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BB Squeeze - HighQTools BBW Squeeze — HighQTools As always, if anyone has any tips or additional features they'd like to see, feel free to reach out! Overview The BBW Percentile Squeeze highlights periods of exceptionally compressed volatility by measuring Bollinger Band Width (BBW) and ranking it within a rolling historical percentile. When BBW falls into the lowest portion of its own distribution, price is statistically “tight” relative to recent history—a condition that often precedes volatility expansion. Instead of plotting an oscillator in a separate pane, this tool expresses information directly on the price chart by changing bar colors during squeeze conditions, keeping charts clean and execution-focused. How It Works Standard Bollinger Bands are calculated using a configurable length and standard deviation. Band width is normalized and evaluated against a rolling lookback window. The current width is converted into a percentile rank (0–100): Lower percentile = tighter volatility Higher percentile = expanded volatility When the percentile drops below the user-defined threshold, the market is considered to be in a squeeze. An optional RTH-only mode allows the percentile calculation to consider Regular Trading Hours bars only, which is especially useful for futures traders who want to ignore overnight volatility distortions. Visual Signals Squeeze Bars Bars are recolored when BBW percentile falls below the selected threshold, indicating extreme compression. Release Bar (optional) The first bar exiting the squeeze can be highlighted separately, marking the resolution of compression. No oscillator, no bands, no shapes—only context applied directly to price. How to Use It The squeeze itself is not a trade signal. Squeeze conditions indicate stored energy—expect range expansion, not direction. Focus on: Market structure Higher-timeframe context Volume, delta, or acceptance/rejection The release from squeeze often provides the best opportunity, especially when aligned with directional bias or structural breaks. For best results, use this tool as a context filter alongside execution setups rather than as a standalone entry signal. Recommended Settings BB Length: 10 Std Dev: 2.0 Percentile Lookback: 200–300 bars Squeeze Threshold: 5-10 percentile RTH-only: Enabled for index futures Disclaimer This indicator is designed to provide context, not predictions. Always combine volatility information with sound risk management and a complete trading plan.

อินดิเคเตอร์ Pine Script®

โดย HighQTools

Market Acceptance Envelope [Interakktive]The Market Acceptance Envelope (MAE) is a diagnostic tool that shows where price statistically belongs — not where it might go. Unlike traditional bands that expand with volatility, MAE expands with acceptance: regions where price rotates comfortably, efficiency drops, and the market agrees on fair value. This is the anti-Bollinger thesis: bands should represent where price IS accepted, not where it MIGHT reach based on standard deviation. █ USAGE The filled corridor represents the current acceptance zone — where price has demonstrated rotational behavior with low directional efficiency. When price is inside the corridor, it's "home." When outside, it's exploring territory the market hasn't yet accepted. For discretionary traders, MAE provides instant context: "Is price where it belongs, or is it extended?" For systematic traders, the exported values (confidence, asymmetry, position) can inform position sizing and filter logic. █ ACCEPTANCE CENTROID Unlike traditional bands centered on a moving average, MAE uses an Acceptance Centroid — a time-weighted price level where acceptance behavior concentrates. The centroid is calculated by weighting price by: • Inverse efficiency (low efficiency = high acceptance) • Volatility stability (stable vol = higher weight) • Dwell factor (time spent near level) This means the centroid drifts toward where price actually rotates, not simply where it averages. █ ASYMMETRIC BOUNDARIES MAE calculates upper and lower boundaries independently. Markets rarely treat up and down equally — during uptrends, the upper boundary may be wider (more accepted upside exploration), while the lower boundary stays tight (quick rejection of dips). This asymmetry is visible on the chart and exported as a metric (-1 to +1). █ CONFIDENCE-BASED VISIBILITY The corridor's opacity reflects acceptance confidence: • High confidence → clearly visible corridor (price is in accepted rotation) • Low confidence → faded corridor (trending/directional market, acceptance not established) When the corridor fades, it's telling you: "Acceptance hasn't been earned here yet." █ WHAT THIS INDICATOR IS • A diagnostic acceptance envelope showing where price statistically belongs • Asymmetric by design — upper and lower calculated independently • Confidence-weighted visibility — fades when acceptance is not earned • Non-repainting — uses closed-bar data only █ WHAT THIS INDICATOR IS NOT • NOT Bollinger Bands (no standard deviation around a mean) • NOT Keltner Channels (no ATR-scaled envelope) • NOT a signal generator — no touches = signals philosophy • NO arrows, NO entries/exits, NO buy/sell recommendations █ HOW IT WORKS MAE uses an acceptance-weighted calculation approach: 1. ACCEPTANCE WEIGHT Each bar receives a weight based on: • Efficiency: (1 - efficiency) — low efficiency = rotational = high acceptance • Volatility Stability: stable vol environment = higher weight • Dwell Factor: price staying near central tendency = higher weight 2. ACCEPTANCE CENTROID Weighted average of price using acceptance weights: centroid = Σ(price × weight) / Σ(weight) Smoothed adaptively — faster during drift, slower when stable. 3. ASYMMETRIC BOUNDARIES Upper and lower distances calculated separately: • rngUp = acceptance-weighted average of (price - centroid) when price > centroid • rngDn = acceptance-weighted average of (centroid - price) when price < centroid 4. CONFIDENCE SCORE Composite of average acceptance weight, volatility stability, and centroid stability. Maps to corridor opacity: high confidence = visible, low confidence = faded. █ SETTINGS Market Acceptance Envelope — Core • Acceptance Lookback (20): Bars to evaluate for acceptance conditions. Higher = smoother, slower response. • Preset (Swing): Scalper = tight/fast, Swing = balanced, Position = wide/stable. • Envelope Sensitivity (1.0): Width multiplier. Higher = wider corridor. Market Acceptance Envelope — Visuals • Show Corridor (true): Display the acceptance corridor. • Show Centroid (false): Display the acceptance centroid line. Market Acceptance Envelope — Data Window • Show Data Window Values (false): Export MAE metrics for external use. █ EXPORTED VALUES When Data Window is enabled: • mae_upper: Upper boundary value • mae_lower: Lower boundary value • mae_centroid: Acceptance centroid value • mae_width: Corridor width (upper - lower) • mae_asymmetry: Asymmetry ratio (-1 to +1, negative = lower wider) • mae_confidence: Acceptance confidence (0-100) • mae_position: Price position (-1 = below, 0 = inside, +1 = above) █ SUITABLE MARKETS Works on all markets: Stocks, Futures, Forex, Crypto, Indices. Works on all timeframes. Higher timeframes show more stable acceptance zones. █ DISCLAIMER This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management. This is a diagnostic tool — it provides context, not signals.

อินดิเคเตอร์ Pine Script®

โดย Interakktive

ที่อัปเดต:

Hurst-Optimized Adaptive Channel [Kodexius]Hurst-Optimized Adaptive Channel (HOAC) is a regime-aware channel indicator that continuously adapts its centerline and volatility bands based on the market’s current behavior. Instead of using a single fixed channel model, HOAC evaluates whether price action is behaving more like a trend-following environment or a mean-reverting environment, then automatically selects the most suitable channel structure. At the core of the engine is a robust Hurst Exponent estimation using R/S (Rescaled Range) analysis. The Hurst value is smoothed and compared against user-defined thresholds to classify the market regime. In trending regimes, the script emphasizes stability by favoring a slower, smoother channel when it proves more accurate over time. In mean-reversion regimes, it deliberately prioritizes a faster model to react sooner to reversion opportunities, similar in spirit to how traders use Bollinger-style behavior. The result is a clean, professional adaptive channel with inner and outer bands, dynamic gradient fills, and an optional mean-reversion signal layer. A minimalist dashboard summarizes the detected regime, the current Hurst reading, and which internal model is currently preferred. 🔹 Features 🔸 Robust Regime Detection via Hurst Exponent (R/S Analysis) HOAC uses a robust Hurst Exponent estimate derived from log returns and Rescaled Range analysis. The Hurst value acts as a behavioral filter: - H > Trend Start threshold suggests trend persistence and directional continuation. - H < Mean Reversion threshold suggests anti-persistence and a higher likelihood of reverting toward a central value. Values between thresholds are treated as Neutral, allowing the channel to remain adaptive without forcing a hard bias. This regime framework is designed to make the channel selection context-aware rather than purely reactive to recent volatility. 🔸 Dual Channel Engine (Fast vs Slow Models) Instead of relying on one fixed channel, HOAC computes two independent channel candidates: Fast model: shorter WMA basis and standard deviation window, intended to respond quickly and fit more reactive environments. Slow model: longer WMA basis and standard deviation window, intended to reduce noise and better represent sustained directional flow. Each model produces: - A midline (basis) - Outer bands (wider deviation) - Inner bands (tighter deviation) This structure gives you a clear core zone and an outer envelope that better represents volatility expansion. 🔸 Rolling Optimization Memory (Model Selection by Error) HOAC includes an internal optimization layer that continuously measures how well each model fits current price action. On every bar, each model’s absolute deviation from the basis is recorded into a rolling memory window. The script then compares total accumulated error between fast and slow models and prefers the one with lower recent error. This approach does not attempt curve fitting on multiple parameters. It focuses on a simple, interpretable metric: “Which model has tracked price more accurately over the last X bars?” Additionally: If the regime is Mean Reversion, the script explicitly prioritizes the fast model, ensuring responsiveness when reversals matter most. 🔸 Optional Output Smoothing (User-Selectable) The final selected channel can be smoothed using your choice of: - SMA - EMA - HMA - RMA This affects the plotted midline and all band outputs, allowing you to tune visual stability and responsiveness without changing the underlying decision engine. 🔸 Premium Visualization Layer (Inner Core + Outer Fade) HOAC uses a layered band design: - Inner bands define the core equilibrium zone around the midline. - Outer bands define an extended volatility envelope for extremes. Gradient fills and line styling help separate the core from the extremes while staying visually clean. The midline includes a subtle glow effect for clarity. 🔸 Adaptive Bar Tinting Strength (Regime Intensity) Bar coloring dynamically adjusts transparency based on how far the Hurst value is from 0.5. When market behavior is more decisively trending or mean-reverting, the tint becomes more pronounced. When behavior is closer to random, the tint becomes more subtle. 🔸 Mean-Reversion Signal Layer Mean-reversion signals are enabled when the environment is not classified as Trending: - Buy when price crosses back above the lower outer band - Sell when price crosses back below the upper outer band This is intentionally a “return to channel” logic rather than a breakout logic, aligning signals with mean-reversion behavior and avoiding signals in strongly trending regimes by default. 🔸 Minimalist Dashboard (HUD) A compact table displays: - Current regime classification - Smoothed Hurst value - Which model is currently preferred (Fast or Slow) - Trend flow direction (based on midline slope) 🔹 Calculations 1) Robust Hurst Exponent (R/S Analysis) The script estimates Hurst using a Rescaled Range approach on log returns. It builds a returns array, computes mean, cumulative deviation range (R), standard deviation (S), then converts RS into a Hurst exponent. calc_robust_hurst(int length) => float r = math.log(close / close ) float returns = array.new_float(length) for i = 0 to length - 1 array.set(returns, i, r ) float mean = array.avg(returns) float cumDev = 0.0 float maxCD = -1.0e10 float minCD = 1.0e10 float sumSqDiff = 0.0 for i = 0 to length - 1 float val = array.get(returns, i) sumSqDiff += math.pow(val - mean, 2) cumDev += (val - mean) if cumDev > maxCD maxCD := cumDev if cumDev < minCD minCD := cumDev float R = maxCD - minCD float S = math.sqrt(sumSqDiff / length) float RS = (S == 0) ? 0.0 : (R / S) float hurst = (RS > 0) ? (math.log10(RS) / math.log10(length)) : 0.5 hurst This design avoids simplistic proxies and attempts to reflect persistence (trend tendency) vs anti-persistence (mean reversion tendency) from the underlying return structure. 2) Hurst Smoothing Raw Hurst values can be noisy, so the script applies EMA smoothing before regime decisions. float rawHurst = calc_robust_hurst(i_hurstLen) float hVal = ta.ema(rawHurst, i_smoothHurst) This stabilized hVal is the value used across regime classification, dynamic visuals, and the HUD display. 3) Regime Classification The smoothed Hurst reading is compared to user thresholds to label the environment. string regime = "NEUTRAL" if hVal > i_trendZone regime := "TRENDING" else if hVal < i_chopZone regime := "MEAN REV" Higher Hurst implies more persistence, so the indicator treats it as a trend environment. Lower Hurst implies more mean-reverting behavior, so the indicator enables MR logic and emphasizes faster adaptation. 4) Dual Channel Models (Fast and Slow) HOAC computes two candidate channel structures in parallel. Each model is a WMA basis with volatility envelopes derived from standard deviation. Inner and outer bands are created using different multipliers. Fast model (more reactive): float fastBasis = ta.wma(close, 20) float fastDev = ta.stdev(close, 20) ChannelObj fastM = ChannelObj.new(fastBasis, fastBasis + fastDev * 2.0, fastBasis - fastDev * 2.0, fastBasis + fastDev * 1.0, fastBasis - fastDev * 1.0, math.abs(close - fastBasis)) Slow model (more stable): float slowBasis = ta.wma(close, 50) float slowDev = ta.stdev(close, 50) ChannelObj slowM = ChannelObj.new(slowBasis, slowBasis + slowDev * 2.5, slowBasis - slowDev * 2.5, slowBasis + slowDev * 1.25, slowBasis - slowDev * 1.25, math.abs(close - slowBasis)) Both models store their structure in a ChannelObj type, including the instantaneous tracking error (abs(close - basis)). 5) Rolling Error Memory and Model Preference To decide which model fits current conditions better, the script stores recent errors into rolling arrays and compares cumulative error totals. var float errFast = array.new_float() var float errSlow = array.new_float() update_error(float errArr, float error, int maxLen) => errArr.unshift(error) if errArr.size() > maxLen errArr.pop() Each bar updates both error histories and computes which model has lower recent accumulated error. update_error(errFast, fastM.error, i_optLookback) update_error(errSlow, slowM.error, i_optLookback) bool preferFast = errFast.sum() < errSlow.sum() This is an interpretable optimization approach: it does not attempt to brute-force parameters, it simply prefers the model that has tracked price more closely over the last i_optLookback bars. 6) Winner Selection Logic (Regime-Aware Hybrid) The final model selection uses both regime and rolling error performance. ChannelObj winner = regime == "MEAN REV" ? fastM : (preferFast ? fastM : slowM) rawMid := winner.mid rawUp := winner.upper rawDn := winner.lower rawUpInner := winner.upper_inner rawDnInner := winner.lower_inner In Mean Reversion, the script forces the fast model to ensure responsiveness. Otherwise, it selects the lowest-error model between fast and slow. 7) Optional Output Smoothing After the winner is selected, the script optionally smooths the final channel outputs using the chosen moving average type. smooth(float src, string type, int len) => switch type "SMA" => ta.sma(src, len) "EMA" => ta.ema(src, len) "HMA" => ta.hma(src, len) "RMA" => ta.rma(src, len) => src float finalMid = i_enableSmooth ? smooth(rawMid, i_smoothType, i_smoothLen) : rawMid float finalUp = i_enableSmooth ? smooth(rawUp, i_smoothType, i_smoothLen) : rawUp float finalDn = i_enableSmooth ? smooth(rawDn, i_smoothType, i_smoothLen) : rawDn float finalUpInner = i_enableSmooth ? smooth(rawUpInner, i_smoothType, i_smoothLen) : rawUpInner float finalDnInner = i_enableSmooth ? smooth(rawDnInner, i_smoothType, i_smoothLen) : rawDnInner This preserves decision integrity since smoothing happens after model selection, not before. 8) Dynamic Visual Intensity From Hurst Transparency is derived from the distance of hVal to 0.5, so stronger behavioral regimes appear with clearer tints. int dynTrans = int(math.max(20, math.min(80, 100 - (math.abs(hVal - 0.5) * 200))))

อินดิเคเตอร์ Pine Script®

โดย UnknownUnicorn113699460

ที่อัปเดต:

ORACLE v13: The Gamified Market HUD ORACLE v13 is not just an indicator; it is a complete Trading HUD (Heads-Up Display) that translates complex market data into an intuitive, video-game-style interface. It turns abstract concepts like "volatility" and "support/resistance" into actionable game mechanics, allowing you to react faster and trade smarter. ⚔️ Key Features: 🛡️ Boss & Shield Mechanics (Support/Resistance): Automatic detection of key levels visualized as "Bosses" (Resistance) and "Shields" (Support). HP System: Watch price "damage" these levels in real-time. When "Boss HP" hits zero, a breakout is imminent. 🔮 The Bestiary (Market Conditions): Instantly identifies the "Enemy Type" you are fighting: 🟢 SLIME: Squeeze zone (low volatility, prepare for a move). 👺 GOBLIN: Chop/Noise (high risk, avoid trading). 🐉 DRAGON: Strong Trend (ride the momentum). 👹 BERSERKER: Extreme Volatility (proceed with caution). 📈 Live Structure Mapping: Real-time ZigZag overlays with automatic HH/LL/LH/HL labels. Breakout Flash: Candles flash WHITE instantly when major structure or Boss levels are broken. 🎮 Combat Stats: Combo Counter: Tracks consecutive directional candles. Aggro Meter: Visualizes volume intensity. Loot Drop Rate: innovative metric calculating the probability of a profitable move based on current ATR. Momentum Bar: RPG-style health bar for trend strength. Why use ORACLE? Most indicators just draw lines. ORACLE gives you Context. It tells you exactly what kind of market environment you are in so you never bring a knife to a Dragon fight. Perfect for scalpers and day traders who need instant situational awareness. Settings: Fully customizable Lookback periods, ZigZag sensitivity, and Visual Themes.

อินดิเคเตอร์ Pine Script®

โดย O_A_O

ที่อัปเดต:

BBMA by RWBTradeLab BBMA by RWBTradeLab A clean, non-repainting BBMA indicator built for traders who combine Bollinger Bands with Linear Weighted Moving Averages and EMA to track volatility expansion, price extremes, and confirmed breakout behavior using closed candles only. What this indicator does This script combines Bollinger Bands (20, 2) with Linear Weighted Moving Averages (LWMA) and a 50 EMA to help traders identify high-probability price extension zones and confirmed BBMA break conditions—without repainting. All calculations and alerts are based strictly on closed candles (no running-bar signals). Core components Bollinger Bands *Period: 20 *Deviations: 2 *Apply to: Close *Visual shift supported (default 0) *Clean white band structure for clarity Linear Weighted Moving Averages (LWMA) *LW MA 5 Low *LW MA 10 Low *LW MA 5 High *LW MA 10 High These weighted averages react faster to recent price action and help define dynamic BBMA zones. Exponential Moving Average *EMA 50 *Apply to: Close *Method: Exponential Used as a higher-timeframe trend and structure reference. BBMA alert logic (closed candle only) Lower BBMA Break Triggered when: *LW MA 5 Low crosses below the Lower Bollinger Band *The candle closes below the Lower Bollinger Band *LW MA 5 Low remains below the Lower Bollinger Band after close Upper BBMA Break Triggered when: *LW MA 5 High crosses above the Upper Bollinger Band *The candle closes above the Upper Bollinger Band *LW MA 5 High remains above the Upper Bollinger Band after close ⚠️ No alerts are generated on running candles—only on confirmed bar close. Visuals on chart *Bollinger Bands plotted in clean white *LW MAs color-coded for easy distinction *EMA 50 plotted in green *Optional show/hide toggles for BB, LW MAs, and EMA Alerts Built-in alerts trigger only on candle close: *BBMA Lower Break (confirmed) *BBMA Upper Break (confirmed) Designed for reliable discretionary trading and automation without repainting issues. Key settings *BB Period & Deviations *LW MA periods (5 & 10, High / Low) *EMA period *Visual shift for Bollinger Bands *Individual visibility toggles Non-repainting confirmation All calculations, plots, and alerts are based on confirmed candles only. No running-bar logic → no repainting. Disclaimer This indicator is a technical analysis tool, not financial advice. Trading involves risk—always use proper risk management and confirm signals with your own analysis. Creator: RWBTradeLab If you find this indicator useful, please leave a like ⭐ and share your feedback.

อินดิเคเตอร์ Pine Script®

โดย RWBTradeLab

ที่อัปเดต:

INAZUMA Bollinger Bands This is an indicator based on the widely used Bollinger Bands, enhanced with a unique feature that visually emphasizes the "strength of the breakout" when the price penetrates the bands. Main Features and Characteristics 1. Standard Bollinger Bands Display Center Line (Basis): Simple Moving Average (\text{SMA(20)}). 1 sigma Lines: Light green (+) and red (-) lines for reference. 2 sigma Lines (Upper/Lower Band): The main dark green (+) and red (-) bands. 2. Emphasized Breakout Zones: "INAZUMA / Flare" and "MAGMA" The key feature is the activation of colored, expanding areas when the candlestick's High or Low breaks significantly outside the \pm 2\sigma bands. Upper Side (Green Base / Flare): When the High exceeds the +2\sigma line, a green gradient area expands upwards. Indication: This visually suggests strong buying pressure or overbought conditions. The color deepens as the price moves further away, indicating higher momentum. Lower Side (Red Base / Magma): When the Low falls below the -2 sigma line, a red gradient area expands downwards. Indication: This visually suggests strong selling pressure or oversold conditions. The color deepens as the price moves further away, indicating higher momentum. Key Insight: This visual aid helps traders quickly assess the momentum and market excitement when the price moves outside the standard Bollinger Bands range. Use it as a reference for judging trend strength and potential entry/exit points. Customizable Settings You can adjust the following parameters in the indicator settings: Length: The period used for calculating the Moving Average and Standard Deviation. (Default: 20) StdDev (Standard Deviation): The multiplier for the band width (e.g., 2.0 for -2 sigma). (Default: 2.0) Source: The price data used for calculation (Default: close).

อินดิเคเตอร์ Pine Script®

โดย maru_jp

RSI Multi Levels kiawosch [TradingFinder] 7-14-42 Consolidation 🔵 Introduction The Relative Strength Index or RSI is a tool used to measure the speed and intensity of price movement, oscillating between zero and one hundred. It is commonly applied to identify strength or weakness in market momentum across different time intervals. Despite its simple formula and wide usage, the behavior of RSI within specific ranges often provides more precise information than traditional overbought and oversold levels. The Multi RSI layout displays three RSI values with periods 7, 14 and 42. The seven period RSI plays the primary role in short term analysis. When this value enters predefined ranges, it shows highly consistent and interpretable behavior that can signal trend continuation, corrections or the start of a range structure. The other two values, RSI 14 and RSI 42, help reveal higher timeframe momentum and provide context for the depth and quality of price movement. Three potential zones are defined, each representing a behavioral range. The position zones forms the basis for signal interpretation : High Potential : 78 to 85 & 22 to 15 Mid Potential : 70 to 78 & 30 to 22 Low Potential : 58 to 62 & 42 to 38 These zones highlight areas where RSI reacts in specific ways to price movement. Entering the High Potential range usually aligns with new highs or lows in price and often precedes continuation after a correction. In contrast, reactions inside the Mid Potential range frequently appear during clean ranges or channel structures. This approach focuses on momentum quality and structural behavior rather than classic overbought and oversold thresholds. In summary, the logic behind the signals follows three principles : Trend continuation, When RSI 7 enters the High Potential zone and price prints a new high or low, continuation after a correction becomes the most likely outcome. Reversal or slowdown, When RSI exits the High Potential zone while price is reaching a previous high or low, the probability of a short term reversal increases. Range behavior, In clean ranges or channel structures, RSI 7 typically reacts inside the Mid Potential zone and produces consistent swing responses. 🔵 How to Use This method is based on observing the repeating behavior of RSI within momentum zones and identifying moments when price continues after a shallow correction or, conversely, when signs of slowing and reversal appear. RSI 7 plays the main role since it gives the most sensitive response to short term price changes. Its entry into or exit from a potential zone, combined with the position of price relative to recent highs and lows, forms the core of the signal logic. RSI 14 and RSI 42 provide higher timeframe confirmation and help evaluate the broader strength or weakness behind each movement. 🟣 Trend continuation after entering the High Potential zone When RSI 7 reaches the High Potential zone while price forms a new high or low, the probability of continuation becomes very high. The typical sequence includes a short correction in price and a retreat of RSI toward the Mid Potential zone. As long as price structure remains intact and RSI turns upward again, continuation becomes the most likely scenario. As shown in the charts, price often expands strongly after this type of correction and breaks the previous high. 🟣 Reversal or slowdown after exiting the High Potential zone If RSI 7 enters the High Potential zone but then exits while price is interacting with a previous high or low, conditions for a short term reversal appear. This behavior is clear in the charts, where price hits a supply or demand area and RSI can no longer return to the upper zone. The drop in RSI reflects weakening momentum and, when accompanied by a confirming candle, increases the chance of a reversal or at least a temporary pause. 🟣 Strong reversal after hitting the Mid Potential zone during deeper corrections Sometimes price enters a deeper corrective phase and RSI 7 moves into or through the Mid Potential zone. When this occurs near a previous low, it can mark the start of a significant reversal. The charts show this pattern clearly, where RSI turns upward while price reacts to support. If the other RSI values show relative alignment, the probability of a strong rebound increases. This signal is often seen after fast declines and can mark the beginning of a recovery wave. 🟣 Range structure and repetitive reactions inside the Mid Potential zone When price enters a clean range or channel, the behavior of RSI 7 changes completely. In such conditions, RSI repeatedly reacts inside the Mid Potential zone. Each time price touches the upper or lower boundary of the range, RSI approaches the upper or lower part of this zone as well. The result is a sequence of predictable swing reactions, perfectly suitable for mean reversion strategies. Breakouts in these environments also tend to show higher failure rates. 🟣 Sharp reactions and fast reversals at extreme levels (RSI near 90 or below 10) Although this approach is not based on classic overbought and oversold logic, extremely high or low RSI readings such as ninety often produce strong immediate reactions in price. These conditions usually occur after sudden spikes or emotional breakouts. As visible in the charts, RSI collapses quickly after reaching such extremes and price often reverses sharply. While not a core signal, these moments add meaningful context to momentum interpretation. 🔵 Settings RSI Setting : This section allows enabling or disabling the three RSI values, adjusting their calculation length and customizing their colors. It is designed to help separate short, medium and longer term momentum visually on the chart. Zones Setting : This section controls the display of momentum zones and the color applied to each area. Adjusting these colors or toggling them on and off helps the trader visually track the intensity and structure of momentum. Levels Setting : This section allows editing the numeric boundaries of the levels or showing and hiding each one individually. These levels form the visual framework for interpreting RSI behavior within the defined momentum zones. 🔵 Conclusion Examining RSI behavior across different momentum zones shows that entering these ranges creates relatively consistent patterns in price movement. Reaching the High Potential zone often corresponds to later stages of a trend, where price has the strength to continue after a brief correction and structure remains intact. In contrast, reactions within the Mid Potential zone occur more frequently when the market transitions into a range or a limited movement phase, where repetitive oscillations dominate. Overall, observing RSI inside these zones helps distinguish between trending movement, corrective phases and range conditions with greater clarity. Entry or exit from each zone provides insight into the underlying strength or weakness of momentum and reveals where the market is positioned within its movement cycle. This perspective, based on momentum regions rather than traditional values alone, offers a more refined understanding of price behavior and highlights the likely direction of the next move.

อินดิเคเตอร์ Pine Script®

โดย TFlab

IDLP - Intraday Daily Levels Pro [FXSMARTLAB]🔥 IDLP – Intraday Daily Levels Pro IDLP – Intraday Daily Levels Pro is a precision toolkit for intraday traders who rely on objective daily structure instead of repainting indicators and noisy signals. Every level plotted by IDLP is derived from one simple rule: Today’s trading decisions must be based on completed market data only. That means: ✅ No use of the current day’s unfinished data for levels ✅ No lookahead ✅ No hidden repaint behavior IDLP reconstructs the previous trading day from the intraday chart and then projects that structure forward onto the current session, giving you a stable, institutional-style intraday map. 🧱 1. Previous Daily Levels (Core Structure) IDLP extracts and displays the full previous daily structure, which you can toggle on/off individually via the inputs: Previous Daily High (PDH) Previous Daily Low (PDL) Previous Daily Open Previous Daily Close, Previous Daily Mid (50% of the range) Previous Daily Q1 (25% of the range) Previous Daily Q3 (75% of the range) All of these come from the day that just closed and are then locked for the entire current session. What these levels tell you: PDH / PDL – true extremes of yesterday’s price action (liquidity zones, breakout/reversal points). Previous Daily Open / Close – how the market positioned itself between session start and end Mid (50%) – equilibrium level of the previous day’s auction. Q1 / Q3 (25% / 75%) internal structure of the previous day’s range, dividing it into four equal zones and helping you see if price is trading in the lower, middle, or upper quarter of yesterday’s range. All these levels are non-repaint: once the day is completed, they are fixed and never change when you scroll, replay, or backtest. 🎯 2. Previous Day Pivot System (P, S1, S2, R1, R2) IDLP includes a classic floor-trader pivot grid, but critically: It is calculated only from the previous day’s high, low, and close. So for the current session, the following are fixed: Pivot P – central reference level of the previous day. Support 1 (S1) and Support 2 (S2) Resistance 1 (R1) and Resistance 2 (R2) These levels are widely used by institutional desks and algos to structure: mean-reversion plays, breakout zones, intraday targets, and risk placement. Everything in this section is non-repaint because it only uses the previous day’s fully closed OHLC. 📏 3. 1-Day ADR Bands Around Previous Daily Open Instead of a multi-day ADR, IDLP uses a pure 1-Day ADR logic: ADR = Range of the previous day ADR = PDH − PDL From that, IDLP builds two clean bands centered around the previous daily Open: ADR Upper Band = Previous Day Open + (ADR × Multiplier) ADR Lower Band = Previous Day Open − (ADR × Multiplier) The multiplier is user-controlled in the inputs: ADR Multiplier (default: 0.8) This lets you choose how “tight” or “wide” you want the ADR envelope to be around the previous day’s open. Typical use cases: Identify realistic intraday extension targets, Spot exhaustion moves beyond ADR bands, Frame reversals after reaching volatility extremes, Align trades with or against volatility expansion Again, since ADR is calculated only from the completed previous day, these bands are totally non-repaint during the current session. 🔒 4. True Non-Repaint Architecture The internal logic of IDLP is built to guarantee non-repaint behavior: It reconstructs each day using time("D") and tracks: dayOpen, dayHigh, dayLow, dayClose for the current day prevDayOpen, prevDayHigh, prevDayLow, prevDayClose for the previous day At the moment a new day starts: The “current day” gets “frozen” into prevDay* These prevDay* values then drive: Previous Daily Levels, Pivots, ADR. During the current day: All these “previous day” values stay fixed, no matter what happens. They do not move in real time, they do not shift in replay. This means: What you see in the past is exactly what you would have seen live. No fake backtests. No illusion of perfection from repainting behavior. 🎯 5. Designed For Intraday Traders IDLP – Intraday Daily Levels Pro is made for: - Day traders and scalpers - Index and FX traders - Prop firm challenge trading - Traders using ICT/SMC-style levels, liquidity, and range logic - Anyone who wants a clean, institutional-style daily framework without noise You get: Previous Day OHLC Mid / Q1 / Q3 of the previous range Previous-Day Pivots (P, S1, S2, R1, R2) 1-Day ADR Bands around Previous Day Open All calculated only from closed data, updated once per day, and then locked.

อินดิเคเตอร์ Pine Script®

โดย FXSMARTLAB

Pro Bollinger Bands Strategy [Breno]This strategy excels in highly volatile financial instruments, including cryptocurrencies, high-beta stocks, commodity futures, and certain exchange-traded funds (ETFs) that exhibit clear mean-reversion characteristics around their Bollinger Bands. The system's ability to utilize scaling (position averaging) and an ATR-based stop loss makes it particularly effective in markets with significant price swings, allowing the trader to capture profits from price extremes while managing increased volatility-related risk. Core Strategy Logic This Strategy implements a comprehensive trend-following and mean-reversion strategy primarily leveraging the Bollinger Bands (BB) indicator for entry and exit signals, complemented by an Average True Range (ATR)-based Stop Loss mechanism and an optional EMA filter. It is designed with robust features for capital management, including configurable leverage and a sophisticated position averaging (scaling) system. Long Entry: A long position is initiated when the closing price crosses over the Lower Bollinger Band (ta.crossover(close,lowerBB)). This signals a potential mean-reversion opportunity following a price dip. Short Entry: A short position is initiated when the closing price crosses under the Upper Bollinger Band (ta.crossunder(close,upperBB)). (Note: Short entries are disabled by default in the script inputs). Exit Conditions (Profit Target): Long positions aim to exit upon interaction with the Upper Bollinger Band. Users can select from three exit methods: "Close When Touch": Exits when close≥upperBB. "Close Above then Below": Exits when the previous close was above the upper band, and the current close is below it (a reversal signal). "High Above": Exits when high>upperBB. The strategy features an optional profitOnly setting, which restricts all exits to only occur if the trade is currently in profit (i.e., close is above the strategy.position_avg_price for longs). Key Features and Customization Bollinger Bands & Filters - Customizable BB Parameters: The Length and Deviation of the Bollinger Bands are fully adjustable, allowing users to fine-tune the sensitivity of the entry and exit signals. Optional EMA Filter: An optional EMA Filter can be enabled to align entries with the prevailing trend, where a Long entry is only permitted if close≥EMA(EmaFilterRange). Risk and Capital Management - Equity Allocation: Position size is dynamically calculated based on a Percentage of Equity (capitalPerc) combined with the set Leverage multiplier. Dynamic Stop Loss (ATR-Based): An optional Stop Loss (SL) is calculated using a multiple (slAtrInput) of the Average True Range (ATR). The SL is set relative to the entry price upon trade activation, providing a volatility-adjusted risk management layer. Position Averaging (Scaling): The script supports the addition of multiple units (pyramiding) to an existing position based on three user-selected criteria: "No": No averaging. "Percent": Adds to the position if the price has dropped by a set percentage (addPct) from the average price. "ATR": Adds to the position if the current price is significantly below a calculated ATR-based support level from the average price.

กลยุทธ์ Pine Script®

โดย brenosilver

ที่อัปเดต:

Gold Fair Value [Alpha Extract]Gold-anchored Bitcoin fair value model is a macro-fundamental valuation indicator that anchors Bitcoin price assessment to gold market dynamics, establishing fair value zones through percentage change influence modelling and adaptive band multipliers. This overlay system provides institutional-grade context for identifying accumulation zones, distribution zones, and fair value equilibrium across all market cycles with minimal chart clutter through sophisticated gradient fill visualization. 🔶 Gold-Anchored Valuation Framework Establishes Bitcoin's theoretical fair value by integrating daily gold price movements into a smoothed asset baseline, applying percentage change calculations over configurable periods to measure gold's momentum influence. The system translates gold's relative strength or weakness into Bitcoin price expectations through adjustable influence multipliers, creating a dynamic fair value line that adapts to shifting macro-fundamental relationships between digital and traditional store-of-value assets. 🔶 Multi-Layer Statistical Band System Implements asymmetric upper and lower band multipliers applied to the fair value baseline, creating five distinct valuation zones: extreme overvaluation, moderate overvaluation, fair value equilibrium, moderate undervaluation, and extreme undervaluation. The asymmetric configuration (default 1.46x upper, 0.74x lower) reflects Bitcoin's historical tendency toward asymmetric volatility patterns with more violent upside moves and grinding downside action, optimizing zone accuracy for actionable trading decisions. 🔶 Gradient Fill Visualization Employs sophisticated transparency-based gradient fills between bands to create visually intuitive valuation heat maps, with darker orange shading indicating proximity to fair value and lighter shading showing extreme deviation zones. The system maintains chart readability by hiding individual band lines while preserving the filled zones, eliminating visual clutter while delivering maximum information density for rapid market assessment without overwhelming the trader with excessive line plots. 🔶 Historical Context & Position Management The lower band zones have historically preceded periods of constructive price behavior including consolidation phases and early-stage recovery rallies, while upper band interactions have preceded distribution and correction events. This historical pattern recognition enables traders to position proactively based on valuation extremes rather than reactively chasing momentum, supporting systematic accumulation during undervaluation periods and graduated profit-taking during overvaluation extremes. All analysis provided by Alpha Extract is for educational and informational purposes only. The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations.

อินดิเคเตอร์ Pine Script®

โดย AlphaExtract

Hyper Squeeze Sniper (Dual Side: Long + Short)Hyper Squeeze Sniper (Dual Side Strategy) This script is a comprehensive Volatility Breakout System designed to identify and trade explosive price moves following periods of consolidation. It combines the classical "Squeeze" theory with Linear Regression Momentum, Volume Analysis, and an ATR-based Trailing Stop to filter false signals and manage risk effectively. The script operates on a logic of "Compression -> Explosion -> Trend Following" suitable for both Long and Short positions. 🛠 Detailed Methodology (How it works) 1. The Squeeze Detection (Consolidation) The core concept relies on the relationship between Bollinger Bands (BB) and Keltner Channels (KC). Condition: When the Bollinger Bands (Standard Deviation) contract and fall inside the Keltner Channels (ATR based), it indicates a period of extremely low volatility (The Squeeze). Visual: The background turns Gray to indicate "Do Not Trade / Wait Mode". 2. Momentum Confirmation (Linear Regression) Instead of using standard lagging indicators, this script utilizes Linear Regression of the price deviation to determine the direction of the breakout. If the Linear Regression Slope > 0, the bias is Bullish. If the Linear Regression Slope < 0, the bias is Bearish. 3. Volume Validation To avoid fake breakouts, a Volume Spike filter is applied. A signal is only valid if the current volume exceeds its moving average by a defined multiplier (Default x1.2). 4. Risk Management: ATR Trailing Stop Once a trade is entered, the script calculates a dynamic Trailing Stop based on the Average True Range (ATR). - Long: The stop line trails below the price and never moves down. - Short: The stop line trails above the price and never moves up. - Exit: The position is closed immediately when the price breaches this volatility-based safety line. How to Use 1. Wait: Look for the Gray Background. This is the accumulation phase. 2. Entry: LONG: Wait for a Green Triangle ▲ (Price breaks Upper BB + Vol Spike + Bullish Momentum). SHORT: Wait for a Red Triangle ▼ (Price breaks Lower BB + Vol Spike + Bearish Momentum). 3. Exit: Close the position when the "X" mark appears or when candles cross the trailing safety line. Settings - BB Length/Mult: Adjust the sensitivity of the squeeze detection. - Vol Spike Factor: Increase this to filter out low-volume breakouts. - ATR Period/Mult: Adjust the trailing stop distance (Higher = Wider stop for swing trading).

อินดิเคเตอร์ Pine Script®

โดย Gustav_Rex

Kernel Channel [BackQuant]Kernel Channel A non-parametric, kernel-weighted trend channel that adapts to local structure, smooths noise without lagging like moving averages, and highlights volatility compressions, expansions, and directional bias through a flexible choice of kernels, band types, and squeeze logic. What this is This indicator builds a full trend channel using kernel regression rather than classical averaging. Instead of a simple moving average or exponential weighting, the midline is computed as a kernel-weighted expectation of past values. This allows it to adapt to local shape, give more weight to nearby bars, and reduce distortion from outliers. You can think of it as a sliding local smoother where you define both the “window” of influence (Window Length) and the “locality strength” (Bandwidth). The result is a flexible midline with optional upper and lower bands derived from kernel-weighted ATR or kernel-weighted standard deviation, letting you visualize volatility in a structurally consistent way. Three plotting modes help demonstrate this difference: When the midline is shown alone, you get a smooth, adaptive baseline that behaves almost like a regression moving average, as shown in this view: When full channels are enabled, you see how standard deviation reacts to local structure with dynamically widening and tightening bands, a mode illustrated here: When ATR mode is chosen instead of StdDev, band width reflects breadth of movement rather than variance, creating a volatility-aware envelope like the example here: Why kernels Classical moving averages allocate fixed weights. Kernels let the user define weighting shape: Epanechnikov — emphasizes bars near the current bar, fades fast, stable and smooth. Triangular — linear decay, simple and responsive. Laplacian — exponential decay from the current point, sharper reactivity. Cosine — gentle periodic decay, balanced smoothness for trend filters. Using these in combination with a bandwidth parameter gives fine control over smoothness vs responsiveness. Smaller bandwidths give sharper local sensitivity, larger bandwidths give smoother curvature. How it works (core logic) The indicator computes three building blocks: 1) Kernel-weighted midline For every bar, a sliding window looks back Window Length bars. Each bar in this window receives a kernel weight depending on: its index distance from the present the chosen kernel shape the bandwidth parameter (locality) Weights form the denominator, weighted values form the numerator, and the resulting ratio is the kernel regression mean. This midline is the central trend. 2) Kernel-based width You choose one of two band types: Kernel ATR — ATR values are kernel-averaged, producing a smooth, volatility-based width that is not dependent on variance. Ideal for directional trend channels and regime separation. Kernel StdDev — local variance around the midline is computed through kernel weighting. This produces a true statistical envelope that narrows in quiet periods and widens in noisy areas. Width is scaled using Band Multiplier , controlling how far the envelope extends. 3) Upper and lower channels Provided midline and width exist, the channel edges are: Upper = midline + bandMult × width Lower = midline − bandMult × width These create smooth structures around price that adapt continuously. Plotting modes The indicator supports multiple visual styles depending on what you want to emphasize. When only the midline is displayed, you get a pure kernel trend: a smooth regression-like curve that reacts to local structure while filtering noise, demonstrated here: This provides a clean read on direction and slope. With full channels enabled, the behavior of the bands becomes visible. Standard deviation mode creates elastic boundaries that tighten during compressions and widen during turbulence, which you can see in the band-focused demonstration: This helps identify expansion events, volatility clusters, and breakouts. ATR mode shifts interpretation from statistical variance to raw movement amplitude. This makes channels less sensitive to outliers and more consistent across trend phases, as shown in this ATR variation example: This mode is particularly useful for breakout systems and bar-range regimes. Regime detection and bar coloring The slope of the midline defines directional bias: Up-slope → green Down-slope → red Flat → gray A secondary regime filter compares close to the channel: Trend Up Strong — close above upper band and midline rising. Trend Down Strong — close below lower band and midline falling. Trend Up Weak — close between midline and upper band with rising slope. Trend Down Weak — close between lower band and midline with falling slope. Compression mode — squeeze conditions. Bar coloring is optional and can be toggled for cleaner charts. Squeeze logic The indicator includes non-standard squeeze detection based on relative width , defined as: width / |midline| This gives a dimensionless measure of how “tight” or “loose” the channel is, normalized for trend level. A rolling window evaluates the percentile rank of current width relative to past behavior. If the width is in the lowest X% of its last N observations, the script flags a squeeze environment. This highlights compression regions that may precede breakouts or regime shifts. Deviation highlighting When using Kernel StdDev mode, you may enable deviation flags that highlight bars where price moves outside the channel: Above upper band → bullish momentum overextension Below lower band → bearish momentum overextension This is turned off in ATR mode because ATR widths do not represent distributional variance. Alerts included Kernel Channel Long — midline turns up. Kernel Channel Short — midline turns down. Price Crossed Midline — crossover or crossunder of the midline. Price Above Upper — early momentum expansion. Price Below Lower — downward volatility expansion. These help automate regime changes and breakout detection. How to use it Trend identification The midline acts as a bias filter. Rising midline means trend strength upward, falling midline means downward behavior. The channel width contextualizes confidence. Breakout anticipation Kernel StdDev compressions highlight areas where price is coiling. Breakouts often follow narrow relative width. ATR mode provides structural expansion cues that are smooth and robust. Mean reversion StdDev mode is suitable for fade setups. Moves to outer bands during low volatility often revert to the midline. Continuation logic If price breaks above the upper band while midline is rising, the indicator flags strong directional expansion. Same logic for breakdowns on the lower band. Volatility characterization Kernel ATR maps raw bar movements and is excellent for identifying regime shifts in markets where variance is unstable. Tuning guidance For smoother long-term trend tracking Larger window (150–300). Moderate bandwidth (1.0–2.0). Epanechnikov or Cosine kernel. ATR mode for stable envelopes. For swing trading / short-term structure Window length around 50–100. Bandwidth 0.6–1.2. Triangular for speed, Laplacian for sharper reactions. StdDev bands for precise volatility compression. For breakout systems Smaller bandwidth for sharp local detection. ATR mode for stable envelopes. Enable squeeze highlighting for identifying setups early. For mean-reversion systems Use StdDev bands. Moderate window length. Highlight deviations to locate overextended bars. Settings overview Kernel Settings Source Window Length Bandwidth Kernel Type (Epanechnikov, Triangular, Laplacian, Cosine) Channel Width Band Type (Kernel ATR or Kernel StdDev) Band Multiplier Visuals Show Bands Color Bars By Regime Highlight Squeeze Periods Highlight Deviation Lookback and Percentile settings Colors for uptrend, downtrend, squeeze, flat Trading applications Trend filtering — trade only in direction of the midline slope. Breakout confirmation — expansion outside the bands while slope agrees. Squeeze timing — compression periods often precede the next directional leg. Volatility-aware stops — ATR mode makes channel edges suitable for adaptive stop placement. Structural swing mapping — StdDev bands help locate midline pullbacks vs distributional extremes. Bias rotation — bar coloring highlights when regime shifts occur. Notes The Kernel Channel is not a signal generator by itself, but a structural map. It helps classify trend direction, volatility environment, distribution shape, and compression cycles. Combine it with your entry and exit framework, risk parameters, and higher-timeframe confirmation. It is designed to behave consistently across markets, to avoid the bluntness of classical averages, and to reveal subtle curvature in price that traditional channels miss. Adjust kernel type, bandwidth, and band source to match the noise profile of your instrument, then use squeeze logic and deviation highlighting to guide timing.

อินดิเคเตอร์ Pine Script®

โดย BackQuant

Damo's Custom EMA Bands 1.0 I was making these manually for a long time. They just give me more peace of mind when I'm using EMAs. They feel more like a net catching price. These are easy to make. All they are is 3 EMAs with the Source at High, Low and (H+L)/2 for the midpoint. I find on a 3-Day chart on BTC the 100 EMA is great for telling what trend we're are in. i.postimg.cc

อินดิเคเตอร์ Pine Script®

โดย TraderDamo

McMillan Volatility Bands (MVB) – with Entry Logic // McMillan Volatility Bands (MVB) with signal + entry logic // Author: ChatGPT for OneRyanAlexander // Notes: // - Bands are computed using percentage volatility (log returns), per the Black‑Scholes framing. // - Inner band (default 3σ) and outer band (default 4σ) are configurable. // - A setup occurs when price closes outside the outer band, then closes back within the inner band. // The bar that re‑enters is the "signal bar." We then require price to trade beyond the signal bar's // extreme by a user‑defined cushion (default 0.34 * signal bar range) to confirm entry. // - Includes alertconditions for both setups and confirmed entries.

อินดิเคเตอร์ Pine Script®

โดย ryan.rybarczyk

Dynamic Fractal Flow [Alpha Extract]An advanced momentum oscillator that combines fractal market structure analysis with adaptive volatility weighting and multi-derivative calculus to identify high-probability trend reversals and continuation patterns. Utilizing sophisticated noise filtering through choppiness indexing and efficiency ratio analysis, this indicator delivers entries that adapt to changing market regimes while reducing false signals during consolidation via multi-layer confirmation centered on acceleration analysis, statistical band context, and dynamic omega weighting—without any divergence detection. 🔶 Fractal-Based Market Structure Detection Employs Williams Fractal methodology to identify pivotal market highs and lows, calculating normalized price position within the established fractal range to generate oscillator signals based on structural positioning. The system tracks fractal points dynamically and computes relative positioning with ATR fallback protection, ensuring continuous signal generation even during extended trending periods without fractal formation. 🔶 Dynamic Omega Weighting System Implements an adaptive weighting algorithm that adjusts signal emphasis based on real-time volatility conditions and volume strength, calculating dynamic omega coefficients ranging from 0.3 to 0.9. The system applies heavier weighting to recent price action during high-conviction moves while reducing sensitivity during low-volume environments, mitigating lag inherent in fixed-period calculations through volatility normalization and volume-strength integration. 🔶 Cascading Robustness Filtering Features up to five stages of progressive EMA smoothing with user-adjustable robustness steps, each layer systematically filtering microstructure noise while preserving essential trend information. Smoothing periods scale with the chosen fractal length and robustness steps using a fixed smoothing multiplier for consistent, predictable behavior. 🔶 Adaptive Noise Suppression Engine Integrates dual-component noise filtering combining Choppiness Index calculation with Kaufman’s Efficiency Ratio to detect ranging versus trending market conditions. The system applies dynamic damping that maintains full signal strength during trending environments while suppressing signals during choppy consolidation, aligning output with the prevailing regime. 🔶 Acceleration and Jerk Analysis Framework Calculates second-derivative acceleration and third-derivative jerk to identify explosive momentum shifts before they fully materialize on traditional indicators. Detects bullish acceleration when both acceleration and jerk turn positive in negative oscillator territory, and bearish acceleration when both turn negative in positive territory, providing early entry signals for high-velocity trend initiation phases. 🔶 Multi-Layer Signal Generation Architecture Combines three primary signal types with hierarchical validation: acceleration signals, band crossover entries, and threshold momentum signals. Each signal category includes momentum confirmation, trend-state validation, and statistical band context; signals are further conditioned by band squeeze detection to avoid low-probability entries during compression phases. Divergence is intentionally excluded for a purely structure- and momentum-driven approach. 🔶 Dynamic Statistical Band System Utilizes Bollinger-style standard deviation bands with configurable multiplier and length to create adaptive threshold zones that expand during volatile periods and contract during consolidation. Includes band squeeze detection to identify compression phases that typically precede expansion, with signal suppression during squeezes to prevent premature entries. 🔶 Gradient Color Visualization System Features color gradient mapping that dynamically adjusts line intensity based on signal strength, transitioning from neutral gray to progressively intense bullish or bearish colors as conviction increases. Includes gradient fills between the signal line and zero with transparency scaling based on oscillator intensity for immediate visual confirmation of trend strength and directional bias. All analysis provided by Alpha Extract is for educational and informational purposes only. The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations.

อินดิเคเตอร์ Pine Script®

โดย AlphaExtract

CandleFlow — Adaptive-Colored Bollinger Bands EN — What it is Classic Bollinger Bands with adaptive color. Bands turn green when the basis slope is rising and red when it is falling. Same BB math; only visuals adapt. Two-state only. Features • Works on any timeframe; built with daily crypto in mind • Inputs: Length 20, Multiplier 2.0, MA Type (SMA/EMA/WMA), Slope Length, Up/Down thresholds, Band fill • Alerts: Trend state turns Up / turns Down Notes • Invite-only access. Source code not provided. • No profit guarantee; this is not financial advice. KR — 요약 표준 볼린저 계산은 그대로, 기준선이 상승하면 초록/하락하면 빨강으로 자동 색상 전환. 일봉 크립토에 최적화. 입력값(기간 20, 배수 2.0, MA 타입, 기울기 길이, 상/하 임계값, 밴드 채우기), 알림(상승/하락 전환) 제공. 초대전용, 코드 비공개. 수익 보장 없음. Trademark Bollinger Bands® is a registered trademark of John Bollinger. Not affiliated or endorsed.

อินดิเคเตอร์ Pine Script®

โดย TV-candleflow

ที่อัปเดต:

Advanced Candle Compression Bollinger Colors candles based on Bollinger Band width relative to its average — showing when volatility tightens. Orange = medium compression Red = strong compression Candle color appears only after several consecutive bars meet the condition. You can adjust thresholds, colors, bar count, and the Bollinger source (default: (High+Low+Close)/3). Useful to spot low-volatility zones that often precede breakouts.

อินดิเคเตอร์ Pine Script®

โดย BrokeNaze

Market Pressure Differential (MPD) [SharpStrat]Market Pressure Differential (MPD) Concept & Purpose The Market Pressure Differential (MPD) is a proprietary indicator designed to measure the internal balance of buying and selling pressure directly on the price chart. Unlike standard momentum or trend indicators, MPD analyzes the structural behavior of each candle—its body, wicks, and overall range—to determine whether the market is dominated by expansion (buying aggression) or contraction (selling absorption). This indicator provides a visual overlay of market pressure that adapts dynamically to volatility, helping traders see real-time shifts in participation intensity without using oscillators. In simple terms: When MPD expands upward → buyer pressure dominates. When MPD contracts downward → seller pressure dominates. Calculation Overview MPD uses a structural candle formula to compute directional pressure: Body Ratio = (Close − Open) / (High − Low) Wick Differential = (Lower Wick − Upper Wick) / (High − Low) Raw Pressure = (Body Ratio × Body Weight) + (Wick Differential × Wick Weight) Then it applies: EMA smoothing (to stabilize short-term noise) Standard deviation normalization (to maintain consistent scaling) ATR projection (to adapt the signal visually to volatility) This produces the MPD projection line and the pressure ribbon, drawn directly on the main chart. Customizable Inputs Users can adjust color schemes, EMA smoothing length, ATR parameters, normalization length, and body/wick weighting to adapt the indicator’s sensitivity and aesthetic to different markets or chart themes. How to Use The Market Pressure Differential (MPD) visualizes the real-time balance between buying and selling pressure. It should be used as a contextual bias tool, not a standalone signal generator. The white line represents the MPD projection, showing how market pressure evolves in real time based on candle structure and volatility. The red line represents the ATR envelope, which defines the market’s expected volatility range. MPD reacts quickly to candle structure, so trend bias is based on how its projection behaves relative to the ATR envelope: Above the ATR band → positive pressure and bullish bias. Below the ATR band → negative pressure and bearish bias. Hovering near the ATR band → neutral or indecisive conditions. The MPD percentage in the label represents the normalized strength of pressure relative to recent volatility. Positive % = buying dominance. Negative % = selling dominance. Higher absolute values = stronger momentum compared to volatility. To trade with MPD: Watch candle colors and the projection line — green or positive % shows buyer control, red or negative % shows seller control. Note transitions above or below the ATR level for early signs of momentum shifts. Combine MPD signals with price structure, key levels, or volume for confirmation. This helps reveal which side controls the market and whether that pressure is strong enough to overcome typical volatility. Disclaimer It introduces a novel structural–pressure approach to visualizing market dynamics. For educational and analytical purposes only; this does not constitute financial advice.

อินดิเคเตอร์ Pine Script®

โดย SharpStrat

Aggregated Scores Oscillator [Alpha Extract]A sophisticated risk-adjusted performance measurement system that combines Omega Ratio and Sortino Ratio methodologies to create a comprehensive market assessment oscillator. Utilizing advanced statistical band calculations with expanding and rolling window analysis, this indicator delivers institutional-grade overbought/oversold detection based on risk-adjusted returns rather than traditional price movements. The system's dual-ratio aggregation approach provides superior signal accuracy by incorporating both upside potential and downside risk metrics with dynamic threshold adaptation for varying market conditions. 🔶 Advanced Statistical Framework Implements dual statistical methodologies using expanding and rolling window calculations to create adaptive threshold bands that evolve with market conditions. The system calculates cumulative statistics alongside rolling averages to provide both historical context and current market regime sensitivity with configurable window parameters for optimal performance across timeframes. 🔶 Dual Ratio Integration System Combines Omega Ratio analysis measuring excess returns versus deficit returns with Sortino Ratio calculations focusing on downside deviation for comprehensive risk-adjusted performance assessment. The system applies configurable smoothing to both ratios before aggregation, ensuring stable signal generation while maintaining sensitivity to regime changes. // Omega Ratio Calculation Excess_Return = sum((Daily_Return > Target_Return ? Daily_Return - Target_Return : 0), Period) Deficit_Return = sum((Daily_Return < Target_Return ? Target_Return - Daily_Return : 0), Period) Omega_Ratio = Deficit_Return ≠ 0 ? (Excess_Return / Deficit_Return) : na // Sortino Ratio Framework Downside_Deviation = sqrt(sum((Daily_Return < Target_Return ? (Daily_Return - Target_Return)² : 0), Period) / Period) Sortino_Ratio = (Mean_Return / Downside_Deviation) * sqrt(Annualization_Factor) // Aggregated Score Aggregated_Score = SMA(Omega_Ratio, Omega_SMA) + SMA(Sortino_Ratio, Sortino_SMA) 🔶 Dynamic Band Calculation Engine Features sophisticated threshold determination using both expanding historical statistics and rolling window analysis to create adaptive overbought/oversold levels. The system incorporates configurable multipliers and sensitivity adjustments to optimize signal timing across varying market volatility conditions with automatic band convergence logic. 🔶 Signal Generation Framework Generates overbought conditions when aggregated score exceeds adjusted upper threshold and oversold conditions below lower threshold, with neutral zone identification for range-bound markets. The system provides clear binary signal states with background zone highlighting and dynamic oscillator coloring for intuitive market condition assessment. 🔶 Enhanced Visual Architecture Provides modern dark theme visualization with neon color scheme, dynamic oscillator line coloring based on signal states, and gradient band fills for comprehensive market condition visualization. The system includes zero-line reference, statistical band plots, and background zone highlighting with configurable transparency levels. snapshot 🔶 Risk-Adjusted Performance Analysis Utilizes target return parameters for customizable risk assessment baselines, enabling traders to evaluate performance relative to specific return objectives. The system's focus on downside deviation through Sortino analysis provides superior risk-adjusted signals compared to traditional volatility-based oscillators that treat upside and downside movements equally. 🔶 Multi-Timeframe Adaptability Features configurable calculation periods and rolling windows to optimize performance across various timeframes from intraday to long-term analysis. The system's statistical foundation ensures consistent signal quality regardless of timeframe selection while maintaining sensitivity to market regime changes through adaptive band calculations. 🔶 Performance Optimization Framework Implements efficient statistical calculations with optimized variable management and configurable smoothing parameters to balance responsiveness with signal stability. The system includes automatic band adjustment mechanisms and rolling window management for consistent performance across extended analysis periods. This indicator delivers sophisticated risk-adjusted market analysis by combining proven statistical ratios in a unified oscillator framework. Unlike traditional overbought/oversold indicators that rely solely on price movements, the ASO incorporates risk-adjusted performance metrics to identify genuine market extremes based on return quality rather than price volatility alone. The system's adaptive statistical bands and dual-ratio methodology provide institutional-grade signal accuracy suitable for systematic trading approaches across cryptocurrency, forex, and equity markets with comprehensive visual feedback and configurable risk parameters for optimal strategy integration.

อินดิเคเตอร์ Pine Script®

โดย AlphaExtract

John Bollinger's Bollinger Bands Japanese below / 日本語説明は下記 This indicator replicates how John Bollinger, the inventor of Bollinger Bands, uses Bollinger Bands, displaying Bollinger Bands, %B and Bandwidth in one indicator with alerts and signals. Bollinger Bands is created by John Bollinger in 1980s who is an American financial trader and analyst. He introduced %B and Bandwidth 30 years later. 🟦 What's different from other Bollinger Bands indicator? Unlike the default Bollinger Bands or other custom Bollinger Bands indicators on TradingView, this indicator enables to display three Bollinger Bands tools into a single indicator with signals and alerts capability. You can plot the classic Bollinger Bands together with either %B or Bandwidth or three tools altogether which requires the specific setting(see below settings). This makes it easy to quantitatively monitor volatility changes and price position in relation to Bollinger Bands in one place. 🟦 Features: Plots Bollinger Bands (Upper, Basis, Lower) with fill between bands. Option to display %B or Bandwidth with Bollinger Bands. Plots highest and lowest Bandwidth levels over a customizable lookback period. Adds visual markers when Bandwidth reaches its highest (Bulge) or lowest (Squeeze) value. Includes ready-to-use alert conditions for Bulge and Squeeze events. 📈Chart Green triangles and red triangles in the bottom chart mark Bulges and Squeezes respectively. 🟦 Settings: Length: Number of bars used for Bollinger Band middleline calculation. Basis MA Type: Choose SMA, EMA, SMMA (RMA), WMA, or VWMA for the midline. StdDev: Standard deviation multiplier (default = 2.0). Option: Select "Bandwidth" or "%B" (add the indicator twice if you want to display both). Period for Squeeze and Bulge: Lookback period for detecting the highest and lowest Bandwidth levels.(default = 125 as specified by John Bollinger ) Style Settings: Colors, line thickness, and transparency can be customized. 📈Chart The chart below shows an example of three Bollinger Bands tools: Bollinger Band, %B and Bandwidth are in display. To do this, you need to add this indicator TWICE where you select %B from Option in the first addition of this indicator and Bandwidth from Option in the second addition. 🟦 Usage: 🟠Monitor Volatility: Watch Bandwidth values to spot volatility contractions (Squeeze) and expansions (Bulge) that often precede strong price moves. John Bollinger defines Squeeze and Bulge as follows; Squeeze: The lowest bandwidth in the past 125 period, where trend is born. Bulge: The highest bandwidth in the past 125 period where trend is going to die. According to John Bollinger, this 125 period can be used in any timeframe. 📈Chart1 Example of Squeeze You can see uptrends start after squeeze(red triangles) 📈Chart2 Example of Bulge You can see the trend reversal from downtrend to uptrends at the bulge(green triangles) 📈Chart3 Bulge DOES NOT NECESSARILY mean the beginning of a trend in opposite direction. For example, you can see a bulge happening in the right side of the chart where green triangles are marked. Nevertheless, uptrend still continues after the bulge. In this case, the bulge marks the beginning of a consolidation which lead to the continuation of the trend. It means that a phase of the trend highlighted in the light blue box came to an end. Note: light blue box is not drawn by the indicator. Like other technical analysis methods or tools, these setups do not guarantee birth of new trends and trend reversals. Traders should be carefully observing these setups along with other factors for making decisions. 🟠Track Price Position: Use %B to see where price is located in relation to the Bollinger Bands. If %B is close to 1, the price is near upper band while %B is close to 0, the price is near lower band. 🟠Set Alerts: Receive alerts when Bandwidth hits highest and lowest values of bandwidth, helping you prepare for potential breakout, ending of trends and trend reversal opportunities. 🟠Combine with Other Tools: This indicator would work best when combined with price action, trend analysis, or market environmental analysis. ————————————————————————————— このインジケーターはボリンジャーバンドの考案者であるジョン・ボリンジャー氏が提唱するボリンジャーバンドの使い方を再現するために、ボリンジャーバンド、%B、バンドウィズ(Bandwidth) の3つを1つのインジケーターで表示可能にしたものです。シグナルやアラートにも対応しています。ボリンジャーバンドは1980年代にアメリカ人トレーダー兼アナリストのジョン・ボリンジャー氏によって開発されました。彼はその30年後に%Bとバンドウィズを導入しました。 🟦 他のボリンジャーバンドとの違い TradingView標準のボリンジャーバンドや他のボリンジャーバンドとは異なり、このインジケーターでは3つのボリンジャーバンドツールを1つのインジケーターで表示し、シグナルやアラート機能も利用できるようになっています。一般的に知られている通常のボリンジャーバンドに加え、%Bやバンドウィズを組み合わせて表示でき、設定次第では3つすべてを同時にモニターすることも可能です。これにより、価格とボリンジャーバンドの位置関係とボラティリティ変化をひと目で、かつ定量的に把握することができます。 🟦 機能: ボリンジャーバンド（アッパーバンド・基準線・ロワーバンド）を描画し、バンド間を塗りつぶし表示。オプションで%Bまたはバンドウィズを追加表示可能。バンドウィズの最高値・最安値を、任意の期間で検出して表示。バンドウィズが指定期間の最高値（バルジ※）または最安値（スクイーズ）に達した際にシグナルを表示。 ※バルジは一般的にボリンジャーバンドで用いられるエクスパンションとほぼ同じ意味ですが、定義が異なります。(下記参照) バルジおよびスクイーズ発生時のアラート設定が可能。 📈 チャート例  下記チャートの緑の三角と赤の三角は、それぞれバルジとスクイーズを示しています。 🟦 設定: Length: ボリンジャーバンドの基準線計算に使う期間。 Basis MA Type: SMA, EMA, SMMA (RMA), WMA, VWMAから選択可能。 StdDev: 標準偏差の乗数（デフォルト2.0）。 Option: 「Bandwidth」または「%B」を選択（両方表示するにはこのインジケーターを2回追加）。 Period for Squeeze and Bulge: Bandwidthの最高値・最安値を検出する期間（デフォルトはジョン・ボリンジャー氏が推奨する125）。 Style Settings: 色、線の太さ、透明度などをカスタマイズ可能。 📈 チャート例  下のチャートは「ボリンジャーバンド」「%B」「バンドウィズ」の3つを同時に表示した例です。 この場合、インジケーターを2回追加し、最初に追加した方ではOptionを「%B」に、次に追加した方では「Bandwidth」を選択します。 🟦 使い方: 🟠 ボラティリティを監視する:  バンドウィズの値を見ることで、価格変動の収縮（スクイーズ）や拡大（バルジ）を確認できます。これらはしばしば強い値動きの前兆となります。ジョン・ボリンジャー氏はスクイーズとバルジを次のように定義しています：スクイーズ: 過去125期間の中で最も低いバンドウィズ→ 新しいトレンドが生まれる場所。バルジ: 過去125期間の中で最も高いバンドウィズ → トレンドが終わりを迎える場所。この「125期間」はどのタイムフレームでも利用可能とされています。 📈 チャート1 スクイーズの例 赤い三角のスクイーズの後に上昇トレンドが始まっているのが確認できます。  📈 チャート2 バルジの例 緑の三角のバルジの箇所で下降トレンドから上昇トレンドへの反転が見られます。  📈 チャート3 バルジが必ずしも反転を意味しない例  下記のチャート右側の緑の三角で示されたバルジの後も、上昇トレンドが継続しています。 この場合、バルジは反転ではなく「トレンド一時的な調整（レンジ入り）」を示しており、結果的に上昇トレンドが継続しています。この場合、バルジは水色のボックスで示されたトレンドのフェーズの終わりを示しています。   ※水色のボックスはインジケーターが描画したものではありません。  また、他のテクニカル分析と同様に、これらのセットアップは必ず新しいトレンドの発生やトレンド転換を保証するものではありません。トレーダーは他の要素も考慮し、慎重に意思決定する必要があります。 🟠 価格とボリンジャーバンドの位置関係を確認する:  %Bを利用すれば、価格がバンドのどこに位置しているかを簡単に把握できます。 %Bが1に近ければ価格はアッパーバンド付近、0に近ければロワーバンド付近にあります。 🟠 アラートを設定する:  バンドウィズが一定期間の最高値または最安値に到達した際にアラートを設定することで、ブレイクアウトやトレンド終了、反転の可能性に備えることができます。 🟠 他のツールと組み合わせる:  このインジケーターは、プライスアクション、トレンド分析、環境認識などと組み合わせて活用すると最も効果的です。

อินดิเคเตอร์ Pine Script®

โดย FX365_Thailand

JLine RZ+|SuperFunded JLINE with Resistance Zone+ — Quick Guide What it is This indicator generalizes the classic “JLINE” concept by letting you choose the MA type (SMA / EMA / WMA) and by converting mixed-order phases—when the fast/mid/slow MAs temporarily overlap—into forward-projected horizontal zones. It also shows a status label (current timeframe) and an optional higher-timeframe (HTF) status so you can align entries with broader trend context. Why this is not a simple mashup ・Structure first: Instead of merely plotting MAs, the script detects mixed-order windows and tracks the max/min envelope formed by the 3 MAs during the overlap, then freezes and extends that range to the right as tradable zones (dynamic S/R derived from regime transitions). ・Context layering: You get a clear “Bullish/Bearish Perfect Order vs Mixed Zone” state, a color-coded MA band, and forward zones that persist beyond the regime change. This provides a workflow (identify structure → watch reactions at projected zones → confirm with status). ・Top-down alignment: The HTF status overlay makes it easy to avoid counter-trend trades or, if you prefer, time mean-reversion only when the current timeframe’s mixed zones line up with HTF conditions. How it works (concise) 1. Compute fast/mid/slow MAs using your selected type (SMA/EMA/WMA). 2. Define states: Bullish Perfect Order (fast > mid > slow), Bearish Perfect Order (fast < mid < slow), or Mixed Zone (neither). 3. While Mixed, maintain an envelope using the highest/lowest of the three MAs. When the regime exits Mixed, save that envelope as a horizontal box and extend it into the future (older boxes auto-delete to keep the chart clean). 4. Paint an MA band between fast & slow with state-aware shading. 5. Show a corner label with the current state; optionally add the HTF state via request.security. Parameters (UI mapping) 1. Moving Average Settings ・MA Type: SMA / EMA / WMA. ・Fast/Middle/Slow Period: Default 20/100/200, editable. ・Paint MA Band: Toggle the band fill between fast and slow MA. 2. Resistance Zone Settings ・Show Resistance Zone: Draw horizontal zones from mixed-order windows and extend to the right. ・Max Number of Zones: Cap the count; oldest zones are removed automatically. ・Zone Color: Set zone color/opacity. 3. Status Display Settings ・Show Status Label: On-chart label showing the current state. ・Label Position: Top/Bottom × Left/Right. 4. Multi-Timeframe Settings ・Show Higher Timeframe Status: Display the HTF state in the label. ・Higher Timeframe: Select the HTF (empty = disabled). Practical usage ・Plan around zones: Treat zones as potential support/resistance derived from regime transitions. Observe how price reacts when it revisits/enters a zone. ・Align with trend: Prefer entries with the PO state (e.g., longs in Bullish PO) and use HTF status to filter. Mean-reversion is still possible, but require clear reaction (wick rejections, engulfings) at a zone. ・Manage clutter: If charts get busy, increase timeframe or lower “Max Number of Zones.” ・Risk first: SL beyond the opposite side of the zone; TPs can target adjacent zones or fixed R-multiples. Notes & limitations ・Zones reflect MA-structure (mixed) envelopes, not price consolidations per se; they are structural guides, not guarantees. ・HTF readouts rely on request.security and your chosen timeframe; data quality and timing follow TradingView constraints. Disclaimer This tool suggests potential reaction areas; it cannot ensure outcomes. Volatility, news and liquidity conditions may invalidate any setup. Use appropriate position sizing and only risk capital you can afford to lose. SuperFunded invite-only To obtain access, please contact me via TradingView DM or the link in my profile. JLINE with Resistance Zone (Advanced) — クイックガイド（日本語）概要本インジは、任意のMAタイプ（SMA / EMA / WMA）で高速・中速・低速の3本を描画し、順序が混在する期間（Mixed）で形成された3MAの最大値/最小値の包絡を水平ゾーンとして将来に延長して表示します。さらに、現在の状態ラベルと、任意で上位時間足（HTF）の状態も重ねて表示できます。新規性（単なる寄せ集めではない点）・構造を先に特定：MAを出すだけでなく、混在期間を検出→その間の3MA包絡を凍結して水平帯に変換→右に延長。レジーム転換由来のS/Rを作ります。・文脈レイヤー：Bullish/BearishのパーフェクトオーダーとMixedを明示、MAバンドと将来に残るゾーンで、構造→反応→確認の手順が取りやすい構成。・トップダウン整合：HTF状態をラベルに併記して、逆行を避けたり、逆張りでも根拠を強めたりできます。使い方のヒントゾーン中心で計画：ゾーンはレジーム転換に基づく潜在的S/R。再訪時のローソク足の反応（ピンバー、包み足など）を確認してからエントリー。トレンド整合：可能ならPO方向に合わせる。逆張りは明確な反応が条件。視認性：時間軸を上げるか Max Number of Zones を下げて整理。リスク管理：損切りは帯の反対側、利確は隣接ゾーンやR倍数で。免責ゾーンは反発を保証しません。ニュース・流動性の急変で機能しない場合があります。資金管理の徹底と自己責任でのご利用をお願いします。 SuperFunded招待専用スクリプトこのスクリプトはSuperFundedの参加者専用です。

อินดิเคเตอร์ Pine Script®

โดย SuperFunded

Quantile Regression Bands [BackQuant]Quantile Regression Bands Tail-aware trend channeling built from quantiles of real errors, not just standard deviations. What it does This indicator fits a simple linear trend over a rolling lookback and then measures how price has actually deviated from that trend during the window. It then places two pairs of bands at user-chosen quantiles of those deviations (inner and outer). Because bands are based on empirical quantiles rather than a symmetric standard deviation, they adapt to skewed and fat-tailed behaviour and often hug price better in trending or asymmetric markets. Why “quantile” bands instead of Bollinger-style bands? Bollinger Bands assume a (roughly) symmetric spread around the mean; quantiles don’t—upper and lower bands can sit at different distances if the error distribution is skewed. Quantiles are robust to outliers; a single shock won’t inflate the bands for many bars. You can choose tails precisely (e.g., 1%/99% or 5%/95%) to match your risk appetite. How it works (intuitive) Center line — a rolling linear regression approximates the local trend. Residuals — for each bar in the lookback, the indicator looks at the gap between actual price and where the line “expected” price to be. Quantiles — those gaps are sorted; you select which percentiles become your inner/outer offsets. Bands — the chosen quantile offsets are added to the current end of the regression line to draw parallel support/resistance rails. Smoothing — a light EMA can be applied to reduce jitter in the line and bands. What you see Center (linear regression) line (optional). Inner quantile bands (e.g., 25th/75th) with optional translucent fill. Outer quantile bands (e.g., 1st/99th) with a multi-step gradient to visualise “tail zones.” Optional bar coloring: bars trend-colored by whether price is rising above or falling below the center line. Alerts when price crosses the outer bands (upper or lower). How to read it Trend & drift — the slope of the center line is your local trend. Persistent closes on the same side of the center line indicate directional drift. Pullbacks — tags of the inner band often mark routine pullbacks within trend. Reaction back to the center line can be used for continuation entries/partials. Tails & squeezes — outer-band touches highlight statistically rare excursions for the chosen window. Frequent outer-band activity can signal regime change or volatility expansion. Asymmetry — if the upper band sits much further from the center than the lower (or vice versa), recent behaviour has been skewed. Trade management can be adjusted accordingly (e.g., wider take-profit upslope than downslope). A simple trend interpretation can be derived from the bar colouring Good use-cases Volatility-aware mean reversion — fade moves into outer bands back toward the center when trend is flat. Trend participation — buy pullbacks to the inner band above a rising center; flip logic for shorts below a falling center. Risk framing — set dynamic stops/targets at quantile rails so position sizing respects recent tail behaviour rather than fixed ticks. Inputs (quick guide) Source — price input used for the fit (default: close). Lookback Length — bars in the regression window and residual sample. Longer = smoother, slower bands; shorter = tighter, more reactive. Inner/Outer Quantiles (τ) — choose your “typical” vs “tail” levels (e.g., 0.25/0.75 inner, 0.01/0.99 outer). Show toggles — independently toggle center line, inner bands, outer bands, and their fills. Colors & transparency — customize band and fill appearance; gradient shading highlights the tail zone. Band Smoothing Length — small EMA on lines to reduce stair-step artefacts without meaningfully changing levels. Bar Coloring — optional trend tint from the center line’s momentum. Practical settings Swing trading — Length 75–150; inner τ = 0.25/0.75, outer τ = 0.05/0.95. Intraday — Length 50–100 for liquid futures/FX; consider 0.20/0.80 inner and 0.02/0.98 outer in high-vol assets. Crypto — Because of fat tails, try slightly wider outers (0.01/0.99) and keep smoothing at 2–4 to tame weekend jumps. Signal ideas Continuation — in an uptrend, look for pullback into the lower inner band with a close back above the center as a timing cue. Exhaustion probe — in ranges, first touch of an outer band followed by a rejection candle back inside the inner band often precedes mean-reversion swings. Regime shift — repeated closes beyond an outer band or a sharp re-tilt in the center line can mark a new trend phase; adjust tactics (stop-following along the opposite inner band). Alerts included “Price Crosses Upper Outer Band” — potential overextension or breakout risk. “Price Crosses Lower Outer Band” — potential capitulation or breakdown risk. Notes The fit and quantiles are computed on a fixed rolling window and do not repaint; bands update as the window moves forward. Quantiles are based on the recent distribution; if conditions change abruptly, expect band widths and skew to adapt over the next few bars. Parameter choices directly shape behaviour: longer windows favour stability, tighter inner quantiles increase touch frequency, and extreme outer quantiles highlight only the rarest moves. Final thought Quantile bands answer a simple question: “How unusual is this move given the current trend and the way price has been missing it lately?” By scoring that question with real, distribution-aware limits rather than one-size-fits-all volatility you get cleaner pullback zones in trends, more honest “extreme” tags in ranges, and a framework for risk that matches the market’s recent personality.

อินดิเคเตอร์ Pine Script®

โดย BackQuant

Rolling Range Bands by tvig Rolling Range Bands Plots two dynamic price envelopes that track the highest and lowest prices over a Short and Long lookback. Use them to see near-term vs. broader market structure, evolving support/resistance, and volatility changes at a glance. What it shows • Short Bands: recent trading range (fast, more reactive). • Long Bands: broader range (slow, structural). • Optional step-line style and shaded zones for clarity. • Option to use completed bar values to avoid intrabar jitter (no repaint). How to read • Price pressing the short high while the long band rises → short-term momentum in a larger uptrend. • Price riding the short low inside a falling long band → weakness with trend alignment. • Band squeeze (narrowing) → compression; watch for breakout. • Band expansion (widening) → rising volatility; expect larger swings. • Repeated touches/rejections of long bands → potential areas of support/resistance. Inputs • Short Window, Long Window (bars) • Use Close only (vs. High/Low) • Use completed bar values (stability) • Step-line style and Band shading Tips • Works on any symbol/timeframe; tune windows to your market. • For consistent scaling, pin the indicator to the same right price scale as the chart. Not financial advice; combine with trend/volume/RSI or your system for entries/exits.

อินดิเคเตอร์ Pine Script®

โดย ludwigcs

11 22 33 44 55 66 77 88 99 1010 1111 1212 1313 1414 1515 1616 1717 1818 1919 2020 2121 2222

เลือกข้อมูลตลาดที่ให้บริการโดย ICE Data Services. เลือกข้อมูลอ้างอิงที่ให้บริการโดย FactSet. Copyright © 2026 FactSet Research Systems Inc.Copyright © 2026, American Bankers Association. CUSIP Database ที่ให้บริการโดย FactSet Research Systems Inc. All rights reserved. SEC filings และเอกสารอื่นๆ ที่ให้บริการโดย Quartr.© 2026 TradingView, Inc.

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