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Shift Structure Cloud [JOAT]Shift Structure Cloud is an open-source Pine Script v6 overlay that converts confirmed swing structure into a clean adaptive trend cloud. It tracks pivot highs and pivot lows, separates continuation breaks from character shifts, and uses the active structure range to build a dynamic average and multi-layer cloud around price. The problem it solves is structural context. Many trend tools react only to moving averages or oscillator thresholds. This script anchors its visual state to confirmed market structure first, then uses an adaptive cloud to show whether price is trading above, below, or inside the current structural center. The result is a chart layer that can help separate continuation from transition without relying on future bars. Core Concepts 1. Confirmed Pivot Structure The script uses ta.pivothigh() and ta.pivotlow() to confirm swing highs and lows. A pivot is only accepted after the configured right-side confirmation window closes, which means the level is delayed by design but does not depend on unconfirmed future plotting. pivotHigh = ta.pivothigh(high, pivotLeft, pivotRight) pivotLow = ta.pivotlow(low, pivotLeft, pivotRight) if not na(pivotHigh) structureHigh := pivotHigh 2. BOS and CHoCH Logic The current structure high and low become break reference levels. A bullish break occurs when price closes above the prior structure high. A bearish break occurs when price closes below the prior structure low. If the break happens against the previous side, it is classified as CHoCH; otherwise it is a continuation BOS. bullBreakRaw = barstate.isconfirmed and not na(priorHigh) and close > priorHigh and priorClose <= priorHigh bearBreakRaw = barstate.isconfirmed and not na(priorLow) and close < priorLow and priorClose >= priorLow bullChoCh = bullBreak and trendSide == -1 bearChoCh = bearBreak and trendSide == 1 3. Adaptive Structure Average Instead of plotting only fixed swing levels, the script calculates the midpoint between the active structure high and low. The midpoint is then smoothed with an adaptive alpha. When price moves far from the structural center, the average becomes more responsive; when price is balanced, it becomes slower. structureMid = (activeHigh + activeLow) * 0.5 structureDrift = f_clamp(math.abs(close - structureMid) / legSize, 0.0, 1.0) adaptAlpha = slowAlpha + (fastAlpha - slowAlpha) * structureDrift structureAverage := structureAverage + adaptAlpha * (structureMid - structureAverage ) 4. Multi-Layer Cloud The cloud is built from ATR-adjusted bands around the adaptive structure average. Inner, middle, and outer layers give a visual read of compression, transition, and extended distance from structure. 5. Strength-Based Candle Coloring When enabled, candles are repainted with a gradient based on distance from the structure average. The candle color is informational only; it does not change the underlying chart data. Features Confirmed BOS and CHoCH detection: Structural events are gated with barstate.isconfirmed Adaptive structure average: A dynamic centerline based on active swing range and price drift Layered trend cloud: Inner, middle, and outer ATR bands visualize distance from structure Structure high and low levels: Current confirmed swing levels can be shown as reference lines Gradient candle mode: Optional candle coloring by structural distance Compact dashboard: Shows side, last shift, strength, bars since shift, and active range Palette presets: Aqua Rose, Neon Desk, Mint Pulse, and VWAP Field Alert conditions: Separate alerts for bullish BOS, bearish BOS, bullish CHoCH, and bearish CHoCH Input Parameters Visual System: Palette Preset: Selects the bull and bear color pair Color Candles: Enables structural candle coloring Dashboard: Shows or hides the top-right dashboard Pivot Dots: Shows confirmed pivot dots Structure Engine: Pivot Left / Pivot Right: Controls swing confirmation sensitivity Fast Adapt Length: Fast smoothing response for the adaptive average Slow Adapt Length: Slow smoothing response for balanced conditions Cloud ATR Length: ATR length used for cloud width Cloud Width: Multiplier applied to the cloud distance BOS and CHoCH Marks: Shows structural event markers Structure Levels: Shows active swing high and low reference lines How to Use This Indicator Step 1: Read the Cloud Side If price is above the adaptive structure average and the cloud is colored bullish, the current structural state favors upside continuation. If price is below and the cloud is bearish, the state favors downside continuation. Step 2: Watch CHoCH Events CHoCH labels mark breaks against the previous structural side. They are useful as transition warnings, not automatic entries. Step 3: Use the Structure Levels The active high and low lines show where the next confirmed break could occur. These are the levels the script uses for BOS and CHoCH classification. Step 4: Combine with Your Own Trigger This script is designed as a structure and context layer. Use it with your own entry model, risk plan, and market selection process. Indicator Limitations Pivot levels confirm after the right-side pivot window closes, so they are intentionally delayed A fast reversal can occur before a new pivot is confirmed Cloud distance is ATR-based, so very low volatility markets can compress the visual bands The script classifies structure; it does not predict future price movement Originality Statement Shift Structure Cloud combines confirmed BOS/CHoCH logic, an adaptive structure midpoint, ATR cloud geometry, and strength-colored candles in one original Pine v6 implementation. The script is not a pasted source clone. It rebuilds structure analysis from public Pine mechanics and adds a distinct visual model around the current swing range. Disclaimer This script is provided for educational and informational use only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Signals and structure readings are based on historical chart data and can be wrong in live market conditions. Always use independent analysis and proper risk management. -Made with passion by jackofalltrades
Pine Script®指標
由officialjackofalltrades提供
Tectonic Regime Protocol [JOAT]Tectonic Regime Protocol Introduction Tectonic Regime Protocol is an open-source Pine Script v6 strategy that combines four analytical modules into a single rule-based trading system: a four-state regime classifier, a three-layer trend filter, a six-pillar confluence entry engine, and an adaptive exit module using ATR-based partial take-profit and a regime-adaptive trailing stop. The strategy is designed for traders who want a fully automated systematic framework to study how regime-gating affects signal quality. Its primary hypothesis is that directional entries made when (1) the market is classified as a trending regime, (2) trend filters across multiple timeframes align, and (3) multiple structural, volume, and momentum inputs agree, produce statistically better outcomes than entries based on any single condition alone. Strategy Default Properties Initial capital: $100,000 Order size: 2% of equity per trade Commission: 0.04% per side Slippage: 2 ticks Maximum open positions: 1 These settings represent realistic conditions for a funded discretionary trader using a liquid futures or equity instrument. The 2% equity sizing limits maximum theoretical drawdown from any single trade while providing meaningful position exposure. Commission and slippage values reflect typical institutional-grade execution costs for electronically traded instruments. Core Concepts 1. Four-State Regime Classifier The regime module classifies each bar into one of four states using ADX relative to a threshold and the ATR-to-SMA(ATR) ratio: Trend Bull, Trend Bear, Range High-Vol, Range Low-Vol. Only Trend states are eligible for entry. Range classifications suppress all entries regardless of how strong the confluence score is. This is the primary market context filter. 2. Three-Layer Trend Filter Three independently computed trend conditions must all agree before a long or short entry is considered: close versus VWMA(200) determines whether price is above or below long-term value; the relationship between fast and slow HMA lines determines medium-term momentum direction; and the close versus a 50-period EMA on a higher timeframe provides multi-timeframe context. 3. Six-Pillar Confluence Score The entry engine scores six market dimensions and requires the composite bull or bear score to exceed 50 of 100 (default, configurable) with a directional lead of at least 8 points above the opposing score. The six pillars are: market structure, OBV slope direction, KAMA position + RSI + WPR composite, swing-low liquidity sweep detection, ATR ratio in productive range, and Fractal Efficiency Ratio above 0.30. bool longSetup = validRegime and regime == 1 and trendBull and bull >= confThreshold and (bull - bear) >= confGap and barstate.isconfirmed 4. Adaptive Exit Module The exit logic uses partial exits at two take-profit levels. TP1 closes 50% of the position at 1.0× risk distance. TP2 closes the remaining position at 2.0× risk distance. After TP1 is reached, the stop is moved to the entry price (breakeven). The stop before TP1 uses a regime-adaptive ATR trail — the stop multiplier is lower in low-volatility regimes (tighter) and higher in high-volatility regimes (looser). A 30-bar time-based exit closes any remaining position if neither TP nor stop is reached. 5. Non-Repainting Architecture All entry conditions are evaluated only when barstate.isconfirmed is true. The HTF EMA is requested with lookahead=barmerge.lookahead_off. Pivot-based conditions use confirmed pivot detection with symmetric lookback. No future bar references are used. Default Settings and Performance Notes The strategy is published with the default Properties values listed above. Results shown on the publication chart are generated using these exact settings. Commission of 0.04% per side is representative of typical electronic execution on liquid instruments. Win rate alone does not characterize strategy performance. The strategy is designed around a two-tier partial exit structure targeting positive expectancy (wins × average win greater than losses × average loss) rather than high win rate. The profit factor and average R-multiple are the more relevant metrics for this type of system. Input Parameters Regime Module: ADX Trend Threshold (default: 20) ATR Ratio High-Vol Threshold (default: 1.2) Trend Filter: VWMA Length (default: 200) Ribbon Fast HMA and Slow HMA lengths HTF Timeframe for EMA(50) filter (default: 240) Enable HTF Filter toggle Confluence Engine: Min Score (default: 50, range 50–95) Min Direction Lead (default: 8) Min FER (default: 0.30) FER Lookback (default: 14) Individual pillar weights (Structure, Volume, Momentum, Liquidity, Volatility, FER) Exit Module: TP1 RR Multiple (default: 1.0) TP2 RR Multiple (default: 2.0) Stop Multiplier for Low / Med / High Volatility Regimes Max Bars Hold (default: 30) How to Evaluate This Strategy Apply it to a liquid instrument with sufficient historical data to generate more than 100 trades. Compare profit factor, Sharpe ratio, average R-multiple, and maximum drawdown — not win rate in isolation. Test it across at least two different instruments or timeframes to assess whether the results reflect genuine structural edge or data-fitting to one specific market. The strategy is not optimized for any single market. Default parameters are deliberately conservative to avoid overfitting. Users who adjust parameters to improve backtested results should recognize that improvement on historical data does not guarantee improvement on future data. Strategy Limitations On lower-timeframe charts with short histories, fewer than 100 trades may result, reducing the statistical reliability of the backtest The HTF filter uses request.security() with a higher timeframe EMA. In live trading, the HTF value updates when the higher timeframe bar closes, which may differ slightly from live server-side execution ATR-based stops and targets mean position sizes and outcomes scale with volatility. In abnormally low-volatility environments, commission costs represent a larger proportion of expected gain The time-based exit at 30 bars may close profitable positions before TP2 is reached in slow-moving markets Backtested performance on any instrument does not predict future performance. Markets change, and parameters that produced edge historically may not do so in future regimes Originality Statement Combining a four-state regime classifier, a three-layer multi-timeframe trend filter, a six-pillar confluence score including Fractal Efficiency Ratio, and a partial-exit adaptive trailing stop system in a single non-repainting open-source strategy is an original integration of methods The Fractal Efficiency Ratio as a pillar in a multi-factor entry score, and as a required gate condition for entry, is not present in existing open-source Pine Script v6 strategy publications as of this writing The regime-adaptive stop multiplier — loosening in high-volatility regimes and tightening in low-volatility regimes — is an original stop calibration approach within this strategic framework The dual entry mode (edge transition OR re-entry when flat with elevated score) increases signal frequency without compromising the fundamental regime and trend filter requirements Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Backtested results are simulated and do not represent real trading. Simulated results have inherent limitations and may not reflect actual trading outcomes due to market impact, execution differences, and changing market conditions. Past backtested performance does not guarantee future results. Trading involves substantial risk of loss. Always conduct independent due diligence and apply proper risk management before using any strategy with real capital. The author accepts no responsibility for trading losses resulting from use of this strategy. Made with passion by jackofalltrades
Pine Script®策略
由officialjackofalltrades提供
Entropic Regime Field [JOAT]Entropic Regime Field is an open-source market state classifier that uses three quantitative measures — Fractal Efficiency Ratio, a synthetic Hurst Exponent approximation, and a Garman-Klass volatility estimator — to classify each bar into one of three entropy states: LOW (predictable, directional structure present), TRANSITION (regime shift underway), and HIGH (chaotic, low-predictability environment). Directional signals from an Adaptive Momentum Oscillator are filtered to fire only during LOW entropy states, where momentum signals have historically more reliable edge than during random or chaotic market behavior. The foundational premise is that markets alternate between periods of organized directional behavior and periods of disorganized random movement. Trading momentum signals indiscriminately across both environments degrades overall performance because the same signal that has edge in a trending market produces random outcomes in a chaotic one. By measuring the structural organization of price movement directly — rather than relying on ADX alone, which is a lagging momentum derivative — Entropic Regime Field attempts to identify when the market's behavior is organized enough for directional signals to have context. Core Concepts 1. Fractal Efficiency Ratio (FER) The FER measures how efficiently price has moved over a lookback period — the ratio of the net directional distance to the total path length of individual bar-to-bar changes. A value near 1.0 indicates straight-line directional movement; a value near 0.0 indicates constant reversals: float ferNet = math.abs(close - close ) float ferPath = math.sum(math.abs(ta.change(close)), ferLen) float ferVal = ferPath > 0.0 ? ferNet / ferPath : 0.0 2. Synthetic Hurst Exponent The Hurst Exponent characterizes the memory of a time series. Values above 0.5 indicate persistence (trending), values near 0.5 indicate randomness, and values below 0.5 indicate anti-persistence (mean-reversion). A simplified Hurst estimate is computed using the variance ratio method: float var1 = ta.variance(ta.change(close, 1), hurstWindow) float var5 = ta.variance(ta.change(close, 5) / 5, hurstWindow) float hurstEst= 0.5 * math.log(var1 / var5) / math.log(5) + 0.5 3. Garman-Klass Volatility Estimator Standard ATR uses only the prior close and current high/low. The Garman-Klass estimator uses all four OHLC prices, producing a more statistically efficient estimate of true volatility: gkBar = 0.5 * math.pow(math.log(high / math.max(low, syminfo.mintick)), 2.0) - (2.0 * math.log(2.0) - 1.0) * math.pow(math.log(close / math.max(open, syminfo.mintick)), 2.0) The GK estimate is averaged over a configurable period and normalized to a 0-100 percentile rank over the trailing 100 bars. 4. Three-Factor Entropy Classification LOW entropy requires FER above a threshold AND ADX above a minimum AND Hurst estimate above 0.52. HIGH entropy is triggered when FER falls below a lower threshold OR ADX falls below a minimum. TRANSITION is the state between the two. 5. Adaptive Momentum Oscillator (AMO) The AMO blends three momentum inputs with fixed weights: RSI(14) centered at 50 (40%), Stochastic(14) centered at 50 (35%), and Williams Percent Range(14) centered at -50 (25%). Directional signals fire only in LOW entropy when AMO crosses zero and KAMA confirms via crossover/under. Features Fractal Efficiency Ratio: Net directional move divided by total path length, configurable lookback Synthetic Hurst Exponent: Variance ratio approximation identifying persistent vs. anti-persistent price behavior Garman-Klass volatility: OHLC-based volatility estimator normalized to percentile rank over 100 bars Three entropy states: LOW, TRANSITION, HIGH — each with distinct visual treatment 10-line entropy ribbon: EMA lines colored by entropy state for visual history of regime transitions Adaptive Momentum Oscillator: RSI + Stochastic + WPR composite with fixed optimal weights Entropy-gated signals: AMO + KAMA confirmation signals fire only in LOW entropy state Regime background tint: Background tinted by entropy state, cleared after 10 bars Trade block on signal: ATR-based TP and stop rendered as boxes on signal bars 12-row institutional dashboard: FER, Hurst estimate, GK volatility percentile, ADX, AMO, entropy state, signal, win rate, bars in current state Non-repainting: All signals gated by barstate.isconfirmed; no future data referenced Four color themes: Phantom, Neon, Classic, Solar Input Parameters Fractal Efficiency: FER Lookback (default: 14) LOW Entropy FER Minimum (default: 0.60) HIGH Entropy FER Maximum (default: 0.35) Hurst Exponent: Hurst Window (default: 20) LOW Entropy Hurst Minimum (default: 0.52) Garman-Klass Volatility: GK Averaging Length (default: 14) ADX Gate: Min ADX for LOW Entropy (default: 22) Signal: AMO Cross Threshold, KAMA Period, Cooldown Bars TP ATR Multiple, SL ATR Multiple How to Use This Indicator Step 1: Read the Entropy State Check the dashboard. LOW entropy means the market is behaving in an organized, directional way — this is when momentum signals carry more weight. HIGH entropy means the market is chaotic — avoid directional signals. Step 2: Watch FER and Hurst Together FER and Hurst are independent measures of market organization. When both agree (high FER AND Hurst > 0.52 simultaneously), the LOW entropy classification is more reliable. Step 3: Enter on AMO + KAMA Confirmation Signals fire only when the AMO crosses zero in the signal direction AND price crosses the KAMA level simultaneously. Both conditions must occur on the same confirmed bar in a LOW entropy environment. Indicator Limitations The Hurst approximation via variance ratio is a simplified estimate. It should be treated as a directional indicator of persistence, not a precise statistical measure The FER computation on every bar may affect chart loading performance for very long lookback periods on large datasets LOW entropy classifications can persist during slow grinding trends that produce high FER but low volatility. These environments may produce signals with narrower ATR-based targets The GK estimator can return unreliable values when open equals close (as occurs on some synthetic instruments or during gaps) This indicator classifies entropy state. It does not predict how long the state will persist or when it will change Originality Statement The combination of Fractal Efficiency Ratio, synthetic Hurst Exponent via variance ratio, and Garman-Klass volatility estimator as a three-factor entropy classification system gating AMO momentum signals is not replicated in any existing open-source Pine Script v6 publication as of this writing The Garman-Klass estimator as a volatility input provides a more statistically efficient OHLC-based volatility measure that captures intraday range information not available in ATR Gating a composite three-input momentum oscillator by an entropy state derived from completely different mathematical principles (efficiency, persistence, and OHLC volatility) rather than using a single lagging derivative like ADX as the sole filter is an original analytical architecture Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Entropy classifications are approximations based on historical price data and do not guarantee future market behavior will repeat. The Hurst approximation used is a simplified estimate, not a statistically rigorous computation. Past win rates do not predict future performance. The author accepts no responsibility for trading losses resulting from use of this indicator. Made with passion by jackofalltrades
Pine Script®指標
由officialjackofalltrades提供
Kinetic Ribbon Trail [JOAT]Kinetic Ribbon Trail Introduction Kinetic Ribbon Trail is an open-source trend-following indicator built on two structural layers: a 20-line Hull Moving Average gradient ribbon that quantifies the spread and conviction of near-term versus long-term momentum, and a Fibonacci-anchored adaptive trailing stop that adjusts its sensitivity based on the current swing structure and volatility ratio. The two layers interact — the ribbon provides visual context for momentum strength while the trail provides the dynamic level that determines directional bias. The unique analytical contribution is the ribbon normalization. Most HMA ribbon indicators simply plot multiple lines and fill between them. Kinetic Ribbon Trail computes the signed spread between the fastest and slowest ribbon line, normalizes it by the 200-bar exponential average of that spread, clamps it to a -1 to +1 range, and uses the result to drive a continuous color gradient between the bear and bull theme colors. This means the ribbon's color intensity directly reflects how unusual the current momentum spread is relative to its historical average — not just whether the ribbon is bullish or bearish. Core Concepts 1. 20-Line HMA Ribbon with rFactor Normalization Twenty Hull Moving Average lines are computed from a base period, incrementing by a configurable step. The spread between the fastest and slowest line is the primary signal variable: rSpread = rh01 - rh20 rAvgSpread = ta.ema(math.abs(rSpread), 200) rFactor = math.max(-1, math.min(1, rSpread / (rAvgSpread * 1.5 + 1e-9))) rCol = color.from_gradient(rFactor, -1, 1, colorBEAR, colorBULL) When the fastest line is far above the slowest relative to its recent average, rFactor approaches +1 and the ribbon glows in full bull theme color. The gradient reflects spread magnitude — a bullish spread twice as wide as normal appears more saturated than one just barely positive. 2. Fibonacci Adaptive Trailing Stop The trailing stop anchors to swing structure rather than to fixed ATR multiples. Confirmed swing highs and lows define a Fibonacci range. Three trail levels are computed from this range at the 0.382, 0.5, and 0.618 Fibonacci retracement. One is selected based on the trail mode: Aggressive, Balanced, or Conservative. A volatility adjustment scales the selected level by the inverse of the current volatility ratio. The trail ratchets: for longs, it can only move up. For shorts, it can only move down. A flip occurs when price closes through the trail level with body ratio and penetration confirmation. 3. Four-State Regime Detection A four-state regime classification determines which visual treatments are active: Trend Bull, Trend Bear, Range High-Vol, Range Low-Vol. The classification uses ADX relative to a threshold and the ATR-to-SMA(ATR) ratio. When a regime transition occurs, the chart background is tinted for 10 bars in the corresponding theme color before clearing. 4. Six-Factor Confidence Score Each signal is assigned a confidence grade (D through A+) based on six weighted factors: swing structure alignment (20%), regime alignment (20%), ADX strength (15%), volume participation (15%), volatility favorability (15%), and SMA50 proximity to trail level (15%). Signals below a user-set minimum grade are suppressed. Features 20-line HMA gradient ribbon: rFactor-normalized color gradient reflecting momentum spread intensity vs. its 200-bar historical average 19 ribbon fill layers: Adjacent HMA lines filled with gradient opacity layers for depth visualization Fibonacci adaptive trailing stop: Trail anchored to swing structure at 0.382 / 0.5 / 0.618 Fibonacci levels with volatility adjustment Trail ratchet with flip confirmation: Trail advances in one direction only; flips require body ratio and penetration confirmation Gradient trail fill: Fill between trail and close — top color opaque, bottom color transparent Four-state regime detection: Trend Bull, Trend Bear, Range High-Vol, Range Low-Vol with background tint on transition Six-factor confidence scoring: A+ / A / B / C / D grading system applied to each signal Confidence filter: Signals below the minimum confidence grade are suppressed Trade block on trail flip: Entry, stop, TP1/TP2/TP3 rendered as gradient boxes on confirmed flip signals Backtest tracker: Win rate and expected value Four color themes: Phantom, Neon, Classic, Solar Non-repainting: All signals gated by barstate.isconfirmed Institutional dashboard: 13-row table with regime, trail level, confidence grade, signal, TP/SL levels, and performance stats Input Parameters Ribbon: Base Length: Fastest HMA period (default: 10) Step: Increment between each ribbon line (default: 14) Fibonacci Trail: Trail Mode: Aggressive (0.618) / Balanced (0.5) / Conservative (0.382) / Auto (regime-adaptive) Pivot Lookback: Bars required to confirm a swing pivot Confidence: Enable Confidence Filter toggle Min Signal Grade: D / C / B / A / A+ Trade Levels: Show Trade Block toggle Risk Preset: Conservative / Balanced / Aggressive / Scalping Extend Bars: How far lines project right How to Use This Indicator Step 1: Read the Ribbon Color A deeply saturated bull color means the ribbon spread is unusually wide — momentum is strong. A muted or transitional color means the spread is near its historical average — momentum is uncertain. Step 2: Watch for Trail Flips A signal fires when the Fibonacci trail flips direction and confidence meets the minimum grade. The trade block appears immediately with entry, stop, and three TP levels. Step 3: Use Regime Context The four-state regime in the dashboard tells you whether you are in a trending or ranging environment. High-confidence signals in trending regimes carry more structural weight than the same grade in a ranging regime. Indicator Limitations Swing detection uses ta.pivothigh() and ta.pivotlow() with a lookback offset. The Fibonacci levels are computed from swings confirmed bars after they occurred In markets with very shallow swing structures, the Fibonacci range can be small relative to ATR, causing the trail to cluster near the current price and produce excessive flips The 20-line ribbon increases visual complexity. Reducing the base length and step can make the ribbon more compact on busy charts The confidence score uses volume as one factor. On timeframes or instruments where volume is not meaningful, this factor should carry less weight Regime detection uses ADX, which lags price. A trend that begins explosively may be classified as ranging for several bars before ADX responds Originality Statement The rFactor normalization — dividing ribbon spread by a 200-bar EMA of absolute ribbon spread, clamped to -1/+1, driving a continuous color.from_gradient() — is an original approach to HMA ribbon coloring that reflects relative momentum intensity rather than absolute direction Anchoring a trailing stop to Fibonacci retracements of the current confirmed swing structure, with volatility-ratio adjustment and body/penetration confirmation on flips, is distinct from standard ATR-multiplier trailing stops The six-factor confidence scoring system applied per signal, producing an A+ to D grade that gates signal output, provides per-trade quality assessment within the indicator itself Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Past confidence grades and win rates do not predict future performance. The author accepts no responsibility for trading losses resulting from use of this indicator. Made with passion by jackofalltrades
Pine Script®指標
由officialjackofalltrades提供
Entropic Liquidity Manifold [JOAT]Entropic Liquidity Manifold Introduction Entropic Liquidity Manifold builds an adaptive POC-style liquidity mean using volume density, auction entropy, displacement, and release scoring. This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used. Core Concepts 1. Adaptive Manifold The equilibrium updates faster when density and entropy rise. 2. Volume Density Volume divided by bar range estimates participation concentration. 3. Auction Entropy Close location identifies whether the auction is balanced or directional. 4. Absorption vs Release High density with balance supports absorption, while displacement with direction supports release. manifold := manifold + adaptiveAlpha * (hlc3 - manifold) Features Adaptive liquidity mean Upper and lower shelves Entropy trace Absorption node markers L+ and L- release labels Input Parameters Density and entropy memory Release and absorption gates Cooldown Manifold, candle, and HUD toggles HUD position selector How to Use This Script Use the manifold as an adaptive auction reference. Absorption nodes mark balance; L+ and L- mark confirmed directional release. Limitations The script uses historical OHLCV data and cannot know future prices. Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting. Model outputs should be interpreted with market context, risk controls, and independent analysis. No visual state should be treated as a certain trade outcome. Originality Statement ELM is original in combining adaptive equilibrium, density, entropy, displacement, and release scoring. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment. -Made with passion by jackofalltrades
Pine Script®指標
由officialjackofalltrades提供
Regime Execution Strategy [JOAT]Regime Execution Strategy Introduction Regime Execution Strategy is an open-source TradingView strategy that integrates adaptive forecast context, extreme-channel state, trend pressure, relative volume, and EMA structure into a single rule-based execution model. The strategy is designed to be realistic, non-repainting, and readable rather than curve-fit to one symbol. The problem it solves is trade filtering. A single signal source can trigger too often in poor conditions. Regime Execution Strategy requires multiple independent votes before entries are allowed, then uses ATR-based stop and target logic for consistent risk framing. Core Concepts 1. Adaptive Forecast Bias The strategy estimates a dynamic mean and band structure. Price above or below the adaptive mean contributes to directional bias. 2. Extreme Channel Bias Persistent upper and lower channel levels define a midpoint and directional state. The channel contributes a second independent vote. 3. Pressure and Structure Gate Momentum, pullback location, and fast/slow EMA structure contribute to the regime score. A minimum vote count and relative-volume filter are required before entry. longSignal = barstate.isconfirmed and bullVotes >= voteThreshold and bullRegime and (longBreakout or longReclaim) 4. ATR-Based Risk Management Stops and targets are derived from ATR and position average price. The strategy also includes max drawdown and max intraday filled order risk controls. Features Integrated regime detection: Forecast, channel, pressure, and EMA structure combine into a regime score Multi-vote entry logic: Entries require several independent components to align More active defaults: Default RVOL and regime thresholds are permissive enough to participate across many timeframes ATR stop and target: Risk is framed with volatility-adjusted exits Bias-flip exits: Positions can close when the opposing regime gains enough votes Risk controls: Max drawdown and max intraday filled orders are included Overlay visuals: Forecast bands and adaptive channel context can be displayed on chart Top-right dashboard: Regime, score, pressure, RVOL, votes, position, band width, and setup Alerts: Long and short setup events Input Parameters Forecast: Source, Forgetting Factor, Regression Horizon, Band Multiplier, ATR Blend, and Rebase Interval Regime: Fast EMA and Slow EMA: Trend structure references Pressure Length: Momentum and pullback window Pressure Threshold: Minimum pressure vote threshold Min RVOL: Participation filter Min Votes: Minimum number of aligned components for entries Risk: Stop ATR: Stop distance multiplier Target ATR: Target distance multiplier Max Drawdown %: Strategy risk halt setting Max Intraday Filled Orders: Limits daily trade frequency How to Use This Strategy Step 1: Read the dashboard regime before judging entries. Step 2: Use votes and pressure to understand why a setup qualified. Step 3: Review stop and target settings for the symbol and timeframe being tested. Step 4: Evaluate results across multiple markets and date ranges, not one optimized window. Strategy Limitations This strategy is not optimized for a specific symbol or timeframe More active defaults can increase trade count and also increase exposure to choppy periods Backtest fills are simulated by TradingView and may not match live execution All entry signals use confirmed-bar logic, so entries can occur after the intrabar move has begun Strategy performance should be evaluated with realistic commission, slippage, and position sizing Originality Statement Regime Execution Strategy is original in its integration of adaptive forecast bias, extreme-channel state, pressure voting, relative volume gating, EMA structure, ATR exits, and dashboard reporting into one open-source strategy. It does not copy third-party source code. Disclaimer This open-source strategy is for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any instrument. Backtested results do not predict future performance. Trading involves substantial risk, and users are responsible for their own risk management. -Made with passion by jackofalltrades
Pine Script®策略
由officialjackofalltrades提供
Adaptive Forecast Bands [JOAT]Adaptive Forecast Bands Introduction Adaptive Forecast Bands is an open-source adaptive regression and mean-reversion framework. It estimates a live fair-value path from price, wraps that path in volatility-aware bands, and marks confirmed re-entry conditions only after the bar closes. The problem this indicator solves is context around stretched price. A static moving average band can lag badly when volatility changes. Adaptive Forecast Bands uses a recursive regression engine, a live model error estimate, and an ATR blend so the envelope expands and contracts with current market behavior. Core Concepts 1. Adaptive Regression Mean The centerline is built from a persistent two-parameter regression state. The script uses normalized local time so the model does not depend on raw bar index growth over long histories. forecastMean = beta0 + beta1 * xNorm forecastErr = source - forecastMean 2. Error-Based Confidence Bands Band width is derived from the model's exponentially weighted error plus an ATR component. This keeps the band reactive to both forecast error and realized volatility. 3. Confirmed Re-Entry Signals The script arms a long or short setup when price reaches an outer band. A signal only prints when price confirms a re-entry back through the relevant band on `barstate.isconfirmed`. 4. Forecast Guide Lines The right-edge guide projects the current regression slope forward for visual context. It is a guide, not a prediction, and is redrawn on the last bar to avoid object clutter. Features Adaptive fair-value line: Recursive regression centerline based on current price behavior Volatility-aware envelope: Error variance and ATR combine to form dynamic upper/lower bands Confirmed long/short labels: Re-entry signals use closed-bar logic Right-edge forecast guide: Dashed and dotted guide lines show current slope context Top-right dashboard: Bias, confidence, band width, slope, guide state, and signal state Alert conditions: Long and short confirmed re-entry events Input Parameters Model: Source: Price source used by the model Forgetting Factor: How quickly the model adapts to new price information Regression Horizon: Normalization horizon for the regression slope Band Multiplier: Multiplier applied to model error ATR Blend: Extra realized-volatility padding in the band width Rebase Interval: Periodic reset to keep the adaptive model stable How to Use This Indicator Step 1: Use the centerline as an adaptive fair-value reference. Step 2: Treat outer-band touches as stretched conditions, not immediate entries. Step 3: Wait for confirmed re-entry labels when enabled. Step 4: Read the dashboard confidence and slope before interpreting the signal. Indicator Limitations The right-edge guide is a visualization of current model slope, not a forecast guarantee Mean-reversion signals can underperform during strong directional trends The model periodically rebases by design to reduce long-history numerical drift Signals are confirmed on closed bars and can appear after the intrabar extreme occurred Originality Statement Adaptive Forecast Bands is an original JOAT implementation combining normalized recursive regression, error-based confidence bands, ATR blending, confirmed re-entry logic, and a compact interpretive dashboard. It does not copy third-party source code. Disclaimer This open-source indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves risk, and historical behavior does not ensure future results. Always use proper risk management. -Made with passion by jackofalltrades
Pine Script®指標
由officialjackofalltrades提供
Aegis Liquidity Ledger [JOAT]Aegis Liquidity Ledger Introduction Aegis Liquidity Ledger is an open-source liquidity pressure indicator built to answer a specific execution question: Where is directional pressure being sourced, and where has that pressure already left behind a meaningful area of interest? The script approaches that problem through two linked components: a volatility-normalized pressure oscillator shelf detection and origin-zone mapping The oscillator explains whether participation is pushing in a bullish or bearish direction. The shelf and origin logic explains where that pressure emerged from. This separation is intentional. It gives traders both the why and the where without forcing everything into a single overlay object. Core Concepts 1. Composite Pressure Engine The script blends multiple rate-of-change windows into one composite pressure signal. Short-term impulse and slower campaign participation are both included so the output does not depend on a single lookback length. 2. Volatility-Normalized Thresholds The pressure signal is measured against its own recent standard deviation rather than a fixed threshold. This allows the expansion bands to adapt to the instrument and timeframe being viewed. 3. Shelf Detection The script scans for repeated upper and lower interactions using body extremes and wick touches. That makes the shelf logic more sensitive to areas where liquidity may have repeatedly rested. 4. Expansion Origin Zones When pressure transitions through an adaptive bound on a confirmed bar, the script creates a source zone around the origin candle that preceded the release. This zone remains relevant until price fully accepts through it. 5. Mitigation Logic Shelves are not removed immediately. They remain live until price fully accepts through the opposite side of the zone, after which they are visually de-emphasized as mitigated. Features Four-window pressure model: fast, medium, slow, and macro ROC blended together Pressure smoothing: EMA smoothing controls oscillator responsiveness Adaptive expansion thresholds: thresholds scale with recent pressure volatility Normalized oscillator: pane output compresses pressure into an interpretable range Demand and supply shelves: persistent shelf zones are drawn directly on the chart Origin-zone logic: shelf creation is tied to confirmed expansion events Touch and intensity tracking: shelf labels summarize interaction count and density Mitigation state: zones are visually softened after full acceptance through them Pressure-based candle coloring: optional chart bars reflect dominant liquidity pressure Institutional dashboard: dashboard summarizes pressure, compression, shelf dominance, and state Input Parameters Pressure Engine Fast ROC Medium ROC Slow ROC Macro ROC Pressure Smoothing Expansion Threshold Multiplier Liquidity Shelves Shelf Window Shelf Width ATR Max Live Shelves Per Side Show Expansion Origin Zones Show Shelf Labels Display Show Pressure Fill Show Expansion Glow Show Zero Line Color Candles By Pressure Dashboard Position Dashboard Size How to Use This Indicator Step 1: Read Pressure Before Reading Shelves Start in the pane. If the pressure engine is neutral or compressed, shelf interactions are more likely to behave as reaction zones than true continuation sources. Step 2: Watch for Confirmed Expansion New shelves matter most when they are created by a confirmed expansion through the adaptive threshold. That is the moment the script treats the move as meaningful enough to register an origin. Step 3: Distinguish Live From Mitigated Zones Fresh shelves are stronger contextual references than mitigated shelves. Once a zone has been fully accepted through, it should be treated as reduced context rather than untouched inventory. Step 4: Compare Upper and Lower Density The interaction counts and intensity values help frame whether the instrument has built more meaningful supply or demand shelves in the current environment. Step 5: Combine With Structure Aegis Liquidity Ledger is not a standalone regime classifier. It works best beside structure or session tools that explain the broader context around the pressure source. Indicator Limitations Liquidity shelves are inferred from price behavior, not from direct order book or market-by-order data Aggressive settings can create more shelves than slower traders may want to track Pressure normalization adapts to the instrument, but abrupt volatility shocks can still distort thresholds temporarily A shelf is an area of contextual interest, not a guarantee of reversal or continuation Originality Statement Aegis Liquidity Ledger is structured around the relationship between a normalized pressure oscillator and persistent source-zone shelves. Its design emphasizes where pressure comes from, how dense liquidity has been on each side of price, and whether a prior source has been mitigated, rather than simply plotting another momentum line. Disclaimer This indicator is provided for educational and informational purposes only. It is not a recommendation to trade and should not be interpreted as financial advice. All shelf and pressure readings are model-based interpretations of chart data and can fail under changing market conditions. Always use independent analysis and risk management.
Pine Script®指標
由officialjackofalltrades提供
Vesper Divergence Cascade [JOAT]Vesper Divergence Cascade Introduction Vesper Divergence Cascade is an open-source divergence and response-structure overlay built around RSI pivots and a smoothed T3 ribbon. It detects regular and hidden bullish or bearish divergence, then maps the likely response area with projected zones, corridors, and target guides directly on the chart. The problem this script solves is incomplete divergence analysis. Many divergence tools draw a line and stop there. That leaves the user without context about whether the move is aligned with local structure, whether the divergence developed in an overbought or oversold condition, and where price might respond if the divergence matters. Vesper Divergence Cascade adds that missing structure. Core Concepts 1. Pivot-Based Divergence Detection Confirmed price pivots are stored alongside the RSI value that existed at the pivot bar. This allows the script to compare current and prior pivot pairs without relying on unstable future references. Regular and hidden divergence types are evaluated independently on both highs and lows. 2. Ribbon Context Filter The T3 ribbon acts as a directional and location filter. Divergence can optionally require price to be extended beyond the ribbon in the direction of the stretch before the event is accepted. 3. Response Zones And Corridors When a divergence confirms, the script can project a response zone, midpoint line, reaction corridor, and target line forward from the pivot area. This turns divergence from a simple signal marker into a structured response map. 4. Signal Quality Context The script uses RSI delta, ATR-normalized price displacement, cooldown logic, and optional overbought or oversold context to grade whether a divergence is meaningful enough to display. Features Regular bullish and bearish divergence: Reversal-oriented pivot disagreement Hidden bullish and bearish divergence: Continuation-oriented pivot disagreement T3 ribbon filter: Smoothed directional context layer Reaction envelopes: Premium and discount response bands around ribbon center Response zones: Forward areas projected from the active divergence Reaction corridors: Larger projected path zones for follow-through context Target lines: Simple objective guides derived from ATR structure Signal labels: On-chart labels with response type and quality readout Pivot dots and reset markers: Optional event markers for visibility Dashboard: Displays RSI, zone state, ribbon state, cooldown, and active signal Confirmed pivots only: Divergence prints only after pivot confirmation Input Parameters RSI Core And Divergence: RSI source and length Overbought and oversold levels Pivot length and divergence window Regular and hidden divergence toggles Quality And Display: Signal cooldown Minimum RSI delta Minimum ATR move Extreme-condition requirement Ribbon-filter requirement Ribbon, pivot dots, dashboard, response zone, signal label, and reaction corridor toggles How to Use This Indicator Step 1: Identify whether the latest signal is regular or hidden, because they imply different response behavior. Step 2: Check whether the signal formed in overbought or oversold context and whether the ribbon was supportive. Step 3: Use the response zone and corridor as a framework for how price may react rather than as a guaranteed destination. Step 4: Use reset markers to track whether momentum is rebalancing after the divergence. Step 5: Prefer divergence that forms after visible extension, not in flat neutral conditions. Indicator Limitations Pivot confirmation introduces intentional delay because divergence is only known after the pivot is confirmed Divergence can persist or fail completely during strong trends Hidden divergence is continuation-oriented and should not be interpreted the same way as regular divergence Projected zones and targets are analytical guides, not forecasts Originality Statement Vesper Divergence Cascade is original in how it combines pivot-stored RSI divergence, a T3 ribbon context filter, response envelopes, projected zones, and reaction corridors inside one divergence workflow. The script is designed to explain what kind of divergence formed, where it formed, and how price may structurally respond afterward. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Divergence is a contextual tool and can fail repeatedly during persistent trends, so all use should include independent analysis and risk management. -Made with passion by jackofalltrades
Pine Script®指標
由officialjackofalltrades提供
Obsidian Regime Ribbon [JOAT]Obsidian Regime Ribbon Introduction Obsidian Regime Ribbon is an open-source trend-state and execution-context overlay built to classify directional conditions before a trader applies any separate entry model. Instead of using a single moving average or one oscillator threshold, it combines an adaptive range filter, efficiency ratio, ADX strength, choppiness, momentum confirmation, higher-timeframe bias, and EMA alignment into one chart layer. The problem this script solves is regime confusion. Traders often apply trend-continuation logic in compression or try fading price while directional participation is still strong. Obsidian Regime Ribbon provides a structured state model with a filtered regime line, layered expansion bands, reclaim signals, stretch tags, execution rails, and a compact dashboard so the user can read whether price is trending cleanly, overextending, or losing sponsorship. Core Concepts 1. Adaptive Range Filter The central filter line is not a static moving average. It uses ATR distance and an efficiency-ratio-driven multiplier so the filter widens during noisy conditions and tightens when price movement becomes more directional. 2. Multi-Factor Regime Gate ADX checks directional strength, choppiness checks compression, momentum confirms directional pressure, higher-timeframe EMA bias provides external context, and EMA spread measures local alignment. These conditions feed a scorecard so the user can separate weak drift from stronger directional structure. 3. Expansion And Reclaim Framework Four ATR-derived bands are projected above and below the regime filter. Confirmed regime shifts create labeled accumulation or distribution windows. Pullback reclaim signals print only after price revisits the regime line and closes back through it on a confirmed bar. 4. Execution Rails Confirmed shifts and reclaim events create forward execution rails and zones directly on the chart. In bullish conditions they behave as demand rails, and in bearish conditions they behave as supply rails. Features Adaptive regime filter: ATR-based directional filter with efficiency-ratio adaptation Layered regime bands: Four expansion bands above and below the filter EMA structure cloud: Fast and slow structure means with directional fill Confirmed regime shift labels: Bullish and bearish shifts print only after confirmation Reclaim signals: Diamond markers when price reclaims the regime line Execution rails: Demand and supply rails with right-edge price labels Stretch tags: Labels when price reaches extreme premium or discount relative to the filter Expansion markers: Additional markers when price pushes through secondary band thresholds State-based candle coloring: Candle tint changes with regime and score strength Dashboard: State, conviction, age, ER, ADX, chop, stretch, HTF alignment, and shift counts Confirmed-bar logic: Regime changes and reclaim signals are designed for confirmed bars only Input Parameters Engine: Range Length and Range Multiplier control the core filter sensitivity Efficiency Length controls how quickly adaptation reacts to directional efficiency Base Confirm Bars controls how many bars are required before a regime shift is locked Stretch Threshold defines when a move is considered overextended in ATR terms Filters And Display: ADX, choppiness, momentum, and higher-timeframe controls define the regime gate Regime band, filter line, candle color, dashboard, execution zone, and stretch tag toggles How to Use This Indicator Step 1: Read the current regime from the dashboard and candle state first. Step 2: Use the conviction score to decide whether the trend is fully structured or transitional. Step 3: Watch regime shift labels to identify when directional control changes. Step 4: Use reclaim diamonds and execution rails as retracement reference instead of chasing outer-band extensions. Step 5: Treat stretch tags as caution zones where reward-to-risk may deteriorate. Indicator Limitations Adaptive filters can still lag the first bar of a sharp reversal because confirmation is intentionally delayed Higher-timeframe alignment can temporarily disagree with local price rotation during early reversals Stretch conditions do not guarantee reversal; they only identify extended distance from the filter This script is a context overlay, not a complete trading system by itself Originality Statement Obsidian Regime Ribbon is original in the way it combines an adaptive range-state engine, multi-factor regime gate, expansion-band framework, reclaim signals, and forward execution rails into one integrated context overlay. The purpose is not to merge unrelated tools, but to build a single decision layer that explains trend state, extension, and pullback quality together. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Regime, reclaim, and stretch conditions are derived from historical price behavior and do not guarantee future outcomes. Always use independent analysis and risk management. -Made with passion by jackofalltrades
Pine Script®指標
由officialjackofalltrades提供
Adaptive Flow II | AnonycryptousAdaptive Flow II | Anonycryptous Description & user manual Why this indicator is different Most trend-following indicators use a fixed moving average. A 50-period EMA moves at the same speed whether the market is trending hard or grinding sideways. It cannot distinguish between a clean directional move and noise. It gives the same weight to a volatile consolidation as it does to a strong impulse. The result is signals that arrive late in trends and fire repeatedly during chop. Adaptive Flow v2 works differently. At its core is a Kaufman Adaptive Moving Average — a moving average that measures the efficiency of price movement on every single bar and adjusts its own speed accordingly. When price is moving cleanly in one direction with low noise, the flow line accelerates toward price. When price is churning sideways with high volatility and no direction, the flow line nearly stops moving. It adapts. Automatically. Without requiring any manual intervention. V2 builds significantly on this foundation. It adds five configurable stop modes, full market structure detection through BOS and CHoCH events, three independent signal filters, dynamic extension bands, a session-anchored VWAP, and an expanded dashboard. The result is a complete adaptive trend and structure system — not just a trend indicator, but a context-aware trading framework. Important notice Adaptive Flow v2 generates signals based on technical indicator 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 Adaptive Flow v2 is an adaptive trend-following indicator built around a Kaufman Adaptive Moving Average with a configurable stop engine and full market structure detection. What it includes: - Kaufman Adaptive Moving Average rendered as a neon glow line with four stacked plot layers - Five stop modes: ATR Trailing, Supertrend, Chandelier, Donchian, and Volatility Pivot - Cloud fill between the flow line and the stop line, reflecting the current trend state - Dynamic extension bands above and below the flow line at configurable ATR distance - BOS and CHoCH structure detection with BOS confirmation filter - Pivot high and low target lines that change color when broken - EMA 200 macro trend filter with higher timeframe support - ADX filter for directional environment confirmation - Session filter to restrict signals to a configurable trading window - Signal cooldown to prevent repeated triggering - Session-anchored VWAP with daily and custom session modes - Bar coloring reflecting the current trend state - Three presets: default, fast, and smooth - Live dashboard with 13 data rows - Seven alert conditions 2. The flow line — Kaufman Adaptive Moving Average The flow line is the visual heart of Adaptive Flow. On every bar it calculates an Efficiency Ratio — a measure of how directionally efficient price movement is relative to total volatility over the lookback period. When the Efficiency Ratio is high — price is moving strongly in one direction with low noise — the flow line accelerates toward price. When the Efficiency Ratio is low — price is ranging with high volatility — the flow line nearly stops moving. This adaptive behavior means the flow line naturally stays close to price during strong trends and pulls away only during genuine transitions. It is not a lagging average that mechanically follows price at a fixed delay. It responds to market character. The flow line is rendered with four stacked plot layers — a sharp core at full opacity and three progressively wider, more transparent layers behind it — creating a neon glow effect that makes it visually distinct on any chart. The noise filter adds an additional gate: KAMA only advances when the price displacement exceeds ATR × threshold. This prevents the flow line from reacting to insignificant micro-movements during low-momentum conditions. Disable it for maximum responsiveness in strong trending environments. 3. Stop engine — five modes The stop engine calculates a dynamic stop level from the flow line. All five modes use the flow line as their reference point, not raw price. This means the stop inherits KAMA's adaptive smoothing before calculating any distance. When the flow line crosses the stop level, the trend flips and a signal fires. 3.1 ATR Trailing (default) The stop trails the flow line at a fixed ATR distance using a ratchet mechanism — it only moves in the direction of the trend and locks in the floor or ceiling. This produces the characteristic smooth, flowing wave that follows the flow line closely. The cloud between the flow line and the stop gives a live view of the trend zone width. Default and recommended for most users. 3.2 Supertrend ATR band above or below the flow line with ratchet mechanism. Similar to ATR Trailing but calculated differently, producing a more angular step-like stop line. More angular appearance, fewer intermediate flips. 3.3 Chandelier The stop trails the highest or lowest flow line value over a configurable lookback window, then subtracts or adds ATR × multiplier. Exits when the flow line has sustained a reversal beyond the lookback range. Better for trending markets where you want to trail a historical extreme rather than the current level. 3.4 Donchian The stop follows the highest or lowest flow line value over a rolling window with no ATR component. Purely range-based. The stop level is exactly the rolling high or low of the flow line — clean, simple, no volatility scaling. 3.5 Volatility Pivot The stop anchors to the last confirmed pivot high or low of the flow line plus an ATR buffer. Structurally aware — the stop sits at a level where the flow line previously reversed, not at an arbitrary distance. Best for traders who want the stop to respect structure rather than trail at a fixed distance. 4. Extension bands When enabled, two bands are drawn above and below the flow line at ATR × multiplier distance. They are not stop levels — they are extension context. When price reaches the upper band during a bullish trend, it may indicate an overextended condition. When price compresses back toward the flow line after touching a band, it may indicate a pullback area. The bands move with the flow line and adapt to current volatility. 5. Market structure — BOS and CHoCH Adaptive Flow v2 includes a full market structure detection engine that runs alongside the adaptive trend engine. Pivot highs and lows are detected on price using configurable left and right bar lookbacks. When price closes beyond a confirmed swing level, the indicator classifies the event as either a Break of Structure or a Change of Character. A BOS fires when price closes beyond a swing level in the direction of the existing structural trend — confirming continuation. Drawn as a dashed line A CHoCH fires when price closes beyond a swing level against the existing structural trend — signaling a potential reversal. Drawn as a solid line. The BOS confirmation requirement prevents false reversals. When set to 1 (default), at least one BOS must confirm the current structural trend before a CHoCH can flip it. This blocks the common false reversal where a sharp pullback briefly closes beyond a swing level before the trend reasserts. Pivot target lines are drawn automatically at the last confirmed pivot high and low. They extend to the right and change color when price closes through them. 6. Signal filters Three optional filters are available. All three can be combined. A signal only fires when all active filters agree. EMA 200 — always active as a macro filter. Bullish signals only fire above the EMA 200. Bearish signals only below. Set the EMA 200 timeframe to a higher timeframe (1H or 4H) when trading on lower timeframes — the native EMA 200 on a 1-minute chart only covers a few hours and provides no meaningful macro context. ADX filter — when enabled, signals only fire when ADX is at or above the configured threshold. Below this level the market is typically ranging and directional signals carry less weight. Default threshold of 20 removes the weakest trend environments. Session filter — when enabled, signals only fire during the configured trading window. Defined in HHMM-HHMM format using exchange timezone. Outside the window the flow line continues calculating but no new signals are generated. Signal cooldown — minimum bars between two signals in the same direction. Prevents repeated triggering during choppy conditions around the stop level. 7. VWAP The VWAP provides a volume-weighted price reference that resets at the start of each session. It represents the average price paid weighted by volume — a key reference for intraday value and institutional order flow. Daily mode resets every calendar day. Custom mode anchors to a specific session defined by start and end times in HHMM-HHMM format. Timezone selection ensures correct boundary alignment. 8. Presets Three preset configurations are available. Selecting a preset overrides the core KAMA calculation parameters. Default — balanced for swing trading on 4H and daily charts. Adaptive length 14 | Fast constant 2 | Slow constant 30 | Noise threshold 0.3. Fast — built for scalping on 1 to 15 minute charts. Adaptive length 6 | Fast constant 2 | Slow constant 15 | Noise threshold 0.15. Shorter lookback for faster momentum shift detection. Lower noise threshold preserves full adaptive speed. Smooth — designed for position trading on daily and weekly charts. Adaptive length 21 | Fast constant 3 | Slow constant 40 | Noise threshold 0.5. Extended lookback demands sustained momentum before accelerating. Aggressive noise filtering for high-conviction reads only. 9. Dashboard The dashboard displays the live state of all indicator components and updates on every bar. Rows displayed: - Adaptive Flow — indicator name with trend-colored header and current timeframe - Trend — current flow line direction: bullish or bearish - Stop Mode — active stop mode in use - Structure — current structural direction from BOS/CHoCH logic - EMA 200 — whether price is above or below the macro filter - VWAP — whether price is above or below session value - ADX — current ADX value with confirmation indicator - Session — whether the session filter is active and the current bar is inside the window - Noise Filter — whether the noise gate is active - Stop Distance — distance from current close to stop level in ATR multiples and as a percentage - Trend Bars — number of bars the current trend has been active - BOS Count — number of confirmed BOS events in the current structural direction - Signal — last signal fired: buy, sell, CHoCH, BOS, or none 10. Settings reference KAMA & Calculation - Price Source: input for the flow line calculation - Adaptive Length: efficiency ratio lookback period - Fast Constant: smoothing speed during trending conditions - Slow Constant: smoothing speed during ranging conditions - Enable Noise Filter: toggle the displacement gate - Noise Threshold: minimum ATR multiple required to advance the flow line - Preset: Default, Fast, or Smooth Stop Engine - Stop Mode: ATR Trailing, Supertrend, Chandelier, Donchian, or Volatility Pivot - ATR Length: volatility measurement period - ATR Multiplier: distance scaling for the stop level - Stop Lookback: rolling window for Chandelier and Donchian modes - Pivot Buffer: ATR buffer for Volatility Pivot mode Market Structure - Show BOS / CHoCH: toggle structure detection - Pivot Left / Right Bars: swing confirmation lookback - Max Structure Levels: maximum lines shown on chart - BOS Required Before CHoCH Flip: false reversal filter - Show Pivot Target Lines: toggle automatic target lines - Target Line Color and Width Signal Filters - EMA 200 Timeframe: leave empty for chart timeframe - Show EMA 200: toggle line and label visibility - EMA 200 Color - Enable ADX Filter: toggle directional environment gate - ADX Length and Threshold - Enable Session Filter: toggle session-based signal restriction - Session Window: HHMM-HHMM format - Signal Cooldown: bars between signals VWAP - Session: Daily or Custom - Timezone: UTC, Exchange, or major financial center timezone - Session Window: for Custom mode - Show VWAP: toggle line and label - VWAP Color Visuals - Bull Color and Bear Color - Cloud Transparency: fill between flow line and stop - Show Extension Bands: toggle ATR extension bands - Extension Band Multiplier: distance from flow line - Show Reversal Signals: toggle triangle markers - Color Candles: toggle bar coloring - Candle Transparency Dashboard - Show Dashboard - Size: Tiny, Small, or Normal - Position: Top Left, Top Right, Bottom Left, or Bottom Right 11. How to use 11.1 Initial setup Select a preset matching your primary trading style. Set the EMA 200 timeframe to a higher timeframe when trading on lower timeframes — 60 for 1H, 240 for 4H. Set the VWAP to Daily or configure a custom session matching your primary market. Choose a stop mode — ATR Trailing is the default and works well across all timeframes. Enable the session filter and ADX filter if you want stricter signal conditions. 11.2 Reading the chart The flow line and its glow indicate the current adaptive trend. Green indicates a bullish environment. Red indicates a bearish environment. The cloud between the flow line and the stop shows the trend zone width — a wide cloud indicates strong momentum, a narrowing cloud indicates the flow line is slowing. The stop line is where the trend flips. A reversal signal fires when the flow line crosses it. Triangle markers appear at the stop line at the signal bar. Extension bands show how far price has moved from adaptive value. Price at the upper band in a bullish trend may indicate overextension. Price returning toward the flow line after touching a band may offer a pullback reference. BOS and CHoCH lines show structural context. Use them to understand whether the trend is in a confirmation phase (BOS firing repeatedly) or approaching a potential reversal (flow line slowing while price approaches a structural level). 11.3 Timeframe guide 1 to 5 minutes — Fast preset. EMA 200 timeframe set to 60 or 240. Session filter recommended. 15 to 30 minutes — Fast or Default preset. EMA 200 timeframe 240 or D. 1 hour to 4 hours — Default preset. Native EMA 200 or D timeframe. Daily and above — Smooth preset. Native EMA 200. 11.4 Stop mode selection guide ATR Trailing — best for most situations. Smooth, flowing, closely follows the flow line. Supertrend — fewer flips, more angular. Good for lower timeframe noise reduction. Chandelier — suited for trending markets where you want to trail a recent high or low. Donchian — clean range-based stop with no ATR influence. Simple and transparent. Volatility Pivot — best when you want the stop at a structurally meaningful KAMA level. 11.5 Context Adaptive Flow v2 identifies adaptive trend direction and market structure. It does not filter by fundamental events, news, or macro calendar. A bullish signal during a risk-off macro event may fail more often than one in a clear trending environment. Always apply your own context and judgment alongside the indicator output. 12. Alerts Seven alert conditions are available: - Bull Trend: flow line crosses above the stop level, EMA 200 above, all active filters passed. - Bear Trend: flow line crosses below the stop level, EMA 200 below, all active filters passed. - Any Trend Change: fires on either bull or bear trend signal. - Bull CHoCH: market structure flips to bullish via Change of Character. - Bear CHoCH: market structure flips to bearish via Change of Character. - Bull BOS: bullish Break of Structure confirms trend continuation. - Bear BOS: bearish Break of Structure confirms trend continuation. All alerts include exchange, ticker, and interval in the message. 13. 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®指標
由Anonycryptous提供
2
Meridian Liquidity Ledger [JOAT]Meridian Liquidity Ledger Introduction Meridian Liquidity Ledger is an open-source Pine Script v6 indicator that maps directional liquidity shelves across a rolling price window. It separates buy-side and sell-side volume concentration, ranks shelves by relative participation strength, extends the most relevant levels through the chart, and summarizes the current liquidity ledger in an institutional-style dashboard. The problem this indicator solves is density. A standard volume profile can show where volume accumulated, but it often does not express directional participation clearly enough for traders who want to know whether the market built more inventory above or below a reference anchor. Meridian Liquidity Ledger addresses that by classifying shelves relative to an adaptive reference price and showing whether each shelf behaves more like a buy shelf or a sell shelf. The script is intended for traders who think in terms of inventory, acceptance, and liquidity stacking. It does not try to replace execution logic. It provides a map of where volume concentrated across the rolling ledger window, where the point of control sits, how dominant the buy-side and sell-side shares are, and how far price has stretched from the anchor and point of control in ATR terms. Because the heavy rendering happens only on the last visible bar, the indicator aims to deliver rich visual output without turning into an unreadable chart wall. Historical shelf zones, profile bars, dotted spines, the point of control extension, and the dashboard all work together to make the liquidity map readable rather than overwhelming. Core Concepts 1. Adaptive Reference Price At the center of the ledger is a reference engine built from an EMA and a deviation adjustment. The script can use a plain EMA reference or a slight adaptive band depending on the user setting. float emaRef = ta.ema(close, referenceLength) float rangeDev = ta.stdev(close, deviationLength) * referenceBias float synthetic = close >= emaRef ? emaRef - rangeDev * 0.20 : emaRef + rangeDev * 0.20 This reference acts as the ledger divider. Shelves above the reference are treated as sell-side inventory zones. Shelves below the reference are treated as buy-side inventory zones. 2. Rolling Price-Volume Binning The script scans a configurable lookback window, divides the full price range into bins, and accumulates total, buy-side, and sell-side volume in each bin. This creates the ledger foundation. Instead of looking only at price touches, the indicator asks where actual traded volume concentrated across the window. That gives each shelf more meaning than a simple horizontal line. 3. Shelf Strength Ranking Each bin’s relative strength is measured as a percentage of the maximum bin volume in the window. Only shelves above the minimum strength threshold are rendered. That keeps weak background noise from cluttering the chart. This is important because the point of the ledger is not to show every possible micro shelf. It is to show the shelves that stood out meaningfully within the chosen lookback. 4. Shelf History And Spine Extension For each active shelf, the script estimates how far left the midpoint price was last crossed, then draws a historical zone, a profile bar on the right, and an optional dotted spine through the shelf midpoint. This creates both historical and forward reference in a single visual package. The effect is similar to having a compressed split-profile, a shelf map, and a point-of-interest extension all in one indicator. 5. Point Of Control And Ledger Balance The point of control is the strongest single shelf in the active ledger. The script can extend that level to the right and label it. At the same time, the dashboard tracks buy share, sell share, total imbalance, top-shelf concentration, and ATR distance to both the reference and the point of control. This makes the ledger useful not just visually but quantitatively. Features Directional liquidity shelves: Separates bins into buy-side and sell-side inventory relative to the reference anchor Adaptive reference engine: Uses EMA and deviation bias to frame the ledger around a contextual central price Rolling volume ledger: Accumulates total, buy, and sell participation across a user-defined window Shelf strength filter: Displays only bins strong enough to matter Historical shelf zones: Shows where active shelves projected through the recent chart history Profile bars on the right edge: Renders compact shelf bars for immediate strength comparison Shelf spines: Optional dotted lines extend each shelf midpoint through the chart Point-of-control extension: Marks and extends the strongest shelf in the current ledger Institutional dashboard: Displays buy share, sell share, imbalance, POC, concentration, shelf count, and ATR distance metrics Confirmed-bar alerts: Includes buy dominance, sell dominance, and anchor stretch conditions Visual Elements Historical shelf zones: These show where strong bins projected back through the active ledger window Right-edge profile bars: Compact bars make it easy to compare shelf strength without reading every label Shelf spines: Optional dotted midpoint lines extend the key shelf levels through the chart Anchor bands: Inner and outer reference bands help frame whether price is balanced or stretched POC label and extension: The strongest shelf remains visible as the primary ledger reference Best Practices Use the ledger to frame where inventory is concentrated before applying your own execution logic Watch the relationship between price, the anchor, and the point of control to judge balance versus stretch Favor shelves that remain visually dominant even as the rolling window updates Remember that shelf color and position are contextual to the current anchor, not absolute predictions of support or resistance Use the buy-share and sell-share readings to understand ledger skew before reacting to a single shelf in isolation Input Parameters Ledger Window: Lookback Bars: Sets the rolling history used to build the ledger Bin Count: Controls the price segmentation granularity Profile Width: Controls the maximum width of the profile bars on the right Shelf Padding: Adjusts the spacing between price and the right-edge profile Reference Engine: Reference EMA Length: Sets the central EMA anchor Deviation Length: Controls the standard-deviation calculation for adaptive biasing Reference Bias: Scales the adaptive offset around the EMA Use Adaptive Anchor Band: Chooses between the synthetic anchor and plain EMA reference Shelf Filters And Display: Minimum Shelf Strength %: Removes shelves below the selected threshold Show Historical Shelf Zones: Toggles the historical box layer Extend Point Of Control: Projects the strongest shelf forward Show Shelf Spines: Enables midpoint extension lines Show Dashboard: Enables the top-right ledger panel How to Use This Indicator Step 1: Start With Buy Share, Sell Share, And Imbalance The dashboard tells you how the rolling ledger is currently distributed. If buy share dominates, the ledger is skewed below or through the anchor in a way that favors buy-side participation. If sell share dominates, the opposite is true. Step 2: Locate The Point Of Control Find the extended POC line. This is the strongest shelf in the current window. It often acts as the most important reference price when judging whether the market is balanced, stretched, or returning to its highest concentration zone. Step 3: Compare Price To The Reference Anchor The reference and its surrounding bands tell you whether price is trading above, below, or far away from the ledger center. This is useful for deciding whether the market is exploring beyond inventory or still trading within its main concentration zone. Step 4: Focus On The Strongest Shelves The most useful shelves are usually the ones with the greatest width, clearest labels, and strongest color intensity. Those are the bins where the rolling window concentrated the most inventory. Step 5: Use The Ledger As A Context Map Meridian Liquidity Ledger is best used as a map of where liquidity stacked and how it is distributed. Pair it with your own entry logic rather than treating any single shelf as an automatic trade signal. Indicator Limitations The ledger is rolling-window dependent, so shelf hierarchy can change as older bars leave the calculation window A strong shelf does not guarantee support or resistance will hold on the next interaction Directional buy and sell classification is based on bar-level bullish versus bearish volume attribution, which is an approximation rather than true order-flow data On illiquid symbols or very small windows, shelf concentration can become unstable and less informative Originality Statement Meridian Liquidity Ledger is original in the way it turns a rolling bin-based volume map into a directional liquidity shelf system with adaptive anchoring. It is not a generic profile overlay: It separates buy-side and sell-side participation relative to an adaptive reference rather than showing only total profile mass It combines historical shelf zones, right-edge shelf bars, shelf spines, and POC extension in one integrated view It frames liquidity through dashboard metrics such as imbalance, concentration, and ATR stretch rather than pure histogram display It creates a practical shelf map for context instead of relying on a single profile style or one static reference Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Liquidity shelves and point-of-control levels are descriptive references built from rolling historical data. They do not guarantee future support, resistance, or directional continuation. Always use independent judgment and proper risk management. -Made with passion by jackofalltrades
Pine Script®指標
由officialjackofalltrades提供
2
Harborside Regime Channel [JOAT]Harborside Regime Channel Introduction Harborside Regime Channel is an open-source regime-mapping indicator built to classify whether the market is expanding, compressing, reclaiming balance, or losing structural support inside a live adaptive channel. The script is designed for traders who need context before they interpret any other signal. Instead of asking only whether price is above or below a moving average, Harborside studies a pivot-fed centerline, adaptive outer rails, higher-timeframe directional agreement, and volatility compression state at the same time. The result is a channel that behaves more like an institutional market map than a simple trend overlay. The problem Harborside solves is regime clarity. Many trend tools keep printing directional color even while the market is actually compressing inside a narrowing structure. Many channel tools show a band but do not explain whether that band is healthy, fragile, extended, or aligned with higher-timeframe pressure. Harborside addresses that by combining channel structure, expansion behavior, and higher-timeframe bias in one chart-first framework. Core Concepts 1. Pivot-Fed Structural Center Harborside does not anchor its regime center to a fixed moving average alone. Instead, confirmed swing highs and swing lows are used to build a rolling center reference. That center is then smoothed to create a structural balance line. This matters because the center is linked to confirmed market geometry rather than only to lagging price averages. The channel therefore breathes with the underlying structure of the market. 2. Adaptive Outer Rails The upper and lower rails are derived from ATR-scaled expansion around the structural center. This means the channel naturally widens when volatility expands and contracts when price compresses. Because the rails are smoothed, they remain readable instead of flickering excessively during intrabar noise. This creates a cleaner map for determining whether price is stretching, reverting, or breaking into a new directional phase. 3. Regime Flips on Confirmed Structural Breaks A bullish regime is not assigned merely because price is green for a few bars. A regime flip occurs when price confirms through the adaptive outer band in the relevant direction. That regime is then maintained until the opposing side is confirmed. This makes the indicator more stable than reactive color-on-close style tools. 4. Compression Detection Harborside measures band width relative to its own historical baseline. When the band compresses below the configured threshold, the script identifies a meaningful reduction in expansion state. This compression state is important because trend-following logic behaves very differently when the market is coiled than when it is already moving freely. Compression is shown directly on the chart and carried into the dashboard state. 5. Projection Rails The script extends projected center, upper, and lower rails forward using current center slope and ATR-scaled projection logic. These projected rails are not predictions in the magical sense. They are forward references showing where the current regime geometry would continue if the active slope persists. That gives the trader a usable visual frame for stretch, continuation, and mean-reversion decisions. 6. Higher-Timeframe Bias Alignment Higher-timeframe bias is requested using offset logic intended to avoid repaint-style behavior from incomplete higher-timeframe bars. Fast and slow higher-timeframe EMA structure is used to determine whether broad directional pressure is supportive, opposing, or neutral. Harborside does not force the higher-timeframe filter on the user. It can be enabled or disabled depending on workflow. 7. Regime Health and Confidence Harborside includes a confidence-style scoring model built from displacement, slope, compression state, and directional bias alignment. This score is not intended to be a trade system on its own. It is a context gauge. A high score means the active regime has cleaner structural support. A low score means the visible state is weaker or more fragile. Features Pivot-fed centerline: The regime center is anchored to confirmed swing structure rather than a static average alone Adaptive outer rails: ATR-scaled bands expand and contract with changing volatility conditions Confirmed regime flips: Bull and bear states change only after confirmed structural breaks through the active channel rails Compression box: Important volatility contraction zones are shown directly on the chart instead of being hidden in a separate pane Projection rails: Forward rails extend the current channel geometry into future bars for context and stretch awareness Higher-timeframe bias filter: Optional HTF directional alignment helps separate local moves from larger directional pressure Regime-colored candles: Candle coloring reflects the active state without relying on cluttered symbols or arrows Band cloud rendering: The active channel body is filled to make directional structure readable at a glance Health and confidence diagnostics: The dashboard summarizes regime quality in compact form Six-row dashboard: The display was intentionally reduced so the chart remains the primary source of information Confirmed-bar alerts: Alerts are available for regime flips, compression holds, center reclaims, HTF alignment, and high-health states Input Parameters Channel Structure: Swing Length: Number of bars required on both sides to confirm pivots used by the structural center Band Multiplier: ATR multiplier used to define the channel width Center Smoothing: Smoothing applied to the structural midpoint Band Smoothing: Smoothing applied to the upper and lower rails Bias and Context: Bias Timeframe: Higher timeframe used for optional directional confirmation Compression Lookback: Baseline window used to measure channel contraction Compression Threshold: Band-width threshold below which the market is treated as compressed Volume Bias Filter: Volume impulse threshold used to label directional support Projection: Projection Bars: Number of bars projected forward Projection ATR Multiplier: Width factor used for forward rails Projection Slope Multiplier: How strongly current center slope influences the forward center projection Display: Show Band Cloud toggle Show Compression Box toggle Show Projection Rails toggle Recolor Candles toggle Show Dashboard toggle How to Use This Indicator Step 1: Read the State from the Chart First Start with the channel itself. Is price controlling the upper side of the structure, the lower side, or compressing near the center? The rails and cloud are meant to answer that visually before the dashboard is consulted. Step 2: Check Compression Before Chasing Direction If the compression box is active, treat the market as coiled rather than trending cleanly. That does not mean price cannot move. It means breakout quality matters more than ordinary directional drift. Step 3: Use Projection Rails as Forward Reference Projection rails are best used for context. If price is already far outside projected geometry, the market may be stretched. If price is traveling inside projected structure, continuation is behaving more normally. Step 4: Compare Local Regime to HTF Bias If the local regime and higher timeframe agree, directional conditions are cleaner. If they disagree, treat the move with more caution. That disagreement often marks either a pullback or a weak local thrust against broader pressure. Step 5: Use Health and Confidence as Filters, Not Commands High confidence does not guarantee follow-through. Low confidence does not guarantee failure. The score is there to grade structural quality, not to replace decision-making. Indicator Limitations Pivot-based structure is intentionally confirmed after the swing forms, so the centerline will never anticipate future pivots Projection rails are structural references, not forecasts of what price must do next HTF alignment is delayed by design because the script uses completed higher-timeframe values for safer non-repainting behavior Compression can persist longer than expected, so directional patience is still required Harborside is a context framework and should not be treated as a guaranteed entry system on its own Originality Statement Harborside Regime Channel is original in the way it combines a pivot-fed structural center, ATR-adaptive regime rails, explicit compression logic, forward projection rails, and optional higher-timeframe agreement into one coherent chart-first overlay. The value of the script is not any one component in isolation. It is the way those components interact to show whether the market is healthy, stretched, compressing, or structurally aligned. Disclaimer This indicator is provided for educational and informational purposes only. It does not provide financial advice, investment advice, or trading recommendations. Any regime reading can fail, reverse, or degrade suddenly due to news, liquidity changes, or ordinary market uncertainty. Always use independent confirmation and risk management.
Pine Script®指標
由officialjackofalltrades提供
Velorum Deviation Corridor [JOAT]Velorum Deviation Corridor Introduction Velorum Deviation Corridor is an open-source adaptive price envelope designed to measure directional bias, stretch, and compression around a dynamic baseline. The script does not treat all volatility the same. It allows different baseline engines and different width engines, then converts that information into an overlay corridor that can show trend continuation, overextension, and volatility contraction in one place. The problem this script solves is that static envelopes often fail when market speed changes. A fixed moving average with a fixed-width band may lag badly during acceleration and overreact during compression. Velorum addresses that by pairing adaptive baseline logic with multiple volatility models, then confirming state shifts only after bars close. The result is a directional overlay that can function as a trend frame, pullback map, and stretch monitor. Core Concepts 1. Adaptive Baseline Selection The script allows the user to choose among several baseline models: EMA, Hull, Adaptive KAMA, VIDYA, FRAMA, and Gaussian smoothing. This makes the corridor usable across different styles. Faster baselines react more quickly to rotation. More adaptive baselines try to react quickly in clean trends and slow down in noisy environments. 2. Multi-Model Width Estimation The width engine can use ATR, standard deviation, Parkinson volatility, efficiency range, or a hybrid model. This matters because volatility can be defined in different ways. ATR captures absolute travel, standard deviation captures dispersion, Parkinson emphasizes high-low structure, and the hybrid approach blends multiple aspects into one corridor width. widthModel = input.string("Hybrid Volatility", "Width Model", options = ) 3. Compression and Expansion Detection The script tracks corridor width over a rolling lookback and compares it against a compression percentile. When width contracts into the lower part of its recent range, the script identifies a compression state. When width expands with directional slope and position agreement, the script identifies expansion. This helps distinguish quiet consolidation from meaningful travel. 4. Trend State and Stretch Logic Trend state is determined by baseline slope, price position relative to the corridor, and confirmation bars. The script also measures stretch so users can see whether price is trading inside the value area of the corridor, near the edge, or outside it. That makes it useful for both continuation logic and reversion-aware caution. 5. Transition Ribbon, Reaction Shelves, and Drift Lanes The overlay uses outer bands, inner bands, corridor fills, glow layers, and a narrow transition ribbon around the baseline. It also projects on-chart structure when important corridor events occur. Confirmed constructive and defensive shifts can create forward shelf boxes. Confirmed excursions outside the corridor can create upper and lower drift lanes. Compression and expansion transitions can also stamp temporary forward boxes directly on the chart, turning the corridor into a working structure map instead of only a band set. Features Six baseline models: EMA, Hull, Adaptive KAMA, VIDYA, FRAMA, and Gaussian Five width engines: ATR, standard deviation, Parkinson, efficiency range, and hybrid volatility Compression detection: Width percentile model highlights contraction phases Trend confirmation bars: Direction changes require confirmation before they are treated as valid Stretch context: Shows whether price is centered, extended, or outside the corridor Layered overlay: Baseline, glow, inner bands, outer bands, fills, and transition ribbon Reaction shelves: Confirmed constructive and defensive shifts can project forward box zones on the chart Drift lanes: Confirmed closes outside the corridor can stamp directional lane boxes Compression shelf and expansion release: Corridor state transitions can create temporary forward structure boxes On-chart labels: Shelf, lane, and release labels appear directly on the price chart Compact dashboard summary: Trend state, regime, stretch, strength, and confirmed shift in a smaller top-right panel Confirmed-bar alerts: Lift, fade, compression, and expansion events Input Parameters Core Engine: Source Baseline Model Baseline Length Fast and Slow Components for adaptive models Trend State: Trend Confirmation Bars Slope Lookback Trend Strength Length Compression Lookback Compression Percentile Width Model: Width Model Width Length Width Multiplier Elasticity Factor How to Use This Indicator Step 1: Identify the Baseline Bias Start with price relative to the baseline and the dashboard's Trend State row. If price is holding above a rising baseline, the corridor is acting as bullish structure. If price is holding below a falling baseline, the corridor is acting as bearish structure. Step 2: Check Compression Before Breakouts Compression phases are useful because directional expansions often begin after width contracts. If the chart is tinted for compression and width percentile is low, watch for a confirmed shift rather than treating every small move as a new trend. Step 3: Use Inner vs Outer Bands Differently The inner bands are the working area for pullbacks and value. The outer bands represent more extended travel. When price repeatedly walks an outer band, that is continuation behavior. When price snaps outside and immediately loses follow-through, that is often stretch rather than sustainable expansion. Step 4: Use Reaction Shelves and Drift Lanes as Forward Reference When a confirmed constructive or defensive shift occurs, Velorum can project a forward shelf box. When price closes beyond the outer corridor, it can print a drift lane. These structures are intended to mark the part of the chart where continuation behavior should stay organized. If price immediately loses those zones, the move is weakening. Step 5: Treat Confirmed Shift as the State Change The confirmed shift output is still the important regime event. Intrabar movement can test both sides of the corridor, but the script only promotes a new state after bar confirmation and only stamps new corridor structures after confirmation. Indicator Limitations No single baseline model is best for every market; users may need to select a model appropriate for their instrument and timeframe Compression does not guarantee breakout direction, only reduced width A fast corridor can overreact in noisy markets while a slow corridor can lag during sharp reversals Stretch beyond the outer band can persist longer than expected in strong trends Reaction shelves and drift lanes are contextual structure tools, not guaranteed support or resistance Originality Statement Velorum Deviation Corridor is original in the way it separates the baseline problem from the width problem and lets those two adaptive layers interact in one confirmed-state overlay. The script is not simply a renamed moving average envelope. It combines multiple smoothing families, multiple volatility families, width percentile compression logic, stretch-state interpretation, transition-ribbon state framing, and event-driven forward shelf and lane boxes into one cohesive corridor framework. Disclaimer This script is provided for educational and informational purposes only. It is not financial advice. Corridor behavior is based on historical price action and can lag, compress, or expand unpredictably during unusual market conditions. Always evaluate signals in context and use appropriate risk controls.
Pine Script®指標
由officialjackofalltrades提供
Kinetic Hull Matrix [JOAT]Kinetic Hull Matrix Overview Kinetic Hull Matrix is an adaptive trend-following indicator centred on a Hull Moving Average cloud with ATR-proportional envelopes, a custom ADX engine, a 0–100 composite signal scoring system, and a multi-timeframe trend table — all rendered in a layered fill system that visually communicates trend strength and cloud penetration depth simultaneously. Retest signals fire when price touches the cloud boundary from within the trending direction, scored by four independent quality factors. The Hull Moving Average — Why It Matters The Hull Moving Average (HMA) was designed to reduce lag while maintaining smoothness. The calculation uses weighted moving averages at half-length and full-length, doubles the half-length result, subtracts the full-length result (creating a de-lagged series), then applies a final WMA at the square root of the length: WMA(2 * WMA(src, n/2) - WMA(src, n), sqrt(n)) This produces a moving average that reacts significantly faster to price changes than a standard EMA or SMA of the same length, while filtering micro-noise through the final WMA pass. The result is a responsive midline that rarely produces whipsaws in trending markets. ATR-Adaptive Cloud Architecture The HMA midline is expanded into a four-layer cloud using the current ATR: - Inner cloud (upper and lower bands): HullMid ± ATR × CloudMultiplier (default 1.0). This is the primary retest detection zone. - Outer bands: HullMid ± ATR × CloudMultiplier × OuterMultiplier (default 1.618, the golden ratio). These define the statistical extreme of the cloud envelope. The cloud dynamically widens during volatile markets and contracts during compression — naturally adapting to market conditions without manual parameter changes. Four fill layers are rendered between the bands using trend-coloured gradients: bright teal in uptrends, muted red in downtrends, creating an intuitive visual heat map of trend energy. Custom ADX Engine Rather than relying on the built-in ta.dmi(), Kinetic Hull Matrix implements its own ADX from first principles: 1. Positive directional movement (plusDM) = max(high - high , 0) when high-to-high exceeds low-to-low 2. Negative directional movement (minusDM) = max(low - low, 0) when low-to-low exceeds high-to-high 3. Both are smoothed via ta.rma() over the ADX length, then divided by the RMA of true range to produce +DI and -DI 4. The directional index DX = abs(+DI - -DI) / (+DI + -DI) * 100, finally smoothed via ta.rma() to produce ADX This gives a transparent, auditable ADX implementation. Values above 25 indicate a trending regime; below 25 indicates ranging conditions. The dashboard and scoring system both use this value. Composite Signal Score (0–100) A retest signal qualifies only when close price enters the inner cloud (touches upper cloud from above in a downtrend or lower cloud from below in an uptrend) while the candle closes back in the trend direction. The resulting signal is then scored: - Proximity score (up to 50): How deeply price penetrated into the cloud. Deeper retests score higher. - Volume score (up to 25): Current volume relative to its 20-bar SMA. Higher participation scores higher. - RSI score (up to 15): RSI directional headroom — long signals score better when RSI has room below 55, short signals when RSI has room above 45. - ADX score (up to 10): Raw ADX value × 0.4, capped at 10. Strong trends produce higher-quality retests. Only signals meeting the configurable minimum score threshold (default 40) are displayed. S/R Line Stamping Each confirmed retest signal stamps a horizontal dotted line at the close price, extending 60 bars forward. These lines serve as dynamic support (for bull retests) and resistance (for bear retests). Lines are automatically invalidated and deleted if price closes through them by more than 0.5 ATR — the indicator only keeps lines that have not been structurally broken. Multi-Timeframe Trend Table (Top Right) Five user-configurable timeframes are assessed using the same dual-EMA logic (fast = HullLen/2, slow = HullLen). Each cell displays BULL or BEAR in the trend's colour. A "X/5 Bull" counter at the bottom summarises alignment. The table also shows current ADX value, RSI, and number of active S/R lines. Inputs Reference Hull Cloud - Hull MA Length (21) — primary HMA period - ATR Length (14) — period for ATR cloud width - Cloud Width (1.0 ATR) — inner cloud half-width multiplier - Outer Band Mult (1.618) — outer band golden-ratio expansion - ADX Length (14) — custom ADX smoothing period - Volume SMA Length (20) — reference for volume scoring - RSI Length (14) Retest Detection - Min Signal Score (40) — minimum composite score to display signal - Max S/R Lines (8) — maximum simultaneous S/R lines on chart - S/R Break Buffer (0.5 ATR) — tolerance before a line is considered broken - Show Score Label / Show S/R Lines MTF Dashboard - Show MTF Trend Table - TF 1–5 — five independently configurable timeframes Visual - Theme: Dark, Light, Auto How to Use 1. Apply to a liquid trending instrument. Allow warmup (roughly 3× Hull Length bars). 2. Identify the trend from cloud colour: teal fills = uptrend, red fills = downtrend. 3. Wait for price to dip into the inner cloud during an uptrend (or spike into it during a downtrend) and close back in the trend direction. 4. Check the score label — prefer grade 55+ (B or higher). Crosscheck with the MTF table: 4+ of 5 timeframes aligned significantly improves reliability. 5. The stamped S/R line from the retest level serves as a reference for re-entry if price pulls back again. Non-Repainting Design All retest signals are gated by barstate.isconfirmed. MTF data uses lookahead_off. S/R line management runs only on confirmed bars. No visual element shifts position after the bar closes. Limitations - In ranging, choppy markets, the cloud direction changes frequently and retest signals may have low predictive value. The ADX score component partially mitigates this, but consider increasing the minimum score threshold in low-trend environments. - S/R lines accumulate during active trend periods. The max line count setting prevents chart clutter. - MTF trend data requires request.security() calls per timeframe. On lower timeframes with very high bar counts, this may slightly affect indicator load time. Disclaimer This indicator is for educational and informational purposes only. No signal scoring system guarantees future performance. Always use proper risk management and conduct independent analysis before trading. Made with passion by officialjackofalltrades
Pine Script®指標
由officialjackofalltrades提供
1
Adaptive Pressure Trail [JOAT]Adaptive Pressure Trail Introduction Adaptive Pressure Trail is an open-source overlay indicator that combines an HMA-based adaptive ratchet trail with a custom volume-weighted Money Flow Index to classify bars into bull pressure, bear pressure, and neutral states. The system uses a three-layer visual architecture — an outer volatility cloud, an inner ratchet band fill, and a core gradient pressure fill between the HMA baseline and candle mid-body — to create a clear, spatially organized picture of momentum and direction on any chart. Volatility squeeze detection identifies compression phases before potential breakouts, and high-confidence signals fire when a squeeze releases simultaneously with pressure alignment. The core problem this indicator solves is that most trail-based systems are either too reactive (flipping constantly on noise) or too slow (missing meaningful moves). The HMA ratchet addresses this: the upper band only falls and the lower band only rises after a direction flip, preventing whipsaw while remaining responsive when momentum is genuine. Layering a volume-weighted MFI filter on top means a directional trail alone is not sufficient — volume-backed money flow must confirm the move before the indicator reports active pressure. Core Concepts 1. HMA Adaptive Ratchet Trail The trail baseline is computed using a Hull Moving Average, which provides low lag while remaining smooth. ATR-scaled upper and lower bands are applied around the HMA. The ratchet rule prevents band noise: the upper band can only move downward (or reset when price closes above it), and the lower band can only move upward (or reset when price closes below it). Direction flips when price closes through the active band. This creates a one-directional drift that is far more stable than a raw crossover trail: The trail direction variable persists with var and updates each bar. Direction == 1 means the lower band is the active trail (bullish), direction == -1 means the upper band is the active trail (bearish). 2. Custom Volume-Weighted MFI Rather than using a standard price-only momentum oscillator, the pressure engine uses a custom volume-weighted Money Flow Index. Positive flow is volume multiplied by HLC3 on bars where HLC3 increased; negative flow is volume multiplied by HLC3 on bars where HLC3 decreased. These are summed over the MFI length and converted to a 0-100 scale using the RSI formula. The result is smoothed with an HMA for responsiveness. This produces a momentum measure that is inherently volume-weighted — large-volume moves carry more influence than low-volume drift. The MFI is further smoothed to distinguish sustained pressure from transient spikes. 3. Pressure Regime Classification Bull pressure is active when the trail direction is bullish AND the smoothed MFI is above the bull threshold. Bear pressure is active when the trail direction is bearish AND MFI is below the bear threshold. Neutral is everything else. This dual-condition structure means you need both directional commitment from the ratchet trail AND volume-backed momentum to enter a pressure state. Either condition alone is insufficient. A rolling 50-bar history tracks what percentage of recent bars were in an active pressure state, producing a Pressure Strength percentage that indicates whether the current regime has been sustained or is a brief spike. 4. Squeeze Detection Band width — the distance between the upper and lower ratchet bands — is compared to its own SMA. When band width drops below 72% of its recent average, the market is compressing. A squeeze start fires a golden diamond marker at the trail level. A squeeze release fires a larger circle marker. The high-confidence signal fires when a squeeze release coincides with an active pressure state, identifying the highest-probability setups where compressed volatility breaks out in a confirmed directional context. 5. Three-Layer Visual Architecture The chart renders three nested visual layers: Outer Cloud: The ATR envelope (cloudMult * ATR from HMA center) filled with a very transparent directional color — gives spatial context to where price is within the volatility range Inner Band Fill: The ratchet upper and lower bands filled with medium transparency — shows the active directional channel Core Pressure Fill: A gradient fill between the HMA baseline and the candle mid-body — transparent at the HMA, saturated at the body, colored by pressure state The trail line itself uses three stacked plots at widths 10, 5, and 2 to create a neon glow shadow effect. Bar coloring uses color.from_gradient driven by MFI intensity, producing increasingly saturated candles as momentum builds. Features HMA Ratchet Trail with Triple-Layer Glow: Direction-persistent adaptive trail rendered as a neon glow (widths 10/5/2) using the bullish lime or bearish fuchsia color Outer ATR Volatility Cloud: Wide ATR envelope filled directionally, providing spatial context at a glance Inner Ratchet Band Fill: Gradient-filled active channel between upper and lower ratchet bands Core Pressure Gradient: Background-to-body gradient between HMA and mid-body, colored by current pressure state HMA Skeleton Reference: Subtle neutral line showing the raw HMA baseline beneath all fills Volatility Squeeze Markers: Golden diamonds during compression, circle flash on breakout High-Confidence Signal: Starred HC LONG / HC SHORT labels when squeeze releases into confirmed pressure alignment — the highest-quality setup the system produces Volume Impulse Labels: When a strong directional candle exceeds the volume threshold, a label shows the volume ratio (e.g., 2.1x vol) at the bar MFI Cross Markers: Small triangles on the trail when MFI crosses the 50 level, marking momentum regime shifts TP Signals: Labeled plotshapes when MFI reaches overbought/oversold extremes in the trail direction Pressure Strength Percentage: Rolling 50-bar % of time spent in active pressure — distinguishes sustained trends from brief spikes Gradient Bar Coloring: color.from_gradient driven by MFI intensity — bars saturate as momentum builds and fade as it weakens 11-Row Dashboard: Pressure state, trail direction, MFI reading, pressure score, pressure strength %, volatility state, band width, trend bars, trail price, ATR Input Parameters Adaptive Trail: Trail HMA Length: Period for the HMA baseline (default 21) Trail ATR Multiplier: Width of inner ratchet bands (default 1.8) Trail ATR Length: ATR lookback for band calculation (default 14) Outer Cloud ATR Width: Outer envelope width multiplier (default 3.2) Squeeze Reference Bars: SMA period for band-width baseline (default 20) Pressure Filter: MFI Length: Volume-weighted money flow lookback (default 14) MFI Smoothing: HMA smoothing on raw MFI (default 7) MFI Bull/Bear Thresholds: Activation levels for pressure states (default 62/38) Signals: TP Overbought/Oversold Levels: MFI levels that trigger TP signals (default 78/22) Impulse Volume Multiplier: Volume multiple above SMA required for impulse label (default 1.3) Visuals: Toggles for entry signals, TP signals, glow, cloud, pressure fill, squeeze markers, and dashboard Bull Color (default lime #a3e635), Bear Color (default fuchsia #e879f9), Neutral Color (default slate #94a3b8) How to Use This Indicator Primary Setup — Trend Following with Pressure Confirmation: Look for the trail to flip direction (circle marker on trail). Wait for MFI to cross the bull or bear threshold, confirming the pressure state activates. Enter in the trail direction once the pressure fill color saturates. Trail your stop at the active trail line. Exit on a TP signal or when the pressure state deactivates. High-Confidence Setup: Wait for squeeze markers (golden diamonds) to appear, indicating compression. When the squeeze releases (larger circle flash) and the pressure state is simultaneously active, the HC LONG or HC SHORT label fires. These are the setups where compressed volatility breaks out with momentum behind it. Filtering with Pressure Strength: The dashboard Pressure Strength percentage tells you how sustained the current move has been. Values above 60% indicate a mature trend. Values below 30% indicate the pressure state is new or unstable. Adjust position sizing accordingly. Reading Impulse Candles: Volume impulse labels (e.g., "2.1x vol") mark bars where a strong directional move was accompanied by significantly elevated volume. These often mark the start or acceleration of a pressure phase and can serve as reference points for support/resistance. APT dashboard showing bull pressure active, MFI at 71.2, P-Score 7.1/10, P-Strength at 64%, band width expanding after a squeeze release, and the trail at current price with ATR reference Indicator Limitations The ratchet trail requires a confirmed close through the active band to flip direction. On higher-timeframe charts with large candle bodies this can mean the flip is confirmed well after the actual turning point The volume-weighted MFI requires volume data. On instruments with unreliable volume reporting (some forex pairs, synthetic indices) the pressure filter may be less meaningful than on equities or futures Squeeze detection uses a 72% band-width threshold. In persistently low-volatility instruments this threshold may trigger too frequently; adjusting the Squeeze Reference Bars parameter can help High-confidence signals require both a squeeze release and active pressure simultaneously. On trending markets with no compression phase, HC signals will be rare MFI thresholds at 62/38 are defaults designed for balanced use; highly trending instruments may require raising the bull threshold and lowering the bear threshold to reduce false pressure activations Originality Statement This indicator is original in its combination of a ratchet-constrained HMA trail with a custom volume-weighted MFI, the three-layer nested visual system, and the squeeze-breakout confluence signal. While HMA trails and MFI oscillators exist independently, this publication is justified because: The ratchet logic applied to HMA (rather than ATR midline or EMA) reduces lag while preventing the constant flipping common in standard trail indicators The custom volume-weighted MFI differs from the standard MFI by using HLC3 as the price component with RSI-formula normalization, producing a smoother measure with better noise rejection The three-layer nested fill architecture (outer cloud, inner band, core pressure gradient) provides a spatially organized visual system where the distance between layers communicates volatility context Squeeze detection integrated with pressure confirmation for HC signals is a novel combination that identifies setups at the intersection of volatility compression and momentum alignment The Pressure Strength rolling percentage provides a trend maturity measure not present in standard trail indicators Disclaimer This indicator is provided for educational and informational purposes only and does not constitute financial advice or a recommendation to buy or sell any financial instrument. Past performance of any pattern or signal does not guarantee future results. All trading involves substantial risk. Always use proper risk management and conduct your own independent analysis. — Made with passion by officialjackofalltrades
Pine Script®指標
由officialjackofalltrades提供
Adaptive Volatility Bands [AVB]Adaptive Volatility Bands (AVB) is a volatility-aware trend-following overlay indicator built on the Kaufman Adaptive Moving Average (KAMA) and dynamically adjusted Bollinger-style bands. **Mathematical Foundation:** The core of AVB is the Kaufman Efficiency Ratio (ER), which measures the ratio of directional price movement to total price movement over a lookback period. An ER near 1.0 indicates a strong trend with minimal noise; an ER near 0.0 indicates choppy, range-bound conditions. The KAMA uses this ratio to automatically adjust its smoothing constant — responding quickly during trends and slowly during consolidation. The bands around the KAMA are not static standard deviations. Instead, they use an adaptive standard deviation that widens when the Efficiency Ratio is low (noisy markets) and tightens when ER is high (trending markets). This creates bands that contract during consolidation (squeeze) and expand during breakouts. **Signal Logic:** Buy signals are generated when price touches the lower band with RSI in oversold territory during an uptrend, or when a squeeze releases with price above the KAMA. Sell signals fire at the upper band with RSI overbought during a downtrend, or at squeeze release below KAMA. Volume confirmation is applied to filter low-conviction signals. **Features:** - Kaufman Adaptive Moving Average with adjustable fast/slow smoothing periods - Adaptive volatility bands that respond to market efficiency - Volatility squeeze detection with bar coloring - RSI and volume filters for signal confirmation - ATR-based stop-loss and take-profit levels - Real-time dashboard showing efficiency ratio, RSI, volatility regime, and trend direction - Fully customizable colors and parameters **Use Cases:** Suitable for forex, crypto, commodities, and equities across all timeframes. Works well on 15-minute to daily charts.
Pine Script®指標
由Jamtrader2020提供
Adaptive Flow Analyzer [JOAT]Adaptive Flow Analyzer Introduction The Adaptive Flow Analyzer is an advanced open-source volatility regime classification indicator that combines dynamic regime detection, entropy analysis, adaptive bands, and momentum waves into a unified flow state system. This indicator helps traders identify whether the market is trending, ranging, or choppy by analyzing volatility patterns, price distribution entropy, and momentum characteristics in real-time. Unlike basic volatility indicators that simply show ATR or Bollinger Bands, this system classifies market conditions into actionable regimes and recommends appropriate trading strategies. Trending regimes favor breakout and trend-following approaches, ranging regimes favor mean-reversion strategies, and choppy regimes signal to avoid trading. The indicator is designed for traders who understand that different market conditions require different strategies and that regime identification is critical for consistent profitability. Why This Indicator Exists This indicator addresses a fundamental challenge in trading: applying the right strategy to the right market condition. Most traders lose money because they use trend-following strategies in ranging markets or mean-reversion strategies in trending markets. By combining multiple regime analysis methodologies, this indicator reveals: Volatility Regime Detection: Classifies markets as Trending, Ranging, or Choppy based on volatility ratio and directional alignment Entropy Analysis: Measures price distribution chaos using information theory - high entropy = uncertainty, low entropy = order Adaptive Bands: Dynamic upper/lower bands that adjust to volatility - shows price position relative to extremes Momentum Waves: RSI rate-of-change visualization showing momentum acceleration and deceleration Chaos Zones: Identifies extreme uncertainty periods when trading should be avoided Strategy Recommendations: Suggests Trend Follow, Mean Revert, or Avoid based on current regime Each component provides a different lens on market flow. Regime classification shows condition, entropy shows uncertainty, bands show extremes, momentum shows acceleration, and chaos zones show danger. Together, they create a comprehensive view of market state. Core Components Explained 1. Volatility Regime Detection The indicator classifies markets into three regimes using volatility ratio and trend alignment: atr = ta.atr(14) atrSma = ta.sma(atr, 50) volRatio = atr / atrSma // Trending: Aligned EMAs + normal volatility trendStrength = (ema9 > ema21 and ema21 > ema50) or (ema9 < ema21 and ema21 < ema50) regime = volRatio > 1.5 ? 0 : // Choppy trendStrength ? 2 : // Trending 1 // Ranging Regime classification: Trending (2): EMAs aligned + volatility ratio < 1.5 - directional market with follow-through Ranging (1): EMAs not aligned + volatility ratio < 1.5 - oscillating market with mean reversion Choppy (0): Volatility ratio > 1.5 - erratic market with no clear pattern The indicator displays regime with color-coded background and text in dashboard. Trending = green, Ranging = orange, Choppy = red. 2. Entropy Calculation Entropy measures the randomness or uncertainty in price distribution using information theory: The indicator: Collects price changes over lookback period (default 50 bars) Creates histogram by dividing changes into bins (default 10 bins) Calculates Shannon entropy: -Σ(p * log(p)) where p = probability Normalizes to 0-100 scale for easy interpretation Entropy interpretation: High entropy (>70): Price changes are random and unpredictable - high uncertainty Medium entropy (40-70): Moderate predictability - mixed conditions Low entropy (<40): Price changes are ordered and predictable - low uncertainty High entropy warns of chaotic conditions where patterns break down. Low entropy confirms regime reliability. The indicator plots entropy as a gradient area chart (green to red). 3. Adaptive Bands System Adaptive bands adjust to volatility and show price position relative to extremes: ma = ta.sma(close, 50) upperBand = ma + (atr * 2.0) lowerBand = ma - (atr * 2.0) // Normalize price position to 0-100 pricePosition = (close - lowerBand) / (upperBand - lowerBand) * 100 The indicator displays: Price position oscillator (0-100 scale) Reference lines at 0 (lower band), 50 (middle), 100 (upper band) Multi-layer glow effect on position line for visibility Color changes based on regime (green for trending, orange for ranging, red for choppy) Price position interpretation: Above 75: Overbought - expect mean reversion in ranging regime Below 25: Oversold - expect mean reversion in ranging regime Sustained above 50: Bullish in trending regime Sustained below 50: Bearish in trending regime 4. Momentum Waves Momentum waves visualize RSI rate-of-change to show acceleration and deceleration: rsi = ta.rsi(close, 14) rsiMomentum = ta.change(rsi, 3) momentumStrength = math.abs(rsiMomentum) / 10 * 100 The indicator plots momentum as gradient area chart: Green gradient: Positive momentum (RSI rising) Red gradient: Negative momentum (RSI falling) Intensity: Stronger color = faster momentum change Height: Taller wave = larger momentum shift Momentum waves reveal: Acceleration into trends (expanding waves) Deceleration at reversals (contracting waves) Momentum divergence from price (warning signal) Momentum exhaustion (extreme waves followed by collapse) 5. Chaos Zone Detection Chaos zones occur when entropy exceeds threshold (75) AND volatility ratio exceeds 1.5: inChaosZone = entropyNormalized > 75 and volRatio > 1.5 When chaos zone is active: Pulsing red background appears "CHAOS ZONE" label displays Dashboard shows "CHAOS" flow state Strategy recommendation changes to "AVOID" Chaos zones represent extreme uncertainty where technical patterns break down. Trading during chaos zones typically results in whipsaws and losses. The indicator warns to stay flat. 6. Strategy Recommendations Based on regime classification, the indicator recommends trading approach: Trending Regime: "TREND FOLLOW" - Use breakout strategies, ride momentum, trail stops Ranging Regime: "MEAN REVERT" - Fade extremes, buy support, sell resistance Choppy Regime: "AVOID" - Stay flat, wait for regime clarity The dashboard displays current recommendation with color coding. This prevents applying wrong strategy to wrong condition. Visual Elements Price Position Oscillator: Multi-layer glow line showing position in bands (0-100) Reference Lines: Horizontal lines at 0, 50, 100 with gradient colors Regime Background: Color-coded background (green/orange/red) based on regime Entropy Area Chart: Gradient fill (green to red) showing uncertainty level Momentum Waves: Gradient area chart showing RSI momentum Chaos Zone Background: Pulsing red background during extreme uncertainty Dashboard: Real-time regime state and strategy recommendations The dashboard displays 9 key metrics: 1. Flow Regime (Trending/Ranging/Choppy) 2. Flow Ratio (volatility multiple) 3. Chaos Index (entropy percentage) 4. Strategy Mode (Trend Follow/Mean Revert/Avoid) 5. Momentum (Strong Up/Strong Down/Neutral) 6. Confidence (High/Medium/Low) 7. Flow State (Directional/Oscillating/Erratic/Chaos) 8. Position (Overbought/Oversold/Neutral) Input Parameters Flow Dynamics: Flow Period: ATR calculation length (default: 14) Band Multiplier: ATR multiple for bands (default: 2.0) Equilibrium Period: Moving average length (default: 50) Adaptive Bands: Enable dynamic band adjustment Entropy Analysis: Chaos Measurement: Lookback for entropy calculation (default: 50) Distribution Bins: Number of histogram bins (default: 10) Chaos Zones: Enable/disable chaos zone detection Visualization: Flow Bands: Show/hide adaptive bands Regime Coloring: Enable/disable background colors Entropy Overlay: Show/hide entropy chart Momentum Waves: Show/hide RSI momentum How to Use This Indicator Step 1: Identify Current Regime Check the dashboard for Flow Regime. This determines your trading approach. Trending = breakouts, Ranging = reversals, Choppy = avoid. Step 2: Assess Chaos Index Check entropy level. High chaos (>70) = unreliable patterns. Low chaos (<40) = reliable patterns. Only trade when chaos is low to medium. Step 3: Check Strategy Recommendation Dashboard shows recommended approach. Follow it. Don't use trend strategies in ranging markets or mean reversion in trending markets. Step 4: Monitor Price Position In ranging regime: Buy near 0-25 (oversold), sell near 75-100 (overbought). In trending regime: Stay with trend when above/below 50. Step 5: Watch Momentum Waves Expanding waves = acceleration (enter trends). Contracting waves = deceleration (prepare for reversal). Divergence = warning. Step 6: Avoid Chaos Zones When chaos zone activates (pulsing red background), close positions and wait. Don't trade during extreme uncertainty. Best Practices Regime determines strategy - always check before trading High entropy + choppy regime = stay flat Low entropy + trending regime = best trend-following conditions Low entropy + ranging regime = best mean-reversion conditions Momentum waves lead price - watch for acceleration Chaos zones are dangerous - respect them Confidence level in dashboard shows setup quality Flow ratio > 1.5 = elevated risk regardless of regime Position oscillator works differently in each regime Regime changes take time to confirm - don't trade transitions Indicator Limitations Regime classification is retrospective - may lag at transitions Entropy calculation requires sufficient data - unreliable on new instruments Choppy regime can persist longer than expected Adaptive bands can whipsaw during regime transitions Momentum waves show acceleration, not direction Chaos zones can have false positives during news events The indicator shows current state, not future regime Strategy recommendations are general - not specific entry signals Regime classification may differ across timeframes Technical Implementation Built with Pine Script v6 using: ATR-based volatility ratio calculations EMA alignment for trend strength detection Shannon entropy calculations with histogram binning Adaptive band system with dynamic adjustment RSI momentum rate-of-change analysis Chaos zone detection with dual criteria Multi-gradient visualization with pulsing effects Real-time dashboard with 9 regime metrics The code is fully open-source and can be modified to suit individual trading styles and preferences. Originality Statement This indicator is original in its comprehensive regime integration approach. While individual components (ATR, entropy, bands, RSI) are established concepts, this indicator is justified because: It synthesizes volatility analysis, entropy theory, and momentum detection into unified regime classification The entropy calculation applies information theory to price distribution for uncertainty measurement Chaos zone detection combines entropy and volatility for extreme condition identification Strategy recommendations adapt to regime in real-time Momentum wave visualization shows RSI acceleration, not just level The confidence scoring system quantifies regime reliability Multi-gradient visualization with pulsing effects enhances regime awareness Real-time dashboard presents 9 metrics simultaneously for holistic regime analysis Each component contributes unique information: Regime shows condition, entropy shows uncertainty, bands show extremes, momentum shows acceleration, chaos shows danger, and strategy shows approach. The indicator's value lies in presenting these complementary perspectives simultaneously with unified classification and actionable recommendations. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors. Regime analysis is a tool for understanding market conditions, not a crystal ball for predicting future behavior. Trending regimes can become ranging. Ranging regimes can become choppy. Past regime patterns do not guarantee future regime patterns. Market conditions change, and strategies that worked historically may not work in the future. The regime classifications displayed are analytical constructs based on current market data, not predictions of future market state. High confidence scores do not guarantee profitable trades. Users must conduct their own analysis and risk assessment before making trading decisions. Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions. The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool. -Made with passion by officialjackofalltrades
Pine Script®指標
由officialjackofalltrades提供
MESA Adaptive Cycle Engine [MarkitTick]💡 The MESA Adaptive Cycle Engine is an advanced, dynamic trend-following overlay designed to adapt to market volatility and cyclical phases. Unlike traditional moving averages that suffer from significant lag during range-bound periods, this tool leverages digital signal processing to stay aligned with the market's dominant cycle. It features an integrated webhook automation system and a real-time risk management dashboard. ✨ Originality and Utility Standard exponential or simple moving averages rely on fixed lookback periods, making them inherently flawed when market conditions shift from trending to cycling. This indicator utilizes the MESA (Maximum Entropy Spectral Analysis) Adaptive Moving Average (MAMA) and Following Adaptive Moving Average (FAMA) concepts. By measuring the phase rate of change via a Hilbert Transform, the moving averages mathematically adapt their alpha speeds. Furthermore, this script is uniquely engineered for modern automated trading, featuring a self-cleaning dashboard and dynamically constructed JSON payloads for external execution engines. 🔬 Methodology and Concepts ● The Hilbert Transform At its core, the script applies a Hilbert Transform to the price source (defaulting to hl2) to extract the real and imaginary components of the market cycle. ● Phase and Period Calculation By calculating the arctangent of the quadrature and in-phase components, it determines the current phase and dominant cycle period. ● Adaptive Alpha The phase's rate of change dictates the alpha variable. In trending markets, the phase changes slowly, allowing the alpha to remain near the Fast Limit. In choppy markets, the phase changes rapidly, dropping the alpha toward the Slow Limit to prevent whipsaws. ● Risk Engine The script establishes automated Stop Loss and Take Profit levels based on an ATR multiplier, updating dynamically upon regime shifts. 🎨 Visual Guide ● MAMA and FAMA Lines The indicator plots two primary lines: the MAMA line (default Green) and the FAMA line (default Red). ● Regime Fill The space between MAMA and FAMA is filled with a semi-transparent Bullish color when MAMA is above FAMA, and a Bearish color when MAMA is below FAMA. ● Entry Signals A small upward triangle is plotted below the bar upon a Golden Cross (Buy Signal), and a downward triangle is plotted above the bar upon a Death Cross (Sell Signal). ● Analytics Dashboard A table in the bottom-right corner displays the current Market Regime, Phase Volatility (ATR), and the active JSON Payload status. 📖 How to Use Wait for a confirmed crossover. A Golden Cross (MAMA crossing above FAMA) initiates a Bullish regime, while a Death Cross initiates a Bearish regime. Use the Regime Fill to hold positions; stay in a long position as long as the fill remains bullish. Monitor the Dashboard for real-time ATR values to assist with manual trailing stops, or rely on the automated Risk Manager's calculated Take Profit (2x ATR) and Stop Loss (1x ATR). Non-standard charts (like Heikin Ashi or Renko) will trigger a runtime warning, as cycle measurements rely on standard time-based OHLC data. ⚙️ Inputs and Settings ● MESA DSP Parameters Price Source: Determines the input data (default hl2). Fast Limit: The maximum alpha speed, usually set to 0.5. Slow Limit: The minimum alpha speed, usually set to 0.05. ● Automation & JSON Payload ATR Multiplier: Controls the width of the Stop Loss and Take Profit levels. Webhook Action (Long/Short): Defines the string action injected into the outgoing JSON payload. 🔍 Deconstruction of the Underlying Scientific and Academic Framework The indicator is deeply rooted in digital signal processing (DSP), specifically pioneered for trading by John Ehlers. The framework models market data as a complex waveform. By passing the data through a 4-bar WMA smoother and then applying a Hilbert Transform, the algorithm isolates the in-phase (I) and quadrature (Q) components. This orthogonal relationship allows the script to map the market's analytic signal onto a complex plane, solving for the instantaneous phase angle. The fundamental academic breakthrough here is using the derivative of this phase (the rate of phase change) to govern the exponential smoothing constant (alpha) of the moving average. This ensures the filter's bandwidth dynamically conforms to the signal's spectral density, offering high-fidelity smoothing without the commensurate group delay found in static linear filters. ⚠️ Disclaimer All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Pine Script®指標
由MarkitTick提供
Ultra Pulse KAMA## Overview TX Ultra Pulse KAMA is a trend-following system built upon the Kaufman Adaptive Moving Average (KAMA) architecture. Unlike standard Moving Averages that lag significantly during trend reversals, this system uses an Efficiency Ratio (ER) to automatically adjust its sensitivity based on market noise. ## How It Works (The Logic) This script does not just plot a KAMA line; it builds a volatility-gated signal system around it: 1. The Adaptive Core (KAMA) The engine calculates the "Efficiency Ratio" (ER) of price action. High ER (Clean Trend): The Moving Average speeds up to capture the move. Low ER (Choppy/Sideways): The Moving Average stops moving (flattens out) to prevent false signals. 2. Volatility Gating (The Trigger) Instead of simple crossovers, this script analyzes the Rate of Change (Delta) of the KAMA line itself. It calculates the Standard Deviation (stdev) of the KAMA's movement over a lookback period. Signal Generation: A signal is only triggered if the KAMA's momentum exceeds a specific volatility threshold (Deviation). This filters out weak breakouts that lack genuine conviction. 3. Trend Filter (The Cloud) A secondary filter layer uses two Exponential Moving Averages (Fast & Slow) to determine the macro regime. Uptrend: Price > Slow EMA & Fast EMA > Slow EMA. Downtrend: Price < Slow EMA & Fast EMA < Slow EMA. If the "Trend Filter" option is ON, Counter-trend signals are strictly suppressed. ## Settings & Modes To make the math accessible, the script includes 3 preset modes that adjust the sensitivity of the Volatility Gate: Aggressive (Scalp): Tighter deviation settings. Reacts faster but captures more noise. Best for 1m-5m charts. Normal (Balanced): The standard deviation setting optimized for 15m-1H charts. Swing (Safe): Requires a significant volatility expansion to trigger. Best for 4H-Daily charts. ## Features Non-Repainting Heikin Ashi: An option to calculate KAMA based on Heikin Ashi source data without repainting issues (using barmerge.lookahead_off). Visual Confirmation: Signals can be set to appear only after the bar closes to ensure validity. Regime Coloring: Candles are colored Aqua (Bullish Trend) or Yellow (Bearish Trend) to visualize the filter state. ## Disclaimer This tool is for educational and analytical purposes only. Technical indicators are lagging by nature and should be used as part of a comprehensive risk management strategy. Past performance does not guarantee future results.
Pine Script®指標
由Tonzlnxz提供
Adaptive Centric Moving Average [LuxAlgo]The Adaptive Centric Moving Average indicator provides a dynamic smoothing tool that adjusts its reactivity based on where the price sits relative to its recent trading range midpoint. 🔶 USAGE The Adaptive Centric Moving Average (AMA) is designed to filter out noise during periods of consolidation while remaining highly responsive during trending moves. When the price is near the center of its recent high-low range, the indicator becomes flatter and less prone to "whipsaws." As price moves toward the extremes of its range, the indicator accelerates to catch the emerging trend. Users can utilize the AMA for trend identification and trailing stop-loss levels. The visual gradient fill between the source price and the AMA line helps traders quickly identify the current trend strength and the distance between price and the smoothed average. 🔶 DETAILS The core logic of the script relies on a normalized relative position (similar to a Stochastic calculation) to determine how far the price is from its range midpoint. 🔹 Adaptive Smoothing Logic The indicator calculates a smoothing factor (alpha) based on the absolute distance from the 50% level of the range. When price is at the midpoint (50%), the alpha is zero, causing the moving average to stay flat. As price moves toward the upper or lower boundaries (0% or 100%), the alpha increases, making the average more reactive. 🔹 The Centric Calculation Unlike standard moving averages that track the source price directly, this indicator centers its target around the range midpoint. The Attenuation Factor scales the distance between the source and the midpoint, while the Power Factor applies an exponent to the smoothing factor, allowing for non-linear reactivity. 🔶 SETTINGS 🔹 Price Settings Source: The price series used for calculations (default is Close). Length: The window size used for pre-smoothing the source and determining the highest highs and lowest lows for the range. 🔹 Adaptive Settings Attenuation Factor: Controls the intensity of the price input relative to the midpoint. Lower values increase reactivity, while higher values provide a more stable, base smoothing speed. Power Factor: Exponents the smoothing factor. Higher values make the moving average significantly flatter when the price is near the range midpoint, requiring stronger moves to trigger a reaction. 🔹 Colors AMA Color: The color of the main Adaptive Centric Moving Average line. Bullish Fill: The color used for the gradient fill when the price is above the AMA. Bearish Fill: The color used for the gradient fill when the price is below the AMA.
Pine Script®指標
由LuxAlgo提供
1
Lorentzian Length Adaptive Moving Average [LLAMA] Adaptation of "Machine Learning: Lorentzian Classification" by Gradient color by base on work by LLAMA: A regime-aware adaptive moving average that bends with the market. Start with a problem traders know: Traditional moving averages are either too slow (EMA200) or too fast (EMA9) Adaptive MAs exist, but they often hug price too tightly or smooth too much, failing to balance bias and tactics LLAMA uses a Lorentzian distance function to adapt its length dynamically. Instead of a fixed smoothing window, it stretches or contracts depending on market conditions. This distortion reduces lag while still providing a clear bias line. The indicator looks back at recent bars and measures how similar they are using a Lorentzian distance (a log‑scaled absolute difference). It keeps track of the “nearest neighbors” — bars that most resemble the current regime. Each neighbor carries a label (long, short, neutral) based on simple price comparisons. By averaging these labels, LLAMA predicts whether the market is leaning bullish or bearish. That prediction is then mapped into a dynamic length between and . Bullish bias -> length stretches toward max (smoother, more stable). Bearish bias -> length contracts toward min (snappier, more reactive). During breakouts, LLAMA tightens and comes into contact with bars, giving actionable signals. During chop, it stretches to avoid false triggers. It covers both ends of the spectrum (bias and tactics) in one line, something static MA's can't do. Think of LLAMA as a lens that bends with the market: Wide lens (max length) for big picture bias. Narrow lens (min length) for tactical precision. The "Lorentzian Loop" is the math that decides when to widen or narrow.
Pine Script®指標
由Starcruiser提供
3
Hurst Exponent Adaptive Filter (HEAF) [PhenLabs]📊 PhenLabs - Hurst Exponent Adaptive Filter (HEAF) Version: PineScript™ v6 📌 Description The Hurst Exponent Adaptive Filter (HEAF) is an advanced Pine Script indicator designed to dynamically adjust moving average calculations based on real time market regimes detected through the Hurst Exponent. The intention behind the creation of this indicator was not a buy/sell indicator but rather a tool to help sharpen traders ability to distinguish regimes in the market mathematically rather than guessing. By analyzing price persistence, it identifies whether the market is trending, mean-reverting, or exhibiting random walk behavior, automatically adapting the MA length to provide more responsive alerts in volatile conditions and smoother outputs in stable ones. This helps traders avoid false signals in choppy markets and capitalize on strong trends, making it ideal for adaptive trading strategies across various timeframes and assets. Unlike traditional moving averages, HEAF incorporates fractal dimension analysis via the Hurst Exponent to create a self-tuning filter that evolves with market conditions. Traders benefit from visual cues like color coded regimes, adaptive bands for volatility channels, and an information panel that suggests appropriate strategies, enhancing decision making without constant manual adjustments by the user. 🚀 Points of Innovation Dynamic MA length adjustment using Hurst Exponent for regime-aware filtering, reducing lag in trends and noise in ranges. Integrated market regime classification (trending, mean-reverting, random) with visual and alert-based notifications. Customizable color themes and adaptive bands that incorporate ATR for volatility-adjusted channels. Built-in information panel providing real-time strategy recommendations based on detected regimes. Power sensitivity parameter to fine-tune adaptation aggressiveness, allowing personalization for different trading styles. Support for multiple MA types (EMA, SMA, WMA) within an adaptive framework. 🔧 Core Components Hurst Exponent Calculation: Computes the fractal dimension of price series over a user-defined lookback to detect market persistence or anti-persistence. Adaptive Length Mechanism: Maps Hurst values to MA lengths between minimum and maximum bounds, using a power function for sensitivity control. Moving Average Engine: Applies the chosen MA type (EMA, SMA, or WMA) to the adaptive length for the core filter line. Adaptive Bands: Creates upper and lower channels using ATR multiplied by a band factor, scaled to the current adaptive length. Regime Detection: Classifies market state with thresholds (e.g., >0.55 for trending) and triggers alerts on regime changes. Visualization System: Includes gradient fills, regime-colored MA lines, and an info panel for at-a-glance insights. 🔥 Key Features Regime-Adaptive Filtering: Automatically shortens MA in mean-reverting markets for quick responses and lengthens it in trends for smoother signals, helping traders stay aligned with market dynamics. Custom Alerts: Notifies on regime shifts and band breakouts, enabling timely strategy adjustments like switching to trend-following in bullish regimes. Visual Enhancements: Color-coded MA lines, gradient band fills, and an optional info panel that displays market state and trading tips, improving chart readability. Flexible Settings: Adjustable lookback, min/max lengths, sensitivity power, MA type, and themes to suit various assets and timeframes. Band Breakout Signals: Highlights potential overbought/oversold conditions via ATR-based channels, useful for entry/exit timing. 🎨 Visualization Main Adaptive MA Line: Plotted with regime-based colors (e.g., green for trending) to visually indicate market state and filter position relative to price. Adaptive Bands: Upper and lower lines with gradient fills between them, showing volatility channels that widen in random regimes and tighten in trends. Price vs. MA Fills: Color-coded areas between price and MA (e.g., bullish green above MA in trending modes) for quick trend strength assessment. Information Panel: Top-right table displaying current regime (e.g., "Trending Market") and strategy suggestions like "Follow trends" or "Trade ranges." 📖 Usage Guidelines Core Settings Hurst Lookback Period Default: 100 Range: 20-500 Description: Sets the period for Hurst Exponent calculation; longer values provide more stable regime detection but may lag, while shorter ones are more responsive to recent changes. Minimum MA Length Default: 10 Range: 5-50 Description: Defines the shortest possible adaptive MA length, ideal for fast responses in mean-reverting conditions. Maximum MA Length Default: 200 Range: 50-500 Description: Sets the longest adaptive MA length for smoothing in strong trends; adjust based on asset volatility. Sensitivity Power Default: 2.0 Range: 1.0-5.0 Description: Controls how aggressively the length adapts to Hurst changes; higher values make it more sensitive to regime shifts. MA Type Default: EMA Options: EMA, SMA, WMA Description: Chooses the moving average calculation method; EMA is more responsive, while SMA/WMA offer different weighting. 🖼️ Visual Settings Show Adaptive Bands Default: True Description: Toggles visibility of upper/lower bands for volatility channels. Band Multiplier Default: 1.5 Range: 0.5-3.0 Description: Scales band width using ATR; higher values create wider channels for conservative signals. Show Information Panel Default: True Description: Displays regime info and strategy tips in a top-right panel. MA Line Width Default: 2 Range: 1-5 Description: Adjusts thickness of the main MA line for better visibility. Color Theme Default: Blue Options: Blue, Classic, Dark Purple, Vibrant Description: Selects color scheme for MA, bands, and fills to match user preferences. 🚨 Alert Settings Enable Alerts Default: True Description: Activates notifications for regime changes and band breakouts. ✅ Best Use Cases Trend-Following Strategies: In detected trending regimes, use the adaptive MA as a trailing stop or entry filter for momentum trades. Range Trading: During mean-reverting periods, monitor band breakouts for buying dips or selling rallies within channels. Risk Management in Random Markets: Reduce exposure when random walk is detected, using tight stops suggested in the info panel. Multi-Timeframe Analysis: Apply on higher timeframes for regime confirmation, then drill down to lower ones for entries. Volatility-Based Entries: Use upper/lower band crossovers as signals in adaptive channels for overbought/oversold trades. ⚠️ Limitations Lagging in Transitions: Regime detection may delay during rapid market shifts, requiring confirmation from other tools. Not a Standalone System: Best used in conjunction with other indicators; random regimes can lead to whipsaws if traded aggressively. Parameter Sensitivity: Optimal settings vary by asset and timeframe, necessitating backtesting. 💡 What Makes This Unique Hurst-Driven Adaptation: Unlike static MAs, it uses fractal analysis to self-tune, providing regime-specific filtering that's rare in standard indicators. Integrated Strategy Guidance: The info panel offers actionable tips tied to regimes, bridging analysis and execution. Multi-Regime Visualization: Combines adaptive bands, colored fills, and alerts in one tool for comprehensive market state awareness. 🔬 How It Works Hurst Exponent Computation: Calculates log returns over the lookback period to derive the rescaled range (R/S) ratio. Normalizes to a 0-1 value, where >0.55 indicates trending, <0.45 mean-reverting, and in-between random. Length Adaptation: Maps normalized Hurst to an MA length via a power function, clamping between min and max. Applies the selected MA type to close prices using this dynamic length. Visualization and Signals: Plots the MA with regime colors, adds ATR-based bands, and fills areas for trend strength. Triggers alerts on regime changes or band crosses, with the info panel suggesting strategies like momentum riding in trends. 💡 Note: For optimal results, backtest settings on your preferred assets and combine with volume or momentum indicators. Remember, no indicator guarantees profits—use with proper risk management. 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