[GYTS] Volatility Toolkit Volatility Toolkit
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- INTRODUCTION --------- 🌸
💮 What is Volatility Toolkit?
Volatility Toolkit is a comprehensive volatility analysis indicator featuring academically-grounded range-based estimators. Unlike simplistic measures like ATR, these estimators extract maximum information from OHLC data — resulting in estimates that are 5-14× more statistically efficient than traditional close-to-close methods.
The indicator provides two configurable estimator slots, weighted aggregation, adaptive threshold detection, and regime identification — all with flexible smoothing options via
GYTS FiltersToolkit integration.
💮 Why Use This Indicator?
Standard volatility measures (like simple standard deviation) are highly inefficient, requiring large amounts of data to produce stable estimates. Academic research has shown that range-based estimators extract far more information from the same price data:
• Statistical Efficiency — Yang-Zhang achieves up to 14× the efficiency of close-to-close variance, meaning you can achieve the same estimation accuracy with far fewer bars
• Drift Independence — Rogers-Satchell and Yang-Zhang correctly isolate variance even in strongly trending markets where simpler estimators become biased
• Gap Handling — Yang-Zhang properly accounts for overnight gaps, critical for equity markets
• Regime Detection — Built-in threshold modes identify when volatility enters elevated or suppressed states
↑ Overview showing Yang-Zhang volatility with dynamic threshold bands and regime background colouring
🌸 --------- HOW IT WORKS --------- 🌸
💮 Core Concept
The toolkit groups volatility estimators by their output scale to ensure valid comparisons and aggregations:
• Log-Return Scale (σ) — Close-to-Close, Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang. These are comparable and can be aggregated. Annualisable via √(periods_per_year) scaling.
• Price Unit Scale ($) — ATR. Measures volatility in absolute price terms, directly usable for stop-loss placement.
• Percentage Scale (%) — Chaikin Volatility. Measures the rate of change of the trading range — whether volatility is expanding or contracting.
Only estimators with the same scale can be meaningfully compared or aggregated. The indicator enforces this and warns when mixing incompatible scales.
💮 Range-Based Estimator Overview
Range-based estimators utilise High, Low, Open, and Close prices to extract significantly more information about the underlying diffusion process than close-only methods:
• Parkinson (1980) — Uses High-Low range. ~5× more efficient than close-to-close. Assumes zero drift.
• Garman-Klass (1980) — Incorporates Open and Close. ~7.4× more efficient. Assumes zero drift, no gaps.
• Rogers-Satchell (1991) — Drift-independent. Superior in trending markets where Parkinson/GK become biased.
• Yang-Zhang (2000) — Composite estimator handling both drift and overnight gaps. Up to 14× more efficient.
💮 Theoretical Background
• Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI
• Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI
• Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI
• Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI
🌸 --------- KEY FEATURES --------- 🌸
💮 Feature Reference
Estimators (8 options across 3 scale groups):
• Close-to-Close — Classical benchmark using closing prices only. Least efficient but useful as baseline. Log-return scale.
• Parkinson — Range-based (High-Low), ~5× more efficient than close-to-close. Assumes zero drift. Log-return scale.
• Garman-Klass — OHLC-optimised, ~7.4× more efficient. Assumes zero drift, no gaps. Log-return scale.
• Rogers-Satchell — Drift-independent, handles trending markets where Parkinson/GK become biased. Log-return scale.
• Yang-Zhang — Gap-aware composite, most comprehensive (up to 14× efficient). Uses internal rolling variance (unsmoothed). Log-return scale.
• Std Dev — Standard deviation of log returns. Log-return scale.
• ATR — Average True Range in absolute price units. Useful for stop-loss placement. Price unit scale.
• Chaikin — Rate of change of range. Measures volatility expansion/contraction, not level. Percentage scale.
Smoothing Filters (10 options via FiltersToolkit):
• SMA / EMA — Classical moving averages
• Super Smoother (2-Pole / 3-Pole) — Ehlers IIR filter with excellent noise reduction
• Ultimate Smoother (2-Pole / 3-Pole) — Near-zero lag in passband
• BiQuad — Second-order IIR with configurable Q factor
• ADXvma — Adaptive smoothing, flat during ranging periods
• MAMA — MESA Adaptive Moving Average (cycle-adaptive)
• A2RMA — Adaptive Autonomous Recursive MA
Threshold Modes:
• Static — Fixed threshold values you define (e.g., 0.025 annualised)
• Dynamic — Adaptive bands: baseline ± (standard deviation × multiplier)
• Percentile — Threshold at Nth percentile of recent history (e.g., 80th percentile for high)
Visual Features:
• Level-based colour gradient — Line colour shifts with percentile rank (warm = high vol, cool = low vol)
• Fill to zero — Gradient fill intensity proportional to volatility level
• Threshold fills — Intensity-scaled fills when thresholds are breached
• Regime background — Chart background indicates HIGH/NORMAL/LOW volatility state
• Legend table — Displays estimator names, parameters, current values with percentile ranks (P##)
💮 Dual Estimator Slots
Compare two volatility estimators side-by-side. Each slot independently configures:
• Estimator type (8 options across three scale groups)
• Lookback period and smoothing filter
• Colour palette and visual style
This enables direct comparison between estimators (e.g., Yang-Zhang vs Rogers-Satchell) or between different parameterisations of the same estimator.
↑ Yang-Zhang (reddish) and Rogers-Satchell (greenish)
💮 Flexible Smoothing via FiltersToolkit
All estimators (except Yang-Zhang, which uses internal rolling variance) support configurable smoothing through 10 filter types. Using Infinite Impulse Response (IIR) filters instead of SMA avoids the "drop-off artefact" where volatility readings crash when old spikes exit the window.
Example: Same estimator (Parkinson) with different smoothing filters
Add two instances of Volatility Toolkit to your chart:
• Instance 1: Parkinson with SMA smoothing (lookback 14)
• Instance 2: Parkinson with Super Smoother 2-Pole (lookback 14)
Notice how SMA creates sharp drops when volatile bars exit the window, while Super Smoother maintains a gradual transition.
↑ Two Parkinson estimators — SMA (red mono-colour, showing drop-off artefacts) vs Super Smoother (turquoise mono colour, with smooth transitions)
↑ Garman-Klass with BiQuad (orangy) and 2-pole SuperSmoother filters (greenish)
💮 Weighted Aggregation
Combine multiple estimators into a single weighted average. The indicator automatically:
• Validates scale compatibility (only same-scale estimators can be aggregated)
• Normalises weights (so 2:1 means 67%:33%)
• Displays clear warnings when scales differ
Example: Robust volatility estimate
Combine Yang-Zhang (handles gaps) with Rogers-Satchell (handles drift) using equal weights:
• E1: Yang-Zhang (14)
• E2: Rogers-Satchell (14)
• Aggregation: Enabled, weights 1:1
The aggregated line (with "fill to zero" enabled) provides a more robust estimate by averaging two complementary methodologies.
↑ Yang-Zhang + Rogers-Satchell with aggregation line (thicker) showing combined estimate (notice how opening gaps are handled differently)
Example: Trend-weighted aggregation
In strongly trending markets, weight Rogers-Satchell more heavily since it's drift-independent:
• Estimator 1: Garman-Klass (faster, higher weight in ranging)
• Estimator 2: Rogers-Satchell (drift-independent, higher weight in trends)
• Aggregation: weights 1:2 (favours RS during trends)
💮 Adaptive Threshold Detection
Three threshold modes for identifying volatility regime shifts. Threshold breaches are visualised with intensity-scaled fills that grow stronger the further volatility exceeds the threshold.
Example: Dynamic thresholds for regime detection
Configure dynamic thresholds to automatically adapt to market conditions:
• High Threshold Mode: Dynamic (baseline + 2× std dev)
• Low Threshold Mode: Dynamic (baseline - 2× std dev)
• Show threshold fills: Enabled
This creates adaptive bands that widen during volatile periods and narrow during calm periods.
Example: Percentile-based thresholds
Use percentile mode for context-aware regime detection:
• High Threshold Mode: Percentile (96th)
• Low Threshold Mode: Percentile (4th)
• Percentile Lookback: 500
This identifies when volatility enters the top/bottom 4% of its recent distribution.
↑ Different threshold settings, where the dynamic and percentile methods show adaptive bands that widen during volatile periods, with fill intensity varying by breach magnitude. Regime detection (see next) is enabled too.
💮 Regime Background Colouring
Optional background colouring indicates the current volatility regime:
• High Volatility — Warm/alert background colour
• Normal — No background (neutral)
• Low Volatility — Cool/calm background colour
Select which source (Estimator 1, Estimator 2, or Aggregation) drives the regime display.
Example: Regime filtering for trade decisions
Use regime background to filter trading signals from other indicators:
• Regime Source: Aggregation
• Background Transparency: 90 (subtle)
When the background shows HIGH volatility (warm), consider tighter stops. When LOW (cool), watch for breakout setups.
↑ Regime background emphasis for breakout strategies. Note the interesting A2RMA smoothing for this case.
🌸 --------- USAGE GUIDE --------- 🌸
💮 Getting Started
1. Add the indicator to your chart
2. Estimator 1 defaults to Yang-Zhang (14) — the most comprehensive estimator for gapped markets
3. Keep "Annualise Volatility" enabled to express values in standard annualised form
4. Observe the legend table for current values and percentile ranks (P##). Hover over the table cells to see a little more info in the tooltip.
💮 Choosing an Estimator
• Trending equities with gaps — Yang-Zhang. Handles both drift and overnight gaps optimally.
• Crypto (24/7 trading) — Rogers-Satchell. Drift-independent without Yang-Zhang's multi-period lag.
• Ranging markets — Garman-Klass or Parkinson. Simpler, no drift adjustment needed.
• Price-based stops — ATR. Output in price units, directly usable for stop distances.
• Regime detection — Combine any estimator with threshold modes enabled.
💮 Interpreting Output
• Value (P##) — The volatility reading with percentile rank. "0.1523 (P75)" means 0.1523 annualised volatility at the 75th percentile of recent history.
• Colour gradient — Warmer colours = higher percentile (elevated volatility), cooler colours = lower percentile.
• Threshold fills — Intensity indicates how far beyond the threshold the current reading is.
• ⚠️ HIGH / 🔻 LOW — Table indicators when thresholds are breached.
🌸 --------- ALERTS --------- 🌸
💮 Direction Change Alerts
• Estimator 1/2 direction change — Triggers when volatility inflects (rising to falling or vice versa)
💮 Cross Alerts
• E1 crossed E2 — Triggers when the two estimator lines cross
💮 Threshold Alerts
• E1/E2/Aggr High Volatility — Triggers when volatility breaches the high threshold
• E1/E2/Aggr Low Volatility — Triggers when volatility falls below the low threshold
💮 Regime Change Alerts
• E1/E2/Aggr Regime Change — Triggers when the volatility regime transitions (High ↔ Normal ↔ Low)
🌸 --------- LIMITATIONS --------- 🌸
• Drift bias in Parkinson/GK — These estimators overestimate variance in trending conditions. Switch to Rogers-Satchell or Yang-Zhang for trending markets.
• Yang-Zhang minimum lookback — Requires at least 2 bars (enforced internally). Cannot produce instantaneous readings like other estimators.
• Flat candles — Single-tick bars produce near-zero variance readings. Use higher timeframes for illiquid assets.
• Discretisation bias — Estimates degrade when ticks-per-bar is very small. Consider higher timeframes for thinly traded instruments.
• Scale mixing — Different scale groups (log-return, price unit, percentage) cannot be meaningfully compared or aggregated. The indicator warns but does not prevent display.
🌸 --------- CREDITS --------- 🌸
💮 Academic Sources
• Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI
• Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI
• Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI
• Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI
• Wilder, J.W. (1978). New Concepts in Technical Trading Systems . Trend Research.
💮 Libraries Used
• VolatilityToolkit Library — Range-based estimators, smoothing, and aggregation functions
• FiltersToolkit Library — Advanced smoothing filters (Super Smoother, Ultimate Smoother, BiQuad, etc.)
• ColourUtilities Library — Colour palette management and gradient calculations Indicator
Liquidation Bubbles [OmegaTools]🔴🟢 Liquidation Bubbles — Advanced Volume & Price Stress Detector
Liquidation Bubbles is a professional-grade analytical tool designed to identify forced positioning events, stop-runs, and liquidation clusters by combining price displacement and volume imbalance into a single, statistically normalized framework.
This indicator is not a repainting signal tool and not a simple volume spike detector. It is a contextual market stress mapper, built to highlight areas where one-sided positioning becomes unstable and the probability of forced order execution (liquidations, stops, margin calls) materially increases.
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## 🔬 Core Concept
Market liquidations do not occur randomly.
They emerge when price deviates aggressively from its volume-weighted equilibrium while volume itself becomes abnormal.
Liquidation Bubbles detects exactly this condition by:
* Estimating a **dynamic equilibrium price** using an *inverted volume-weighted moving average*
* Measuring **directional price stress** relative to that equilibrium
* Measuring **volume stress** relative to its own adaptive baseline
* Normalizing both into **Z-score–like metrics**
* Highlighting only **statistically extreme, asymmetric events**
The result is a clear visual map of stress points where market participants are most vulnerable.
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⚙️ Methodology (How It Works)
1️⃣ Advanced Inverted VWMA (Equilibrium Engine)
The script uses a custom Advanced VWMA, where:
* High volume bars receive less weight
* Low volume bars receive more weight
This produces a **robust equilibrium level**, resistant to manipulation and volume bursts.
This equilibrium is used for **both price and volume normalization**, creating a consistent statistical framework.
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2️⃣ Price Stress (Directional)
Price stress is calculated as:
* The **maximum deviation** between high/low and equilibrium
* Directionally signed (upside vs downside)
* Normalized by its own historical volatility
This allows the script to distinguish:
* Aggressive upside exhaustion
* Aggressive downside capitulation
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3️⃣ Volume Stress
Volume stress is measured as:
* Deviation from volume equilibrium
* Normalized by historical volume dispersion
This filters out:
* Normal high-volume sessions
* Illiquid noise
And isolates abnormal participation imbalance.
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4️⃣ Liquidation Logic
A liquidation event is flagged when:
* Both price stress and volume stress exceed adaptive thresholds
* The imbalance is directional and statistically extreme
Optional Combined Score Mode allows aggregation of price & volume stress into a single composite metric for smoother signals.
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🔵 Bubble System (Signal Hierarchy)
The indicator plots **two tiers of bubbles**:
🟢🔴 Small Bubbles
* Early warning stress points
* Localized stop-runs
* Micro-liquidations
* Often precede reactions or short-term reversals
🟢🔴 Big Bubbles
* Full liquidation clusters
* Forced unwinds
* High probability exhaustion zones
* Frequently align with:
* Intraday extremes
* Range boundaries
* Reversal pivots
* Volatility expansions
Bubble color:
* **Green** → Downside liquidation (sell-side exhaustion)
* **Red** → Upside liquidation (buy-side exhaustion)
Bubble placement is **ATR-adjusted**, ensuring visual clarity without overlapping price.
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🔄 Cross-Market Volume Analysis
The script allows optional **external volume sourcing**, enabling:
* Futures volume applied to CFDs
* Index volume applied to ETFs
* Spot volume applied to derivatives
This is critical when:
* Your traded instrument has unreliable volume
* You want **institutional-grade confirmation**
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🧠 How to Use Liquidation Bubbles
This indicator is **not meant to be traded alone**.
Best use cases:
* 🔹 Confluence with support & resistance
* 🔹 Contextual confirmation for reversals
* 🔹 Identifying fake breakouts
* 🔹 Liquidity sweep detection
* 🔹 Risk management (avoid entering into liquidation zones)
Ideal for:
* Futures
* Indices
* Crypto
* High-liquidity FX pairs
* Intraday & swing trading
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🎯 Who This Tool Is For
Liquidation Bubbles is designed for:
* Advanced discretionary traders
* Order-flow & liquidity-based traders
* Macro & index traders
* Professionals seeking **context**, not signals
If you want **where the market is fragile**, not just where price moved — this tool was built for you.
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📌 Key Characteristics
✔ Non-repainting
✔ Statistically normalized
✔ Adaptive to volatility
✔ Works on all timeframes
✔ Futures & crypto ready
✔ No lagging indicators
✔ No moving average crosses
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Liquidation Bubbles does not predict the future.
It shows you where the market is most likely to break.
— OmegaTools Indicator
Volume-Weighted Hybrid Channel [Capitalize Labs]Volume-Weighted Hybrid Channel (VWHC) is a channel-only indicator designed to visualise mean and volatility structure using a blended framework. It combines a configurable mean engine (SuperSmoother, EMA, SMA, or RMA) with an anchored VWAP component, then builds a four-level band ladder around a hybrid mean using a hybrid width that blends a range engine (ATR or true range variants) with anchored, volume-weighted standard deviation. The result is a smooth, adaptive channel intended to help us contextualise price location and volatility expansion or contraction relative to the hybrid mean.
The indicator supports Weekly or Session anchoring for the VWAP and sigma components, and includes optional transition smoothing after anchor resets to reduce visual stepping. Band levels are user-defined (with automatic ordering enforcement), and optional gradient fills can be enabled for clearer zone recognition. An optional Band Occupancy Table is included to show how frequently price closes inside each zone, either over a rolling lookback or since the most recent anchor reset. This table is informational only and does not generate signals.
This script is an indicator, not a strategy. It does not place trades, generate alerts, or provide entry or exit instructions. Outputs depend on chart symbol, timeframe, and data quality, including volume availability. The channel is designed to be non-repainting in the sense that it uses confirmed bar data and does not use forward-looking logic; however, like all indicators, the current bar can update until it closes.
Risk Warning
This material is educational research only and does not constitute financial advice, investment recommendation, or a solicitation to buy or sell any instrument. Foreign exchange and CFDs are complex, leveraged products that carry a high risk of rapid losses; leverage amplifies both gains and losses, and you should not trade with funds you cannot afford to lose. Market conditions can change without notice, and news or illiquidity may cause gaps and slippage; stop-loss orders are not guaranteed.
The analysis presented does not take into account your objectives, financial situation, or risk tolerance. Before acting, assess suitability in light of your circumstances and consider seeking advice from a licensed professional. Past performance and back-tested or hypothetical scenarios are not reliable indicators of future results, and no outcome or level mentioned here is assured. You are solely responsible for all trading decisions, including position sizing and risk management. No external links, promotions, or contact details are provided, in line with PulseWire House Rules.
Disclaimer
Use of this indicator is at our own discretion and risk. It is a visual analysis tool and should be validated through independent testing and a documented trading plan before being used in live decision-making. Indicator
Indicator
VWATR Stop-Loss BandsPurpose
The script provides an adaptive stop‑loss framework built from VWATR, it anchors protective levels to price extremes and scales them with both volatility and volume. The objective is to create stop‑loss zones that reflect real market intensity rather than arbitrary fixed distances.
How it works
The script computes true range, multiplies it by volume, and smooths both the volume‑weighted range and raw volume using the selected moving average, their ratio forms VWATR, a volatility measure normalized by traded volume. It then calculates the standard deviation of VWATR to capture volatility‑of‑volatility. Stop‑loss levels are constructed by offsetting the low and high by one VWATR, with additional layers created by adding or subtracting one to five standard deviations. The plots use strong colors for core levels and progressively lighter tones for outer layers, establishing a clear visual hierarchy.
Rationale
This structure gives the trader stop‑loss levels that adapt to changing market conditions, expanding during high‑energy phases and contracting during quiet periods, which reduces premature stop‑outs and aligns risk with actual volatility. The standard deviation layers provide a graded map of volatility stress, allowing the user to assess how far price must travel to breach increasingly extreme thresholds. The result is a stop‑loss system that is both reactive and context‑aware, offering more informed decision‑making than static offsets. Indicator
RSI Median DeviationRSI Median Deviation – Adaptive Statistical RSI for High-Probability Extremes
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder in 1978 to measure the magnitude of recent price changes and identify potential overbought or oversold conditions. It calculates the ratio of upward to downward price movements over a specified period, scaled to 0-100. However, standard RSI often relies on fixed thresholds like 70/30, which can produce unreliable signals in varying market regimes due to their lack of adaptability to the actual distribution of RSI values.
This indicator was developed because I needed a reliable tool for spotting intermediate high-probability bottoms and tops. Instead of arbitrary horizontal lines, it uses the RSI’s own historical median as a dynamic centerline and measures how far the current RSI deviates from that median over a chosen lookback period. The main signals are triggered only at 2 standard deviation (2σ) extremes — statistically rare events that occur roughly 5 % of the time under a normal distribution. I selected 2σ because it is extreme enough to be meaningful yet frequent enough for practical trading. For oversold signals I further require RSI to be below 42, a filter that significantly improved results in my mean-reversion tests (enter on oversold, exit on the first bar the condition is no longer true).
The combination of percentile median + standard deviation bands is deliberate: the median is far more robust to outliers than a simple average, while the SD bands automatically adjust to the current volatility of the RSI itself, producing adaptive envelopes that work equally well in ranging and trending markets.
Underlying Concepts and Calculations
Base RSI: RSI = 100 − (100 / (1 + RS)), RS = average gain / average loss (default length 10).
Percentile Median: 50th percentile of the last "N" RSI values (default 28 = 4 weeks)
→ dynamic, outlier-resistant centerline.
Standard Deviation Bands: rolling stdev of RSI (default length 27 = = 4 weeks (almost))
→ bands = median ± 1σ / 2σ.
Optional Dynamic MA Envelopes: user-selectable moving average (TEMA, WMA, etc., default WMA length 37) for additional momentum context.
Trend Bias Coloring
Independent of the statistical extremes, the RSI line itself is colored green when above the user-defined Long Threshold (default 60) and red when below the Short Threshold (default 47). This provides an instant bullish/bearish bias overlay similar to classic RSI usage, without interfering with the main 2σ extreme signals.
Extremes are highlighted with background color (green for oversold 2σ + RSI<42, magenta for overbought 2σ) and small diamond markers for ultra-extremes (RSI <25 or >85).
Originality and Development Rationale
The indicator was built and refined through extensive testing on dozens of assets including major cryptocurrencies:
(BTC, ETH, SOL, SUI, BNB, XRP, TRX, DOGE, LINK, PAXG, CVX, HYPE, VIRTUAL and many more),
the Magnificent 7 stocks,, QQQ, SPX, and gold.
Default parameters were chosen to deliver consistent profitability in simple mean-reversion setups while maximizing Sortino ratio and minimizing maximum drawdown across this broad universe — ensuring the settings are robust and not overfitted to any single instrument or timeframe.
How to Use It
Ideal for swing / position trading on the 1h to daily charts (the same defaults work).
Oversold (high-probability long): RSI crosses below lower 2σ band AND RSI < 42
→ green background
→ enter long, exit the first bar the condition disappears.
Overbought (high-probability short): RSI crosses above upper 2σ band
→ magenta background
→ enter short, exit on opposite signal or at median. (Shorts were not tested, it's only an idea)
Use the green/red RSI line coloring for quick trend context and to avoid fighting strong momentum.
Always confirm with price action and manage risk appropriately.
This indicator is not a standalone trading system.
Disclaimer: This is not financial advice. Backtests are based on past results and are not indicative of future performance.
Indicator
Today Range Calculator1. Indicator Name
Today (Today’s Volatility)
2. One-line Introduction
Displays real-time 30-day historical volatility (HV30) as a compact table on the chart, helping traders instantly assess market risk levels.
3. General Overview
Today ↑↓ is a lightweight informational widget that calculates and displays the 30-day Historical Volatility (HV30) of the asset in real time.
Using logarithmic returns over the past 30 periods, the script computes variance and then annualizes it to express volatility as a percentage (%) per year.
The result is shown in a clean 1x1 table cell, which can be positioned anywhere on the chart—top/bottom, left/right—depending on your preference.
This makes it easy to quickly evaluate whether the current market is high-risk (volatile) or stable, without cluttering the chart.
It’s especially useful for position sizing, risk management, volatility-based entry/exit decisions, and as a filter for breakout strategies.
Built with performance in mind, the script uses minimal system resources and can be used alongside any indicator or strategy without interference.
4. Key Advantages
📈 Real-time HV30 Display
Calculates and displays 30-day historical volatility using annualized log return variance.
📍 Custom Table Positioning
Place the volatility display in any corner of the chart for optimal visibility.
🧮 Accurate Log Return Calculation
Uses logarithmic returns to ensure precise volatility representation over time.
🎯 Quick Market Sentiment Read
Helps you determine at a glance whether the asset is in a calm or volatile environment.
🧼 Minimalist Design
Clean 1-cell table format keeps your chart readable and organized.
🚀 Ultra-Lightweight Script
Runs efficiently with negligible impact on chart performance.
📘 Indicator User Guide
📌 Basic Concept
Today ↑↓ calculates 30-day Historical Volatility (HV30) by analyzing the asset’s log returns over the past 30 bars.
The result is annualized and shown as a percentage to reflect volatility in standardized terms.
Useful for gauging risk levels and strategy suitability in current market conditions.
⚙️ Settings Explained
Table Position: Choose where the volatility table appears:
Top Left / Top Right / Bottom Left / Bottom Right
📈 High Volatility Example
HV30 > 50% indicates a volatile environment
Suggests wider stop-losses, cautious position sizing, or favoring breakout strategies
📉 Low Volatility Example
HV30 < 15% suggests a calm market or range-bound behavior
Useful as a signal for upcoming volatility expansions or breakout preparations
🧪 Recommended Use Cases
Position Sizing: Scale position size based on HV30 readings
Strategy Filter: Activate certain systems only when volatility meets predefined conditions
Breakout Timing: Identify low-volatility zones as potential breakout opportunities
🔒 Precautions
This indicator does not generate buy/sell signals; it is a volatility reference tool
HV thresholds vary across asset classes—adjust interpretation accordingly
Since HV30 is historical, it may lag during rapid market changes Indicator
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Volume Weighted Volatility RegimeThe Volume-Weighted Volatility Regime (VWVR) is a market analysis tool that dissects total volatility to classify the current market 'character' or 'regime'. Using a Linear Regression model, it decomposes volatility into Trend, Residual (mean-reversion), and Within-Bar (noise) components.
Key Features:
Seven-Stage Regime Classification: The indicator's primary output is a regime value from -3 to +3, identifying the market state:
+3 (Strong Bull Trend): High directional, upward volatility.
+2 (Choppy Bull): Moderate upward trend with noise.
+1 (Quiet Bull): Low volatility, slight upward drift.
0 (Neutral): No clear directional bias.
-1 (Quiet Bear): Low volatility, slight downward drift.
-2 (Choppy Bear): Moderate downward trend with noise.
-3 (Strong Bear Trend): High directional, downward volatility.
Advanced Volatility Decomposition: The regime is derived from a three-component volatility model that separates price action into Trend (momentum), Residual (mean-reversion), and Within-Bar (noise) variance. The classification is determined by comparing the 'Trend' ratio against the user-defined 'Trend Threshold' and 'Quiet Threshold'.
Dual-Level Analysis: The indicator analyzes market character on two levels simultaneously:
Inter-Bar Regime (Background Color): Based on the main StdDev Length, showing the overall market character.
Intra-Bar Regime (Column Color): Based on a high-resolution analysis within each single bar ('Intra-Bar Timeframe'), showing the micro-structural character.
Calculation Options:
Statistical Model: The 'Estimate Bar Statistics' option (enabled by default) uses a statistical model ('Estimator') to perform the decomposition. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead).
Normalization: An optional 'Normalize Volatility' setting calculates an Exponential Regression Curve (log-space).
Volume Weighting: An option (Volume weighted) applies volume weighting to all volatility calculations.
Multi-Timeframe (MTF) Capability: The entire dual-level analysis can be run on a higher timeframe (using the Timeframe input), with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Integrated Alerts: Includes 22 comprehensive alerts that trigger whenever the 'Inter-Bar Regime' or the 'Intra-Bar Regime' crosses one of the key thresholds (e.g., 'Regime crosses above Neutral Line'), or when the 'Intra-Bar Dominance' crosses the 50% mark.
Caution: Real-Time Data Behavior (Intra-Bar Repainting) This indicator uses high-resolution intra-bar data. As a result, the values on the current, unclosed bar (the real-time bar) will update dynamically as new intra-bar data arrives. This behavior is normal and necessary for this type of analysis. Signals should only be considered final after the main chart bar has closed.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration. Indicator
Volume Weighted Intra Bar LR Standard DeviationThis indicator analyzes market character by providing a detailed view of volatility. It applies a Linear Regression model to intra-bar price action, dissecting the total volatility of each bar into three distinct components.
Key Features:
Three-Component Volatility Decomposition: By analyzing a lower timeframe ('Intra-Bar Timeframe'), the indicator separates each bar's volatility into:
Trend Volatility (Green/Red): Volatility explained by the intra-bar linear regression slope (Momentum).
Residual Volatility (Yellow): Volatility from price oscillating around the intra-bar trendline (Mean-Reversion).
Within-Bar Volatility (Blue): Volatility derived from the range of each intra-bar candle (Noise/Choppiness).
Layered Column Visualization: The indicator plots these components as a layered column chart. The size of each colored layer visually represents the dominance of each volatility character.
Dual Display Modes: The indicator offers two modes to visualize this decomposition:
Absolute Mode: Displays the total standard deviation as the column height, showing the absolute magnitude of volatility and the contribution of each component.
Normalized Mode: Displays the components as a 100% stacked column chart (scaled from 0 to 1), focusing purely on the percentage ratio of Trend, Residual, and Noise.
Calculation Options:
Statistical Model: The 'Estimate Bar Statistics' option (enabled by default) uses a statistical model ('Estimator') to perform the decomposition. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead).
Normalization: An optional 'Normalize Volatility' setting calculates an Exponential Regression Curve (log-space).
Volume Weighting: An option (Volume weighted) applies volume weighting to all intra-bar calculations.
Multi-Component Pivot Detection: Includes a pivot detector that identifies significant turning points (highs and lows) in both the Total Volatility and the Trend Volatility Ratio. (Note: These pivots are only plotted when 'Plot Mode' is set to 'Absolute').
Note on Confirmation (Lag): Pivot signals are confirmed using a lookback method. A pivot is only plotted after the Pivot Right Bars input has passed, which introduces an inherent lag.
Multi-Timeframe (MTF) Capability:
MTF Analysis: The entire intra-bar analysis can be run on a higher timeframe (using the Timeframe input), with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Pivot detection (Calculate Pivots) is disabled if a Higher Timeframe (HTF) is selected.
Integrated Alerts: Includes 9 comprehensive alerts for:
Volatility character changes (e.g., 'Character Change from Noise to Trend').
Dominant character emerging (e.g., 'Bullish Trend Character Emerging').
Total Volatility pivot (High/Low) detection.
Trend Volatility pivot (High/Low) detection.
Caution! Real-Time Data Behavior (Intra-Bar Repainting) This indicator uses high-resolution intra-bar data. As a result, the values on the current, unclosed bar (the real-time bar) will update dynamically as new intra-bar data arrives. This behavior is normal and necessary for this type of analysis. Signals should only be considered final after the main chart bar has closed.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration. Indicator
Volume Weighted Intra Bar Standard DeviationThis indicator provides a high-resolution analysis of market volatility by dissecting each bar on the chart into its fundamental components. It uses data from a lower, intra-bar timeframe to separate the total volatility of a single bar into its 'directional' and 'non-directional' parts.
Key Features:
Intra-Bar Volatility Decomposition: For each bar on the chart, the indicator analyzes the underlying price action on a smaller timeframe ('Intra-Bar Timeframe') and quantifies two types of volatility:
Between-Bar Volatility (Directional): Calculated from price movements between the intra-bar candles. This component represents the directional, trending price action within the main bar.
Within-Bar Volatility (Non-Directional): Calculated from price fluctuations inside each intra-bar candle. This component represents the choppy, noisy, or ranging price action.
Dual Display Modes: The indicator offers two modes to visualize this information:
Absolute Mode: Plots the total standard deviation as a stacked column chart, showing the absolute magnitude of volatility and the contribution of each component.
Normalized Mode: Plots the components as a 100% stacked column chart (scaled from 0 to 1), focusing purely on the percentage ratio of 'between-bar' (trending) and 'within-bar' (choppy) volatility.
Calculation Options:
Statistical Model: The 'Estimate Bar Statistics' option (enabled by default) uses a statistical model ('Estimator') to perform the decomposition. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead).
Normalization: An optional 'Normalize Volatility' setting calculates volatility in percentage terms (log-space).
Volume Weighting: An option (Volume weighted) applies volume weighting to all intra-bar volatility calculations.
Volatility Pivot Detection: Includes a built-in pivot detector that identifies significant turning points (highs and lows) in the total volatility line. (Note: This is only visible in 'Absolute Mode').
Note on Confirmation (Lag): Pivot signals are confirmed using a lookback method. A pivot is only plotted after the Pivot Right Bars input has passed, which introduces an inherent lag.
Multi-Timeframe (MTF) Capability:
MTF Analysis Lines: The entire intra-bar analysis can be run on a higher timeframe (using the Timeframe input), with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Pivot detection (Calculate Pivots) is disabled if a Higher Timeframe (HTF) is selected.
Integrated Alerts: Includes 6 alerts for:
Volatility character changes (e.g., 'Character Change from Choppy to Trend').
Dominant character emerging (e.g., 'Trend Character Emerging').
Total Volatility pivot (High/Low) detection.
Caution: Real-Time Data Behavior (Intra-Bar Repainting) This indicator uses high-resolution intra-bar data. As a result, the values on the current, unclosed bar (the real-time bar) will update dynamically as new intra-bar data arrives. This behavior is normal and necessary for this type of analysis. Signals should only be considered final after the main chart bar has closed.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration. Indicator
Volume Weighted LR Standard DeviationThis indicator analyzes market character by decomposing total volatility into three distinct, interpretable components based on a Linear Regression model.
Key Features:
Three-Component Volatility Decomposition: The indicator separates volatility based on the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): Calculates volatility based on the selected Source (dies führt hauptsächlich zu 'Trend'- und 'Residual'-Volatilität).
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead). This separates volatility into:
Trend Volatility (Green/Red): Volatility explained by the regression's slope (Momentum).
Residual Volatility (Yellow): Volatility from price oscillating around the regression line (Mean-Reversion).
Within-Bar Volatility (Blue): Volatility from the high-low range of each bar (Noise/Choppiness).
Dual Display Modes: The indicator offers two modes to visualize this decomposition:
Absolute Mode: Displays the total standard deviation as a stacked area chart, partitioned by the variance ratio of the three components.
Normalized Mode: Displays the direct variance ratio (proportion) of each component relative to the total (0-1), ideal for identifying the dominant market character.
Calculation Options:
Normalization: An optional 'Normalize Volatility' setting calculates an Exponential Regression Curve (log-space), making the analysis suitable for growth assets.
Volume Weighting: An option (Volume weighted) applies volume weighting to all regression and volatility calculations.
Multi-Component Pivot Detection: Includes a pivot detector that identifies significant turning points (highs and lows) in both the Total Volatility and the Trend Volatility Ratio. (Note: These pivots are only plotted when 'Plot Mode' is set to 'Absolute').
Note on Confirmation (Lag): Pivot signals are confirmed using a lookback method. A pivot is only plotted after the Pivot Right Bars input has passed, which introduces an inherent lag.
Multi-Timeframe (MTF) Capability:
MTF Volatility Lines: The volatility lines can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Pivot detection (Calculate Pivots) is disabled if a Higher Timeframe (HTF) is selected.
Integrated Alerts: Includes 9 comprehensive alerts for:
Volatility character changes (e.g., 'Character Change from Noise to Trend').
Dominant character emerging (e.g., 'Bullish Trend Character Emerging').
Total Volatility pivot (High/Low) detection.
Trend Volatility pivot (High/Low) detection.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration. Indicator
Volume Weighted Standard DeviationThis indicator calculates the Standard Deviation and decomposes total volatility into its core components, allowing to analyze the underlying character of the market.
Key Features:
Volatility Decomposition: The indicator separates volatility based on the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): Calculates a simple (Volume-Weighted) Standard Deviation of the selected Source.
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility (choppiness, noise) and between-bar volatility (trending moves). (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead).
Dual Display Modes: The indicator offers two modes to visualize this information:
Absolute Mode: Plots the total standard deviation as a stacked area chart, showing the proportional contribution of the 'Between' and 'Within' components.
Normalized Mode: Plots the direct ratio of each component's variance (from 0 to 1), making it easy to identify which character is dominant.
Calculation Options: The volatility calculation can be optionally Volume weighted. An optional Normalize Volatility setting performs the calculation in logarithmic space, making volatility comparable across different price scales.
Volatility Pivot Detection: Includes a built-in pivot detector that identifies significant turning points (highs and lows) in the total volatility line. (Note: This is only visible in 'Absolute Mode').
Note on Confirmation (Lag): Pivot signals are confirmed using a lookback method. A pivot is only plotted after the Pivot Right Bars input has passed, which introduces an inherent lag.
Multi-Timeframe (MTF) Capability:
MTF Volatility Lines: The volatility lines can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Pivot detection (Calculate Pivots) is disabled if a Higher Timeframe (HTF) is selected.
Integrated Alerts: Includes 6 alerts for:
Volatility character changes (e.g., 'Trend Character Emerging', 'Character Change from Trend to Choppy').
Volatility pivot (high or low) detection.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration. Indicator
Indicator
Double Median SD Bands | MisinkoMasterThe Double Median SD Bands (DMSDB) is a trend-following tool designed to capture market direction in a way that balances responsiveness and smoothness, filtering out excessive noise without introducing heavy lag.
Think of it like a house:
A jail (too restrictive) makes you miss opportunities.
No house at all (too unsafe) leaves you exposed to false signals.
DMSDB acts like a comfortable house with windows—protecting you from the noise while still letting you see what’s happening in the market.
🔎 Methodology
The script works in the following steps:
Standard Deviation (SD) Calculation
Computes the standard deviation of the selected price source (ohlc4 by default).
The user can choose whether to use biased (sample) or unbiased (population) standard deviation.
Raw Bands Construction
Upper Band = source + (SD × multiplier)
Lower Band = source - (SD × multiplier)
The multiplier can be adjusted for tighter or looser bands.
First Median Smoothing
Applies a median filter over half of the length (len/2) to both bands.
This reduces noise without creating excessive lag.
Second Median Smoothing
Applies another median filter over √len to the already smoothed bands.
This produces a balance:
Cutting the length → maintains responsiveness.
Median smoothing → reduces whipsaws.
The combination creates a fast yet clean band system ideal for trend detection.
📈 Trend Logic
The trend is detected based on price crossing the smoothed bands:
Long / Bullish (Purple) → when price crosses above the upper band.
Short / Bearish (Gold) → when price crosses below the lower band.
Neutral → when price remains between the bands.
🎨 Visualization
Upper and lower bands are plotted as colored lines.
The area between the bands is filled with a transparent zone that reflects the current bias:
Purple shading = Bullish zone.
Golden shading = Bearish zone.
This creates a visual tunnel for trend confirmation, helping traders quickly identify whether price action is trending or consolidating.
⚡ Features
Adjustable Length parameter (len) for dynamic control.
Adjustable Band Multiplier for volatility adaptation.
Choice between biased vs. unbiased standard deviation.
Double median smoothing for clarity + responsiveness.
Works well on cryptocurrencies (e.g., BTCUSD) but is flexible enough for stocks, forex, and indices.
✅ Use Cases
Trend Following → Ride trends by staying on the correct side of the bands.
Entry Timing → Use crossovers above/below bands for entry triggers.
Filter for Other Strategies → Can serve as a directional filter to avoid trading against the trend.
⚠️ Limitations & Notes
This is a trend-following tool, so it will perform best in trending conditions.
In sideways or choppy markets, whipsaws may still occur (although smoothing reduces them significantly).
The indicator is not a standalone buy/sell system. For best results, combine with volume, momentum, or higher-timeframe confluence.
All of this makes for a really unique & original tool, as it removes noise but keeps good responsitivity, using methods from many different principles which make for a smooth a very useful tool Indicator
Implied Volatility RangeThe Implied Volatility Range is a forward-looking tool that transforms option market data into probability ranges for future prices. Based on the lognormal distribution of asset prices assumed in modern option pricing models, it converts the implied volatility curve into a volatility cone with dynamic labels that show the market’s expectations for the price distribution at a specific point in time. At the selected future date, it displays projected price levels and their percentage change from today’s close across 1, 2, and 3 standard deviation (σ) ranges:
1σ range = ~68.2% probability the price will remain within this range.
2σ range = ~95.4% probability the price will remain within this range.
3σ range = ~99.7% probability the price will remain within this range.
What makes this indicator especially useful is its ability to incorporate implied volatility skew. When only ATM IV (%) is entered, the indicator displays the standard Black–Scholes lognormal distribution. By adding High IV (%) and Low IV (%) values tied to strikes above and below the current price, the indicator interpolates between these inputs to approximate the implied volatility skew. This adjustment produces a market-implied probability distribution that indicates whether the option market is leaning bullish or bearish, based on the data entered in the menu:
ATM IV (%) = Implied volatility at the current spot price (at-the-money).
High IV (%) = Implied volatility at a strike above the current spot price.
High Strike = Strike price corresponding to the High IV input (OTM call).
Low IV (%) = Implied volatility at a strike below the current spot price.
Low Strike = Strike price corresponding to the Low IV input (OTM put).
Expiration (Day, Month, Year) = Option expiration date for the projection.
Once these inputs are entered, the indicator calculates implied probability ranges and, if both High IV and Low IV values are provided, adjusts for skew to approximate the option market’s distribution. If no implied volatility data is supplied, the indicator defaults to a lognormal distribution based on historical volatility, using past realized volatility over the same forward horizon. This keeps the tool functional even without implied volatility inputs, though in that case the output represents only an approximation of ATM IV, not the actual market view.
In summary, the Implied Volatility Range is a powerful tool that translates implied volatility inputs into a clear and practical estimate of the market’s expectations for future prices. It allows traders to visualize the probability of price ranges while also highlighting directional bias, a dimension often difficult to interpret from traditional implied volatility charts. It should be emphasized, however, that this tool reflects only the market’s expectations at a specific point in time, which may change as new information and trading activity reshape implied volatility. Indicator
CandelaCharts - Projections 📝 Overview
Projections turns a hand-picked swing window into clean, forward price levels. You pick a time range and an anchor (wick or body); the tool finds that window’s reference extremes (Level 0 & Level 1) and then projects directional extensions (e.g., −1, −2, −2.5, −4) in the chosen bias (Auto / Bullish / Bearish). It draws flat lines across the chart with optional labels so you can plan targets, fade zones, or continuation levels at a glance.
📦 Features
This section highlights the core capabilities you’ll rely on most.
Window-based engine — Define a start/end time; the script records open/high/low/close inside that window and builds levels from those extremes.
Two anchor styles — Project from Wick extremes (Hi/Lo) or Body extremes (max/min of OHLC at the high/low bars).
Directional bias — Auto (up if net up; doji resolves by wick dominance), or force Bullish/Bearish for one-sided extensions.
Default & Custom levels — Toggle pre-sets (−1/−2/−2.5/−4) or enter your own comma-separated list (decimals supported).
Readable drawings — Per-level colors (defaults) or unified bull/bear color (custom), with label size, line style, and width controls.
⚙️ Settings
Use these controls to define the window, pick the projection style, and customize the visuals.
Settings (Core)
From / To — Start and end timestamps of the capture window (everything is computed from this segment).
Bias — Auto / Bullish / Bearish. Guides which way negative levels extend (up for bull, down for bear).
Anchor — Wick uses Hi/Lo; Body uses the body extremes at the high/low bars.
Levels
Levels = Default — Enable any of −1, −2, −2.5, −4 and set each color.
Levels = Custom — Provide your own list (e.g., “−0.5, −1, −1.5, −3”) and pick Bullish/Bearish colors. (Custom uses one color per side.)
Style
Labels — Show/Hide the numeric level tag at the line’s right edge; choose label size.
Lines — Pick solid/dashed/dotted and line width.
⚡️ Showcase
Bearish Projection
Bullish Projection
📒 Usage
Follow these steps to set the window, generate levels, and turn them into a trade plan.
1) Mark the window — Set From/To around the swing you want to project (e.g., prior day, news impulse, weekly move).
2) Choose bias — Auto adapts; or lock Bullish/Bearish if you only want upside or downside projections.
3) Pick anchor — Wick = raw extremes; Body = more conservative reference. Body helps when single-print wicks distort levels.
4) Select levels — Toggle defaults or add a custom list. Negative values (−1, −2, …) extend beyond the reference extreme in the bias direction. (Level 0 and 1 are always drawn as the reference pair.)
5) Style it — Turn labels on, adjust size, and set line style/width for visibility on your timeframe.
6) Trade plan — Treat projections as reaction/continuation zones: scale out into −1/−2/−2.5, watch for fades back into the band, or ride continuation when price accepts beyond a level.
🚨 Alerts
There are no built-in alerts in this version.
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Indicator
Extreme Zone Volume ProfileExtreme Zone Volume Profile (EZVP)
Originality & Innovation
The Extreme Zone Volume Profile (EZVP) revolutionizes traditional volume profile analysis by applying statistical zone classification to volume distribution. Unlike standard volume profiles that display raw volume data, EZVP segments the price range into statistically meaningful zones based on percentile thresholds, allowing traders to instantly identify where volume concentration suggests strong support/resistance versus areas of potential breakout.
Technical Methodology
Core Algorithm:
Distributes volume across user-defined bins (20-200) over a lookback period
Calculates volume-weighted price levels for each bin
Applies percentile-based zone classification to the price range (not volume ranking)
Zone B (extreme zones): Outer percentile tails representing potential rejection areas
Zone A (significant zones): Secondary percentile bands indicating strong interest levels
Center Zone: Bulk trading range where most price discovery occurs
Mathematical Foundation:
The script uses price-range percentiles rather than volume percentiles. If the total price range is divided into 100%, Zone B captures the extreme price tails (default 2.5% each end ≈ 2 standard deviations), Zone A captures the next significant bands (default 14% each ≈ 1 standard deviation), leaving the center for normal distribution trading.
Key Calculations:
POC (Point of Control): Price level with maximum volume accumulation
Volume-weighted mean price: Total volume × price / total volume
Median price: Geometric center of the price range
Rightward-projected bars: Volume bars extend forward from current time to avoid historical chart clutter
Trading Applications
Zone Interpretation:
Zone B (Red/Green): Extreme price levels where volume suggests strong rejection potential. Price reaching these zones often indicates overextension and possible reversal points.
Zone A (Orange/Teal): Significant support/resistance areas with substantial volume interest. These levels often act as intermediate targets or consolidation zones.
Center (Gray): Fair value area where most trading occurs. Price tends to return to this range during normal market conditions.
Strategic Usage:
Reversal Trading: Look for rejection signals when price enters Zone B areas
Breakout Confirmation: Volume expansion beyond Zone B boundaries suggests genuine breakouts
Support/Resistance: Zone A boundaries often provide reliable entry/exit levels
Mean Reversion: Price tends to gravitate toward the volume-weighted mean and POC lines
Unique Value Proposition
EZVP addresses three key limitations of traditional volume profiles:
Visual Clarity: Standard profiles can be cluttered and difficult to interpret quickly. EZVP's color-coded zones provide instant visual feedback about price significance.
Statistical Framework: Rather than relying on subjective interpretation of volume nodes, EZVP applies objective percentile-based classification, making support/resistance identification more systematic.
Forward-Looking Display: Rightward-projecting bars keep historical price action clean while maintaining current market structure visibility.
Configuration Guide
Lookback Period (10-1000): Controls the historical depth of volume calculation. Shorter periods for intraday scalping, longer for swing trading.
Number of Bins (20-200): Resolution of volume distribution. Higher values provide more granular analysis but may create noise on lower timeframes.
Zone Percentages:
Zone B: Extreme threshold (default 2.5% = ~2σ statistical significance)
Zone A: Significant threshold (default 14% = ~1σ statistical significance)
Visual Controls: Toggle individual elements (POC, median, mean, zone lines) to customize display complexity for your trading style.
Technical Requirements
Pine Script v6 compatible
Maximum bars back: 5000 (ensures sufficient historical data)
Maximum boxes: 500 (supports high-resolution bin counts)
Maximum lines: 50 (accommodates all zone and reference lines)
This indicator synthesizes volume profile theory with statistical zone analysis, providing a quantitative framework for identifying high-probability support/resistance levels based on volume distribution patterns rather than arbitrary price levels. Indicator
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