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Trend

Trend Velocity Channel [BackQuant]Trend Velocity Channel Overview Trend Velocity Channel is a trend and momentum-acceleration overlay built around one idea, trend strength is the gap between a fast “lead” average and a slow “lag” average . When the lead line pulls away from the lag line, the market is accelerating in that direction. When that gap collapses, trend energy is fading and reversals become more likely. Instead of using a single moving average slope or crossover, this indicator measures: A leading trend line (DEMA) that reacts quickly. A lagging trend line (slower EMA) that represents slower consensus value. A normalized “velocity / crush” metric: the distance between them in ATR units . A trend regime based on the sign of that velocity. A dynamic channel defined by the lead line on one side and a padded lag boundary on the other. A reversal level engine that marks flip bars and tracks retests and invalidations. The result is a channel that visually answers: Are we accelerating or decelerating? How strong is the current acceleration relative to recent history? Where is the “danger edge” where a reversal would be confirmed? Which flip levels remain relevant and which got invalidated? Concept: lead vs lag as a proxy for trend velocity Markets trend when price doesn’t just move, it keeps moving faster than the slow baseline can follow . If a fast estimator (lead) separates from a slow estimator (lag), that separation is a practical proxy for “velocity”: Lead above lag, bullish acceleration. Lead below lag, bearish acceleration. Lead converging back into lag, trend energy compressing. This script calls that separation Crush , meaning the lead line is “crushing away” from the lag line. Core components 1) Leading line: DEMA The lead line is a Double Exponential Moving Average: dema = DEMA(price, maLen) Why DEMA: It reduces lag relative to a standard EMA. It reacts faster to genuine directional moves. It still smooths noise enough to act as a structural line. DEMA is used as the “inner” channel edge and the glow anchor. 2) Lagging line: Slow EMA The lag line is a slower EMA: lagMA = EMA(price, round(maLen * 1.5)) Why a slower EMA: It represents a slower-moving consensus baseline. It creates a meaningful “gap” against the lead line. It is less sensitive to micro-chop, so separation signals are cleaner. The lag line also becomes the basis for the channel’s outer edge. 3) Volatility normalization: ATR Raw MA distance is not comparable across regimes. A 50-point gap might be huge in a low-vol market and nothing in a high-vol market. So the gap is normalized by ATR: atr = ATR(14) rawCrush = (dema - lagMA) / atr Interpretation: rawCrush = “how many ATRs the lead line is away from the lag line.” This standardizes the signal across instruments and volatility states. 4) Crush smoothing The gap can still jitter, especially in choppy markets. So it is EMA-smoothed: crush = EMA(rawCrush, crushSmth) Lower crushSmth: Faster regime flips, more noise. Higher crushSmth: More stable regimes, slower reaction. Trend regime and flips Trend direction is derived directly from the sign of the smoothed crush: trend = crush > 0 ? +1 : -1 flip = trend != trend Meaning: Bull regime: lead (DEMA) is above lag baseline in ATR units. Bear regime: lead is below lag baseline. Flip: the velocity sign changed, meaning acceleration has switched direction. This is not a price crossover system, it is a lead-lag separation regime system . Measuring strength: crushNorm The script also grades how extreme current crush is relative to recent conditions: crushAbs = abs(crush) crushHigh = highest(crushAbs, 80) crushNorm = crushHigh > 0 ? min(crushAbs / crushHigh, 1) : 0 Interpretation: crushNorm near 0 means separation is small relative to recent extremes, trend is weak or compressing. crushNorm near 1 means separation is near the largest seen recently, trend acceleration is strong. This strength scale drives: Color intensity (gradient) Glow width “Peak Crush” alert condition Channel construction Inner edge The inner edge is the leading line: inner = dema This is the “fast structure” of the move. Outer edge The outer edge is built from the lag line plus an ATR padding: outer = (bull) lagMA - atr * chanPad outer = (bear) lagMA + atr * chanPad This is important. The lag line sits behind price, so the script offsets it outward by a user-defined fraction of ATR. This creates a more realistic boundary that accounts for volatility. Interpretation: In bull regimes, the outer boundary is below lagMA, creating a support-like corridor beneath price. In bear regimes, the outer boundary is above lagMA, creating a resistance-like corridor above price. The channel is intentionally asymmetric This channel is not “± ATR around a mean.” It is directional: Inner edge hugs price via fast DEMA. Outer edge is anchored to lagMA and padded outward. So it behaves like a trend corridor where: The inner edge shows where the trend is currently “being pulled.” The outer edge shows the boundary where the trend would be meaningfully compromised if crossed. Ribbon fill (3-layer depth) Two midpoints are created between inner and outer: mid1 = inner + (outer - inner) * 0.33 mid2 = inner + (outer - inner) * 0.66 Then the fill is layered: inner → mid1 (most opaque) mid1 → mid2 mid2 → outer (most transparent) This creates a depth effect that visually communicates where price is sitting within the corridor. When the corridor is tight and strong, the ribbon looks concentrated. When it expands, the ribbon spreads and fades. Color logic (trend + strength) The indicator uses a gradient color where direction sets the palette and crushNorm sets intensity: Bull: faint green → strong green as crushNorm increases Bear: faint red → strong red as crushNorm increases This means you can read two things instantly: Direction (bull vs bear) Acceleration strength (faded vs intense) Glow engine on DEMA Glow width scales with ATR and crushNorm: glowW = atr * 0.07 * (0.5 + crushNorm) So: High acceleration = larger glow, more “energy” around the lead line. Low acceleration = smaller glow. Glow is built as multiple invisible plots above and below DEMA with layered fills, forming a halo around the lead line that encodes strength. Flip-aware band breaking The outer boundary line is broken on flips: bandBrk = flip ? na : outer plot(..., plot.style_linebr) This prevents a misleading continuous line across regime changes, since the outer edge swaps sides on flip. Crush reversal levels (flip levels engine) This script includes a level system that plants a dashed horizontal level on every regime flip, then tracks: Whether price retests it (first touch marker) Whether price invalidates it (deletes it) How long it extends forward How many levels are kept 1) Level placement On a flip: If trend flips bullish, the level is placed at the flip bar’s low. If trend flips bearish, the level is placed at the flip bar’s high. That makes sense structurally: Bull flip low is a “pivot low” candidate. Bear flip high is a “pivot high” candidate. Then a dashed line is drawn forward ~60 bars. 2) Level storage and maxLvls Levels are stored in an array and capped by maxLvls. When the cap is exceeded, the oldest is deleted. This keeps the chart readable. 3) Level invalidation (broken logic) Each level is monitored: Bull flip level breaks if price closes far below it: close < level - atr * 2.5 Bear flip level breaks if price closes far above it: close > level + atr * 2.5 This is a volatility-scaled invalidation. If price pushes through a flip level by a large margin in ATR terms, it’s no longer acting like a meaningful reaction point. 4) Retest detection A “touch” is detected when: close is within 0.25 ATR of the level, and close two bars ago was not close (distance > 0.5 ATR), and the level hasn’t been marked retested yet. On first retest, an “x” marker is printed and the level’s retested flag is set to true so it won’t spam. What these levels represent They are not generic support/resistance. They are regime pivot levels created by a change in lead-lag acceleration. In practice: Untested flip levels can act like “memory zones” where price may react. Retested levels become less special, still relevant but not “naked.” Invalidated levels are removed to reduce noise. Signals and alerts The script provides: Crush Bull: flip into bullish regime (crush crosses above 0 via smoothing logic) Crush Bear: flip into bearish regime Peak Crush: crushNorm > 0.85, meaning separation is near recent max, strong acceleration Important: Peak Crush is not a reversal call. It flags strong trend energy. That can precede continuation or exhaustion, you use it as context, not a standalone trade trigger. How to use it Trend following framework Stay aligned with the regime color. In bull regime, treat the outer boundary as the “structure floor.” In bear regime, treat the outer boundary as the “structure ceiling.” The inner DEMA is your fast guide, the outer edge is your compromise boundary. Acceleration read Increasing color intensity and thicker glow imply acceleration is strengthening. Fading color and shrinking glow imply acceleration is decaying and the move is losing energy. A regime flip is a clean state change, not a micro-signal. Using reversal levels Treat naked flip levels as potential reaction zones. Watch first retest behavior, clean rejection suggests the flip level is holding. If the level invalidates by 2.5 ATR, it’s removed because structure has been overwritten. Key inputs explained MA Length (maLen) Sets both the lead line length and the lag line length (scaled by 1.5). Lower values: More sensitive, more flips. Higher values: Smoother, fewer flips, slower response. Crush Smoothing (crushSmth) Controls stability of the velocity signal. Lower: Fast flips, noisier regime. Higher: More confirmation, later flips. Channel Padding (chanPad) Controls how much extra ATR space is added beyond lagMA. Higher padding: Wider channel, fewer boundary touches. Lower padding: Tighter boundary, more reactive “risk edge.” Max Levels Controls how many historical flip levels are retained. Summary Trend Velocity Channel treats trend as lead-lag separation expressed in ATR units. A fast DEMA tracks the active move, a slower EMA defines baseline value, and their normalized gap (Crush) defines both direction and acceleration strength . That strength drives an adaptive visual language (gradient color, glow width, ribbon depth). The channel itself is directional, with the lead line as the inner edge and a volatility-padded lag boundary as the outer edge, acting as a structural “compromise line.” On every regime flip the script plants a pivot level, tracks retests, and deletes invalidated levels, giving you a clean map of acceleration-based reversal zones.
Pine Script® インジケーター
BackQuantの投稿
Adaptive Volatility Trend [WillyAlgoTrader]Adaptive Volatility Trend (AVT) is a trend-following overlay indicator that dynamically adjusts its sensitivity to market conditions using the Kaufman Efficiency Ratio and ATR-based volatility bands. Unlike static moving averages or fixed-width channels, AVT continuously adapts: it accelerates in strong directional moves and slows down during choppy, range-bound price action — reducing whipsaws where most trend indicators fail. 🔍 WHAT MAKES IT ORIGINAL The core innovation is a self-tuning mechanism built on three adaptive layers: 1. Kaufman Efficiency Ratio (ER) as an adaptive engine. The ER measures how "efficient" price movement is — the ratio of net directional change to total path traveled over N bars. An ER near 1.0 means price moved in a clean straight line (strong trend); near 0.0 means it went sideways with lots of noise. AVT uses the smoothed ER to dynamically blend between a fast constant (2-period EMA speed) and a slow constant (30-period EMA speed), producing an Adaptive Moving Average that responds quickly in trends and becomes sluggish in chop. 2. ER-scaled ATR bands. The volatility channel doesn't just use raw ATR × multiplier. It incorporates the Efficiency Ratio to narrow the bands during trending conditions (where ER is high) and widen them during ranging markets (where ER is low). This means the channel contracts when the trend is clean — keeping signals tight — and expands when price is noisy — filtering out false breakouts. 3. Composite Signal Scoring System (0–100). Every signal receives a quality score based on three weighted components: — Trend strength (0–40 pts): derived from the Efficiency Ratio magnitude — Momentum (0–30 pts): RSI distance from the neutral 50-level in the signal direction — Volume confirmation (0–30 pts): current volume relative to its 20-period average Only signals exceeding the user-defined minimum score threshold are displayed — letting you filter out low-conviction setups. ⚙️ HOW IT WORKS Trend detection: The indicator calculates an Adaptive Moving Average using the Kaufman method. The slope of this line determines trend direction: if the line rises by more than 5% of current ATR, the trend is classified as bullish; if it falls by the same threshold, bearish. A small dead zone (ATR × 0.05) prevents noise from flipping the trend. Signal generation: A BUY signal fires when: — Trend flips from bearish/neutral to bullish (slope turns positive) — Price is above the adaptive line — RSI is not in overbought territory (if RSI filter is enabled) — Volume exceeds its moving average × threshold (if volume filter is enabled; auto-disabled on forex) — Composite score meets the minimum threshold — Bar is confirmed (close-based, no repainting) SELL signals use the mirror logic. Anti-repaint compliance: All signals require barstate.isconfirmed — they only trigger on the close of the bar and never change on historical data. A warmup period (minimum 50 bars or 2× Trend Length) prevents unreliable early signals. Volume filter on forex: The indicator automatically detects instruments with no volume data (common on forex pairs) and bypasses the volume filter for those symbols, so it works seamlessly across asset classes. 📖 HOW TO USE Reading the chart: — Green trend line + upward slope = bullish regime — Red trend line + downward slope = bearish regime — Yellow trend line = neutral / transitioning — ▲ labels below bars = confirmed BUY signal — ▼ labels above bars = confirmed SELL signal — The shaded channel around the trend line shows volatility-adjusted support/resistance zones Quick-start presets: — Conservative (Length 30 / ATR 20 / Mult 2.5): fewer signals, higher reliability — suited for swing trading on 4H–Daily — Default (Length 20 / ATR 14 / Mult 2.0): balanced for most timeframes — Aggressive (Length 12 / ATR 10 / Mult 1.5): more signals — suited for 15min–1H — Scalping (Length 8 / ATR 7 / Mult 1.2): fast response — optimized for 1–5min charts Signal quality: Use the Score value in the dashboard to gauge conviction: — 70–100: strong trend + momentum + volume alignment — 40–69: moderate setup, consider additional confluence — Below threshold: signal filtered out (not shown) Dashboard panel: Displays current trend direction, last signal with its score, Efficiency Ratio %, RSI value, timeframe, and indicator version. Position is adjustable to any corner of the chart. Alerts & automation: Supports both standard TradingView alert messages and JSON webhook format for integration with 3Commas, Alertatron, or custom bots. Alert messages include ticker, price, timeframe, and signal score. ⚙️ KEY SETTINGS REFERENCE — Trend Length (default 21): lookback for adaptive MA — higher = smoother, lower = faster — ATR Length (default 14): period for volatility bands — higher = wider bands — Band Multiplier (default 2.0): ATR multiplier for channel width — higher = fewer false signals — RSI Filter (on by default): blocks buy signals when RSI > 70, sell signals when RSI < 30 — Volume Filter (on by default): requires volume > SMA(20) × 1.2 — auto-disabled on forex — Min Signal Score (default 40): minimum composite score for signal display — Efficiency Smoothing (default 5): EMA smoothing of the Kaufman ER ⚠️ IMPORTANT NOTES — This indicator does not use future data. No lookahead, no repainting. — Past performance shown on any chart does not guarantee future results. — AVT is a tool for identifying trend direction and generating signal candidates — it is not a complete trading system. Always use proper risk management and consider additional confluence before entering trades. — The indicator works best in trending markets. In prolonged sideways conditions, even filtered signals may produce whipsaws — the Efficiency Ratio in the dashboard helps you assess whether the current market is trending enough for signal reliability.
Pine Script® インジケーター
WillyAlgoTraderの投稿
Mentor Michael - Adaptive Regime Pro v1.0📌 Professional Entropy-Based Adaptive Trend System | Gold Optimized Mentor Michael – Adaptive Regime Pro v1.0 is a professional-grade adaptive trend engine designed to automatically adjust to changing market conditions using entropy-driven volatility modeling. This system is engineered especially for XAUUSD (Gold), where price behavior shifts rapidly between expansion and compression phases. Instead of using fixed moving averages or static volatility bands, this indicator dynamically adapts smoothing and structure based on real-time market regime detection. The result is a clean, professional trend framework that measures both direction and quality. 🧠 Core Engine – Entropy-Based Market Regime Detection At the heart of the system is an entropy calculation derived from: • Logarithmic return dispersion • Standard deviation vs mean normalization • Controlled scaling between 0 and 1 This produces a normalized entropy value representing market uncertainty. Low Entropy → Structured, directional market High Entropy → Choppy, mean-reverting market The system uses this value to drive all adaptive components. 📊 Adaptive EMA (Dynamic Smoothing Model) Unlike traditional EMAs with fixed smoothing constants, this system modifies the alpha coefficient dynamically. When entropy is high: • EMA becomes more reactive • Adjusts faster to noise When entropy is low: • EMA becomes smoother • Better at riding sustained trends This prevents lag during breakouts while avoiding overreaction during consolidation. 📦 Dynamic Volatility Bands (Dual Structure Model) Two ATR-based envelopes are built around the adaptive EMA: Inner Bands (Fast Reaction Zone) Used for detecting regime shifts. Price closing above inner upper band → Bullish regime Price closing below inner lower band → Bearish regime Outer Bands (Volatility Expansion Zone) Track broader volatility expansion and serve as structural references. Band width scales automatically based on trend strength. Stronger trend → Wider bands Choppy market → Narrower bands This creates a volatility-aware structure instead of static channels. 🎯 Trend State Logic The script maintains internal trend memory to avoid signal flickering. A regime shift only occurs when price confirms beyond the inner band. • Bullish Trend • Bearish Trend • Neutral State This produces cleaner trend transitions and professional-level stability. 💪 Signal Strength Meter (0–100) Signal Strength = (1 − Normalized Entropy) × 100 This converts volatility behavior into a measurable percentage. High Score → Clean directional conditions Low Score → Compression or indecision Instead of guessing trend quality, you see it numerically. 🖥 Trend Dashboard Panel The built-in dashboard (top-right corner) displays: • Current Trend State • Signal Strength (%) • Entropy (%) The panel updates in real time and can be toggled ON/OFF. Designed for fast visual decision-making without clutter. 🎨 Visual Structure • Adaptive color-coded EMA • Dynamic layered volatility fills • Optional bar coloring • Controlled transparency for clean overlays • Professional layout for live trading environments The structure is designed to look premium and readable across all timeframes. 🔔 Alert System Built-in alert conditions trigger on: • Bullish Regime Shift • Bearish Regime Shift Alerts activate only when confirmed regime transitions occur. Suitable for: • Manual execution • Automation • Session monitoring ⚙️ Input Parameters Explained Entropy Lookback Controls regime sensitivity. Lower values increase responsiveness. Higher values produce smoother macro trends. Fast Band Multiplier Controls inner band width (signal sensitivity). Slow Band Multiplier Controls outer band width (volatility envelope scale). Visual Controls Custom colors, transparency, dashboard toggle, and bar coloring options. 💎 Optimized for XAUUSD (Gold) Gold trends strongly but consolidates sharply. This adaptive entropy structure is specifically tuned to handle that expansion-compression behavior. Recommended for XAUUSD 4H: Lookback: 22–28 Fast Multiplier: 1.6–1.9 Slow Multiplier: 3.2–3.8 Also performs well on: • BTCUSD • Major Forex pairs • Indices ✅ Ideal For • Trend-following traders • Swing traders • Volatility regime analysis • Confluence with Order Blocks / FVG / Liquidity Sweeps • Gold and Crypto trading 🔥 What Makes This Different? Most indicators use: • Fixed smoothing • Static ATR bands • No regime awareness Adaptive Regime Pro: • Measures entropy in real time • Dynamically adjusts smoothing • Scales volatility structure • Quantifies trend strength objectively • Maintains stable regime memory It is not just a moving average —It is a volatility-aware adaptive regime system. ⚠️ Disclaimer This script is provided for educational and analytical purposes only. It does not provide financial or investment advice. Always apply proper risk management.
Pine Script® インジケーター
Mentor_Michael03の投稿
Multi-Index VWAP DashboardTo post this on the TradingView Community Scripts, you want a description that highlights its multi-instrument correlation and institutional session data. It’s not just a VWAP indicator; it’s a "Tape Reading" dashboard for index traders. Here is a structured description you can copy and paste: Description Overview The Multi-Index Institutional VWAP Dashboard is a high-performance Tape Reading tool designed for NQ, ES, and YM traders. It provides a real-time "at-a-glance" matrix of how the three major US Indices are performing relative to critical institutional benchmarks. Instead of cluttering your main chart with dozens of lines, this dashboard compiles the data into a clean, Bookmap-inspired UI. Key Benchmarks Tracked The dashboard monitors price action for NQ, ES, and YM against: NY VWAP: Anchored specifically to the New York Open (09:30 AM ET). PD NY VWAP: The closing value of the previous day's New York session VWAP—a major level for institutional mean reversion. LOD/HOD Anchored VWAP: Dynamic VWAPs that re-anchor automatically to the current Day's High and Day's Low. 15m Opening Range (OR): Detects if price is trading Inside, Above (▲), or Below (▼) the first 15 minutes of the NY session. Trend Matrix: A real-time momentum filter for each index to identify cross-market divergence. Features Bookmap Style Visuals: Uses custom bubble icons (◎) for a modern, heat-map aesthetic. Timezone Optimized: Hard-coded for New York Session hours while respecting your local chart offset. Customizable Layout: Full control over dashboard position (Top/Bottom/Corners) and text sizing to fit any monitor resolution. Cross-Index Correlation: Easily spot "SMT Divergence" (e.g., when NQ is above its NY VWAP but ES is below it). How to Use Bullish Confirmation: Look for "All Green" bubbles across all three indices, specifically price holding above the NY VWAP and OR High. Mean Reversion: Use the PD NY VWAP and HOD/LOD VWAP as targets or areas of interest for potential reversals. Trend Divergence: If NQ is showing "Bullish" while YM is showing "Bearish," exercise caution as the indices are decoupled. Settings Tips Position: Move the dashboard to the "Bottom Right" if you have other indicators at the top. Style: Toggle between "Solid," "Bubble," or "Ring" icons in the script settings to match your chart's theme.
Pine Script® インジケーター
bansheecapitalの投稿
EMA xPair [crlmx]EMA indicator pair with smooth gradient fill. Timeframe adjustable to fixed value or follow the chats. Key Features - Two configurable EMAs (default 8 / 24 on day TF) - 15 reference timeframes from 1min to Monthly - Gradient fill between EMAs - colour tracks the dominant line - Midline between the two EMAs - acts as a dynamic centre reference - Streamlined inputs / UI brought to you by crlmx Trading Applications - Use as trend filter, not entry trigger - Gradient fill enhances visual read on trend bias - Midline acts as support/resistance between the two EMAs - Daily 8/24 works across all instruments and timeframes - Daily 30/50 gives a very solid HTF trend signal across assets for swing / position trading - Recommended Settings Scalping (fast): EMA1: 8 | EMA2: 24 | TF: 1min | Chart: 1m–5m Scalping: EMA1: 8 | EMA2: 24 | TF: 3–5min | Chart: 1m–5m Day Trading: EMA1: 8 | EMA2: 24 | TF: Day | Chart: 15m–1H Swing Trading: EMA1: 30 | EMA2: 50 | TF: Day | Chart: 4H–1D Version History v1.21 (Latest - 23 Feb 2026) - Gradient fill between EMAs with transparency control - 15 reference timeframes (1min to Monthly) - Midline defaults to off
Pine Script® インジケーター
crlmxの投稿
Adaptive Trend RegimeAdaptive Trend Regime Adaptive Trend Regime is a market regime detection indicator designed to identify whether the market is trending bullish, trending bearish, or moving sideways. The indicator combines EMA alignment, ADX trend strength, and EMA slope momentum to filter market noise and highlight only meaningful directional movement. Instead of reacting to every price fluctuation, this tool focuses on detecting sustained market conditions. ━━━━━━━━━━━━━━━━━━ How It Works Fast and Slow EMAs determine market direction. ADX measures trend strength and filters ranging markets. EMA slope confirms momentum and removes weak trends. Volatility-adjusted zones adapt dynamically using ATR. The background zone changes color depending on market regime: 🟢 Bullish Trend — Strong upward momentum 🔴 Bearish Trend — Strong downward momentum 🟡 Range — Low momentum or consolidation ━━━━━━━━━━━━━━━━━━ Parameters Fast EMA Length Controls short-term market direction sensitivity. Slow EMA Length Defines the broader trend structure. ADX Threshold Minimum trend strength required to classify the market as trending. Higher values produce more conservative signals. Slope Dead Zone (%) Filters small EMA movements considered market noise. Increasing this value reduces false trend detection. Slope Lookback Number of bars used to calculate EMA slope momentum. ATR Multiplier Controls the size of the displayed trend zone relative to market volatility. ━━━━━━━━━━━━━━━━━━ Best Usage • Trend-following strategies • Market regime filtering • Trade confirmation • Avoiding low-momentum environments Works across all markets and timeframes. ━━━━━━━━━━━━━━━━━━ Notes This indicator does not provide buy or sell signals. It is intended to help traders understand market conditions and trade in alignment with prevailing momentum.
Pine Script® インジケーター
ferCVの投稿
Strategic Trend FilterStrategic Trend Filter (STF) | MisinkoMaster Strategic Trend Filter is a structurally weighted trend confirmation overlay designed to identify high-quality directional environments while filtering out low-volatility noise and weak structural movement. Rather than relying on traditional moving averages, STF constructs a dynamically weighted equilibrium level derived from multiple price components and structural factors. It then validates trend conditions only when price displacement is supported by sufficient volatility expansion. The result is a disciplined trend filter that emphasizes structural strength over simple price crossing behavior. Core Philosophy Many trend tools respond primarily to price direction. STF goes further by incorporating: • Structural correlation behavior • Statistical dispersion • Rate-of-change magnitude • Price range positioning • Volatility confirmation This multi-factor structure allows the filter to respond only when price movement demonstrates internal coherence and sufficient expansion. In short, STF is designed to confirm quality trends, not just directional movement. Key Features Multi-factor structural weighting model Dynamic equilibrium filter instead of traditional moving average Volatility-confirmed trend validation Volume-aware filter stabilization Median-based volatility confirmation Automatic trend coloring Optional on-chart long and short labels Overlay design for direct price interaction Reduced whipsaws in low-volatility environments Suitable as a directional bias filter for strategies How It Works (Conceptual) The indicator builds a composite equilibrium level using several internal components: Structural Correlation Measures how individual price components relate to the composite price structure over the lookback window. Statistical Dispersion Standard deviation measurements help evaluate how far price is distributing around equilibrium. Momentum Magnitude Absolute rate-of-change calculations measure directional displacement strength. These components are combined into weighted factors that influence how much each price dimension contributes to the final filter value. The resulting filter represents a dynamic structural equilibrium rather than a simple average. Additionally, a volatility confirmation layer compares current true range behavior against its median condition. Trend state changes are validated only when sufficient volatility is present. Proprietary weighting relationships remain protected in the invite-only implementation. Trend Logic Explained Bullish State Activated when price structure holds above the dynamic filter and volatility confirms expansion. This suggests sustained upward pressure supported by structural alignment. Bearish State Activated when price structure remains below the filter and volatility confirms expansion. This indicates organized downside movement rather than random fluctuation. If volatility contracts or price fails to maintain structural positioning, the filter avoids unnecessary state changes. Volume Stabilization Mechanism When volume declines relative to the previous bar, the filter stabilizes temporarily. This reduces sensitivity during participation drops, helping avoid false transitions caused by thin liquidity conditions. This feature improves robustness in lower-liquidity assets and during session transitions. Visual Components Dynamic Filter Line Represents structural equilibrium and adjusts continuously to price behavior. Color-Coded Environment Filter and candles change color to reflect bullish or bearish state. Shaded Region A filled zone between price and filter visually highlights directional dominance. Optional Long / Short Labels When enabled, transition points are clearly marked on the chart. Inputs Overview Lookback Period Controls the primary structural evaluation window. Higher values create smoother, more stable filters. Lower values increase responsiveness. Confirmation Length Defines the volatility median window used for expansion validation. Allow Labels? Enables or disables on-chart long and short markers. Parameter Tuning Guidance Shorter Lookback → Faster adaptation → More sensitive to structural shifts → Suitable for lower timeframes Longer Lookback → More stable equilibrium → Better for swing or position trading Shorter Confirmation Length → Faster volatility confirmation → More reactive signals Longer Confirmation Length → Stricter volatility validation → Fewer but stronger transitions Best Use Cases Directional bias filter for breakout systems Confirmation layer for momentum strategies Trend qualification before position scaling Volatility-aware trade filtering Multi-timeframe bias alignment Portfolio-level environment scanning Strategy Integration Ideas Use STF to: • Trade only in the direction of confirmed trend state • Avoid mean-reversion setups during strong structural expansion • Filter out low-volatility consolidation phases • Improve win rate by aligning entries with structural bias STF performs best when paired with entry triggers such as pullbacks, continuation patterns, or momentum expansions. Summary Strategic Trend Filter is a structurally weighted, volatility-confirmed overlay designed to detect organized directional movement while filtering weak or noisy price action. By combining correlation structure, dispersion metrics, momentum magnitude, and volatility validation, STF delivers a disciplined trend confirmation framework suitable for discretionary traders and systematic strategy developers alike.
Pine Script® インジケーター
MisinkoMasterの投稿
9
Directional Logistic Oscillator | GainzAlgoOverview The Directional Logistic Oscillator (DLO) is a momentum-based indicator designed to measure directional market strength and identify potential trend reversals or mean-reversion opportunities. It builds on the classic Directional Movement Index (DMI) by transforming its components (+DI, -DI, and ADX) into probabilistic signals using logistic functions, then combining them into a bounded oscillator that oscillates between approximately -1 and +1. Unlike traditional oscillators like RSI or MACD, DLO emphasizes directional probability by estimating the likelihood of bullish or bearish dominance while factoring in overall trend strength (via ADX). This makes it particularly useful for: Spotting overbought/oversold conditions in ranging markets. Confirming trend shifts in trending markets. Generating reversal signals based on oscillator cycles. The oscillator is plotted as histogram bars (columns) for visual clarity, with color-coding to highlight strength and direction. Positive values indicate bullish momentum, negative values bearish, and crossings of key levels can signal trading opportunities. How It Works At its core, DLO processes DMI data through a logistic transformation to create "probabilities" of directional movement: 1. DMI Calculation : Uses the standard DMI with a user-defined length (default 14) to compute +DI (upward movement), -DI (downward movement), and ADX (trend strength). 2. Logistic Probability : Each DMI component is normalized against its long-term mean and passed through a logistic (sigmoid) function. This creates smooth probabilities between 0 and 1. The logistic function is defined as: logistic_prob(series, mean_lb, slope, smooth_len) => mean = ta.sma(series, mean_lb) z = (series - mean) * slope prob_raw = 1.0 / (1.0 + math.exp(-z)) ta.ema(prob_raw, smooth_len) This step makes the indicator adaptive to market conditions, with the "slope" controlling how sharply it reacts to deviations from the mean. 3. Net Directional Strength : Bullish minus bearish probability, scaled by ADX probability and a user-defined multiplier, then bounded using a hyperbolic tangent (tanh) function to keep values between -1 and +1. net_dir = prob_plus - prob_minus strength_raw = net_dir * prob_adx * osc_scale strength_bound = tanh(strength_raw) Tanh ensures smooth, bounded output without clipping extremes unnaturally. 4. Smoothing and Signals: The raw strength is smoothed with EMA, then further processed into SMA and EMA lines for signal generation. Percentile-based thresholds (adaptive over a lookback period) detect extreme zones for mean-reversion signals. The result is a visually intuitive oscillator: Green bars for bullish, red for bearish, with varying intensity based on momentum. Inputs DLO offers customizable settings grouped for ease of use. Defaults are tuned for balanced performance on daily charts. DMI Settings DI Length (default: 14): Controls DMI sensitivity. Shorter lengths react faster to price changes but add noise; longer lengths smooth signals for trends. Mean Lookback (default: 360): The period for calculating the long-term average of DMI components. Higher values provide a more stable baseline, reducing false signals from short-term volatility. Lower values make the indicator more responsive but noisier Difference between high and low mean lookback period, lower length can pick up on new trends faster but at the cost of increased noise. Logistic Probability Settings LR Slope (higher = steeper) (default: 0.18): Adjusts the steepness of the logistic curve. Lower values create gradual transitions (smoother oscillator); higher values make sharp shifts, emphasizing extremes. Probability Smoothing (EMA) (default: 3): Short EMA to reduce noise in probabilities. Keep low (1-5) for responsiveness; higher for smoothness. Oscillator Settings Oscillator Scale (pre-tanh) (default: 2.5): Multiplies net strength before bounding. Higher values increase sensitivity and amplitude (larger swings); lower values compress the range for subtler signals. Comparison of 4 different settings for Oscillator scale, showing that as the scale parameter increases, the oscillator output becomes more pronounced, exhibiting higher amplitude compression toward the bounds and spending more time saturated near the extreme values of +1 and −1. Oscillator Smoothing Length (default: 7): Period for SMA/EMA smoothing of the final oscillator. Longer = smoother, fewer signals; shorter = more reactive. Color & Display Settings Buy Color / Sell Color: Customize colors for bullish/bearish visuals. Plot Reversion Signals (default: true): Shows arrows for cycle reversals (local highs/lows). Plot Mean-Reversion Signals (default: true): Arrows for crossings from extreme percentile zones. Plot Oscillator MA (default: false): Overlays an SMA on the oscillator for additional confirmation. Allow Intrabar Updating (default: true): Enables real-time updates within incomplete bars (may cause minor repainting). Visuals Oscillator Histogram: Columns colored green (bullish) or red (bearish), with lighter shades for weaker momentum. Crosses above/below zero signal momentum shifts. Horizontal Lines: Zero (neutral), +0.5 (strong bullish), -0.5 (strong bearish). Background Highlights: Subtle green/red shading when in strong zones. Bar Colors: Mirrors oscillator direction on the price chart. Color-coded trend regimes: green/teal highlight strong and weak uptrends, red/purple mark strong and weak downtrends, while the oscillator histogram confirms direction and strength through its polarity and amplitude. Signals Mean-Reversion (MR) Signals : Triangles (▲/▼) when the smoothed oscillator crosses up from low percentiles (oversold) or down from high percentiles (overbought). These are adaptive, using historical data for dynamic extremes. Buy: Oscillator crosses above lower threshold (e.g., 10th/5th percentile). Sell: Crosses below upper threshold (e.g., 90th/95th percentile). Reversion Signals : Arrows (⬆/⬇) at local turning points in the oscillator cycle, indicating potential reversals. Zero-Line Crosses : Basic bullish/bearish momentum changes. Usage Tips Trend Confirmation: Use in trending markets—persistent positive/negative values confirm up/down trends. Pair with moving averages for entries. Mean-Reversion: In sideways markets, trade MR signals from extremes. Combine with support/resistance. Divergences: Look for price making new highs/lows while DLO doesn't for reversal setup. Alerts MR Buy/Sell: Extreme zone crosses (percentile-based). Reversion Up/Down: Cycle turning points. Osc Bullish/Bearish Cross: Zero-line crosses. Limitations Like all oscillators, DLO can lag in strong trends or produce false signals in choppy markets, use with confirmation. Percentile thresholds adapt over time but may vary by asset volatility. Not a standalone system; always combine with risk management.
Pine Script® インジケーター
GainzAlgoの投稿
15
ZION Momentum Flow [wjdtks255]■ Overview: Visualizing Market Sentiment Velocity The ZION Momentum Flow is a high-precision oscillator designed to visualize the underlying energy shifts within price action. It functions by neutralizing standard momentum noise and highlighting the pure velocity of market sentiment. ■ Key Analytic Features Energy Gradient Columns: Instead of a simple line, this script uses color-coded columns to show the intensity of the trend. Bright colors indicate high-conviction "surge" zones. Smoothing Algorithm: By integrating a smoothing EMA on the core RSI derivative, it provides a stable signal that filters out market "hiccups." Surge Detection: The integrated threshold lines (+15/-15) help traders identify when momentum has reached a critical mass for a potential breakout or breakdown. ■ How to Interpret Bullish Surge: Columns turn Bright Green as they cross the +15 level. Bearish Surge: Columns turn Bright Red as they cross the -15 level. Momentum Exhaustion: Watch for columns returning toward the Zero Baseline as a sign of trend cooling.
Pine Script® インジケーター
wjdtks255の投稿
ZION Trend Strike [wjdtks255]■ Overview: Strategic Trend Strike System The ZION Trend Strike is a high-performance trend-following indicator that synchronizes price action with momentum velocity. It is designed to identify "Strike Zones" where trend direction and institutional momentum converge for high-probability entries. ■ Technical Methodology ZION Momentum Oscillator: A proprietary EMA-smoothed RSI derivative that centers around a zero-baseline. It measures the internal strength of the trend rather than just price movement. Dynamic Trend Guide: A 20-period EMA that changes color based on momentum bias, serving as a visual filter to prevent trading against the primary trend. Strike Signals: "BUY" and "SELL" labels are triggered only when price behavior and the ZION Oscillator show a synchronized breakout or breakdown. ■ How to Use Long Entry: Look for the BUY label when the Dynamic Trend Guide turns green. Short Entry: Look for the SELL label when the Dynamic Trend Guide turns red.
Pine Script® インジケーター
wjdtks255の投稿
Trend Cloud with Institutional Volume Filter [wjdtks255]■ Overview: High-Conviction Trend Identification The Trend Cloud with Institutional Volume Filter is a specialized trend-following system that solves the "whipsaw" problem of traditional volatility indicators. It integrates ATR-based volatility bands with a strict volume conviction filter. ■ The "Conviction" Logic Many trend indicators fail during low-volume consolidation. This script introduces an Institutional Volume Filter that mandates a signal must be accompanied by volume exceeding its 20-period SMA. This ensures that "BUY" or "SELL" labels only appear when there is significant market participation. ■ Visual Dashboard Components Momentum Cloud: A dynamic color-coded zone that illustrates the strength and direction of the current trend regime. Institutional Labels: Clear "BUY" and "SELL" markers provided in a label format for instant readability.
Pine Script® インジケーター
wjdtks255の投稿
1
True Baseline Median SuperTrendTrue Baseline Median SuperTrend (TBM SuperTrend) | MisinkoMaster True Baseline Median SuperTrend is a volatility-adaptive trend indicator designed to refine traditional SuperTrend logic by introducing a volatility-filtered baseline and median-based smoothing techniques. Instead of relying on a fixed midpoint calculation, TBM SuperTrend dynamically constructs its baseline from structurally significant price observations, then applies layered median smoothing to reduce noise while preserving trend integrity. The result is a cleaner, more stable trend-following tool that reacts to meaningful shifts in volatility and directional pressure without excessive whipsaws. Core Philosophy Most SuperTrend-style indicators anchor their bands to a simple price midpoint and apply an ATR-based offset. While effective, this approach can be overly sensitive during volatile consolidations. TBM SuperTrend improves this structure by: • Building a volatility-qualified baseline • Filtering insignificant price movements • Applying median smoothing instead of simple averaging • Retaining ATR-based adaptive band distance This creates a trend structure that prioritizes meaningful price expansion over random noise. Key Features Volatility-qualified baseline construction Median-smoothed upper and lower bands ATR-based adaptive volatility envelope Dynamic trend state detection Automatic candle coloring Clear long and short transition labels Reduced whipsaw behavior compared to standard SuperTrend Works across intraday and higher timeframes Designed for trend continuation and breakout frameworks How It Works (Conceptual) The indicator operates in three structural layers: Volatility Measurement Market volatility is assessed using an ATR-based structure. Baseline Construction Instead of averaging all recent prices, the script filters price samples based on volatility conditions. Only structurally relevant bars contribute to the baseline calculation. This ensures that the baseline reflects meaningful movement rather than passive drift. Median Smoothing Both the volatility-adjusted bands and the baseline structure undergo median smoothing. Median smoothing is less sensitive to outliers than standard averaging, which helps stabilize the trend line during erratic price spikes. After the adaptive bands are constructed, price interaction with those bands determines directional bias: • Price closing above the upper threshold confirms bullish trend state • Price closing below the lower threshold confirms bearish trend state Internal implementation details remain proprietary in the protected version. Trend Logic Explained Bullish State When price maintains strength above the adaptive upper boundary, the indicator confirms a long bias. The trailing structure shifts beneath price, acting as dynamic support. Bearish State When price closes below the adaptive lower boundary, the indicator confirms a short bias. The trailing structure shifts above price, acting as dynamic resistance. State transitions occur only when decisive boundary breaks happen, helping reduce false flips. Visual Components Trend Lines Only the active directional band is displayed, reducing clutter and emphasizing current bias. Shaded Volatility Zone A filled region between price and the active band visually highlights trend dominance. Long / Short Labels Clear on-chart labels mark confirmed trend transitions. Candle Coloring Price candles automatically reflect current trend state for immediate visual recognition. Inputs Overview Source Defines the price series used for baseline construction. ATR Length Controls the volatility lookback period. True Baseline Length Determines the window used for constructing the volatility-qualified baseline. Factor Adjusts the volatility multiplier that expands or contracts the adaptive bands. Median Period Controls the median smoothing strength applied to the bands. Lower values increase responsiveness. Higher values improve stability and reduce noise. Why Median Smoothing Matters Traditional smoothing methods (like EMA or SMA) can be distorted by sharp price spikes. Median-based smoothing reduces the impact of extreme values, making TBM SuperTrend particularly effective in: • Crypto markets • High-volatility equities • News-driven instruments • Lower timeframe trading This improves structural consistency during sudden volatility expansions. Best Use Cases Trend-following systems Breakout confirmation Pullback entries within established trends Trailing stop framework Directional bias filtering Volatility-adaptive strategy design Parameter Tuning Guidance Shorter ATR Length → Faster adaptation → More sensitivity → Suitable for intraday trading Longer ATR Length → Smoother volatility structure → Better for swing trading Higher Factor → Wider bands → Fewer signals → Stronger trend confirmation Lower Factor → Tighter bands → Earlier entries → More reversals Longer Median Period → Smoother band structure → Reduced whipsaws Shorter Median Period → Faster reaction → More sensitivity to shifts Practical Strategy Integration Use TBM SuperTrend as: • Primary directional filter • Trailing stop mechanism • Confirmation layer for breakout systems • Bias alignment tool across multiple timeframes It performs best when combined with momentum confirmation or volume expansion tools. Summary True Baseline Median SuperTrend enhances traditional SuperTrend logic by introducing volatility-qualified baseline construction and median smoothing for structural stability. The result is a cleaner, more adaptive trend tool that prioritizes meaningful price movement while minimizing noise. It is well suited for traders seeking a disciplined, volatility-aware trend framework that remains robust across changing market conditions.
Pine Script® インジケーター
MisinkoMasterの投稿
11
Tema RSI Return + Trend + Impulse FilterTEMA 9 RSI Return + Trend & Impulse Filter This indicator combines Triple EMA momentum, RSI-style normalization, slope confirmation, and ATR-based impulse filtering to produce structured, non-repainting trade signals. It is designed for traders who want disciplined entries aligned with trend strength and volatility expansion. 🔍 Core Logic Structure • TEMA (Triple EMA) for responsive trend detection • Slope confirmation to validate directional bias • Normalized oscillator (0–100 scale) for return-from-extreme logic • Upper & lower band re-entry structure • ATR impulse filter to confirm candle strength • Confirmed-bar logic (no repainting signals) 🧠 Signal Flow Oscillator reaches extreme level Market structure aligns with TEMA slope Impulse candle confirms volatility expansion Signal prints on confirmed bar close This layered filtering reduces weak reversals and low-momentum entries. ⚙ Recommended Usage • Lower timeframes (M1 / M5) • Gold (XAUUSD) • Major Forex pairs • High volatility trading sessions This script is intended for analytical and educational purposes only. Risk management remains the trader’s responsibility. Custom Pine Script development & indicator-to-strategy conversion available via profile
Pine Script® インジケーター
yower_Pinescriptの投稿
Delta Ladder Order Flow [UAlgo]Delta Ladder Order Flow is an overlay order flow visualizer that builds a per bar delta ladder using lower timeframe candles as an intrabar proxy. For each recent bar, the script pulls the underlying lower timeframe open, high, low, close, and volume arrays, then distributes volume into discrete price buckets. Each bucket accumulates estimated buy volume and sell volume, producing a ladder that resembles a footprint style view. The display focuses on three core outputs: A delta heatmap ladder where each price level is colored by net delta dominance A Point of Control highlight that marks the highest total volume level inside the bar A stacked imbalance detector that scans diagonally across levels to identify aggressive one sided participation and optionally projects that stack forward The system is designed with stability controls for real world chart conditions. It includes dynamic scaling to prevent excessive level counts on high range bars, object budgeting through bars to draw limits, and text filtering to reduce clutter. 🔹 Features 1) Intrabar Resolution via Lower Timeframe Data The ladder is constructed using request.security_lower_tf. You select an Intrabar Resolution timeframe that must be lower than the chart timeframe. The script then receives arrays of LTF candles for each chart bar and uses them as a proxy for footprint style aggregation. This approach provides a practical order flow approximation on TradingView charts without requiring native tick level data. 2) Ladder Aggregation with Tick Size Multiplier Price levels are aggregated using the symbol mintick multiplied by a user multiplier. Increasing the multiplier produces thicker ladder steps and fewer levels. Decreasing it produces finer granularity but increases the number of boxes drawn. This control is critical for balancing detail versus performance across different symbols and volatility regimes. 3) Dynamic Scaling to Prevent High Range Bar Overload A single volatile bar can contain too many price steps if the granularity is too fine. To prevent crashes, the script estimates how many steps would be required for the bar and increases the effective step size when the raw step count exceeds Max Levels per Bar. This keeps rendering stable even during high volatility events while still maintaining a consistent ladder representation. 4) Buy, Sell, and Neutral Volume Attribution Each LTF candle’s direction is inferred from its open and close: Close above open is treated as buy side volume Close below open is treated as sell side volume Close equal open is treated as neutral and split evenly between buy and sell Volume is then distributed across the price buckets covered by the LTF candle range so that wide candles spread their influence across multiple levels. 5) Delta Heatmap Ladder with Intensity Scaling Each price bucket computes delta as buy volume minus sell volume and total volume as the sum of both. Ladder cells are colored positive or negative based on delta sign, and transparency is scaled by how dominant the delta is relative to the maximum total volume level inside that bar. This yields a compact heatmap where strong imbalances visually stand out. A square root curve is applied to intensity to improve mid tone visibility without making everything fully opaque. 6) Point of Control Highlight The ladder tracks the price level with the highest total volume and marks it as the Point of Control. When enabled, the POC row uses a dedicated border color and a stronger border width so the acceptance anchor is immediately visible. 7) Stacked Imbalance Detection and Projection The script can detect stacked diagonal imbalances. It compares volume across adjacent price levels using a diagonal logic similar to footprint tools: Bullish diagonal checks buy volume at a level versus sell volume at the level below Bearish diagonal checks sell volume at a level versus buy volume at the level above An imbalance requires the winning side to exceed the losing side by the configured Imbalance Ratio and also exceed a minimum volume threshold to filter low volume noise. When consecutive imbalanced levels reach the Stacked Levels count, the stack is marked and optionally extended forward as a zone. Stack members also override normal heatmap coloring and are rendered more solid for emphasis. 8) Clean Visual Controls Several options support readability: Bars to Draw limits workload and object count Show Delta Values can be toggled on or off Min Delta to Show Text filters small prints Ladder Width percent controls how wide the ladder is relative to the bar space Text size can be adjusted for different chart zoom levels Box outline can be hidden by default for a cleaner footprint aesthetic 🔹 Calculations 1) Intrabar data acquisition (lower timeframe arrays) The script requests arrays of LTF OHLCV values for each chart bar using request.security_lower_tf. ltf_open = request.security_lower_tf(syminfo.tickerid, tf_input, open) ltf_close = request.security_lower_tf(syminfo.tickerid, tf_input, close) ltf_high = request.security_lower_tf(syminfo.tickerid, tf_input, high) ltf_low = request.security_lower_tf(syminfo.tickerid, tf_input, low) ltf_vol = request.security_lower_tf(syminfo.tickerid, tf_input, volume) These arrays contain the lower timeframe candles that make up each chart bar. Each chart bar index has its own embedded array. 2) Base tick step (bucket size control) Bucket size starts from mintick multiplied by Tick Size Multiplier. var float base_tick_step = syminfo.mintick * tick_size_mult This is the baseline price increment used to build the ladder levels. 3) Last bar execution model (performance design) The script only builds and draws ladders when barstate.islast is true. It then reconstructs the last N bars using an index offset. if barstate.islast int start_idx = math.max(0, bar_index - bars_to_draw + 1) for i = start_idx to bar_index int offset = bar_index - i float arr_o = ltf_open float arr_c = ltf_close float arr_h = ltf_high float arr_l = ltf_low float arr_v = ltf_vol This design dramatically reduces CPU and memory load compared to updating every bar. 4) Dynamic scaling per bar (anti crash protection) For each bar, the script estimates how many price steps would be needed using the current bucket size. If that count exceeds Max Levels per Bar, it increases the step size only for that bar. float bar_h = high float bar_l = low float bar_range = bar_h - bar_l float raw_steps = bar_range / base_tick_step int scaler = 1 if raw_steps > max_levels_per_bar scaler := int(math.ceil(raw_steps / max_levels_per_bar)) float current_tick_step = base_tick_step * scaler Result: Calm bars use fine granularity High range bars are automatically compressed into fewer buckets 5) LTF candle direction classification (buy, sell, neutral) Each LTF candle is classified using its open and close. Neutral candles split volume evenly. bool is_buy = c > o bool is_sell = c < o bool is_neutral = c == o This is a heuristic proxy for aggressor side. It is not true bid ask data. 6) Align LTF candle range to bucket grid The candle low and high are rounded to the current tick step so bucket prices align cleanly. float low_aligned = math.round(l / current_tick_step) * current_tick_step float high_aligned = math.round(h / current_tick_step) * current_tick_step 7) Step counting and volume per step The script computes how many bucket levels the candle touches and divides volume equally across them. int steps = int(math.round((high_aligned - low_aligned) / current_tick_step)) + 1 if steps > 500 steps := 500 float vol_per_step = v / steps This means wide candles distribute volume across more ladder cells, while tight candles concentrate volume into fewer cells. 8) Writing volume into the ladder map (PriceLevel storage) Each chart bar owns a DeltaLadder with a map of price to PriceLevel. Each PriceLevel stores buy and sell volume. Volume is added step by step. type PriceLevel float price float buy_vol = 0.0 float sell_vol = 0.0 type DeltaLadder int bar_idx map levels float min_price = 10000000.0 float max_price = 0.0 float max_vol_level = 0.0 float poc_price = na float poc_vol = 0.0 The add method updates volumes and also tracks max volume and POC: method add_volume(DeltaLadder this, float price, float vol, bool is_buy, bool is_neutral) => if not this.levels.contains(price) this.levels.put(price, PriceLevel.new(price)) PriceLevel lvl = this.levels.get(price) if is_neutral lvl.buy_vol += vol * 0.5 lvl.sell_vol += vol * 0.5 else if is_buy lvl.buy_vol += vol else lvl.sell_vol += vol float t = lvl.total() if t > this.max_vol_level this.max_vol_level := t if t > this.poc_vol this.poc_vol := t this.poc_price := price The main loop calls this method for each bucket level touched by each LTF candle: for p = 0 to steps - 1 float level_price = low_aligned + (p * current_tick_step) ladder.add_volume(level_price, vol_per_step, is_buy, is_neutral) 9) Delta and total volume formulas Delta and total are defined as methods on PriceLevel. method delta(PriceLevel this) => this.buy_vol - this.sell_vol method total(PriceLevel this) => this.buy_vol + this.sell_vol These values drive both coloring and POC selection. 10) Stacked imbalance detection (diagonal footprint logic) Prices are sorted so neighbor comparisons are correct. A stack_map stores whether each price belongs to a bullish or bearish stacked run. float prices = ladder.levels.keys() array.sort(prices) map stack_map = map.new() Diagonal comparisons: Bullish diagonal compares BuyVol at level i with SellVol at level below i minus 1 Bearish diagonal compares SellVol at level i with BuyVol at level above i plus 1 Bullish check includes a zero handling rule: if i > 0 float p_below = array.get(prices, i-1) PriceLevel lvl_below = ladder.levels.get(p_below) if lvl_below.sell_vol == 0 if lvl.buy_vol > imb_min_vol direction := 1 else if lvl.buy_vol > lvl_below.sell_vol * imb_ratio and lvl.buy_vol > imb_min_vol direction := 1 Bearish check includes symmetric logic: if i < array.size(prices) - 1 float p_above = array.get(prices, i+1) PriceLevel lvl_above = ladder.levels.get(p_above) if lvl_above.buy_vol == 0 if lvl.sell_vol > imb_min_vol direction := -1 else if lvl.sell_vol > lvl_above.buy_vol * imb_ratio and lvl.sell_vol > imb_min_vol direction := -1 Runs are tracked and only accepted if the number of consecutive levels meets the stacked requirement: if math.abs(i - run_start_idx) >= stack_count for k = run_start_idx to i - 1 stack_map.put(array.get(prices, k), run_dir) The script also draws a projected zone for the detected stack band: box.new(right_time, p_top + current_tick_step/2, right_time + 1000 * 60 * 60 * 24, p_bot - current_tick_step/2, xloc=xloc.bar_time, border_width=0, bgcolor=color.new(c_stack, 85), extend=extend.right) 11) Heatmap intensity and transparency mapping For each price level, intensity is computed as abs(delta) relative to the maximum total volume level in the bar, then curved and mapped into transparency. float intensity = ladder.max_vol_level > 0 ? math.abs(delta) / ladder.max_vol_level : 0 intensity := math.min(intensity, 1.0) float curved_intensity = math.sqrt(intensity) float transp = 97 - (curved_intensity * 57) Stacked members force stronger visibility: if stack_map.contains(p) intensity := 1.0 transp := 30 12) POC marking in the drawing pass POC is detected during volume accumulation, then used in rendering to upgrade the border style for that cell. bool is_poc = show_poc and (p == ladder.poc_price) color border_c = is_poc ? col_poc : col_outline int border_w = is_poc ? 2 : 1 13) Delta text rendering filter Text labels are optional and can be filtered by a minimum absolute delta threshold. if show_text and math.abs(delta) >= text_threshold string txt = str.tostring(delta, format.volume) label.new(int((left_time + right_time)/2), p, txt, xloc=xloc.bar_time, style=label.style_none, textcolor=txt_col, size=text_size)
Pine Script® インジケーター
UAlgoの投稿
Accumulation Zone Profiles [UAlgo]Accumulation Zone Profiles is an overlay indicator that detects low volatility accumulation phases and automatically builds a fixed range volume profile for each confirmed zone. The script uses a statistical volatility model based on log returns, identifies periods where volatility compresses into an unusually quiet regime, then verifies that price action remains sufficiently sideways before confirming the zone. When a zone is confirmed, the indicator draws two complementary views: A highlighted accumulation range on the chart A fixed range volume profile drawn to the right of the zone, including Point of Control and Value Area levels The intent is to turn consolidation into a structured map. Instead of treating ranges as vague rectangles, the script assigns a volume distribution to the range so you can see where the market accepted price, where it rejected price, and which levels are most likely to matter during expansion. 🔹 Features 1) Statistical Accumulation Detection Using Log Volatility The detection engine starts from log returns r = ln(C / C ) and builds an EWMA based volatility estimate. Volatility is converted into log space and evaluated with a rolling distribution model. A z score determines whether the current volatility is unusually low relative to its own history. Zones begin when the z score falls below a configurable entry threshold and they end after volatility recovers above an exit threshold for a configurable number of confirmation bars. 2) Sideways Quality Filter With Trend Score Not every low volatility period is true accumulation. The script measures drift using a trend score defined as: absolute sum of returns divided by sum of absolute returns Lower values indicate more rotation and less directional drift. A maximum trend score filter ensures zones remain meaningfully sideways before a profile is created. 3) Non Repainting Option Using Confirmed Bars When enabled, the system only updates on confirmed bars. This reduces repainting behavior and makes zone start and zone end decisions more stable for live trading workflows. 4) Fixed Range Volume Profile Per Zone For each confirmed accumulation zone, the script builds a histogram of volume across a user selected number of price rows. Each bar’s volume is distributed into bins according to how much of that candle range overlaps each bin. This produces a true fixed range profile for the zone. The profile is drawn to the right of the zone so it does not cover price action. 5) Point of Control and Value Area Levels The highest volume row is treated as the Point of Control. Value Area High and Value Area Low are computed by expanding outward from POC until a target percent of total volume is captured. This creates a practical acceptance framework inside the zone. Optional plotting allows: Highlighting the POC row Drawing VAH and VAL lines Drawing zone boundary guides Showing an information label that summarizes zone statistics 6) Tick Alignment For Clean Levels If enabled, the zone range, bin step size, and derived levels are aligned to the instrument tick size. This produces cleaner price levels and reduces floating point noise in labels and lines. 7) Object Budget Management Volume profiles use many boxes. The script computes an effective rows value based on the number of profiles you choose to keep, then limits total box usage so you are less likely to hit platform object limits. Older profiles are deleted automatically when new ones are created. 8) Alerts Two alerts are available: Accumulation Zone Started Accumulation Zone Confirmed and Profile Created This supports automation such as watchlist monitoring and breakout preparation. 🔹 Calculations 1) Log Return and EWMA Variance The script defines log return as ln(C / C ) and uses an EWMA of squared returns as a variance proxy. Alpha for EWMA: f_alpha(int len) => 2.0 / (len + 1.0) Log return: lr = math.log(close / close ) lr := na(close ) or close == 0.0 ? 0.0 : lr EWMA variance and volatility: alphaFast = f_alpha(fastLen) var float ewmaVarR = na ewmaVarR := na(ewmaVarR ) ? lr * lr : alphaFast * (lr * lr) + (1.0 - alphaFast) * ewmaVarR vol = math.sqrt(math.max(ewmaVarR, 0.0)) 2) Log Volatility Distribution and z Score Volatility is transformed into log space to stabilize distribution behavior. The script maintains EWMA estimates of mean and second moment, then computes standard deviation and z score. eps = 1e-10 logVol = math.log(vol + eps) alphaDist = f_alpha(distLen) var float m1 = na var float m2 = na m1 := na(m1 ) ? logVol : alphaDist * logVol + (1.0 - alphaDist) * m1 m2 := na(m2 ) ? logVol * logVol : alphaDist * (logVol * logVol) + (1.0 - alphaDist) * m2 sigma = math.sqrt(math.max(m2 - m1 * m1, eps)) z = (logVol - m1) / sigma Interpretation: Negative z means volatility is below its typical level More negative z means stronger compression 3) Zone Start and Zone End Conditions Entry and exit logic uses the z score relative to thresholds: Start when z is less than or equal to minus Enter Threshold End when z is greater than or equal to minus Exit Threshold for Exit Confirm Bars lowNow = not na(z) and z <= -enterZ highNow = not na(z) and z >= -exitZ Exit confirmation counter: zb.exitCount := highNow ? zb.exitCount + 1 : 0 bool exitByConfirm = zb.exitCount >= exitBars A maximum zone duration also forces closure: bool exitByMax = zb.barCount() >= maxZoneBars If exit is triggered via confirmation bars, the script removes those last bars from the zone before profiling to avoid contaminating the accumulation range with the volatility recovery phase. 4) Sideways Drift Score Filter During zone building, returns are accumulated: sumR is the signed drift sumAbsR is total movement magnitude Trend score: method driftScore(ZoneBuilder this) => math.abs(this.sumR) / math.max(this.sumAbsR, 1e-10) A zone is accepted only if: Bar count is at least Min Zone Bars Drift score is less than or equal to Max Trend Score 5) Profile Range and Row Step Once accepted, the profile range is built from the min low and max high of the zone. The range is optionally aligned to tick. Step size equals range divided by rows, with optional tick alignment: float stepRaw = (hi - lo) / rows float step = stepRaw if alignTick step := math.max(syminfo.mintick, f_roundToTick(stepRaw)) 6) Volume Histogram Construction For each bar in the zone, volume is assigned into bins. If the candle range is very small, volume goes to a single nearest bin. Otherwise, volume is distributed proportionally by overlap between candle range and each bin range. Core proportional distribution logic: float overlap = math.max(0.0, math.min(bh, binHi) - math.max(bl, binLo)) if overlap > 0 float frac = overlap / br array.set(binVol, b, array.get(binVol, b) + bv * frac) This produces binVol, a per row volume distribution. 7) POC Calculation POC is the index of the maximum bin volume. POC price is the center of that row. if v > maxV maxV := v pocIdx := b float poc = lo + (pocIdx + 0.5) * step 8) Value Area Computation Value Area is derived by expanding outward from POC until the cumulative volume reaches Value Area percent of total volume. Target volume: float target = totV * (valueAreaPct / 100.0) Expand left and right by choosing the side with higher next volume until the target is met. This creates a contiguous value area band. VAL and VAH mapping to prices: float valP = lo + left * step float vahP = lo + (right + 1) * step 9) Rendering Logic Zone highlight is drawn directly over the accumulation period using a box with configurable fill and border transparency. The volume profile is drawn as a stack of boxes to the right of the zone. Each row width is proportional to row volume relative to max row volume. Transparency is mapped so high volume rows appear more prominent. POC row can be highlighted using a dedicated color and transparency configuration. VAH and VAL can be drawn as horizontal lines across the profile region, and optional boundary lines can mark the start and end of the detected zone. 10) Profile Retention and Cleanup Profiles are stored in an array. When the number of stored profiles exceeds Keep Last Profiles, the oldest profile is deleted and all of its objects are removed. This keeps the chart responsive and prevents reaching the platform maximum object counts.
Pine Script® インジケーター
UAlgoの投稿
Price-Volume-Volatility Cube [LuxAlgo]The Price-Volume-Volatility Cube indicator provides a 3D visualization of the relationship between price, volume, and volatility using a Cabinet Oblique projection. By mapping these three critical market dimensions onto a normalized 3D space, the tool allows traders to observe how market conditions evolve and cluster within a specific lookback window. 🔶 USAGE The indicator renders a wireframe cube on the chart that represents the boundaries of the selected lookback period. Each data point within that period is plotted as a colored sphere inside the cube, creating a "cloud" that reveals the character of recent price action. 🔹 The 3D Axes The cube uses three distinct axes to position data points: Volume (X-Axis): Represents the relative volume of the bar. Points further to the right indicate higher relative volume. Volatility (Y-Axis): Represents the True Range (TR) of the bar, projected as depth. Points appearing "deeper" in the cube indicate higher volatility. Price (Z-Axis): Represents the closing price. Points higher up in the cube indicate prices closer to the period's high, while lower points represent prices near the period's low. 🔹 Interpreting the Data Path The current bar is highlighted with projection lines that connect its position to the floor and the individual axes. This helps you identify if the current market state is an outlier (e.g., high price, high volume, low volatility) or if it is sitting within a common cluster. The colors of the points transition from red (near the period low) to green (near the period high), providing an immediate visual cue for price location regardless of the cube's orientation. 🔶 DETAILS The script utilizes a Cabinet Oblique projection to transform 3D coordinates into 2D screen space. This specific projection preserves the proportions of the X and Z axes while scaling the Y (depth) axis by half at a 45-degree angle to maintain visual clarity. To maintain a consistent visual experience, the indicator automatically calculates the vertical height based on the Cube Base Width . This ensures the visualization maintains a perfect 1:1:1 aspect ratio, keeping the geometry as a true cube regardless of the user's horizontal scaling. Additionally, the vertical position of the cube is automatically handled to ensure the visualization remains centered and visible within the indicator pane. 🔹 Normalization To ensure the data fits perfectly within the cube, all values are normalized between 0 and 1 based on the minimum and maximum values found within the user-defined lookback period. This means the cube always represents the relative "range" of behavior over that specific window of time. 🔶 SETTINGS 🔹 Cube Settings Lookback Period: Determines the number of bars used to calculate the min/max values for normalization and the number of points rendered inside the cube. 🔹 Visuals Cube Base Width (Bars): Controls the horizontal scale of the cube in chart bars and automatically determines the height to maintain a 1:1:1 aspect ratio. 🔹 Position Horizontal Offset (Bars): Moves the cube left or right relative to the last bar.
Pine Script® インジケーター
LuxAlgoの投稿
2
Multi-Horizon Volatility Waterfall [LuxAlgo]The Multi-Horizon Volatility Waterfall indicator is a quantitative tool that visualizes market volatility as a multi-layered spectrum across ten distinct time horizons. By normalizing Average True Range (ATR) using percentile ranking, the script identifies volatility clusters and regime shifts, providing a comprehensive "heat map" of market expansion and compression directly on the price chart and in a dedicated oscillator pane. 🔶 USAGE The indicator provides a holistic view of volatility by stacking different lookback periods—from "Fast" (micro-bursts) to "Slow" (macro-shifts). This allows traders to observe how volatility "flows" through different timeframes, often signaling the inception of major trends before they are reflected in price action. 🔹 The Volatility Waterfall (Oscillator Pane) The bottom pane features ten horizontal ribbons representing different volatility horizons. Hot (Red): Indicates that current volatility is in the highest percentiles relative to its recent history for that specific horizon. Cold (Blue): Indicates a compression phase where volatility is historically low. Aggregate Line: A central line representing the average "heat" across all ten horizons, serving as a primary gauge for the overall market regime. 🔹 Main Chart Visuals The script projects its findings onto the main price chart through three primary features: Gradient Candles: When enabled, candles are colored based on the aggregate volatility heat, allowing for immediate identification of "hot" price action. Expansion Glow: A dynamic background highlight that "pulses" and fades based on the intensity of volatility expansion. The glow becomes more opaque as the market enters extreme expansion (Aggregate Heat > 70%). Pro Dashboard: A real-time data table providing the exact Aggregate Heat percentage, a Regime Classifier (Expansion, Neutral, or Compression), and the Fast/Slow Ratio. 🔶 HOW TO USE The Multi-Horizon Volatility Waterfall can be used to identify high-probability trading environments based on the "state" of market volatility. Identifying Squeeze Breakouts: Look for periods where all ten ribbons in the waterfall are "Cold" (Blue). This indicates a deep volatility compression across all time horizons. A sudden shift to "Hot" (Red) in the top (Fast) ribbons often precedes a powerful breakout. Trend Confirmation: In a trending market, volatility should ideally remain in the "Neutral" to "Hot" range. If price continues to move but the Waterfall turns "Cold" across the board, it may suggest the trend is losing participation and entering a distribution or consolidation phase. Volatility Clusters: When the Aggregate Heat exceeds 70%, the "Expansion Glow" appears on the main chart. This signifies a high-intensity market environment. Traders can use this to adjust risk management, as higher volatility typically requires wider stop-losses but offers greater reward potential. Mean Reversion: Extreme "Hot" readings across all ribbons (a full red waterfall) can sometimes signal an exhausted move. If price reaches a key resistance level while the Waterfall is at maximum heat, it may indicate a climax followed by a reversal or a period of sideways "cooling." 🔶 DETAILS The core methodology of the Waterfall is based on Percentile Rank Normalization . Standard volatility measures like ATR are difficult to compare across different assets or timeframes because their absolute values vary. By converting ATR into a percentile rank (0-100%) over a long-term lookback (e.g., 200 bars), the indicator creates a standardized "Heat" metric. Vertical Alignment: When all ten horizons turn red simultaneously, it indicates a "Volatility Cluster." This suggests that the expansion is occurring across all time horizons, often preceding a high-conviction breakout. Volatility Flow: Traders can watch for heat starting at the "Fast" (top) ribbons and moving down toward the "Slow" (bottom) ribbons. This "Waterfall" effect suggests that a short-term momentum burst is successfully transitioning into a sustained structural trend. 🔶 SETTINGS 🔹 Main Settings Base Horizon Step: The multiplier used to define the 10 horizons. If set to 10, the horizons will range from 10 to 100 periods. Percentile Lookback: The historical window used to determine the percentile rank of the current volatility. Smoothing: Applies an EMA to the volatility heat to reduce noise and provide a cleaner visual flow. 🔹 Visualization Cold/Hot Colors: Customizes the gradient colors for low and high volatility states. Color Candles by Volatility Heat: Toggles the gradient candle coloring on the main chart. Max Glow Intensity (%): Controls the maximum brightness of the background expansion glow to prevent it from overpowering the price action. 🔹 Dashboard Show Dashboard: Toggles the visibility of the real-time data table. Position/Size: Adjusts the location and scale of the dashboard on the chart interface.
Pine Script® インジケーター
LuxAlgoの投稿
Mean Deviation Trend [BackQuant]Mean Deviation Trend Overview Mean Deviation Trend is a structure-based trend and regime indicator that measures directional pressure as the market’s sustained deviation from a moving “mean,” then uses that pressure to drive an adaptive band , dynamic coloring, and a level engine that marks deviation peak extremes after momentum fades. Most trend tools start with direction, for example slope or MA cross, then try to estimate strength later. This script does the reverse: It first quantifies how far price is displaced from a central mean in volatility-adjusted units . It then smooths and accumulates that deviation to determine trend direction and conviction . Finally it converts conviction into a band that tightens when pressure is strong and widens when pressure is weak. The result is a single framework that blends: A mean anchor (EMA). A signed deviation engine normalized by ATR. A conviction score based on sustained deviation. An adaptive band that behaves like dynamic support/resistance. A “deviation peak” level system that plants levels at extremes after the push fades. Optional glow, fills, candle coloring, and flip markers. Core concept: deviation from mean as trend fuel A trend is not just “price up” or “price down.” A trend is a persistent imbalance where price spends time displaced from fair value and keeps re-asserting that displacement. This indicator treats the mean as a moving fair value proxy, and it measures how aggressively price is departing from it. Key idea: If price stays above the mean and that displacement is sustained, bullish pressure is dominant. If price stays below the mean and that displacement is sustained, bearish pressure is dominant. If price keeps snapping back and deviation cannot sustain, regime is weak and uncertainty is high. This is why the script doesn’t rely on a single moment like a cross. It cares about persistence . Mean anchor (the “center of gravity”) The mean is defined as an EMA of close: mean = EMA(close, meanLen) Why EMA: It responds faster than SMA to regime changes. It provides a stable anchor without overreacting to single bars. The mean line is not just a moving average here, it is the reference line that deviation is measured against. Everything downstream depends on the mean being a consistent “center.” Volatility normalization (why ATR is essential here) Raw distance from mean is meaningless across volatility regimes. A $200 deviation on BTC might be noise one week and huge another week. To fix this, the script normalizes deviation by ATR: atr = ATR(14) rawDev = (close - mean) / atr Interpretation: rawDev is “how many ATR units price is away from the mean.” This makes deviation comparable across timeframes and volatility states. This is critical because it turns the indicator into a dimensionless pressure metric rather than a price-distance tool. Deviation smoothing (instantaneous pressure vs noisy pressure) Instantaneous deviation can spike on one candle and mean nothing. So the script applies EMA smoothing to raw deviation: devSmooth = EMA(rawDev, devLen) What this does: Reduces single-bar spikes. Keeps the sign and general magnitude of displacement. Creates a cleaner “pressure line” that responds but does not jitter. This is the first stage of filtering: “Are we meaningfully deviating, or just wicking?” Deviation accumulation (turning pressure into conviction) This is the part that makes the indicator behave like a trend conviction model rather than a simple oscillator. The script computes: cumDev = SMA(devSmooth, devAccum) Even though it’s coded as an SMA, conceptually it behaves like a rolling accumulation of the deviation signal: If devSmooth stays positive for multiple bars, cumDev rises and stays positive. If devSmooth stays negative for multiple bars, cumDev drops and stays negative. If devSmooth flips sign repeatedly, cumDev compresses toward zero. This is the key “persistence detector.” It converts short-term deviation into a medium-term conviction read. Trend direction and flips Trend direction is derived purely from the sign of cumulative deviation: tDir = cumDev > 0 ? +1 : -1 flip = tDir != tDir Interpretation: Bull regime means the market’s sustained deviation is above the mean (pressure up). Bear regime means sustained deviation is below the mean (pressure down). A flip marks a regime transition where the sustained bias changes sign. This is intentionally simple because all the complexity is in how cumDev is built. Measuring conviction: devNorm (adaptive strength scale) The script measures absolute conviction: devAbs = abs(cumDev) Then it normalizes it relative to a rolling peak: devHigh = highest(devAbs, 80) devNorm = devHigh > 0 ? min(devAbs / devHigh, 1) : 0 Meaning: devNorm is a 0..1 strength scale. 0 means current conviction is tiny relative to recent extremes. 1 means conviction is at the strongest level seen in the last ~80 bars. This is not a z-score, it’s a “relative-to-recent-peak” normalization. That matters because it makes the band behavior adapt to each instrument’s recent character, not a fixed threshold system. Adaptive band logic (tight when confident, wide when uncertain) The band is built to behave differently depending on conviction. When conviction is strong, the band should hug price and act like a close structural guide. When conviction is weak, the band should widen and stop pretending it is precise. This is done by interpolating between two ATR multipliers: bandTight = ATR multiplier when devNorm is high bandWide = ATR multiplier when devNorm is low bandMult = bandWide - devNorm * (bandWide - bandTight) bandW = atr * bandMult Interpretation: devNorm near 1 → bandMult approaches bandTight → band width shrinks. devNorm near 0 → bandMult approaches bandWide → band width expands. So the band width is not arbitrary. It is a direct function of trend conviction. Active band placement (trend-aware support/resistance) The “active band” is placed on the opposite side of the mean depending on direction: If bullish: activeBand = mean - bandW If bearish: activeBand = mean + bandW So in bullish regimes, the band behaves like a dynamic support zone beneath the mean. In bearish regimes, it behaves like dynamic resistance above the mean. Then it is smoothed: activeBand = EMA(activeBand, 3) This prevents the band from stepping too harshly when ATR shifts. Outer band (secondary structure reference) A second band is created at half width on the opposite side: bull: outerBand = mean + bandW * 0.5 bear: outerBand = mean - bandW * 0.5 Then smoothed again. This outer line is not the main “stop band,” it is more of an additional structure marker to show where the mean plus/minus partial deviation zone sits. It can help visually gauge whether price is extended relative to the mean structure while still in the same regime. Color system (strength-aware gradient) The trend color is not binary. It is strength-weighted: If bullish, devNorm drives a gradient from a faint bull tint to full bull. If bearish, devNorm drives a gradient from a faint bear tint to full bear. This gives you an immediate read: Bright strong color = conviction high. Faded color = conviction low, regime fragile. It also ties into the glow and fill so the whole visual language matches the same underlying “pressure” variable. Deviation peak level engine (how the script plants levels) This indicator includes a separate mechanism that marks important extremes after a strong deviation push fades. The idea is: When trend pressure peaks and then collapses, the extreme price printed at peak deviation often becomes a reaction level later. This is similar in spirit to: exhaustion extremes, climactic deviation points, distribution/accumulation turning zones, but the script formalizes it using the deviation engine. 1) Track the strongest deviation peak The script stores a running peak: peakDev: maximum devAbs seen since last reset peakPrice: the extreme price at that peak (high for bull, low for bear) peakDir: direction at peak peakBar: bar index of peak When devAbs prints a new high, it updates those values. 2) Define “fade” (momentum has cooled) A fade event triggers when: peakDev is meaningfully large (peakDev > 0.3) current devAbs drops below a fraction of the peak: devAbs < peakDev * fadeThr fadeThr is the key user control. Lower fadeThr requires a deeper drop from peak before planting a level. What “fade” means in practice: A strong push happened (deviation expanded). That push is no longer active (deviation contracted). So the extreme created during the push is now “locked in” as a candidate level. 3) Plant a level at the extreme When faded: A dashed horizontal line is created at peakPrice. The line is projected forward (bar_index + 60). It is stored in an array with direction and retest state. It also respects maxLvls by deleting the oldest levels to avoid clutter. 4) Maintain levels and delete invalid ones Each bar, levels are checked: If price breaks far beyond the level (by about 2 ATR in the wrong direction), the level is deleted. That “broken” rule is a pragmatic invalidation filter. If price rips through a former deviation extreme by a large margin, the level is no longer acting like a meaningful reaction zone. 5) Detect retests and mark them A retest is detected when: close is within ~0.25 ATR of the level, and two bars ago price was not near it (distance > 0.5 ATR), and the level hasn’t already been marked as retested. When that happens: A diamond marker is printed (◆) above or below depending on approach. The level is flagged as retested so it won’t spam markers. So levels are not just static drawings. They have state: naked vs retested, and they get culled if invalidated. Glow system (volatility-scaled aesthetic, strength-scaled intensity) Glow is not random decoration here. Its width scales with devNorm: glowMult = 0.4 + devNorm * 1.2 glowW = atr * 0.08 * glowMult So in strong trends: Glow band expands. The mean core visually “radiates” more. In weak trends: Glow shrinks and becomes less prominent. The glow is built using multiple invisible plots above and below the mean, then layered fills with different transparencies. It creates a soft gradient aura around the mean that encodes strength. Band fill and line break behavior The active band is plotted with plot.style_linebr and forced to break on flips: bandBrk = flip ? na : activeBand This prevents the band from drawing a misleading connecting line across a regime change. It visually resets when direction flips, which matters because the band swaps sides of the mean when regime changes. Fill is drawn between: the active band line and hl2 (mid-price reference) So you get a shaded zone that reflects the current regime color and strength. Candles and flip labels Candles can be colored by the same strength-weighted regime color, which makes the entire chart consistent. On flips: Bull flip prints ▲ at the low. Bear flip prints ▼ at the high. These are regime markers, not “entry signals” by default. They simply identify when the cumulative deviation sign changed. How to read this indicator in practice 1) Regime and conviction Direction comes from cumDev sign. Conviction comes from devNorm intensity. Bright color + stable band on one side means strong sustained pressure. Faded color + widening band means weak sustained pressure and higher uncertainty. 2) Using the active band as structure In a bullish regime, activeBand is below mean and can behave like: dynamic support, risk boundary, trend “line in the sand.” In bearish regime, it flips above mean and acts like dynamic resistance. Because the band widens when conviction is low, it naturally tells you “do not treat this as a tight stop zone when the trend is weak.” 3) Using deviation peak levels Peak levels represent exhaustion extremes after a strong deviation impulse faded: If price returns to a naked level, that area can act as a reaction zone. Once retested, the script marks it and treats it as less “special.” If price breaks it by a wide margin, the script removes it as invalid. This level engine is best viewed as “structural memory of deviation events,” not generic support/resistance. 4) Extreme deviation alert devNorm > 0.85 means the current sustained deviation is near the strongest seen recently. That’s useful for: identifying trend climax states, detecting when continuation is strong but risk of snapback rises, flagging conditions where mean reversion pressure is building. It does not guarantee reversal, it flags “stretch.” Inputs and what they actually change Mean Length (meanLen) Controls the anchor responsiveness: Lower = mean follows price more closely, deviation shrinks, more frequent flips. Higher = mean is slower, deviation grows, trend regimes last longer. Deviation Smoothing (devLen) Controls how noisy the deviation signal is: Lower = faster response, more jitter. Higher = smoother pressure, slower flips. Deviation Accumulation (devAccum) Controls persistence requirement: Lower = trend conviction reacts quickly but can whipsaw. Higher = requires sustained deviation, fewer flips, more confirmation. Band Tight / Band Wide These define the band behavior range: bandTight: how close the band gets when conviction is strong. bandWide: how far it drifts when conviction is weak. If you want the band to behave more like a stop guide, reduce bandWide. If you want it to act more like a regime boundary, increase bandWide. Fade Threshold + Max Levels These shape the level engine: fadeThr lower = requires bigger cooling before planting levels (fewer, more meaningful). fadeThr higher = plants levels earlier (more levels, more noise). maxLvls controls clutter and historical depth. Alerts (what they represent) Dev Bull / Dev Bear: regime flips, cumulative deviation changed sign. Dev Faded: a deviation peak cooled enough to plant a level. Extreme Dev: sustained deviation is near local maximum, stretch condition. Summary Mean Deviation Trend models trend as sustained, volatility-normalized displacement from a mean rather than simple direction. It smooths and accumulates signed deviation to extract regime and conviction, then converts that conviction into an adaptive ATR band that tightens when pressure is strong and widens when pressure is weak. On top of that, it tracks deviation peak extremes and plants forward levels only after deviation fades, creating a structured map of “where trend impulses peaked” and how price reacts when those zones are revisited.
Pine Script® インジケーター
BackQuantの投稿
MTF Trend Panel [Dow/SMC]■ 概要 複数の時間足（マルチタイムフレーム：MTF）のトレンド方向をひとつのチャート上で一目で確認できるパネル型インジケーターです。トレンドの判定基準として、「ダウ理論（Dow）」と「スマートマネーコンセプト（SMC）」の2種類のロジックからお好みのものを選択できます。 ■ 主な特徴 2種類のトレンド判定ロジック: Dow（ダウ理論モード）: 直近2つのピボットハイ（高値）とピボットロー（安値）を比較し、高値・安値の切り上げで「上昇トレンド」、切り下げで「下降トレンド」と判定します。 SMC（スマートマネーコンセプトモード）: ローソク足の終値が直近のピボットハイ、またはピボットローをブレイク（BOS / CHoCH）した方向に基づいてトレンドを判定します。 最大6つの時間足を監視: 月足、週足、日足、4時間足、1時間足、15分足など、監視したい時間足を最大6つまで任意に設定可能です。 カスタマイズ可能なUI: パネルの表示位置（四隅）や、文字のサイズをチャート環境に合わせて自由に変更できます。 ■ 設定項目 判定ロジック設定: ロジックの切り替え（Dow / SMC）、ピボット判定に用いる左右のバー数（Left/Right Bars） タイムフレーム設定: パネルに表示する6つの時間足（Timeframe 1 ～ 6） パネル設定: 表示位置（Top Right, Bottom Leftなど）、文字サイズ ---------------------------------------------------------------------------------------- ■ Overview This indicator provides a multi-timeframe (MTF) panel that allows you to check the current trend direction across up to 6 different timeframes at a glance. You can seamlessly switch between two distinct logic modes for trend detection: Dow Theory and Smart Money Concepts (SMC). ■ Key Features Two Trend Detection Logics: Dow Mode: Uses classic Dow Theory. It compares the last two Pivot Highs and Pivot Lows. An uptrend is identified by higher highs and higher lows, while a downtrend is identified by lower highs and lower lows. SMC Mode: Based on Smart Money Concepts. The trend is determined by the closing price breaking the most recent Pivot High or Pivot Low (BOS / CHoCH). Monitor Up to 6 Timeframes: Fully customizable. You can set up to 6 timeframes to monitor simultaneously (e.g., 1M, 1W, D, 4H, 1H, 15m). Customizable UI: Easily adjust the panel's position on the chart (top-right, bottom-left, etc.) and text size to fit your trading setup. ■ Settings Logic Settings: Choose between 'Dow' and 'SMC'. Adjust Left/Right bars for Pivot calculations. Timeframe Settings: Select 6 specific timeframes to display on the panel. Panel Settings: Select screen position and text size.
Pine Script® インジケーター
MGtrader12358の投稿
Donchian Ribbon [UAlgo]Donchian Ribbon is a chart-overlay Donchian Channel ribbon that visualizes multiple lookback lengths at the same time. Instead of plotting a single Donchian Channel, the script builds a fixed stack of channels that increase in length and blends them into a clean, layered ribbon above and below price using progressive fills. The goal is to make market structure and regime easier to read without clutter: - When the ribbon expands and stays orderly (fast boundaries leading, slow boundaries following), it often reflects sustained range expansion and more directional flow. - When the ribbon compresses and bands overlap frequently, it typically reflects consolidation, rotational behavior, and reduced clarity. - The slowest channel provides the structural “outer frame” of the market’s recent range, while shorter channels react first and show how quickly the range is shifting. This indicator is designed as a context tool. It does not attempt to “predict” direction by itself, but it gives a high-quality visual map of evolving highs/lows across multiple sensitivities so you can align entries, risk, and expectations with the current regime. 🔹 Features 1) Multi-Length Donchian Stack (Ribbon Engine) The script constructs several Donchian Channels from a Base Length and a Step Length. Each band represents a different sensitivity level: - Fast bands respond quickly to recent highs and lows. - Slow bands respond more conservatively and define broader containment. By stacking these lengths together, you can see short-term responsiveness and higher-level structure simultaneously. 2) Two-Sided Ribbon (Upper and Lower Envelopes) The indicator visualizes both sides of the Donchian framework: - Upper ribbon is built from stacked Donchian highs (highest highs per length). - Lower ribbon is built from stacked Donchian lows (lowest lows per length). This keeps interpretation intuitive: price pressing into the upper ribbon suggests pressure toward recent highs, while leaning into the lower ribbon suggests pressure toward recent lows. 3) Gradient Depth via Layered Fills (Clean Charts) Instead of drawing many lines, the script fills the space between consecutive bands. Transparency is gradually adjusted from the fast band to the slow band, producing a smooth depth effect that stays readable even on busy charts. Intermediate plots are intentionally hidden so the ribbon remains the main visual output. 4) Regime Readability (Expansion vs Compression) Because each band has a different lookback length, the ribbon naturally communicates volatility and state: - Expansion: spacing between fast and slow bands increases, commonly seen in stronger directional phases. - Compression: spacing collapses and bands cluster, commonly seen in ranges, pauses, or choppy rotation. This helps you quickly decide whether to treat price action as breakout-oriented, trend-continuation, or mean-reverting. 5) Trend Baseline Reference (Slow Midpoint) A baseline is plotted using the midpoint of the slowest channel. This provides a stable reference that helps you judge whether price is operating in the upper or lower half of the broader range structure. 🔹 Calculations 1) Donchian High, Low, and Midpoint Per Band Each Donchian band is computed from its own length: - High = highest high over the lookback length - Low = lowest low over the lookback length - Mid = average of High and Low id.high := ta.highest(id.length) id.low := ta.lowest(id.length) id.mid := math.avg(id.high, id.low) 2) Length Sequencing (Base Length + Step Length) The indicator creates a fixed number of bands. Lengths are built as: - Band 1: base_length - Band 2: base_length + step_length - Band 3: base_length + 2 * step_length - ... - Final band: base_length + (ribbon_count - 1) * step_length This yields a consistent progression from fast to slow sensitivity. int len = base_length + (i * step_length) channels.push(DonchianChannel.new(len)) 3) Iterative Updates with Arrays and Methods All bands are stored in an array and updated every bar using a unified method call. This ensures every band follows identical rules and makes the logic scalable and maintainable. for dc in channels dc.update() 4) Upper Ribbon Construction (Layered Fills Between Highs) The upper ribbon is created by filling between consecutive Donchian highs. Each layer uses the same upper tone with progressively stronger visibility toward the slow band. fill(p_fast_high, p_mid1_high, color.new(col_upper, 90), "Ribbon Upper 1") fill(p_mid1_high, p_mid2_high, color.new(col_upper, 80), "Ribbon Upper 2") fill(p_mid2_high, p_mid3_high, color.new(col_upper, 70), "Ribbon Upper 3") fill(p_mid3_high, p_slow_high, color.new(col_upper, 60), "Ribbon Upper 4") 5) Lower Ribbon Construction (Layered Fills Between Lows) The lower ribbon is created by filling between consecutive Donchian lows with the lower tone, again using progressive transparency. fill(p_fast_low, p_mid1_low, color.new(col_lower, 90), "Ribbon Lower 1") fill(p_mid1_low, p_mid2_low, color.new(col_lower, 80), "Ribbon Lower 2") fill(p_mid2_low, p_mid3_low, color.new(col_lower, 70), "Ribbon Lower 3") fill(p_mid3_low, p_slow_low, color.new(col_lower, 60), "Ribbon Lower 4") 6) Trend Baseline (Slow Midpoint) The baseline is the midpoint of the slowest Donchian band, plotted as a stable center reference for the broadest range framework. plot(dc_slow.mid, "Trend Baseline", color = color.from_gradient(0.5, 0, 1, col_lower, col_upper), linewidth = 2) 7) Visualization Choice (Hidden Internals, Visible Structure) To keep charts clean, most intermediate plots are hidden and the ribbon fills do the heavy lifting visually, while the slow boundaries remain visible as the outer frame. p_fast_high = plot(dc_fast.high, "Fast High", color = color.new(col_upper, 80), display = display.none) p_fast_low = plot(dc_fast.low, "Fast Low", color = color.new(col_lower, 80), display = display.none) p_slow_high = plot(dc_slow.high, "Slow High", color = color.new(col_upper, 50)) p_slow_low = plot(dc_slow.low, "Slow Low", color = color.new(col_lower, 50))
Pine Script® インジケーター
UAlgoの投稿
Rolling Liquidity Clusters Channel [LuxAlgo]The Rolling Liquidity Clusters Channel indicator identifies dynamic support and resistance zones by calculating levels that maximize candle wick touches while strictly avoiding intersections with candle bodies within a rolling window. This tool provides a unique perspective on liquidity clusters, highlighting price levels where historical rejection is most concentrated without being invalidated by price "closing" through them. 🔶 USAGE The indicator plots a channel consisting of an Upper Level, a Lower Level, and a Mid Level. The space between these levels is filled with a vertical gradient to visually represent the strength of the liquidity zone. Upper Level (Red): Represents a resistance zone where the most upper wicks are concentrated without any candle body in the lookback window crossing above it. Lower Level (Green): Represents a support zone where the most lower wicks are concentrated without any candle body in the lookback window crossing below it. Mid Level (Orange): Represents the equilibrium or average of the current liquidity channel. Traders can use these levels to identify potential reversal points or areas of price consolidation. A breakout from the channel might indicate a shift in market structure as price moves beyond the most inclusive "non-broken" wick levels. 🔶 DETAILS The script employs a specific constraint logic to ensure the levels represent true "untouched" liquidity: 🔹 Body-Crossing Constraint Before identifying the wick touches, the script calculates the highest candle body high and lowest candle body low within the user-defined window. The resulting levels are guaranteed to stay outside of this "body zone," ensuring that the plotted levels represent prices that the market reached but failed to sustain via a close. 🔹 Maximizing Touches To find the most significant level, the algorithm searches for the most inclusive price point. For the upper level, it identifies the lowest "high" that remains above all candle bodies. For the lower level, it identifies the highest "low" that remains below all candle bodies. This mathematical approach effectively finds the level where the most price action "clusters" via wicks. 🔹 Vertical Gradient Fills The visual style uses a vertical gradient fill. The upper half fades from 90% transparency at the Upper Level (Red) to 100% transparency at the Mid Level. The lower half follows a similar logic, fading from the Lower Level (Green) toward the center. This creates a "glow" effect, emphasizing the outer boundaries where liquidity is highest. 🔶 SETTINGS Window Size: The number of bars used for the rolling calculation. A larger window creates more stable, long-term levels, while a smaller window adapts quickly to recent price action. Upper Level: Customize the color of the upper resistance level and its associated gradient fill. Lower Level: Customize the color of the lower support level and its associated gradient fill. Mid Level: Customize the color of the central equilibrium line.
Pine Script® インジケーター
LuxAlgoの投稿
Evasive SuperTrend [LuxAlgo]The Evasive SuperTrend indicator provides a modernized approach to trend following by implementing a unique "evasive" logic designed to reduce premature trend flips during periods of high market noise and consolidation. Unlike the traditional SuperTrend which can only move closer to the price (or stay flat), this tool identifies when price action gets too close to the volatility band and "evades" the price by pushing the band further away, effectively giving the current trend more breathing room. 🔶 USAGE The indicator can be used similarly to a standard SuperTrend to identify trend direction and potential trailing stop levels, but with added intelligence regarding market noise. 🔹 Identifying Trend and Noise Solid Line: Indicates a standard trend phase where the price is maintaining a healthy distance from the volatility band. Dotted Line: Indicates the "Evasive" mode is active. This occurs when price action enters a "Noise Zone," causing the indicator to proactively push the band away to prevent a false breakout. Gradient Fill: The background fill provides a visual heat map of the trend strength relative to the source price, with higher transparency indicating proximity to a potential trend flip. 🔹 Trading Signals Users can look for "BULL" and "BEAR" labels which mark the points where price successfully penetrates the evasive band. Because the band actively retreats during noise, a trend flip often carries more significance as it requires price to overcome an adaptive volatility threshold. 🔶 DETAILS The core innovation of this script is the "Noise Avoidance Logic." Standard SuperTrends are strictly monotonic (they only move up in a bull trend and down in a bear trend). This often leads to "whipsaws" where a minor price spike touches the band and flips the trend unnecessarily. The Evasive SuperTrend calculates a Noise Threshold . If the distance between the price and the band is less than this threshold (calculated in ATR units), the band is pushed back by a specified Expansion Alpha . This allows the trend to persist through choppy sideways movement that would otherwise trigger a reversal. 🔶 SETTINGS 🔹 Supertrend Settings ATR Length: Determines the lookback period for the Average True Range calculation used to set the band distance. Base Multiplier: Sets the initial distance of the band from the price. Higher values result in fewer, longer-term trend signals. 🔹 Noise Avoidance Logic Noise Threshold (xATR): Defines the "danger zone" around the band. If price enters this ATR-based range, the band begins to evade. Expansion Alpha (xATR): The distance the band moves away from the price when noise is detected. Higher values make the indicator more "stubborn" against trend changes. 🔹 Visualization Show Signal Labels: Toggles the visibility of the BULL and BEAR trend change labels. Show Gradient Fills: Toggles the dynamic background coloring between the price and the band.
Pine Script® インジケーター
LuxAlgoの投稿
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