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Crypto ETFs AUM📘 Description: BTC ETFs AUM Tracker This indicator tracks the Assets Under Management (AUM) and daily inflows/outflows of the main U.S.-listed Bitcoin ETFs, allowing you to visualize institutional capital movement into Bitcoin products over time. It helps traders correlate institutional capital movement with Bitcoin price behavior. 🧩 Overview The script adds up the daily AUM changes from selected Bitcoin ETFs to estimate the total net inflow/outflow of capital into spot BTC funds. It also accumulates those flows over time to display the total aggregated AUM balance, giving you a clearer sense of market direction and institutional sentiment. Two display modes are available: Balance view: plots the cumulative sum of net inflows (total ETF AUM). Inflows view: shows daily inflows (green) and outflows (red) as histogram columns, together with a smoothed moving average line. ⚙️ Inputs Explained Base Settings Base Multiplier (base_multi) – Scaling factor applied to all AUM values. Leave at 1 for USD units, or adjust to display values in millions (1e6) or billions (1e9). Smoothing (c_smoothing) – Period length for the simple moving average used to calculate the smoothed mean inflow/outflow line. Show Balance (showBalance) – When enabled, displays the total cumulative AUM balance (sum of all net inflows over time). Show Inflows (showInflows) – When enabled, displays the daily inflows/outflows as colored columns. ETF Selection You can toggle which ETFs are included in the calculation: BIT (BlackRock) GBTC (Grayscale) FBTC (Fidelity) ARKB (ARK/21Shares) BITB (Bitwise) EZBC (Franklin Templeton) BTCW (WisdomTree) BTCO (Invesco Galaxy) BRRR (Valkyrie) HODL (VanEck) Each switch determines whether the ETF’s AUM and daily flow data are included in the total calculation. 📊 Displayed Values Green Columns → Positive daily net inflows (AUM increased). Red Columns → Negative daily net outflows (AUM decreased). Orange Line → Smoothed moving average of net flows, used to identify persistent inflow/outflow trends. Blue Line (if enabled) → Total cumulative AUM balance (sum of all historical flows). 💡 Usage Notes Works best on daily timeframe, since ETF data is typically updated once per trading day. Not all ETFs have identical data history; missing data points are automatically skipped. The indicator doesn’t represent official fund NAV or guarantee data accuracy — it visualizes TradingView’s public financial feed. You can combine this tool with price action or on-chain metrics to analyze institutional Bitcoin flows. Note: Some ETF data may not be available to all users depending on their TradingView data subscription or market access. Missing values are automatically skipped. 🧠 Disclaimer This script is for educational and analytical purposes only. It is not financial advice, and no investment decisions should be based solely on this indicator. Data accuracy depends on TradingView’s financial data sources and exchange reporting frequency.
Pine Script® インジケーター
mks17の投稿
2
Timebender 369 Time CalculatorOverview The Timebender Digits indicator visualizes rhythmic price cycles by marking confirmed swing highs and lows with dynamically colored numerical stamps. Each number is derived from the sum of the current candle’s hour and minute, reduced to a single digit (1–9), providing a visual “time signature” for each structural turn in market flow. This is a structural-pivot model inspired by LuxAlgo’s swing logic, rebuilt from the ground up in Pine v6 using the Timebender Rulebook framework for flawless compilation and precision label anchoring. Core Features Dynamic Swing Detection: Detects structural highs/lows using ta.pivothigh() and ta.pivotlow(), confirmed after the selected number of bars (len). Digit Logic (1–9): Converts the pivot candle’s timestamp into a reduced digit from 1–9, acting as a symbolic rhythm marker. Phase-Based Coloring: 1-3 → Accumulation (Gray) 4-6 → Manipulation (Green) 7-9 → Distribution (Blue) Floating or Fixed Labels: Option to keep digits visually anchored above/below candles (yloc.abovebar/belowbar) or locked to price (yloc.price) with customizable ATR offset. Clean Visuals: Transparent background, no boxes, no tooltips — just crisp digits that scale smoothly with zoom. Master Toggle: Instantly hide/show all digits without removing the indicator. Inputs & Customization Show Digits on Chart: Enable/disable plotting. Pivot Length: Number of bars used to confirm swings (default 21). Float Above/Below Bars: Switch between floating or price-anchored mode. ATR Offset Multiplier: Adjust spacing when price-anchored. Digit Size: Tiny → Huge (default Large). Color Controls: Customize the Accumulation, Manipulation, and Distribution color palette. Use Cases Visualize time-based rhythm in market structure. Identify cyclical energy between accumulation, manipulation, and distribution phases. Study how market timing aligns with structural swing formation.
Pine Script® インジケーター
bon_appetradeの投稿
Oscillator CandlesticksI've always wondered why we don't use candlesticks for oscillators...then I stopped wondering and made an oscillator with candlesticks. The following oscillators are available as a proof of concept: * Consumer Channel Index (CCI) * Rate of Change (ROC) * Relative Strength Index (RSI) * Trend Strength Index (TSI) You can add a moving average to the ohlc4 value of the oscillator and choose the type of the moving average and whether it should be influenced by volume.
Pine Script® インジケーター
llbotの投稿
Smart Money Toolkit - PD Engine Bias Map [KedArc Quant]📄 Description Smart Money Toolkit is an advanced multi-layer Smart Money Concepts framework that automatically detects structure shifts, premium-discount zones, and institutional order flow. It’s built around the PD Engine, which calculates the midpoint of the most recent market swing and dynamically determines BUY or SELL bias based on where current price trades relative to that equilibrium. This toolkit visualizes structure, order blocks, and bias context in one clean map — giving traders an institutional-grade lens without signal clutter. 💡 Why It’s Unique * Not a mashup of open-source scripts. Every module — CHoCH/BOS logic, order-block zone detection, PD bias engine, and structure mapping — is written from scratch to ensure clean, consistent behavior in Pine Script v6. * Bias engine with true equilibrium logic: The 50% PD (Premium-Discount) zone adapts in real time to the latest swing, giving a live institutional price map. * Visual precision: Minimalist premium/discount shading, structured labeling (HH, HL, LH, LL, CHoCH), and context tables for clarity. * Performance-optimized: Handles multiple visual layers (FVG, OB, CHoCH, BOS) efficiently without repainting. 🎯 Entry and Exit Logic (Discretionary Framework) This toolkit is not a signal generator; it’s a contextual trading framework that guides your decisions. BUY Bias (Discount Zone) * Price trades below PD Mid → Market is in *discount*. * Wait for a bullish CHoCH or rejection from demand OB/FVG before entering long. * Target 1 = PD Mid; Target 2 = next opposing OB/FVG. SELL Bias (Premium Zone) * Price trades above PD Mid → Market is in *premium*. * Wait for a bearish CHoCH or rejection from supply OB/FVG before shorting. * Target 1 = PD Mid; Target 2 = next opposing OB/FVG. This sequence enforces the institutional concept: > Bias → Structure Shift → Confirmation → Execution ⚙️ Input Configuration Setting Description Swing Sensitivity Controls how far back to look for HH/LL pivots. OB/FVG Detection Enable or disable visual order block or fair-value-gap zones. PD Engine Toggles PD midpoint line, zone shading, and bias table. Multi-TF Bias Sync Optionally reads higher-time-frame bias to confirm entries. Color Themes Switch between Light / Dark / Institutional color sets. All inputs are modular — you can show only the components you use (e.g., disable BOS/CHoCH labels or hide OB zones for a clean view). 🧮 Formula / Logic Summary Concept Formula PD Mid (Equilibrium) `(Recent Swing High + Recent Swing Low) / 2` BUY Bias `close < PD Mid` SELL Bias `close > PD Mid` CHoCH / BOS Detected via pivot-based structure reversal: HH→LL or LL→HH Order Block Last bullish/bearish candle before displacement. Fair Value Gap (FVG) Gap between prior candle’s high/low and next candle’s range. These formulas align with Smart Money Concepts taught in institutional trading frameworks. 🤝 How It Helps Traders * Institutional Context: Instantly visualize premium vs. discount regions — see where smart money is likely accumulating or distributing. * Bias Confidence: Removes guesswork — you know whether you should be a buyer or seller based on structure + PD bias. * Cleaner Decision-Making: Combines all SMC elements (BOS, CHoCH, OB, FVG, PD) in one cohesive visual map. * Timeframe Agnostic: Works seamlessly on any timeframe or instrument (Forex, Indices, Crypto, Equities). 📚 Glossary PD Mid (Equilibrium) The midpoint between recent swing high and low — the market’s fair value. Premium Zone Price above PD Mid — sellers gain control. Discount Zone Price below PD Mid — buyers gain control. CHoCH (Change of Character) First structural signal of possible reversal. BOS (Break of Structure) Continuation signal confirming trend direction. OB (Order Block) Institutional candle marking accumulation/distribution. FVG (Fair Value Gap) Imbalance zone where price moved too quickly — often rebalanced. ❓ FAQ Q: Is this a signal generator? A: No — it’s a contextual framework for professional price-action trading. Q: Does it repaint? A: No. All structure points and bias logic are confirmed on bar close. Q: Can it be used on any market or timeframe? A: Yes. It’s structure-based, not instrument-specific. Q: How often does bias change? A: Only when a new swing high/low forms and PD recalculates — keeping the bias stable. Q: Can I backtest it? A: You can build an entry rule (e.g., CHoCH + OB + PD alignment) on top of it for strategy testing. ⚠️ Disclaimer This script is provided for educational purposes only. Past performance does not guarantee future results. Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Pine Script® インジケーター
kedarcquantの投稿
VSTrade OMCThe indicator calculates the ratio of Open Interest (OI) of a futures contract to the market capitalization (Market Cap) of the spot asset. OI is the number of open (unclosed) futures positions in the market, expressed in contracts. Market Cap is the total value of the asset (price * circulating supply). The ratio shows how "overheated" or "interesting" the futures market is relative to the size of the asset.This is not a direct trading signal, but a tool for analyzing liquidity, speculation, and market sentiment. Индикатор рассчитывает отношение Open Interest (OI) фьючерсного контракта к рыночной капитализации (Market Cap) спотового актива. OI — это количество открытых (незакрытых) фьючерсных позиций на рынке, выраженное в контрактах. Market Cap — общая стоимость актива (цена * circulating supply). Отношение (ratio) показывает, насколько "перегрет" или "интересен" рынок фьючерсов относительно размера актива. Это не прямой торговый сигнал, а инструмент для анализа ликвидности, спекуляции и рыночных настроений.
Pine Script® インジケーター
Vector_Trading_PEの投稿
MTF Market Bias+ (Smart Multi-Timeframe Trend Dashboard)The MTF Market Bias+ indicator provides a clear, data-driven view of market direction across multiple timeframes — from scalper to swing trader level. It automatically calculates the bullish / bearish / neutral bias for each selected timeframe using various configurable methods such as EMA slope, price vs EMA, or EMA50 vs EMA200. This tool gives you an instant overview of market alignment and helps you identify when lower and higher timeframes are in sync — the most powerful condition for high-probability trades. 🔍 Core Features ✅ Multi-Timeframe Bias Dashboard: Visual table showing bullish/bearish sentiment across your chosen timeframes (from 3m to 1W). ⚙️ Customizable Methods: Choose between EMA Slope (default) → detects trend direction by EMA momentum Price vs EMA → shows short-term strength or weakness EMA50 vs EMA200 → classic golden cross vs death cross structure 🎨 Configurable Colors, Size & Layout: Adjust background, text, and label sizes for any chart style. 📊 Summary Row: Displays the majority trend (bullish, bearish, or neutral) with real-time score. 🧩 Adaptive Background Mode (optional): Automatically colors your chart background according to overall bias. 💡 Method Info Panel: Clearly shows which method and parameters are active (e.g. “EMA Slope | EMA=50”). 📈 How to Use Add the indicator to your chart. Select the timeframes you want to monitor (e.g. 3m, 5m, 15m, 1h, 4h, D, W). Watch for alignment between lower and higher timeframes: When all turn green → strong bullish alignment → consider longs. When all turn red → strong bearish alignment → consider shorts. Mixed colors indicate consolidation or correction phases. Combine it with your favorite Fair Value Gap, CHOCH/BOS, or Liquidity Sweep strategy to significantly improve trade timing and confidence. 🧩 Author’s Note This indicator is designed for traders who want fast, visual confirmation of multi-timeframe structure without cluttering their charts. It’s simple, lightweight, and highly adaptable — whether you’re scalping on 3-minute charts or swing trading daily candles.
Pine Script® インジケーター
DaHarleyの投稿
2
Cumulative Volume Delta Profile and Heatmap [BackQuant]Cumulative Volume Delta Profile and Heatmap A multi-view CVD workstation that measures buying vs selling pressure, renders a price-aligned CVD profile with Point of Control, paints an optional heatmap of delta intensity, and detects classical CVD divergences using pivot logic. Built for reading who is in control, where participation clustered, and when effort is failing to produce result. What is CVD Cumulative Volume Delta accumulates the difference between aggressive buys and aggressive sells over time. When CVD rises, buyers are lifting the offer more than sellers are hitting the bid. When CVD falls, the opposite is true. Plotting CVD alongside price helps you judge whether price moves are supported by real participation or are running on fumes. Core Features Visual Analysis Components CVD Columns - Plot of cumulative delta, colored by side, for quick read of participation bias. CVD Profile - Price-aligned histogram of CVD accumulation using user-set bins. Shows where net initiative clustered. Split Buy and Sell CVD - Optional two-sided profile that separates positive and negative CVD into distinct wings. POC - Point of Control - The price level with the highest absolute CVD accumulation, labeled and line-marked. Heatmap - Semi-transparent blocks behind price that encode CVD intensity across the last N bars. Divergence Engine - Pivot-based detection of Bearish and Bullish CVD divergences with optional lines and labels. Stats Panel - Top level metrics: Total CVD, Buy and Sell totals with percentages, Delta Ratio, and current POC price. How it works Delta source and sampling You select an Anchor Timeframe that defines the higher time aggregation for reading the trend of CVD. The script pulls lower timeframe volume delta and aggregates it to the anchor window. You can let it auto-select the lower timeframe or force a custom one. CVD is then accumulated bar by bar to form a running total. This plot shows the direction and persistence of initiative. Profile construction The recent price range is split into Profile Granularity bins. As price traverses a bin, the current delta contribution is added to that bin. If Split Buy and Sell CVD is enabled, positive CVD goes to the right wing and negative CVD to the left wing. Widths are scaled by each side’s maximum so you can compare distribution shape at a glance. The Point of Control is the bin with the highest absolute CVD. This marks where initiative concentrated the most. Heatmap For each bin, the script computes intensity as absolute CVD relative to the maximum bin value. Color is derived from the side in control in that bin and shaded by intensity. Heatmap Length sets how far back the panels extend, highlighting recurring participation zones. Divergence model You define pivot sensitivity with Pivot Left and Right . Bearish divergence triggers when price confirms a higher high while CVD fails to make a higher high within a configurable Delta Tolerance . Bullish divergence triggers when price confirms a lower low while CVD fails to make a lower low. On trigger, optional link lines and labels are drawn at the pivots for immediate context. Key Settings Delta Source Anchor Timeframe - Higher TF for the CVD narrative. Custom Lower TF and Lower Timeframe - Force the sampling TF if desired. Pivot Logic Pivot Left and Right - Bars to each side for swing confirmation. Delta Tolerance - Small allowance to avoid near-miss false positives. CVD Profile Show CVD Profile - Toggle profile rendering. Split Buy and Sell CVD - Two-sided profile for clearer side attribution. Show Heatmap - Project intensity panels behind price. Show POC and POC Color - Mark the dominant CVD node. Profile Granularity - Number of bins across the visible price range. Profile Offset and Profile Width - Position and scale the profile. Profile Position - Right, Left, or Current bar alignment. Visuals Bullish Div Color and Bearish Div Color - Colors for divergence artifacts. Show Divergence Lines and Labels - Visualize pivots and annotations. Plot CVD - Column plot of total CVD. Show Statistics and Position - Toggle and place the summary table. Reading the display CVD columns Rising CVD confirms buyers are in control. Falling CVD confirms sellers. Flat or choppy CVD during wide price moves hints at passive or exhausted participation. CVD profile wings Thick right wing near a price zone implies heavy buy initiative accumulated there. Thick left wing implies heavy sell initiative. POC marks the strongest initiative node. Expect reactions on first touch and rotations around this level when the tape is balanced. Heatmap Brighter blocks indicate stronger historical net initiative at that price. Stacked bright bands form CVD high volume nodes. These often behave like magnets or shelves for future trade. Divergences Bearish - Price prints a higher high while CVD fails to do so. Effort is not producing result. Potential fade or pause. Bullish - Price prints a lower low while CVD fails to do so. Capitulation lacks initiative. Potential bounce or reversal. Stats panel Total CVD - Net initiative over the window. Buy and Sell volume with percentages - Side composition. Delta Ratio - Buy over Sell. Values above 1 favor buyers, below 1 favor sellers. POC Price - Current control node for plan and risk. Workflows Trend following Choose an Anchor Timeframe that matches your holding period. Trade in the direction of CVD slope while price holds above a bullish POC or below a bearish POC. Use pullbacks to CVD nodes on your profile as entry locations. Trend weakens when price makes new highs but CVD stalls, or new lows while CVD recovers. Mean reversion Look for divergences at or near prior CVD nodes, especially the POC. Fade tests into thick wings when the side that dominated there now fails to push CVD further. Target rotations back toward the POC or the opposite wing edge. Liquidity and execution map Treat strong wings and heatmap bands as probable passive interest zones. Expect pauses, partial fills, or flips at these shelves. Stops make sense beyond the far edge of the active wing supporting your idea. Alerts included CVD Bearish Divergence and CVD Bullish Divergence. Price Cross Above POC and Price Cross Below POC. Extreme Buy Imbalance and Extreme Sell Imbalance from Delta Ratio. CVD Turn Bullish and CVD Turn Bearish when net CVD crosses zero. Price Near POC proximity alert. Best practices Use a higher Anchor Timeframe to stabilize the CVD story and a sensible Profile Granularity so wings are readable without clutter. Keep Split mode on when you want to separate initiative attribution. Turn it off when you prefer a single net profile. Tune Pivot Left and Right by instrument to avoid overfitting. Larger values find swing divergences. Smaller values find micro fades. If volume is thin or synthetic for the symbol, CVD will be less reliable. The script will warn if volume is zero. Trading applications Context - Confirm or question breakouts with CVD slope. Location - Build entries at CVD nodes and POC. Timing - Use divergence and POC crosses for triggers. Risk - Place stops beyond the opposite wing or outside the POC shelf. Important notes and limits This is a price and volume based study. It does not access off-book or venue-level order flow. CVD profiles are built from the data available on your chart and the chosen lower timeframe sampling. Like all volume tools, readings can distort during roll periods, holidays, or feed anomalies. Validate on your instrument. Technical notes Delta is aggregated from a lower timeframe into an Anchor Timeframe narrative. Profile bins update in real time. Splitting by side scales each wing independently so both are readable in the same panel. Divergences are confirmed using standard pivot definitions with user-set tolerances. All profile drawing uses fixed X offsets so panels and POC do not swim when you scroll. Quick start Anchor Timeframe = Daily for intraday context. Split Buy and Sell CVD = On. Profile Granularity = 100 to 200, Profile Position = Right, Width to taste. Pivot Left and Right around 8 to 12 to start, then adapt. Turn on Heatmap for a fast map of interest bands. Bottom line CVD tells you who is doing the lifting. The profile shows where they did it. Divergences tell you when effort stops paying. Put them together and you get a clear read on control, location, and timing for both trend and mean reversion.
Pine Script® インジケーター
BackQuantの投稿
9
Inside Bar Highlighter by nkChartsOverview: The Inside Candle Highlighter is a simple yet powerful TradingView indicator designed to identify inside bars (inside candles) on your chart. An inside candle is defined as a candle whose high is lower than the previous candle's high and low is higher than the previous candle's low, meaning it forms entirely within the range of the preceding candle. Inside candles are commonly interpreted by traders as periods of market consolidation or indecision and often precede breakouts or significant price moves. This indicator highlights these candles directly on your chart, making them easy to spot at a glance. Features Detects Inside Candles: Automatically identifies bars that are fully contained within the previous bar’s high-low range. Confirmed Bar Coloring: Colors the candle after it closes, ensuring no repainting occurs during formation. Style Tab Customization: Users can adjust the candle color directly from the Style tab, allowing seamless integration with your chart theme. Clean & Minimal: Only inside candles are highlighted, keeping charts uncluttered. How Traders Can Use It Identify Consolidation Zones: Quickly spot periods where the market is contracting. Prepare for Breakouts: Inside candles often signal an upcoming directional move; traders can plan entry or exit points based on breakouts from the inside candle range. Combine With Other Indicators: Use alongside trend indicators, volume tools, or support/resistance levels to enhance trade confirmation. Recommended Use Works on all timeframes — from intraday charts to daily or weekly charts. Particularly useful in price action trading, swing trading, and trend-following strategies. Ideal for traders who want a visual cue for consolidation and potential breakout areas without adding complexity to the chart. Note: This indicator only highlights inside candles. Interpretation and trading decisions are left to the user.
Pine Script® インジケーター
nkChartsの投稿
Nifty vs Nifty Fut Premium indicator This indicator compares Nifty Spot and Nifty Futures prices in real-time, displaying the premium (or discount) between them at the top of the pane. Trading applications: Arbitrage opportunities: When the premium becomes unusually high or low compared to fair value (based on cost of carry), traders can exploit the mispricing through cash-futures arbitrage Market sentiment: A rising premium often indicates bullish sentiment as traders are willing to pay more for futures, while a declining or negative premium suggests bearish sentiment Rollover strategy: Near expiry, monitoring the premium helps traders decide optimal timing for rolling positions from current month to next month contracts Risk assessment: Sudden spikes in premium can signal increased demand for leveraged long positions, potentially indicating overbought conditions or strong momentum
Pine Script® インジケーター
manishchaksの投稿
🐬RSI_CandleRSI_Candle Calculates the RSI based on the open, high, low, and close prices, and displays it in the form of candles. The overbought and oversold zones are highlighted with background colors, which become darker as the RSI value approaches 100 or 0. ----- RSI_Candle RSI를 시가, 고가, 저가, 종가로 계산하여 캔들로 보여줍니다. 과매수/과매도 구간에서 배경색으로 보여주며, 100/0에 가까울수록 배경색이 짙어집니다. -----
Pine Script® インジケーター
BossOfDolphinGang_の投稿
Session-Conditioned Regime ATRWhy this exists Classic ATR is great—until the open. The first few bars often inherit overnight gaps and 24-hour noise that have nothing to do with the intraday regime you actually trade. That inflates early ATR, scrambles thresholds, and invites hyper-recency bias (“today is crazy!”) when it’s just the open being the open. This tool was built to: Separate session reality from 24h noise. Measure volatility only inside your defined session (e.g., NYSE 09:30–16:00 ET). Judge candles against the current regime, not the last 2–3 bars. A rolling statistic from the last N completed sessions defines what “typical” means right now. Label “large” and “small” objectively. Bars are colored only when True Range meaningfully departs from the session regime—no gut feel, no open-bar distortion (gap inclusion optional). Overview Purpose: objectively identify unusually big or small candles within the active trading session, compared to the recent session regime. Use cases: volatility filters, entry/exit confirmation, session bias detection, adaptive sizing. This indicator replaces generic ATR with a session-conditioned, regime-aware measure. It colors candles only when their True Range (TR) is abnormally large/small versus the last N completed sessions of the same session window. How it works Session gating: Only bars inside the selected session are evaluated (presets for NYSE, CME RTH, FX NY; custom supported). Per-bar TR: TR = max(high, prevRef) − min(low, prevRef). prevRef is the prior close for in-session bars. First bar of the session can include the overnight gap (optional; default off). Regime statistic: For any bar in session k, aggregate all in-session TRs from the previous N completed sessions (k−N … k−1), then compute Median (default) or Mean. Today’s anchor: Running statistic from today’s session start → current bar (for context and the on-chart ratio). Color logic: Big if TR ≥ bigMult × RegimeStat Small if TR ≤ smallMult × RegimeStat Colored states: big bull, big bear, small bull, small bear. Non-triggering bars retain the chart’s native colors. Panel (top-right by default) Regime ATR (Nd): session-conditioned statistic over the past N completed sessions. Today ATR (anchored): running statistic for the current session. Ratio (Today/Regime): intraday volatility vs regime. Sample size n: number of bars used in the regime calculation. Inputs Session Preset: NYSE (09:30–16:00 ET), CME RTH (08:30–15:00 CT), FX NY (08:00–17:00 ET), Custom (session + IANA timezone). Regime Window: number of completed sessions (default 5). Statistic: Median (robust) or Mean. Include Open Gap: include overnight gap in the first in-session bar’s TR (default off). Big/Small thresholds: multipliers relative to RegimeStat (defaults: Big=1.5×, Small=0.67×). Colors: four independent colors for big/small × bull/bear. Panel position & text size. Hidden outputs: expose RegimeStat, TodayStat, Ratio, and Z-score to other scripts. Alerts RegimeATR: BIG bar — triggers when a bar meets the “Big” condition. RegimeATR: SMALL bar — triggers when a bar meets the “Small” condition. Hidden outputs (for strategies/screeners) RegimeATR_stat, TodayATR_stat, Today_vs_Regime_Ratio, BarTR_Zscore. Notes & limitations No look-ahead: calculations only use information available up to that bar. Historical colors reflect what would have been known then. Warm-up: colors begin once there are at least N completed sessions; before that, regime is undefined by design. Changing inputs (session window, multipliers, median/mean, gap toggle) recomputes the full series using the same rolling regime logic per bar. Designed for standard candles. Styling respects existing chart colors when no condition triggers. Practical tips For a broader or tighter notion of “unusual,” adjust Big/Small multipliers. Prefer Median in markets prone to outliers; use Mean if you want Z-score alignment with the panel’s regime mean/std. Use the Ratio readout to spot compression/expansion days quickly (e.g., <0.7× = compressed session, >1.3× = expanded). Roadmap More session presets: 24h continuous (crypto, index CFDs). 23h/Globex futures (CME ETH with a 60-minute maintenance break). Regional equities (LSE, Xetra, TSE), Asia/Europe/NY overlaps for FX. Half-day/holiday templates and dynamic calendars. Multi-regime comparison: track multiple overlapping regimes (e.g., RTH vs ETH for futures) and show separate stats/ratios. Robust stats options: trimmed mean, MAD/Huber alternatives; optional percentile thresholds instead of fixed multipliers. Subpanel visuals: rolling TodayATR and Ratio plots; optional Z-score ribbon. Screener/strategy hooks: export boolean series for BIG/SMALL, plus a lightweight strategy template for backtesting entries/exits conditioned on regime volatility. Performance/QOL: per-symbol presets, smarter warm-up, and finer control over sample caps for ultra-low TF charts. Changelog v0.9b (Beta) Session presets (NYSE/CME RTH/FX NY/Custom) with timezone handling. Panel enhancements: ratio + sample size n. Four-state bar coloring (big/small × bull/bear). Alerts for BIG/SMALL bars. Hidden Z-score stream for downstream use. Gap-in-TR toggle for the first in-session bar. Disclaimer For educational purposes only. Not investment advice. Validate thresholds and session settings across symbols/timeframes before live use.
Pine Script® インジケーター
scottallenの投稿
Kalman Filter [DCAUT]█ Kalman Filter 📊 ORIGINALITY & INNOVATION The Kalman Filter represents an important adaptation of aerospace signal processing technology to financial market analysis. Originally developed by Rudolf E. Kalman in 1960 for navigation and guidance systems, this implementation brings the algorithm's noise reduction capabilities to price trend analysis. This implementation addresses a common challenge in technical analysis: the trade-off between smoothness and responsiveness. Traditional moving averages must choose between being smooth (with increased lag) or responsive (with increased noise). The Kalman Filter improves upon this limitation through its recursive estimation approach, which continuously balances historical trend information with current price data based on configurable noise parameters. The key advancement lies in the algorithm's adaptive weighting mechanism. Rather than applying fixed weights to historical data like conventional moving averages, the Kalman Filter dynamically adjusts its trust between the predicted trend and observed prices. This allows it to provide smoother signals during stable periods while maintaining responsiveness during genuine trend changes, helping to reduce whipsaws in ranging markets while not missing significant price movements. 📐 MATHEMATICAL FOUNDATION The Kalman Filter operates through a two-phase recursive process: Prediction Phase: The algorithm first predicts the next state based on the previous estimate: State Prediction: Estimates the next value based on current trend Error Covariance Prediction: Calculates uncertainty in the prediction Update Phase: Then updates the prediction based on new price observations: Kalman Gain Calculation: Determines the weight given to new measurements State Update: Combines prediction with observation based on calculated gain Error Covariance Update: Adjusts uncertainty estimate for next iteration Core Parameters: Process Noise (Q): Represents uncertainty in the trend model itself. Higher values indicate the trend can change more rapidly, making the filter more responsive to price changes. Measurement Noise (R): Represents uncertainty in price observations. Higher values indicate less trust in individual price points, resulting in smoother output. Kalman Gain Formula: The Kalman Gain determines how much weight to give new observations versus predictions: K = P(k|k-1) / (P(k|k-1) + R) Where: K is the Kalman Gain (0 to 1) P(k|k-1) is the predicted error covariance R is the measurement noise parameter When K approaches 1, the filter trusts new measurements more (responsive). When K approaches 0, the filter trusts its prediction more (smooth). This dynamic adjustment mechanism allows the filter to adapt to changing market conditions automatically, providing an advantage over fixed-weight moving averages. 📊 COMPREHENSIVE SIGNAL ANALYSIS Visual Trend Indication: The Kalman Filter line provides color-coded trend information: Green Line: Indicates the filter value is rising, suggesting upward price momentum Red Line: Indicates the filter value is falling, suggesting downward price momentum Gray Line: Indicates sideways movement with no clear directional bias Crossover Signals: Price-filter crossovers generate trading signals: Golden Cross: Price crosses above the Kalman Filter line, suggests potential bullish momentum development, may indicate a favorable environment for long positions, filter will naturally turn green as it adapts to price moving higher Death Cross: Price crosses below the Kalman Filter line, suggests potential bearish momentum development, may indicate consideration for position reduction or shorts, filter will naturally turn red as it adapts to price moving lower Trend Confirmation: The filter serves as a dynamic trend baseline: Price Consistently Above Filter: Confirms established uptrend Price Consistently Below Filter: Confirms established downtrend Frequent Crossovers: Suggests ranging or choppy market conditions Signal Reliability Factors: Signal quality varies based on market conditions: Higher reliability in trending markets with sustained directional moves Lower reliability in choppy, range-bound conditions with frequent reversals Parameter adjustment can help adapt to different market volatility levels 🎯 STRATEGIC APPLICATIONS Trend Following Strategy: Use the Kalman Filter as a dynamic trend baseline: Enter long positions when price crosses above the filter Enter short positions when price crosses below the filter Exit when price crosses back through the filter in the opposite direction Monitor filter slope (color) for trend strength confirmation Dynamic Support/Resistance: The filter can act as a moving support or resistance level: In uptrends: Filter often provides dynamic support for pullbacks In downtrends: Filter often provides dynamic resistance for bounces Price rejections from the filter can offer entry opportunities in trend direction Filter breaches may signal potential trend reversals Multi-Timeframe Analysis: Combine Kalman Filters across different timeframes: Higher timeframe filter identifies primary trend direction Lower timeframe filter provides precise entry and exit timing Trade only in direction of higher timeframe trend for better probability Use lower timeframe crossovers for position entry/exit within major trend Volatility-Adjusted Configuration: Adapt parameters to match market conditions: Low Volatility Markets (Forex majors, stable stocks): Use lower process noise for stability, use lower measurement noise for sensitivity Medium Volatility Markets (Most equities): Process noise default (0.05) provides balanced performance, measurement noise default (1.0) for general-purpose filtering High Volatility Markets (Cryptocurrencies, volatile stocks): Use higher process noise for responsiveness, use higher measurement noise for noise reduction Risk Management Integration: Use filter as a trailing stop-loss level in trending markets Tighten stops when price moves significantly away from filter (overextension) Wider stops in early trend formation when filter is just establishing direction Consider position sizing based on distance between price and filter 📋 DETAILED PARAMETER CONFIGURATION Source Selection: Determines which price data feeds the algorithm: OHLC4 (default): Uses average of open, high, low, close for balanced representation Close: Focuses purely on closing prices for end-of-period analysis HL2: Uses midpoint of high and low for range-based analysis HLC3: Typical price, gives more weight to closing price HLCC4: Weighted close price, emphasizes closing values Process Noise (Q) - Adaptation Speed Control: This parameter controls how quickly the filter adapts to changes: Technical Meaning: Represents uncertainty in the underlying trend model Higher values allow the estimated trend to change more rapidly Lower values assume the trend is more stable and slow-changing Practical Impact: Lower Values: Produces very smooth output with minimal noise, slower to respond to genuine trend changes, best for long-term trend identification, reduces false signals in choppy markets Medium Values: Balanced responsiveness and smoothness, suitable for swing trading applications, default (0.05) works well for most markets Higher Values: More responsive to price changes, may produce more false signals in ranging markets, better for short-term trading and day trading, captures trend changes earlier, adjust freely based on market characteristics Measurement Noise (R) - Smoothing Control: This parameter controls how much the filter trusts individual price observations: Technical Meaning: Represents uncertainty in price measurements Higher values indicate less trust in individual price points Lower values make each price observation more influential Practical Impact: Lower Values: More reactive to each price change, less smoothing with more noise in output, may produce choppy signals Medium Values: Balanced smoothing and responsiveness, default (1.0) provides general-purpose filtering Higher Values: Heavy smoothing for very noisy markets, reduces whipsaws significantly but increases lag in trend change detection, best for cryptocurrency and highly volatile assets, can use larger values for extreme smoothing Parameter Interaction: The ratio between Process Noise and Measurement Noise determines overall behavior: High Q / Low R: Very responsive, minimal smoothing Low Q / High R: Very smooth, maximum lag reduction Balanced Q and R: Middle ground for most applications Optimization Guidelines: Start with default values (Q=0.05, R=1.0) If too many false signals: Increase R or decrease Q If missing trend changes: Decrease R or increase Q Test across different market conditions before live use Consider different settings for different timeframes 📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES Comparison with Traditional Moving Averages: Versus Simple Moving Average (SMA): The Kalman Filter typically responds faster to genuine trend changes Produces smoother output than SMA of comparable length Better noise reduction in ranging markets More configurable for different market conditions Versus Exponential Moving Average (EMA): Similar responsiveness but with better noise filtering Less prone to whipsaws in choppy conditions More adaptable through dual parameter control (Q and R) Can be tuned to match or exceed EMA responsiveness while maintaining smoothness Versus Hull Moving Average (HMA): Different noise reduction approach (recursive estimation vs. weighted calculation) Kalman Filter offers more intuitive parameter adjustment Both reduce lag effectively, but through different mechanisms Kalman Filter may handle sudden volatility changes more gracefully Response Characteristics: Lag Time: Moderate and configurable through parameter adjustment Noise Reduction: Good to excellent, particularly in volatile conditions Trend Detection: Effective across multiple timeframes False Signal Rate: Typically lower than simple moving averages in ranging markets Computational Efficiency: Efficient recursive calculation suitable for real-time use Optimal Use Cases: Markets with mixed trending and ranging periods Assets with moderate to high volatility requiring noise filtering Multi-timeframe analysis requiring consistent methodology Systematic trading strategies needing reliable trend identification Situations requiring balance between responsiveness and smoothness Known Limitations: Parameters require adjustment for different market volatility levels May still produce false signals during extreme choppy conditions No single parameter set works optimally for all market conditions Requires complementary indicators for comprehensive analysis Historical performance characteristics may not persist in changing market conditions USAGE NOTES This indicator is designed for technical analysis and educational purposes. The Kalman Filter's effectiveness varies with market conditions, tending to perform better in markets with clear trending phases interrupted by consolidation. Like all technical indicators, it has limitations and should not be used as the sole basis for trading decisions, but rather as part of a comprehensive trading approach. Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Always test thoroughly with different parameter settings across various market conditions before using in live trading. No technical indicator can predict future price movements with certainty, and all trading involves risk of loss.
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