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Historical Volatility

Liquidity & Momentum Master (LMM)💎 Liquidity & Momentum Master (LMM) A professional dual-system indicator that combines: 📦 High-Volume Support/Resistance Zones and 📊 RSI + Bollinger Band Combo Signals — to visualize both smart money footprints and momentum reversals in one clean tool. 🧱 1. High-Volume Liquidity Zones (Support/Resistance Boxes) Conditions Visible only on 1H and higher timeframes (1H, 4H, 1D, etc.) Detects candles with abnormally high volume and strong ATR-based range Separates bullish (support) and bearish (resistance) zones Visualization All boxes are white, with adjustable transparency (alphaW, alphaBorder) Each box extends to the right automatically Only the most important (Top-N) zones are kept — weaker ones are removed automatically Interpretation White boxes = price areas with heavy liquidity and volume concentration Price approaching these zones often leads to bounces or rejections Narrow spacing = consolidation, wide spacing = potential large move 💎 2. RSI Exit + BB-RSI Combo Signals RSI Exit (Overbought/Oversold Recovery) RSI drops from overbought (>70) → plots red “RSI” above the candle RSI rises from oversold (<30) → plots green “RSI” below the candle Works on 15m, 30m, 1H, 4H, 1D → Indicates short-term exhaustion recovery BB-RSI Combo (Momentum Reversal Confirmation) Active on 1H and higher only Requires both: ✅ RSI divergence (bullish or bearish) ✅ Bollinger Band re-entry (after temporary breakout) Combo Buy (Green Diamond) Bullish RSI divergence Candle closes back above lower Bollinger Band Combo Sell (Red Diamond) Bearish RSI divergence Candle closes back below upper Bollinger Band → Confirms stronger reversal momentum compared to standard RSI signals
Pine Script® indicator
by HSeungpyo
HTF Ranges - AWR/AMR/AYR [bilal]📊 Overview Professional higher timeframe range indicator for swing and position traders. Calculate Average Weekly Range (AWR), Average Monthly Range (AMR), and Average Yearly Range (AYR) with precision projection levels. ✨ Key Features 📅 Three Timeframe Modes AWR (Average Weekly Range): Weekly swing targets - Default 4 weeks AMR (Average Monthly Range): Monthly position targets - Default 6 months AYR (Average Yearly Range): Yearly extremes - Default 9 years 🎯 Dual Anchor Options Period Open: Week/Month/Year opening price RTH Open: First RTH session (09:30 NY) of the period 📐 Projection Levels 100% Range Levels: Upper and lower targets from anchor Fractional Levels: 33% and 66% zones for partial targets Custom Mirrored Levels: Set any percentage (0-200%) with automatic mirroring Example: 25% shows both 25% and 75% Example: 150% shows both 150% and -50% 📊 Information Table Active range type (AWR/AMR/AYR) Average range value for selected period Current period range and percentage used Distance remaining to targets (up/down) Color-coded progress (green/orange/red) 🎨 Fully Customizable Orange theme by default (differentiates from daily indicators) Line colors, styles (solid/dashed/dotted), and widths Toggle labels on/off Adjustable lookback periods for each timeframe Independent settings for each range type ⚡ Smart Features Lines start at actual period open (not fixed lookback) Automatically tracks current period high/low Works on any chart timeframe Real-time range tracking Alert conditions when targets reached or exceeded 🎯 Use Cases AWR (Weekly Ranges): Swing trade targets (3-7 day holds) Weekly support/resistance zones Identify weekly trend vs rotation Compare daily moves to weekly context AMR (Monthly Ranges): Position trade targets (2-4 week holds) Monthly breakout levels Institutional-level zones Earnings play targets AYR (Yearly Ranges): Major reversal zones Long-term support/resistance Identify macro trend strength Annual high/low projections 💡 Trading Strategies AWR Strategy (Swing Trading): Week opens near AWR lower level = potential long setup Target AWR 66% and 100% levels Week hits AWR upper in first 2 days = watch for reversal Use fractional levels as scale-in/scale-out points AMR Strategy (Position Trading): Month opens near AMR extremes = fade setup Month breaks AMR in week 1 = expansion (trend) month Target opposite AMR extreme for swing positions Use 33%/66% for partial profit taking AYR Strategy (Long-term Context): Price near AYR extremes = major reversal zones Breaking AYR levels = historic moves (rare) Use for macro trend confirmation Great for yearly forecasting and planning 📊 Range Interpretation <33% Range Used: Early in period, room for expansion 33-66% Range Used: Normal progression 66-100% Range Used: Extended, approaching extremes >100% Range Used: Expansion period - trending or high volatility ⚙️ Settings Guide Lookback Periods: AWR: 4 weeks (standard) - adjust to 8-12 for smoother average AMR: 6 months (standard) - seasonal patterns AYR: 9 years (standard) - captures full cycles Anchor Type: Period Open: Use for clean week/month/year open reference RTH Open: Use if you only trade day session, ignores overnight gaps Custom Levels: 25% = quartile targets 75% = three-quarter targets 80% = "danger zone" for reversals 111% = extended breakout target 🔄 Combine with ADR Indicator Run both indicators together for complete multi-timeframe analysis: ADR for intraday precision AWR/AMR/AYR for swing/position context See if today's ADR move is significant in weekly/monthly context Multi-timeframe confluence = highest probability setups 💼 Ideal For Swing Traders: Use AWR for 3-10 day holds Position Traders: Use AMR for 2-8 week holds Long-term Investors: Use AYR for macro context Index Futures Traders: ES, NQ, YM, RTY Multi-timeframe Analysis: Combine with daily ADR
Pine Script® indicator
by bilalmil
Exact-Month Avg & Vol (USDT) + Winsor/Clip/RV - V0.95d by McTogaWhat the indicator does 1) Data basis & window Uses the chart symbol by default (or manually via input). Works internally with daily closing prices (request.security(..., “D”, ...)) – regardless of whether you use D/W/M in the chart. Exact monthly logic: The evaluation window is determined by actual calendar months (1/3/6/12 or custom), not by fixed 30/90 days. 2) Returns & preprocessingReturn definition selectable: logarithmic (default) or simple return – each in %/day. Winsorizing (lower/upper percentile) and clipping (|r| ≤ X percentage points) optional to limit outliers. 3) Key figures (not annualized)Arithmetic daily volatility: Mean of absolute daily returns in %.Median volatility: Median of absolute daily returns in %. Standard deviation (StdDev) of daily returns in %. Realized variance (RV) = Σ r² and √RV (indicative of cumulative realized vol). 4) Annualization (optional) Basis 252 or 365 days. For |r|-based measures (arithmetic/median), optional Abs→Sigma factor √(π/2) to bring them closer to StdDev. Provides arithmetic p.a., median p.a., StdDev p.a., RV p.a.. 5) Additional metrics Avg Price: Arithmetic average of daily closes in the window. Days (effDays): Number of trading days actually considered in the window. 6) Display & operation Only active on D/W/M (intraday everything is suppressed). Short mode (default): compact table with Avg Price • Days • Arith Vol • Median Vol • StdDev • √RV • Arith p.a. • Median p.a. • StdDev p.a. • RV p.a. Full mode: detailed table; individual rows can be toggled (Avg Price, Arith/Median/StdDev, RV, Annuals). Positions: table can be selected at 4 corners; toggle without restarting. Label (optional): compact text summary on the chart (corner selectable). Price plot (optional): 1D close as overlay. 7) Help, Debug & AlertsOnline help: 3 lines in the status bar (Help-On variant).Debug table (optional): shows RetCount, Winsor limits, clip status, key figures.Alert: Trigger when arithmetic daily volatility ≥ threshold value. 8) RobustnessTables/label handles are correctly deleted/recreated when TF/mode/position changes.No prohibited global writes in functions; clear typing (no na on bool).Typical useSelect monthly window (e.g., 3M) → optionally set Winsor/clip.Short or full as needed; select position. Annualization on/off; activate Abs→Sigma if necessary. Optional: Switch on label/price plot/debug; set alert threshold.
Pine Script® indicator
by TorstenGast
Volatility Dashboard (ATR-Based)Here's a brief description of what this indicator does: - This measures volatility of currents based on ATR (Average True Range) and plots them against the smoothed ATR baseline (SMA of ATR for the same periods). - It categorizes the market as one of the three regimes depending on the above-mentioned ratio: - High Volatility (ratio > 1.2) - Normal Volatility (between 0.8 and 1.2), |- Low Volatility (ratio < 0.8, green) - For each type of trading regime, Value Area (VA) coverage to use: for example: 60-65% in high vol trade regimes, 70% in normal trade regimes, 80-85% in low trade regimes * What you’ll see on the chart: - Compact dashboard in the top-right corner featuring: - ATR (present, default length 20) - ATR Avg (ATR baseline) - The volatility regime identified based on the color-coded background and the coverage recommended for the VA. Important inputs that can be adjusted: - ATR Length (default 20) - “High/Low volatility thresholds” (default values: 1.2 – The VA coverage recommendations for each scheme (text) Purpose: - Quickly determine whether volatility is above/below average and adjust the coverage of the Value Area. If you're using this for the GC1! Use 14 ATR Length, For ES or NQ Use Default Setting(20)
Pine Script® indicator
by sandunmathers
Volatility Cones **Volatility Cones - Interactive** This indicator visualizes volatility cones based on historical or manual volatility and projects them up to 252 trading days into the future. **Features:** - Automatic start at the first trading day of the year (customizable) - Volatility calculation from historical data or manual input - Display of ±1σ, ±2σ, and ±3σ bands - Projection of expected price movements based on volatility **Use Case:** Ideal for options traders and risk management to assess expected price movements over different time horizons.
Pine Script® indicator
by lejo_joh
MTF K-Means Price Regimes [matteovesperi] ⚠️ The preview uses a custom example to identify support/resistance zones. due to the fact that this identifier clusterizes, this is possible. this example was set up "in a hurry", therefore it has a possible inaccuracy. When setting up the indicator, it is extremely important to select the correct parameters and double-check them on the selected history. 📊 OVERVIEW Purpose MTF K-Means Price Regimes is a TradingView indicator that automatically identifies and classifies the current market regime based on the K-Means machine learning algorithm. The indicator uses data from a higher timeframe (Multi-TimeFrame, MTF) to build stable classification and applies it to the working timeframe in real-time. Key Features ✅ Automatic market regime detection — the algorithm finds clusters of similar market conditions ✅ Multi-timeframe (MTF) — clustering on higher TF, application on lower TF ✅ Adaptive — model recalculates when a new HTF bar appears with a rolling window ✅ Non-Repainting — classification is performed only on closed bars ✅ Visualization — bar coloring + information panel with cluster characteristics ✅ Flexible settings — from 2 to 10 clusters, customizable feature periods, HTF selection ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔬 TECHNICAL DETAILS K-Means Clustering Algorithm What is K-Means? K-Means is one of the most popular clustering algorithms (unsupervised machine learning). It divides a dataset into K groups (clusters) so that similar elements are within each cluster, and different elements are between clusters. Algorithm objective: Minimize within-cluster variance (sum of squared distances from points to their cluster center). How Does K-Means Work in Our Indicator? Step 1: Data Collection The indicator accumulates history from the higher timeframe (HTF): RSI (Relative Strength Index) — overbought/oversold indicator ATR% (Average True Range as % of price) — volatility indicator ΔP% (Price Change in %) — trend strength and direction indicator By default, 200 HTF bars are accumulated (clusterLookback parameter). Step 2: Creating Feature Vectors Each HTF bar is described by a three-dimensional vector: Vector = Step 3: Normalization (Z-Score) All features are normalized to bring them to a common scale: Normalized_Value = (Value - Mean) / StdDev This is critically important, as RSI is in the range 0-100, while ATR% and ΔP% have different scales. Without normalization, one feature would dominate over others. Step 4: K-Means++ Centroid Initialization Instead of random selection of K initial centers, an improved K-Means++ method is used: First centroid is randomly selected from the data Each subsequent centroid is selected with probability proportional to the square of the distance to the nearest already selected centroid This ensures better initial centroid distribution and faster convergence Step 5: Iterative Optimization (Lloyd's Algorithm) Repeat until convergence (or maxIterations): 1. Assignment step: For each point find the nearest centroid and assign it to this cluster 2. Update step: Recalculate centroids as the average of all points in each cluster 3. Convergence check: If centroids shifted less than 0.001 → STOP Euclidean distance in 3D space is used: Distance = sqrt((RSI1 - RSI2)² + (ATR1 - ATR2)² + (ΔP1 - ΔP2)²) Step 6: Adaptive Update With each new HTF bar: The oldest bar is removed from history (rolling window method) New bar is added to history K-Means algorithm is executed again on updated data Model remains relevant for current market conditions Real-Time Classification After building the model (clusters + centroids), the indicator works in classification mode: On each closed bar of the current timeframe, RSI, ATR%, ΔP% are calculated Feature vector is normalized using HTF statistics (Mean/StdDev) Distance to all K centroids is calculated Bar is assigned to the cluster with minimum distance Bar is colored with the corresponding cluster color Important: Classification occurs only on a closed bar (barstate.isconfirmed), which guarantees no repainting . Data Architecture Persistent variables (var): ├── featureVectors - Normalized HTF feature vectors ├── centroids - Cluster center coordinates (K * 3 values) ├── assignments - Assignment of each HTF bar to a cluster ├── htfRsiHistory - History of RSI values from HTF ├── htfAtrHistory - History of ATR values from HTF ├── htfPcHistory - History of price changes from HTF ├── htfCloseHistory - History of close prices from HTF ├── htfRsiMean, htfRsiStd - Statistics for RSI normalization ├── htfAtrMean, htfAtrStd - Statistics for ATR normalization ├── htfPcMean, htfPcStd - Statistics for Price Change normalization ├── isCalculated - Model readiness flag └── currentCluster - Current active cluster All arrays are synchronized and updated atomically when a new HTF bar appears. Computational Complexity Data collection: O(1) per bar K-Means (one pass): - Assignment: O(N * K) where N = number of points, K = number of clusters - Update: O(N * K) - Total: O(N * K * I) where I = number of iterations (usually 5-20) Example: With N=200 HTF bars, K=5 clusters, I=20 iterations: 200 * 5 * 20 = 20,000 operations (executes quickly) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📖 USER GUIDE Quick Start 1. Adding the Indicator TradingView → Indicators → Favorites → MTF K-Means Price Regimes Or copy the code from mtf_kmeans_price_regimes.pine into Pine Editor. 2. First Launch When adding the indicator to the chart, you'll see a table in the upper right corner: ┌─────────────────────────┐ │ Status │ Collecting HTF │ ├─────────────────────────┤ │ Collected│ 15 / 50 │ └─────────────────────────┘ This means the indicator is accumulating history from the higher timeframe. Wait until the counter reaches the minimum (default 50 bars for K=5). 3. Active Operation After data collection is complete, the main table with cluster information will appear: ┌────┬──────┬──────┬──────┬──────────────┬────────┐ │ ID │ RSI │ ATR% │ ΔP% │ Description │Current │ ├────┼──────┼──────┼──────┼──────────────┼────────┤ │ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │ │ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │ │ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │ └────┴──────┴──────┴──────┴──────────────┴────────┘ The arrow ► indicates the current active regime. Chart bars are colored with the corresponding cluster color. Customizing for Your Strategy Choosing Higher Timeframe (HTF) Rule: HTF should be at least 4 times higher than the working timeframe. | Working TF | Recommended HTF | |------------|-----------------| | 1 min | 15 min - 1H | | 5 min | 1H - 4H | | 15 min | 4H - D | | 1H | D - W | | 4H | D - W | | D | W - M | HTF Selection Effect: Lower HTF (closer to working TF): More sensitive, frequently changing classification Higher HTF (much larger than working TF): More stable, long-term regime assessment Number of Clusters (K) K = 2-3: Rough division (e.g., "uptrend", "downtrend", "flat") K = 4-5: Optimal for most cases (DEFAULT: 5) K = 6-8: Detailed segmentation (requires more data) K = 9-10: Very fine division (only for long-term analysis with large windows) Important constraint: clusterLookback ≥ numClusters * 10 I.e., for K=5 you need at least 50 HTF bars, for K=10 — at least 100 bars. Clustering Depth (clusterLookback) This is the rolling window size for building the model. 50-100 HTF bars: Fast adaptation to market changes 200 HTF bars: Optimal balance (DEFAULT) 500-1000 HTF bars: Long-term, stable model If you get an "Insufficient data" error: Decrease clusterLookback Or select a lower HTF (e.g., "4H" instead of "D") Or decrease numClusters Color Scheme Default 10 colors: Red → Often: strong bearish, high volatility Orange → Transition, medium volatility Yellow → Neutral, decreasing activity Green → Often: strong bullish, high volatility Blue → Medium bullish, medium volatility Purple → Oversold, possible reversal Fuchsia → Overbought, possible reversal Lime → Strong upward momentum Aqua → Consolidation, low volatility White → Undefined regime (rare) Important: Cluster colors are assigned randomly at each model recalculation! Don't rely on "red = bearish". Instead, look at the description in the table (RSI, ATR%, ΔP%). You can customize colors in the "Colors" settings section. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ INDICATOR PARAMETERS Main Parameters Higher Timeframe (htf) Type: Timeframe selection Default: "D" (daily) Description: Timeframe on which the clustering model is built Recommendation: At least 4 times larger than your working TF Clustering Depth (clusterLookback) Type: Integer Range: 50 - 2000 Default: 200 Description: Number of HTF bars for building the model (rolling window size) Recommendation: - Increase for more stable long-term model - Decrease for fast adaptation or if there's insufficient historical data Number of Clusters (K) (numClusters) Type: Integer Range: 2 - 10 Default: 5 Description: Number of market regimes the algorithm will identify Recommendation: - K=3-4 for simple strategies (trending/ranging) - K=5-6 for universal strategies - K=7-10 only when clusterLookback ≥ 100*K Max K-Means Iterations (maxIterations) Type: Integer Range: 5 - 50 Default: 20 Description: Maximum number of algorithm iterations Recommendation: - 10-20 is sufficient for most cases - Increase to 30-50 if using K > 7 Feature Parameters RSI Period (rsiLength) Type: Integer Default: 14 Description: Period for RSI calculation (overbought/oversold feature) Recommendation: - 14 — standard - 7-10 — more sensitive - 20-25 — more smoothed ATR Period (atrLength) Type: Integer Default: 14 Description: Period for ATR calculation (volatility feature) Recommendation: Usually kept equal to rsiLength Price Change Period (pcLength) Type: Integer Default: 5 Description: Period for percentage price change calculation (trend feature) Recommendation: - 3-5 — short-term trend - 10-20 — medium-term trend Visualization Show Info Panel (showDashboard) Type: Checkbox Default: true Description: Enables/disables the information table on the chart Cluster Color 1-10 Type: Color selection Description: Customize colors for visual cluster distinction Recommendation: Use contrasting colors for better readability ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 INTERPRETING RESULTS Reading the Information Table ┌────┬──────┬──────┬──────┬──────────────┬────────┐ │ ID │ RSI │ ATR% │ ΔP% │ Description │Current │ ├────┼──────┼──────┼──────┼──────────────┼────────┤ │ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │ │ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │ │ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │ │ 4 │ 45.0 │ 1.20 │ -0.3 │ Low Vol,Bear │ │ │ 5 │ 72.1 │ 3.05 │ 2.8 │ High Vol,Bull│ │ └────┴──────┴──────┴──────┴──────────────┴────────┘ "ID" Column Cluster number (1-K). Order doesn't matter. "RSI" Column Average RSI value in the cluster (0-100): < 30: Oversold zone 30-45: Bearish sentiment 45-55: Neutral zone 55-70: Bullish sentiment > 70: Overbought zone "ATR%" Column Average volatility in the cluster (as % of price): < 1%: Low volatility (consolidation, narrow range) 1-2%: Normal volatility 2-3%: Elevated volatility > 3%: High volatility (strong movements, impulses) Compared to the average volatility across all clusters to determine "High Vol" or "Low Vol". "ΔP%" Column Average price change in the cluster (in % over pcLength period): > +0.05%: Bullish regime -0.05% ... +0.05%: Flat (sideways movement) < -0.05%: Bearish regime "Description" Column Automatic interpretation: "High Vol, Bull" → Strong upward momentum, high activity "Low Vol, Flat" → Consolidation, narrow range, uncertainty "High Vol, Bear" → Strong decline, panic, high activity "Low Vol, Bull" → Slow growth, low activity "Low Vol, Bear" → Slow decline, low activity "Current" Column Arrow ► shows which cluster the last closed bar of your working timeframe is in. Typical Cluster Patterns Example 1: Trend/Flat Division (K=3) Cluster 1: RSI=65, ATR%=2.5, ΔP%=+1.5 → Bullish trend Cluster 2: RSI=50, ATR%=0.8, ΔP%=0.0 → Flat/Consolidation Cluster 3: RSI=35, ATR%=2.3, ΔP%=-1.4 → Bearish trend Strategy: Open positions when regime changes Flat → Trend, avoid flat. Example 2: Volatility Breakdown (K=5) Cluster 1: RSI=72, ATR%=3.5, ΔP%=+2.5 → Strong bullish impulse (high risk) Cluster 2: RSI=60, ATR%=1.5, ΔP%=+0.8 → Moderate bullish (optimal entry point) Cluster 3: RSI=50, ATR%=0.7, ΔP%=0.0 → Flat Cluster 4: RSI=40, ATR%=1.4, ΔP%=-0.7 → Moderate bearish Cluster 5: RSI=28, ATR%=3.2, ΔP%=-2.3 → Strong bearish impulse (panic) Strategy: Enter in Cluster 2 or 4, avoid extremes (1, 5). Example 3: Mixed Regimes (K=7+) With large K, clusters can represent condition combinations: High RSI + Low volatility → "Quiet overbought" Neutral RSI + High volatility → "Uncertainty with high activity" Etc. Requires individual analysis of each cluster. Regime Changes Important signal: Transition from one cluster to another! Trading situation examples: Flat → Bullish trend → Buy signal Bullish trend → Flat → Take profit, close longs Flat → Bearish trend → Sell signal Bearish trend → Flat → Close shorts, wait You can build a trading system based on the current active cluster and transitions between them. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 USAGE EXAMPLES Example 1: Scalping with HTF Filter Task: Scalping on 5-minute charts, but only enter in the direction of the daily regime. Settings: Working TF: 5 min HTF: D (daily) K: 3 (simple division) clusterLookback: 100 Logic: IF current cluster = "Bullish" (ΔP% > 0.5) → Look for long entry points on 5M IF current cluster = "Bearish" (ΔP% < -0.5) → Look for short entry points on 5M IF current cluster = "Flat" → Don't trade / reduce risk Example 2: Swing Trading with Volatility Filtering Task: Swing trading on 4H, enter only in regimes with medium volatility. Settings: Working TF: 4H HTF: D (daily) K: 5 clusterLookback: 200 Logic: Allowed clusters for entry: - ATR% from 1.5% to 2.5% (not too quiet, not too chaotic) - ΔP% with clear direction (|ΔP%| > 0.5) Prohibited clusters: - ATR% > 3% → Too risky (possible gaps, sharp reversals) - ATR% < 1% → Too quiet (small movements, commissions eat profit) Example 3: Portfolio Rotation Task: Managing a portfolio of multiple assets, allocate capital depending on regimes. Settings: Working TF: D (daily) HTF: W (weekly) K: 4 clusterLookback: 100 Logic: For each asset in portfolio: IF regime = "Strong trend + Low volatility" → Increase asset weight in portfolio (40-50%) IF regime = "Medium trend + Medium volatility" → Standard weight (20-30%) IF regime = "Flat" or "High volatility without trend" → Minimum weight or exclude (0-10%) Example 4: Combining with Other Indicators MTF K-Means as a filter: Main strategy: MA Crossover Filter: MTF K-Means on higher TF Rule: IF MA_fast > MA_slow AND Cluster = "Bullish regime" → LONG IF MA_fast < MA_slow AND Cluster = "Bearish regime" → SHORT ELSE → Don't trade (regime doesn't confirm signal) This dramatically reduces false signals in unsuitable market conditions. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 OPTIMIZATION RECOMMENDATIONS Optimal Settings for Different Styles Day Trading Working TF: 5M - 15M HTF: 1H - 4H numClusters: 4-5 clusterLookback: 100-150 Swing Trading Working TF: 1H - 4H HTF: D numClusters: 5-6 clusterLookback: 150-250 Position Trading Working TF: D HTF: W - M numClusters: 4-5 clusterLookback: 100-200 Scalping Working TF: 1M - 5M HTF: 15M - 1H numClusters: 3-4 clusterLookback: 50-100 Backtesting To evaluate effectiveness: Load historical data (minimum 2x clusterLookback HTF bars) Apply the indicator with your settings Study cluster change history: - Do changes coincide with actual trend transitions? - How often do false signals occur? Optimize parameters: - If too much noise → increase HTF or clusterLookback - If reaction too slow → decrease HTF or increase numClusters Combining with Other Techniques Regime-Based Approach: MTF K-Means (regime identification) ↓ +---+---+---+ | | | | v v v v Trend Flat High_Vol Low_Vol ↓ ↓ ↓ ↓ Strategy_A Strategy_B Don't_trade Examples: Trend: Use trend-following strategies (MA crossover, Breakout) Flat: Use mean-reversion strategies (RSI, Bollinger Bands) High volatility: Reduce position sizes, widen stops Low volatility: Expect breakout, don't open positions inside range ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📞 SUPPORT Report an Issue If you found a bug or have a suggestion for improvement: Describe the problem in as much detail as possible Specify your indicator settings Attach a screenshot (if possible) Specify the asset and timeframe where the problem is observed
Pine Script® indicator
by a3d796g67gyuvhg
Sigma Volatility BandsThis indicator models and displays bands of potential future price based on historic realized volatility. This can be used for finding price target where there is no past price action. The price bands are derived from Standard Deviations based on input bars back of historic volatility. More Inputs: Lookback = Number of bars considered Forward Bars = Number of bars to project bands forward There are two display modes: Forward shifted envelopes = (see below) Draws bands of price from the Standard Deviation Forward for Anchor Lines = Draws a wedge out number of bars forward (Vibe coded. Message me for suggested updates and improvements)
Pine Script® indicator
by norok
DTR & ATR with live zonesThis indicator is designed to help traders gauge the day's volatility in real-time. It compares the current Daily True Range (DTR)—the distance between the session's high and low—to the historical Average True Range (ATR). The main purpose is to project potential price levels where the market might reach based on its average volatility. These levels (100% ATR, 150%, 200%, etc.) can be used as price targets. For instance, if you're in a long trade, you might consider taking partial or full profits as the price approaches these upper ATR extension levels. The indicator is highly customisable, allowing you to control the appearance of the ATR lines, zones, and labels to fit your charting preferences. Core Concepts: ATR and DTR To use this indicator effectively, it's important to understand its two main components: Average True Range (ATR): This is a classic technical analysis indicator that measures market volatility. It calculates the average range of price movement over a specific period (e.g., 14 days). A higher ATR means the price is, on average, moving more, while a low ATR indicates less volatility. This script uses a higher timeframe ATR (e.g., Daily) to establish a stable volatility baseline for the current trading day. Daily True Range (DTR): This is simply the difference between the current trading session's highest high and lowest low (session high - session low). It tells you how much the price has actually moved so far today. The indicator's logic revolves around comparing the live, unfolding DTR to the historical, baseline ATR. An on-screen table conveniently shows this comparison as a percentage, to show how volatile the day has been. How It Works: The Dynamic & Locked Mechanism The most clever part of this indicator is how it draws the ATR levels. It operates in two distinct phases during the trading session: Phase 1: Dynamic Expansion (Before DTR meets ATR) At the start of the session, the DTR is small. The indicator calculates the remaining range needed to "complete" the 100% ATR level (difference = avg_atr - dtr). It then adds this remaining amount to the session high and subtracts it from the session low. This creates a "floating" 100% ATR range that expands dynamically as the session high or low is extended. Phase 2: The Lock-in (After DTR meets or exceeds ATR) Once the day's range (DTR) becomes equal to or greater than the avg_atr, the day has met its "expected" volatility. At this point, the levels lock in place. The indicator intelligently determines the anchor point for the locked range. Once this primary 100% ATR range is established (either dynamically or locked), the script projects the other levels (150%, 200%, 250%, and 300%) by adding or subtracting multiples of the avg_atr from this base. How to Use It for Trading The primary use of this indicator is to set logical, volatility-based price targets. Setting Profit Targets: If you enter a long position, the upper ATR levels (100%, 150%, 200%) serve as excellent areas to consider taking profits. A move to the 200% or 250% level often signifies an overextended or "exhaustion" move, making it a high-probability exit zone. For short positions, the lower ATR levels serve the same purpose. Assessing Intraday Momentum: The on-screen table tells you how much of the expected daily range has been used. If it's early in the session and the DTR is only at 30% of the ATR, you can anticipate more significant price movement is likely to come. Conversely, if the DTR is already at 150% of ATR, the bulk of the day's move may already be complete. Mean Reversion Signals: If the price pushes to an extreme level (e.g., 250% ATR) and shows signs of stalling (e.g., bearish divergence on an oscillator), it could signal a potential reversal or pullback, offering an opportunity for a counter-trend trade. Key Settings ATR Length & Smoothing Type: These settings control how the baseline ATR is calculated. The default 14 period and RMA smoothing are standard, but you can adjust them to your preference. Session Settings: This is crucial. You must set the Market Session and Time Zone to match the primary trading hours of the asset you are analysing (e.g., "0930-1600" for the NYSE session). Show Lines / Show Labels / Show Zones: The script gives you full control over the visual display. You can toggle each ATR level's lines, labels, and background zones individually to avoid a cluttered chart and focus only on the levels that matter to your strategy.
Pine Script® indicator
by Mereep01
3
HV-SMA DeltaHistorical Volatility with SMA Multiplier Concept This indicator acts as a "volatility explosion meter" for the market. Its core principle is to compare the current volatility with its historical average to detect moments when the market begins to "swing" with significantly more force. The main components are as follows: ① Historical Volatility (HV) This line is an indicator of the current price volatility. If this line moves higher, it means the price is swinging wildly (high volatility). If this line is low, it means the price is calm or moving within a narrow range (low volatility). ② SMA x Multiplier This line functions as a "threshold" or "volatility resistance" level. It is calculated from the moving average of past volatility and then multiplied by an adjustable number (smaMultiplier) to create an upper band. In simple terms, this line tells us: "Normally, volatility should not exceed this level." ③ Difference (Histogram) This is the result of subtracting the Threshold Line (②) from the HV value (①). Appear when the HV breaks above the threshold line. This signals that "volatility has now spiked significantly above its historical average." Appear when the HV is still below the threshold line. This indicates that volatility remains at a normal or below-average level. . . How to Use This indicator does not tell you the direction of the price. Instead, it indicates the "power" or "momentum" of the movement. Therefore, it should always be used in conjunction with other tools to confirm the direction. ① Look for "Volatility Breakout" signals. ② Use it to confirm the strength of a trend. ③ Use it for risk management. You can try adjusting the smaLength and smaMultiplier values in the indicator's settings to fit the specific asset and timeframe you are trading. More volatile assets may require a higher Multiplier. ----------------------------------------------------------- หลักการทำงาน (Concept) Indicator ตัวนี้เป็น "เครื่องวัดการระเบิดของความผันผวน" ในตลาด โดยแกนหลักเป็นการเปรียบเทียบความผันผวนในปัจจุบันกับความผันผวนโดยเฉลี่ยในอดีต เพื่อหาจังหวะที่ตลาดเริ่ม "เหวี่ยง" แรงขึ้นอย่างมีนัยสำคัญ ส่วนประกอบหลักๆ มีดังนี้: ① Historical Volatility (HV) เส้นนี้คือตัวชี้วัดความผันผวนของราคา ณ ปัจจุบัน ถ้าเส้นนี้วิ่งขึ้นสูง แปลว่าราคากำลังแกว่งตัวรุนแรง (ผันผวนสูง) ถ้าเส้นนี้อยู่ต่ำ แปลว่าราคานิ่งๆ หรือเคลื่อนไหวในกรอบแคบๆ (ผันผวนต่ำ) ② SMA x Multiplier เส้นนี้ทำหน้าที่เป็น "เส้นเกณฑ์" หรือ "แนวต้านของความผันผวน" ถูกคำนวณมาจากเส้นค่าเฉลี่ยของความผันผวนในอดีต แล้วคูณด้วยตัวเลข Adjustable (sma-Multiplier) เพื่อสร้างเป็นกรอบบน พูดง่ายๆ คือ เส้นนี้บอกเราว่า "โดยปกติแล้ว ความผันผวนไม่ควรจะเกินระดับนี้" ③ Difference (Histogram) เป็นผลลัพธ์จากการนำค่า HV ข้อ ① มาลบกับ เส้นเกณฑ์ ข้อ ② เกิดขึ้นเมื่อ HV ทะลุเส้นเกณฑ์ขึ้นไป เป็นสัญญาณว่า ณ ตอนนี้ "ความผันผวนได้พุ่งสูงกว่าค่าเฉลี่ยในอดีตอย่างมีนัยสำคัญ" เกิดขึ้นเมื่อ HV ยังอยู่ต่ำกว่าเส้นเกณฑ์ บอกว่าความผันผวนยังอยู่ในระดับปกติหรือต่ำกว่าค่าเฉลี่ย . . วิธีการนำไปใช้ (How to Use) Indicator ตัวนี้ ไม่ได้บอกทิศทางของราคา แต่จะบอก "พลัง" หรือ "โมเมนตัม" ของการเคลื่อนไหว เราจึงควรใช้มันร่วมกับเครื่องมืออื่นเพื่อยืนยันทิศทางเสมอ ① มองหาสัญญาณ "การระเบิดของราคา" (Volatility Breakout) ② ใช้ยืนยันความแข็งแกร่งของเทรนด์ ③ ใช้ในการบริหารความเสี่ยง สามารถลองปรับค่า smaLength และ smaMultiplier ในการตั้งค่า Indicator เพื่อให้เข้ากับสินทรัพย์และ Timeframe ที่เทรดได้นะ สินทรัพย์ที่เหวี่ยงแรงๆ อาจต้องใช้ Multiplier ที่สูงขึ้น เป็นต้น
Pine Script® indicator
by MeesatiTrade
ADR - Average Daily Range [KasTrades]This is an Average Daily Range (ADR) indicator. There are two settings for ADR: Two Look back period ADR range (e.g. 7 and 14 days) One Look back period ADR (e.g. 5 days only) Two day ADR ranges are typically used in equities and index futures whereas one day ADR is typically used in forex. The opening time by default is 17:00 New York (Eastern) time. The ranges are always calculated from the opening price of the first bar on the respected timeframe.
Pine Script® indicator
by KasTrades14
Volatility Adjusted Relative Strength (VARS) - Histogram OptionI’ve developed a new version of VARS that includes an option to toggle it into a histogram view. I recommend using a single neutral color rather than the conventional “red below 0, green above 0” scheme — because true RS analysis shouldn’t rely on color cues. The focus should be on the immediacy and persistence of RS itself to capture that initial breakout move as the most optimal RRR entry. This also provides clearer insight and visualization into how RS functions (both traditional and VARS) since RS is a static EOD metric derived from a defined timeframe. I want to emphasize again that VARS is useful to identify low-risk entries, with relative strength calibrated to the volatility of the reference index (in this case, AMEX:SPY ). It is not used to determine my exits — those should be governed by a strict, non-discretionary framework for partial profit-taking and final exit of a position.
Pine Script® indicator
by jfsrev
8
First Passage Time - Distribution AnalysisThe First Passage Time (FPT) Distribution Analysis indicator is a sophisticated probabilistic tool that answers one of the most critical questions in trading: "How long will it take for price to reach my target, and what are the odds of getting there first?" Unlike traditional technical indicators that focus on what might happen, this indicator tells you when it's likely to happen. Mathematical Foundation: First Passage Time Theory What is First Passage Time? First Passage Time (FPT) is a concept in stochastic processes that measures the time it takes for a random process to reach a specific threshold for the first time. Originally developed in physics and mathematics, FPT has applications in: Quantitative Finance: Option pricing, risk management, and algorithmic trading Neuroscience: Modeling neural firing patterns Biology: Population dynamics and disease spread Engineering: Reliability analysis and failure prediction The Mathematics Behind It This indicator uses Geometric Brownian Motion (GBM), the same stochastic model used in the Black-Scholes option pricing formula: dS = μS dt + σS dW Where: S = Asset price μ = Drift (trend component) σ = Volatility (uncertainty component) dW = Wiener process (random walk) Through Monte Carlo simulation, the indicator runs 1,000+ price path simulations to statistically determine: When each threshold (+X% or -X%) is likely to be hit Which threshold is hit first (directional bias) How often each scenario occurs (probability distribution) 🎯 How This Indicator Works Core Algorithm Workflow: Calculate Historical Statistics Measures recent price volatility (standard deviation of log returns) Calculates drift (average directional movement) Annualizes these metrics for meaningful comparison Run Monte Carlo Simulations Generates 1,000+ random price paths based on historical behavior Tracks when each path hits the upside (+X%) or downside (-X%) threshold Records which threshold was hit first in each simulation Aggregate Statistical Results Calculates percentile distributions (10th, 25th, 50th, 75th, 90th) Computes "first hit" probabilities (upside vs downside) Determines average and median time-to-target Visual Representation Displays thresholds as horizontal lines Shows gradient risk zones (purple-to-blue) Provides comprehensive statistics table 📈 Use Cases 1. Options Trading Selling Options: Determine if your strike price is likely to be hit before expiration Buying Options: Estimate probability of reaching profit targets within your time window Time Decay Management: Compare expected time-to-target vs theta decay Example: You're considering selling a 30-day call option 5% out of the money. The indicator shows there's a 72% chance price hits +5% within 12 days. This tells you the trade has high assignment risk. 2. Swing Trading Entry Timing: Wait for higher probability setups when directional bias is strong Target Setting: Use median time-to-target to set realistic profit expectations Stop Loss Placement: Understand probability of hitting your stop before target Example: The indicator shows 85% upside probability with median time of 3.2 days. You can confidently enter long positions with appropriate position sizing. 3. Risk Management Position Sizing: Larger positions when probability heavily favors one direction Portfolio Allocation: Reduce exposure when probabilities are near 50/50 (high uncertainty) Hedge Timing: Know when to add protective positions based on downside probability Example: Indicator shows 55% upside vs 45% downside—nearly neutral. This signals high uncertainty, suggesting reduced position size or wait for better setup. 4. Market Regime Detection Trending Markets: High directional bias (70%+ one direction) Range-bound Markets: Balanced probabilities (45-55% both directions) Volatility Regimes: Compare actual vs theoretical minimum time Example: Consistent 90%+ bullish bias across multiple timeframes confirms strong uptrend—stay long and avoid counter-trend trades. First Hit Rate (Most Important!) Shows which threshold is likely to be hit FIRST: Upside %: Probability of hitting upside target before downside Downside %: Probability of hitting downside target before upside These always sum to 100% ⚠️ Warning: If you see "Low Hit Rate" warning, increase this parameter! Advanced Parameters Drift Mode Allows you to explore different scenarios: Historical: Uses actual recent trend (default—most realistic) Zero (Neutral): Assumes no trend, only volatility (symmetric probabilities) 50% Reduced: Dampens trend effect (conservative scenario) Use Case: Switch to "Zero (Neutral)" to see what happens in a pure volatility environment, useful for range-bound markets. Distribution Type Percentile: Shows 10%, 25%, 50%, 75%, 90% levels (recommended for most users) Sigma: Shows standard deviation levels (1σ, 2σ)—useful for statistical analysis ⚠️ Important Limitations & Best Practices Limitations Assumes GBM: Real markets have fat tails, jumps, and regime changes not captured by GBM Historical Parameters: Uses recent volatility/drift—may not predict regime shifts No Fundamental Events: Cannot predict earnings, news, or macro shocks Computational: Runs only on last bar—doesn't give historical signals Remember: Probabilities are not certainties. Use this indicator as part of a comprehensive trading plan with proper risk management. Created by: Henrique Centieiro. feedback is more than welcome!
Pine Script® indicator
by HenriqueCentieiro
9
Lakshmi - Vajra Energy Signal (VES)Vajra Energy Signal (VES) is an advanced volume analysis indicator that detects energy accumulated inside the market. When assessing the strength of trading activity, conventional practice looks at the magnitude of volume; VES is designed with the understanding that the same volume can have different meanings depending on the price range. VES analyzes the complex relationship between price movement and volume with a proprietary algorithm and can detect internal market activities that are invisible from surface‑level price action, visualizing the characteristic whereby the value rises before a breakout. In other words, VES views the market as an “energy system.” In the energy accumulation phase, relatively high volume occurs relative to the price range, and in the energy release phase, the stored energy is emitted as high volatility in price, that is, a breakout—this is the core concept on which VES is established. ⚡️ Basic Demonstration i.imgur.com As you can see in the image above, VES simply displays the highs and lows of energy stored in the market as a thin line in a separate panel. It is easy for traders to understand its intuitive patterns: it rises when hidden buying accumulation or selling activity continue and sink when a price breakout occurs. It can be applied across symbols and markets (stocks, commodities, cryptocurrencies, spot, and futures). While reducing clutter in price scale labels, it also supports dynamic autoscaling. ⚡️ Practical Usage VES is expected to be used for the following purposes. - Entry signal When the VES value continues to rise—i.e., during energy accumulation—it can be considered on standby for a breakout. After a breakout, a trader can confirm the trend direction and enter. - Exit signal If the VES value rises during a trend, consider the possibility of a reversal and consider taking profits. - Risk management If the VES value remains elevated for a long period, regard it as increased market uncertainty and an approaching breakout; adopt a cautious trading strategy to prepare for higher volatility and adjust position size. For example, in the BINANCE:SOLUSDT daily chart below, VES clearly shows how it functions in short‑term trading. i.imgur.com In September 2023, when the price was moving around 20 USDT, VES formed frequent small spikes. These early spikes suggest that market participants were still in a wait‑and‑see mode and that small‑scale accumulation was being conducted intermittently. A decisive change came in early October 2023. While the price still stagnated in the 20–25 USDT range, VES suddenly formed a huge spike. The scale of this spike was far larger than those in September 2023, clearly suggesting that hidden substantial trading activities by large investors had begun. In mid‑October 2023, the price began to rise. It climbed stepwise from 25 USDT to 40 USDT, then to 60 USDT and 75 USDT, and then surged to above 120 USDT within just a few weeks. This suggests that the energy built in the buy accumulation phase in early October 2023 was converted into price appreciation. Therefore, after such a large VES signal is observed and the price breaks upward, entering a long position could have been profitable. A large VES reaction is not only a quiet “buy signal” as in the example above; it can also be a “sell signal.” Such a case is explained below using an example on the BTC chart. i.imgur.com This BITSTAMP:BTCUSD 4‑hour chart is a valuable example showing how VES detects top formation on a short timeframe. In the first half of February 2024, the price moved in a relatively narrow 96,000–99,000 USD range. During this period, VES remained stable at low levels, and the market continued a calm uptrend. The first sign appeared on February 16, 2024. While the price still held around 97,000 USD, VES formed a clearly identifiable small spike. This implied that some large investors had begun to take profits, or that new sellers had started to build short positions. However, at that point, the impact on price was limited, and many traders may have overlooked the signal. The decisive turning point came on February 23, 2024. With the price moving around 98,000 USD, VES suddenly formed a huge spike. The scale of this spike was far larger than previous moves, clearly indicating that significant energy was accumulating. Importantly, even at this moment the price still remained at the highs. On the surface, price barely moved and the bull trend appeared intact, but VES detected a major internal change underway. On February 24, 2024, the price collapsed and began to fall. It dropped about 15% from 97,000 USD to 82,000 USD in a few days. The speed and magnitude of this decline corroborated the quiet “sell signal” indicated by the VES spikes. The key lesson from this chart is that a VES spike does not necessarily mean buy accumulation. A large VES spike formed at high prices may instead indicate a distribution phase—that is, large investors exiting or building short positions. When the price is at elevated levels, a VES spike should be considered not only as a precursor to further upside but also as a warning of potential downside. From a trading‑strategy perspective, the huge VES spike on February 23, 2024 was a clear signal to exit or to consider entering short positions. At that point, traders should have either closed long positions or to consider building a short position. The moment when price started to decline from its peak was exactly the entry timing for a short. On the 4‑hour timeframe, changes in VES appear faster and more dramatically. While this allows more agile responses, the risk of false signals is also higher; therefore, confirmation on other timeframes and comprehensive judgment with price action are essential. VES is a powerful tool for reading internal market activities, and this chart clearly shows that its interpretation requires flexibility that takes into account market conditions and price location. ⚡️ Parameter Settings Strength 1: The lower the number, the more it emphasizes responses closer to the present timeframe; the higher the number, the more it emphasizes responses farther from the present timeframe. 5 is recommended. Strength 2: The lower the number, the greater the volatility of the value; the higher the number, the smaller the volatility. 5 is recommended. Scale: Adjusts the display scale. −30 is recommended. ⚡️ Conclusion Vajra Energy Signal (VES) visualizes the cycle of energy accumulation in the market from the relative relationship between price range and volume, detecting hidden activities by market participants that conventional volume analysis cannot capture. VES serves as a powerful auxiliary tool for early detection of turning points, enabling deeper market understanding and more accurate timing decisions. As the examples show, there is a possibility of sensing major price movements in advance. When using VES, flexible interpretation according to market environment and price location is required, and it demonstrates its true value when combined with price action and other analysis methods such as support/resistance. ⚡️ Important Notes - VES is a tool that infers internal market energy; it does not guarantee trades or suggest future results. - We strongly recommend using it together with price action analysis and support/resistance. - Confirmation across different timeframes improves reliability. - Effectiveness may vary depending on market conditions and liquidity. - Very illiquid instruments or newly listed assets may produce more noise. ⚡️ How to Get Access This indicator is Public Invite‑Only. If you would like access, please apply by following the Author’s Instructions.
Pine Script® indicator
by lakshmivibha
SMR - Simple Market Recap📊 Simple Market Recap (SMR) 🎯 A comprehensive market overview tool displaying price changes, percentage movements, and status indicators for multiple financial instruments across customizable timeframes with intelligent data synchronization. ━━━━━━━━━━━━━━ 📋 OVERVIEW The Simple Market Recap indicator provides a professional market analysis dashboard that displays key performance metrics for major financial instruments. This educational tool features intelligent asset selection, automatic dark mode detection, comprehensive period analysis with bilingual support, and advanced data synchronization ensuring accurate price data regardless of the current chart symbol. Perfect for: Market overview analysis and educational study Multi-asset performance comparison and research Weekly, daily, and monthly market recap visualization Educational purposes and market trend analysis ━━━━━━━━━━━━━━ 🚀 KEY FEATURES & ENHANCEMENTS 🌙 Intelligent Dark Mode Detection Automatic chart background color analysis and adaptation Dynamic color scheme adjustment for optimal visibility Enhanced contrast ratios for both light and dark themes Professional appearance across all chart backgrounds 📊 Comprehensive Asset Coverage Major Forex Pairs: EURUSD, GBPUSD, AUDUSD, NZDUSD, USDCHF, USDJPY, USDCAD Indices & Dollar: DXY (US Dollar Index), SPX (S&P 500) Commodities: XAUUSD (Gold), USOIL (Crude Oil) Bonds: US10Y (10-Year Treasury) Cryptocurrencies: BTCUSDT, ETHUSDT Selective asset display with individual on/off controls Fixed asset order: DXY, EURUSD, GBPUSD, AUDUSD, NZDUSD, USDCHF, USDCAD, USDJPY, XAUUSD, USOIL, SPX, US10Y, ETHUSDT, BTCUSDT ⏰ Flexible Timeframe Analysis Multiple Periods: Daily (1D), Weekly (1W), Monthly (1M) Time Selection: Current Period or Previous Period analysis Dynamic Titles: Automatic report naming with dates and periods Historical Comparison: Compare current vs previous period performance 📈 Enhanced Data Visualization Professional table with adaptive row count based on selected assets Color-coded price movements: Enhanced green for positive, bright red for negative Status emojis: ↗️ Up, ↘️ Down, ↔️ Sideways, ❓ No data Smart price formatting based on asset type and price level Improved contrast colors for better visibility in all lighting conditions 🔄 Advanced Data Synchronization Symbol-Independent Accuracy: Correct data display regardless of current chart symbol Real-Time Security Requests: Direct data fetching from specific instrument sources Cross-Asset Reliability: Accurate price data for all monitored assets simultaneously Data Integrity: No cross-contamination between different financial instruments ━━━━━━━━━━━━━━ 🎨 PROFESSIONAL TABLE LAYOUT Adaptive Design Features: Automatic dark mode detection and color adaptation Enhanced contrast ratios for better readability Professional color scheme with clear data separation Responsive design for all screen sizes and themes Comprehensive Data Display: Dynamic Title Row: Period-specific report titles with dates Asset Column: Selected financial instruments Open/Close Prices: Period opening and closing values Change Percentage: Color-coded performance indicators Pips Movement: Precise pip calculations for each asset Status Indicators: Visual emoji representations of trend direction Visual Design Features: Merged title cells for clean header presentation Asset-specific price formatting for optimal readability Color-coded positive/negative movements Professional table borders and spacing ━━━━━━━━━━━━━━ ⚙️ ADVANCED CUSTOMIZATION Timeframe Controls: Report Period selection: Daily, Weekly, or Monthly analysis Time Selection toggle: Current vs Previous period comparison Dynamic row count based on active asset selection Automatic title generation with period-specific formatting Asset Selection: Individual toggle controls for each supported asset Major forex pairs with complete coverage Cryptocurrency and precious metals options Index and commodity instrument support Display Options: 9 table positioning options across the entire chart 5 text size levels from Tiny to Huge for optimal visibility Language selection between English and Vietnamese Automatic theme adaptation for all chart backgrounds ━━━━━━━━━━━━━━ ⚠️ EDUCATIONAL & ANALYTICAL PURPOSE This indicator is designed exclusively for educational market analysis and research purposes . 📚 Educational Applications: Understanding multi-asset market performance correlation Studying period-based price movements and trends Analyzing market volatility across different timeframes Learning to read and interpret market recap data 📊 Analysis Capabilities: Market overview visualization for educational study Multi-timeframe performance comparison research Historical period analysis and trend identification Cross-asset correlation studies and market research 🚨 Important Disclaimer: This tool provides educational market data visualization only and does NOT generate trading signals or investment advice. All data is for learning and analysis purposes. Users must conduct independent research and consult financial professionals before making any investment decisions. ━━━━━━━━━━━━━━ 🛠️ SETUP & CONFIGURATION Quick Start Guide: Add the indicator to your chart from the indicators library Select your preferred language (English or Vietnamese) Choose your desired reporting timeframe (Daily, Weekly, or Monthly) Select Current Period or Previous Period for analysis Toggle on/off specific assets you want to monitor Adjust table position and text size for optimal viewing Advanced Configuration: Customize asset selection based on your analysis needs Configure timeframe settings for different market studies Set up language preferences for your region Fine-tune display options for your screen setup Optimize table positioning for your chart layout Theme Optimization: Indicator automatically detects your chart theme Colors adapt automatically for optimal contrast and readability No manual adjustments required for theme changes Professional appearance maintained across all backgrounds ━━━━━━━━━━━━━━ 🔧 TECHNICAL SPECIFICATIONS Performance & Reliability: Pine Script v6 with optimized data retrieval Real-time updates with minimal CPU and memory usage No repainting or lookahead bias in calculations Stable performance across all timeframes and instruments Universal Compatibility: Works with all TradingView chart types and instruments Compatible with mobile and desktop platforms Supports all timeframes with period-specific analysis Cross-platform functionality with consistent behavior Data Precision: High-precision floating-point calculations Asset-specific formatting and pip calculations Real-time price data from multiple exchanges Accurate percentage and movement calculations Advanced Features: Automatic chart background detection and color adaptation Dynamic table sizing based on active asset selection Intelligent price formatting for different asset classes Professional status indicators with emoji visualization ━━━━━━━━━━━━━━ 📋 VERSION HISTORY v1.7 - Enhanced Data Synchronization & Color Improvements Fixed critical data synchronization issue - accurate data regardless of current chart symbol Enhanced data retrieval system with symbol-specific security requests Improved color scheme: brighter red for negative values, enhanced contrast Fixed asset order: DXY, EURUSD, GBPUSD, AUDUSD, NZDUSD, USDCHF, USDCAD, USDJPY, XAUUSD, USOIL, SPX, US10Y, ETHUSDT, BTCUSDT Optimized price formatting with proper decimal display and leading zeros Enhanced calendar-based time calculations for accurate period reporting Improved pip calculations for different asset classes Professional color coding with adaptive contrast for all themes Previous Versions: v1.6 - Data accuracy improvements and bug fixes v1.5 - Enhanced market analysis with flexible timeframes v1.4 - Professional table layout and bilingual support Earlier versions - Core market data display functionality development ━━━━━━━━━━━━━━ Author: tohaitrieu Version: 1.7 Category: Market Analysis / Educational Overview Language Support: English, Vietnamese License: Educational Use Only This indicator is provided exclusively for educational and analytical purposes to help users understand market overview concepts and multi-asset analysis. It features automatic theme adaptation, flexible timeframe analysis, enhanced data synchronization, and comprehensive market data visualization for the most accurate and informative educational experience. It does not provide trading signals or investment advice. Always conduct thorough research and consider professional guidance before making financial decisions.
Pine Script® indicator
by tohaitrieu
Omega ATR Indicator📖 Introduction The Ω ATR Indicator was created to provide a more complete and professional framework for volatility analysis than the classic Average True Range (ATR). While the traditional ATR is a useful tool, it has limitations: it delivers a simple rolling average of volatility, but it does not adapt to market regimes, it does not highlight extreme events, and it often leaves the trader with incomplete information about risk. The Ω ATR takes the same foundation and elevates it into a multi-dimensional volatility dashboard, adding statistical layers, adaptive calculations, and clear visual references that allow traders to interpret volatility in a way that is immediately actionable. 🔎 What makes it different from a standard ATR? This indicator introduces several features beyond the classic formula: True Range Core – plots the raw True Range (TR) for each bar, providing a direct, bar-by-bar view of volatility impulses. Standard & Adjusted ATR – includes both the conventional ATR (smoothed average) and an Adjusted ATR that automatically corrects for extreme conditions by incorporating percentile rescaling. Percentile Volatility Levels – dynamically calculated extreme thresholds (99.8%, 75%, 50%, 25%), plotted as dotted levels across the chart. These act as reference lines for “normal” vs. “abnormal” volatility, useful for spotting unusual price expansions or contractions. Linear Regression Volatility Trend – overlays a regression line of volatility, showing whether the market is moving toward expansion (rising vol), contraction (falling vol), or stability. Monetary Value Translation – the indicator converts volatility into points, ticks, and dollar values (based on the instrument’s point value). This allows futures traders and high-value instruments users to immediately see how much volatility is “worth” in cash terms. Interactive Table Display – a real-time statistics table is displayed directly on the chart, showing: SMA of ATR in $ and points Percentile-based volatility range (VAR) in $ and points Tick equivalences, for quick position sizing ⚡ How traders can use it The Ω ATR Indicator is designed to be versatile, fitting both discretionary traders and systematic strategy developers. Risk Management: ATR-based stop losses and position sizing are significantly improved by using the adjusted ATR and percentile thresholds. Traders can size their positions according to volatility regimes, not just raw averages. Breakout & Exhaustion Detection: When TR or ATR values spike above the 99.8% or 95% percentile levels, this often corresponds to breakout conditions or volatility exhaustion — useful for breakout strategies, mean-reversion setups, and volatility fades. Market Regime Identification: The regression line helps distinguish if volatility is rising (trending environment, larger swings expected) or compressing (range-bound environment, lower risk opportunities). Multi-Asset Flexibility: Works equally well on equities, futures, crypto, and FX. Its point/tick/dollar conversion makes it especially powerful for futures traders who need to quantify risk precisely. Scalping to Swing Trading: On lower timeframes, it acts as a micro-volatility detector; on higher timeframes, it functions as a strategic risk gauge for position management. ⚙️ Settings and Customization Length: The ATR lookback period (default = 34). Shorter lengths (14–21) for intraday traders who want fast response. Longer lengths (34–55) for swing/position traders who want smoother readings. AVG / ADJ AVG: Toggle to display the standard ATR or the adjusted ATR. Volatility Levels: Enable/disable up to 4 percentile-based levels (1st = 25%, 2nd = 50%, 3rd = 75%, 4th = 99.8%). Recommended: keep 3 levels active for clarity. Color Controls: All plots and levels are fully customizable to match your chart style. Table Display: Positioned on the chart (default: middle-right) with key values updated in real time. 🧭 Best Practices for Use Combine with Trend Tools: Volatility readings are most powerful when combined with trend filters or volume analysis. For example, a breakout with both high volatility and trend confirmation is stronger than either alone. ATR Stops: Use the Adjusted ATR rather than the standard one when trailing stops in highly volatile instruments like crypto or Nasdaq futures, as it adapts to outlier spikes. Dollar Risk Translation: Use the dollar-value outputs to predefine maximum acceptable risk per trade (e.g., “I only risk $250 per position”). This bridges volatility to portfolio risk management. Event Monitoring: Around economic events or earnings, expect volatility spikes above higher percentile levels. The indicator makes these moves instantly visible. 📌 Summary The Ω ATR Indicator is not just “another ATR.” It is a comprehensive volatility framework that transforms volatility from a simple statistic into an actionable trading signal. By combining: the classic ATR, an adjusted ATR, percentile extremes, regression-based volatility trends, and real-time dollar conversions, …this tool allows traders to precisely understand, visualize, and act on volatility in ways that a standard ATR simply cannot provide. Whether you are scalping intraday moves, swing trading equities, or managing futures positions, the Ω ATR equips you with a professional-grade volatility dashboard that clarifies risk, highlights opportunity, and adapts across all markets and timeframes. 👉 Designed and developed by OmegaTools for traders who demand precision, clarity, and adaptability in their volatility analysis.
Pine Script® indicator
by OmegaTools
MIT MACD • Filled/Hollow Momentum HistogramThe MIT MACD • Filled/Hollow Momentum Histogram is an enhanced version of the classic MACD. - Dual-style histogram (filled for acceleration, hollow for deceleration). - Customizable colors for bars, MACD/Signal lines, and background. - Background highlight when the slow line crosses the zero-line. - Fully adjustable parameters, keeping TradingView defaults. 此脚本是经典 MACD 的进阶版，支持实心/空心动能柱体，零轴背景高亮，参数与配色可自由调整，更直观捕捉趋势与动能变化。
Pine Script® indicator
by HONGJIT
Realized Volatility (StdDev of Returns, %)Realized Volatility (StdDev of Returns, %) This indicator measures realized (historical) volatility by calculating the standard deviation of log returns over a user-defined lookback period. It helps traders and analysts observe how much the price has varied in the past, expressed as a percentage. How it works: Computes close-to-close logarithmic returns. Calculates the standard deviation of these returns over the selected lookback window. Provides three volatility measures: Daily Volatility (%): Standard deviation over the chosen period. Annualized Volatility (%): Scaled using the square root of the number of trading days per year (default = 250). Horizon Volatility (%): Scaled to a custom horizon (default = 5 days, useful for short-term views). Inputs: Lookback Period: Number of bars used for volatility calculation. Trading Days per Year: Used for annualizing volatility. Horizon (days): Adjusts volatility to a shorter or longer time frame. Notes: This is a statistical measure of past volatility, not a forecasting tool. If you change the scale to logarithmic, the indicator readibility improves. It should be used for analysis in combination with other tools and not as a standalone signal.
Pine Script® indicator
by risk_alpha
Realized Volatility (StdDev of Returns, %)📌 Realized Volatility (StdDev of Returns, %) This indicator measures realized volatility directly from price returns, instead of the common but misleading approach of calculating standard deviation around a moving average. 🔹 How it works: Computes close-to-close log returns (the most common way volatility is measured in finance). Calculates the standard deviation of these returns over a chosen lookback period (default = 200 bars). Converts results into percentages for easier interpretation. Provides three key volatility measures: Daily Realized Vol (%) – raw standard deviation of returns. Annualized Vol (%) – scaled by √250 trading days (market convention). Horizon Vol (%) – volatility over a custom horizon (default = 5 days, i.e. weekly). 🔹 Why use this indicator? Shows true realized volatility from historical returns. More accurate than measuring deviation around a moving average. Useful for traders analyzing risk, position sizing, and comparing realized vs implied volatility. ⚠️ Note: It is best used on the Daily Chart! By default, this uses log returns (which are additive and standard in quant finance). If you prefer, you can easily switch to simple % returns in the code. Volatility estimates depend on your chosen lookback length and may vary across timeframes.
Pine Script® indicator
by risk_alpha
Auto Fib V2Auto Fib V2 — Advanced Fibonacci Mapping Tool Introduction Auto Fib V2 is an advanced Fibonacci retracement indicator that automatically adapts to recent market ranges. Rather than manually drawing Fibonacci lines, this script dynamically maps them based on the most recent highs and lows, allowing traders to see the chart as if it were a "navigation map." Its primary purpose is to help identify potential buy and sell zones with greater clarity. Key Concept The script is built on a simple but powerful interpretation of Fibonacci retracement: When the price moves below the 0.236 level, it suggests an oversold zone, where buyers may step in and market reversal potential increases. When the price rises above the 0.764 level, it highlights an overbought zone, where sellers may become more active and risk of reversal grows. Between these extremes, the Golden Pocket (0.382–0.618 zone) is highlighted as the area where institutional traders and algorithms often react. Historically, this is one of the most respected Fibonacci areas in technical analysis. Features & Customization Automatic Range Detection: The indicator automatically finds the recent high/low (based on user-defined lookback bars) and applies Fibonacci levels. Flexible Direction Setting: Traders can use Auto Mode to let the script decide direction from price movement, or manually choose upward/downward mapping. Multiple Levels Display: Beyond the standard levels, extra fractional retracements (0.146, 0.309, 0.441, etc.) are included for more precise mapping. Golden Pocket Highlighting: Visually emphasizes the 0.382–0.618 retracement zone for quick recognition. Custom Styles: Switch between line-based and dot-based plotting, with adjustable colors and transparency for improved readability. Practical Use Auto Fib V2 is not intended as a direct buy/sell signal generator, but as a contextual guide. Traders can use it to: Confirm whether the current price area is closer to an overbought or oversold condition. Combine it with oscillators (RSI, MACD) or trend indicators (EMA, ADX) to strengthen trading decisions. Identify confluence zones where Fibonacci levels overlap with key supports/resistances. Quickly adapt to market shifts without the need to redraw Fibonacci retracement lines repeatedly. Why Use Auto Fib V2? Manual Fibonacci drawing can be subjective, often depending on the swing points a trader chooses. Auto Fib V2 reduces that subjectivity by using consistent logic, creating a more systematic approach. For intraday traders, it provides rapid context to assess whether the market is stretched or balanced. For swing traders, it offers a map of reaction zones across higher timeframes.
Pine Script® indicator
by Choronicles
Intelligent Trading SuiteIntelligent Trading Suite “One script to rule them all.” Overview The Intelligent Trading Suite is a professional-grade decision system built in Pine Script. It is a unified engine—not a bundle of indicators—that combines adaptive pattern recognition, historical memory, and multi-context intelligence into one framework. Using a deep historical pattern database and integrating session dynamics, market calendars, holiday effects, and economic events, it filters noise and adapts to conditions. Core emphasis: precise pattern detection with target-price projection that remains stable as new candles print (mitigates target drift) and early detection of forming geometric patterns and divergences/hidden divergences. Core Features All-Timeframe Operation: Works across every TradingView timeframe—from 1m to 1W—without performance drift. Pattern Recognition with Targets: Detects triangles, wedges, cup & handle, flags, and H&S; projects targets and stabilizes them against common drift as price evolves. Early Signal Engine: Flags forming patterns and divergences before completion and notifies when prerequisites align. Historical Pattern Intelligence: Stores and compares thousands of prior states (Hull, VWAP, RSI, MACD, SMA, CVD) to weight current conditions and calibrate confidence. Context & Regime Awareness: Adjusts for volatility regimes, liquidity sessions, day-of-week bias, holidays, and macro events. Unified Signal & Confidence: Fuses all streams into a single Overall signal with calibrated confidence levels (Weak / Neutral / Strong). Visualization & Alerts Compact Ultimate Intelligence Table showing each analytical pillar, plus the Overall signal, and an option to show them on the chart as well. Alerts on table for: new pattern detection, divergence events, volatility shifts, and trend reversals. Important Notes -Free plan runtime: TradingView Free accounts may hit platform limits. Fix: Open settings → switch Mode from Paid to Free → runs within Free limits. -Heavy computation: The script is calculation- and data-intensive; initial runs can take time. If a rare runtime error occurs, simply reload the page and continue. Attributions Hull Moving Average (Alan Hull) VWAP (Volume Weighted Average Price) RSI (Relative Strength Index, J. Welles Wilder Jr.) MACD (Moving Average Convergence Divergence, Gerald Appel) Black Flag ATR bands (Jose Azcarate) Proprietary enhancements, target-stabilization logic, and the nuclear intelligence architecture are original research for this suite. Compliance Educational and analytical use only No financial advice Ad-free; aligned with TradingView House Rules Proper attribution included Access To get access, please read the Author’s instructions on the script’s page.
Pine Script® indicator
by FutureisinPast
2
Monthly Expected Move (IV + Realized)What it does Overlays 1-month expected move bands on price using both forward-looking options data and backward-looking realized movement: IV30 band — from your pasted 30-day implied vol (%) Straddle band — from your pasted ATM ~30-DTE call+put total HV band — from Historical Volatility computed on-chart ATR band — from ATR% extrapolated to ~1 trading month Use it to quickly answer: “How much could this stock move in ~1 month?” and “Is the market now pricing more/less movement than we’ve actually been getting?” Inputs (quick) Implied (forward-looking) Use IV30 (%) — paste annualized IV30 from your options platform. Use ATM 30-DTE Straddle — paste Call+Put total (per share) at the ATM strike, ~30 DTE. Realized (backward-looking) HV lookback (days) — default 21 (≈1 trading month). ATR length — default 14. Note: TradingView can’t fetch option data automatically. Paste the IV30 % or the straddle total you read from your broker (use Mark/mid prices). How it’s calculated IV band (±%) = IV30 × √(21/252) (annualized → ~1-month). Straddle band (±%) = (ATM Call + Put) / Spot to that expiry (≈30 DTE). HV band (±%) = stdev(log returns, N) × √252 × √(21/252). ATR band (±%) = (ATR(len)/Close) × √21. All bands are plotted as upper/lower envelopes around price, plus an on-chart readout of each ±% for quick scanning. How to use it (at a glance) IV/Straddle bands wider than HV/ATR → market expects bigger movement than recent actuals (possible catalyst/expansion). All bands narrow → likely a low-mover; look elsewhere if you want action. HV > IV → realized swings exceed current pricing (mean-reversion or vol bleed often follows). Pro tips For ATM straddle: pick the expiry closest to ~30 DTE, use the ATM strike (closest to spot), and add Call Mark + Put Mark (per share). If the exact ATM strike isn’t quoted, average the two neighboring strikes. The simple straddle/spot heuristic can read slightly below the IV-derived 1σ; that’s normal. Keep the chart on daily timeframe—the math assumes trading-day conventions (~252/yr, ~21/mo).
Pine Script® indicator
by rixman14