERTREND LOGISTIC REGRESSION FEATURES SuperTrend Core Logistic Regression Model Candle Features Trend Context Features Technical Features Separate Bull and Bear Models Exponential Decay Weighting Minimum Sample Gating Probability Labels and Filtering Gradient-Colored SuperTrend Visualization Optional Momentum Dots Alerts SUPERTREND CORE The SuperTrend is the foundation of every signal. All detection, training, and prediction is tied to SuperTrend flips. The core SuperTrend calculation in this indicator is standard: ATR multiplied by a user-defined factor produces the trailing line, and a flip occurs when price crosses through the line, changing the direction state. 🔹How SuperTrend is calculated The SuperTrend is derived from Average True Range (ATR) with a user-configurable period and factor. When the calculated line is below price, the indicator is in an uptrend state and the line acts as dynamic support. When the line is above price, the indicator is in a downtrend state and the line acts as dynamic resistance. A flip occurs at the exact bar where price crosses through the line, changing the direction from bullish to bearish or vice versa. 🔹Why SuperTrend was chosen SuperTrend is one of the most widely used trend-following tools on TradingView. It produces clean, deterministic signals with well-understood behavior. Rather than reinventing or modifying the underlying calculation, this indicator treats SuperTrend as a signal source and adds a separate statistical layer on top. This keeps the core behavior familiar to traders already using SuperTrend and ensures that every flip is still detected, regardless of the probability score. 🔹SuperTrend Inputs Two inputs control the SuperTrend calculation: Factor (the ATR multiplier, default 3.0) and ATR Period (the number of bars in the ATR calculation, default 10). These correspond to the standard SuperTrend parameters. Changing these values affects where flips occur, which in turn affects what signals the model trains on. LOGISTIC REGRESSION MODEL Logistic regression is a statistical model that predicts binary outcomes from a set of input features. It takes each feature, multiplies it by a learned weight, sums the results, adds a bias term, and passes the total through a sigmoid function that maps the output to a probability between 0 and 1. The model learns the weights by comparing its predictions against actual outcomes and adjusting through gradient descent. 🔹What is Logistic Regression? Logistic regression works by finding the set of weights that best separates winning signals from losing signals in feature space. A large positive weight on a feature means that higher values of that feature are associated with winning outcomes. A large negative weight means higher values are associated with losing outcomes. A weight near zero means the feature does not discriminate between winners and losers on this chart. The sigmoid function is what turns the weighted sum into a probability. It outputs values near 0 when the weighted sum is very negative, values near 1 when the weighted sum is very positive, and values near 0.5 when the weighted sum is near zero. This gives the output a natural probability interpretation. 🔹How the model is trained Training happens every time a new SuperTrend flip occurs. The indicator looks at all past resolved signals (signals that have already seen their next opposite flip and therefore have a known outcome) and runs gradient descent over them. Gradient descent calculates how much each weight should change to reduce the model's prediction error, then applies those changes iteratively. The indicator runs multiple training epochs on each update to ensure the weights converge reasonably well to the current data. L2 regularization is applied to prevent any single weight from becoming extreme. Weight clipping further constrains weights to a reasonable range, avoiding instability when training data is thin or features are noisy. Together, these make the model more robust on small sample sizes. 🔹Outcome evaluation For training to work, every historical signal needs a win/loss label. The indicator uses flip-to-flip evaluation: a bull signal is considered a win if the close at the next bear flip is higher than the close at the bull flip. A bear signal is considered a win if the close at the next bull flip is lower than the close at the bear flip. This matches the natural lifecycle of a SuperTrend trade, where entry and exit are both on flips. 🔹A Winning Signal Example A winning bull signal forms when a bull flip occurs and, by the time the next bear flip occurs, the close at the bear flip is higher than the close at the bull flip. The probability label on the bull flip reflects the model's confidence at entry, while the outcome is confirmed at the next flip. 🔹A Losing Signal Example A losing signal forms when price fails to move in the signal's direction by the next opposite flip. For example, a bull flip where price immediately reverses and ends lower than entry when the next bear flip occurs. CANDLE FEATURES Candle features describe the shape and volume of the flip candle itself, compared against recent averages. These are the most direct, local features the model uses. All candle features are toggleable in the "Candle Features" input group and are normalized to a range centered at zero, where zero means the feature value matches the recent average. 🔹Body Body measures the size of the flip candle's body (the absolute distance from open to close) relative to the average body size over the recent lookback window. A value above zero means the flip candle had a larger body than recent candles, suggesting stronger conviction. A value below zero means the body was smaller than usual, suggesting indecision. The model learns whether strong-bodied flips tend to produce winning trends on this chart. 🔹Upper Wick Upper Wick measures the length of the upper wick (the distance from the body top to the high) relative to recent average upper wicks. Long upper wicks can indicate rejection at highs, while short upper wicks suggest price accepted the top of the candle cleanly. The model learns how upper wick behavior at flips correlates with outcomes. 🔹Lower Wick Lower Wick measures the length of the lower wick (the distance from the body bottom to the low) relative to recent average lower wicks. Long lower wicks can indicate rejection at lows, while short lower wicks suggest clean acceptance. This feature is disabled by default because it historically showed the weakest predictive signal across tested instruments. 🔹Range Range measures the total high-to-low range of the flip candle relative to the recent average range. A wide-range flip candle indicates volatility expansion, while a tight-range candle suggests contraction. The model learns whether flips during volatility expansion tend to perform differently from flips during contraction. 🔹Volume Volume compares the flip candle's volume to the average volume over the recent lookback window. Higher than average volume at a flip generally indicates stronger participation, while lower than average volume suggests weak conviction. The model learns how volume conviction at flips relates to trend outcomes. 🔹Delta Volume Delta Volume estimates the net buying versus selling pressure within the flip candle by sampling 1-minute lower timeframe bars. The indicator distributes each 1-minute bar's volume to either the bullish or bearish side based on whether that bar closed up or down, then outputs the net direction as a feature value from fully bearish to fully bullish. This gives the model a finer-grained view of what happened inside the flip candle beyond the aggregate close. TREND CONTEXT FEATURES Trend context features describe the market conditions leading into the flip, not just the flip candle itself. These are calculated from the lookback window before the flip. All trend context features are toggleable in the "Trend Features" input group. 🔹Momentum Momentum counts consecutive candle direction leading into the flip. Each bullish candle increments the streak in the positive direction, and each bearish candle increments it in the negative direction. The value is capped so very long streaks do not dominate. A strongly positive momentum value before a bull flip indicates buying was already building; a strongly negative value before a bull flip indicates a sharp reversal from recent selling. The model learns which regime tends to produce better bull outcomes. 🔹Pre-Flip Trend Pre-Flip Trend averages the signed candle bodies (close minus open) over the recent lookback window, normalized by the average range. This gives a broader picture of whether the market was drifting up, drifting down, or chopping sideways before the flip. Unlike momentum, which only counts direction, pre-flip trend captures the magnitude of the directional bias. 🔹ATR Slope ATR Slope compares the current ATR value to the ATR value from the lookback period ago. A positive slope means volatility is expanding into the flip, often associated with stronger follow-through. A negative slope means volatility is contracting, often associated with weaker signals. The model learns whether volatility expansion at the flip is a positive or negative factor for the specific instrument. 🔹Volume Trend Volume Trend compares the average volume of recent bars to the average volume of bars further back. A positive value means participation is increasing; a negative value means it is fading. This feature is disabled by default because it historically showed weak signal across tested instruments. 🔹ST Distance ST Distance measures how far price was from the SuperTrend line before the flip, normalized by ATR. A value near zero means the flip was a tight cross; a larger absolute value means price was well above or below the line and had to travel significantly to trigger the flip. The model learns whether tight crosses or aggressive breaks produce better outcomes. 🔹Trend Duration Trend Duration measures how many bars the previous trend lasted before flipping. Short previous trends might indicate choppy conditions where flips come and go quickly. Longer previous trends might signal genuine exhaustion at reversal. The model learns how previous trend length relates to the success of the current flip. TECHNICAL FEATURES Technical features bring in classic technical indicator readings at the flip point. These are toggleable in the "Technical Features" input group. 🔹RSI RSI (Relative Strength Index) is calculated with the same lookback as the other features and then centered around the 50 level. Values near the oversold end push the feature toward -1, values near the overbought end push it toward +1, and values near 50 are near zero. The model learns whether overbought or oversold RSI readings at flips correlate with different outcomes on the specific chart. On some instruments, flips at extreme RSI readings perform well; on others, they perform poorly. The model discovers this from the data. 🔹BB Position BB Position measures where price sits within Bollinger Bands at the flip. Price at the lower band gives a value of -1, price at the basis gives 0, and price at the upper band gives +1. The Bollinger Bands are calculated with the same lookback as the other features. This feature captures mean-reversion versus breakout context: a flip near the lower band is different from a flip near the upper band, and the model learns which band positions tend to precede successful trends. SEPARATE BULL AND BEAR MODELS The indicator maintains completely independent models for bull signals and bear signals. Each has its own set of weights, its own training dataset, and its own prediction logic. 🔹Why separate models? A single model that assumes features mean opposite things for opposite directions would be an oversimplification. For example, a long lower wick on a bull flip might indicate strong buyer defense, while a long lower wick on a bear flip might indicate weak sellers. These are different setups with different implications, and forcing them into one model with flipped signs would blur the signal. By training separate bull and bear models, the indicator gives each direction room to learn its own relationships. A feature that strongly predicts bull wins might be irrelevant or even negatively correlated for bear wins, and the separate models can capture this without interference. 🔹Implementation Each direction has its own array of signals and its own weights array. When a bull flip occurs, the bull signals array is updated and the bull model is retrained. When a bear flip occurs, the bear signals array and bear model are updated separately. The two models never share state, and their predictions are based only on their own training data. EXPONENTIAL DECAY WEIGHTING Not all training examples are equally relevant. Recent signals reflect current market conditions, while older signals may reflect regimes that no longer apply. The indicator addresses this with exponential decay weighting during training. 🔹How decay works Each resolved signal is assigned a weight based on its age. The newest resolved signal gets the highest weight (1.0 after normalization), and older signals get progressively smaller weights based on a decay factor. A decay factor close to 1 means old and new signals are weighted roughly equally. A decay factor close to 0 means recent signals dominate and old signals are effectively ignored. 🔹Why decay is important Markets change. A feature that strongly predicted wins six months ago might have weak or reversed predictive power now. Without decay weighting, the model would be slow to adapt to new conditions because old data would dilute the influence of recent outcomes. With decay weighting, the model naturally updates its weights to reflect the most recent dynamics while still using historical data to maintain stability. PROBABILITY LABELS AND FILTERING When a new flip passes the minimum sample gate, the indicator calculates the probability from the current feature values and the trained weights. This is displayed as a colored triangle label at the flip bar. 🔹Label Appearance Bull flip labels appear below the bar as upward-pointing green triangles with the probability percentage inside. Bear flip labels appear above the bar as downward-pointing red triangles with the probability percentage inside. The colors are partially transparent so the labels do not obscure price action. 🔹High Probability Example A high probability label means the model found the current flip's features similar to past flips that resolved as wins. For example, a bull flip with strong pre-flip momentum, expanding volatility, positive delta volume, and price well above the SuperTrend line might receive a probability above 65% if those conditions have historically preceded successful bull trends. 🔹Low Probability Example A low probability label means the model found the current flip's features similar to past flips that resolved as losses. Low probability signals might share characteristics with flips that occurred during choppy conditions or weak momentum regimes. 🔹Min Probability Filter A Min Probability input lets users hide labels below a confidence threshold. Setting it to 0 shows every signal. Setting it to 60 only shows labels where the model estimates at least 60% probability of a profitable outcome. This filter only affects visual display and alerts. The SuperTrend line and color change still appear on every flip, and the model still trains on every signal regardless of the filter. 🔹Interpreting the probability The probability represents the model's estimate that the current flip will resolve profitably by the next opposite flip, based on how similar past flips performed. A 70% label does not guarantee a win; it means the model finds this flip's conditions more similar to past winners than past losers. Probabilities should be interpreted relative to the base rate (the overall percentage of past flips that won) rather than as absolute guarantees. VISUAL CUSTOMIZATION The indicator includes several visual elements that help traders see the SuperTrend state and the probability labels clearly. 🔹Gradient-Colored SuperTrend The SuperTrend line is plotted with a color gradient based on how far current price has moved from the line since the most recent flip. The color intensifies as price extends further in the trend direction, giving a visual indication of how developed the trend is at any point. Fills between the body midpoint and the SuperTrend line reinforce this gradient effect. 🔹Momentum Dots An optional momentum dots display overlays circles on the SuperTrend line with colors that shift between yellow and the trend color (green or red) based on price position. This provides a secondary visual cue for trend strength. The Enable Momentum Dots input toggles this display on or off. INPUTS 🔹SuperTrend Factor: ATR multiplier used in the SuperTrend calculation. Default is 3.0. Increasing this value makes the SuperTrend less sensitive and produces fewer, wider flips. Decreasing it makes the SuperTrend more sensitive and produces more frequent flips. ATR Period: Number of bars used in the ATR calculation. Default is 10. Larger periods smooth the ATR, while smaller periods make it more reactive. 🔹Display Enable Momentum Dots: Toggles the momentum dots overlay on the SuperTrend line. Default is on. 🔹Filters Min Probability %: Minimum probability required for a signal label to appear on the chart. Default is 0 (show all signals). Setting this to a higher value hides lower-confidence signals. 🔹Candle Features Body: Enable body size feature. Default is on. Upper Wick: Enable upper wick feature. Default is on. Lower Wick: Enable lower wick feature. Default is off. Range: Enable candle range feature. Default is on. Volume: Enable volume feature. Default is on. Delta Vol: Enable delta volume feature using 1-minute LTF data. Default is on. 🔹Trend Features Momentum: Enable consecutive candle direction feature. Default is on. Pre-Flip Trend: Enable average directional body feature. Default is on. ATR Slope: Enable volatility expansion feature. Default is on. Volume Trend: Enable volume building feature. Default is off. ST Distance: Enable distance from SuperTrend line feature. Default is on. Trend Duration: Enable previous trend length feature. Default is on. 🔹Technical Features RSI: Enable RSI feature. Default is on. BB Position: Enable Bollinger Band position feature. Default is on. ALERTS The indicator includes alert conditions for the following events: Bull Flip: Fires on a confirmed bullish SuperTrend flip that passes the Min Probability filter. Bear Flip: Fires on a confirmed bearish SuperTrend flip that passes the Min Probability filter. Users can configure alerts from the TradingView alerts menu and choose which condition to subscribe to. IMPORTANT NOTES 🔹Non-Repainting Behavior Signals are detected and probability labels are calculated on the bar where the SuperTrend flip confirms. The probability value is based only on feature values at the time of the flip and the model weights as of that bar. The outcome label used for training is only recorded after the next opposite flip has occurred, so the current bar's prediction never uses future data. 🔹Probability Interpretation The probability represents the model's learned estimate from past data on the current chart. It is not a guaranteed win rate. Markets can shift in ways the model has not yet seen, and sample size is always a limitation. Probabilities should be used as one input among many in a trading decision, not as a standalone signal. UNIQUENESS The SuperTrend Logistic Regression indicator takes a distinct approach to SuperTrend enhancement. Rather than altering the SuperTrend calculation itself, it preserves the classic SuperTrend behavior and adds a statistical layer on top that scores each flip independently. Every flip is still detected, so users never miss signals; the probability only determines what gets visually emphasized. The logistic regression implementation uses proper gradient descent with L2 regularization, weight clipping, and exponential decay weighting, making the training process stable and adaptive. Weights persist across bars and are refined with each new resolved signal rather than being recalculated from scratch. Separate bull and bear models learn direction-specific feature relationships independently, avoiding the oversimplification of assuming features have opposite meanings for opposite directions. All 14 features are toggleable, spanning candle structure, trend context, and technical indicators, so users can customize which market characteristics feed into the model. The probability is backed by a concrete, testable definition: the likelihood that the current flip will resolve profitably by the time the next opposite flip occurs, based on how similar past flips performed. This matches how SuperTrend is naturally traded on flip-to-flip cycles. Minimum sample gating ensures that probability labels only appear once the model has enough training data to make meaningful predictions, preventing misleading early signals. Together, these choices make the indicator a disciplined, data-driven extension of SuperTrend that adapts to each instrument and timeframe it runs on, rather than applying a one-size-fits-all scoring system.
Pine Script® indicator
by fluxchart
CandelaCharts - Killzone Supertrend📝 Overview The CandelaCharts - Killzone Supertrend indicator integrates professional, noise-filtered Supertrend volatility-based trend-following logic within specific intraday sessions. By isolating trend analysis to key Killzones and providing advanced smoothing tools, traders can effectively filter out market noise and identify high-probability trend shifts during periods of peak institutional activity. 📦 Features 5 Customizable Sessions : Tracks trends across Asia, London, NY AM, NY Lunch, and NY PM sessions. Continuous Detection : Unlike standard session indicators that reset, this logic runs continuously in the background. This ensures that the trend state is established accurately before the session begins, eliminating "initialization lag." Full Session Backgrounds : Highlight the entire vertical pane for each session with customizable colors and transparency for maximum focus. Source Smoothing : Smooth the price source (hl2) before calculation to filter out minor whipsaws and reduce false signals in choppy markets. Multi-Method ATR : Choose between RMA, SMA, EMA, or WMA for volatility calculations based on your preferred responsiveness. Visual Signal Markers : Clear Triangle Up/Down markers appear instantly when a trend flip occurs within an active session. Trend Fill : Shaded backgrounds between the Supertrend line and price provide a visual "cushion" to assess trend strength. Dynamic Session Labels : Centered labels that automatically adjust their position based on the session's price range. Session Dividers : Clear vertical dividers to signal the transition between trading periods. ⚙️ Settings ATR Period : Lookback period for the Average True Range calculation (default: 10). Multiplier : Volatility multiplier for the trailing stop (default: 3.0). Source Smoothing : EMA period to smooth price before detection (0 = off). ATR Method : Choose the smoothing method (RMA, SMA, EMA, WMA). Show Signals : Toggle Triangle Up/Down markers for trend changes. Show Trend Fill : Toggle the shaded background between price and Supertrend. Label Size : Customize the text size of session labels. Timezone : Supports America/New_York, UTC, and Exchange time. Divider Style : Style and color settings for vertical lines. Show Session : Toggle the Supertrend logic and markers. Background : Toggle the full vertical pane background color. Session Name & Time : Define labels and time windows. Session Color : Sets the theme for the labels and dividers. Show Labels : Toggle the centered session identifiers. Show Divider : Toggle vertical start/end lines. ⚡️ Showcase Supertrend Lines & Signals Session Boxes & Full Backgrounds 🚨 Alerts Trend changes are visually indicated by line color shifts and Triangle markers (Buy/Sell) within each active session. ⚠️ Disclaimer Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Pine Script® indicator
by CandelaCharts
Conflux 4 | AnonycryptousConflux 4 | Anonycryptous Description & user manual Why this indicator is different Most signal indicators fire on one condition. Price crosses a moving average. RSI hits a level. A candle closes above a line. One condition. One trigger. And because one condition alone is never enough, the signals come constantly — in trends, against trends, in chop, in news spikes — with no filter for whether the setup actually makes sense. Conflux 4 works differently. It does not fire on one condition. It requires four independent filters to agree at the same moment, in the same direction, before anything appears on the chart. Trend, momentum, volatility structure, and trend strength. All four. If one filter disagrees, nothing is drawn. Not a reduced signal. Nothing. The result is an indicator that is quiet most of the time — and deliberate when it speaks. When a signal does appear, Conflux 4 does not just mark a dot and leave you to figure out the rest. It draws a complete trade block automatically: entry, stop, and up to four take profit levels. The stop trails dynamically after the first target is reached, moving to breakeven and continuing from there. The trade is managed visually until it resolves. The dashboard shows the live state of every filter at all times, so you always know why a signal appeared — or why it did not. Important notice Conflux 4 generates signals based on technical filter alignment. These signals are not financial advice. They do not predict the future. They do not guarantee profitability. All trading decisions are made entirely by the user. Always manage your own risk. Always apply your own judgment. 1. Overview Conflux 4 is a four-filter confluence signal indicator. A signal only fires when all four filters align simultaneously in the same direction. When that happens, a complete trade block is drawn including entry, stop, and take profit levels. What it includes: - Four-filter confluence engine: trend, momentum, volatility structure, and trend strength - Four presets: scalp, daytrader, swing, and manual - Three stop modes: Supertrend trailing, ATR cap, and fixed percentage - Automatic trade block with up to four take profit levels - Dynamic trailing stop that activates after TP1 and moves to breakeven - Live dashboard showing the state of every filter in real time - Configurable signal cooldown, bar coloring, and background shading - Alerts for bullish and bearish signal events 2. The four filters A signal is only valid when all four conditions align. 2.1 Trend filter — VWMA and EMA alignment Price must be above the volume weighted moving average and the fast EMA must be above the slow EMA for a bullish signal. Reverse for bearish. This confirms alignment with the prevailing macro trend before anything else is evaluated. 2.2 Momentum filter — RSI threshold RSI must be above the configured bullish threshold (default 55) for long signals, or below the bearish threshold (default 45) for short signals. This filters out setups forming in low-momentum environments where follow-through is less reliable. 2.3 Volatility filter — Supertrend The Supertrend indicator must confirm the same direction as the trend filter. Because Supertrend adapts to volatility using ATR, it naturally avoids triggering during minor fluctuations and choppy price action. 2.4 Trend strength filter — ADX ADX must be above the configured threshold (default 25) to confirm a directional environment. Below this level, price is typically ranging and confluence signals carry less weight. The ADX filter can be disabled if you prefer to evaluate trend strength manually. If any single filter is not in agreement, no signal is generated. 3. Presets Conflux 4 includes four preset configurations that adjust the stop mode and risk/reward levels to suit different trading styles. -Scalp Designed for short timeframes and futures scalping. Stop mode: ATR cap. Take profit levels: 0.5R / 1.0R / 1.5R / 2.0R. -Daytrader Designed for mid-timeframe trading on 15 minute to 1 hour charts. Stop mode: Supertrend trailing. Take profit levels: 0.5R / 1.0R / 2.0R / 3.0R. -Swing Designed for higher timeframe trading on 4 hour and daily charts. Stop mode: Fixed percentage. Take profit levels: 1.0R / 1.5R / 2.5R / 3.5R. -Manual Full control over all parameters. No preset overrides apply. 4. Stop modes 4.1 Supertrend The stop follows the Supertrend line dynamically for the duration of the trade. This allows the stop to trail price as long as momentum holds. 4.2 ATR cap The stop is based on the Supertrend level but capped at a maximum distance defined by an ATR multiplier. This prevents the stop from becoming too wide in volatile conditions. 4.3 Fixed percentage The stop is placed at a fixed percentage below the entry for long trades and above the entry for short trades. The distance does not change after entry. 5. Trade block logic When a signal fires, the trade block is drawn automatically: - Entry line at the signal bar close - Stop line at the calculated level based on the active stop mode - Up to four take profit lines at configurable risk/reward ratios - Visual zone shading between entry and stop, and between entry and each take profit Trailing behavior: Before TP1 is reached, the stop holds its initial position. After TP1 is reached, the stop moves to breakeven and begins trailing dynamically. The stop only moves in the direction of the trade — it never moves against it. The trade block remains active until the stop is hit or the Supertrend flips direction. After resolution, the block is cleared and the indicator is ready for the next setup. 6. Dashboard The dashboard displays the live state of every filter and the current trade situation. It updates on every bar close. Rows displayed: - Trend — overall direction from VWMA and EMA alignment - VWMA — whether price is above or below the VWMA - EMA — whether the fast EMA is above or below the slow EMA - RSI — current RSI value and whether the momentum threshold is met - Supertrend — current Supertrend direction - ADX — current ADX value and whether the trend strength threshold is met - Confluence — number of filters currently in agreement - Stop mode — active stop mode in use - Last signal — how many bars since the last signal fired - Cooldown — whether the cooldown period is still active - Trade — current trade state: none, long, or short - TP progress — which take profit levels have been reached The dashboard header color reflects the current trend direction. 7. Settings Trend filters - VWMA length: period of the volume weighted moving average used as the primary trend filter - Fast EMA / Slow EMA: periods of the two exponential moving averages used for secondary trend confirmation - Show EMA lines: toggle EMA visibility on the chart - EMA colors and line width: visual styling options Momentum - RSI length: period for the RSI calculation - Bullish threshold: RSI must be above this level for a long signal (default 55) - Bearish threshold: RSI must be below this level for a short signal (default 45) Volatility and Supertrend - ATR length: period for the ATR calculation used by the Supertrend - Supertrend multiplier: sensitivity of the Supertrend — higher values produce fewer flips - Show Supertrend line, fill, and color options ADX - Enable ADX filter: toggle the trend strength requirement on or off - ADX length: period for the ADX calculation - ADX threshold: minimum ADX value required for a signal (default 25) Signal settings - Signal cooldown: minimum number of bars between two signals - Show signals, signal text, background shading, and bar coloring Trade block - Show trade block: toggle the full trade block visualization - Stop mode: Supertrend, ATR cap, or fixed percentage - ATR cap multiplier and fixed percentage stop size - Take profit levels: four configurable RR ratios - Visual styling for stop, entry, and take profit lines Dashboard - Position: top left, top right, bottom left, or bottom right - Size: tiny, small, or normal - Visibility toggle 8. How to use Select a preset or switch to manual and configure the filters to match your trading style and timeframe. Choose a stop mode. Supertrend is best for trending markets where you want the stop to follow price. ATR cap limits the maximum stop size. Fixed percentage suits swing trades where a known maximum loss matters more than trailing. Set your risk/reward take profit levels. Monitor the dashboard. When all four filters align, the confluence count reaches four and a signal fires. The trade block is drawn automatically. A green marker indicates a bullish signal. A red marker indicates a bearish signal. The trade block shows the full setup from entry to each take profit level. Decision-making remains entirely with the user. 9. Notes Low signal frequency is intentional. Four filters aligning simultaneously is a selective condition. Signals will not appear on every bar or even every session. That is by design. Higher timeframes generally produce more stable signals. On lower timeframes the ADX threshold may need to be lowered or disabled to account for faster price structure. Signals are more meaningful when they form at key structural levels such as support, resistance, or liquidity zones. Conflux 4 does not evaluate those levels — that context comes from the trader. The ADX threshold can be adjusted for markets that tend to range. Lowering it increases signal frequency. Raising it makes the filter more selective. 10. Disclaimer This indicator is provided for educational and informational purposes only. All outputs are based on historical price action calculations and do not guarantee future results. Trading financial instruments involves significant risk of loss. Past performance does not indicate future results. Use at your own discretion.
Pine Script® indicator
by Anonycryptous
SupOsc + SSL + Willy SignalsWhat It Does This is a confluence signal indicator that combines three separate technical indicators and only fires a buy or sell signal when all three agree simultaneously. The idea is to reduce false signals by requiring multiple independent conditions to align before triggering an entry. It plots simple B (buy) and S (sell) labels directly on your chart. The Three Indicators 1. SuperTrend Oscillator (SupOsc) A normalized oscillator built from a SuperTrend calculation. Rather than plotting the SuperTrend line itself, it measures how far price is from the SuperTrend bands and converts that into an oscillator value between -1 and +1. A smoothed EMA histogram runs underneath it. For signals, it watches for the oscillator crossing the -0.50 level upward (buy) or crossing the +0.50 level downward (sell). Think of it as a momentum/trend confirmation filter. 2. SSL Channel A simple but effective trend direction tool that uses SMAs of the highs and lows to determine whether price is in a bullish or bearish regime. When the upper SSL line is above the lower line, it's bullish. When below, it's bearish. The signal requires SSL to be confirming the same direction as the SupOsc before anything fires. 3. Williams %R A momentum oscillator that measures where price closed relative to its recent high-low range, on a scale of 0 to -100. The indicator checks the previous candle's Williams %R reading — requiring it to have been in oversold territory (below -80) for buys, or overbought territory (above -20) for sells. This acts as a pullback/exhaustion filter, helping you buy dips and sell rips rather than chasing. Does It Repaint? Largely no, but with one caveat to be aware of. The SupOsc and Williams %R components are calculated purely on current timeframe bars using standard closed-bar data — no repainting there. The SSL component uses request.security() with lookahead=barmerge.lookahead_off, which is the correct, repaint-safe setting. However, if you set the SSL Timeframe to a higher timeframe than your chart, the SSL values will only update when that higher timeframe bar closes — meaning mid-bar the value reflects the previous completed HTF bar, which is standard and expected behavior, not true repainting. The Williams %R check also looks at wR (the previous bar's value), which is already a closed bar — safe. Bottom line: Signals that appear on a closed bar will not disappear or move. Signals on the current live bar could technically shift if conditions change before the bar closes, which is true of virtually any indicator. Personally I find it works best for confirmations when combined with the CCI as seen in the image below.
Pine Script® indicator
by parkerberlinger
Position Sizing CalculatorA simple automated calculator that shows how many shares can be bought or sold if a specific maximum amount is to be risked on the position. The risk per share is assumed to be the distance to the respective buy or sell line of the Supertrend indicator. This is based on a calculation of the ATR for the last ten days, which is multiplied by a fixed factor and plotted against the highest or lowest candle of the past ten days. The parameters can be changed manually. By default, a risk of $500 per trade is assumed. For each of the last bars, the calculator displays the distance to the calculated exit and, through a simple division, calculates the number of shares that could be bought or sold in a potential long or short position to achieve this hypothetical maximum risk. Of course, there is no guarantee that the respective price will actually be reached, but the calculator can help provide a reference point for sizing the position. The principle is clearly visible in the screenshots: FRT is a stock that moves slowly and is only a short distance from the stop-loss level. At the current price of $114.47 and a calculated stop at $108.99, 91 shares could be purchased to risk $500. In total, that would be an order of $10,416.77 for a long position. SOUN, on the other hand, has a very wide margin to the stop-loss; it is a stock with high volatility. Therefore, only 300 shares can be purchased here to achieve the same hypothetical risk. The position would thus be worth only $2,841. Designed by tuvot_1a, programmed by Claude.
Pine Script® indicator
by tuvot_1a
1
XAUUSD Asymmetric Trend [MatsukazeAlgo]🇬🇧 ENGLISH Gold trends differently depending on when you trade. During Asia, stop runs reverse. During London and NY, breakouts keep running. A fixed-parameter trend indicator ignores this — it applies the same sensitivity 24 hours a day. This indicator adapts its asymmetric thresholds per session automatically. Based on Asymmetric Volatility Trend Line by QuantAlgo . Gold-optimized with 6 additions. How the Asymmetry Works The trend line uses different evidence requirements for continuation vs reversal. Continuing a trend requires less price movement. Reversing requires more. This makes the trend sticky — once it starts, it does not flip on small pullbacks. The Gold version changes these ratios per session: Asia (19:00–03:00 ET): 0.7x continuation / 1.0x reversal. Easier to reverse. Matches the stop-run reversal pattern that dominates Gold during Asian hours. London (03:00–09:00 ET): 0.3x continuation / 1.0x reversal. Much harder to reverse. Breakouts during London tend to run. The indicator lets them. NY (09:00–17:00 ET): 0.3x continuation / 1.0x reversal. Same as London. NY session momentum is real — the trend line follows it without flipping on noise. Daily and higher timeframes use the original 0.5x/1.0x ratio since session distinctions do not apply. The dashboard shows the active ratio (e.g. "LDN 0.3x/1.0x") so you always know which mode is running. DXY Bias Bull signals only fire when the US Dollar Index is weakening (DXY below its EMA). Bear signals only fire when DXY is strengthening. Gold and USD move inversely — this filter removes signals that fight the macro trend. Psych Level Awareness (off by default) When enabled, the volatility threshold tightens by 25% near $50 and $100 round numbers. Gold reacts at these levels. The tighter threshold makes the trend line more sensitive to reversals near round numbers, catching turns that a fixed threshold would miss. Reversal markers switch from ◆ to gold-colored ◆ when near a psych level. Visual Design The default view is minimal: a single trend line with a gradient fill. No labels, no signals, no background colors. Enable signals (▲▼), bar coloring, and session backgrounds individually from settings. Presets Default: Swing trading on 4H and Daily. Balanced sensitivity. Fast Response: Intraday on 5min to 1H. Lower threshold, faster reaction. Smooth Trend: Position trading on Daily and Weekly. Higher threshold, fewer flips. Credits Original asymmetric volatility concept by QuantAlgo . Session-adaptive asymmetry, DXY integration, psych level tightening, and Gold-specific tuning by MatsukazeAlgo. --- 🇯🇵 日本語 ゴールドのトレンドはセッションによって違う。アジアではストップ狩りが反転する。ロンドンとNYではブレイクアウトがそのまま走る。固定パラメータのトレンドインジケーターはこの違いを無視する。 このインジケーターはセッションごとに非対称の閾値を自動で調整する。 QuantAlgoのAsymmetric Volatility Trend Lineをベースに、ゴールド専用の6つの改良を追加。 非対称のしくみ トレンドラインは「継続」と「反転」で異なる証拠を要求する。継続には小さな動きで十分。反転には大きな動きが必要。一度始まったトレンドは小さなプルバックでは反転しない。 ゴールド版はこの比率をセッション別に変える： アジア（19:00–03:00 ET）：継続0.7x / 反転1.0x。反転しやすい設定。 ロンドン（03:00–09:00 ET）：継続0.3x / 反転1.0x。反転しにくい設定。ブレイクアウトが走る。 NY（09:00–17:00 ET）：継続0.3x / 反転1.0x。ロンドンと同じ。 日足以上はオリジナルの0.5x/1.0x。ダッシュボードに現在の比率が表示される。 DXYバイアス Bull = DXY弱い時のみ。Bear = DXY強い時のみ。ゴールドとドルは逆相関。マクロトレンドに逆らうシグナルを除外。 心理的価格帯（デフォルトOFF） ONにすると、$50/$100付近でボラティリティ閾値が25%縮小。トレンドラインが反転に敏感になる。 ビジュアル デフォルトはトレンドラインとグラデーションfillのみ。シグナル（▲▼）、バーの色、セッション背景は設定で個別にON可能。 プリセット Default：スイング（4H/日足）。Fast：デイトレ（5分〜1時間）。Smooth：ポジション（日足/週足）。
Pine Script® indicator
by MatsukazeAlgo
UCY-VWATR (live)═══════════════════════════════════════ UCY-VWATR — Volume Weighted ATR Bands with Supertrend ═══════════════════════════════════════ ▸ OVERVIEW A volatility-band indicator that combines a Volume Weighted Moving Average (VWMA) center line with ATR-based deviation bands and a Supertrend overlay for trend direction. The indicator visualizes how far price extends from its volume-weighted mean in units of Average True Range, while the Supertrend acts as a dynamic trend filter. ═══════════════════════════════════════ ▸ HOW IT WORKS - VWMA forms the central reference band (default: 20 period), giving more weight to bars with higher volume than a standard moving average. - ATR (default: 14 period) generates three pairs of upper and lower deviation bands at ±1, ±2, and ±3 multiples — mapping volatility expansion zones around the mean. - Supertrend (default: 10 period, factor 3.0) determines the prevailing trend direction. Green = uptrend, Red = downtrend. - Body-middle (the midpoint of each candle's open and close) is compared against each band. When the body crosses beyond a band in the direction of the active trend, a colored fill appears — darker fills indicate stronger displacement from the mean. ═══════════════════════════════════════ ▸ HOW TO READ THE FILLS In an UPTREND (green Supertrend): - Body above VWMA → light green fill (mild momentum) - Body above +1 ATR → medium green - Body above +2 ATR → strong green - Body above +3 ATR → extreme green (potential exhaustion) In a DOWNTREND (red Supertrend): - Body below VWMA → light red fill - Body below -1 ATR → medium red - Body below -2 ATR → strong red - Body below -3 ATR → extreme red (potential exhaustion) The intensity of the fill provides an at-a-glance read of how stretched price is relative to its volume-weighted mean. ═══════════════════════════════════════ ▸ POTENTIAL USE CASES - Trend-following: Enter in the direction of the Supertrend when price pulls back to VWMA or ±1 ATR band. - Mean reversion: Look for exhaustion signals when price reaches ±3 ATR bands against the prevailing trend. - Breakout confirmation: A break and hold above/below ±1 ATR in the direction of a fresh Supertrend flip can act as trend confirmation. - Volatility context: Wider band spacing signals high volatility regimes; narrow bands indicate compression. ═══════════════════════════════════════ ▸ SETTINGS - VWMA Length: 20 (medium-term balance) - ATR Length: 14 (classic Wilder period) - ATR Multipliers: 1.0 / 2.0 / 3.0 - Supertrend ATR Length: 10 - Supertrend Factor: 3.0 All parameters are user-adjustable to fit different timeframes and instruments. Lower multipliers suit ranging markets; higher multipliers suit trending or volatile assets. ═══════════════════════════════════════ ▸ NOTES - Works on all timeframes and instruments (stocks, futures, forex, crypto). - VWMA requires volume data — best results on instruments with reliable volume feeds (avoid forex spot pairs without aggregated volume). - Designed as a visual decision-support tool, not a standalone signal generator. ═══════════════════════════════════════ ⚠️ DISCLAIMER This indicator is published for educational and analytical purposes only. It does not constitute financial advice or a recommendation to buy or sell any asset. All trading decisions and their outcomes are the sole responsibility of the user. Past performance does not guarantee future results.
Pine Script® indicator
by ugurcagriyilmaz
2
Regression Deviation Channel [JOAT]Regression Deviation Channel Introduction The Regression Deviation Channel is an institutional-style statistical trend and execution framework built around segmented regression, deviation envelopes, premium/discount zoning, breakout qualification, and risk mapping. Instead of acting like a plain moving-average channel, it models price through a best-fit regression path, measures dispersion with RMSE, then classifies where price is trading inside that structure: discount, equilibrium, or premium. This version is designed to feel more like a desk-grade directional map than a simple overlay. It combines a frozen regression segment, internal band hierarchy, confidence scoring, Supertrend stack alignment, breakout detection, and ATR-based trade mapping into one visual structure. The goal is not just to show where price is, but whether the current move is balanced, compressed, expanding, or resolving. Why This Indicator Exists Most channels are too simple. They show boundaries but do not explain what price is doing inside those boundaries. This indicator was built to solve that by combining: Segmented Regression: Tracks the current directional price path with a proper best-fit slope Deviation Architecture: Uses RMSE to define statistically meaningful channel width Premium / Discount Zoning: Splits the channel into expensive, fair value, and cheap territory Breakout Qualification: Scores breakout quality using slope, participation, structure, and location Trend Stack Context: Adds Supertrend alignment to distinguish strong directional pressure from noise Trade Mapping: Builds clean ATR-based stop and multi-target projections after confirmed breaks The result is a regression channel that does more than draw lines. It gives context, bias, execution framing, and visual hierarchy. Core Components Explained 1. Segmented Regression Engine = f_ols(winLen) basisVal = intercept + slope * float(barsInSeg - 1) upperVal = basisVal + rmse * multiplier lowerVal = basisVal - rmse * multiplier The core engine uses manual ordinary least squares regression to calculate the channel basis. Once the segment matures, the regression values are frozen and projected forward until price resolves beyond the envelope. This “freeze and resolve” behavior keeps the channel visually stable instead of constantly shifting every bar. 2. RMSE Deviation Structure Root mean squared error defines channel width, making the envelope responsive to how tightly price is hugging the trend. Tight RMSE = cleaner trend structure Wide RMSE = unstable or volatile structure Internal bands split the envelope into inner, quarter, and outer zones These nested bands create a true structure ladder instead of a single upper/lower shell. 3. Premium / Discount Channel Arrays The channel is separated into three value areas: Premium: Upper edge territory where price is extended and expensive relative to the current regression path Equilibrium: The center band around fair value and neutral orderflow balance Discount: Lower edge territory where price is cheap relative to the active path This makes the indicator more useful for directional context: Bull channels pressing premium signal strong continuation pressure Bear channels pressing discount signal strong downside control Repeated failure to hold premium/discount can signal exhaustion or rebalancing 4. Breakout Confidence Model Breakouts are not treated equally. The indicator scores breakout quality using four ingredients: Participation: Distance from the regression basis normalized by ATR Slope Force: Strength of the normalized regression slope Location: Whether price is already pressing the outer structure Alignment: Whether price direction and Supertrend stack agree with the channel breakoutConfidence = participation + slopeForce + location + alignment This helps separate lazy drifts from high-quality channel resolution. 5. Supertrend Ribbon Stack The Supertrend layer is not there as a generic add-on. It acts as a second-order directional filter. Bull channel + bull Supertrend = higher-quality directional stack Bear channel + bear Supertrend = stronger downside stack When regression and Supertrend disagree, price is more likely in transition The fill between regression basis and Supertrend visually shows whether pressure is aligned or conflicted. 6. ATR Risk Map After a confirmed breakout, the indicator projects: 1 ATR-based stop level 3 reward targets using configurable risk-reward multiples Auto-expiring lines so stale trade maps are removed This gives the channel direct execution value instead of leaving the user to manually measure every move. Visual Elements Metallic Basis Line: Gold-toned centerline for the active regression basis Outer Deviation Shell: Main channel boundaries with glow Inner Structure Bands: Internal ladder for pressure staging Premium / Discount Fills: Separate upper and lower value zones inside the channel Equilibrium Fill: Neutral fair-value region Supertrend Ribbon: Context layer showing secondary directional alignment Iridescent Candles: Candle coloring that intensifies as control and confidence improve Breakout Markers: Compact signals for confirmed resolves Readiness Diamonds: Pre-break alignment markers when channel conditions are strong The visual hierarchy is designed so you can read the channel at a glance without relying on heavy objects or clutter. Dashboard The dashboard is intentionally compact and fixed to the right side. It shows only the highest-signal metrics: Bias Regime Flow Channel Position Confidence Compression Trend Stack Trade Map How to Use This Indicator Step 1: Identify Channel Bias Check whether the regression slope is bullish or bearish. That defines the primary directional path. Step 2: Read Value Location See whether price is trading in premium, equilibrium, or discount. This tells you whether price is extended or balanced inside the channel. Step 3: Watch Trend Stack Alignment When Supertrend and regression agree, directional pressure is cleaner. When they disagree, reduce conviction. Step 4: Monitor Confidence Use the breakout confidence score to judge whether price is merely drifting or building a meaningful resolution. Step 5: Trade the Resolve, Not the Noise Use breakout markers and ATR map levels when price exits the frozen envelope with qualified pressure. Best Practices Use higher timeframes for cleaner channel geometry Treat equilibrium as fair value, not a signal by itself Bull channels work best when premium holds and pullbacks respect the inner bands Bear channels work best when discount holds and rallies fail at internal structure High compression followed by rising confidence often precedes expansion Use the risk map for framing, not blind automation Indicator Limitations Regression is still a model of recent price, not a guarantee of future direction Sudden event-driven moves can invalidate the frozen segment quickly Premium and discount are relative to the current channel, not absolute market value High breakout confidence can still fail in thin or news-driven markets Short segments increase responsiveness but also increase noise Technical Implementation Built in Pine Script v6 using: Manual OLS regression RMSE deviation envelopes Segment freeze-and-resolve logic Internal quarter and inner bands Premium/discount channel zoning Supertrend stack integration Breakout confidence scoring ATR-based stop and target map Compact institutional dashboard Originality Statement This indicator is original in how it treats a regression channel as a full market-state framework instead of a static overlay. The value is not just in plotting upper and lower lines, but in combining: Segment freezing Internal value zoning Directional stack confirmation Breakout qualification Execution mapping Each layer contributes different information: regression defines path, RMSE defines structure, premium/discount defines value, Supertrend defines stack, and confidence defines quality. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Regression channels, premium/discount zones, and breakout scores are analytical tools, not guarantees of market outcome. All trading decisions remain the responsibility of the user. -Made with passion by officialjackofalltrades
Pine Script® indicator
by officialjackofalltrades
Trend Quality Band [EXCAVO]Volatility-Ranked SuperTrend That Tightens in Calm Markets and Widens in Volatile Ones The Trend Quality Band is an adaptive trend-following indicator built on a SuperTrend core whose band width is controlled entirely by ATR percentile rank. Instead of a fixed multiplier, the band compresses when current volatility is historically low and expands when it is historically high - giving the trend line room when it needs it and keeping it tight when conditions allow. This is not a standard SuperTrend with a different parameter. The driving mechanism is a statistical rank: each bar, the current ATR is compared against its full lookback history to produce a 0-100% rank, which then scales the band multiplier non-linearly between configurable compress and expand factors. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ▸ HOW TO USE Step 1 → Add the indicator. The adaptive trend band appears immediately. Blue band below price = bullish trend. Red band above price = bearish. Step 2 → Watch for flip signals. Triangles mark the bar where the trend changed direction. Bullish flip = triangle below bar. Bearish = above. Step 3 → Read the ATR Rank in the dashboard. Below 35% = low volatility (compressed band, trend holds tight). Above 65% = high volatility (expanded band, wider room before a flip fires). Step 4 → Use the Regime label. "Low Vol" means the band is near its narrowest - trends confirmed here are high quality. "High Vol" means the band is expanded to filter noise in choppy conditions. Step 5 → Set alerts for Bullish or Bearish Trend Flip to be notified on confirmed direction changes. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ▸ HOW IT CALCULATES ◆ ATR Percentile Rank On every bar, the indicator computes the ATR using the configured length, then ranks it against its own history over the Rank Lookback period: atr_rank = percentrank(ATR, lookback) / 100 This produces a value from 0 to 1. A rank of 0.1 means current ATR is lower than 90% of recent history (unusually quiet). A rank of 0.9 means current ATR exceeds 90% of recent history (unusually volatile). ◆ Non-Linear Multiplier Scaling The rank is mapped to a scaling factor using three zones defined by the Compress Below and Expand Above thresholds (default 0.35 / 0.65): t = clamp((atr_rank - compress_thresh) / (expand_thresh - compress_thresh), 0, 1) rank_scale = compress_factor + t x (expand_factor - compress_factor) eff_mult = base_multiplier x rank_scale When rank is below the compress threshold, rank_scale approaches the Compress Factor (default 0.65). When rank exceeds the expand threshold, rank_scale approaches the Expand Factor (default 1.55). Between the thresholds, the scale interpolates linearly. The result: a multiplier that ranges from approximately 1.6x (base 2.5 x 0.65) to 3.9x (base 2.5 x 1.55) depending on regime. ◆ SuperTrend Ratchet Logic The adaptive multiplier feeds a standard SuperTrend ratchet: upper_raw = src + eff_mult x ATR lower_raw = src - eff_mult x ATR lower_band = close > lower_band ? max(lower_raw, lower_band ) : lower_raw upper_band = close < upper_band ? min(upper_raw, upper_band ) : upper_raw The ratchet means the active band can only move in the direction of the trend - it never widens to catch a missed flip. A flip fires when price closes beyond the active band. The direction variable tracks the current trend state. ◆ Regime Classification The rank is compared against the two thresholds to produce a named regime: Low Vol (rank < 0.35), Normal (0.35-0.65), or High Vol (rank > 0.65). This regime label and the live multiplier value are shown in the dashboard so the trader can see exactly why the band is positioned where it is. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ▸ WHAT MAKES IT DIFFERENT ◆ ATR Percentile Rank as the Sole Driver Most adaptive SuperTrend variants modulate bands using the Efficiency Ratio (a directional momentum measure) or volatility ratios against a moving average. This indicator uses a statistical rank: the current ATR is compared against its entire recent history rather than a smoothed baseline. A rank of 80% means the current bar is more volatile than 80% of recent bars - a precise, context-aware signal that a fixed multiplier or a ratio cannot capture. ◆ Compress-and-Expand Band Behavior The two-threshold system creates three distinct regimes. In the Low Vol regime the band compresses toward the Compress Factor - trend flips require less movement, keeping the indicator responsive during quiet trends. In the High Vol regime the band expands toward the Expand Factor - preventing false flips during breakouts and spike-heavy conditions. The Normal regime interpolates between the two, creating a smooth transition rather than a step function. ◆ Live Multiplier Transparency The dashboard shows the actual effective multiplier value on every bar. This tells the trader exactly how wide the band currently is and why. When the multiplier reads 1.6x the band is near its tightest. When it reads 3.8x the band is near its widest. No guesswork about how the indicator is behaving. ◆ Non-Repainting by Default Flip signals are gated by barstate.isconfirmed - they only fire on the closed bar. The Allow Repainting input is available for users who prefer real-time updates, but the default ensures historical flips on the chart are accurate. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ▸ DASHBOARD Real-time panel (top right by default) shows the current state: Trend - BULLISH or BEARISH, colored by direction ATR Rank - current ATR percentile rank as a percentage (0-100%) Regime - Low Vol / Normal / High Vol based on rank thresholds Multiplier - effective band multiplier currently in use Band - current price level of the active trend band Legend table (bottom left) identifies all visual elements on the chart: ━ (blue) - Bullish trend band ━ (red) - Bearish trend band ┅ (orange) - Midline EMA, color reflects volatility regime ▲ (blue) - Bullish trend flip ▼ (red) - Bearish trend flip ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ▸ SETTINGS Core Settings ATR Length - 14 (lookback for ATR calculation) Base Multiplier - 2.5 (center-point multiplier at rank = 0.5) Source - 0 = HL2, 1 = Close, 2 = HLC3 ATR Rank Settings Rank Lookback - 200 bars (history used for percentile rank) Compress Below - 0.35 (rank threshold for low volatility regime) Expand Above - 0.65 (rank threshold for high volatility regime) Compress Factor - 0.65 (multiplier scale at minimum rank) Expand Factor - 1.55 (multiplier scale at maximum rank) Visualization Bullish Color - blue (customizable) Bearish Color - red (customizable) Signal Color - orange (customizable) Show Band Fill - ON (semi-transparent fill between band and price) Show Flip Signals - ON (arrow shapes at trend flip bars) Show Background - OFF (chart background colored by trend) Show Smooth Band - ON (EMA-smoothed band line, removes staircase appearance) Smooth Length - 5 (EMA period for band smoothing) Show Midline - ON (EMA of price colored by volatility regime) Midline Length - 20 (EMA period for the midline) Dashboard Show Dashboard - ON Show Legend - ON Dashboard Position - Top Right Alert Settings Allow Repainting - OFF JSON Alerts - OFF ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ▸ ALERTS Bullish Trend Flip - trend changed from bearish to bullish on bar close Bearish Trend Flip - trend changed from bullish to bearish on bar close Trend Flip - any direction change JSON payloads include action, direction, ticker, price, timeframe, and indicator. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Best regards, EXCAVO Disclaimer Trading involves significant risk. This indicator is a technical analysis tool and does not constitute financial advice, investment recommendations, or a guarantee of future results. Past indicator behavior does not guarantee future performance. Always use proper risk management and your own judgment.
Pine Script® indicator
by EXCAVO
SuperTrend Flip Zones [AGPro Series]# SuperTrend Flip Zones 🔷 OVERVIEW SuperTrend Flip Zones is a trend-following overlay designed for traders who appreciate the clarity of SuperTrend, but want a more selective and more structured version of it on the chart. Traditional SuperTrend tools are popular because they are simple: the line flips, the color changes, and the chart immediately prints a directional signal. That simplicity is useful, but it also creates a familiar weakness. In many market conditions, raw SuperTrend flips can appear too early, too close to noise, or without enough expansion to show that a genuine directional transition is taking hold. This script was built to solve that exact problem. Instead of treating every SuperTrend direction change as equally meaningful, SuperTrend Flip Zones evaluates the quality of the flip itself. Only qualified flips are promoted into visible BUY / SELL events, and each accepted signal creates a forward-projecting support or resistance zone built around the new SuperTrend structure. The result is not just another SuperTrend clone with different colors. It is a more selective, more chart-aware framework that helps traders judge whether a flip is worth paying attention to, and where the new trend should continue to defend itself after that flip occurs. 🔷 WHAT MAKES THIS DIFFERENT The biggest difference is that this script does not stop at the flip. Most SuperTrend indicators on the platform focus on one task only: detect the directional switch and mark it immediately. SuperTrend Flip Zones takes a broader view. It asks two additional questions: 1. Was the flip strong enough to deserve attention? 2. After the flip, where is the live structural zone that the new trend is expected to protect? That design choice creates a very different chart experience. Instead of receiving every mechanical transition equally, the user sees a filtered signal environment. Weak flips can be ignored, while stronger flips remain visible and are reinforced by an ATR-based zone that extends forward. This makes the tool useful not only at the exact moment of the flip, but also in the bars that follow, when traders are deciding whether the move is still being respected. It also creates clear separation from other AGProLabs tools in the same family. This is not a pullback-quality script. It is not focused on grading retracements inside an already established trend. It is focused on the transition point itself, and on the acceptance zone created by that transition. 🔷 CORE LOGIC The script is built around a custom SuperTrend engine using the selected ATR model, source, and multiplier. When the direction flips, the script does not blindly trust the event. The flip is scored through a multi-factor quality model that examines: - candle body efficiency, - range expansion relative to ATR, - price separation from the active SuperTrend line, - alignment with a trend EMA, - maturity of the prior trend leg before the reversal occurred. Only flips that meet the minimum quality threshold are accepted. Once a bullish or bearish flip qualifies: - a BUY or SELL signal is printed, - the signal can be promoted to BUY+ or SELL+ when the score is stronger, - a rectangular support or resistance zone is created around the new SuperTrend level, - that zone is extended forward to provide ongoing structure. This makes the indicator useful both as a signal filter and as a post-signal map. 🔷 WHY THE ZONES MATTER A standard SuperTrend line tells you where the trailing stop or directional boundary currently sits. This script adds another layer by converting qualified flips into live zones. Those zones are important because they help visualize where the market should continue to accept price if the new directional phase is healthy. In bullish conditions, the zone behaves like a dynamic support belt around the fresh SuperTrend structure. In bearish conditions, the zone behaves like a dynamic resistance belt. If price continues to respect that zone, the flip remains structurally valid. If price loses the zone, the chart communicates that the new directional state is weakening or failing. This produces a more practical read than a line alone, especially for traders who do not always enter on the exact signal bar and instead evaluate continuation quality after the move begins. 🔷 VISUAL DESIGN The script is designed to look polished and organized without overloading the chart. Visual elements include: - bullish and bearish SuperTrend line states, - restrained BUY / SELL labels, - right-extending flip zones, - soft trend cloud for directional context, - compact AGPro panel with merged header row, - configurable panel placement, - dark and light theme support, - adjustable label and panel text sizing. The goal is to keep the chart premium and readable rather than dense and noisy. 🔷 HOW TO USE IT SuperTrend Flip Zones is most useful for traders who want a higher-quality directional read rather than every raw SuperTrend crossover. A typical workflow is: - use the line and cloud to identify the active directional state, - wait for a qualified BUY or SELL rather than reacting to every raw flip, - monitor the projected zone as a live support or resistance area, - observe whether price continues to defend that zone or loses it. This makes the script suitable for discretionary trend-following, continuation analysis, and cleaner overlay-based chart reading. 🔷 BEST FIT This tool is especially useful for: - traders who already use SuperTrend but want cleaner signal selection, - traders who prefer support / resistance style context after the flip, - users who want a premium visual overlay without excessive label density, - trend traders who want a more selective buy sell workflow. 🔷 TRANSPARENCY This is an analytical indicator, not a trading strategy. Like all trend-following tools, it can become less effective in highly compressed or directionless market conditions. The filtering logic is designed to reduce weak transitions, but it does not replace chart context, timeframe awareness, or risk management. All logic is based on confirmed bar data inside the script framework. The purpose is to organize price action more clearly, not to guarantee future market behavior.
Pine Script® indicator
by AGProLabs
Conflux Engine | AnonycryptousConflux Engine | Anonycryptous Description & user manual Why this indicator is different? Most signal indicators work the same way. One condition triggers. One signal fires. The trader either takes it or does not. The problem is that a single condition — a crossover, a level break, a momentum read — is almost never enough to define a genuinely high-quality trade. Markets are too complex and too noisy for that. Conflux Engine works differently. It does not fire on one condition. It requires multiple independent market forces to align simultaneously before a signal appears. Structure has to agree. Volume has to confirm. Momentum has to support. Volatility has to be in the right zone. Session positioning has to be favorable. And optionally, the higher timeframe trend and the ribbon have to be aligned too. Only when enough of these forces agree — and agree clearly — does the indicator produce a signal. This is what confluence means in practice. Not one thing being right. Multiple independent things being right at the same time. The result is fewer signals. But the signals that do appear carry more weight than anything a single-condition system can produce. Important notice Conflux Engine generates trading signals based on a multi-factor scoring engine. These signals are not financial advice. They do not predict the future. They do not guarantee profitability. They are a systematic read of current market conditions across multiple dimensions. All trading decisions are made entirely by the user. Always manage your own risk. Always apply your own judgment. 1. Overview Conflux Engine is a scoring-based signal indicator for traders who want structured, high-conviction entries rather than frequent, noisy ones. Six independent pillars evaluate the market continuously. Each pillar scores independently. The scores combine into a total out of 100. When the total exceeds the signal threshold — and the dominant direction leads the opposite direction by a minimum gap — a signal fires. Additional hard gates can be enabled: an ADX noise filter to block signals during choppy markets, a VWMA filter to ensure macro trend alignment, a Supertrend filter for dynamic trend confirmation, and an Ultra Ribbon filter using 15 Hull Moving Averages for the fastest momentum read. The result is an indicator that is selective by design. It is not built to fire constantly. It is built to fire well. 2. The six pillars 2.1 Structure Evaluates market structure using swing pivot highs and lows. A higher high combined with a higher low defines a bullish structure. A lower high combined with a lower low defines a bearish structure. This pillar answers the most fundamental question in trading: is the market making progress in a direction, or is it deteriorating? Weight: up to 16 points. 2.2 Volume Uses OBV slope via linear regression to determine whether volume is accumulating in the direction of price or diverging from it. Rising OBV slope on a bullish signal means participation supports the move. Falling OBV slope on a bullish signal is a warning. This pillar separates moves with institutional backing from moves without it. Weight: up to 16 points. 2.3 Momentum Evaluates three independent momentum reads: KAMA position (a Kaufman adaptive moving average that adjusts its speed to market conditions), RSI relative to the 50 midline with slope direction, and Williams %R for price positioning within the recent range. Two of three aligned scores partial points. All three aligned scores full points. Weight: up to 16 points. 2.4 Liquidity Detects sweep events — moments where price wicks beyond a recent swing high or low and closes back inside. These events mark liquidity grabs and often precede directional moves. A confirmed bull sweep sets up a long bias context. A confirmed bear sweep sets up a short bias context. The context remains active for a configurable number of bars, decaying over time. Weight: up to 16 points. 2.5 Volatility Measures ATR relative to its own moving average to identify the volatility sweet spot. Signals during dead, flat markets carry less meaning. Signals during chaotically explosive moves are harder to execute cleanly. This pillar rewards the in-between: active, directional, manageable volatility. Weight: up to 16 points. 2.6 Session Evaluates price positioning within the current day's developing range. Price in the lower portion of the range (discount) favors long bias. Price in the upper portion (premium) favors short bias. This pillar can be toggled independently from the session time filter — you can use session scoring without restricting signals to specific hours, or vice versa. Weight: up to 20 points. 3. Hard gates Beyond the six scoring pillars, Conflux Engine includes four optional hard gates. These do not add points. They block signals entirely when their condition is not met. 3.1 ADX noise filter Blocks signals when ADX is below a configurable threshold. ADX measures trend strength. A low ADX means the market is ranging and directionless — exactly the environment where momentum signals fail most often. Default threshold: 35. Adjustable up to 100 for maximum selectivity. 3.2 VWMA filter Price must be above the Volume Weighted Moving Average for long signals, and below it for short signals. The VWMA is slower than a standard EMA and reflects the average price weighted by volume — a more meaningful macro reference than a simple average. Default length: 200. 3.3 Supertrend filter The Supertrend must confirm the signal direction. This is a dynamic trend line based on ATR bands that flips cleanly between bull and bear states. It acts as an additional structural confirmation that the trend environment supports the entry. 3.4 Ultra Ribbon filter The fastest gate. Built from 15 Hull Moving Averages spanning a range of lengths. When the fastest HMA is above the slowest HMA, the ribbon is bullish. When below, bearish. Because Hull MAs minimize lag, this gate reacts to trend changes earlier than most moving average systems. The ribbon also serves as a trailing stop option in the backtest — the slowest HMA tracks trend without being too reactive. 4. Signal scoring Every bar, both a bullish and bearish score are computed from the six pillars. The scores are added together. A signal fires when: - The dominant score meets or exceeds the signal threshold (default 70) - The dominant score exceeds the opposite score by at least the directional lead (default 20) - All enabled hard gates are cleared This two-condition check — threshold plus gap — prevents marginal signals from appearing when the market is ambiguous. Both bull and bear can score reasonably high during mixed conditions. The gap requirement ensures the dominant direction is meaningfully ahead. Pillar weights are individually adjustable. The system allows traders to prioritize the factors most relevant to their trading style and instrument. The Extreme Threshold (default 90) flags signals where the confluence score is exceptionally high. These are the highest-conviction setups in the system. 5. The Ultra Ribbon The Ultra Ribbon is a 15-layer Hull Moving Average ribbon that sits on the chart as both a visual trend tool and a momentum gate. Three themes are available: Classic — green and red. Clear, functional, no ambiguity. Phantom — cyan and pink with purple exhaustion. A darker, stylized read of the same data. (the default) Custom — full color control for bull, bear, and exhaustion states. The ribbon color adapts dynamically. When the spread between the fastest and slowest HMA is wide relative to its historical average, the ribbon fades toward the exhaustion color — a visual signal that the trend may be overextended. When the spread is moderate, the ribbon shows its full trend color. Candle coloring follows the ribbon's bull/bear state continuously, giving an immediate read of trend direction on every bar. The dashboard accent color and signal indicators follow the active theme, giving the entire indicator a unified visual identity across chart and panel. 6. Multi-timeframe filter When enabled, the MTF filter evaluates the trend on a higher timeframe using a 50-period EMA. If the higher timeframe trend agrees with the signal direction, a weight bonus is added to the total score. If it disagrees, no bonus is added — but the signal is not blocked unless the score falls below threshold as a result. This behavior is intentional. The HTF filter adds weight to aligned signals without making every counter-trend setup impossible. It rewards confluence with the bigger picture without enforcing hard alignment. Default timeframe: 240 (4-hour). Default weight bonus: 20 points. 7. Backtest and performance tracking Confluence Engine includes a built-in performance tracker that logs every signal, applies configurable stop and target multipliers based on the current regime, and tracks wins, losses, and win rate across the visible history. Stop loss modes: - ATR — a fixed multiple of ATR from the entry price. Simple and consistent. - Pivot — stop placed at the most recent swing low (for longs) or swing high (for shorts). Respects structure. - Supertrend — stop placed at the dynamic Supertrend level at the time of entry. Tighter and adaptive. - Trailing (h15) — stop follows the slowest HMA of the Ultra Ribbon. Trends with the market and gives winners more room. Target multipliers are adjustable for each regime: Scalp, Intraday, and Swing. The regime is determined by the current ADX value. Recent log shows the last three trade results in R multiples. This gives a quick read on recent system performance without requiring a separate journaling tool. Note: the backtest uses bar close logic and approximated fill prices. It is a directional performance reference, not a precise simulation. Session filtering does not retroactively apply to historical trades — enabling session filtering after a test period will affect forward signals but not past performance data. 8. Dashboard reference The dashboard updates on every bar and shows: - Header: indicator name and current timeframe - Pillar rows 1–6: score per pillar, colored by direction - HTF Trend: higher timeframe alignment and weight (when MTF enabled) - Signal: LONG / SHORT / WAIT with direction color - Win Rate: percentage of tracked signals that hit target - Recent Log: last three results in R multiples - Score: total confluence score out of 100 - Session: OPEN or FILTERED The dashboard header and accent colors follow the active ribbon theme. Tiny, Small, and Normal size options are available. 9. Settings reference General Settings - Signal Threshold: minimum score to trigger a signal (50–95, default 70) - Extreme Threshold: score above which extreme confluence is flagged (80–100, default 90) - Directional Lead: minimum gap between bull and bear score (default 20) Multi-Timeframe Trend - Enable MTF Filter - HTF Timeframe (default 240) - HTF Weight (default 20) Quality Filters (Noise Reduction) - Enable ADX Noise Filter - Min ADX Value (0–100, default 35) Trend Confirmation - Enable VWMA Filter + length - Enable Supertrend Filter + ATR length + multiplier - Show/hide Supertrend and VWMA lines Pillar Weights - Individual weight for each of the six pillars Session Filtering - Filter Entries by Session (time gate) - Enable Session Pillar Scoring (premium/discount scoring) - Trading Session input Trade Suggestions (ATR Multipliers) - SL and TP multipliers for Scalp, Intraday, and Swing regimes Ultra Ribbon - Enable Ribbon Filter - Show Ribbon on Chart - Base Length and Length Step - Theme: Classic / Phantom / Custom - Custom color inputs (bull, bear, elite) Backtest & UI - Enable Performance Tracking - Start Year - Show Active Trade Lines - Show Recent Trade Log - Stop Loss Mode: ATR / Pivot / Supertrend / Trailing (h15) UI Settings - Show Dashboard - Dashboard Position - Dashboard Size: Tiny / Small / Normal 10. How to use 10.1 Initial setup 1. Load the indicator on your preferred chart and timeframe. 2. Select a ribbon theme that matches your visual preference. 3. Set the signal threshold based on your desired selectivity. Start at 70. 4. Set the directional lead. 15–20 is a balanced starting point. 5. Enable the hard gates relevant to your style. For intraday trading, ADX + Supertrend is a strong combination. For swing trading, VWMA + MTF adds macro context. 6. Configure the session scoring if you trade specific sessions. NY traders: set session to 1330–2000 UTC (or your local equivalent). 7. Set your backtest start year and stop mode preference. 10.2 Reading a signal When a signal appears: - Check the dashboard. Which pillars are active? A signal with Structure + Volume + Momentum all scoring is stronger than one carried primarily by Session and Volatility. - Check the score. A signal at 72 with a 20-point gap is valid but tight. A signal at 88 with a 30-point gap is a high-conviction setup. - Check the ribbon. Is it cleanly bullish or bearish? Is it near exhaustion color? Signals during ribbon exhaustion carry more risk. - Check the hard gates. They cleared — but were they close? A signal that barely cleared ADX 35 is different from one with ADX at 55. 10.3 Managing entries Confluence Engine does not tell you the exact entry price. It tells you when conditions align. Your entry technique — pullback, breakout, limit at structure — remains your decision. Use the stop mode that fits your trade: ATR for consistency, Pivot for structure-respect, Supertrend for dynamic adaptation, Trailing h15 for trend trades you want to hold. 10.4 Interpreting win rate The built-in win rate is a useful reference, not a guarantee of future performance. A 65% win rate over 50 signals on a specific asset and timeframe tells you the system has been profitable in that environment. It does not guarantee the next signal wins. Win rate should always be evaluated alongside average RR. A 60% win rate at 2R average beats a 70% win rate at 0.8R average. Use the recent log and the trade lines together to assess both dimensions. 10.5 Optimizing settings If you see too many signals: raise the threshold, raise the directional lead, raise the ADX minimum, or enable additional hard gates. If you see too few signals: lower the threshold slightly, reduce the directional lead, or disable one or two hard gates. Do not optimize purely for win rate without considering signal frequency. A system that fires once per week at 80% win rate is different in practice from one that fires daily at 65%. Both can be profitable. Choose what fits your trading style. 11. Timeframe guide 1m–5m — Ultra Ribbon filter on, ADX threshold 30–40, Supertrend on, session scoring on. Focus on fast momentum signals during active sessions. 15m–30m — Full filter stack recommended. Threshold 70–75. Strong balance of frequency and quality. 1H–4H — VWMA and MTF filter add significant value. Threshold 75–80. Fewer signals, higher conviction. Daily — Disable session scoring. Enable VWMA and MTF only. Use as swing context, not scalp tool. 12. What this indicator does not do - Does not predict price direction with certainty - Does not guarantee profitability - Does not replace your own risk management - Does not account for news events, gaps, or liquidity voids - Does not track open positions in real time - Does not connect to any broker or execution system - Does not replace the Risk Management Engine for position sizing and account compliance For position sizing, drawdown compliance, and trade logging, pair with Risk Management Engine | Anonycryptous. For complete session analysis and market context, pair with Environment | Anonycryptous. Together, the three tools cover strategy context, signal generation, and risk execution — a complete framework for structured trading. 13. Disclaimer This indicator is provided for educational and informational purposes only. Nothing in this document constitutes financial advice or any form of recommendation. All trading decisions are made entirely by the user. The indicator provides signal analysis based on configurable parameters — the relevance of any output depends on how those parameters are set and the market conditions in which the indicator is used. Trading financial instruments involves substantial risk of loss. Past performance of the backtest function is not indicative of future results. You may lose all of your invested capital. Anonycryptous accepts no responsibility or liability for any losses incurred as a result of using this indicator or any content in this manual.
Pine Script® indicator
by Anonycryptous
3
In1 + In2 Dual Confirmation SignalsIn1 + In2 Dual Confirmation Signal Indicator What It Tracks This indicator is essentially a two-filter confirmation system designed to keep you out of low-quality trades. It combines two completely different approaches to reading the market — one tracks momentum and trend direction, the other tracks buying/selling pressure — and only fires a signal when both agree at the same time. Think of it like needing two different analysts to sign off on a trade before you take it. The Two Engines In1 — Stochastic SuperTrend The first engine is a hybrid of two classic tools: the RSI and the Stochastic oscillator, fed into a SuperTrend framework. Here's what it's doing under the hood: It calculates the RSI of price, then runs a Stochastic calculation on that RSI (not on price directly). This smooths out a lot of noise. That Stochastic RSI value is then used as the "price" input for a SuperTrend algorithm, which dynamically plots upper and lower bands and flips direction when the value breaks through them. When the SuperTrend flips bullish and the Stochastic RSI is below 50 (not overbought), you get an In1 Buy arrow. When it flips bearish and the Stochastic RSI is above 50 (not oversold), you get an In1 Sell arrow. The below/above 50 filter is important — it prevents the indicator from calling a bullish flip when momentum is already stretched high, and vice versa. In2 — EVEREX (Engineered Volume & Price Flow) The second engine is more sophisticated. It's measuring the quality and direction of buying vs. selling pressure on each candle by looking at multiple factors simultaneously: How the candle closed relative to its range The spread between open and close How much price actually shifted Volume weighting on all of the above It normalizes all of these inputs and produces a single oscillator line. When that line flips from falling to rising, the background goes green (bulls taking over). When it flips from rising to falling, it goes red (bears taking over). The signal fires on those flip moments specifically — not while it's already trending in one direction. How the Dual Confirmation Logic Works This is where it gets smart. The indicator doesn't require both signals on the exact same candle — that would be too restrictive and you'd miss a lot of valid setups. Instead, it uses a lookback window: For a BUY signal to fire: In1 must have printed a bullish arrow on this candle OR within the last 1–2 candles AND if In1 fired 1–2 bars ago (not this candle), the Stochastic RSI line must still be rising — confirming the momentum hasn't already reversed AND In2 must flip green on this candle (that's the confirmation trigger) For a SELL signal to fire: Same logic in reverse — In1 bearish arrow within 1–2 candles, Stoch RSI still falling, In2 flips red The B/S label prints on the candle where In2 flips — that's your entry candle. Adjusting Signal Frequency To get MORE signals (more sensitive, more trades, more false positives): Lower the ST Multiplier (default 10) — a smaller multiplier makes the SuperTrend flip more often Lower the RSI Length (default 10) or K (default 7) — shorter lookbacks react faster Lower the EVEREX Length (default 10) or Signal Length (default 5) — the EVEREX oscillator will flip more frequently To get FEWER signals (more selective, higher quality, fewer trades): Raise the ST Multiplier — SuperTrend becomes harder to flip, only strong moves qualify Raise the RSI Length and K — smoother, slower momentum readings Raise the EVEREX Lookback (default 20) — the volume normalization uses a longer baseline, making it harder for a single candle to register as significant Raise the EVEREX Length and Smooth — the oscillator becomes less twitchy The Timeframe input is also huge — running In1 on a higher timeframe than your chart while watching In2 on the current chart creates a natural multi-timeframe filter that dramatically reduces noise. How Alerts Work There's a single alert condition called "In1+In2 Signal" that fires on either a Buy or Sell signal. When you set up the alert in TradingView, set it to "Once Per Bar Close" for confirmed signals, or "Once Per Bar" if you want real-time notification (more on that below). The message simply tells you a dual confirmation signal fired and to check the chart for the B/S label. Real-Time vs. After Close — The Repainting Question This is the most important thing for any trader to understand about this indicator. In2 (EVEREX) is fully real-time and does NOT repaint. It's calculated purely from current bar data — price action, spread, volume — so what you see on the forming candle is what you get. If it flips green mid-candle, that flip is real. In1 has a setting called "Wait for Timeframe Close." This is critical: When turned ON — In1 only updates when the selected timeframe candle fully closes. The SuperTrend flip is confirmed and will not repaint. This is the safer setting for signal reliability. When turned OFF — In1 updates in real time using lookahead. You'll see signals earlier, but if the higher timeframe candle closes differently than it looked mid-bar, the signal can vanish. This is the classic repainting scenario. The 1–2 bar lookback window for In1 is also non-repainting because it uses dir , bars_since_up, and direction tracking that are all based on closed bar values — once a bar closes, those values are locked. So a signal that printed on a closed candle will stay there. Bottom line for your workflow: Run "Wait for Timeframe Close" set to ON and set your alert to "Once Per Bar Close" — every signal you see on a closed candle is confirmed and won't disappear on you.
Pine Script® indicator
by parkerberlinger
SuperTrend Take-Profit Dimensions [AlgoAlpha]🟠 OVERVIEW A multi-dimensional take-profit aid that scores how typical the current bar looks compared to past SuperTrend pivots, so you can tell when a trend has reached favorable exit conditions. The indicator runs a standard SuperTrend and records every confirmed zigzag pivot that occurs during a matching-direction run. Tops go into a bull pool , bottoms into a bear pool . Each pivot is stored as a set of readings across several independent axes, such as relative volume , time of day , and price position inside the recent range . On every bar, the current reading on each axis is compared to that historical pool. A blended score from 0 to 100 tells you how closely the current conditions resemble where past pivots in the same direction have clustered. The idea is to give trend followers a data-backed sense of when to start tightening up, rather than guessing an exit or using a fixed R-multiple. The three built-in axes were chosen deliberately to be as uncorrelated as possible , each describing a different dimension of market context: volume (relative volume percentile), time (time of day), and price (position in recent range). Correlated inputs would double-count the same information and distort the blended score; picking axes that describe genuinely different aspects of the market means each one contributes independent evidence, and the score reflects how many distinct dimensions are currently in agreement. 🟠 CONCEPTS SuperTrend — An ATR-based trailing stop that flips between bullish and bearish states. Controls which pool of historical pivots the script reads from. Pivot pool — A rolling store of confirmed zigzag pivots, split by direction. Bull pool holds pivot highs that printed during bullish SuperTrend runs; bear pool holds pivot lows from bearish runs. Capped at 2000 entries per side . Context axis — A 0–100 value measured at the pivot bar. The script ships with three built-ins ( relative volume percentile , time of day , position in recent range ) and one optional user-plugged signal. Axis independence — The three built-in axes cover volume , time , and price respectively, chosen so each describes a structurally different part of the market. Low correlation between axes keeps the blended score from being dominated by any single factor. Conditional histogram — For each active axis, the script walks its pool and keeps only pivots whose bins on every other active axis match the current bar. The survivors are binned to form a histogram. Axis score — For one axis, the count of pivots in the current bar's bin divided by the count in the histogram's tallest bin, scaled to 0–100 . 100 means the current context sits in the densest part of past pivots. Blended favourability score — Arithmetic mean of the active per-axis scores. This is what the gauge and table display. Density-match scoring — The score measures how common the current context is among past pivots. It is not a forward probability and makes no claim about what happens next. 🟠 FEATURES Right-side context profiles — Stacked mini histograms render to the right of price, one per active axis. • Bar heights show how pivots in each axis's conditional pool distribute across bins. • A dashed vertical line marks the current bar's bin on that axis, so you can see at a glance where today sits against history. • Bar hue tracks the active SuperTrend direction. Favourability gauge — A vertical gradient table in the bottom-right showing the blended score, with a chevron marking the current level. Green at the top, red at the bottom. Favourability breakdown table — A two-column readout of each active axis's individual score out of 100, plus a final row that classifies the blended score as Good , Neutral , or Bad . Position and text size are configurable. Bar coloring — Bars fade from neutral grey toward the opposing trend colour as the blended score rises toward 100, so the chart itself signals when the context is stretched. Take-profit markers — Small orange markers print above or below the bar when the blended score hits 100 for the active SuperTrend direction. Timeframe guard — The time-of-day axis disables automatically on daily and higher timeframes, where the reading has no meaning, and a banner explains this so the blended score stays honest. Multi-dimensional scoring engine — Four independent axes feed into a single score, each conditioned on all the others. • Three built-in axes can be toggled on or off individually. • A fourth axis accepts any plot via source input , provided the series stays within 0–100 on all loaded bars. • An on-chart warning prints if the custom signal leaves that range, and the axis is ignored until it is corrected. Deliberately uncorrelated built-in axes — Volume ( relative volume percentile ), time ( time of day ), and price ( position in recent range ) cover three structurally different facets of market context. Keeping the axes independent means each one adds new information to the blend rather than reinforcing the others. Alert conditions — Six alerts are included: SuperTrend bullish flip, SuperTrend bearish flip, score peak match, and crossovers into the Good , Neutral , and Bad bands. 🟠 HOW TO USE Add the script to an intraday chart on a liquid instrument and let it run long enough to populate the pools. More history means more stable conditional histograms. Let SuperTrend define the active regime. The script only scores in the direction of the current trend; bar coloring and take-profit markers respect that regime. Read the gauge and breakdown table together. The gauge shows the blended level; the table shows which individual axes are pulling it up or down. Use the right-side profiles as a sanity check. If the dashed current-bin marker is sitting on or near the tallest bar across most axes, the current context closely resembles past pivot contexts in that direction. Treat high scores as a cue to tighten management, not as reversal signals. A reading of 100 means conditions match where pivots have historically clustered, not that the trend is guaranteed to end. Adjust the zigzag pivot length to control how strict the pool is. Lower values admit more pivots ( bigger, noisier sample ); higher values keep only firmer pivots ( smaller, cleaner sample ). Plug your own signal into the custom axis to test whether an existing 0–100 oscillator adds useful conditioning, such as an RSI or a normalised momentum reading. For best results, pick a signal that is not strongly correlated with the three built-ins, so the custom axis adds a new dimension rather than re-stating an existing one. Enable only the alerts that fit your workflow. The band-crossover alerts fire once per transition , not on every bar inside a band. 🟠 LIMITATIONS The pool holds every confirmed pivot during a matching-direction run, not only pivots that ended the trend. Intermediate pullbacks sit alongside genuine terminal pivots. Raising the zigzag pivot length filters the pool further if you want a cleaner sample. On strongly trending symbols the pool is dominated by pullback pivots rather than true terminal exits, because strong trends have many small pullbacks and only one final top or bottom. On choppy symbols the ratio is more balanced. Read the score with this in mind. The blended score is a density-match measure, not a forward probability . A high reading means today's context is common among past pivots of this direction. It does not predict that the trend is about to end. The time-of-day axis has no meaning on daily and higher timeframes and is disabled automatically on those timeframes. A warning banner confirms when this is active. The custom axis requires a source already scaled to 0–100 on every loaded bar. Values outside that range disable the axis and surface a warning. Toggling the custom axis on a live chart starts the range check from the current bar; reload the chart to validate against full loaded history . Pools are capped at 2000 entries per direction , with the oldest entries dropped first. On very long intraday histories the effective lookback is symbol- and timeframe-dependent. All scoring uses data up to and including the confirmation bar of each pivot; pivots themselves are detected with the standard zigzag confirmation lag, meaning the scoring population on any given bar reflects pivots confirmed at least zzLen bars earlier. 🟠 CONCLUSION SuperTrend Take-Profit Dimensions combines a standard SuperTrend with a rolling pool of historical pivot contexts and scores the current bar against that pool across up to four independent axes spanning volume, time, and price. The output is a blended 0–100 favourability reading , a per-axis breakdown, and a set of context profiles that show where past pivots have clustered. It gives trend followers a structured, data-backed way to judge when the current context matches where trends have historically given back profit, without pretending to predict the next bar.
Pine Script® indicator
by AlgoAlpha
10
M15_Scalp_V1This is how I personally set up M15 scalping on EURUSD. Specifically during the London/NY overlap, I built it to search for one high-conviction trend reversal every day. How it operates Selective Entry: Identifies reversals early without purchasing the peak by using a tight SuperTrend and RSI filter. Institutional Filter: To ensure that it only activates when actual money is affecting the market, I included a volume check. Risk First: Based on a 2% risk of my entire balance, it automatically determines lot sizes. One Shot: To prevent overtrading and high-spread hours, trading is restricted to one setup per day between 11:00 AM and 10:00 PM IST. Configuration: Ideal for the M15 period
Pine Script® strategy
by neediness999
M15_Scalp_V1This is how I set up my M15 scalping for EURUSD. I made it so that it looks for one strong trend reversal every day, especially during the London/NY overlap. How it works: Selective Entry: Uses a tight SuperTrend and RSI filter to find reversals early without having to buy at the top. Institutional Filter: I added a volume check so that it only goes off when there is real money moving the market. Risk First: It figures out the lot sizes for me based on a 2% risk of my total balance. One Shot: Only one setup can be traded per day between 11:00 AM and 10:00 PM IST to keep people from overtrading and trading during high-spread hours. Preparation: The M15 timeframe is best for this.
Pine Script® strategy
by neediness999