始めましょう

Supertrend

Trend Sniper v2.5 - Haar Wavelet Edition [Jamallo]Author's Note: The previous Trend Sniper v2.5 was built around a 2-Pole Butterworth Super Smoother with Parkinson historical volatility driving the trailing stops. This edition replaces that entire core with a Maximal Overlap Discrete Wavelet Transform (MODWT) using Haar basis functions and a Vervoort ATR trailing stop . Where the Butterworth produced smooth, continuous curves, the Haar wavelet produces structural steps — only updating when true market movement exceeds the calculated noise energy floor. Same Trend Sniper framework, completely different engine under the hood. Intro Trend Sniper v2.5 - Haar Wavelet Edition the Maximal Overlap Discrete Wavelet Transform (MODWT) using Haar basis functions. The result is a structural, step-based signal line that ignores minor price fluctuations entirely and only updates when true market movement exceeds a dynamically calculated noise threshold. Combined with a Vervoort ATR trailing stop, dual SuperTrend envelopes, and KAMA midpoint, this indicator provides a complete trend-following framework built on signal processing principles rather than traditional moving average logic. Breakdown Haar Wavelet Signal Line (MODWT + Adaptive Deadband) The core of this indicator is a 5-level cascaded MODWT Haar wavelet decomposition applied to smoothed Heikin-Ashi price. At each level, price is split into a smooth coefficient (trend) and a detail coefficient (noise). The user selects a decomposition level (1–5), controlling the structural scale — from 2-bar micro-structure up to 32-bar macro-structure. An adaptive deadband then wraps the smooth coefficient: the average absolute detail energy is measured over a lookback window and scaled by a multiplier. The signal line only steps to a new value when the smooth coefficient moves beyond this noise-energy threshold. This creates the characteristic "staircase" behavior — flat holds during noise, clean steps on real moves. The signal line colors by its own step direction: bull when it steps up, bear when it steps down. Vervoort ATR Trailing Stop A Sylvain Vervoort-style trailing stop is anchored directly to the Haar wavelet signal line rather than raw price. The stop distance is calculated as ATR × multiplier. In an uptrend, the stop ratchets upward and never retreats; in a downtrend, it ratchets downward. The stop flips when price closes through it. Because it's anchored to the structural wavelet line instead of noisy price, it produces cleaner, more decisive flip points. The trailing stop uses independent CMO (Chande Momentum Oscillator) + deadband hysteresis for its coloring — it only changes color when confirmed momentum cleanly breaches the CMO threshold, preventing color flicker during consolidation. Dual SuperTrend Envelopes Two SuperTrend calculations using smoothed Heikin-Ashi ATR create the outer structure: Slow SuperTrend (default mult 9.0) — the wide envelope defining macro trend boundaries Fast SuperTrend (default mult 6.0) — combined with the signal line to create the Fast Trigger dots The Fast Trigger is the midpoint of the fast SuperTrend and the Haar signal, plotted as orange circles for quick visual reference of momentum alignment. KAMA Midpoint & 4-State Fill A Kaufman Adaptive Moving Average smooths the midpoint between the slow SuperTrend and the Haar signal. The fill between the KAMA midpoint and the signal line uses four distinct color states based on whether price is above/below the slow SuperTrend and whether the signal is above/below the fast trigger — providing an immediate visual read on trend alignment and momentum phase. End The wavelet decomposition reveals the true step-by-step nature of price movement by mathematically separating signal from noise — use it alongside your own risk management and confluence analysis. Trade the structure, not the noise.
Pine Script® インジケーター
Jamallo22の投稿
Syndicate Confluence [JOAT]Syndicate Confluence Introduction Syndicate Confluence is an open-source overlay indicator that unifies three independent analytical engines into a single spatially organized visual system. Engine 1 is an adaptive Kalman filter with a Supertrend ratchet trail — it classifies the macro directional regime and generates a triple-glow neon trail on the chart. Engine 2 is an institutional order block zone mapper — it identifies swing-pivot order blocks, classifies them by trading session, and renders them as persistent box-based zones with session-colored borders and labeled displacement ratios. Engine 3 is an HMA pressure trail paired with a custom volume-weighted MFI — it classifies each bar into bull pressure, bear pressure, or neutral states. The three-layer visual architecture ties all three engines together: an outer ATR cloud communicates the macro volatility context of the Kalman filter; a corridor fill between the Kalman Supertrend line and the HMA trail communicates whether both engines are aligned in the same direction; and a core gradient fill between the HMA trail and the candle mid-body communicates the intensity of the current pressure state. When all three layers are saturated in the same color, the confluence is at its strongest. When they are fragmented, the market is transitioning. The highest-confidence signal — the starred HC Long or HC Short label — fires only when a trail flip, Kalman direction, and order block proximity all coincide simultaneously. This triple-engine intersection is the indicator's primary setup, and the remaining visual layers exist to help traders evaluate whether conditions are building toward or away from that state. Core Concepts 1. Adaptive Kalman Regime Engine The Kalman filter maintains a running estimate and error variance. Each bar, the gain is computed as err / (err + noise), where noise = alpha * period. The estimate is updated toward close proportional to the gain, and the error variance self-adjusts — expanding when prediction is poor (high responsiveness), contracting when the filter tracks well (high smoothness). A Supertrend ratchet is applied to the Kalman value: ATR-scaled upper and lower bands drift with a direction-persistence rule — the upper band can only fall, the lower band can only rise. Direction flips when the Kalman value closes through the active band. Applying the ratchet to a Kalman-smoothed price removes the micro-fluctuations that cause excessive flips in price-based systems. 2. Session-Colored Order Block Zones When a swing pivot low is confirmed, the indicator searches back for the last bearish candle before the pivot. If the subsequent displacement exceeds ATR * dispMult, that candle becomes a bull order block. The zone is drawn at the candle's midpoint with ATR-scaled height. Zone border color is determined by the birth session: London = blue (#60a5fa), NY = pink (#f472b6), Asia = green (#34d399). The label shows type, session, displacement ratio (e.g., "▲ BULL LON 1.8x 5030.41"), and updates its x-position every bar to track the right edge of the chart. Border thickness scales with displacement ratio — zones from 2x+ displacement moves get thicker borders. 3. HMA Pressure Trail and Volume-Weighted MFI An HMA ratchet trail determines directional commitment. The custom volume-weighted MFI sums volume * hlc3 on rising bars (positive flow) and volume * hlc3 on falling bars (negative flow), normalizes with the RSI formula, and smooths with an HMA. Bull pressure is active when the trail is bullish AND the smoothed MFI exceeds the bull threshold. Bear pressure when trail is bearish AND MFI below the bear threshold. The pressure strength percentage tracks the rolling 50-bar proportion of bars spent in an active pressure state. 4. Three-Layer Visual Architecture Outer ATR Cloud: k_val ± cloudMult * ATR filled with directional color at near-full transparency — communicates macro volatility context and Kalman regime at a glance Corridor Fill: The zone between the Kalman Supertrend line and the HMA trail — fills cyan when both agree bullish, rose when both agree bearish, neutral gray when diverging. When the corridor narrows and both trails converge in the same direction, confluence is building Core Pressure Gradient: Between the HMA trail and the candle mid-body — transparent at the HMA, saturated at the body, colored by pressure state. Deep color indicates active, volume-backed directional pressure 5. Signal Hierarchy ★ HC Long / ★ HC Short: Trail flip + Kalman direction + OB proximity — the highest-confidence setup. Starred label with colored background Trail flip arrows: Triangle up/down when trail flips in Kalman direction with MFI above/below 50 — standard entry signal MFI cross-50 triangles: Small triangles on the Kalman trail when MFI crosses the 50 level in the trail direction — momentum regime shift marker TP labels: Fire when MFI reaches overbought or oversold extremes in the trail direction K▲ / K▼ labels: Mark the exact bar where the Kalman Supertrend direction flips Squeeze diamond / circle: Diamond on squeeze start, circle on squeeze release Volume impulse labels: "1.8x vol" label on high-volume directional bars above the configured multiple Proximity diamonds: Fire on the first bar where price enters the OB proximity buffer Features Adaptive Kalman Filter: Self-calibrating gain updates noise estimate each bar — faster during impulses, smoother during consolidation Supertrend Ratchet on Kalman: Direction-persistent bands applied to the filtered price — stable, low-whipsaw regime signal Triple-Layer Kalman Glow: Widths 9/5/2 with decreasing transparency create a neon halo effect on the Supertrend trail Outer ATR Volatility Cloud: Wide envelope around the Kalman value, gradient-filled by regime direction Corridor Fill (Kalman ST ↔ HMA Trail): The alignment region between both trails — fills directionally when confluent, neutral when diverging Core Pressure Gradient Fill: HMA-to-mid-body gradient colored by active pressure state Session-Colored OB Zone Borders: London blue / NY pink / Asia green borders encode session context directly in the zone visual OB Zone Labels: Type, session, displacement ratio, and price level — updated live at right chart edge ★ HC Long / HC Short Labels: Triple-confluence signal fired when trail flip, Kalman direction, and OB proximity align Trail Flip Arrows: Triangle up/down entry signals when trail flips in Kalman direction with MFI midline confirmation MFI Cross-50 Markers: Small triangles on the trail at momentum regime shifts TP Overbought/Oversold Labels: Fire at MFI extremes in trail direction K▲/K▼ Kalman Flip Labels: Pinpoint the exact bar of each Kalman regime change Squeeze Detection: Diamond on Kalman band compression start, circle on release K-Velocity Dots: Brightness-scaled dots on the trail communicating momentum acceleration Volume Impulse Labels: Ratio labels on high-volume directional bars Proximity Diamonds: Alert when price first enters the OB proximity buffer Regime Transition Circles: Fire at every Kalman regime change on the trail line Gradient Bar Coloring: Saturates with MFI intensity when Kalman and trail agree, fades to neutral otherwise 13-Row Dashboard: K-Regime, Trail, Pressure state, Zone proximity, Confluence, MFI, P-Strength %, Squeeze state, Band Width, Trend Bars, K-Velocity %, ATR 9 Alertconditions: Long/short signals, HC signals, TP signals, squeeze release, Kalman flips Input Parameters Regime Engine: Kalman Alpha: Base noise smoothing — lower = smoother, more lag (default 0.02) Kalman Beta: Error variance recovery rate (default 0.10) Kalman Period: Gain magnitude scaler (default 50) ST Factor: ATR multiplier for Supertrend bands on Kalman (default 1.5) ST ATR Length: ATR lookback for band calculation (default 10) Cloud ATR Width: Outer cloud multiplier (default 2.5) Squeeze Threshold %: Band width below this % of SMA triggers squeeze (default 80%) Zone Engine: Swing Length: Pivot confirmation lookback (default 5) OB Lookback: Bars searched for qualifying order block candle (default 20) Displacement ATR Mult: Minimum move to validate an OB (default 0.8) Zone ATR Width: Zone height as ATR fraction (default 0.75) Max Active OBs / Side: Oldest zones trimmed beyond this limit (default 8) Proximity Buffer (ATR): Approach detection radius (default 1.5) Momentum Engine: MFI Length: Volume-weighted money flow lookback (default 14) MFI Smooth: HMA smoothing on raw MFI (default 5) Trail HMA Length: HMA period for pressure trail (default 14) Trail ATR Mult: Trail band width (default 1.5) MFI Bull/Bear Thresholds: Pressure activation levels (default 58/42) Signals: TP Overbought / Oversold: MFI extremes for TP labels (default 78/22) Impulse Vol Multiplier: Volume multiple for impulse labels (default 1.5) How to Use This Indicator HC Signal Setup: The ★ HC Long / HC Short label is the primary setup. It fires when the trail flips in the Kalman direction while price is within proximity of an active order block. Enter on the labeled bar. Trail your stop at the HMA trail line. Look for the TP label or pressure state deactivation as an exit reference. Corridor Fill as Trend Quality Gauge: When the corridor between the Kalman trail and HMA trail is narrow and saturated with color, both trend systems are locked in the same direction — this is the highest-confidence trending condition. When the corridor is wide or neutral gray, the two systems are diverging — reduce size or wait for re-alignment. Reading the Signal Hierarchy: Start with the Kalman regime (K▲/K▼ label and trail color) for macro direction. Add the trail flip arrow for timing. Confirm with MFI cross-50 triangle. Check if an OB zone is nearby for HC bonus. Exit on TP label or when the corridor fill turns neutral. Squeeze Breakout Setup: When the golden diamond squeeze marker fires, the Kalman bands are compressing. Wait for the circle squeeze release marker. If the trail is aligned with the Kalman regime at release, the first trail flip after the release is a high-quality breakout entry. Indicator Limitations Order block detection requires a confirmed swing pivot, which in Pine Script v6 is offset by swingLen bars — zones are created after the fact relative to the actual pivot candle The corridor fill between the Kalman trail and HMA trail can produce wide fills on instruments with large spread between the two systems — this is informational, not a defect, but may visually dominate the chart on some timeframes HC signals require all three conditions simultaneously. On instruments with sparse order block formation, HC signals may be infrequent compared to standard trail flip arrows The volume-weighted MFI requires volume data. On instruments with unreliable volume reporting, the pressure engine may be less meaningful than on equities or futures Squeeze detection uses 80% of the 20-bar SMA as the threshold. On instruments that are persistently low-volatility, this threshold may trigger continuously — adjust the squeeze percentage parameter upward for such instruments Originality Statement This indicator is original in its three-engine confluence architecture, the corridor fill system between the Kalman Supertrend and HMA trail, and the session-colored OB zone integration with the starred HC signal. The publication is justified because: The corridor fill between the Kalman Supertrend trail and the HMA pressure trail creates a novel visual quality gauge — the width and saturation of the corridor communicates alignment strength between macro regime and near-term pressure in a single spatial layer Session-colored OB zone borders encode institutional session context directly into the zone visual without requiring a separate session indicator, making the chart self-contained for context-aware zone evaluation The HC signal requires three independent engine conditions to coincide: Kalman regime direction, trail flip timing, and OB proximity. This triple-gate structure is a more restrictive and higher-quality filter than any two-condition confluence approach The three-layer visual architecture (outer cloud, corridor fill, core pressure gradient) creates a spatially organized picture where the distance between layers communicates regime context, trail alignment, and pressure intensity at different spatial scales simultaneously The K-velocity dot brightness system embeds momentum acceleration directly into the trail visualization without requiring a separate panel — the trail itself communicates direction, state, and rate of change simultaneously Disclaimer This indicator is provided for educational and informational purposes only and does not constitute financial advice or a recommendation to buy or sell any financial instrument. Past performance of any pattern or signal does not guarantee future results. All trading involves substantial risk. Always use proper risk management and conduct your own independent analysis. — Made with passion by officialjackofalltrades
Pine Script® インジケーター
officialjackofalltradesの投稿
AG Pro HTF Bias Dashboard [AGPro Series]AG Pro HTF Bias Dashboard Overview / What it does AG Pro HTF Bias Dashboard is a higher-timeframe context tool built for traders who want a fast, structured view of directional conditions across multiple larger timeframes without crowding the chart with extra signals, zones, or decision noise. The script summarizes higher-timeframe bias in a compact dashboard and presents each selected row as Bull, Bear, or Neutral, together with a mode-specific status readout. The goal is not to predict the next candle or replace a full trade plan. The goal is to make larger-timeframe context easier to read at a glance. This indicator is designed to answer a simple but important workflow question: "What is the broader directional environment across the higher timeframes I care about right now?" Instead of forcing the user to manually flip through multiple charts and compare structure or trend conditions one by one, the dashboard keeps that information visible in a single panel. The script supports multiple bias engines so the same dashboard can be adapted to different styles of chart reading. Users can evaluate higher-timeframe context through EMA Stack alignment, confirmed Swing Structure, SuperTrend direction, or MACD Momentum agreement. This makes the tool flexible enough for trend-following traders, structure-based traders, and users who prefer momentum-style confirmation. Unlike many overlays that try to combine entries, exits, alerts, pattern detection, and signal generation inside one study, this script stays focused on one task: higher-timeframe directional context. That single-purpose design is intentional. It keeps the output clean, readable, and easier to integrate into an existing process. Unique Edge The main strength of this script is not signal generation. Its edge is structured context compression. Instead of plotting a large number of higher-timeframe elements directly on the chart, AG Pro HTF Bias Dashboard converts higher-timeframe conditions into a compact visual matrix. This makes it possible to assess multi-timeframe agreement quickly while keeping the chart itself relatively clean. A second differentiator is the ability to switch the bias engine. The dashboard is not locked to one interpretation framework. Users can work with: - EMA Stack, for ribbon-style alignment - Swing Structure, for confirmed HH/HL and LH/LL progression - SuperTrend, for ATR-based directional trend state - MACD Momentum, for momentum agreement between line, signal, and histogram Another important detail is the higher-timeframe validity filter. Rows that are not actually higher than the current chart timeframe are marked as Lower/EQ instead of being treated as valid higher-timeframe context. This helps keep the dashboard aligned with its intended purpose. The script also includes confluence logic, so the user can see not only the state of each row, but also the dominant higher-timeframe bias and how many valid rows support that direction. In practice, this helps users distinguish between broad directional agreement and mixed conditions. Methodology The dashboard can display three to five higher-timeframe rows, depending on user settings. Each row evaluates one selected timeframe and classifies it into Bull, Bear, or Neutral. Bias Mode options: 1) EMA Stack This mode evaluates directional alignment using a three-EMA structure. A bullish state requires price and the EMA ribbon to be aligned in bullish order. A bearish state requires the opposite alignment. When the full sequence is not aligned, the row can remain neutral and display a partial status such as 2/3 or 1/3 rather than forcing a directional label. 2) Swing Structure This mode uses confirmed pivot logic to read higher-timeframe structure. It looks for confirmed higher highs / higher lows or lower highs / lower lows, and then evaluates position relative to the active swing range. Because this logic depends on confirmed pivots, structure changes are naturally more selective and may appear later than faster trend models. 3) SuperTrend This mode reads directional state using an ATR-based trend framework. It is intended for users who prefer a cleaner directional state model rather than ribbon alignment. 4) MACD Momentum This mode classifies bias through agreement between the MACD line, signal line, and histogram. It is useful for traders who prefer momentum confirmation over structure or moving-average ordering. The dashboard then calculates: - the number of valid bullish rows - the number of valid bearish rows - the dominant higher-timeframe state - the confluence count across valid rows Optional chart context features are also included. Depending on settings, the script can color candles according to the active chart bias, plot the active EMA ribbon or SuperTrend on the chart, apply a subtle background tint when confluence is strong enough, and show a compact mini context tag on the chart. States / Context Output This indicator is a context dashboard, not an alert engine. It does not generate buy or sell alerts, does not mark trade entries, and does not claim to identify optimal execution points. Its outputs are state-based and contextual: - Bull - Bear - Neutral - Confluence summary - Mode-specific status text The mini chart tag, when enabled, is only a compact summary of dominant higher-timeframe direction and current confluence. It should be read as context, not as a trade instruction. Key Inputs Higher Timeframes Users can select three to five rows and define the exact higher timeframes to monitor. Bias Mode Choose between EMA Stack, Swing Structure, SuperTrend, and MACD Momentum. Engine Parameters The script exposes relevant inputs for each engine, including EMA lengths, Swing Strength, SuperTrend ATR settings, and MACD settings. HUD Controls The panel position and panel scale can be customized so the dashboard can fit different layouts and chart styles. Style Controls Users can adjust theme and directional colors for bullish, bearish, and neutral states. Chart Context Controls Optional features include candle coloring, active indicator plotting for EMA / SuperTrend, strong-confluence background tinting, mini context tag visibility, tag anchor, tag offset, and tag font size. Limitations & Transparency This script is not a prediction model. It summarizes directional context from user-selected higher-timeframe logic. Higher-timeframe tools can update only when data from those larger intervals updates. Because of that, the dashboard should be understood as a context layer rather than a real-time trigger engine. Swing Structure mode uses confirmed pivots. That means structure changes may appear later than faster directional methods, because confirmation requires completed pivot information. Neutral states do not necessarily mean the market is untradeable. They simply indicate that the selected bias engine does not currently show clear directional alignment under the chosen rules. The confluence count is a summary statistic, not a quality score. A larger number of aligned rows does not automatically mean a better trade. It only means more selected higher-timeframe rows currently point in the same direction. Rows marked Lower/EQ are excluded from valid higher-timeframe confluence because they are not above the active chart timeframe. This script is intended to support discretionary analysis and chart organization. It should be combined with the user’s own execution framework, risk model, and market understanding. Risk Disclosure This indicator is provided for analysis and educational use. It does not provide financial advice, investment advice, or guaranteed outcomes. Market conditions can change quickly, and no single indicator or dashboard can remove uncertainty from trading or investing. Users should evaluate higher-timeframe context together with price action, liquidity, volatility, risk management, and their own decision process. Past behavior, historical alignment, or current confluence does not guarantee future performance.
Pine Script® インジケーター
AGProLabsの投稿
2
Self-Aware Trend System [WillyAlgoTrader]🧠 Self-Aware Trend System (SATS) is an adaptive SuperTrend-based trend-following system that continuously measures its own operating environment through a 4-factor Trend Quality Index (TQI) and modulates band width, asymmetry, and flip logic in real time. Unlike a fixed SuperTrend — which uses the same ATR multiplier forever — SATS knows when the market is trending vs. chopping, compresses bands in clean trends to lock profit tighter, widens them in noisy conditions to avoid whipsaws, and can detect regime collapse through a "character-flip" even when price hasn't broken the band yet. Each confirmed signal comes with a full trade plan (Entry, SL, TP1/TP2/TP3 at user-defined R multiples), and the system tracks its own realized R, win rate, drawdown, and per-regime edge — building an honest, instrument-specific performance log directly on your chart. The name "Self-Aware" refers to one specific property: the indicator measures the quality of its own environment every bar and feeds that measurement back into its band width and flip conditions. It doesn't predict the future — it reacts to present conditions with mathematically defined adaptation rules. 🧩 WHY THESE COMPONENTS WORK TOGETHER A classic SuperTrend has one problem: its ATR multiplier is fixed. In a clean trending market the bands are too wide, giving back profit on every pullback. In a choppy market the bands are too tight, generating whipsaw after whipsaw. Traders try to fix this by manually switching multipliers per timeframe or per instrument — but that's guesswork. SATS chains a different approach: Market state measurement (TQI) → Non-linear band modulation → Asymmetric band widths → Character-flip detection → R-multiple trade plan → Outcome tracking → Regime-aware statistics The TQI engine measures market quality from four independent angles each bar (efficiency, volatility regime, structure, momentum persistence). The non-linear modulation translates that quality into band width — high quality compresses bands, low quality expands them, using a power curve that avoids both over-reacting to mild fluctuations and under-reacting to severe regime changes. Asymmetric bands tighten the active side (in the direction of the trend) while loosening the passive side — creating a "ratchet with leverage" that locks in profit faster than it invalidates the trend. Character-flip detection catches regime collapses (high quality → low quality) even when price hasn't broken the band — critical for exiting stale trends before they fully reverse. And performance tracking records every signal's realized R, building a real statistical picture of how the system performs on your specific instrument and timeframe. Without TQI, the bands are blind. Without asymmetry, profit-taking lags. Without character-flip, exits happen too late. Without performance tracking, you have no idea if the system has a real edge on your instrument. All four work together — each layer addresses a specific weakness of classic SuperTrend. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Trend Quality Index (TQI) — 4-factor continuous quality measurement. TQI is computed every bar as a weighted combination of four independent 0..1 factors: — 🧭 Efficiency (default weight 0.35) : Kaufman Efficiency Ratio = |close − close | / sum(|close − close |). Measures directional movement vs. total path. 1.0 = perfect straight line, 0.0 = pure noise. Default window 20 bars. — 📊 Volatility Regime (weight 0.20) : uses Volume Z-score when volume data is available (z = (volume − sma) / stdev, mapped from to ), or falls back to ATR ratio (current ATR vs. long-baseline ATR) on volume-less instruments. — 🏗️ Structure (weight 0.25) : price position within its recent range. pricePos = (close − lowest) / (highest − lowest). Then tqiStruct = |pricePos − 0.5| × 2. Trends pin price to one edge (1.0), chop oscillates around the midpoint (0.0). No ATR dependency. — ⏩ Momentum Persistence (weight 0.20) : of the last N bars, what fraction moved in the same direction as the overall window change? alignedBars / N. Default 10 bars. Final TQI = (factor1 × w1 + factor2 × w2 + factor3 × w3 + factor4 × w4) / sum(weights), clamped to 0..1. Each weight is user-configurable. 2️⃣ Non-linear band modulation with power curve. Instead of a linear "multiplier × (1 − tqi)", SATS uses a power curve: qualityDeviation = (1 − tqi)^curvePower tqiMult = 1 − qStrength + qStrength × (0.6 + 0.8 × qualityDeviation) With curvePower = 1.5 (default), mild quality drops (from 0.9 to 0.7) cause small band expansion, but severe drops (0.5 to 0.2) cause rapid expansion. This matches how traders actually think: ignore small wobbles, react strongly to clear regime changes. 3️⃣ Asymmetric band widths — ratchet with leverage. In a strong uptrend, the lower band (active, trailing price up) tightens while the upper band (passive, not used as stop) widens: activeMult = symMult × (1 − asymStrength × tqi × 0.3) passiveMult = symMult × (1 + asymStrength × tqi × 0.4) Effect: as trend quality rises, the trailing stop moves closer to price (locking profit faster) while the opposite band moves away (so an accidental pullback doesn't trigger a flip). This is the "leverage" — asymmetric response to confirmed trend strength. 4️⃣ EMA-smoothed multipliers before ratchet application. Raw TQI can spike bar-to-bar. If those spikes fed directly into the SuperTrend ratchet logic, bands would compress at a high-TQI bar and stay stuck there (SuperTrend math never loosens active bands against the trend). SATS EMA-smooths the multipliers (alpha 0.15) before ratchet application — preventing stickiness. This is the critical fix that makes adaptive SuperTrend actually work in practice. 5️⃣ Efficiency-weighted ATR. Used for band construction and SL/TP sizing (not for TQI itself, to avoid circular feedback): effATR = rawATR × (0.5 + 0.5 × ER) Clean trending volatility counts full (ER = 1.0 → effATR = rawATR). Noisy chop volatility is halved (ER = 0.0 → effATR = 0.5 × rawATR). This makes SL/TP distances proportional to "useful" volatility, not total volatility. 6️⃣ Character-flip detection with age guard. Classic SuperTrend only flips on price breaks. But a trend can die internally — quality collapses, momentum fades — before price actually breaches the band. Character-flip catches this: charFlipDown = prevTQI > 0.55 (high) AND currentTQI < 0.25 (low) AND trendAge ≥ minAge AND close < source The age guard (default 5 bars) prevents whipsaw on fresh trends — a newborn trend hasn't had time to establish quality, so early TQI noise can't kill it. After the age threshold, a quality collapse triggers an immediate flip even without price break. 7️⃣ Auto-fixed TP order. If a user accidentally sets TP1 > TP2 (or TP3 < TP2), the indicator automatically sorts them. Math: fixedMin = min(all), fixedMax = max(all), middle = sum − min − max. The three TP lines always end up in correct order on the chart regardless of user input order. 8️⃣ R-multiple trade planning with pivot-anchored SL. On each signal: — Entry = close at bar of confirmed flip — SL = min(pivot − slMult×ATR, entry − slMult×ATR) for longs (mirror for shorts) — TP1/2/3 = entry ± risk × R-multiple The SL uses whichever is further from entry — the recent pivot (if available) or a pure ATR distance. This ensures the stop always has a minimum ATR buffer regardless of how close the nearest pivot is. 9️⃣ Performance tracking with realized R accounting. Every signal is tracked bar-by-bar for TP hits, SL hits, and timeout (default 100 bars). On close-out, realized R is calculated assuming 1/3 position per TP: — TP3 hit: realized = (tp1R + tp2R + tp3R) / 3 (all three filled) — SL hit after TP1: realized = (1/3) × tp1R + (2/3) × (−1R) — SL hit after TP1+TP2: realized = (1/3) × tp1R + (1/3) × tp2R + (1/3) × (−1R) — Pure SL: realized = −1R — Timeout: realized = sum of already-hit TP portions (no penalty) Results feed a rolling buffer (up to 100 signals), which drives: — Rolling Win Rate — Rolling Avg R — Rolling drawdown (window DD) — All-time drawdown — Current and max win/loss streaks 🔟 9-cell regime edge tracking. Every completed signal is bucketed by the market regime at entry time: Efficiency bin (low/mid/high) × Volatility bin (low/normal/high) = 3×3 = 9 cells. Each cell accumulates its own EWMA of realized R. The dashboard shows the current regime's historical edge — e.g., "Trending + High Vol: +0.85R (23 trades)". This lets you see which market conditions the system actually profits in. 1️⃣1️⃣ Experimental self-calibration (off by default). When enabled, the system monitors its rolling avg R and drifts the Quality Influence parameter toward the user default if recent edge is poor (below threshold). This is explicitly marked experimental — no claim of improved results — and recommended off until validated on your instrument. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — TQI computation : Compute four factors (Efficiency, Volatility Regime, Structure, Momentum Persistence). Weight and combine into a single 0..1 value. Step 2 — ATR and effective ATR : rawATR = ta.atr(len). effATR = rawATR × (0.5 + 0.5 × ER). Step 3 — Adaptive multiplier : Apply legacy ER adaptation (optional) and non-linear TQI curve. If asymmetric bands enabled, split into active/passive multipliers. Step 4 — EMA smoothing : Smooth both multipliers with alpha 0.15 to prevent ratchet stickiness. Step 5 — SuperTrend bands : upperBand = source + upperMult × effATR. lowerBand = source − lowerMult × effATR. Ratchet logic: lower only rises, upper only falls, until a flip. Step 6 — Flip detection : Price flip (close crosses opposite band) OR character-flip (TQI collapse + age guard). On flip: reset trend age, start new segment. Step 7 — Trade plan : On confirmed flip, compute Entry/SL/TP1/TP2/TP3. Draw lines and labels. Cache the market regime (ER bin × Vol bin) for later edge attribution. Step 8 — Outcome tracking : Each bar, check active trade for TP1/TP2/TP3/SL hits and timeout. On close-out, calculate realized R, push to history buffer, update rolling stats, drawdown, streaks, and regime cell. Step 9 — Dashboard render : On last bar, render live state (Trend, TQI, regime, performance stats, TQI breakdown, regime edge). 📖 HOW TO USE 🎯 Quick start: 1. Add indicator — preset is "Auto" (adapts to your current timeframe) 2. Green line = bullish trend, red = bearish trend 3. Line transparency reflects TQI: bright = high quality, faded = low quality 4. ▲ BUY / ▼ SELL labels appear on confirmed flips 5. Entry, SL, TP1, TP2, TP3 lines drawn automatically at the signal 6. Copy levels to your exchange, let the dashboard track outcomes 👁️ Reading the chart: — 🟢 Bright green line = bullish trend with high TQI — aggressive participation — 🟢 Faded green line = bullish trend with low TQI — cautious, possible regime shift — 🔴 Bright red line = bearish trend with high TQI — 🔴 Faded red line = bearish trend with low TQI — Line flip + label = new trade signal — Dashed TP lines turning solid + "✓" = TP was hit — Score on label (e.g., "85/102") = multi-factor confluence strength 📊 Dashboard fields: — Preset: Auto-resolved (Scalping / Default / Swing / Crypto) — Trend: Bullish ▲ / Bearish ▼ — TQI: current quality index (0..1) — Q.Strength: effective Quality Influence (may drift if auto-calibration enabled) — Signal: current bar signal (BUY / SELL / —) — Regime: Trending / Mixed / Choppy + Low/Norm/High Vol — ER / RSI / Vol Z: raw filter values — TQI Components breakdown: Efficiency / Volatility / Structure / Momentum (each 0..1) — Performance section: Win Rate, Avg R, Window DD, All-Time DD, Streak W/L, Regime Edge 🔧 Tuning guide: — Too many whipsaws : increase Quality Influence (0.5–0.7), increase Structure weight, increase Base Band Width — Missing moves / signals too late : decrease Quality Influence (0.2–0.3), decrease Base Band Width, increase asymmetry — Choppy instrument : use Swing preset, enable Character-Flip, raise minAge to 10+ — Strong trending instrument : use Scalping preset, enable Asymmetric Bands with strength 0.6+ — No volume data : automatically falls back to ATR ratio for volatility regime — no action needed ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Preset : Auto / Custom / Scalping / Default / Swing / Crypto 24/7 (auto-adapts ATR, band width, ER window, RSI, SL multiplier) — ATR Length (13), Base Band Width (2.0 × ATR) 📐 Trend Quality Engine: — Enable TQI (default On) — Quality Influence (0.4): how strongly TQI compresses/expands bands — Quality Curve Power (1.5): non-linearity — Smooth Adaptive Multipliers (On): critical fix for ratchet stickiness — Asymmetric Bands (On) + Asymmetry Strength (0.5) — Efficiency-Weighted ATR (On) — Character-Flip (On) + Min Age (5) + High/Low TQI thresholds (0.55 / 0.25) — TQI factor weights : ER 0.35, Volatility 0.20, Structure 0.25, Momentum 0.20 🎯 Risk: — SL Buffer (1.5 × ATR), TP1/2/3 R-multiples (1.0 / 2.0 / 3.0), Trade Timeout (100 bars) 🤖 Self-Learning (experimental): — Auto-calibration (default Off), calibration window, bad/good R thresholds, quality step, cooldown, floor/ceiling — Reset Learning Memory button 📊 Dashboard: position, TQI breakdown toggle, performance stats toggle, score breakdown toggle 🔔 Alerts — 🟢 BUY — ticker, TF, price, TQI, score, SL, TP1, TP2, TP3 — 🔴 SELL — same payload Plain text and JSON webhook formats supported. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. SuperTrend ratchet logic is monotonic — once the trailing band moves, it cannot move back against the trend until a flip. Character-flip uses only previous-bar TQI and current-bar close, both available at bar close. — 📊 TQI is descriptive, not predictive. It measures current market quality from 4 factors — it does not forecast future price. A high TQI reading means "the market is currently behaving like a trend" — it can still fail on the next bar. — 📏 Performance stats are walk-forward, not backtested. The rolling buffer records signals as they happen, bar by bar. Drawdown, win rate, and regime edge are honest forward-looking statistics on your specific instrument and timeframe — not curve-fitted optimization results. — ⚖️ The realized R accounting assumes 1/3 position per TP . This mirrors a standard "scale out at each target" approach. Traders who hold full position to a single target should interpret the R values accordingly. — 🔄 Auto-calibration is experimental. It's off by default and should stay off until you've validated it on your specific instrument. The drift is mean-reverting (toward your user default), not profit-maximizing — no claim of improvement is made. — 🔒 The Reset Learning Memory button clears the rolling buffer, regime cells, drawdown, and streak stats. Use when changing instruments or after significant market regime shifts. — 🛠️ SATS is a decision-support and trade-planning tool , not an automated bot. It identifies trend conditions, measures environmental quality, provides structured trade plans with R-based targets, and tracks outcomes — trade decisions and execution remain yours. — 🌐 Works on all markets and timeframes. Volume-dependent features (Volume Z in TQI) auto-fall-back to ATR-based measurement when volume data is unavailable.
Pine Script® インジケーター
WillyAlgoTraderの投稿
53
SOXL Trend Surge v4.2 - Tiered Exit + BE Buffer SOXL Trend Surge v4.2 — Tiered Exit + BE Buffer SOXL Trend Surge v4.2 is a systematic trend-following strategy designed specifically for AMEX:SOXL (Direxion Daily Semiconductor Bull 3X ETF) on the 45-minute timeframe. It was built through iterative backtesting from 2017 to 2026 across 167 trades, refining entry filters, exit structure, and risk management to produce consistent results. WHY THIS COMBINATION OF INDICATORS This strategy combines four distinct components, each serving a specific and non-redundant role: The 200 EMA defines the macro trend direction. Entries are only taken when price is above this level with a minimum 0.5% buffer, filtering out entries that occur too close to the moving average where trend conviction is weak. The Supertrend indicator (Factor 3.0, ATR Period 10) acts as dynamic intrabar trend confirmation. Unlike a static moving average crossover, Supertrend adapts its sensitivity to current volatility through its ATR multiplier — tightening during low-volatility consolidation and widening during expansion. An entry is only valid when Supertrend is in bullish mode (direction = 1), meaning price has closed above the dynamic support level. ATR (Average True Range) drives all exit mechanics. Every profit target, stop level, and trailing stop is expressed as a multiple of the current ATR rather than a fixed dollar amount. This means the strategy automatically scales its exits to SOXL's current volatility — wider targets and stops during high-volatility regimes, tighter during calm periods. This is essential for a 3x leveraged ETF where daily range can vary from 2% to 20%. The VIX filter acts as a macro fear gate. SOXL's behavior during high-VIX regimes is structurally different from low-VIX trending environments. Above VIX 28, false breakouts become far more common and adverse moves become more severe. The strategy blocks all new entries when VIX exceeds 28 and force-closes any open position if VIX spikes above 35. This single filter eliminated several of the largest historical losses in backtesting. Volume confirmation ensures that entries only occur when volume is above its 20-bar SMA, confirming that institutional participation supports the move. These five components work together as a layered gate — price must satisfy all conditions simultaneously before an entry is triggered. No single indicator alone would produce these results. WHAT IS SUPERTREND Supertrend is a trend-following indicator that plots a line above or below price based on ATR-adjusted support and resistance levels. When price closes above the Supertrend line, it signals a bullish trend. When price closes below it, the trend is bearish. The Factor input controls sensitivity — a higher factor (3.0 used here) produces fewer but higher-confidence signals, which is appropriate for a leveraged ETF like SOXL where overtrading is costly. HOW THE STRATEGY ENTERS A long entry is triggered when all of the following are true simultaneously: Price is above the 200 EMA with a 0.5% buffer Supertrend is bullish (direction = 1) ATR is rising (above its 20-bar SMA), confirming expanding momentum Volume is above its 20-bar SMA VIX is below 28 Time is within the active session window (Hour 14–19 UTC, approximately 10am–3pm ET) Cooldown period has elapsed since the last exit (15 bars normally, 80 bars after a losing trade) HOW THE STRATEGY EXITS — THREE-TIER SYSTEM Rather than a single take profit, exits occur in three stages: Tier 1 — 33% of position closed at 1.5x ATR above entry. This fires on the majority of trades and locks in a guaranteed partial profit quickly. Tier 2 — Another 33% closed at 3.0x ATR above entry. This captures the larger SOXL runners that continue trending after Tier 1. Final 33% — After Tier 1 fires, a breakeven buffer stop is placed at entry price + 0.3x ATR, ensuring the strategy structurally cannot lose money once the first partial is taken. After Tier 2 fires, the final position trails with a 1.5x ATR trailing stop and has no hard cap — designed to ride SOXL's fat-tail moves, which historically reached up to 79% MFE in backtesting. ADDITIONAL RISK CONTROLS VIX Force Exit — If VIX spikes above 35 while in a trade, the full position is closed immediately. Dynamic Cooldown — After a losing trade, the strategy waits 80 bars (~3 trading days) before re-entering, preventing re-entry into a broken trend. Max Hold Stop — Any trade still open after 400 bars (~15 trading days) is closed regardless of profit or loss status, eliminating dead trades. Pyramid Add — A single add-on entry is allowed when price breaks above the prior 10-bar swing high with volume confirmation, to compound on the strongest trending moves. BACKTEST PERFORMANCE (January 2017 – April 2026) Starting capital: $500 Net profit: $1,080.33 (+216.07%) CAGR: 13.25% annualized Profit factor: 2.50 Win rate: 87.43% (146 wins, 21 losses out of 167 total trades) Sharpe ratio: 0.155 Sortino ratio: 0.194 Max drawdown (close-to-close): 18.64% Average win: $12.33 Average loss: $34.25 Commission: 0.1% per side Slippage: 1 tick per side The 167-trade sample spans multiple market regimes including the 2020 COVID crash, the 2021–2022 semiconductor cycle, the 2022 rate hike bear market, and the 2023–2025 recovery. RECOMMENDED SETTINGS EMA Length: 200 — do not lower below 150 ATR Length: 14 Tier 1 ATR Multiplier: 1.5 Tier 2 ATR Multiplier: 3.0 BE Stop Buffer: 0.3 Supertrend Factor: 3.0 Supertrend ATR Period: 10 VIX Entry Block: 28.0 VIX Force Exit: 35.0 Cooldown Bars: 15 Cooldown After Loss: 80 Max Hold Bars: 400 Volume MA Length: 20 EMA Buffer: 0.005 Timeframe: 45 minutes Symbol: AMEX:SOXL Recalculate after order is filled: Check Recalculate on every tick: Check POSITION SIZING NOTE This strategy defaults to 100% of equity per trade. This default is used in backtesting solely to measure signal quality and directional accuracy across the full equity curve. It is not a recommended live trading position size. For live trading, reduce position size to 10–25% of equity based on your own risk tolerance. Risking 100% of equity on a 3x leveraged ETF in live trading carries significant risk of severe loss. DRAWDOWN AND RISK DISCLOSURE This strategy trades SOXL, a 3x leveraged ETF. Drawdowns are larger and faster than they appear in traditional backtests. GAP RISK — SOXL can gap down 10–30% at the open during market stress events. Stop losses and VIX exits cannot protect against gap opens. The position closes at the open price, not the stop price. VIX FILTER LAG — The VIX filter uses the prior session's VIX level. An intraday flash crash will not be caught until the next bar closes. LEVERAGE DECAY — SOXL loses value over time through daily rebalancing. Extended sideways or choppy markets erode the underlying ETF even when the strategy is flat. 2022 DRAWDOWN — During the 2022 rate hike cycle, SOXL lost approximately 95% of its value. The strategy averaged -$33.74 per trade that year, drawing down approximately -$490 on a $500 starting account. Anyone trading this live in 2022 would have needed significant resilience to continue. BACKTEST LIMITATIONS — All results assume fills at bar close with 0.1% commission and 1 tick slippage. Real-world execution during volatile markets will be worse than backtested results. Past performance is not indicative of future results. This script is published for educational purposes. Nothing here constitutes financial advice.
Pine Script® ストラテジー
MrStockatonの投稿
Long-Term Trend Confluence Combo [Tiamat Crypto]This script identifies **long-term trend changes** using confluence of three powerful indicators on a higher timeframe (default: Weekly): - Moving Averages (200 + 50) - SuperTrend - Ichimoku Cloud **Key Features:** - Works exclusively with **closed HTF bars** → **zero repainting** - User-defined minimum confluence threshold (1–3 indicators) - Clear background coloring based on overall trend - Large visual labels + arrows on confirmed trend reversals - Real-time info table showing status of each component - Built-in alerts for Bull & Bear trend starts **Settings:** - Choose any higher timeframe (W, M, D, 4H...) - Enable/disable individual indicators - Adjust MA lengths, SuperTrend multiplier, Ichimoku periods **Ideal for:** Swing traders and position traders who want clean, reliable long-term trend signals without noise. **How to use:** 1. Add to your chart 2. Set Higher Timeframe (recommended: Weekly) 3. Adjust confluence threshold (2 is default and recommended) 4. Enable alerts for trend change notifications **No repainting** – all signals are based on closed higher-timeframe bars only. Created by Tiamat Crypto
Pine Script® インジケーター
TiamatCryptoの投稿
BTC Ultimate Entry System BTC Ultimate Entry System A multi-criteria scoring indicator designed for high-conviction entries on 15-minute BTCUSDT charts. Combines 7 technical factors into a single coherent signal, eliminating guesswork. How It Works The indicator scores each candle against 7 criteria: 2HR EMA bias, local EMA slope, Supertrend direction, Bollinger Band touches, VWAP alignment, volume spike confirmation, and RSI/Stochastic RSI momentum. When your threshold is met (default: 5/7), a signal fires with automatic ATR-based risk levels. The 7 Criteria 2HR EMA Bias — Higher-timeframe directional confirmation EMA 9/21 Slope — Local momentum on your chart Supertrend — Trend-following filter BB Band Touch — Reversal or bounce setup VWAP Side — Volume-weighted price alignment Vol Spike + OBV — Conviction confirmation RSI / Stoch RSI — Momentum without overbought/oversold extremes Visual Signals Full arrows (▲/▼) = Signal fired, ready to enter Dimmer dots = Watch mode, one criterion away Green/red volume backgrounds = Directional volume spike Orange backgrounds = RSI in extreme zone, use caution Auto-drawn SL/TP lines = ATR-based risk/reward Real-Time Dashboard Live text display shows current score, bias direction, all 7 criteria status, MTF context (1H/4H EMA), and entry/SL/TP levels. Customizable Adjust min score threshold, EMA lengths, Supertrend factor, Bollinger Band sensitivity, volume spike multiplier, and RSI parameters. Three trading style presets included. Best For Day traders and swing traders on BTCUSDT 15m charts seeking entries with 2–3x risk:reward and 55%+ win rate. Paper Trade First Run in paper trading mode for 10–15 signal cycles before live trading. Always confirm signals visually on the chart. Character count: ~1,100 (fits TradingView's description limit) Feel free to trim or adjust tone based on your publishing style.
Pine Script® インジケーター
Todrockの投稿
1
Machine Learning Supertrend [Aslan]Hey everyone 👋, This is an indicator I've been working on for a long time. Its not really finished yet, but I think it has huge potential. It uses a SuperTrend foundation layer with momentum filtering, volume confirmation, and, most importantly, an adaptive engine that continuously adjusts its own parameters based on recent performance. It fires entry arrows on the chart while running a background simulation to score how the current settings are performing — then quietly adjusts itself over time. Two systems run in parallel: the signal engine that produces the arrows you see, and a background test matrix that opens and closes simulated trades to feed the optimizer. The optimizer adjusts parameters, which produces better signals, which feeds back into better learning. The Core Concept At its heart this is a SuperTrend indicator — a volatility band that flips bullish or bearish as price crosses it. Signals fire either when that flip occurs (Reversal mode) or when price pushes to a new extreme within the current trend (Breakout mode). On top of this, three adaptive learning layers run continuously: Global Optimizer — rolling window of recent trade results that proposes parameter changes based on win rate, Sortino ratio, and profit factor Micro-Batch Processor — a faster layer that groups results into mini-batches for quicker adjustments Regime Grid — a 2D memory map that remembers what settings worked under similar market conditions (trend strength × volatility) and biases proposals accordingly The Most Important Settings — Start Here Band Width (Group ②) — Default: 1.4 The single most impactful setting in the entire indicator. Controls how wide the SuperTrend bands are. Lower values (1.0–1.2) create tight bands that flip often, giving more signals but more noise. Higher values (2.0–3.0) only flip on large structural moves, giving fewer but stronger signals. If your chart feels too noisy, raise this first. Higher values result in more trend following signals, while lower ones result in more contrarian signals. Lookback Window (Group ②) — Default: 30 How many bars back the indicator scans when detecting new highs and lows. Lower values (10–15) react to minor swings and fire frequently. Higher values (50–100) only react to large structural pivots. Tune this alongside Band Width — they work together. Signal Type (Group ①) — Default: Reversal Pick one and stick with it. Reversal catches turning points when a trend exhausts. Breakout rides momentum to new extremes. Reactivity / Master Dial (Group ⑥) — Default: 10 Controls how aggressively the adaptive engine responds to new information. Value of 1 = very conservative, slow to adapt, stays close to your base inputs. Value of 20 = aggressive, adapts quickly and can drift far from base settings. Start at 10 and only raise it if the market you're trading changes character frequently. Signal Spacing (Group ①) — Default: 10 Minimum bars between any two signals. Prevents clustered rapid-fire entries in choppy zones. Lower on fast timeframes (3–5 on 1-min), higher on daily charts (20–30). Group-by-Group Reference ① Signal Mode Signal Type — Reversal catches trend exhaustion flips. Breakout rides momentum to new extremes. Pick one. Require Fresh Pivot — When on, a signal only fires if price made a genuine new high/low first. Off = more signals, more noise. Signal Spacing — Minimum bars between signals. Tune per timeframe. ② Volatility Envelope Lookback Window — Bars scanned for new highs/lows. Lower = more reactive, more signals. Smoothing Period — ATR calculation period. Lower = faster reaction to volatility, more band flips. Band Width — ATR multiplier for band width. The most impactful setting in the indicator. Lower = more signals, higher = fewer stronger signals. Price Basis — Which price source feeds SuperTrend. hlcc4 (default) is smoothest, close is most reactive. True Range Mode — On = RMA-smoothed ATR (standard). Off = EMA-smoothed, faster but noisier. ③ Momentum Filter Active — Toggles RSI filtering. Off = more signals but no momentum confirmation. Length — RSI period. Lower = more volatile RSI, filter triggers more easily. Hot Zone Memory — How many bars back it checks whether RSI was overbought (for sell confirmation). Higher = more lenient. Cold Zone Memory — Same concept for oversold / buy confirmation. RSI Hot/Cold Levels (set in Group ⑬) — Overbought/oversold thresholds. Default 70/30. Wider = more signals, tighter = fewer. ④ Flow Analysis Sample Depth — Bars averaged to define "normal" volume. Surge Threshold — Volume must exceed this multiple of average to count as a surge (1.2 = 20% above average). Require Surge — When on, signals only fire with volume confirmation. Dramatically reduces count but greatly improves quality. Worth enabling. ⑤ Signal Quality Key Levels Only — Only signals at major structural turning points fire. Fewer signals — suited for swing traders. Key Level Depth — ATRs the price range must span to qualify as a key level. Only matters when Key Levels Only is on. ⑥ Master Dial Reactivity (1–20) — The meta-knob for the entire adaptive engine. Controls batch size, adaptation speed, deadband sensitivity, and EMA alpha simultaneously. If you only change one adaptive setting, change this. Micro-Batch Processing — Enables the faster mini-batch learning layer. On = quicker adaptation. Live Pressure Sensor — Tracks cumulative up/down-tick volume flow on live bars to bias the optimizer's step size. Only affects live charts. ⑦ Auto-Tune Engine Enable Auto-Tune — Master switch. Off = fixed parameters forever, just a traditional indicator. Use Background Test Matrix — Runs the 5×5 simulated trade grid. Must be on for any adaptation to occur. Lock Envelope to Base — Forces plotted bands to use your original inputs visually even if internal parameters have drifted. The signal engine always uses adapted values regardless. ⑧ Optimizer Most users don't need to touch these — the defaults work well. Step Size — Base learning rate. Higher = faster but potentially overshooting adaptation. History Depth — Rolling window of trades used to compute statistics. Higher = slower but more stable learning. Win Ceiling / Floor — Win rate thresholds that trigger parameter tightening or loosening. Momentum Smoothing — EMA blend factor for applying new proposals. Higher = faster-acting changes. Update Cooldown — Minimum bars between parameter updates. Prevents rapid oscillation. Deadband Width / Period — Proposed changes must exceed these thresholds before being applied. Filters micro-jitter. Anchor Revert Interval / Strength — Every N bars, parameters drift back toward your base inputs. Safety mechanism against unbounded drift. P&L Cap per Trade — Clips outlier trades at this USD value before learning from them. Prevents one giant win/loss from distorting statistics. ⑨ Risk Guard Max Entries / Session — Stops new signals after this many trades in a day. Session Loss Limit — Pauses trading if cumulative session P&L drops below this USD amount. Base Pause After Loss — Bars to wait after a losing trade. Prevents revenge trading. Streak Limit — Pauses after this many consecutive losses. Scale Pause by Loss Size — Larger losses trigger proportionally longer pauses. Enforce on Test Matrix — Applies risk rules to the background simulation too. Usually leave off so the matrix always has fresh data. ⑩ Context Memory (Regime Grid) Enable Regime Grid — Activates the market-context memory system. Regime / Volatility Bins — Resolution of the grid on each axis. More bins = finer resolution but slower confidence buildup per cell. Neighbor Blend Radius — How much adjacent grid cells blend into each other. Higher = smoother but less precise. Decay Half-Life — How quickly older data in a cell loses weight. Lower = faster forgetting. Max Grid Influence — How much the regime grid can dominate the global optimizer. 0.65 = up to 65% grid contribution. ⑪ Decay Traces Short-term fading trade memory that specifically monitors for large adverse moves to tighten stops. Enable Trace Buffer — Activates short-term memory. Fade Rate — Energy reduction per bar. Higher = only very recent outcomes matter. Adverse Move Threshold — MAE in ATR units above which a trade is flagged as a tail event. Guard Tighten Cap — Maximum stop tightening allowed from tail-event feedback. ⑫ State Snapshot Restore String — Paste a previously exported snapshot here to reload learned parameters and grid cells across reloads. Export Now — Toggle on to emit the current learned state as an alert string. Toggle off afterward. Import on Next Bar — Applies the Restore String on the next confirmed bar. Risk Management (TP/SL Overlay) Show TP & SL — Toggles the visual overlay. TP/SL for — Which signal type drives the levels — Contrarian, AI Supertrend, or Both. TP 1/2/3 — Take-profit multipliers relative to the stop distance. Set any to 0 to disable that level. Quick Tuning Guide Too many noisy signals? Raise Band Width → raise Lookback Window → raise Signal Spacing → enable Require Surge → enable Key Levels Only. Too few signals? Lower Band Width → lower Lookback Window → lower Signal Spacing → disable Require Surge → disable Key Levels Only → widen RSI Hot/Cold levels. Want faster adaptation? Raise Reactivity toward 15–18 → lower History Depth → lower Decay Half-Life. Want more stability? Lower Reactivity toward 3–5 → raise History Depth → raise Anchor Revert Interval. Starting fresh on a new instrument? Let the indicator run for at least 50–100 bars before evaluating, then use Export Now to save the learned state so it survives a chart reload.
Pine Script® インジケーター
Zimordの投稿
40
Hurst Exponent Adaptive Supertrend [QuantAlgo]🟢 Overview The Hurst Exponent Adaptive Supertrend identifies trending and mean-reverting market conditions by dynamically adjusting its sensitivity and band width based on the real-time persistence of price movement. It estimates the Hurst exponent through variance scaling to classify the current market regime, applies a Kalman smoother with a Hurst-scaled tracking gain to follow price with regime-appropriate responsiveness, and constructs a supertrend band whose width expands in choppy conditions and contracts in strongly trending ones. This allows traders to stay positioned through genuine trends while filtering out noise-driven whipsaws across any timeframe or instrument. 🟢 How It Works The indicator's core methodology centres on a three-layer pipeline: regime classification via the Hurst exponent, adaptive price smoothing via a Kalman filter, and dynamic band construction that responds to the estimated market state. First, the Hurst exponent is estimated by comparing short-run and long-run return variance over the configured lookback window. A lag-q variance is scaled against a lag-1 variance, and the ratio is log-transformed to produce a raw H value that is then clamped between 0 and 1: var1 = ta.variance(close - close , active_h_period) varq = ta.variance(close - close , active_h_period) H_raw = math.log(varq / math.max(var1, 1e-10)) / (2.0 * math.log(active_h_lag)) H = math.max(0.0, math.min(H_raw, 1.0)) H values above 0.5 indicate persistent, trending behaviour. Values below 0.5 indicate mean-reversion or choppiness. This reading then drives every downstream calculation. Next, a Kalman smoother tracks price using a gain that is amplified in trending regimes and suppressed in choppy ones, keeping the smoothed price line tight to momentum when it matters and sluggish when it does not: adaptive_gain = math.max(math.min(active_kf_gain * (0.5 + safeH), 0.99), 0.01) kf := na(kf ) ? close : kf + adaptive_gain * (close - kf ) Finally, the ATR-based band width is computed using a Hurst-scaled multiplier. When H is low (choppy market), the multiplier is large, widening the band to avoid false flips. When H is high (strong trend), the multiplier approaches the base value, keeping the band tight to price: h_mult = active_atr_base + active_atr_hscale * (1.0 - safeH) band = ta.atr(active_atr_len) * h_mult The supertrend logic then ratchets the upper and lower bands in the direction of the prevailing trend, flipping state only when the Kalman-smoothed price crosses the opposing band. This prevents band drift from causing premature reversals during normal consolidation: upBand := prevT == 1 ? math.max(kf - band, prevUp) : kf - band dnBand := prevT == -1 ? math.min(kf + band, prevDn) : kf + band trend := kf > prevDn ? 1 : kf < prevUp ? -1 : prevT 🟢 Signal Interpretation ▶ Bullish Trend (Supertrend Line Below Price with Bullish Color): When the Kalman-smoothed price crosses above the upper band, the indicator flips to a bullish state and the trailing line plots below price as a dynamic support level - the floor that price must decisively break before the uptrend is considered invalidated. The support level ratchets higher with each new bar, never pulling back, locking in the floor as the trend develops. In choppy regimes the band width is deliberately wide, meaning price can pull back significantly without breaching support, keeping traders positioned through noise-driven corrections that lack genuine bearish conviction. ▶ Bearish Trend (Supertrend Line Above Price with Bearish Color): When the Kalman-smoothed price crosses below the lower band, the indicator flips to a bearish state and the trailing line plots above price as a dynamic resistance level - the ceiling price must reclaim before a bullish reversal is confirmed. The resistance level ratchets lower with each new bar, tightening the ceiling as the downtrend develops. As with the bullish state, a wide band in low-H environments requires a substantial recovery move before the indicator reverses, allowing traders to hold directional bias through corrective bounces that stay within the noise threshold. 🟢 Features ▶ Preconfigured Presets: Three optimised parameter sets tailored to different trading styles and timeframes. "Default" delivers balanced trend detection for swing trading on 4-hour and daily charts, with moderate Kalman gain and band scaling suited to typical momentum cycles. "Fast Response" uses a higher tracking gain, shorter ATR window, and tighter base multiplier for intraday trading on 5-minute to 1-hour charts, producing earlier trend flips better suited to active traders. "Smooth Trend" applies a lower Kalman gain, longer ATR period, and wider band scaling for position trading on daily and weekly charts, confirming only major directional shifts with minimal false positives. ▶ Built-in Alerts: Two alert conditions enable automated monitoring of trend transitions without constant chart observation. "Bullish Trend Signal" triggers on the bar the indicator first flips to a bullish state, alerting for potential long entries. "Bearish Trend Signal" fires on the bar the indicator first confirms a bearish state, signalling potential short entries or long exits. Both alerts include the exchange, ticker, and timeframe in the alert message for immediate context. ▶ Visual Customisation: Six color presets (Classic, Aqua, Cosmic, Cyber, Neon, and Custom) accommodate different chart themes and personal preferences, with coordinated bullish and bearish color schemes applied consistently to the trend line. When the Custom preset is selected, independent color pickers for bullish and bearish states allow full manual control over the indicator's appearance.
Pine Script® インジケーター
QuantAlgoの投稿
AG Pro Supertrend Pullback Quality [AGPro Series]AG Pro Supertrend Pullback Quality OVERVIEW AG Pro Supertrend Pullback Quality is an overlay indicator built to evaluate the quality of pullbacks that occur inside an already established Supertrend direction. This script is not designed as a simple Supertrend flip tool. Instead of focusing on every direction change, it studies whether a pullback into the active Supertrend structure is orderly, controlled, and potentially supportive of trend continuation. The goal is to help users distinguish between clean retracement behavior and weaker pullbacks that may reflect noise, instability, or reduced trend quality. The indicator combines Supertrend context with a structured quality model. When price interacts with the active trend line and surrounding touch zone, the script evaluates that event using several internal dimensions such as pullback depth, line acceptance, rejection behavior, recovery efficiency, and local noise conditions. The result is summarized into a class-based readout so the chart remains visual and practical. Because of this design, the script is better understood as a continuation-quality classifier than as a traditional signal generator. It does not attempt to predict every reversal, and it does not assume that all pullbacks within trend are equal. Its main purpose is to organize pullback structure into a clearer analytical framework. UNIQUE EDGE The core difference of this script is its emphasis on pullback quality rather than trend flips. Many Supertrend-based tools are centered around directional transitions. That approach can be useful, but it also tends to compress several different market behaviors into a single yes/no event. In practice, not every trend pullback carries the same structural character. Some are shallow and noisy, some are too deep, and some interact with the trend line in a more orderly way before continuation attempts develop. AG Pro Supertrend Pullback Quality focuses on that middle layer. It studies what happens after a trend is already active and asks a more specific question: is the current pullback behaving like a controlled retracement, or is it showing weaker continuation quality? This creates a more workflow-oriented reading model. Instead of using Supertrend only as a directional switch, the script uses it as a live structural reference and grades the quality of pullback interaction around that reference. That makes the tool different from standard flip scripts, entry-only markers, and pure trend state displays. METHODOLOGY The script begins with the native Supertrend framework to define active directional context. Once a bullish or bearish state is established, a touch zone is formed around the relevant Supertrend line using ATR-based spacing. This zone is not meant to represent a guaranteed support or resistance region. It is a structured interaction area used to evaluate how price behaves during retracement. From there, the script evaluates pullback quality through several components: 1) Trend State and Age A newly flipped trend often behaves differently from a more established one. For that reason, the script includes a stabilization concept and tracks how mature the current trend leg is before weighting pullback quality. 2) Pullback Depth The retracement is measured relative to ATR and recent price structure. Pullbacks that are too shallow may carry limited informational value, while pullbacks that are too deep may indicate reduced continuation quality. The script scores depth inside a preferred operating range rather than treating all pullbacks equally. 3) Acceptance Relative to the Supertrend Line A pullback is not evaluated only by whether price touches the zone. The script also checks whether price remains positioned in a way that supports the active trend state. This helps separate cleaner acceptance behavior from weaker interaction. 4) Rejection Character When price reaches the pullback area, candle behavior matters. The script looks at rejection-style characteristics within the touch and recovery window to estimate whether price is responding constructively to the active trend reference. 5) Recovery Efficiency After contact with the zone, the script measures whether the market recovers with enough directional efficiency. Fast and orderly recovery behavior is treated differently from hesitant or weak re-expansion. 6) Noise Filter Frequent directional churn and inefficient travel can reduce the usefulness of pullback classification. The script includes a noise component so that structurally weaker environments do not receive the same quality treatment as cleaner trend conditions. These components are combined into a final score, which is then mapped into a simple class output. This makes the visual output easier to read without hiding the fact that pullback quality is multi-factor by nature. QUALITY CLASSES The final result is summarized into four broad classes: A-Class Represents the strongest pullback quality readings among the currently evaluated conditions. B-Class Represents constructive pullback quality, but with less strength than the highest tier. C-Class Represents acceptable but weaker pullback structure. Weak Represents pullback conditions that do not meet the stronger quality profile. These classes are meant to organize chart behavior, not to forecast a required outcome. They should be interpreted within broader market context, timeframe behavior, and the user’s own process. CHART ELEMENTS The script includes several visual layers: - Supertrend line for directional context - ATR-based touch zone around the active Supertrend reference - Pullback quality labels for qualified events - Compact information panel showing trend state, depth, acceptance, rejection, recovery, noise, and final status The visual design is intentionally restrained so that price remains readable. The goal is to keep the chart informative without turning the overlay into a dense signal map. SIGNALS AND ALERTS The script can generate alerts for the following event types: - Bullish Pullback Quality Ready - Bearish Pullback Quality Ready - Bullish Pullback Confirmed - Bearish Pullback Confirmed - Bullish Pullback Invalidated - Bearish Pullback Invalidated In general terms, Ready events indicate that the recent pullback has achieved the minimum quality conditions defined by the model. Confirmed events require stronger follow-through logic. Invalidated events help flag cases where a previously qualified pullback context is no longer aligned with the prior state. These alerts are designed as structured workflow checkpoints rather than standalone instructions. KEY INPUTS ATR Length Controls the ATR foundation used by the Supertrend and zone logic. Supertrend Factor Adjusts the spacing and sensitivity of the Supertrend calculation. Pullback Lookback Defines the local structure window used during pullback evaluation. Stabilization Bars After Flip Helps reduce the weight of very early post-flip behavior. Recovery Window Defines how long the script should monitor post-touch recovery behavior. Touch Zone Size and Max Line Penetration Control how the script defines valid interaction around the Supertrend line. Depth Range Inputs Allow users to define what the script should consider a more optimal pullback depth range. Ready and Confirmed Score Thresholds Allow the strictness of class qualification and alert generation to be tuned. LIMITATIONS AND TRANSPARENCY This script is an analytical classification tool. It does not know future price action, and it does not guarantee continuation after a qualified pullback. Like other trend-following frameworks, Supertrend-based structure can become less reliable during choppy or highly unstable market phases. The inclusion of a noise filter helps address that issue, but it does not remove it. The quality model is also sensitive to volatility, timeframe selection, and the interaction between ATR-based spacing and local structure. A pullback that appears constructive on one timeframe may not behave the same way on another. Users should test settings carefully and interpret results in context. Labels and classes summarize a model output. They are not a substitute for broader chart reading, risk planning, liquidity awareness, or execution discipline. RISK DISCLOSURE This script is provided for technical analysis and chart study only. It does not provide financial, investment, legal, or tax advice. Trading and investing involve risk. Past behavior, structural classification, and indicator output do not guarantee future results. Users are responsible for their own decisions, testing process, and risk management framework.
Pine Script® インジケーター
AGProLabsの投稿
1
SuperTrend Cluster (Zeiierman)█ Overview SuperTrend Cluster (Zeiierman) is a weighted multi-SuperTrend regime indicator that combines 5 differently configured SuperTrend models into a single consensus view. Instead of relying on a single ATR length and a single factor, the script builds a cluster of fast, medium, and slow SuperTrend members, measures how strongly they agree, and then plots the dominant bullish or bearish regime as a weighted trend line. The result is a cleaner trend map built from internal SuperTrend agreement rather than a single trend line. █ How It Works For each bar, the script does 3 main things: ⚪ Build 5 SuperTrend members Each member first smooths the source with the selected moving average type and length, then applies its own SuperTrend calculation using the chosen ATR Length and Factor. That gives 5 outputs: 5 direction states 5 active SuperTrend lines ⚪ Measure weighted agreement Each member contributes its assigned weight to either the bullish side or the bearish side. The script sums: Bullish cluster weight Bearish cluster weight Those are converted into: Bull Cluster Score Bear Cluster Score Cluster Strength So the final regime is based on weighted internal agreement rather than on a single member. ⚪ Filter through the Base SuperTrend Even if the cluster is bullish or bearish enough, the selected Base SuperTrend must also align with that side before the final regime flips. That means: A bullish cluster only becomes active if the base member is bullish A bearish cluster only becomes active if the base member is bearish This keeps the final output more structured and avoids cluster flips that are not confirmed by the chosen anchor member. █ How to Use Use this for trend trading with SuperTrend. Bull Cluster → look for longs. Bear Cluster → look for shorts. The % shows how strong the trend is: Higher % = stronger agreement Low % = weak/mixed market Use the weighted SuperTrend line as your guide: Above it → bullish bias Below it → bearish bias Pullbacks to the line = potential entries Best trades happen when direction and score are both strong. █ How to Read the Cluster Scores Bull Cluster Score Measures how much of the total weighted cluster is currently bullish. Bear Cluster Score Measures how much of the total weighted cluster is currently bearish. █ Settings Consensus Threshold — minimum weighted agreement required before the bullish or bearish cluster becomes valid. Base SuperTrend Index — selects which of the 5 members acts as the base reference for flip markers, label placement, and final alignment. ATR Length — controls how fast or slow the volatility band reacts. Factor — controls how far the SuperTrend line sits from the price. Smoothing — selects the moving average used before the SuperTrend is calculated. Length — controls how much smoothing is applied. Weight — controls that member’s influence inside the final weighted cluster. Key effect: Lower ATR Length + lower Factor = faster, more reactive member Higher ATR Length + higher Factor = slower, more stable member Higher Weight = greater impact on cluster direction Higher Consensus Threshold = fewer but stronger regime flips ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Pine Script® インジケーター
Zeiiermanの投稿
9
Pulse Trend Radar [WillyAlgoTrader]⦿ Pulse Trend Radar is an overlay indicator built on a Kaufman Adaptive Moving Average (KAMA) core with median-ATR volatility bands — producing an adaptive trend system that speeds up in trending markets and slows down in noise. Every trend flip generates a signal scored by a 4-factor quality engine (0–100) with letter grades (A+ through C). The indicator also detects and visualizes liquidity zones from pivot highs/lows, marks order blocks from the last opposite candle before each trend flip, tracks real-time P&L with a live trade tracker, and monitors win/loss outcomes — creating a complete trend-following framework with Smart Money context. 🧩 WHY THESE COMPONENTS WORK TOGETHER A trend indicator alone tells you direction — but not whether the entry is near a liquidity pool (where stops cluster), not whether there's institutional supply/demand nearby (order blocks), not how strong the signal is (all flips treated equally), and not how the system performs over time (no feedback). This indicator layers four analysis dimensions onto the adaptive trend core: KAMA adaptive trend + median ATR bands → Trend direction and flip detection Liquidity zones from pivots → Where stop-hunts and liquidity grabs are likely Order blocks from pre-flip candles → Where institutional supply/demand was established 4-factor signal scoring → Quality filtering — not all flips are equal Win/loss tracker → Performance feedback on this instrument and timeframe The KAMA core adapts its speed via the Efficiency Ratio — in a strong trend, the MA tracks price closely and the bands tighten, producing early signals. In choppy conditions, the MA barely moves and the bands widen, filtering out noise. The liquidity zones show where clusters of stops sit (above pivot highs, below pivot lows) — entries near these zones have higher follow-through because the liquidity grab fuels the move. The order blocks mark the institutional footprint before each trend change — these zones often act as support/resistance on retests. And the signal score combines trend strength, volume delta, efficiency acceleration, and liquidity proximity into a single quality metric — letting you prioritize A+ setups over C-grade ones. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Kaufman Adaptive Moving Average (KAMA) trend core. The KAMA computes a smoothing constant from the Efficiency Ratio: ER = |price − price | / sum(|price − price |, N) fastSc = 2 / (fastLen + 1), slowSc = 2 / (slowLen + 1) sc = (ER × (fastSc − slowSc) + slowSc)² KAMA = KAMA + sc × (price − KAMA ) When ER → 1 (pure trend): sc approaches fastSc² → KAMA tracks price tightly. When ER → 0 (pure noise): sc approaches slowSc² → KAMA barely moves. This produces a line that accelerates into trends and goes flat in chop — without any manual period switching. 2️⃣ Median ATR volatility bands. Instead of standard ATR (arithmetic mean of true ranges), the indicator uses a median of recent true ranges computed via a ring buffer over the volatility lookback (default 50 bars). The median is more robust to outlier spikes (gap bars, flash wicks) than the mean — producing smoother, more stable band widths. Bands: upper = KAMA + medianATR × multiplier, lower = KAMA − medianATR × multiplier. Trend flips when the previous bar's source price crosses beyond a band: source > upper → bullish, source < lower → bearish. The active band (lower in uptrend, upper in downtrend) is plotted as the trend line. 3️⃣ Displacement-based gradient fill. The fill between the trend line and price is not a fixed transparency — it scales with displacement: displacement = |price − KAMA| / (medianATR × multiplier). The further price stretches from KAMA, the more intense the fill becomes (transparency decreases from 95 to 60). This creates a visual "heat map" effect: faint fill near KAMA (low extension), bright fill far from KAMA (overbought/oversold). This gives immediate visual feedback on how extended the current move is without needing a separate oscillator. 4️⃣ Liquidity zone detection and sweep tracking. Pivot highs and lows (configurable lookback, default 4 bars) are marked as liquidity zones: — Above pivot highs → bearish liquidity (buy stops cluster above swing highs — potential sell-side liquidity) — Below pivot lows → bullish liquidity (sell stops cluster below swing lows — potential buy-side liquidity) Each zone extends rightward as a thin box (height = 0.15× medianATR). Zones are automatically removed when price sweeps through them (high crosses above bearish zone top, or low crosses below bullish zone bottom) — representing the liquidity grab event. Up to 15 zones per side (configurable). The signal scoring engine measures the nearest liquidity zone distance on each trend flip — entries closer to a liquidity pool receive a higher quality score because the stop-hunt provides fuel for the ensuing move. 5️⃣ Order block detection on trend flips. When the trend flips, the previous bar is marked as an order block: — Bullish flip → demand order block (the last bearish candle before the reversal — where institutional buying absorbed selling pressure) — Bearish flip → supply order block (the last bullish candle before the drop — where institutions distributed) Each OB is drawn as a box from the previous candle's high to low, extending rightward. OBs are automatically invalidated (deleted) when price closes beyond the opposite edge after 3+ bars — indicating the zone has been broken. Up to 10 OBs per side (configurable). 6️⃣ 4-factor signal quality scoring (0–100). Each trend flip is scored on four factors: — 📐 Trend strength (25 pts) : combined from ER (directional efficiency) and displacement from KAMA — measures how strong the trend is at the moment of the flip — 📊 Volume delta alignment (25 pts) : buy volume vs sell volume accumulated during the previous trend leg — bullish flip with positive volume delta scores higher (smart money was accumulating) — ⚡ Efficiency acceleration (25 pts) : current ER minus previous ER — positive acceleration means the trend is gaining momentum, not losing it — 💧 Liquidity proximity (25 pts) : distance to the nearest liquidity zone — closer = higher score (the flip is near a liquidity grab point) Grades: A+ (≥ 80), A (≥ 60), B (≥ 40), C (< 40). Signal labels display "Long A+" / "Short B" etc. 7️⃣ OBV-based volume regime detection. On Balance Volume (OBV) delta = OBV − SMA(OBV, 20). Classified as: — Accumulation : OBV delta > 0 — more volume on up-moves than down-moves (institutional buying) — Distribution : OBV delta < 0 — more volume on down-moves (institutional selling) Displayed in the dashboard with directional coloring. Auto-displays "N/A" on instruments without volume data. 8️⃣ Live trade tracker with P&L. On each signal: a dashed entry line extends horizontally, a vertical connector line tracks from entry to current price, and a P&L label updates in real-time showing percentage gain/loss. Green = profit, red = loss. Replaced on each new signal. 9️⃣ Win/loss markers + win rate tracking. Each signal is tracked as a mini-trade: entry at signal close, SL at entry ± medianATR × SL multiplier, TP1 at entry ± risk × TP1 multiplier. If TP1 is reached before SL → green ● marker at the signal bar (win). If SL is reached first → red ● marker (loss). Running win rate displayed in the dashboard as "67% (4W/2L)". 🔟 ATR-based TP/SL with hit tracking. Three take-profit levels as risk multiples (default 1.0/2.0/3.0 × risk) plus SL (default 3× medianATR from entry). Lines extend rightward with labels showing price + percentage. Labels update with ✓ on hit (green) or ✗ on SL hit (red). Active until the next signal replaces them. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — KAMA: Efficiency Ratio from configurable lookback → adaptive smoothing constant → KAMA line that accelerates in trends, goes flat in chop. Step 2 — Median ATR bands: True ranges stored in ring buffer → median computed → upper/lower bands = KAMA ± median × multiplier. Step 3 — Trend detection: Previous bar's source > upper band → bullish flip. Source < lower band → bearish flip. Active band plotted as trend line. Gradient fill scales with displacement. Step 4 — Liquidity zones: Pivot highs/lows → boxes above/below. Swept zones auto-deleted. Step 5 — Order blocks: On flip → previous candle becomes OB. Invalidated when price closes beyond opposite edge. Step 6 — Signal scoring: 4 factors (trend strength, volume delta, ER acceleration, liquidity proximity) → 0–100 → A+/A/B/C grade. Step 7 — Trade tracking: SL/TP placed, lines extend, win/loss evaluated per trade. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — adaptive trend line, liquidity zones, and order blocks appear 2. "Long A+" / "Short B" labels = trend flip signals with quality grade 3. Green/red liquidity zone boxes = where stops cluster (potential sweep targets) 4. Green/red order blocks = institutional supply/demand zones 5. SL/TP lines auto-appear with P&L tracker 👁️ Reading the chart: — 🟢 Green trend line = bullish (lower band active) — 🔴 Red trend line = bearish (upper band active) — 🟢/🔴 Gradient fill = displacement from KAMA (brighter = more extended) — 🟢 Small boxes below price = bullish liquidity zones (buy-side stops) — 🔴 Small boxes above price = bearish liquidity zones (sell-side stops) — 🟢 Larger boxes = demand order blocks (institutional buying zone) — 🔴 Larger boxes = supply order blocks (institutional selling zone) — 🟢 ● = win (TP1 reached), 🔴 ● = loss (SL hit) — Dashed line + PnL label = live trade tracker 📊 Dashboard fields: — Trend: ▲ Bullish / ▼ Bearish — Last Signal: BUY/SELL with grade — Score: 0–100 quality rating — Strength: trend strength percentage — P&L: current trade percentage — Win Rate: wins/losses with percentages — SL / TP1: current trade levels with ✓/✗ status — Vol Regime: Accumulation / Distribution — Vol Delta: buy vs sell volume percentage — Efficiency: current ER percentage 🔧 Tuning guide: — Too many signals: increase Band Multiplier (2.0–2.5) or ER Length (15–20) — Too few signals: decrease Band Multiplier (1.2–1.5) or ER Length (8–10) — Signals too late: decrease Slow Smoothing (15–20), decrease Volatility Length (20–30) — Stops too tight: increase SL ATR Multiplier (2.5–4.0) — Want only A+/A signals: monitor grades in dashboard, skip B/C entries ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Efficiency Ratio Length (default 13): KAMA lookback — higher = smoother — Fast/Slow Smoothing (default 2/30): KAMA acceleration/deceleration — Band Multiplier (default 1.8): band width in median ATR — Volatility Length (default 50): median ATR ring buffer size 🎯 SL/TP: — SL (× ATR) (default 3): stop distance in median ATR — TP1/TP2/TP3 (× risk) (default 1.0/2.0/3.0): R:R multiples 💧 Liquidity: — Pivot Lookback (default 4) / Max Zones (default 15) 🟧 Order Blocks: — Max Order Blocks (default 10) 🎨 Visual: — Gradient fill, trade tracker, win/loss markers (all toggleable) — Configurable signal label size (Tiny–Large) — Configurable dashboard font size (Tiny–Normal) — Auto / Dark / Light theme 🔔 Alerts — 🟢 BUY / 🔴 SELL — ticker, price, TF, SL, TP1, TP3 All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. Trend flips use the previous bar's source vs the previous bar's band value — the signal fires on the bar after the crossing bar closes. KAMA and band values are deterministic once a bar is confirmed. — 📐 The median ATR is more robust than standard ATR . A single flash wick or gap bar shifts the mean (standard ATR) significantly but barely affects the median. This produces more stable band widths and fewer false flips during anomalous bars. — 📊 Volume delta is accumulated within each trend leg and resets on every trend flip. It represents the buy/sell balance during the specific move — not the overall volume profile. The pre-reset delta value is used for the signal score (capturing the exiting leg's character). — 💧 Liquidity zones are automatically swept and removed when price touches them. This prevents stale zones from cluttering the chart. If a zone disappears, it means price swept through it — the liquidity has been taken. — 🟧 Order blocks are invalidated after 3+ bars if price closes beyond the opposite edge. This prevents old OBs that have clearly failed from persisting. — ⚖️ The 4-factor score uses the volume delta from before the trend reset (preResetVolDelta) — not the current leg's delta, which would be zero at the moment of the flip. This correctly captures whether the previous leg had accumulation or distribution behind it. — 📏 Win/loss tracking evaluates TP1 vs SL only — if TP1 is reached before SL, it's a win. The trade closes on the first event and is not re-evaluated. — 🛠️ This is a trend-following signal and analysis tool , not an automated trading bot. It provides adaptive trend detection, liquidity context, order block zones, and signal quality grading — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume features auto-adapt to instruments without volume data (OBV and volume delta show "N/A").
Pine Script® インジケーター
WillyAlgoTraderの投稿
7
Arc VWAP Supertrend [BOSWaves]Arc VWAP Supertrend - Momentum-Adaptive Trend Engine with VWAP-Confirmed Structure Overview Arc VWAP Supertrend is a dynamic trend-following system built around a self-accelerating arc that continuously repositions relative to price, combined with a multi-period VWAP confirmation layer that filters directional flips against prevailing volume-weighted price context. Rather than applying a static band or fixed multiplier envelope around price, the arc responds to both structural momentum and the distance between price and VWAP. As price extends further from the volume-anchored reference, the arc accelerates its chase, producing tighter trend adherence during high-conviction moves and broader breathing room during consolidation. This creates an inherently adaptive system that scales its sensitivity to actual market behaviour rather than a fixed parameter. Trend flips are assessed against session, weekly, and monthly VWAP simultaneously. Each flip is classified as confirmed when VWAP agrees with the directional change, or filtered when VWAP context conflicts with the signal, giving traders immediate visibility into the structural quality of each transition without additional overlay indicators. Conceptual Framework Arc VWAP Supertrend is built on the premise that trend-following tools should respond proportionally to the conditions they are measuring. A trend system applying identical sensitivity during a low-volatility consolidation and a high-momentum breakout treats structurally different environments as equivalent, introducing unnecessary noise in one context and unacceptable lag in the other. The arc mechanism addresses this through velocity-based acceleration. When a new trend begins, the arc is placed at a measured ATR distance from price, establishing structural breathing room. From that anchor point it begins accelerating toward price at a rate that scales with VWAP distance, moving faster when price is extended and easing when price is contained near the volume-weighted mean. Three principles shape the design: Trend direction should be confirmed by the market's own volume-weighted price context rather than a pure momentum or volatility calculation alone. Arc sensitivity should increase when price behaviour warrants it and reduce when conditions are contained. Structural flip levels should be maintained as actionable reference points only while they remain unbroken, disappearing immediately upon invalidation rather than cluttering the chart with historical noise. Theoretical Foundation The indicator combines a velocity-accumulating arc engine, ATR-scaled positioning, multi-period VWAP construction, and a distance-normalised acceleration boost into a single cohesive system. Arc velocity accumulates from zero on each new flip, increasing each smoothing interval by the base acceleration rate scaled by VWAP distance normalisation. This means the arc moves slowly immediately after a flip, when trend conviction is unproven, and progressively faster as the trend matures and price distance from VWAP grows. A slow ATR, calculated across 100 bars, provides a stable volatility reference governing initial arc placement and step size, insulating the system from transient volatility spikes that would otherwise cause erratic repositioning. VWAP is computed independently across three anchor periods: session, week, and month, each resetting cleanly at its respective boundary. The configurable filter mode allows traders to define which period must agree with a flip, whether any single agreement suffices, or whether full alignment across all three is required before a flip qualifies as confirmed. This creates a spectrum of filtering strictness suited to different trading approaches and timeframe contexts. Four systems operate in coordination: Arc Engine : Manages velocity accumulation, step progression, and directional positioning. VWAP Layer : Handles multi-period construction, distance normalisation, and flip qualification. Flip Level System : Creates, extends, and instantly removes horizontal structural reference lines. Visualisation Layer : Renders a candle gradient, cloud fill, and directional markers calibrated to current trend state. How It Works Arc VWAP Supertrend processes each bar through a structured sequence of operations: Initialisation : Occurs once sufficient ATR history exists, placing the arc below price at a configurable ATR multiple and establishing the opening trend direction. Trend State Logic : Close relative to arc governs trend state each bar, with a close below flipping to bearish and a close above flipping to bullish. Flip Processing : On each flip, the arc repositions to the opposite side of price at the full starting distance, velocity resets to zero, and a flip level is drawn at the pivot extreme. Arc Acceleration : The arc begins accelerating toward price at a rate scaled by both the base acceleration input and the current VWAP distance factor, with smoothing applied across a configurable bar window to reduce noise without introducing meaningful structural lag. VWAP Assessment : Each flip is simultaneously assessed against the selected VWAP filter, classifying transitions as confirmed where VWAP agrees with the new direction, or filtered where VWAP context conflicts. Flip Level Management : Flip levels extend rightward bar by bar until price closes through them, at which point the line and its associated label are deleted immediately. Visualisation Update : A candle gradient reflects both trend direction and distance from the arc, with colour intensity increasing as price extends further from the arc surface. A cloud fill between arc and price provides continuous directional context across the full visible chart range. Interpretation Arc VWAP Supertrend should be read as a continuous directional framework with structural quality classification at each transition point: Arc Surface : Functions as dynamic support or resistance depending on trend direction. While price holds above the arc in a bullish trend, the arc traces an accelerating floor beneath the advance. In a bearish trend the arc descends as an accelerating ceiling above price. Candle Gradient : Communicates extension relative to the arc, with bright candles indicating price is well extended from the arc and faded candles indicating proximity and potential inflection. Confirmed Flips : Carry the weight of VWAP alignment, where price is not only crossing the arc but doing so from a position consistent with the volume-weighted price context. Filtered Flips : Warrant additional validation, as VWAP is positioned counter to the new direction. Acting on filtered signals without supplementary confirmation introduces structural risk that confirmed signals do not carry. Flip Levels : Mark the price at which each directional change originated. While intact they serve as reference boundaries for re-entry, stop placement, and structural assessment. Their immediate removal on breach keeps the chart unambiguous, with only levels of ongoing structural relevance remaining visible. Cloud Fill Width : Gives a continuous visual measure of how aggressively the arc is tracking the current trend. A narrow cloud indicates close arc proximity and elevated flip risk; a wide cloud reflects a well-developed, momentum-backed trend with the arc accelerating firmly behind price. Signal Logic & Visual Cues Arc VWAP Supertrend communicates through four concurrent visual systems: Arc Line : Traces the current trend boundary, smoothed across the configured window and suppressed at flip bars to avoid visual discontinuity. Cloud Fill : Grades from the trend colour at arc proximity to full saturation at price, with transparency rendering it unobtrusive during normal trend conditions. Candle Colouring : Applies a gradient from the current trend colour at low distance to full saturation at high distance, with distance normalised against three ATR units, producing a live visualisation of trend extension directly on the price bars. Flip Markers : A pair of layered triangles, one solid and one semi-transparent glow, positioned at a configurable ATR offset from the arc to ensure visibility above candle wicks. Flip Level Lines : Extend from the pivot price rightward until breach, each accompanied by a price label whose size is configurable independently of the line style. Four alert conditions cover bullish and bearish transitions in both confirmed and filtered states, enabling automated monitoring of trend changes classified by their VWAP context. Strategy Integration Arc VWAP Supertrend applies across trend-following, momentum, and structure-based methodologies: Trailing Reference : The arc surface provides a natural trailing stop. As velocity accumulates and the arc accelerates toward price, it functions as a progressively tightening dynamic stop that responds to the maturity of the move rather than a fixed lookback period. Tiered Signal Treatment : VWAP confirmation classification allows confirmed flips to trigger immediate action while filtered flips prompt a verification step, building a natural two-tier entry discipline directly into the indicator's output without additional tools. Pullback Re-entry : Flip levels provide structural anchors for re-entry on pullbacks. A price return toward an intact flip level during a confirmed trend offers a structurally referenced entry point with the arc serving as the invalidation boundary beyond the level. Position Sizing : The candle gradient supports exposure scaling and risk assessment. Entries taken when candles are faded, indicating close arc proximity, carry greater structural uncertainty than entries aligned with a well-extended, brightly coloured trend. Multi-Timeframe Application : Higher-timeframe arc direction establishes macro bias while lower-timeframe flip confirmation and VWAP filter classification provide entry precision. Confirmed flips on the lower timeframe aligned with higher-timeframe arc direction represent the highest-quality intersection of the system's outputs. Technical Implementation Details Core Engine : Velocity-accumulating arc with ATR-scaled initial placement, step progression, and VWAP distance acceleration boost VWAP Layer : Independent session, weekly, and monthly VWAP computed from rolling cumulative volume and price-volume, resetting at each period boundary Filter System : Configurable agreement mode across session, week, month, any, or all VWAP periods with separate confirmed and filtered flip classification Visualisation : Smoothed arc plot, gradient cloud fill, ATR-normalised candle gradient, layered flip markers, and auto-removing flip level lines with configurable style, width, transparency, and label sizing Alert Coverage : Bullish confirmed, bearish confirmed, bullish filtered, and bearish filtered flip events Optimal Application Parameters Timeframe Guidance: 1 - 15 min : Intraday trend tracking with session VWAP filter for same-day directional context 1H - 4H : Swing trend identification with weekly VWAP filter for multi-session structural alignment Daily - Weekly : Macro trend positioning with monthly VWAP filter for broad directional confirmation Suggested Baseline Configuration: Arc Speed : 0.12 Start Distance : 2.0x Smoothing : 3 VWAP Filter : Session VWAP Speed Boost : 1.5 Arrow Offset : 1.2x These parameters represent a balanced starting point. Instruments with faster characteristic swing cadence benefit from higher arc speed; slower, trend-persistent instruments suit lower values with a higher start distance to avoid premature flips during normal retracements. Parameter Calibration Notes Use the following adjustments to refine behaviour without altering the core logic: Arc flipping too frequently : Raise Start Distance to place the arc further from price on each new trend, requiring a larger adverse move before a flip triggers. Arc too slow to follow strong trends : Raise Arc Speed or VWAP Speed Boost to increase acceleration rate, particularly on instruments with fast-developing directional moves. Too many filtered signals : Switch VWAP filter to Any to require only single-period agreement, loosening the confirmation threshold without removing VWAP context entirely. Too many false confirmed signals : Switch to All to require full agreement across session, weekly, and monthly VWAP before a flip qualifies as confirmed. Arc visually noisy during consolidation : Raise Smoothing to increase arc averaging, reducing short-term noise at the cost of modest additional lag during transitions. Flip levels persisting beyond usefulness : Reduce Max Levels to limit the number of active structural references retained simultaneously, concentrating display on the most recent pivot history. Disclaimer Arc VWAP Supertrend is a professional-grade trend analysis tool. Directional signals, flip classifications, and arc behaviour reflect historical price and volume relationships and do not constitute assured future outcomes. Performance is dependent on market conditions, instrument characteristics, parameter selection, and disciplined application within a broader analytical framework incorporating risk management, timeframe context, and corroborating analysis. BOSWaves recommends treating this indicator as one component of a structured trading methodology rather than a standalone signal system.
Pine Script® インジケーター
BOSWavesの投稿
14
Multi-Asset SuperTrend Map [BigBeluga]🔵 OVERVIEW Multi-Asset SuperTrend Map is a comparative market-structure visualization tool that displays multiple assets side-by-side using a unified SuperTrend framework. Instead of switching charts or stacking indicators, this tool compresses several markets into a single view, allowing traders to instantly assess trend direction, volatility alignment, and volume pressure across assets. Each asset is reconstructed as a scaled synthetic candle stream, aligned to the current chart’s volatility, and overlaid with its own SuperTrend logic. 🔵 CORE CONCEPT SuperTrend as Regime Filter — Each asset uses the same ATR-based SuperTrend logic to determine bullish or bearish state. Volatility Normalization — Assets are scaled using ATR ratios so high-price and low-price symbols can be compared visually on one chart. Synchronized Time Axis — All assets are plotted on the current chart timeframe, enabling true bar-to-bar comparison. Trend + Delta Context — In addition to trend direction, the indicator aggregates directional volume (delta) to reveal participation strength. 🔵 CALCULATION & LOGIC 1. SuperTrend Engine The indicator uses TradingView’s native SuperTrend calculation: = ta.supertrend(factor, atrPeriod) ATR Length controls volatility smoothing. ATR Factor defines band width and trend sensitivity. Trend direction is binary: Bullish when price is above the SuperTrend line. Bearish when price is below the SuperTrend line. 2. Multi-Asset Scaling Logic Each external symbol is fetched using request.security() . ATR is calculated both on the chart symbol and the external symbol. A scaling coefficient is derived: chart ATR ÷ symbol ATR // --- compute scale factor on SAME timeframe atrChart = ta.atr(200) atrSym2 = request.security(sym, timeframe.period, ta.atr(200)) k = atrSym2 != 0.0 ? atrChart / atrSym2 : 1.0 All OHLC values are remapped so different assets share a comparable vertical range. 3. Synthetic Candle Reconstruction Each asset is redrawn using: Vertical lines for wicks Thick lines for candle bodies Candle color logic: Trend-based (SuperTrend direction) if enabled Otherwise standard bullish/bearish candle logic 4. SuperTrend Mapping The SuperTrend line for each asset is remapped and drawn as a polyline. This allows trend curvature and regime shifts to be compared visually across symbols. 5. Delta Volume Aggregation Directional volume is accumulated: Volume added when close > open Volume subtracted when close < open Delta is displayed per asset, showing whether bullish or bearish participation dominates. 🔵 VISUAL STRUCTURE Each asset is wrapped inside a bounding box representing its full recent range. Background color reflects current trend direction (bullish or bearish). Asset label displays: Symbol name Current price Trend direction arrow (▲ / ▼) Delta volume is displayed beneath the asset block for flow context. ⚠️MARKET SESSION BEHAVIOR On lower timeframes (e.g. 1m–12h), traditional stock markets are closed during weekends . During these periods, price data may appear as flat or static candles with minimal or no movement. This is expected behavior and reflects the absence of active trading, not a calculation error. Crypto markets remain unaffected and continue updating normally. 🔵 HOW TO USE Compare trend alignment across correlated markets (e.g., BTC vs ETH). Identify relative strength when one asset trends while others stall. Use delta volume to confirm whether trends are supported by participation. Spot early divergence when price trends align but delta disagrees. Combine with higher-timeframe structure or liquidity tools for execution. 🔵 CONCLUSION Multi-Asset SuperTrend Map transforms SuperTrend from a single-market indicator into a cross-market decision framework . By normalizing volatility, synchronizing time, and adding volume delta context, it enables traders to evaluate trend quality, alignment, and participation across assets — all from one chart. This makes it especially powerful for crypto pairs, index baskets, and correlated markets where relative behavior matters as much as absolute price direction.
Pine Script® インジケーター
BigBelugaの投稿
6
[Kpt-Ahab] HeatMap FusionWhat is “HeatMap Fusion”? HeatMap Fusion merges RSI, Volume Trend, ROC and an enhanced SuperTrend into one stacked heat-map. Smooth colour gradients reveal—at a glance—whether each component is bullish, neutral, or bearish, without cluttering the chart with multiple separate panes. Key Features Multi-indicator heat-map Three symbols with volume- or price-based colouring. RSI, ROC and SuperTrend share the same colour scale → instant market-breadth read-out. View switcher – choose RSI, ROC, SuperTrend, Volume SMA, Up/Down Volume or ALL from a single dropdown. Six colour schemes (red⇅green, purple⇅blue, etc.) for both light and dark layouts. Optional RSI divergence detection. Heikin-Ashi–driven SuperTrend plus Rapid Volatility Trend lines. Performance-optimised – only three request.security() calls for the selected symbols. Inputs Group Core settings Indicator Layer to display Color Scheme (Heatmap) 6 presets Symbol 3 tickers, volume/price mode, look-back length RSI Period, MA type, BB width, divergence flag Volume Trend SMA length, up/down columns ROC Period & intensity threshold SuperTrend Two ATR sets, Heikin-Ashi on/off (Every parameter is commented inside the script.) How to Use Add the script to any chart. Set SymCal to on when your symbol has real volume data (futures, ETFs, equities). Replace the three default tickers with your own—e.g. ES1!, ZB1!, CL1! for a macro setup. Pick a colour scheme; Purple ⇅ Blue looks great on dark backgrounds. Choose ALL for the full heat-map with labels, or isolate any single layer via the dropdown. Notes The heat-map lives in the main pane on fixed Y-bands (0 – 70). Do not enable Auto-Fit scaling. If a symbol has no volume, SymCal = on yields no colouring—switch it off to fall back to price-based gradients.
Pine Script® インジケーター
Kpt-Ahabの投稿
Prismatic Trend Matrix [JOAT]Prismatic Trend Matrix Introduction The Prismatic Trend Matrix is an advanced open-source multi-dimensional trend analysis system that combines Hull Moving Average, SuperTrend, ADX strength filtering, and moving average confluence into a unified trend detection engine. This indicator analyzes trend across multiple dimensions simultaneously, creating a prismatic view of market direction with gradient visualization that reveals trend strength and conviction. Unlike single-indicator trend systems, the Prismatic Trend Matrix provides multi-layered trend intelligence through Hull MA smoothing, SuperTrend band analysis, ADX strength measurement, and EMA/SMA alignment detection. The indicator is designed for traders who understand that strong trends require confirmation across multiple analytical dimensions. Why This Indicator Exists This indicator addresses the need for comprehensive trend analysis that goes beyond simple moving averages. By combining four distinct trend methodologies with gradient visualization, it reveals: Hull Moving Average: Weighted moving average with reduced lag for responsive trend detection SuperTrend Component: ATR-based bands that identify trend direction and support/resistance ADX Strength Filter: Measures trend strength to separate strong trends from weak/choppy conditions Moving Average Matrix: Three EMAs and two SMAs create alignment-based trend confirmation Trend Classification: Five-state system (Strong Bull, Weak Bull, Sideways, Weak Bear, Strong Bear) Counter-Trend Detection: Identifies potential reversals when price moves against established trend Prismatic Gradient: Visual fill between Hull MA and SuperTrend shows trend intensity Core Components Explained 1. Hull Moving Average (HMA) The Hull MA uses weighted moving averages to create a smooth trend line with minimal lag: The calculation involves three steps: Step 1: Calculate WMA of half-length period Step 2: Calculate WMA of full-length period Step 3: Calculate WMA of the difference using square root of length The result is a moving average that responds quickly to price changes while maintaining smoothness. The indicator applies additional EMA smoothing (default 3 periods) to reduce noise. 2. SuperTrend Calculation SuperTrend uses ATR-based bands to identify trend direction: Source: Average of high and low (HL2) Upper Band: Source + (ATR × Factor) Lower Band: Source - (ATR × Factor) Direction: Bullish when close > upper band, bearish when close < lower band Three modes control band adjustment: Strict Mode: Bands adjust only when price crosses or previous band is breached Quick Mode: Bands adjust when price crosses previous band Quicker Mode: Bands adjust immediately with price SuperTrend provides dynamic support/resistance levels that adapt to volatility. 3. ADX Strength Measurement The Average Directional Index measures trend strength: DI+ (Directional Indicator Plus): Measures upward directional movement DI- (Directional Indicator Minus): Measures downward directional movement ADX: Smoothed average of the difference between DI+ and DI-, normalized Threshold: ADX above threshold (default 25) indicates strong trend Rising ADX: Indicates strengthening trend momentum ADX filters out weak trends and choppy conditions, ensuring signals occur only during strong directional movement. 4. Moving Average Matrix Five moving averages create a trend alignment system: Fast EMA (9): Short-term trend direction Medium EMA (21): Intermediate trend direction Slow EMA (50): Primary trend direction Fast SMA (50): Smoothed primary trend Slow SMA (200): Long-term institutional trend Alignment is measured by comparing the order of these averages: Bullish Alignment: EMA9 > EMA21 > EMA50 > SMA50 (all in ascending order) Bearish Alignment: EMA9 < EMA21 < EMA50 < SMA50 (all in descending order) Mixed Alignment: Averages not in order (choppy or transitional conditions) Perfect alignment indicates strong institutional conviction in the trend direction. 5. Composite Trend Classification [/b> The indicator combines all components into a five-state trend classification: Strong Bull (State 2): Hull rising + SuperTrend bullish + MA alignment bullish + ADX strong Weak Bull (State 1): Hull rising + (SuperTrend bullish OR MA alignment bullish) Sideways (State 0): Mixed signals or weak trend conditions Weak Bear (State -1): Hull falling + (SuperTrend bearish OR MA alignment bearish) Strong Bear (State -2): Hull falling + SuperTrend bearish + MA alignment bearish + ADX strong This classification provides clear trend assessment at a glance. 6. Counter-Trend Detection [/b> The indicator identifies potential reversals when price moves against established trend: Counter-Trend Bull: Trend state neutral/bearish + close > open + price rising + DI+ > DI- + close > Hull + ADX > 20 Counter-Trend Bear: Trend state neutral/bullish + close < open + price falling + DI- > DI+ + close < Hull + ADX > 20 Counter-trend signals include anti-overlap logic to prevent signal clustering and ensure clean placement. 7. Prismatic Gradient Visualization The indicator creates a gradient fill between Hull MA and SuperTrend: Gradient Layers: Multiple intermediate values calculated between Hull and SuperTrend (default 15 layers) Color Intensity: Transparency increases from Hull (solid) to SuperTrend (transparent) Dynamic Coloring: Gradient color matches trend state (green = bullish, red = bearish, cyan = sideways) Visual Effect: Creates a glowing prismatic effect that emphasizes trend strength The gradient provides intuitive visual feedback on trend intensity and direction. 8. Platform Levels Platform levels are horizontal lines at the current Hull MA value: Extension: Lines extend forward and backward from current bar (default 7 bars each direction) Color Coding: Platform color matches current trend state Purpose: Provides visual reference for potential support/resistance at Hull MA level Platforms help identify key levels where price may find support or resistance. Visual Elements Hull Trend Line: Thick line (3px) with regime-based coloring showing primary trend SuperTrend Line: Medium line (2px) with step-line style showing dynamic support/resistance EMA Matrix: Three thin lines showing fast, medium, and slow EMAs with transparency Prismatic Gradient: Multi-layer fill between Hull and SuperTrend creating glow effect Platform Levels: Horizontal lines at Hull MA value extending forward/backward Counter-Trend Signals: Triangles marking potential reversal points Background Coloring: Subtle background tint for strong bull/bear states Information Dashboard: Displays trend state, Hull direction, ADX strength, momentum, alignment, SuperTrend, DI balance, price vs Hull, gradient zone, counter-trend status, and signal How to Use This Indicator Step 1: Check Trend State Monitor the dashboard for current trend state (Strong Bull, Weak Bull, Sideways, Weak Bear, Strong Bear). Trade in the direction of strong states. Step 2: Verify ADX Strength Ensure ADX is above threshold (default 25) for strong trends. Low ADX indicates choppy conditions - avoid trend-following strategies. Step 3: Confirm MA Alignment Check if moving averages are aligned (Bullish/Bearish/Mixed). Perfect alignment confirms institutional conviction. Step 4: Monitor Hull Direction Hull rising = bullish bias, Hull falling = bearish bias. Hull provides the primary trend direction signal. Step 5: Use SuperTrend for Support/Resistance SuperTrend line acts as dynamic support in uptrends and resistance in downtrends. Breaks of SuperTrend warn of trend changes. Step 6: Watch for Counter-Trend Signals Counter-trend signals at extreme levels may indicate reversals. Use these cautiously and confirm with other factors. Step 7: Assess Gradient Zone Price in upper gradient zone (near Hull) = strong trend, price in lower zone (near SuperTrend) = weak trend or potential reversal. Best Practices Trade only in Strong Bull or Strong Bear states for highest probability Avoid trading in Sideways state - wait for clear trend establishment Use ADX as a filter - only trade when ADX > 25 for strong trends Confirm trend with MA alignment before entering positions Use SuperTrend as trailing stop level in trending markets Counter-trend signals work best at extreme levels with divergence Monitor gradient zone - price near SuperTrend may indicate trend exhaustion Combine with higher timeframe trend for additional confirmation Input Parameters Hull Trend Engine: Hull Length: Period for Hull MA calculation (default: 20) Hull Smoothing: Additional EMA smoothing (default: 3) SuperTrend Layer: ATR Period: Period for ATR calculation (default: 10) ATR Factor: Multiplier for band width (default: 3.0) Mode: Strict, Quick, or Quicker (default: Quick) Trend Strength: ADX Length: Period for ADX calculation (default: 14) ADX Smoothing: Smoothing period for ADX (default: 14) Strength Threshold: Minimum ADX for strong trend (default: 25) MA Matrix: Fast EMA: Short-term EMA (default: 9) Medium EMA: Intermediate EMA (default: 21) Slow EMA: Primary EMA (default: 50) Fast SMA: Smoothed primary (default: 50) Slow SMA: Long-term institutional (default: 200) Visual Configuration: Bullish/Bearish Trend Colors: Customizable colors for trend states Sideways/Weak Trend Colors: Colors for neutral and weak states Gradient Layers: Number of gradient fills (default: 15) Show Platforms: Toggle platform level display (default: enabled) Platform Extension: Bars to extend platforms (default: 7) Originality Statement This indicator is original in its multi-dimensional trend approach. While individual components (Hull MA, SuperTrend, ADX, EMAs) are established concepts, this indicator is justified because: It combines four distinct trend methodologies into a unified classification system The five-state trend classification provides clear trend assessment Prismatic gradient visualization creates intuitive trend intensity display Counter-trend detection with anti-overlap logic identifies potential reversals MA alignment analysis measures institutional conviction Integration of Hull MA smoothness with SuperTrend adaptability creates balanced trend detection The comprehensive dashboard presents all trend dimensions simultaneously Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Trend analysis does not guarantee profitable trades. Past trends do not guarantee future trends. Always use proper risk management and never risk more than you can afford to lose. -Made with passion by officialjackofalltrades
Pine Script® インジケーター
officialjackofalltradesの投稿
Smooths Trend BreakerSmooths Trend Breaker Overview Smooths Trend Breaker is a trend identification and entry timing tool that combines an adaptive ATR-based supertrend, a higher timeframe EMA trend filter, volume confirmation, an RSI gate, a price compression range detector, and FVG-gated star candlestick pattern recognition. Each component was chosen to address a specific weakness in standalone supertrend systems — noise in choppy markets, late entries, and signals that contradict the larger trend — and all components work together as a single decision framework rather than as separate overlapping indicators. Component Methodology Adaptive Supertrend Engine The core engine uses an ATR-based supertrend calculation. True Range is computed on each bar as the maximum of the current high-low range, the absolute distance from the prior close to the current high, and the absolute distance from the prior close to the current low. ATR is then derived using Wilder's smoothing method — a modified exponential moving average with a smoothing factor of 1/N — rather than a simple average, which gives more weight to recent volatility while maintaining memory of past conditions. The upper and lower bands are calculated as the midpoint of the bar's high-low range plus or minus the ATR multiplied by a user-defined multiplier. Bands are then locked directionally — the lower band can only move upward and the upper band can only move downward — preventing the line from retreating when price moves against the trend. The trend direction flips only when a closing price crosses the opposite band, not on intrabar wicks, ensuring signals are close-confirmed. Rather than using fixed ATR settings across all timeframes, the indicator auto-selects ATR length and multiplier based on the chart's timeframe in seconds. Shorter timeframes receive a shorter ATR period and higher multiplier to account for proportionally larger noise relative to signal. Longer timeframes receive a longer period and lower multiplier to avoid over-sensitivity on slower-moving instruments. This eliminates the need to manually adjust parameters when switching timeframes. Higher Timeframe EMA Filter When enabled, the indicator uses `request.security()` to retrieve a 50-period EMA from a higher timeframe selected automatically based on the chart timeframe — for example a 15-minute EMA is referenced when viewing a 5-minute chart, and a 4-hour EMA is referenced when viewing a 1-hour chart. A Buy label is only confirmed when price closes above this EMA and a Sell label is only confirmed when price closes below it, aligning entries with the larger structural trend. Volume Confirmation The volume filter computes a 20-bar simple moving average of volume. A signal is confirmed only when the flip bar's volume exceeds this average by a user-defined threshold, defaulting to 1.2 times the average. This filters out supertrend flips that occur on low-participation bars, which have historically higher failure rates. RSI Gate A 14-period RSI using Wilder's smoothing is computed on each bar. Buy signals are blocked when RSI exceeds a user-defined overbought level (default 70) and Sell signals are blocked when RSI falls below a user-defined oversold level (default 30). This prevents chasing exhausted moves at extremes. Range Breaker The Range Breaker compares the current N-bar rolling range (highest high minus lowest low) against the prior N-bar rolling range from the equivalent lookback window shifted N bars back. When the current range is less than a defined ratio of the prior range — meaning price has compressed significantly relative to its recent volatility — a consolidation zone is declared. Horizontal lines are drawn at the highest high and lowest low of the active zone and extend forward with the current bar. When a closing price breaks outside either level the zone is sealed and a breakout marker fires. Star Pattern Detection with FVG Gate Morning Star, Morning Doji Star, Evening Star, and Evening Doji Star patterns are detected using strict 3-candle criteria. The first candle must be a strong directional bar with a body filling at least 50% of its range. The middle candle — the star — must have a body of 25% or less of its range and a total range smaller than 80% of the first candle's body. The confirmation candle must be directionally opposite to the first candle with a body filling at least 40% of its range, closing past the midpoint of the first candle's body. Additionally, a Fair Value Gap check is applied to the candle immediately before the star. A bearish FVG exists when the high of bar N is below the low of bar N+2, creating a downward price gap. A bullish FVG exists when the low of bar N is above the high of bar N+2, creating an upward price gap. An Inverse FVG check scans back 45 bars for a prior FVG zone whose price range overlaps with the pre-star candle, indicating price has returned to fill an old imbalance. If neither an FVG nor an IFVG is present on the candle before the star, the pattern does not fire regardless of candle structure. This ensures every star signal is anchored to a real price imbalance. How to Use It The highest probability setups occur when the supertrend line has already established direction, the range detector is not showing an active chop zone, and a signal fires with volume and HTF agreement. The Range Breaker lines are a caution flag — while they are active and unbroken, the supertrend will produce lower quality signals due to market compression. The star patterns provide a precision entry trigger that can be used to time entries at reversal points, particularly when a star fires near an active Range High or Range Low level. Trend continuation Wait for a pullback toward the supertrend line, then enter when the next Buy or Sell label prints in the direction of the established trend. Breakout entries When a range zone has been active for several bars and the supertrend is already pointing in one direction, a range breakout marker firing in that same direction is a high-quality entry trigger. Star entries A star pattern firing at or near a Range High or Range Low, with the supertrend already in agreement, represents the highest confluence setup available in the indicator. What to avoid Do not enter trend signals while a range zone is active with no breakout. Do not take signals that contradict the HTF EMA. Do not enter late into an extended trend where price is far from the supertrend line. Settings ATR Length and Multiplier auto-scale by timeframe but can be manually overridden. Volume threshold multiplier defaults to 1.2× the 20-bar average. RSI overbought and oversold levels default to 70 and 30. Range sensitivity has three modes controlling lookback period, compression ratio, and minimum bar count. Past zones to display defaults to 5, maximum 20.
Pine Script® インジケーター
CaptainSmoothの投稿
Alpha Signal Engine [MarkitTick]💡 The Alpha Signal Engine is an advanced, multi-dimensional trend-following system designed to provide traders with highly filtered, high-probability market signals. At its core, it dynamically calculates a volatility-adjusted trailing band to determine the primary market direction. However, unlike traditional trend indicators that rely on a single data point, this engine passes every potential trend reversal through a rigorous, six-layer filtering mechanism. By requiring confluence across higher timeframe trends, momentum, volume, volatility regimes, and price action strength, it drastically reduces the noise and false signals inherent in choppy markets. It also features a built-in heads-up dashboard and fully formatted JSON webhook capabilities for automated trading integration. ✨ Originality and Utility ● A Dynamic, Adaptive Baseline Standard trailing stop or trend indicators, such as the classic Supertrend, typically use a static multiplier against the Average True Range (ATR). The Alpha Signal Engine innovates by introducing a "Dynamic Factor." This factor continuously adapts the band's distance from price by factoring in the current baseline multiplier, the relative volatility (ATR normalized by price), and the immediate price change momentum. This allows the bands to tighten during periods of strong, directional momentum and widen during erratic volatility, providing a more responsive and intelligent trailing mechanism. ● The Six-Pillar Filtering Gateway The true utility of this indicator lies in its modular filtering engine. Traders often have to clutter their charts with half a dozen indicators to confirm a setup. This script centralizes that logic. Users can selectively enable or disable filters based on their specific asset and trading style, turning the indicator into a customizable algorithmic engine. Whether you need volume confirmation, ADX trend strength, or simple RSI momentum, the script handles the complex boolean logic internally and only outputs a signal when your precise market conditions are met. 🔬 Methodology and Concepts ● Dynamic Factor Calculation The indicator establishes its baseline trend using an upper and lower band. The distance of these bands from the median price is dictated by a dynamically calculated factor. This factor is the sum of a base value, a volatility component (ATR divided by Close, scaled by a user weight), and a price movement component (percentage change of the close, scaled by a user weight). This raw factor is then smoothed using a Simple Moving Average (SMA) to prevent erratic band shifts. ● Trend Determination The trend direction flips when the closing price crosses the active dynamic band. If the price closes above the upper band, the trend shifts bullish, and the lower band becomes the active support. Conversely, closing below the lower band shifts the trend bearish, making the upper band the active resistance. ● The Filter Matrix A signal is only generated when a trend flip aligns with all activated filters: HTF Alignment: Uses the request context to pull the trend direction from a higher timeframe, ensuring you are not trading against the macro trend. ADX Trending: Measures the Average Directional Index to ensure the market is in an active trending phase (above a defined threshold) rather than a sideways chop. Volume Surge: Compares current volume against a Volume SMA. The current bar must exhibit a volume spike greater than the defined multiplier to confirm institutional participation. RSI Momentum: A simple but effective gatekeeper requiring the Relative Strength Index to be above 50 for longs and below 50 for shorts. ATR Volatility Regime: Compares the current ATR against a 50-period SMA of the ATR. It ensures the market is operating within a "normal" volatility ratio, preventing entries during extreme, unpredictable volatility spikes or dead, illiquid periods. Candle Body Strength: Calculates the absolute size of the candle body (Open to Close) and mandates it must be larger than a specific fraction of the ATR, ensuring the signal candle has true directional conviction. 🎨 Visual Guide ● Chart Elements Up Trend Line: Displayed as a solid, teal-colored line trailing below the price action during a bullish phase. It acts as dynamic support. Down Trend Line: Displayed as a solid, bright pink/red line trailing above the price action during a bearish phase. It acts as dynamic resistance. Trend Cloud (Fill): A colored gradient fill exists between the median price and the active trend line. A teal cloud visually represents bullish dominance, while a pink/red cloud represents bearish dominance. Buy Signals: Indicated by small, teal "B" labels positioned below the signal candle. Sell Signals: Indicated by small, pink/red "S" labels positioned above the signal candle. ● Filter Dashboard Located in the top right corner of the chart, this HUD (Heads-Up Display) provides a real-time status check of your system. The left column lists the available filters (HTF Align, ADX Trend, Vol Surge, RSI Gate, ATR Regime, Body Str). The right column displays the current status of each filter. A gray "OFF" indicator means the user has disabled the filter in the settings. A green "ON" or "Aligned" text indicates the condition is currently met. A red "Opposed" or unlit indicator means the condition is active but currently failing to meet the required criteria. The bottom rows clearly state the current overarching trend direction and whether a signal is pending or waiting. 📖 How to Use • Interpreting the System To effectively use the Alpha Signal Engine, begin by observing the main trend lines and the color of the cloud. This provides your baseline bias. Do not take trades purely on the band flipping. Instead, rely on the explicit "B" and "S" labels. • Signal Execution When a "B" (Buy) or "S" (Sell) label appears, it means the price has successfully flipped the trend AND all user-activated filters in the dashboard are glowing green. This is your entry trigger. The active trend line (the teal line for longs, the pink line for shorts) serves as an ideal, dynamic stop-loss placement. • Customizing the Engine The system is designed to be tuned. If you are trading a highly liquid asset like major forex pairs, you may want to enable the ADX and HTF filters to catch long, sustained moves. If you are trading volatile crypto assets, enabling the Volume Surge and Candle Body filters can help you avoid fake-outs and trap wicks. Monitor the on-chart dashboard to see which filters are keeping you out of bad trades and adjust your settings accordingly. ⚙️ Inputs and Settings • Supertrend Settings ATR Length: The lookback period for calculating the Average True Range. Base Factor: The starting multiplier for the dynamic bands. Volatility & Price Change Weights: Determines how aggressively the bands react to sudden spikes in relative volatility and price momentum. Factor Smoothing: Applies an SMA to the final dynamic multiplier to keep the bands stable. • Filter Settings Enable HTF Alignment: Toggle and define the higher timeframe (e.g., Daily) to align with. ADX Settings: Toggle the filter, define the lookback length, and set the minimum trend strength threshold (default is 20). Volume Settings: Toggle the filter, define the Volume MA length, and set the multiplier required to classify as a "surge." RSI Settings: Toggle the filter and set the RSI lookback length. ATR Regime Settings: Define the minimum and maximum acceptable ratios of current ATR versus historical ATR. Candle Body Settings: Define the minimum required size of the candle body as a fraction of the current ATR. • Webhook Action Names These text inputs allow you to define specific payload strings (e.g., "long", "closeshort") that the indicator will output via JSON alerts, perfectly formatting the data for third-party automation services like 3Commas or PineConnector. 🔍 Deconstruction of the Underlying Scientific and Academic Framework The Alpha Signal Engine is grounded in several well-documented tenets of quantitative financial analysis and statistical market theory. ● Volatility-Adjusted Trailing Stops The foundation of the indicator relies on the Average True Range (ATR), introduced by J. Welles Wilder Jr. The ATR is a measure of the degree of price volatility. By tying the trailing stop (the dynamic band) to the ATR, the system acknowledges the statistical reality of market variance. The innovation here is the dynamic multiplier. By adjusting the distance based on the normalized rate of change (momentum), the script attempts to solve the lagging nature of fixed-multiplier trailing stops, utilizing principles found in adaptive moving averages (like Kaufman's AMA), where sensitivity increases alongside directional conviction. ● Multi-Dimensional Confluence Theory The filtering engine operates on the academic principle of conditional probability and confluence. In market microstructure, no single indicator holds a permanent statistical edge. The HTF filter is rooted in Dow Theory, prioritizing the primary trend over secondary reactions. The ADX filter utilizes Wilder's Directional Movement Index to mathematically separate trending environments from mean-reverting environments, applying a statistical threshold to directional strength. The Volume Surge filter relies on the Volume Price Trend concepts, positing that significant price movements must be sponsored by outsized volume to validate institutional participation and avoid anomalous low-liquidity spikes. The ATR Regime filter applies mean-reverting principles to volatility itself (volatility clustering), ensuring that entries are only taken when the variance of the asset is within historically "normal" parameters, avoiding the fat tails of extreme market shocks. By chaining these disparate mathematical models (trend, momentum, volume, volatility) via Boolean logic, the system mathematically reduces the frequency of trades while theoretically increasing the probability of the remaining sample size. ⚠️ Disclaimer All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Pine Script® インジケーター
MarkitTickの投稿
4
KNN Supertrend Horizon [LuxAlgo]The KNN Supertrend Horizon indicator is a machine learning tool that combines K-Nearest Neighbors (KNN) classification with Supertrend logic to identify high-probability trend directions and price rejection zones. 🔶 USAGE The indicator provides a comprehensive view of market trends by filtering traditional Supertrend calculations through a machine learning engine. It is designed to help traders stay on the right side of the trend while identifying potential exhaustion points through visual "Rejection Orbs." 🔹 Trend Identification The core trend logic is driven by the KNN engine, which analyzes RSI and volatility (ATR) features over a lookback window to determine the most likely trend direction. When the ML confidence aligns with the Supertrend, the indicator displays a colored horizon at the top or bottom of the chart. 🔹 3D Rejection Orbs Specialized rejection signals appear when price interacts with the Supertrend level and forms a significant wick. The size of the orb is dynamically adjusted based on relative volume. A label attached to the orb displays the exact volume of the rejection candle. These orbs serve as potential entry or exit signals where price is "bouncing" off the trend baseline. 🔹 Confidence Visualization The script features "Liquid Smooth" gradient candle coloring. The intensity of the candle colors shifts based on the ML engine's confidence level. Brighter, more vibrant colors indicate a high-conviction trend, while muted colors suggest the trend may be weakening or entering a sideways phase. 🔶 DETAILS The KNN engine functions by searching for historical similarities in price behavior. By comparing the current RSI and ATR-based volatility to the past N bars (Search Window), it finds the K closest matches (Neighbors) to predict the current trend state. A confidence buffer is applied to this probability to filter out market noise and prevent rapid signal flipping. 🔶 SETTINGS 🔹 Machine Learning Settings K-Neighbors: The number of historical neighbors the algorithm looks for to determine the trend direction. Search Window: The lookback period (in bars) used to find similar historical patterns. 🔹 Supertrend Settings ATR Length: The period used for the Average True Range calculation. Factor: The multiplier applied to the ATR to set the distance of the Supertrend line. 🔹 Noise Filter Settings Smooth Price Input: Enables HMA smoothing on the price source used for ML features. ML Confidence Buffer (%): The percentage threshold above/below 50% required to trigger a trend change. 🔹 Rejection Signal Settings Show 3D Rejection Orbs: Toggles the visibility of the volume-based rejection bubbles. Min Wick-to-Body Multiplier: The required ratio of wick length to body size to qualify as a rejection. Min Bubble Gap: The minimum number of bars required between consecutive rejection signals. 🔹 Visual & Dashboard Settings Liquid Smoothness: Controls the EMA smoothing applied to the ML confidence for visual gradients. Vibrancy: Increases the color intensity of the gradient candles and horizons. Show Dashboard: Toggles the real-time statistics table containing trend direction, ML confidence, and relative volatility.
Pine Script® インジケーター
LuxAlgoの投稿
6
StealthTrail SuperTrend ML Pro [WillyAlgoTrader]🤖 StealthTrail SuperTrend ML Pro is an overlay indicator that builds on the adaptive SuperTrend core from StealthTrail and adds three layers of intelligence: an instrument profiling engine that classifies the market into Trending, Ranging, or Volatile regimes and auto-tunes all SuperTrend parameters accordingly; a 13-feature machine learning scoring system that evaluates every candidate signal on momentum, trend, volatility, structure, volume, HTF alignment, divergence, session quality, and regime context — producing a 0–100 confidence score; and a self-learning mechanism that tracks signal outcomes over time and dynamically adjusts the confidence gate to optimize signal quality. The result is a SuperTrend that configures itself, scores its own signals, and learns from its results. 🧩 WHY THESE COMPONENTS WORK TOGETHER A standard SuperTrend has fixed parameters that work well in one market regime and fail in another. Manually tuning ATR length, multiplier, and filters for each instrument and timeframe is time-consuming and becomes outdated when conditions change. This indicator solves the problem through a three-layer intelligence stack: Layer 1 — Regime classification → Auto-tuning: The instrument profiler continuously measures efficiency ratio (trend strength), autocorrelation (serial dependence), volatility clustering, and normalized volatility — classifying the market into TRENDING, RANGING, or VOLATILE. Each regime produces different optimal SuperTrend parameters. The auto-tuner interpolates ATR length, multiplier, cushion, cooldown, and RSI threshold using regime-weighted blending — so the SuperTrend self-configures for current conditions. Layer 2 — ML signal scoring: Even with auto-tuned parameters, not every SuperTrend flip is a good trade. The 13-feature ML engine evaluates each flip against momentum, volume, trend efficiency, volatility shock, band distance, MACD, price structure, regime confidence, MTF alignment, ADX strength, RSI divergence, volume profile zone, and session quality. Each feature is normalized to 0–100, weighted, passed through a sigmoid function, and combined into a single confidence score. Signals below the confidence gate are rejected — they pass the classic SuperTrend logic but fail the multi-dimensional quality check. Layer 3 — Self-learning gate: The ML confidence gate itself adapts over time. The system tracks each signal's outcome (win/loss evaluated after N bars using the ATR at entry for fair comparison). When the win rate exceeds 70%, the gate lowers (allowing more signals). When it drops below 50%, the gate raises (becoming stricter). A decay factor prevents old signals from dominating. This creates a feedback loop: the indicator learns which confidence level produces profitable signals on this specific instrument and timeframe. Without auto-tuning, the SuperTrend uses static parameters. Without ML scoring, good and bad flips are treated equally. Without self-learning, the confidence gate is a fixed guess. Each layer eliminates a specific category of bad signals that the previous layer can't catch. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Instrument profiling and regime classification. The profiler computes four metrics over a configurable lookback (default 100 bars): — 📐 Efficiency Ratio : ER = |close − close | / sum(|close − close |, N). Measures net directional movement vs total path. ER → 1.0 = pure trend, ER → 0.0 = pure chop. — 🔄 Autocorrelation : correlation between return and return over a sliding window. High positive autocorrelation = trending persistence. Near-zero = random. Negative = mean-reverting. — 📏 Volatility Clustering : ratio of short-term ATR (20 bars) to long-term ATR (lookback). Values > 1.0 indicate a volatility spike (breakout or crash). Values < 1.0 indicate compression. — 📈 Normalized Volatility : ATR / close × 100. Measures absolute volatility as percentage of price — allows cross-instrument comparison. These are smoothed with EMA and combined into three regime scores: — trendScore = ER × regimeSensitivity — rangeScore = (1 − ER) × (1 − |autocorrelation|) × regimeSensitivity — volatScore = clamp(volClustering − 1, 0, 2) × regimeSensitivity The highest score determines the regime: TRENDING, RANGING, or VOLATILE. Regime confidence = highest_score / total_scores × 100%. 2️⃣ Regime-weighted auto-tuning (6 parameters). Each SuperTrend parameter is computed as a weighted blend of regime-optimal values: effectiveParam = wT × trendOptimal + wR × rangeOptimal + wV × volatileOptimal Where wT, wR, wV are the normalized regime weights. The parameters and their regime-optimal ranges: — ATR Length: Trending=10, Ranging=16, Volatile=21 (further scaled by normalized volatility) — Base Multiplier: Trending=2.0, Ranging=3.2, Volatile=3.8 (scaled by normalized vol) — Flip Cushion: Trending=0.05, Ranging=0.25, Volatile=0.15 — Signal Cooldown: Trending=2, Ranging=5, Volatile=3 — RSI Threshold: Trending=40, Ranging=52, Volatile=45 — RSI Length: derived as ATR Length × 0.9 — Adaptive Smoothing: ATR Length × 4.0 This means in a trending regime, the SuperTrend uses shorter ATR, lower multiplier (tighter bands), minimal cushion, and permissive RSI — catching trends early. In a ranging regime: longer ATR, wider multiplier, large cushion, strict RSI — avoiding chop. In volatile conditions: intermediate settings with wider bands to accommodate spikes. 3️⃣ 13-feature ML scoring engine. Each feature is normalized to 0–100, multiplied by its weight, summed, normalized by total weight, and passed through a sigmoid function to produce the final 0–100 confidence score. Features and their weights: — 💪 F1: Momentum (RSI alignment with trend) — w=0.15 — 📈 F2: Volume Surge (volume / SMA ratio) — w=0.08 — 📐 F3: Trend Efficiency (ER × 100) — w=0.15 — ⚡ F4: Volatility Shock (inverted vol clustering) — w=−0.08 (negative = penalizes vol spikes) — 📏 F5: Band Distance (sigmoid of close-to-band ATR distance) — w=0.10 — 📊 F6: MACD (normalized histogram vs ATR) — w=0.08 — 🏗️ F7: Price Structure (HH/HL for bull, LL/LH for bear over 10 bars) — w=0.08 — 🧠 F8: Regime Confidence (% confidence in current regime) — w=0.04 — 🌐 F9: MTF Confluence (aligned with HTF = 100, not = 0) — w=0.12 — 💪 F10: ADX Strength (ADX × 2.5, capped at 100) — w=0.10 — 🔀 F11: RSI Divergence (aligned div = 100, counter div = 10) — w=0.08 — 📊 F12: Volume Profile Zone (proximity to highest-volume bar) — w=0.06 — 🕐 F13: Session Quality (hour-based scoring for optimal trading sessions) — w=0.04 The raw weighted sum is normalized, then passed through: mlScore = 100 / (1 + exp(−0.08 × (normalizedScore − 50))). This sigmoid compresses extreme values and centers the output around 50. All 13 weights plus the bias term are user-configurable — you can adjust how much each factor contributes. Negative weights penalize a factor (e.g., W4 = −0.08 means high volatility shock reduces the score). 4️⃣ Self-learning confidence gate. The system maintains 5 pending signal slots. Each stores the entry price, direction, bar index, and ATR at entry. After the evaluation horizon (default 15 bars), the outcome is assessed: win = (close − entryPrice) × direction > 0.5 × entryATR (profitable by at least half an ATR, using the ATR at entry time — not current ATR — for fair comparison) A decay factor (0.98) is applied to historical totals before adding new results, preventing stale data from dominating. When total tracked signals ≥ 8: — Win rate > 70% → gate decreases by 1.5 (more permissive) — Win rate < 50% → gate increases by 1.5 (more restrictive) — Gate is clamped to The dashboard shows the current gate value, whether it's auto-adjusted, and the tracked win rate with sample size. 5️⃣ Multi-timeframe confluence with auto-HTF selection. The indicator automatically selects the appropriate higher timeframe based on your current TF: 1M→15M, 5M→30M, 15M→1H, 1H→4H, 4H→D, D→W. Or you can manually specify the HTF. Three strictness levels: — Loose: MTF misalignment adds negative ML score but doesn't block — Moderate: MTF misalignment reduces signal quality — Strict: MTF misalignment hard-blocks the signal entirely HTF trend is determined by EMA(20) vs EMA(50) on the higher timeframe. 6️⃣ Adaptive SuperTrend core (from StealthTrail). The band calculation uses pre-computed interpolated ATR values (ATR bank at 9 fixed periods with lerp interpolation) for smooth adaptation to any auto-tuned ATR length. Same mechanics as StealthTrail: adaptive multiplier (ATR / SMA ratio), band ratcheting, flip cushion, and cooldown — but now all parameters are regime-driven. 7️⃣ Three-mode trailing TP/SL system. Three SL modes: ATR (entry ± mult × ATR), Band (SuperTrend band as SL), Fixed % (percentage from entry). Three trailing modes: — ATR : trail at fixed ATR distance from price — simple, consistent — Band : use the SuperTrend band itself as trailing stop — structurally anchored — ATR → Band (hybrid) : start with tight ATR trail, switch to band when it catches up — best of both The trail only ratchets in the profit direction (never moves away from price). TP1/TP2/TP3 hit markers (✓) appear on the chart. On TP3 or SL hit, the trade closes and lines are removed. 8️⃣ RSI divergence detection. Scans for bullish divergence (price lower low, RSI higher low, RSI < 40) and bearish divergence (price higher high, RSI lower high, RSI > 60). Divergences aligned with the signal direction boost the ML score (F11 = 100). Counter-divergences penalize it (F11 = 10). Optional visualization as dots on the chart. 9️⃣ Volume profile zone proximity. Tracks the highest-volume bar in the last 50 bars. Proximity to this bar's price level is scored: within 1.5× ATR = 100 (near institutional activity), further = proportionally lower. Signals near high-volume zones tend to have more follow-through. 🔟 Session quality scoring. For intraday timeframes, each hour receives a quality score based on typical institutional activity: London/NY overlap (13–17 UTC) = 100, European session (8–12) = 80, US afternoon (18–20) = 70, Asian session (0–7) = 30. An optional kill zone filter suppresses all signals during specified hours. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Instrument profiling: ER, autocorrelation, vol clustering, normalized vol → EMA-smoothed → regime classification (TRENDING / RANGING / VOLATILE) with confidence %. Step 2 — Auto-tuning: Regime weights blend optimal parameters for ATR length, multiplier, cushion, cooldown, RSI threshold/length. Step 3 — SuperTrend calculation: Interpolated ATR from pre-computed bank → adaptive multiplier (ATR/SMA ratio) → upper/lower bands → ratcheting → flip detection with cushion + cooldown. Step 4 — Classic filters: Momentum (RSI), volume, session, MTF hard-block (if strict). Step 5 — ML feature extraction: 13 features normalized to 0–100 from current market state. Step 6 — ML scoring: Weighted sum → weight normalization → sigmoid → 0–100 confidence score. Step 7 — Signal decision: Classic filters pass AND (ML disabled OR mlScore ≥ gate) → confirmed signal. Step 8 — Self-learning: Signal stored in pending slot → evaluated after horizon bars → win rate updated → gate adjusted. Step 9 — TP/SL placement: SL from band/ATR/fixed% → TPs as ATR multiples → trailing stop ratchets per mode. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — Auto-Tune is ON by default, parameters self-configure 2. The SuperTrend band and Long/Short labels appear 3. Dashboard shows: trend, strength, regime, ML score, gate, win rate, TP/SL status 4. Enable ML Filter for quality scoring (off by default — enable after reviewing signal quality) 5. Self-Learning auto-adjusts the gate over time 👁️ Reading the chart: — 🟢 Green band + "Long" label = confirmed bullish signal — 🔴 Red band + "Short" label = confirmed bearish signal — ⚫ Gray dot = classic filter blocked the flip — 🟡 Yellow triangle = ML rejected the signal (score below gate) — 🟢 Green dot below bar = bullish RSI divergence — 🔴 Red dot above bar = bearish RSI divergence — 📈 Regime badge = current market classification (📈 TRENDING / 📊 RANGING / ⚡ VOLATILE) — 🟢 Green dashed = TP1/TP2/TP3, 🔴 Red dashed = SL, 🔵 Blue dotted = entry — "TP1 ✓" / "SL ✗" labels = outcome markers 📊 Dashboard sections: — Main: trend, signal, strength, ADX, HTF alignment — 🤖 ML Engine: ML score, confidence gate (fixed or auto), win rate with sample size — 🎯 Position: status (LONG/SHORT/FLAT), entry, SL (with trail mode icon), TP levels (✓ for hit), R:R ratio — 🧠 Regime: classification + confidence % 🔧 Tuning guide: — Start simple: Auto-Tune ON, ML OFF — let the regime engine handle parameters — Add ML: Enable ML Filter after 50+ signals to see which score level produces winners — Enable Self-Learning: after 100+ bars of ML being active — let the gate auto-calibrate — Adjust weights: if you know your market (e.g., volume is unreliable on forex → set W2 to 0) — Strict MTF: for higher-timeframe alignment — reduces signals, increases quality — Trail Mode: Band for trend-following, ATR for scalping, ATR→Band for hybrid ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Auto-Tune (default On): regime-driven parameter self-configuration — ATR Length / Base Multiplier : manual overrides when auto-tune is off 🧠 Adaptive Engine: — Profiling Lookback (default 100): bars for regime classification — Regime Sensitivity (default 1.0): scaling factor for regime scores 📐 Multi-Timeframe: — MTF Confluence (default On): Auto/Manual HTF selection — Strictness (default Moderate): Loose / Moderate / Strict 🤖 ML Signal Filter: — Enable ML (default Off): activate 13-feature scoring — Confidence Gate (default 21): minimum ML score to pass — Self-Learning (default On): auto-adjust gate from tracked outcomes — Evaluation Horizon (default 15 bars): outcome assessment window — 13 individual weights + bias : fully configurable feature importance 🔍 Filters: — Flip Cushion, Cooldown, RSI Momentum, Volume, Session Kill Zone 🎯 TP/SL: — SL Mode (default Band): ATR / Band / Fixed % — Trail Mode (default Band): ATR / Band / ATR → Band — TP Levels (1–3): ATR multipliers (default 1.5 / 2.5 / 4.0) 🔔 Alerts — 🟢 LONG / 🔴 SHORT — ticker, price, TF, band, ML score, ADX, HTF, SL, TP1, regime — 🎯 TP1 / TP2 / TP3 HIT — trade progress — 🛑 SL HIT — stopped out All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. The confirmed trend direction is stored separately from the real-time calculation — signals only fire on closed bars. HTF data uses lookahead_off. A warmup period (max of profiling lookback and 55 bars) prevents signals during insufficient data. — 🤖 The ML scoring is not machine learning in the neural network sense . It's a weighted linear model with sigmoid activation — a logistic regression analog. The 13 features are hand-crafted from market microstructure, and the weights are configurable by the user. There is no gradient descent, backpropagation, or training phase. The "self-learning" adjusts only the confidence gate threshold, not the feature weights. — 📐 Auto-tuning produces different parameters on every bar as the regime shifts. The ATR length and multiplier change continuously — this is by design. If you prefer fixed parameters, disable Auto-Tune. — ⚖️ The self-learning gate requires at least 8 tracked signals before it begins adjusting. With the decay factor (0.98), the effective sample is weighted toward recent signals. The gate moves slowly (±1.5 per adjustment) and is clamped to . — 📊 Win rate evaluation uses ATR at entry time , not current ATR. A signal is a "win" if price moves > 0.5× entry ATR in the signal direction within the evaluation horizon. This prevents volatile periods from inflating win counts. — 🔄 The pre-computed ATR bank (9 fixed periods with lerp interpolation) is a performance optimization that allows smooth ATR adaptation to any auto-tuned length without calling ta.atr() dynamically — which Pine Script doesn't support with variable-length arguments. — 📏 Volume Profile Zone tracks the single highest-volume bar in the last 50 bars, not a full volume profile. It decays after 50 bars with no new volume peak. — 🕐 Session scoring uses UTC-based hours. On daily or higher timeframes, session quality defaults to 50 (neutral) as intraday session distinctions don't apply. — 🛠️ This is a signal scoring and analysis tool , not an automated trading bot. It classifies regimes, scores signals, tracks outcomes, and manages TP/SL — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume features auto-adapt to instruments without volume data.
Pine Script® インジケーター
WillyAlgoTraderの投稿
6
Adaptive Supertrend+ [MAB]Adaptive SuperTrend+ is an adaptive trend-following indicator that eliminates the guesswork of manually tuning a SuperTrend multiplier. Instead of relying on a single fixed factor, it continuously tests a range of multipliers in parallel and automatically selects the one that has been performing best on recent price action — giving you a SuperTrend that self-optimizes to current market conditions. 🔶 HOW IT WORKS Traditional SuperTrend indicators require the user to pick a multiplier and stick with it, regardless of whether market conditions favor a tight or wide band. Adaptive SuperTrend+ solves this by running multiple SuperTrend instances simultaneously across a user-defined factor range. Each instance is scored using an exponential performance metric that tracks how well that particular multiplier has aligned with directional price movement. On every bar, the highest-scoring factor is selected to render the final SuperTrend line — fully automatic, no manual tuning required. 🔶 USAGE 🔹 Trend Direction Teal line below price — Bullish trend is active. The line acts as a dynamic trailing support level. Red line above price — Bearish trend is active. The line acts as a dynamic trailing resistance level. 🔹 Trade Signals Teal triangle (▲) below bar — Bullish signal. Price has crossed above the band, indicating a potential long entry or trend reversal to the upside. Red triangle (▼) above bar — Bearish signal. Price has crossed below the band, indicating a potential short entry or trend reversal to the downside. Because the active multiplier adapts to recent performance, signals generated by Adaptive SuperTrend+ reflect a band that has been validated against current volatility conditions rather than a static parameter chosen arbitrarily. 🔶 SETTINGS 🔹 ATR Settings ATR Length — The lookback period used to calculate Average True Range. Controls how quickly the volatility measurement responds to recent price swings. 🔹 Factor Range Min Factor — The smallest SuperTrend multiplier included in the tested range. Max Factor — The largest SuperTrend multiplier included in the tested range. Factor Step — The increment between each tested multiplier. Smaller steps produce a finer search across the range but increase computation. 🔶 NOTES Suitable for any market and timeframe. Best used as a trend filter or trailing stop reference alongside your existing entry and exit criteria. Past performance of any selected factor does not guarantee future results. Always apply proper risk management.
Pine Script® インジケーター
MarketAlgoBotの投稿
Lucky: MTF Trend & Breakout DashboardLucky: MTF Trend & Breakout Dashboard All-In-One Trend, Breakout & Confluence Indicator with Live Dashboards | Pine Script v6 Free to use. Add it to your chart and start reading the market with clarity. Built by a trader, for traders. No noise. No repainting. Pure confluence. 🔶 WHAT IS THIS INDICATOR? Lucky: MTF Trend & Breakout Dashboard is an all-in-one overlay indicator that combines nine proven technical tools into a single, clean chart — and then summarizes everything in two live dashboards so you can make high-confidence decisions without flipping between indicators. It is designed for one purpose: helping you identify high-probability trend entries and breakouts with multi-timeframe confirmation, so you are never trading against the bigger picture. Rather than layering five separate indicators on top of each other, this script does all the heavy lifting behind the scenes and delivers the signal to you — a clean Buy or Sell label, a scored setup rating, and a complete view of market structure across up to eight timeframes simultaneously. AMD (Advanced Micro Devices) — 15-minute chart. The Supertrend haze fills show the bearish regime clearly. The Bias Table (top-right) confirms all timeframes are aligned bearish with 0% bullish agreement. The Price Point Live Dashboard (bottom-right) displays 35+ live reference levels. Notice the SL Touched and Buy labels showing where the UT Bot fired and where the suggested stop was hit. 🔶 FEATURES Trend and Momentum Engine - Adaptive UT Bot trailing stop with volume-weighted Buy/Sell signal labels - Supertrend with dynamic ATR multiplier and haze fill for bullish and bearish regimes - MACD crossover filter with minimum separation guard to suppress weak signals - Zero Lag SMA (ZLSMA) as an optional trend direction filter Moving Averages - Three fully configurable MAs: Fast, Medium, and Long - Supports EMA, SMA, WMA, VWMA, RMA, and HMA types - Optional fourth Medium-Long MA for advanced confluence stacking VWAP - Session, Day, Week, Month, Quarter, and Year anchor modes - Standard Deviation or Percentage band modes - Up to three bands at 1x, 2x, and 3x Multi-Timeframe Bias Table - Displays up to eight timeframes: 1m, 5m, 15m, 30m, 1h, 2h, 4h, and Daily - Rows include: Fast MA Cross, Price above MA200, Price above VWAP, MACD, Supertrend, ZLSMA, RSI, ADX, 3-Day Bias, Weekly Bias, Monthly Bias, and Quarterly Bias - Average agreement percentage column — aim for 70% or higher before entering Price Point Live Dashboard - 35+ live data points updated in real time - Includes Previous Day High/Low/Close, Pivot R1/PP/S1, 52-Week High, 20/50/200-Day MAs, VWAP deviation, Opening Range levels, ATR, Gap percentage, and Relative Volume - Color coded: green means price is above the level, red means price is below the level Opening Range Breakout - Tracks 5m, 15m, 30m, and 60m opening range levels automatically - Live ABOVE, BELOW, or INSIDE status in both dashboards - Supports NYSE, LSE, and TSE session presets plus custom hours Candlestick Pattern Detection — 14 Patterns - Bullish Engulfing and Bearish Engulfing - Hammer and Shooting Star - Morning Star and Evening Star - Inside Bar, Tweezer Top, and Tweezer Bottom - Doji, Dragonfly Doji, and Gravestone Doji - Liquidity Sweep High and Liquidity Sweep Low Phase 2 — Advanced Analytics - Trend Strength Score (TSS): 0 to 100 composite score across 5 weighted components - Trade Probability Score (TPS): 0 to 100 score across 12 weighted factors — shows High Probability, Good Setup, Neutral, or Avoid - Liquidity Sweep Detection: identifies stop-hunt wicks above swing highs and below swing lows - Relative Strength: compares intraday return vs up to 2 configurable benchmarks (default: QQQ and SPY) - Volatility State: BB/KC classification showing SQUEEZE, NORMAL, or EXPANSION Automated Risk Management - Auto-calculated Stop Loss from entry using UT Bot stop, Supertrend, VWAP, MA200, and Donchian floor in priority order - Auto Take Profit lines at R1, R1.5, R2, and R3 - Freeze TP when touched — preserves hit targets even after price retraces - Lines limited to 10 bars to keep the chart clean One-Click Stock Presets - Pre-calibrated settings for NVDA, AAPL, AMD, TSLA, and META - Each preset sets the optimal UT Bot sensitivity, ATR period, swing filter, ADX filter, volume filter, and Supertrend multiplier for that ticker Alerts - Four built-in alert conditions: Momentum Buy, Momentum Sell, Base Long, and Base Short - Real-time alert option for immediate webhook or push notification on UT Bot flip 🔶 HOW IT WORKS — THE SIGNAL STACK The indicator uses a layered confluence approach. Follow this five-step workflow: Step 1 — Check the Bias Table Look at the BIAS INDICATOR table in the top-right corner. Check the AVG column. Six or more rows showing Y for your direction means market structure is aligned. Step 2 — Wait for a UT Bot Label The core entry trigger is a Buy or Sell label from the adaptive trailing stop. This fires when the stop flips direction with volume confirmation. It is your primary entry signal. Step 3 — Confirm with Supertrend and MACD Check that Supertrend direction agrees (green = bullish) and that MACD is above the Signal line. Step 4 — Check Your Score Look at the Trade Probability Score in the bottom-right dashboard. 80+ is high probability. 60 to 79 is a good setup. Below 40 is avoid. Step 5 — Use the Suggested Stop Loss An automated Stop Loss line appears below entry for longs and above entry for shorts. Take Profit lines at R1, R2, and R3 are plotted automatically. 🔶 THE BIAS TABLE — DETAILED The Bias Table evaluates every row independently on each selected timeframe: - 3 Day Bias — close today vs close 3 trading days ago - Weekly Bias — close today vs close 5 trading days ago - Monthly Bias — close today vs close 21 trading days ago - Quarterly Bias — close today vs close 13 weeks ago - VIX Fear Index — below 18 is BULLISH, 18 to 22 is NEUTRAL, above 22 is BEARISH - Opening Range Breakout — shows ABOVE, BELOW, or INSIDE the active OR window - Fast MA above Slow MA — EMA(10) vs EMA(20) evaluated per timeframe - Price above MA200 — whether price is above the 200-period MA per timeframe - Price above VWAP — whether price is above VWAP per timeframe - MACD above Signal — whether MACD line is above Signal line per timeframe - Supertrend — 1 = Bullish, -1 = Bearish, 0 = Neutral flip zone - ZLSMA Rising — whether the ZLSMA is sloping upward - RSI In Zone — classic 30/70 bands or your custom buy/sell range - ADX at or above Minimum — whether ADX exceeds your configured threshold A reading of 75% or higher in the AVG column is a high-conviction directional setup. 🔶 TRADE PROBABILITY SCORE — FACTOR BREAKDOWN - MTF Alignment — 20 points — average bullish percentage across active timeframes - EMA Stack — 10 points — Fast above Medium above Long MA - VWAP Location — 8 points — price above session VWAP - Price above MA200 — 7 points — price above the 200-period MA - MACD Alignment — 8 points — MACD line above Signal line - Supertrend Direction — 10 points — Supertrend in bullish state - ADX Strength — 8 points — 20 = 4pts, 30 = 6pts, 40 = 8pts - Relative Volume — 7 points — 1.0x = 3pts, 1.5x = 5pts, 2.0x = 7pts - ORB Status — 7 points — price above the opening range - RS vs Benchmark — 5 points — outperforming QQQ or custom symbol - Volatility State — 5 points — Normal or Expansion preferred - Key Level Proximity — 5 points — above Pivot S1 and below Pivot R1 Score interpretation: - 80 to 100 — HIGH PROBABILITY — enter with confidence - 60 to 79 — GOOD SETUP — valid trade, standard position sizing - 40 to 59 — NEUTRAL — reduce size or wait for improvement - 0 to 39 — AVOID — conditions are not aligned 🔶 RECOMMENDED ENTRY CHECKLIST - Bias Table shows 70% or higher agreement in your direction - UT Bot Buy or Sell label confirmed on bar close - Supertrend agrees with the signal direction - MACD above Signal for longs / below Signal for shorts - Price above VWAP for longs / below VWAP for shorts - VIX is BULLISH or NEUTRAL — not BEARISH for long trades - ADX is 20 or higher — trend is strong enough to trade - Trade Probability Score is 60 or higher All eight checked = maximum confluence. Six or more = tradeable with standard risk. Fewer than five = wait for a better setup. 🔶 BEST TIMEFRAMES AND TRADING STYLES - Scalping — 1-minute or 5-minute chart - Day Trading — 5-minute or 15-minute chart - Swing Trading — 1-hour or 4-hour chart - Position Trading — Daily chart The Bias Table always displays higher timeframe context regardless of your current chart timeframe. 🔶 SETTINGS OVERVIEW Moving Average Group — configure Fast, Medium, Medium-Long (optional), and Long MAs. Supports EMA, SMA, WMA, VWMA, RMA, and HMA. Defaults: EMA 10, EMA 20, SMA 200. VWAP Settings — toggle on/off, choose anchor period, configure up to three bands. MACD — set Fast, Slow, and Signal periods. Configure minimum MA distance and MACD separation filters. UT Bot Settings — sensitivity, ATR period, draw-on-close toggle, percentage change filter, swing filter, 2-bar confirmation, and ZLSMA filter. Stop Loss and Take Profit — toggle on/off, limit to 10 bars, extra tick protection, R1/R1.5/R2/R3 targets, and Freeze TP when touched. Supertrend — ATR period, ATR multiplier, neutral bars after flip, dynamic cap, and fill toggle. ADX Filter — require ADX at or above minimum with DI alignment before signals fire. RSI Filter — require RSI within custom pullback zones for longs and shorts. Bias Table — toggle all rows individually, select timeframes, configure position, text size, and background color. Phase 2 Settings: - TREND AND TRADE SCORES — toggle TSS and TPS in the dashboard - LIQUIDITY SWEEPS — configure lookback bars, minimum wick size, and bar-close gate - RELATIVE STRENGTH — configure Benchmark 1 and Benchmark 2 symbols - VOLATILITY STATE — configure BB and KC lengths and multipliers Stock Presets — one-click setup for NVDA, AAPL, AMD, TSLA, or META. 🔶 IMPORTANT NOTES - Enable "Draw visuals only on bar close" in UT Bot settings to prevent real-time repainting - The 3 Day, Weekly, Monthly, and Quarterly Bias rows are hidden on futures and charts with fewer than 5,000 bars - The Bias Table automatically switches to D, W, and M columns on Daily, Weekly, or Monthly charts - All request.security() calls are consolidated to 22 total, within TradingView's limit of 40 - Phase 2 Liquidity Sweep labels are gated on bar close by default to prevent repainting 🔶 CONCLUSION Lucky: MTF Trend & Breakout Dashboard was built to be the only trend indicator you need on your chart. It combines the entry precision of the UT Bot, the directional context of Supertrend, the multi-timeframe intelligence of the Bias Table, and the risk management of automated SL/TP levels — and scores the entire setup objectively from 0 to 100 before you pull the trigger. This is a free release. If it helps your trading, follow the author to be notified of future indicators and strategy tools. Past performance is not indicative of future results. All signals should be used with proper risk management and your own independent analysis. 🔶 CREDITS AND INSPIRATION This indicator was inspired by "Luxy Momentum, Trend, Bias and Breakout Indicators V7" by TradingView user orenluxy , whose original work introduced me to the concept of combining a multi-timeframe bias table with UT Bot signals and a price point dashboard in a single overlay. The Lucky MTF Trend & Breakout Dashboard is a ground-up rewrite in Pine Script v6 with significant architectural changes and new systems including the Trade Probability Score, Trend Strength Score, Liquidity Sweeps, Relative Strength, Volatility State, candlestick patterns, one-click stock presets, and automated SL/TP — but the creative spark came from orenluxy's work, and that deserves to be acknowledged. If you enjoy this indicator, I encourage you to also check out the original by searching orenluxy on TradingView.
Pine Script® インジケーター
HelixStratの投稿
13
Adaptive SuperTrend Oscillator [QuantAlgo]🟢 Overview The Adaptive SuperTrend Oscillator transforms the classic SuperTrend indicator into a normalized momentum score that adapts to changing market conditions. Instead of displaying a simple above/below signal on the price chart, it measures how far price has moved from the SuperTrend line and scales that distance against an Efficiency Ratio-driven ATR that automatically adjusts between trending and ranging environments. The result is a centered oscillator with dynamically calculated overbought and oversold thresholds, helping traders read the strength behind a trend rather than just its direction, across different markets and timeframes. 🟢 How It Works The foundation of the indicator is the distance between the closing price and the SuperTrend line: = ta.supertrend(active_multiplier, active_atr_length) price_distance = close - supertrend_line A positive distance means price is above the SuperTrend line, indicating a bullish condition. A negative distance indicates price is below it, reflecting a bearish condition. The raw distance alone is not directly comparable across instruments or timeframes, so the indicator normalizes it using an adaptive ATR. The normalization layer is driven by an Efficiency Ratio, which measures how directionally efficient recent price movement has been. It compares the net price change over the lookback window against the total path length traveled: price_change = math.abs(close - close ) path_length = math.sum(math.abs(close - close ), active_er_length) efficiency_ratio = path_length != 0 ? price_change / path_length : 0.0 A high Efficiency Ratio means price is moving in a consistent direction with little back-and-forth. A low ratio indicates choppy, non-directional movement. This reading is then used to blend between a fast and slow ATR period: adaptive_atr = efficiency_ratio * ta.atr(active_norm_fast) + (1.0 - efficiency_ratio) * ta.atr(active_norm_slow) score = adaptive_atr != 0 ? price_distance / adaptive_atr * 100 : 0.0 During trending conditions the fast ATR period is weighted more heavily, allowing the score to move more freely. During choppy conditions the slow ATR period dominates, dampening the score and reducing low-conviction readings. The final score is expressed as a percentage of the adaptive ATR, making it directly comparable across different instruments and volatility environments. Overbought and oversold levels are derived dynamically from the rolling standard deviation of the score itself rather than fixed values: score_deviation = ta.stdev(score, 100) ob_extreme = score_deviation * 3 ob_level = score_deviation * 2 os_level = -score_deviation * 2 os_extreme = -score_deviation * 3 This means the threshold levels expand during volatile periods and contract during quiet ones, keeping the overbought and oversold zones statistically consistent relative to recent score behavior. 🟢 Signal Interpretation ▶ Bullish Trend (Score Above Zero, Outside Neutral Zone, Green): When the score is positive and exceeds the neutral threshold, the oscillator confirms that price is above the SuperTrend line and momentum is directionally efficient enough to register. The score's gradient intensity reflects how far momentum has extended relative to the adaptive ATR baseline. The trend remains bullish until the score crosses back below zero or into the neutral zone. ▶ Bearish Trend (Score Below Zero, Outside Neutral Zone, Red): When the score is negative and falls below the neutral threshold, the oscillator confirms that price is below the SuperTrend line. A deeper negative score indicates stronger downside momentum relative to the normalization baseline. The trend remains bearish until the score crosses back above zero or into the neutral zone. ▶ Neutral Zone (Score Within Threshold, Grey): When the absolute score value is within the neutral threshold, the oscillator treats the reading as non-directional regardless of which side of zero it sits on. This filters out low-conviction conditions where the SuperTrend distance is small relative to the adaptive ATR, preventing the indicator from registering trend signals during consolidation or choppy price action. ▶ Overbought and Oversold Levels (2σ and 3σ Bands): When the score reaches the 2σ or 3σ bands, it indicates that momentum has extended significantly relative to its own recent history. These are not reversal signals by themselves, but they mark zones where the trend is stretched and worth monitoring for potential exhaustion. 🟢 Features ▶ Preconfigured Presets: Three parameter sets cover different trading approaches. "Default" uses moderate SuperTrend sensitivity for swing trading on 4-hour and daily charts. "Fast Response" tightens the SuperTrend bands and shortens normalization windows for intraday use on 5-minute to 1-hour charts. "Smooth Trend" widens the SuperTrend bands and extends normalization windows for position trading on daily and weekly timeframes. ▶ Built-in Alerts: Seven alert conditions cover the full range of oscillator states. Trend transition alerts fire when the score crosses into bullish, bearish, or neutral territory. Separate alerts trigger when the score reaches the 2σ overbought or oversold levels and again when it reaches the more extreme 3σ levels, enabling graduated monitoring without requiring constant chart observation. ▶ Visual Customization: Six color presets (Classic, Aqua, Cosmic, Cyber, Neon, plus Custom) coordinate colors across the score line, ribbon fills, overbought/oversold bands, and optional bar coloring. The ribbon uses three fill layers between the score line and zero, each at increasing transparency, creating a gradient that visually represents the weight of momentum behind the current reading. Optional bar coloring applies trend state colors directly to price bars for quick multi-timeframe reference.
Pine Script® インジケーター
QuantAlgoの投稿
2