Neural Direction OscillatorNeural Direction Oscillator
www.tradingview.com
Neural Direction Oscillator is an advanced momentum and trend analysis indicator that combines **Directional Movement Index (DMI)**, **ADX trend strength**, **logistic probability modeling**, and a neural-inspired oscillator to identify high-probability market direction with greater precision.
Instead of using traditional momentum calculations, the indicator converts bullish and bearish directional movement into probability values using a logistic transformation. These probabilities are then combined with ADX trend strength to create a dynamic Neural Direction Oscillator that adapts to changing market conditions while filtering unnecessary market noise.
The oscillator is normalized through a neural activation function, producing smooth directional readings that clearly distinguish bullish momentum, bearish momentum, and neutral market conditions. Dynamic color transitions instantly show whether buying or selling pressure is strengthening or weakening.
To improve signal quality, the indicator supports multiple confirmation methods including **Zero-Line Crossovers**, **Momentum Reversal Detection**, or a combination of both. This allows traders to customize signals according to their preferred trading style, whether they focus on early reversals or confirmed trend continuation.
An optional Mean-Reversion Engine calculates dynamic percentile-based upper and lower thresholds, automatically identifying statistically extreme momentum conditions where price may be preparing for a reversal. Small directional arrows highlight these opportunities without cluttering the chart.
The indicator also includes an integrated EMA trend filter plotted directly on the price chart, helping traders align oscillator signals with the prevailing market trend. Buy and Sell labels are automatically displayed on the chart whenever signal conditions are met, providing clear and easy-to-follow trading confirmations.
Background highlighting and adaptive candle coloring further enhance trend visualization by emphasizing periods of strong bullish or bearish momentum.
## Features
• Neural-Inspired Directional Oscillator
• Logistic Probability-Based Trend Analysis
• DMI (+DI / -DI) Momentum Engine
• ADX Trend Strength Confirmation
• Neural Activation Function (Tanh Normalization)
• Zero-Line Crossover Signals
• Momentum Reversal Detection
• Combined Trend Confirmation Mode
• Dynamic Mean-Reversion Levels
• Percentile-Based Adaptive Thresholds
• Optional Oscillator Moving Average (SMA, EMA, RMA & WMA)
• Automatic BUY & SELL Signals on Price Chart
• Integrated EMA Trend Filter
• Dynamic Candle Coloring & Background Trend Highlighting
• Real-Time TradingView Alert Conditions
• Suitable for Forex, Gold, Crypto, Stocks, Indices, Futures, and all TradingView-supported markets.
This indicator is designed for traders who combine **momentum analysis, trend-following strategies, Smart Money Concepts (SMC), algorithmic trading, and quantitative market analysis**. By integrating probability modeling with directional movement and adaptive smoothing, it provides a cleaner view of market momentum while helping traders identify trend continuation and reversal opportunities with greater confidence.
**Disclaimer:** This indicator is intended for educational and analytical purposes only. It should not be considered financial advice or a guarantee of future trading performance. Always use proper risk management and combine its signals with your own market analysis before making trading decisions.
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インジケーター
BULL BEARS VOLUMES AND ACTIVITIESwww.tradingview.com
BULL BEARS VOLUMES AND ACTIVITIES is a multi-symbol volume activity dashboard designed to visualize estimated buying and selling pressure across up to **20 customizable markets** in a single panel. Using each candle's price position within its high-low range, the indicator estimates how much of the total volume was driven by buyers versus sellers, providing a real-time view of market participation and directional pressure. Every symbol is displayed with paired **Bull (Green)** and **Bear (Red)** activity bars whose heights are proportional to their estimated buying and selling volume, while the exact volume values, ticker name, and live market price are shown for quick comparison. Price labels are automatically color-coded to reflect whether the current price is trading above or below its opening price, allowing traders to instantly identify stronger and weaker markets. The dashboard supports any asset class including **Forex, Crypto, Stocks, Indices, Commodities, and Futures**, with a fully configurable analysis timeframe independent of the chart timeframe. Its clean visual layout makes it easy to monitor institutional buying and selling activity, compare volume dominance across multiple symbols, identify relative market strength, and track capital rotation from a single screen without constantly switching between charts. This indicator is ideal for traders seeking a fast, visual overview of bullish versus bearish volume activity to support market analysis, watchlist monitoring, and trade confirmation alongside other technical tools.
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インジケーター
RSI LEVELS WITH MACHINE LEARNINGS.RSI Levels with Machine Learning
www.tradingview.com
**RSI Levels with Machine Learning** is an advanced momentum analysis indicator that combines the traditional Relative Strength Index (RSI) with an adaptive machine learning-inspired pattern recognition engine to generate higher-quality BUY and SELL signals while filtering out low-probability market conditions.
Instead of relying solely on fixed RSI overbought and oversold levels, this indicator continuously studies historical market behavior, compares current momentum characteristics with previously observed price patterns, and dynamically adjusts its market bias based on statistical similarity. The result is a smarter RSI that adapts to changing market conditions instead of using static calculations alone.
At the core of the indicator is a **Machine Learning Memory Bank**, which stores hundreds of historical RSI behavior patterns and evaluates them against the current market using a nearest-neighbor similarity model. Multiple RSI-derived features—including momentum, acceleration, percentile ranking, trend strength, and price relationship—are analyzed to identify historical situations that closely resemble the current market environment.
Each detected pattern contributes to a weighted voting system that produces:
• Bullish Market Bias
• Bearish Market Bias
• Confidence Percentage
• Analog Similarity Strength
Rather than generating signals from every RSI crossover, the indicator assigns an intelligent ranking score to every potential trade. BUY and SELL opportunities are evaluated using several confirmation layers, including:
• Machine Learning Pattern Recognition
• Confidence Score
• Analog Match Quality
• Adaptive RSI Supertrend Direction
• Volatility Filter
• Momentum Strength
• Signal Cooldown Protection
Only signals that satisfy the required quality thresholds are displayed, helping traders avoid unnecessary market noise and focus on higher-probability opportunities.
The indicator introduces an adaptive **RSI Supertrend**, which automatically adjusts its sensitivity according to machine learning confidence. During uncertain market conditions, the trend filter becomes more conservative, while in stronger market environments it reacts more efficiently to trend changes.
An optional RSI Signal Line provides additional momentum confirmation, while the built-in momentum histogram helps visualize the relationship between the Machine Learning RSI and its signal line for easier trend analysis.
To improve chart readability, the indicator can automatically repaint price candles using a clean blue-and-white color scheme that reflects the current machine learning trend direction, making bullish and bearish phases instantly recognizable.
The indicator also includes classic RSI reference zones with enhanced visualization:
• Extreme Overbought Level (80)
• Overbought Level (70)
• Neutral Level (50)
• Oversold Level (30)
• Extreme Oversold Level (20)
Background highlighting further emphasizes strong overbought and oversold conditions to help traders quickly identify potential reversal or continuation areas.
A built-in dashboard continuously displays important market statistics, including:
• Current Machine Learning Bias
• Machine Learning RSI Value
• Confidence Percentage
• BUY Rank
• SELL Rank
• Volatility Rank
• Learning Memory Size
Every component of the indicator is fully customizable. Traders can adjust memory depth, learning horizon, analog count, confidence thresholds, volatility filters, RSI parameters, Supertrend settings, signal line type, visualization, dashboard appearance, colors, and alert preferences to match their own trading style.
Built-in alerts notify traders whenever important events occur, including:
• BUY Signal
• SELL Signal
• RSI Overbought
• RSI Oversold
## Best Used For
• Momentum Trading
• Trend Confirmation
• Machine Learning-Based RSI Analysis
• Swing Trading
• Intraday Trading
• Scalping
• Reversal Trading
• Continuation Trading
• Cryptocurrency Markets
• Forex Markets
• Stocks and Indices
## Important Notice
This indicator uses a machine learning-inspired pattern recognition approach based entirely on historical market data. It does not predict future prices or guarantee profitable trades. All signals, confidence scores, and market bias calculations should be used as decision-support tools alongside sound risk management, market structure analysis, and your overall trading strategy.
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www.tradingview.com
インジケーター
Smart Money Volume Matrixwww.tradingview.com
Smart Money Volume Matrix is an advanced institutional volume analysis indicator that transforms raw volume data into a complete Smart Money visualization system. By combining Higher Timeframe (HTF) market structure, Lower Timeframe (LTF) volume spikes, stacked volume imbalances, projection blocks, and dynamic volume profiles, it helps traders understand where institutional activity is concentrated and how it may influence future price movement.
The indicator automatically anchors its analysis to a Higher Timeframe candle while collecting detailed Lower Timeframe volume information inside that candle. This multi-timeframe approach allows traders to see exactly where aggressive buying and selling occurred throughout the formation of each HTF candle, providing a much deeper understanding of institutional order flow than standard volume indicators.
Every significant volume spike is plotted as a dynamic bubble whose size reflects relative trading activity. Bullish and bearish spikes are separated automatically, making it easy to distinguish buying pressure from selling pressure at different price levels.
To further enhance market structure analysis, the indicator detects stacked volume imbalances created by repeated buying or selling at the same price region. These imbalance zones often represent institutional accumulation or distribution areas that can become important support and resistance levels during future price action.
A unique Projection Matrix displays the complete Higher Timeframe candle alongside its internal volume structure, including spike distribution, stacked imbalances, and an integrated volume profile. Previous HTF candles can also be displayed as Ghost Projection Blocks, allowing traders to compare current institutional activity with previous market cycles.
The built-in Volume Profile organizes traded volume across multiple price levels inside every Higher Timeframe candle, helping identify high-volume nodes, low-volume areas, and potential price acceptance or rejection zones.
Connection lines link the live chart with each projection block, while automatic OHLC labels provide a clear reference to important Higher Timeframe price levels. Real-time Bullish and Bearish Volume Spike signals, together with Volume Imbalance alerts, help traders react quickly whenever institutional participation increases.
Features
• Multi-Timeframe Smart Money Volume Analysis
• Automatic Higher Timeframe Projection Blocks
• Previous HTF Ghost Block Comparison
• Lower Timeframe Volume Spike Detection
• Dynamic Spike Bubble Visualization
• Stacked Bullish & Bearish Volume Imbalance Zones
• Integrated Volume Profile Inside Every HTF Candle
• Automatic Volume Distribution Matrix
• Institutional Buy & Sell Pressure Visualization
• HTF Open, High, Low & Close Mapping
• Projection Connection Lines
• Live Bullish & Bearish Volume Spike Signals
• Real-Time Volume Imbalance Detection
• Fully Customizable Timeframes & Display Settings
• TradingView Alert Conditions for Volume Spikes & Imbalances
• Optimized for Forex, Gold, Indices, Crypto, Stocks, Futures, and all TradingView-supported markets.
This indicator is ideal for traders who use Smart Money Concepts (SMC), ICT methodologies, institutional order flow, volume profile analysis, liquidity trading, footprint concepts, and professional price action analysis. It provides a detailed visualization of how institutional volume develops inside Higher Timeframe candles, allowing traders to identify accumulation, distribution, and high-probability trading opportunities with greater confidence.
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www.tradingview.com インジケーター
Whale Liquidity Zones and volume signalswww.tradingview.com
Whale Liquidity Zones & Volume Signals is an advanced institutional volume analysis indicator designed to reveal where large market participants are actively trading. By combining Volume Profile, Delta Analysis, Whale Volume Detection, Absorption, and Liquidity Zones into one powerful tool, it helps traders identify the most important price levels where significant buying or selling interest exists.
Unlike traditional volume indicators, this script separates bullish and bearish volume across every price level to build a detailed Buy/Sell Volume Profile. It automatically detects unusually large "whale" transactions using a dynamic volume percentile model, allowing traders to focus on institutional activity instead of ordinary market noise.
The integrated Delta Heatmap visualizes buying and selling pressure at each price level, making it easier to identify which side of the market is in control. At the same time, the Absorption Profile highlights areas where aggressive buying or selling has been absorbed, often signaling potential reversals or major institutional accumulation and distribution.
The indicator also automatically detects high-probability Whale Liquidity Zones by combining absorption peaks, strong delta imbalance, and significant traded volume. These zones are projected directly onto the chart as institutional Supply and Demand areas that traders can use for future market reactions.
To further enhance market structure analysis, the script calculates the Point of Control (POC) and optional Value Area, highlighting where the majority of trading activity occurred during the selected lookback period. These levels often act as important support, resistance, and price acceptance zones.
Strong Whale Volume Bubbles identify exceptionally high-volume candles directly on the chart, while live Whale Buy and Sell Signals combine institutional volume with absorption confirmation to generate high-quality trading opportunities.
A professional dashboard continuously displays market bias, Buy vs Sell Volume, Strong Whale Activity, Absorption Volume, and the current Whale Volume Threshold, providing an instant overview of institutional market conditions.
Features
• Advanced Buy & Sell Volume Profile
• Dynamic Whale Volume Detection using Volume Percentiles
• Institutional Buy & Sell Pressure Analysis
• Delta Heatmap by Price Level
• Absorption Profile Detection
• Automatic Whale Liquidity Zones (Supply & Demand)
• Point of Control (POC) Detection
• Optional Value Area Highlighting
• Strong Whale Volume Bubble Markers
• Live Whale Buy & Sell Signals
• Bullish & Bearish Delta Dominance Detection
• Institutional Market Bias Dashboard
• Highly Customizable Profile Resolution & Visual Settings
• Real-Time TradingView Alert Conditions
• Optimized for Forex, Gold, Indices, Crypto, Stocks, Futures, and other TradingView-supported markets.
This indicator is built for traders who follow Smart Money Concepts (SMC), institutional order flow, volume profile analysis, footprint-style trading, liquidity concepts, Wyckoff methodology, and price action trading. Whether you're scalping, day trading, or swing trading, it provides a comprehensive view of where institutional liquidity and whale participation are most likely influencing price.
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www.tradingview.com インジケーター
Neural Signal Matrix Oscillatorwww.tradingview.com
Neural Signal Matrix Oscillator is an advanced multi-factor momentum oscillator that combines trend, momentum, mean reversion, volume pressure, and volatility into a single adaptive scoring model. Rather than relying on a single technical indicator, it builds a weighted neural-style matrix that continuously evaluates multiple market conditions to generate higher-quality trading signals and market bias.
At the core of the indicator is a dynamic scoring engine that analyzes EMA trend direction, RSI behavior, price momentum, volume pressure, and volatility expansion. Each market component contributes to the final oscillator through customizable weighting, allowing traders to emphasize the factors that best suit their trading style.
A unique Adaptive Reliability System continuously monitors the historical performance of every market component. Instead of assigning fixed importance to each factor, the indicator automatically adjusts their influence based on how accurately they have predicted price movement over recent market conditions. Components with higher reliability receive greater weighting, while weaker components contribute less, allowing the oscillator to adapt naturally as market behavior changes.
The oscillator is displayed on a normalized 0–100 scale, making it easy to identify bullish momentum, bearish pressure, neutral conditions, and potential reversals. A smoothed Signal Line helps filter market noise and provides crossover signals that can be used for potential trade entries and exits.
To further improve signal quality, the indicator supports multiple Signal Modes, including Early, Balanced, and Strict. Traders can choose between faster entries for aggressive trading or stronger confirmation for higher-probability setups. An optional Liquidity Sweep Confirmation adds an additional layer of validation by requiring recent liquidity sweeps before confirming buy or sell signals.
A built-in Histogram visualizes the strength of momentum between the oscillator and signal line, while the adaptive color gradient highlights changes in buying and selling pressure. Bullish and bearish entry markers are automatically plotted whenever all selected confirmation conditions align.
The integrated Neural Dashboard provides a real-time breakdown of every market component, including its normalized weight, adaptive reliability score, overall market bias, oscillator value, and current trading signal. This allows traders to understand not only what the indicator is signaling, but also why it is producing that signal.
Key Features
Multi-factor neural-style market scoring engine
Adaptive reliability weighting system
Trend, Momentum, Volume, Volatility, and Mean Reversion analysis
Dynamic 0–100 oscillator
Smoothed signal line with crossover detection
Early, Balanced, and Strict signal modes
Optional liquidity sweep confirmation
Momentum histogram with gradient visualization
Automatic BUY and SELL signal generation
Comprehensive real-time Neural Dashboard
Fully customizable inputs, weights, colors, smoothing, and confirmation settings
The Neural Signal Matrix Oscillator is designed for traders who want to combine trend analysis, momentum confirmation, volume behavior, adaptive learning, and market structure into a single intelligent oscillator that continuously adjusts to changing market conditions while delivering cleaner and more reliable trading signals.
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www.tradingview.com インジケーター
Apex Volume Profile and HyperTrend Regressionwww.tradingview.com
Apex Volume Profile and HyperTrend Regression is an advanced trend-following indicator that combines dynamic regression analysis with a curve-aligned volume profile to reveal where the market is trending and where the highest concentration of trading activity has occurred. Unlike traditional horizontal volume profiles, the profile follows the regression path, allowing traders to analyze volume within the context of an evolving trend.
The indicator supports both Linear Regression and HyperTrend Curve modes, making it suitable for trending and curved market structures. It automatically builds a volume profile around the regression channel, identifies the Point of Control (POC), plots Standard Deviation (±1, ±2, ±3 SD) bands, and displays a dynamic channel grid to highlight potential support, resistance, and volatility zones.
Key features include trend-aligned volume profiling, dynamic POC detection, adaptive regression channels, Standard Deviation bands, volume-weighted profile visualization, automatic bullish/bearish trend detection, and a real-time dashboard displaying trend direction, POC price, POC volume, and channel high/low levels.
This indicator is designed for traders who want to combine trend analysis, market structure, and volume distribution into a single professional tool, helping identify high-probability support and resistance zones, trend continuation opportunities, and key liquidity areas with greater precision.
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インジケーター
Schrodinger Zone Probability [JOAT]SCHRÖDINGER ZONE PROBABILITY
The most quantitatively ambitious indicator in the JOAT suite. Detects Fair Value Gaps and Order Blocks the way a serious SMC engine should — and then, before they are touched, treats each one as a superposition zone with two simultaneous probabilities: P_S (the probability it will act as Support when revisited) and P_R (the probability it will act as Resistance). The two probabilities sum to one. The zone exists in a superposition of both states until price actually touches it; at that moment the wavefunction collapses to a single classical state — S or R — driven by the bars-after-touch confirmation logic. Then the script tags the zone with the committed direction and archives the collapse.
Detection — FVGs and OBs done properly
Two independent zone types feed the superposition engine:
Fair Value Gaps — the standard 3-candle imbalance definition, ATR-filtered (minimum gap = configurable × ATR, default 0.30×) so only meaningful gaps qualify. Bull and bear FVGs both detected.
Order Blocks — three methods exposed:
Last Opposite — latest opposite-color candle before displacement.
Extreme Opposite — most extreme (lowest low / highest high) candle in the walk-back window.
Strict Volume — Last Opposite filtered by volume above MA.
Displacement (the move that creates the zone) requires a body of displacement ATR multiple × ATR (default 1.20×). A configurable walk-back window controls how far back to search for the OB origin. Configurable mitigation rule (Wick = any pierce, Close = bar must close beyond).
The headline math — three-factor superposition probability
The collapse probabilities P_S / P_R are computed as a weighted blend of three orthogonal factors:
Distance factor — distance from current price to the zone, decayed exponentially with a configurable half-life in ATR units (default 2.0 ATR). Closer zones have higher commit probability.
Direction factor — which side of the zone current price is on. Above the zone leans the read toward Support collapse; below leans toward Resistance.
Flow factor — EMA-slope alignment over a configurable flow window (default 20 bars). Bullish flow biases toward Support; bearish flow biases toward Resistance.
Each factor's weight is independently tunable. Defaults (0.45 distance / 0.30 direction / 0.25 flow) are the script's institutional calibration. The output is two probabilities that sum to 1.
A zone with P_S ≈ P_R ≈ 0.5 is in pure superposition — the model is genuinely undecided. A zone with P_S = 0.85 / P_R = 0.15 is in a state nearly committed to Support; the wavefunction has already partly collapsed.
Wavefunction collapse — the engine's headline event
When price enters the zone within a configurable touch tolerance (default 0.05 × ATR slack) and holds inside for the configurable holdBars window (default 3 bars), the zone collapses to a single classical state:
Collapse to S — price bounced; the zone acted as Support. Marker prints "(+)→S" at the centroid.
Collapse to R — price was rejected from the other side; the zone acted as Resistance. Marker prints "(+)→R".
A configurable connector line is drawn at the committed level. Collapsed zones are optionally archived (default ON) so the chart shows the full history of how superpositions resolved.
Visual system — superposition rendering
Vertical gradient fill — each zone is rendered as a stack of N sub-boxes (configurable, default 8 slices) with progressive transparency, creating a vertical gradient that visually communicates "high probability of support at the bottom of the zone, high probability of resistance at the top". This is the script's signature visual.
Glow border — configurable glow intensity; becomes thicker when uncertainty is high (P_S ≈ P_R).
Animated superposition pulse — for zones in pure superposition (P ≈ 0.5), transparency oscillates with bar_index to indicate undecided state. Configurable period and amplitude.
Probability labels — P_S / P_R values printed on each active zone.
Zone type tags — FVG_BU, FVG_BE, OB_BU, OB_BE so origin is unambiguous.
Collapse markers — fancy glyphs (+)→S / (+)→R or plain S / R, configurable.
Show-only-superposition mode — hide collapsed and archived zones for a minimalist view.
Right extension — zones project a configurable number of bars to the right.
A locked institutional palette (cyan-teal bull / magenta bear) gives the chart a distinctive quantum-finance identity.
Dashboard
Monospaced table positionable to any of nine corners. Surfaces:
Active superposition zone count and archived count.
Nearest zone with its P_S / P_R values and distance.
Last collapse direction with bars-ago.
Current flow direction.
Detection thresholds and weights in use.
Mitigation rule.
Alerts
Multiple alert conditions:
New Superposition Zone Created (FVG or OB)
Collapse to Support
Collapse to Resistance
Approaching Zone (within collapse-touch tolerance)
High-Uncertainty Zone formed (P_S ≈ P_R ≈ 0.5)
How to read it
Three reads, in order of conviction:
Collapse alert with extreme one-sided probability — e.g. a zone with P_S = 0.85 collapses to S. The model was confidently pointing at one outcome, and the market confirmed it. The highest-conviction confluence read the script produces.
Approaching a zone with sharp probability bias — when P_S or P_R is dominant before touch, the model is committed to one direction. Position toward the dominant side; if the collapse confirms, you are in early.
High-uncertainty zone (P ≈ 0.5) — stand-aside signal. The model is genuinely undecided; trade only with strong external confluence (HTF structure, news flow) or skip the zone entirely.
Suggested settings
Defaults (FVG ATR 0.30×, displacement 1.20×, OB Last-Opposite, 15-bar walk-back, weights 0.45 / 0.30 / 0.25, half-life 2.0 ATR, 3-bar hold) are tuned for 15m–4H on liquid markets. For lower timeframes drop displacement to 1.0× and hold to 2. For HTF raise FVG ATR to 0.50× to keep only large gaps. The weights are calibrated together — change one and the others rebalance the probabilities; experimenting with the weights is a legitimate way to specialise the script to your instrument.
Originality
The implementation — the dual-source zone detector (FVG + OB) with three OB methods, the three-factor probability blend (distance / direction / flow) with independent weights, the exponential ATR-halflife distance decay, the touch-with-hold collapse-confirmation state machine, the vertical-gradient zone render using N stacked sub-boxes, the uncertainty-modulated glow border, the animated superposition pulse for high-uncertainty zones, the archive-on-collapse logic, and the dashboard's probability-aware layout — is JOAT-original. No third-party code reused. The Schrödinger framing (superposition → collapse) is the original conceptual contribution; the math is purpose-built.
Limitations
The "probability" output is a heuristic blend of three factors that historically correlate with which side a zone acts as — it is a ranked confidence, not a true Bayesian posterior. The factor weights are exposed precisely because no single weighting is universally correct. The collapse confirmation requires the holdBars window to elapse, so collapse markers lag the actual touch by that window (intentional — single-bar pierces should not commit a zone). The animated pulse for high-uncertainty zones is purely visual.
-made with passion by jackofalltrades
インジケーター
インジケーター
volume profil multitimeframe**Volume Profile D/W/M — Auction Map**
Volume Profile D/W/M is a visual auction-analysis indicator designed to display confirmed Daily, Weekly, or Monthly volume profiles on the chart. It focuses on value areas, volume concentration, auction structure, and important reaction zones. The script is intended for discretionary market analysis and does not generate automatic buy or sell signals.
---
## Overview
This indicator builds a volume profile from a selected confirmed period:
* Daily
* Weekly
* Monthly
Only one mode is active at a time. The goal is to keep the chart readable while still showing the most important auction levels.
The profile highlights where volume was concentrated during the selected period and displays key levels such as POC, VAH, VAL, HVN, LVN, VWAP, Initial Balance, naked POC levels, imbalance zones, confluence zones, and auction-state information.
---
## Main Features
### Confirmed Volume Profile
The script draws confirmed profiles from closed periods. This makes historical profiles stable and prevents them from constantly changing after the period has closed.
Available profile modes:
* Daily profile
* Weekly profile
* Monthly profile
The current developing profile can also be displayed with the dedicated option, but it should be understood as a live preview and not as a confirmed profile.
---
### POC, VAH and VAL
The script displays the main volume profile levels:
* POC: the price row with the highest volume
* VAH: upper boundary of the value area
* VAL: lower boundary of the value area
These levels are used to read market acceptance, rejection, rotation, and possible return-to-value behavior.
---
### HVN and LVN
The script can highlight:
* HVN: high-volume nodes, where the market accepted price
* LVN: low-volume nodes, where price often moved quickly or found less acceptance
HVN levels may act as areas of balance or reaction. LVN levels may act as rejection zones or acceleration zones depending on context.
---
### Bull / Bear Split and Delta Imbalance Rows
Each profile row can be split into bullish and bearish volume estimates. This helps visualize whether a price area was dominated by bullish or bearish pressure.
The indicator also includes imbalance rows, which highlight areas where one side strongly dominated the row volume.
To avoid label clutter, imbalance labels can be displayed as:
* a single multiplier label
* one label per row
* no label
The multiplier mode is recommended for normal use.
---
### Confluence Zones
The confluence module looks for clusters where several important levels are close to each other.
Examples of levels used in confluence:
* POC
* VAH / VAL
* HVN / LVN
* Period open / close
* Naked POC
* Profile high / low
* Poor high / poor low
* Composite levels
A confluence zone does not predict direction by itself. It simply marks an area where several auction references are grouped together.
---
### Naked POC Tracking
The script can track previous POC levels that have not yet been revisited. These levels are often watched as potential return-to-value or magnet zones.
Naked POC levels include status logic such as:
* Fresh
* Tested
* Respected
* Broken
* Dead
The extension distance can be adjusted so naked POC levels do not appear too far away from the rest of the profile.
---
### VWAP and Initial Balance
The indicator includes optional period VWAP and VWAP bands.
It can also display Initial Balance levels:
* IB High
* IB Low
* IB Mid
* 1x / 2x IB extensions
These tools are useful for reading whether price is rotating inside value, expanding away from balance, or failing an attempted breakout.
---
### Auction Dashboard
The dashboard summarizes useful auction information such as:
* selected mode
* current price location
* auction state
* value relation
* POC migration
* profile shape
* nearest target
* risk zone
* dominant session
* confluence score
* POC, VAH, VAL, VWAP and IB information
The dashboard is only a reading aid. It should not be used as a standalone trading system.
---
## Beginner Tutorial
### Step 1 — Choose the Profile Mode
Start with Daily mode.
Daily mode is usually the easiest to understand because each profile represents one completed trading day.
Once you are comfortable, you can test Weekly and Monthly modes to read the larger market structure.
---
### Step 2 — Read the Main Levels
Start with three levels:
* POC
* VAH
* VAL
A simple way to read them:
* Price above VAH: market is trading above accepted value
* Price below VAL: market is trading below accepted value
* Price around POC: market is rotating near the main accepted price
* Price between VAH and VAL: market is inside value
---
### Step 3 — Look for Reaction Areas
After the basic value area is understood, check:
* HVN zones
* LVN zones
* naked POC levels
* confluence zones
* VWAP
* Initial Balance
Do not use every line as a trade signal. The goal is to identify areas where price may react, pause, reject, or accelerate.
---
### Step 4 — Use the Dashboard
The dashboard helps summarize the profile state.
For example:
* If price is above VAH and POC migration is rising, the market may be accepting higher prices.
* If price rejects above VAH and returns inside value, it may indicate a failed auction.
* If price is near a confluence zone, the area may deserve more attention.
---
## Example Use Cases
### Example 1 — Return to Value
Price trades above VAH, fails to hold, and returns inside the value area.
A trader may watch for a rotation back toward POC.
This is not a direct entry signal. Confirmation should come from price action, market structure, or another method.
---
### Example 2 — POC Magnet
Price moves away from the previous POC but later returns toward it.
A naked POC or composite POC may act as a reference level where traders expect a reaction or pause.
---
### Example 3 — LVN Acceleration
Price approaches an LVN zone.
Because LVN zones represent low acceptance, price may either reject quickly or move through the area with speed.
The direction depends on context, not on the LVN alone.
---
### Example 4 — Weekly Context, Daily Execution
A trader can use Weekly mode to identify larger auction levels, then switch back to a lower chart timeframe to observe how price reacts near those levels.
This helps separate macro context from execution timing.
---
## Recommended Timeframes
The script is not designed for very low timeframes with heavy settings.
Recommended chart timeframes:
* 5 minutes and above for Daily mode
* 15 minutes and above for Weekly mode
* 15 minutes, 30 minutes, or 1 hour for Monthly mode
Using the script on a 1-minute chart is not recommended, especially with Weekly or Monthly mode, developing profile enabled, high profile rows, many historical profiles, or multiple visual modules active.
Very low timeframes may require too many historical bars or too many drawing objects, which can cause TradingView limits to be reached.
---
## Performance Recommendations
For stable use, start with these settings:
* Profiles History: 3
* Profile Rows: 48
* Current Developing Profile: Off
* Imbalance Labels: Multiplier
* Composite Display: Near Profile
* Naked POC extension: short distance
If the chart becomes heavy, reduce:
* profile rows
* history count
* developing profile
* imbalance zones
* VWAP bands
* Initial Balance extensions
* confluence labels
---
## Important Notes
This indicator is an analytical tool, not a trading system.
It does not predict the market and does not provide guaranteed results. All levels should be interpreted with market context, price action, risk management, and the trader’s own strategy.
Volume profile analysis is most useful when combined with structure, trend, volatility, session behavior, and confirmation from price action.
Use the script to build a map of important auction areas, not as a standalone reason to enter or exit a trade.
インジケーター
CVD Multi-Timeframe DashboardCVD Multi-Timeframe Dashboard
═══════════════════════════════════════════
WHAT IT DOES
═══════════════════════════════════════════
Most CVD tools only show you the timeframe you're standing on. This one shows
you the whole stack at once. Stay on your execution chart — 1m, 3m, 5m,
whatever you trade — and read the net buying vs. selling pressure of the 5m,
15m, 1h, 4h, Daily and Weekly in a single on-chart table.
In one glance you know whether the bigger picture is backing your trade or
fighting it.
═══════════════════════════════════════════
WHY IT'S USEFUL
═══════════════════════════════════════════
Price can rise while volume delta quietly turns negative — buyers stepping
back even as the candle stays green. That divergence is an early warning, and
it's far more powerful when you can see it line up (or break down) across
multiple timeframes:
- All rows green → broad, one-sided buying. Trend trades have the wind behind them.
- All rows red → broad selling pressure. Longs are swimming upstream.
- Mixed rows → the timeframes disagree — often a pullback, rotation, or a
turning point forming.
This turns CVD from a single-timeframe reading into a top-down confluence tool.
═══════════════════════════════════════════
HOW IT WORKS
═══════════════════════════════════════════
Volume Delta = volume hitting the offer (buying) minus volume hitting the bid
(selling). The script uses TradingView's ta.requestVolumeDelta() engine, which
scans lower-timeframe data to approximate that split as accurately as the
data allows.
Each row anchors that engine to a different timeframe and reports the NET delta
of that timeframe's CURRENT, developing bar — i.e. how much net buy/sell flow
has built up since that candle opened. As a higher-timeframe bar progresses,
its value accumulates; when a new bar opens, it resets. That's why the rows
genuinely differ from one another instead of repeating the same number.
═══════════════════════════════════════════
READING THE TABLE
═══════════════════════════════════════════
TF → the monitored timeframe
CVD Δ → net volume delta of its current bar (auto-formatted K / M / B)
Bias → BUY (positive) or SELL (negative), colour-coded
═══════════════════════════════════════════
SETTINGS
═══════════════════════════════════════════
- Timeframes to monitor — up to 6 slots, each with its own on/off toggle and
timeframe. Set them equal to or higher than your chart timeframe.
- Lower timeframe — resolution used to approximate up/down volume. Automatic
by default; lower = more precise, higher = more history.
- Style — table position, text size, and your own positive/negative colours.
═══════════════════════════════════════════
ALERTS
═══════════════════════════════════════════
"CVD bias flip" fires the moment any monitored timeframe's delta crosses
between positive and negative — useful for catching a shift in flow without
staring at the screen.
═══════════════════════════════════════════
NOTES & LIMITATIONS
═══════════════════════════════════════════
- Monitor timeframes ≥ your chart timeframe; lower ones aren't meaningful.
- The symbol must provide volume data, or the script will tell you.
- Lower-timeframe scanning approximates buy/sell volume — it isn't true
tick or bid/ask data. Use it as a directional gauge, not an exact figure.
Built on TradingView's open-source CVD logic and the ta.requestVolumeDelta()
function from the TradingView/ta library. Open-source — feedback and forks
welcome. インジケーター
Black Merton Volatility Engine [JOAT]Black Merton Volatility Engine
Introduction
Black Merton Volatility Engine blends multiple realized-volatility estimators with expected-move rails, cone rank, jump pressure, and tail-state classification.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Composite Realized Volatility
Close-to-close, Parkinson, Garman-Klass, Rogers-Satchell, and Yang-Zhang-style estimates contribute to the volatility state.
2. Volatility Cone
Current volatility is ranked against a historical cone to identify squeeze and shock conditions.
3. Expected Move Rails
Annualized volatility is converted into a multi-day expected move around price.
4. Tail and Jump Pressure
Large returns, rail breaches, and volatility divergence contribute to tail and jump states.
expectedMove = close * realizedVol * math.sqrt(days / 252)
Features
Composite realized volatility
Expected-move rails
Squeeze and shock regimes
Gamma pin, tail shock, clean expansion, and jump labels
Movable quant HUD
Input Parameters
Fast, base, and slow vol windows
Vol cone window
Expected move days
Squeeze and shock percentiles
Cooldown and display toggles
How to Use This Script
Use the rails as volatility context. Squeeze, shock, tail, and jump states describe volatility conditions, not a certain direction.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
BMV is original in blending several volatility estimators, cone ranking, jump pressure, and expected-move visualization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
インジケーター
QuantEdge Momentum ML [PRO]🟦 QuantEdge Momentum ML PRO is a k-Nearest Neighbors driven momentum oscillator built on an adaptive machine-learning core. Unlike RSI, Stochastic, or MACD — which apply the same static formula to every asset — QE-ML PRO learns the dual-horizon RSI fingerprints that have historically led to bullish versus bearish outcomes on the exact instrument being traded, then scores the current bar against the N closest historical matches. The result is a non-parametric, self-calibrating oscillator whose decision boundary is shaped by the asset's own behaviour rather than a hard-coded curve.
The indicator integrates nine independent layers — feature engine, training sampler, k-NN predictor, WMA signal line, stdev-adjusted OB/OS bands, filtered signal dots, gradient channel, theme-adaptive dashboard, and a nine-theme palette — all rendered on a single, clean oscillator panel.
🟦 HOW THE CORE ENGINE WORKS
**Dual-Horizon RSI Feature Vector**
Each bar, the Feature Engine computes two RSI values at different lookback windows and smooths both through a shared trend-length WMA:
- `rsiFast = WMA(RSI(close, FastPeriod), TrendLength)` — reactive short-term momentum
- `rsiSlow = WMA(RSI(close, SlowPeriod), TrendLength)` — structural mid-term momentum
The pair `(rsiSlow, rsiFast)` is a 2-dimensional point in RSI feature space. Every training sample stores one such point along with a ±1 label that records whether price rose or fell since the previous sample. Over time the dataset accumulates a cloud of labelled points that maps which RSI states historically preceded up-moves versus down-moves on this exact asset.
**Training Sampler — Multi-Trigger Collector**
Three collection modes decide when to append a new labelled sample:
| Mode | Trigger | Use Case |
|---|---|---|
| **MA Crossover** | Fast WMA crosses Slow WMA | Clean, sparse samples — classic single-trigger behaviour |
| **Periodic** | Every N bars (user-set) | Fills dataset fast on new / low-history charts |
| **Hybrid** | MA crossover **OR** every N bars | Richest training set — recommended for fresh assets |
Sampling is gated by `barstate.isconfirmed` so the dataset never absorbs unconfirmed values from a flickering live bar.
**k-NN Predictor with Adaptive k**
On every bar, the predictor computes Euclidean distance in the 2D RSI feature space between the live `(rsiSlow, rsiFast)` point and every historical sample:
```
d = sqrt((rsiSlow_now - rsiSlow_hist)² + (rsiFast_now - rsiFast_hist)²)
```
The K closest historical points vote by summing their ±1 labels. The effective K is resolved adaptively using the classical statistical heuristic:
```
kEff = max(3, min(kMax, floor(sqrt(N))))
```
This means early bars — when only a handful of samples exist — use a small K, and the value stabilises as the dataset fills. On a fresh chart you never get a noisy prediction from an undersized neighborhood, and on a mature dataset K automatically scales up for smoother output.
**Bias Correction — Label-Mean Recentering**
Raw k-NN output is biased whenever the label distribution is skewed. On a trending asset, Periodic sampling fills the dataset with mostly +1 (or mostly −1) labels, pushing every prediction off zero. QE-ML PRO subtracts the expected value from the raw sum:
```
prediction = neighborLabelSum − (kEff × meanLabelAcrossDataset)
```
This keeps the mid-level visually centred at zero regardless of how trending the underlying asset has been. The correction is applied on every bar and is what makes the oscillator read cleanly on both sideways and strongly trending markets.
**Minimum Sample Gate**
Until the dataset has reached the user-defined Minimum Training Samples threshold, the predictor outputs exactly zero. This prevents unreliable readings during the warm-up phase on fresh charts.
**FIFO Rotation**
The dataset is hard-capped at Max Dataset Size. Once the cap is reached, the oldest sample is discarded on every new insertion — classical rolling window memory that keeps the k-NN scan bounded and the indicator fast on long histories.
🟦 PREDICTION LINE — FIVE VISUAL STYLES
All five styles are line-based. Only the visual effect differs — the underlying k-NN math is identical across styles.
| Style | Character |
|---|---|
| **Stratum** | Thick adaptive line with zone-based opacity: solid in extreme zones, semi-transparent in the mid zone. Layered intensity aesthetic — default |
| **Neon** | Bright core line with an outer glow halo. Cyberpunk luminous effect, best on dark backgrounds |
| **Resonance** | LRI-style gradient line that fades near the midline and brightens toward the rolling extremes |
| **Pulse** | Adaptive bull/bear color (above midline = bull, below = bear) plus the WMA signal line. The QE-ML PRO classic look |
| **Mono** | Single flat theme-bull line, no gradient, no adaptive coloring. Minimalist single-color silhouette |
🟦 SIGNAL LINE
A WMA of the raw prediction output, used as a crossover trigger line in the MACD convention. Crossovers between the prediction and signal line mark momentum regime changes.
**Two Visual Styles**
| Style | Rendering |
|---|---|
| **Neon** | Bright core line wrapped in a wider semi-transparent glow halo — cyberpunk aesthetic |
| **Flat** | Plain single-color line, no halo, no gradient — minimalist clean look |
🟦 SIGNAL DOTS — FILTERED CROSSOVER MARKERS
A two-layer neon cross-dot renderer fires on every Prediction × Signal crossover that survives the active filter mode. Four progressive filters decide which raw crosses reach the chart:
| Filter Mode | Behaviour | Signal Count |
|---|---|---|
| **All Crosses** | Every cross becomes a dot | Highest — noisy on choppy assets |
| **Zone Only** | Only crosses inside an OB or OS strip | Mean-reversion triggers — strongest reversal setups |
| **Mid Aligned** | Bull dots only above mid, bear dots only below | Trend-following — keeps you on regime side |
| **Strict** | Zone Only + Mid Aligned + extra strength multiplier on mid-zone crosses | Fewest signals, highest conviction — default |
Two additional gates filter out whipsaws:
- **Cooldown (bars)** — minimum spacing between consecutive dots, prevents cluster spam in ranges
- **Min Strength** — minimum `|prediction − signal|` separation at the moment of the cross, drops razor-thin crossovers that close back on themselves
Each dot is a two-layer plot: an outer glow halo with user-adjustable size and opacity, and a bright solid core on top — independently sized and opacity-controlled so users can dial in the exact visual weight they want.
The dot is placed at the actual cross point: bull dots at `min(prediction, signalLine)`, bear dots at `max(prediction, signalLine)`.
🟦 DYNAMIC BANDS — STDEV-ADJUSTED OB / OS ZONES
QE-ML PRO does not use fixed 80 / 20 overbought / oversold levels. Instead, the bands adapt to the actual historical range of the prediction output:
- **Channel Extremes** — rolling highest / lowest of the prediction over a user-configurable lookback
- **Stdev Band** — EMA of rolling standard deviation of the prediction, multiplied by the user's stdev length
- **OB Level** = `rangeHi − stdevBand` (inner boundary of the overbought strip)
- **OS Level** = `rangeLo + stdevBand` (inner boundary of the oversold strip)
The result is a pair of mean-reversion zones that tighten during quiet markets and widen during volatile ones — no manual recalibration needed across assets.
The strips are rendered as gradient fills anchored on the live prediction plot, so they only appear visually while the prediction is actually inside the zone.
🟦 CHANNEL GRADIENT
Two symmetric gradient fills bracket the mid line. The upper fill stretches from `midValue` to `rangeHi`, the lower fill from `midValue` to `rangeLo`. Opacity fades from full intensity at the extremes to fully transparent at the midline — a visual range meter showing how close the prediction is sitting to its historical boundaries.
Colors are pulled from the active Theme. A single opacity slider controls the gradient intensity.
🟦 DASHBOARD — LIVE DATA PANEL
A compact 2-column × 7-row monospace panel drawn on the last bar only (zero historical overhead). Every field updates in real time on the live bar.
| Row | Left | Right |
|---|---|---|
| Header | QE-ML PRO | Regime (▲ BULL / ▼ BEAR / ■ NEUTRAL) |
| Row 1 | Prediction | Raw value + trend arrow vs previous bar |
| Row 2 | Signal | WMA trigger line value |
| Row 3 | Strength | 10-block gauge of `|prediction − signal|` normalised against rolling channel |
| Row 4 | Zone | OB / MID / OS tag |
| Row 5 | Dataset | Sample count / effective k |
| Row 6 | Mode | Active Learning Mode (MA Cross / Periodic / Hybrid) |
**Theme-Aware Auto-Invert**
The panel background scaffolds auto-switch:
- **Tropic / Amber / Pastel / Cyber / Gold / Electric / Candy** → dark panel with bright theme accent text
- **Midnight / Graphite** → light panel with dark theme accent text
This guarantees legibility on every theme without breaking the theme's color identity — because Midnight and Graphite use deep dark bull tones that would drown against a black panel.
**Direction via Glyphs, Not Color**
Both columns share the same full-strength theme tone. Regime direction is conveyed by `▲ ▼ ■` glyphs rather than color shifts, which keeps the panel reading cleanly even on the most minimal themes.
🟦 NINE COLOR THEMES
One theme selector drives every colored component — Prediction line, Signal line, Channel fill, OB / OS strips, Mid-level line, Signal Dots, and Dashboard panel. No per-color manual inputs.
| Theme | Character | Bull | Bear |
|---|---|---|---|
| **Tropic** | Cyan steel + deep orange — electric contrast (default) | Cyan | Deep Orange |
| **Amber** | Warm amber + indigo blue — fire tones | Amber | Red |
| **Pastel** | Sky blue + soft lavender — cool arctic glow | Sky Blue | Lavender |
| **Cyber** | Neon lime + hot crimson — cyber terminal | Neon Green | Crimson |
| **Gold** | Bright gold + scarlet — solar warmth | Yellow Gold | Red |
| **Electric** | Electric aqua + magenta — high-voltage neon | Aqua | Magenta |
| **Candy** | Neon green + hot pink — dark energy pop | Mint Green | Hot Pink |
| **Midnight** | Deep navy + dark crimson — dark depth (auto light dashboard) | Navy Blue | Dark Red |
| **Graphite** | Near-black + silver grey — monochrome minimal (auto light dashboard) | Near Black | Grey |
🟦 ALERT SYSTEM — TEN CONDITIONS
Every alert is gated by its matching "Show X" visibility toggle — if a component is hidden from the chart, its alerts are automatically suppressed. This eliminates the mismatch between visual signals and alert signals that plagues many indicators.
| Alert | Condition | Gated By |
|---|---|---|
| Crossover OB | Prediction crosses above the overbought boundary | Show OB/OS Fill |
| Crossunder OB | Prediction crosses back down through OB | Show OB/OS Fill |
| Crossover OS | Prediction crosses up through oversold boundary | Show OB/OS Fill |
| Crossunder OS | Prediction crosses below the oversold boundary | Show OB/OS Fill |
| Crossover Mid | Prediction crosses above the mid line — bullish regime flip | Show Mid Level |
| Crossunder Mid | Prediction crosses below the mid line — bearish regime flip | Show Mid Level |
| Crossover Signal | Prediction crosses above its WMA signal line (MACD bullish) | Show Signal Line |
| Crossunder Signal | Prediction crosses below its WMA signal line (MACD bearish) | Show Signal Line |
| Bull Signal Dot | A filtered Bull Signal Dot is plotted (uses Filter Mode + Cooldown + Min Strength) | Show Signal Dots |
| Bear Signal Dot | A filtered Bear Signal Dot is plotted (uses Filter Mode + Cooldown + Min Strength) | Show Signal Dots |
🟦 SETTINGS REFERENCE
**Visual**
- Theme — nine cohesive palettes. Default: Tropic
**Machine Learning**
- Neighbors (k) — upper bound on neighbors used by the predictor. Default: 100
- Adaptive k — scales k with dataset size using the `floor(sqrt(N))` heuristic. Default: ON
- Learning Mode — MA Crossover / Periodic / Hybrid. Default: MA Crossover
- Sample Every (bars) — bar interval for the Periodic / Hybrid trigger. Default: 5
- Minimum Training Samples — warm-up gate, predictor outputs zero until reached. Default: 30
- Max Dataset Size — hard FIFO cap. Default: 500 (safe on all timeframes)
**Feature Engine**
- Trend Length — WMA smoothing applied to both RSI features. Default: 20
- RSI Fast Period — first feature dimension. Default: 5
- RSI Slow Period — second feature dimension. Default: 20
- MA Fast Period — fast WMA for the crossover training trigger. Default: 5
- MA Slow Period — slow WMA for the crossover training trigger. Default: 20
**Prediction Line**
- Show Prediction Line — master toggle. Default: ON
- Prediction Style — Stratum / Neon / Resonance / Pulse / Mono. Default: Stratum
- Prediction Width — 1 to 5. Default: 2
**Signal Line**
- Show Signal Line — toggle. Default: ON
- Signal Style — Neon / Flat. Default: Neon
- Signal Period — WMA length of the signal line. Default: 20
- Signal Width — 1 to 5. Default: 1
**Signal Dots**
- Show Signal Dots — toggle. Default: ON
- Filter Mode — All Crosses / Zone Only / Mid Aligned / Strict. Default: Strict
- Cooldown (bars) — minimum spacing between dots. Default: 5
- Min Strength — minimum `|prediction − signal|` at the cross. Default: 0.5
- Core Dot Size — 1 to 8. Default: 3
- Core Dot Opacity — 0 to 100. Default: 100
- Glow Dot Size — 1 to 12. Default: 8
- Glow Dot Opacity — 0 to 100. Default: 30
**Channel Fill**
- Show Channel Fill — toggle. Default: ON
- Channel Opacity — 0 to 100. Default: 25
- Channel Lookback — rolling highest / lowest window. Default: 500
**OB / OS Fill**
- Show OB/OS Fill — toggle. Default: ON
- Zone Stdev Length — stdev window that offsets the OB / OS boundaries inward. Default: 20
**Mid Level**
- Show Mid Level — toggle. Default: ON
- Mid Level Value — Y-value of the reference line. Default: 0
- Mid Level Style — Solid / Dashed / Dotted. Default: Dashed
**Dashboard**
- Show Dashboard — toggle. Default: ON
- Panel Position — six slots (Top/Middle/Bottom × Right/Left). Default: Middle Right
- Panel Text Size — Tiny / Small / Normal / Large. Default: Small
**Alerts**
- Ten opt-in toggles, one per alert condition. All default: ON
🟦 TRADER PRESETS — SETTINGS BY STYLE
QE-ML PRO is volatility-agnostic thanks to the adaptive bands and bias correction, but the reactivity of the predictor scales directly with the feature and sampler parameters. The four presets below are tested starting points you can drop straight into the settings panel — adjust by ±20% to taste.
---
** SCALPER — 1m / 3m / 5m**
High-frequency entries, tight stops, many signals per session. Priority is reaction speed — you want the predictor to flip states within a handful of bars of an actual move.
| Setting | Value |
|---|---|
| Trend Length | 10 |
| RSI Fast Period | 3 |
| RSI Slow Period | 14 |
| MA Fast Period | 3 |
| MA Slow Period | 10 |
| Signal Period | 8 |
| Neighbors (k) | 40 |
| Adaptive k | ON |
| Learning Mode | **Hybrid** |
| Sample Every | 2 |
| Minimum Training Samples | 20 |
| Max Dataset Size | **300** (keeps 1m charts fast) |
| Filter Mode | **All Crosses** or Zone Only |
| Cooldown | 2 |
| Min Strength | 0.3 |
| Channel Lookback | 200 |
| Zone Stdev Length | 10 |
| Prediction Style | Neon or Stratum |
**Why:** Low smoothing (Trend=10) + short RSI pair (3/14) keeps the features razor-sharp. Hybrid learning means you never wait for an MA crossover during quiet 1m sessions. Max Dataset capped at 300 protects you from the TradingView per-bar calculation limit on long 1m histories.
---
** DAY TRADER — 15m / 30m / 1H**
Balanced reactivity and conviction — the default profile. You want clean crosses without noise spam, and signals that survive the open / close volatility spikes.
| Setting | Value |
|---|---|
| Trend Length | 20 (default) |
| RSI Fast Period | 5 (default) |
| RSI Slow Period | 20 (default) |
| MA Fast Period | 5 (default) |
| MA Slow Period | 20 (default) |
| Signal Period | 20 (default) |
| Neighbors (k) | 100 (default) |
| Adaptive k | ON |
| Learning Mode | **MA Crossover** (default) |
| Minimum Training Samples | 30 (default) |
| Max Dataset Size | 500 (default) |
| Filter Mode | **Strict** (default) |
| Cooldown | 5 (default) |
| Min Strength | 0.5 (default) |
| Channel Lookback | 500 (default) |
| Zone Stdev Length | 20 (default) |
| Prediction Style | Stratum (default) |
**Why:** Every default value was tuned for this range. Strict filter + 5-bar cooldown keeps the dot count honest on a 30m chart. MA Crossover sampling gives you clean sparse data since 15m+ charts already have enough crossover events.
---
** SWING TRADER — 4H / 1D**
Lower signal frequency, higher conviction per signal. You're holding for days or weeks — every dot needs to mean something.
| Setting | Value |
|---|---|
| Trend Length | 30 |
| RSI Fast Period | 7 |
| RSI Slow Period | 30 |
| MA Fast Period | 7 |
| MA Slow Period | 30 |
| Signal Period | 30 |
| Neighbors (k) | 150 |
| Adaptive k | ON |
| Learning Mode | MA Crossover |
| Minimum Training Samples | 50 |
| Max Dataset Size | 800 |
| Filter Mode | **Strict** |
| Cooldown | 10 |
| Min Strength | 0.8 |
| Channel Lookback | 800 |
| Zone Stdev Length | 30 |
| Prediction Style | Stratum or Mono |
**Why:** Longer feature periods mean the predictor only moves on genuine structural shifts. Larger k (150) + bigger dataset (800) gives the k-NN vote a wider base so outliers don't flip the sign. Cooldown of 10 bars on a 4H chart = 40 hours minimum between dots — exactly what a swing trader wants.
---
** POSITION / LONG-TERM — 1D / 1W / 1M**
Macro regime detection. You're looking for the handful of generational setups per year — noise is the enemy.
| Setting | Value |
|---|---|
| Trend Length | 50 |
| RSI Fast Period | 10 |
| RSI Slow Period | 40 |
| MA Fast Period | 10 |
| MA Slow Period | 40 |
| Signal Period | 40 |
| Neighbors (k) | 200 |
| Adaptive k | ON |
| Learning Mode | **Hybrid** |
| Sample Every | 3 |
| Minimum Training Samples | 40 |
| Max Dataset Size | 1000 |
| Filter Mode | **Strict** |
| Cooldown | 15 |
| Min Strength | 1.0 |
| Channel Lookback | 1000 |
| Zone Stdev Length | 40 |
| Prediction Style | Mono or Pulse |
**Why:** Weekly and monthly charts have few crossover events per year — without Hybrid mode the dataset starves. Sample Every = 3 on a weekly chart means one sample every 3 weeks, which is plenty of structural density. Min Strength 1.0 filters out every shallow cross — you only see dots on generational momentum inflections.
---
**Tuning Tip**
If the predictor feels **too reactive** → increase Trend Length and Signal Period by 25%, raise Cooldown.
If the predictor feels **too sluggish** → switch Learning Mode to Hybrid, decrease Min Samples, lower Trend Length.
If the dashboard shows **Dataset N is stuck low** → switch Learning Mode from MA Crossover to Hybrid — crossover events are too rare on your current settings.
If you see **runtime / timeout errors** on long histories → drop Max Dataset Size to 300 and Channel Lookback to 300.
🟦 COMPATIBILITY
Works on all asset classes and all timeframes in TradingView Pine Script v6.
- **Crypto** — Spot, futures, perpetual contracts
- **Forex** — All pairs
- **Equities** — Stocks, ETFs, indices
- **Commodities** — Metals, energy, agriculture
- **Timeframes** — 1m through Monthly
The k-NN engine learns each asset's own RSI fingerprint distribution, and the stdev-adjusted bands auto-scale to the volatility of that distribution, so the indicator is truly self-calibrating across assets and timeframes — no manual recalibration required.
🟦 TECHNICAL NOTES
- Pine Script v6
- No repainting — training samples are gated by `barstate.isconfirmed` so the dataset never absorbs unconfirmed live-bar values
- Dataset is hard-capped via FIFO rotation; no unbounded memory growth
- Dashboard renders only on `barstate.islast` — zero historical overhead
- All drawing objects are stateless plots (no label / box / line object pools), so `max_*_count` limits cannot be exceeded
- k-NN distance pass is O(N), sort is O(N log N), both bounded by Max Dataset Size
- Default Max Dataset Size of 500 is tuned to stay within TradingView's per-bar calculation budget on histories up to ~50,000 bars
- Bias correction uses a single extra accumulator pass during the distance sweep — no performance penalty
🟦 DISCLAIMER
This indicator is provided for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. The k-NN engine learns from historical patterns, but markets do not guarantee that historical patterns will repeat. Always conduct your own analysis and apply proper risk management. インジケーター
Delta Absorption Scanner[MarkitTick]💡 This advanced analytical tool is engineered to bridge the gap between price action and order flow dynamics by identifying critical moments where market participants encounter significant liquidity barriers. In the modern trading landscape, volume alone is often insufficient to determine market direction. The Delta Absorption Scanner provides a sophisticated lens through which traders can observe the interaction between aggressive market orders and passive limit orders, specifically highlighting "Absorption" events. These events occur when high-volume "Effort" fails to produce a proportional price "Result," signaling a potential exhaustion of the current trend or a hidden accumulation/distribution phase. By synthesizing volume delta, candle spread, and multi-timeframe context into a unified interface, this script empowers traders to make decisions based on the structural integrity of the market rather than superficial price movements.
✨ Originality and Utility
The primary utility of this script lies in its multi-layered approach to market analysis, moving beyond simple oscillators or trend-following moving averages.
Unlike standard volume indicators that merely report total activity, this scanner differentiates between buying and selling pressure by calculating candle-based delta, allowing for a more granular view of market intent.
The script introduces a unique "Scanner" architecture that monitors four distinct high-timeframe (HTF) perspectives simultaneously. This provides an institutional-grade view of the trend without the need to constantly switch chart intervals.
It incorporates a proprietary "Absorption" detection logic that correlates delta percentage with the physical spread of the candle. This identifies "hidden" strength or weakness that is often invisible to the naked eye.
The inclusion of Fair Value Gap (FVG) and Swing High/Low detection within the dashboard creates a comprehensive "Confluence Engine," ensuring that short-term delta signals are validated by higher-level market structures.
By utilizing non-repainting multi-timeframe logic (security calls with index offsets), the indicator maintains the highest standards of data integrity, making it suitable for both discretionary trading and systemic strategy development.
🔬 Methodology and Concepts
The core logic begins with the calculation of "Candle Delta," which determines the dominant force within a single bar based on its polarity. If a candle closes above its open, the entire volume is attributed to positive delta; if it closes below, it is negative.
The indicator then calculates the "Spread," defined as the absolute distance between the high and low of the bar. This metric is critical for the "Effort vs. Result" analysis.
Absorption is mathematically flagged when a candle exceeds the user-defined "Minimum Delta %" threshold but fails to generate significant directional movement, or when the spread is disproportionately small compared to the volume injected.
The Support (S3) and Resistance (R3) levels are derived from the most recent significant high-volume or high-delta bars, creating dynamic zones that reflect where institutional liquidity was last engaged.
Multi-Timeframe Integration: The script utilizes the request.security() function with a bar offset. This ensures that the data displayed from higher timeframes is "confirmed" and prevents the visual bias known as repainting.
Trend determination on the dashboard is calculated using a proprietary relationship between the current price and the 14-period smoothed high/low averages, providing a stable "Trend Bias" for each monitored timeframe.
● Main Feature Components
• Volume Delta labels
The script places dynamic labels above or below candles that exhibit significant delta. These labels display the Delta percentage, helping traders identify where "Climax" volume is occurring.
• Spread Analysis (S)
Next to the Delta % is a value representing the "Spread." This allows for an immediate visual comparison: High Delta with Low Spread suggests passive absorption (reversal), while High Delta with High Spread suggests aggressive momentum (continuation).
• Multi-Timeframe (HTF) Dashboard
A sophisticated table displayed on the chart that aggregates data from up to four higher timeframes. This dashboard is the "brain" of the scanner, providing a bird's-eye view of the market's broader health.
🎨 Visual Guide
Positive Delta Labels: Displayed as green labels with white text. These signify bars where buying volume was dominant.
Negative Delta Labels: Displayed as red labels with white text. These signify bars where selling volume was dominant.
Neutral/Spread Labels: Displayed in a dark neutral color to represent bars where the spread is being analyzed without a significant delta bias.
Dashboard - Trend Column: Displays "UP" in green for bullish regimes and "DN" in red for bearish regimes for each of the four HTF settings.
Dashboard - S3/R3 Column: Displays the price of the nearest significant support or resistance level identified by the script.
Dashboard - Distance % Column: A dynamic calculation showing how far the current price is from the S3/R3 levels. Green indicates distance from support, while red indicates distance from resistance.
Dashboard - FVG Column: Displays "+FVG" in green if a bullish Fair Value Gap exists on that timeframe, or "-FVG" in red if a bearish gap is present.
Dashboard - Swing Column: Identifies if the current price is near a local "Top" or "Bottom" based on pivot logic.
📖 How to Use
Step 1: Identify "Effort" on the Chart. Look for a large Delta % label (e.g., >20%) appearing at a local high or low.
Step 2: Analyze the "Result." If the Delta is high (Green/Positive) but the candle spread (S) is small and price fails to move higher, this is a classic Bearish Absorption signal. Limit sellers are "absorbing" the market buyers.
Step 3: Consult the Dashboard. Check if the HTF trends are in alignment. For a short trade based on Bearish Absorption, you ideally want to see "DN" trends on higher timeframes and the presence of a "-FVG."
Step 4: Proximity to S/R. Use the "Dist %" column to ensure you are not selling directly into a higher-timeframe support (S3) or buying directly into resistance (R3).
Step 5: Confluence. The highest probability trades occur when a Delta climax appears at a dashboard-confirmed Swing Top/Bottom in the direction of the HTF trend.
⚙️ Inputs and Settings
Positive/Negative Delta Color: Customizes the aesthetic of the bull/bear labels to match your chart theme.
Max Labels on Chart: Controls the lookback period for visual labels to maintain chart performance and reduce clutter.
Minimum Delta % to Show: A sensitivity filter. Higher values (e.g., 50%) will only show the most extreme volume events, while lower values (e.g., 10%) provide more frequent signals.
Show Spread (S): Toggles the visibility of the candle spread value within the labels.
HTF 1-4 Settings: Allows the user to define which timeframes the dashboard should track (e.g., 1H, 4H, Daily, Weekly).
Dashboard Position: Permits the user to move the table to different corners of the chart for better visibility.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
• The Law of Effort vs. Result
Based on the principles established by Richard Wyckoff, this indicator quantifies "Effort" as Volume Delta and "Result" as Price Spread. In a balanced market, increased effort should lead to an equivalent result. When these two diverge (Anomalies), it suggests a change in market character.
• Auction Market Theory (AMT)
The indicator utilizes AMT principles by identifying areas of "High Volume Nodes" (represented by S3/R3) where the market has found value or met significant opposition. The "Distance %" feature measures the market's deviation from these nodes, which often acts as a mean-reversion catalyst.
• Order Flow Imbalance
While traditional indicators use price as a lagging derivative, the Delta Absorption Scanner attempts to lead price by observing the imbalance between aggressive market participants. By isolating the delta within each bar, the script identifies where one side of the "Auction" is becoming exhausted.
• Statistical Significance of Spread
The inclusion of spread analysis is rooted in statistical volatility measurements. A narrow spread during high volume indicates a high density of limit orders (Liquidity), which is a precursor to price reversals or significant breakouts once the liquidity is exhausted.
• Multi-Timeframe Structuralism
The scanner's architecture is based on the theory that lower-timeframe "noise" is resolved by higher-timeframe "structure." By mapping FVGs and Swings across four dimensions, the script applies a fractal analysis to the current bar's delta events.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. インジケーター
インジケーター
Relative Volume Context [Alturoi]Relative Volume Context evaluates whether current volume is unusual relative to its historical time-of-day or calendar context.
Instead of comparing volume to a global average, the script estimates expected volume for the current time bucket (e.g., minute of hour, hour of day, day of week, month). This creates a like-for-like comparison against historical behavior occurring at the same structural moment.
All outputs are derived from a single statistical volume model.
How It Works
For each selected time bucket, the script maintains:
Sample size (N)
Mean volume (expected value)
Variance (used for Z-Score)
When a new bar forms, current volume is compared to the historical statistics of its bucket.
This produces:
Expected Volume – Typical volume for this time bucket
Difference – Actual minus expected
Surprise (%) – Relative deviation from expected
Z-Score – Standardized deviation from the historical distribution
Sample Size & Confidence – Transparency into statistical reliability
Optional session-aware bucketing allows intraday traders to model volume relative to session structure.
Why Time Conditioning Matters
Volume follows structural patterns (open, midday, close, weekday effects).
Comparing current volume to a global average ignores these effects.
By conditioning volume on time, the indicator helps distinguish:
Routine activity
Statistically elevated participation
Structurally quiet periods
How to Use
This indicator is designed as a contextual tool, not a trading signal.
It may assist in:
Evaluating whether breakouts occur with elevated participation
Distinguishing routine session volume from abnormal spikes
Assessing whether price movement is supported by unusual activity
Interpret readings alongside price structure and risk management.
Disclaimer
This script is provided for educational and informational purposes only and does not constitute financial advice. Trading involves risk, and past behavior does not guarantee future results. インジケーター
インジケーター
Multi-Distribution Volume Profile (Zeiierman)█ Overview
Multi-Distribution Volume Profile (Zeiierman) is a flexible, structure-first volume profile tool that lets you reshape how volume is distributed across price, from classic uniform profiles to advanced statistical curves like Gaussian, Lognormal, Student-t, and more.
Instead of forcing every market into a single "one-size-fits-all" profile, this tool lets you model how volume is likely concentrated inside each bar (body vs wicks, midpoint, tails, center bias, right-skew, heavy tails, etc.) and then stacks that behavior across a whole lookback window to build a rich, multi-distribution map of traded activity.
On top of that, it overlays a dynamic Center Band (value area) and a fade/gradient model that can color each price row by volume, hits, recency, volatility, reversals, or even liquidity voids, turning a plain profile into a multi-dimensional context map.
Highlights
Choose from multiple Profile Build Modes , including uniform, body-only, wick-only, midpoint/close/open, center-weighted, and a suite of probability-style distributions (Gaussian, Lognormal, Weibull, Student-t, etc.)
Flexible anchor layout: draw the profile on Right/Left (horizontal) or Bottom/Top (vertical) to fit any chart layout
Value Area / Center Band computed from volume quantiles around the POC.
Gradient-based Fade Metrics: volume, price hits, freshness (time decay), volatility impact, dwell time, reversal density, compression, and liquidity voids
Separate bullish vs bearish volume at each price row for directional structure insights
█ How It Works
⚪ Profile Construction
The script scans a user-defined Bars Included window and finds the full high–low span of that zone. It then divides this range into a user-controlled number of Price Levels (rows).
For each historical bar within the window:
It measures the candle’s price range, body, and wicks.
It assigns volume to rows according to the selected Profile Build Mode, for example:
* Range Uniform – volume spread evenly across the full high–low range.
* Range Body Only / Range Wick Only – concentrate volume inside the body or wicks only.
* Midpoint / Close / Open Only – allocate volume entirely into one price row (pinpoint modeling).
HL2 / Body Center Weighted – center weights around the middle of the range/body.
Recent-Weighted Volume – amplify newer bars using exponential time decay.
Volume Squared (Hard) – aggressively boost bars with large volume.
Up Bars Only / Down Bars Only – filter volume to only bullish or bearish bars.
For more advanced shapes, the script uses continuous distributions across the bar’s span:
Linear, Triangular, Exponential to High
Cosine Centered, PERT
Gaussian, Lognormal, Cauchy, Laplace
Pareto, Weibull, Logistic, Gumbel
Gamma, Beta, Chi-Square, Student-t, F-Shape
Each distribution produces a weight for each row within the bar’s range, normalized so the total volume remains consistent, but the shape of where that volume lands changes.
⚪ POC & Center Band (Value Area)
Once all rows are accumulated:
The row with the highest total volume becomes the Point of Control (POC)
The script computes cumulative volume and finds the band that wraps a user-defined Center of Profile % (e.g., 68%) around the center of distribution.
This range is displayed as a central band, often treated like a value area where price has spent the most “effort” trading.
⚪ Gradient Fade Engine
Each row also gets a fade metric, chosen in Fade Metric:
Volume – opacity based on relative volume.
Price Hits – how frequently that row was touched.
Blended (Vol+Hits) – average of volume & hits.
Freshness – emphasizes recent activity, controlled by Decay.
Volatility Impact – rows that saw larger ranges contribute more.
Dwell Time – where price “camped” the longest.
Reversal Density – where direction changes cluster.
Compression – tight-range compression zones.
Liquidity Void – inverse of volume (thin liquidity zones).
When Apply Gradient is enabled, the row’s bullish/bearish colors are tinted from faint to strong based on this chosen metric, effectively turning the profile into a heatmap of your chosen structural property.
█ How to Use
⚪ Explore Different Distribution Assumptions
Switch between multiple Profile Build Modes to see how your assumptions about intrabar volume affect structure:
Use Range Uniform for classical profile reading.
Deploy Gaussian, Logistic, or Cosine shapes to emphasize central clustering.
Try Pareto, Lognormal, or F-Shape to focus on tail / extremal activity.
Use Recent-Weighted Volume to prioritize the most recent structural behavior.
This is especially useful for traders who want to test how different modeling assumptions change perceived value areas and levels of interest.
⚪ Identify Value, Acceptance & Rejection Zones
Use the POC and Center of Profile (%) band to distinguish:
High-acceptance zones – wide central band, thick rows, strong gradient → fair value areas
Rejection zones & tails – thin extremes, low dwell time, high volatility or reversal density
These regions can be used as:
Targets and origin zones for mean reversion
Context for breakout validation (leaving value)
Bias reference for intraday rotations or swing rotations
⚪ Read Directional Structure Within the Profile
Because each row is split into bullish vs bearish contributions, you can visually read:
Where buyers dominated a price region (large bullish slice)
Where sellers absorbed or defended (large bearish slice)
Combining this with Fade Metrics like Reversal Density, Dwell Time, or Freshness turns the profile into a structural order-flow map, without needing raw tick-by-tick volume data.
⚪ Use Fade Metrics for Contextual Heatmaps
Each Fade Metric can be used for a different analytical lens:
Volume / Blended – emphasize where volume and activity are concentrated.
Freshness – highlight the most recently active zones that still matter.
Volatility Impact & Compression – spot areas of explosive moves vs coiled ranges.
Reversal Density – locate micro turning points and battle zones.
Liquidity Void – visually pop out thin regions that may act as speedways or magnets.
█ Settings
Profile Build Mode – Selects how each bar’s volume is distributed across its price range (uniform, body/wick, midpoint/close/open, center-weighted, or statistical distribution families).
Bars Included – Number of bars used to build the profile from the current bar backward.
Price Levels – Vertical resolution of the profile: more levels = smoother but heavier.
Anchor Side – Where the profile is drawn on the chart: Right, Left, Bottom, or Top.
Offset (bars) – Horizontal offset from the last bar to the profile when using Right/Left modes.
Apply Gradient – Toggles the fade/heatmap coloring based on the selected metric.
Fade Metric – Chooses the property driving row opacity (Volume, Hits, Freshness, Volatility Impact, Dwell Time, Reversal Density, Compression, Liquidity Void).
Decay – Time-decay factor for Freshness (values close to 1 keep older activity relevant for longer).
Profile Thickness – Relative thickness of the profile along the time axis, as a % of the lookback window.
Center of Profile (%) – Volume percentage used to define the central band (value area) around the POC.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
インジケーター
PoC Migration Map [BackQuant]PoC Migration Map
A volume structure tool that builds a side volume profile, extracts rolling Points of Control (PoCs), and maps how those PoCs migrate through time so you can see where value is moving, how volume clusters shift, and how that aligns with trend regime.
What this is
This indicator combines a classic volume profile with a segmented PoC trail. It looks back over a configurable window, splits that window into bins by price, and shows you where volume has concentrated. On top of that, it slices the lookback into fixed bar segments, finds the local PoC in each segment, and plots those PoCs as a chain of nodes across the chart.
The result is a "migration map" of value:
A side volume profile that shows how volume is distributed over the recent price range.
A sequence of PoC nodes that show where local value has been accepted over time.
Lines that connect those PoCs to reveal the path of value migration.
Optional trend coloring based on EMA 12 and EMA 21, so each PoC also encodes trend regime.
Used together, this gives you a structural read on where the market has actually traded size, how "value" is moving, and whether that movement is aligned or fighting the current trend.
Core components
Lookback volume profile - a side histogram built from all closes and volumes in the chosen lookback window.
Segmented PoC trail - rolling PoCs computed over fixed bar segments, plotted as nodes in time.
Trend heatmap - optional color mapping of PoC nodes using EMA 12 versus EMA 21.
PoC labels - optional labels on every Nth PoC for easier reading and referencing.
How it works
1) Global lookback and binning
You choose:
Lookback Bars - how far back to collect data.
Number of Bins - how finely to split the price range.
The script:
Finds the highest high and lowest low in the lookback.
Computes the total price range and divides it into equal binCount slices.
Assigns each bar's close and volume into the appropriate price bin.
This creates a discretized volume distribution across the entire lookback.
2) Side volume profile
If "Show Side Profile" is enabled, a right-hand volume profile is drawn:
Each bin becomes a horizontal bar anchored at a configurable "Right Offset" from the current bar.
The horizontal width of each bar is proportional to that bin's volume relative to the maximum volume bin.
Optionally, volume values and percentages are printed inside the profile bars.
Color and transparency are controlled by:
Base Profile Color and its transparency.
A gradient that uses relative volume to modulate opacity between lower volume and higher volume bins.
Profile Width (%) - how wide the maximum bin can extend in bars.
This gives you an at-a-glance view of the volume landscape for the chosen lookback window.
3) Segmenting for PoC migration
To build the PoC trail, the lookback is divided into segments:
Bars per Segment - bars in each local cluster.
Number of Segments - how many segments you want to see back in time.
For each segment:
The script uses the same price bins and accumulates volume only from bars in that segment.
It finds the bin with the highest volume in that segment, which is the local PoC for that segment.
It sets the PoC price to the center of that bin.
It finds the "mid bar" of the segment and places the PoC node at that time on the chart.
This is repeated for each segment from older to newer, so you get a chain of PoCs that shows how local value has migrated over time.
4) Trend regime and color coding
The indicator precomputes:
EMA 12 (Fast).
EMA 21 (Slow).
For each PoC:
It samples EMA 12 and EMA 21 at the mid bar of that segment.
It computes a simple trend score as fast EMA minus slow EMA.
If trend heatmap is enabled, PoC nodes (and the lines between them) are colored by:
Trend Up Color if EMA 12 is above EMA 21.
Trend Down Color if EMA 12 is below EMA 21.
Trend Flat Color if they are roughly equal.
If the trend heatmap is disabled, PoC color is instead based on PoC migration:
If the current PoC is above the previous PoC, use the Up PoC Color.
If the current PoC is below the previous PoC, use the Down PoC Color.
If unchanged, use the Flat PoC Color.
5) Connecting PoCs and labels
Once PoC prices and times are known:
Each PoC is connected to the previous one with a dotted line, using the PoC's color.
Optional labels are placed next to every Nth PoC:
Label text uses a simple "PoC N" scheme.
Label background uses a configurable label background color.
Label border is colored by the PoC's own color for visual consistency.
This turns the PoCs into a visual path that can be read like a "value trajectory" across the chart.
What it plots
When fully enabled, you will see:
A right-sided volume profile for the chosen lookback window, built from volume by price.
Colored horizontal bars representing each price bin's relative volume.
Optional volume text showing each bin's volume and its percentage of the profile maximum.
A series of PoC nodes spaced across the chart at the mid point of each segment.
Dotted lines connecting those PoCs to show the migration path of value.
Optional PoC labels at each Nth node for easier reference.
Color-coding of PoCs and lines either by EMA 12 / 21 trend regime or by up/down PoC drift.
Reading PoC migration and market pressure
Side profile as a pressure map
The side profile shows where trading has been most active:
Thick, opaque bars represent high volume zones and possible high interest or acceptance areas.
Thin, faint bars represent low volume zones, potential rejection or transition areas.
When price trades near a high volume bin, the market is sitting on an area of prior acceptance and size.
When price moves quickly through low volume bins, it often does so with less friction.
This gives you a static map of where the market has been willing to do business within your lookback.
PoC trail as a value migration map
The PoC chain represents "where value has lived" over time:
An upward sloping PoC trail indicates value migrating higher. Buyers have been willing to transact at increasingly higher prices.
A downward sloping trail indicates value migrating lower and sellers pushing the center of mass down.
A flat or oscillating trail indicates balance or rotational behaviour, with no clear directional acceptance.
Taken together, you can interpret:
Side profile as "where the volume mass sits", a static pressure field.
PoC trail as "how that mass has moved", the dynamic path of value.
Trend heatmap as a regime overlay
When PoCs are colored by the EMA 12 / 21 spread:
Green PoCs mark segments where the faster EMA is above the slower EMA, that is, a local uptrend regime.
Red PoCs mark segments where the faster EMA is below the slower EMA, that is, a local downtrend regime.
Gray PoCs mark flat or ambiguous trend segments.
This lets you answer questions like:
"Is value migrating higher while the trend regime is also up?" (trend confirming value).
"Is value migrating higher but most PoCs are red?" (value against the prevailing trend).
"Has value started to roll over just as PoCs flip from green to red?" (early regime transition).
Key settings
General Settings
Lookback Bars - how many bars back to use for both the global volume profile and segment profiles.
Number of Bins - how many price bins to split the high to low range into.
Profile Settings
Show Side Profile - toggle the right-hand volume profile on or off.
Profile Width (%) - how wide the largest volume bar is allowed to be in terms of bars.
Base Profile Color - the starting color for profile bars, with transparency.
Show Volume Values - if enabled, print volume and percent for each non-zero bin.
Profile Text Color - color for volume text inside the profile.
PoC Migration Settings
Show PoC Migration - toggle the PoC trail plotting.
Bars per Segment - the number of bars contained in each segment.
Number of Segments - how many segments to build backwards from the current bar.
Horizontal Spacing (bars) - spacing between PoC nodes when drawn. (Used to separate PoCs horizontally.)
Label Every Nth PoC - draw labels at every Nth PoC (0 or 1 to suppress labels).
Right Offset (bars) - horizontal offset to anchor the side profile on the right.
Up PoC Color - color used when a PoC is higher than the previous one, if trend heatmap is off.
Down PoC Color - color used when a PoC is lower than the previous one, if trend heatmap is off.
Flat PoC Color - color used when the PoC is unchanged, if trend heatmap is off.
PoC Label Background - background color for PoC labels.
Trend Heatmap Settings
Color PoCs By Trend (EMA 12 / 21) - when enabled, overrides simple up/down coloring and uses EMA-based trend colors.
Fast EMA - length for the fast EMA.
Slow EMA - length for the slow EMA.
Trend Up Color - color for PoCs in a bullish EMA regime.
Trend Down Color - color for PoCs in a bearish EMA regime.
Trend Flat Color - color for neutral or flat EMA regimes.
Trading applications
1) Value migration and trend confirmation
Use the PoC path to see if value is following price or lagging it:
In a healthy uptrend, price, PoCs, and trend regime should all lean higher.
In a weakening trend, price may still move up, but PoCs flatten or start drifting lower, suggesting fewer participants are accepting the new highs.
In a downtrend, persistent downward PoC migration confirms that sellers are winning the value battle.
2) Identifying acceptance and rejection zones
Combine the side profile with PoC locations:
High volume bins near clustered PoCs mark strong acceptance zones, good areas to watch for re-tests and decision points.
PoCs that quickly jump across low volume areas can indicate rejection and fast repricing between value zones.
High volume zones with mixed PoC colors may signal balance or prolonged negotiation.
3) Structuring entries and exits
Use the map to refine trade location:
Fade trades against value migration are higher risk unless you see clear signs of exhaustion or regime change.
Pullbacks into prior PoC zones in the direction of the current PoC slope can offer higher quality entries.
Stops placed beyond major accepted zones (clusters of PoCs and high volume bins) are less likely to be hit by random noise.
4) Regime transitions
Watch how PoCs behave as the EMA regime changes:
A flip in EMA 12 versus EMA 21, coupled with a turn in PoC slope, is a strong signal that value is beginning to move with the new trend.
If EMAs flip but PoC migration does not follow, the trend signal may be early or false.
A weakening PoC path (lower highs in PoCs) while trend colors are still green can warn of a late-stage trend.
Best practices
Start with a moderate lookback such as 200 to 300 bars and a moderate bin count such as 20 to 40. Too many bins can make the profile overly granular and sparse.
Align "Bars per Segment" with your trading horizon. For example, 5 to 10 bars for intraday, 10 to 20 bars for swing.
Use the profile and PoC trail as structural context rather than as a direct buy or sell signal. Combine with your existing setups for timing.
Pay attention to clusters of PoCs at similar prices. Those are areas where the market has repeatedly accepted value, and they often matter on future tests.
Notes
This is a structural volume tool, not a complete trading system. It does not manage execution, position sizing or risk management. Use it to understand:
Where the bulk of trading has occurred in your chosen window.
How the center of volume has migrated over time.
Whether that migration is aligned with or fighting the current trend regime.
By turning PoC evolution into a visible path and adding a trend-aware heatmap, the PoC Migration Map makes it easier to see how value has been moving, where the market is likely to feel "heavy" or "light", and how that structure fits into your trading decisions.
インジケーター
Volume Gaps & Imbalances (Zeiierman)█ Overview
Volume Gaps & Imbalances (Zeiierman) is an advanced market-structure and order-flow visualizer that maps where the market traded, where it did not, and how buyer-vs-seller pressure accumulated across the entire price range.
The core of the indicator is a price-by-price volume profile built from Bullish and Bearish volume assignments. The script highlights:
True zero-volume voids (regions of no traded volume)
Bull/Bear imbalance rows (horizontal volume slices)
A multi-section Delta Panel, showing aggregated Buy–Sell pressure per vertical sector
A clean separation between profile structure, volume efficiency, and delta flows
Together, these components reveal market inefficiencies, displacement zones, and fair-value regions that price tends to revisit — making it an exceptional tool for structural trading, order-flow analysis, and contextual confluence.
Highlights
Identifies true volume voids (untraded price regions), more precisely than standard FVG tools
Plots Bull vs Bear volume at each price row for fine-grained imbalance reading
Includes a sector-based Delta Grid that aggregates Buy–Sell dominance
█ How It Works
⚪ Profile Construction
The indicator scans a user-defined Lookback window and divides the full high–low range into Rows. Each bar's volume is allocated into the correct price bucket:
Bullish volume when close > open
Bearish volume when close <= open
This produces three values per price level:
Bull Volume
Bear Volume
Total Volume & Imbalance Profile
Rows where no volume at all occurred are marked as volume gaps — signaling true untraded zones, often produced by impulsive imbalanced moves.
⚪ Zero-Volume Gaps (True Voids)
Unlike candle-based Fair Value Gaps (FVGs), volume gaps identify the deeper, structural inefficiency: Price moved so fast through a region that no trades occurred at those prices. These areas often attract revisits because liquidity never exchanged hands there.
⚪ Bull/Bear Volume Imbalance
Every price row is drawn using two colored horizontal segments:
Bull segment proportional to bullish volume
Bear segment proportional to bearish volume
This reveals where buyers or sellers dominated individual price levels.
⚪ Delta Panel
The full volume profile is cut into Summary Sections. For each block, the script computes: Δ = (Bull Volume − Bear Volume) ÷ Total Volume × 100%
█ How to Use
⚪ Spot True Voids & Inefficiencies
Zero-volume zones highlight where the price moved without trading. These areas often behave like:
Refill zones during retracements
Targets during displacement
Thin regions price slices through quickly
Ideal for both SMC-style trading and structural mapping.
⚪ Identify Bull/Bear Control at Each Price Level
Broad bullish segments show zones of buyer absorption, while wide bearish slices reveal seller control.
This helps you interpret:
Where buyers supported the price
Where sellers defended a level
Which price levels matter for continuation or reversal
⚪ Use Delta Sectors for Contextual Direction
The delta panel shows where market pressure is accumulating, revealing whether the profile is dominated by:
Bullish flow (positive delta)
Bearish flow (negative delta)
Neutral flow (balanced or minimal delta)
█ Settings
Lookback – Number of bars scanned to build the profile.
Rows – Vertical resolution of price bins.
Source – Price source used to assign volume into rows.
Summary Sections – Number of vertical delta sectors.
Summary Width – Horizontal size of the delta bar panel.
Gap From Profile – Distance between profile and delta grid.
Show Delta Text – Toggle Δ% labels.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
インジケーター
ICT HTF Volume Candles (Based on HTF Candles by Fadi)# ICT HTF Volume Candles - Multi-Timeframe Volume Analysis
## Overview
This indicator provides multi-timeframe volume visualization designed to complement price action analysis. It displays volume data from up to 6 higher timeframes simultaneously in a separate panel, allowing traders to identify volume spikes, divergences, and institutional activity without switching between timeframes.
**Original Concept Credits:** This indicator builds upon the HTF Candles framework by Fadi, adapting it specifically for volume analysis with enhanced features including gap-filling for extended hours, multiple scaling methods, and advanced synchronization.
## What Makes This Script Original
### Key Innovations:
1. **Three Volume Scaling Methods:**
- **Per-HTF Auto Scale:** Each timeframe scales independently for detailed comparison
- **Global Auto Scale:** All timeframes use unified scale for relative volume comparison
- **Manual Scale:** User-defined maximum for consistent analysis across sessions
2. **Bullish/Bearish Volume Differentiation:**
- Volume bars colored based on price movement (close vs open)
- Separate styling for bullish (green) and bearish (red) volume periods
- Helps identify whether volume supports price direction
3. **Advanced Time Synchronization:**
- Custom daily candle open times (Midnight, 8:30 AM, 9:30 AM ET)
- Timezone-aware calculations for New York trading hours
- Real-time countdown timers for each timeframe
- **Gap-filling technology** for continuous display during extended hours and weekends
4. **Flexible Display Options:**
- Configurable spacing and positioning
- Label placement (top, bottom, or both)
- Day-of-week or time interval labels on candles
- Works reliably in backtesting and live trading
## How It Works
### Volume Calculation
The indicator uses `request.security()` with optimized parameters to fetch volume data from higher timeframes:
- **Volume Open/High/Low/Close (OHLC):** Tracks volume changes within each HTF candle
- **Color Logic:** Compares HTF close vs open prices to determine bullish/bearish classification
- **Alignment:** All volume bars share a common baseline for easy visual comparison
- **Gap Handling:** Uses `gaps=barmerge.gaps_off` to maintain continuity during non-trading hours
### Technical Implementation
```
1. Monitors HTF timeframe changes using request.security() with lookahead
2. Creates new VolumeCandle object when HTF bar opens
3. Updates current candle's volume H/L/C on each chart bar
4. Applies selected scaling method to normalize display height
5. Repositions all candles and labels on each bar update
6. Fills gaps automatically during extended hours for consistent display
```
### Scaling Methods Explained
**Method 1 - Auto Scale per HTF:**
Each timeframe displays volume relative to its own maximum. Best for identifying patterns within each individual timeframe.
**Method 2 - Global Auto Scale:**
All timeframes share the same scale based on the highest volume across all HTFs. Best for comparing relative volume strength between timeframes.
**Method 3 - Manual Scale:**
User sets maximum volume value. Best for maintaining consistent scale across different trading sessions or instruments.
## How to Use This Indicator
### Setup
1. Add indicator to your chart (it appears in a separate panel below price)
2. Configure up to 6 higher timeframes (default: 5m, 15m, 1H, 4H, 1D, 1W)
3. Set number of candles to display for each timeframe
4. Choose volume scaling method based on your analysis needs
5. Enable "Fix gaps in non-trading hours" for extended hours trading (enabled by default)
### Interpretation
**Volume Spikes:**
- Sudden increase in volume height indicates institutional activity or strong conviction
- Compare volume between timeframes to identify where the real money is moving
- Look for volume spikes that appear across multiple timeframes simultaneously
**Bullish vs Bearish Volume:**
- **Green volume bars:** Price closed higher (buying pressure)
- **Red volume bars:** Price closed lower (selling pressure)
- High green volume during uptrend = confirmation of strength
- High red volume during downtrend = confirmation of weakness
- High volume opposite to trend = potential reversal warning
**Multi-Timeframe Context:**
- **5m/15m:** Scalping and day trading activity
- **1H/4H:** Swing trading and intraday institutional flows
- **Daily/Weekly:** Major position building and long-term trends
**Divergences:**
- Price making new highs but volume declining = weakening trend
- Volume increasing while price consolidates = potential breakout brewing
- Price breaks level but volume doesn't confirm = likely false breakout
### Practical Examples
**Example 1 - Institutional Confirmation:**
Price breaks above resistance. Check volume across timeframes:
- 5m shows spike = retail interest
- 15m + 1H + 4H all show spikes = institutional confirmation
- **Trade confidence: HIGH**
**Example 2 - False Breakout Detection:**
Price breaks resistance with:
- High volume on 5m only
- Normal/low volume on 1H and 4H
- **Interpretation:** Likely retail trap, institutions not participating
- **Action:** Wait for pullback or avoid
**Example 3 - Accumulation Phase:**
Price ranges sideways but:
- Daily volume gradually increasing
- Weekly volume above average
- **Interpretation:** Smart money accumulating
- **Action:** Prepare for breakout in direction of volume
**Example 4 - Volume Divergence:**
Price makes new high:
- Current high has lower volume than previous high across all timeframes
- **Interpretation:** Weakening momentum
- **Action:** Consider profit-taking or reversal trade
## Configuration Parameters
### Timeframe Settings
- **HTF 1-6:** Select timeframes (must be higher than chart timeframe)
- **Max Display:** Number of candles to show per timeframe (1-50)
- **Limit to Next HTFs:** Display only first N enabled timeframes (1-6)
### Styling
- **Bull/Bear Colors:** Separate colors for body, border, and wick
- **Padding from current candles:** Distance offset from live price action
- **Space between candles:** Gap between individual volume bars
- **Space between Higher Timeframes:** Gap between different timeframe groups
- **Candle Width:** Thickness of volume bars (1-4, multiplied by 2)
### Volume Settings
- **Volume Scale Method:** Choose 1, 2, or 3
- 1 = Auto Scale per HTF (each TF independent)
- 2 = Global Auto Scale (all TF unified)
- 3 = Manual Scale (user-defined max)
- **Auto Scale Volume:** Enable/disable automatic scaling
- **Manual Scale Max Volume:** Set maximum when using Method 3
### Label Settings
- **HTF Label:** Show/hide timeframe names with color and size options
- **Label Positions:** Display at Top, Bottom, or Both
- **Label Alignment:** Align centered or Follow Candles
- **Remaining Time:** Show countdown timer until next HTF candle
- **Interval Value:** Display day-of-week or time on each candle
### Custom Daily Candle
- **Enable Custom Daily:** Override default daily candle timing
- **Open Time Options:**
- **Midnight:** Standard 00:00 ET daily open
- **8:30 AM:** Align with economic data releases
- **9:30 AM:** Align with NYSE market open
- Useful for specific trading strategies or market alignment
### Advanced Settings
- **Fix gaps in non-trading hours:** Maintains alignment during extended hours and weekends (recommended: ON)
- Prevents visual gaps during forex weekend closures
- Ensures consistent display during crypto 24/7 trading
- Improves backtesting reliability
## Best Practices
1. **Pair with Price Action:** Use alongside HTF price candles indicator for complete picture
2. **Start Simple:** Enable 2-3 timeframes initially (e.g., 15m, 1H, 4H), add more as needed
3. **Match Settings:** Use same candle width/spacing as companion price indicator for visual alignment
4. **Scale Appropriately:**
- Use **Global scale** (Method 2) when comparing timeframes
- Use **Per-HTF scale** (Method 1) for pattern analysis within each timeframe
- Use **Manual scale** (Method 3) for consistent day-to-day comparison
5. **Watch for Volume Clusters:** High volume appearing simultaneously across multiple HTFs signals significant market events
6. **Confirm Breakouts:** Always check if volume supports the price movement across higher timeframes
7. **Extended Hours:** Keep "Fix gaps" enabled for 24/7 markets (Forex, Crypto) and weekend analysis
## Technical Notes
- **Timezone:** All calculations use America/New_York timezone for consistency
- **Real-time Updates:** Volume and timers update on each tick during market hours
- **Performance:** Optimized with max_bars_back=5000 for extensive historical analysis
- **Compatibility:** Works on all instruments with volume data (Stocks, Forex, Crypto, Futures)
- **Gap Handling:** Uses `barmerge.gaps_off` to fill data gaps during non-trading periods
- **Backtesting:** Uses `lookahead=barmerge.lookahead_on` for stable historical data without repainting
- **Data Continuity:** Automatically handles market closures, weekends, and extended hours
## Updates & Improvements
**Version 2.0 (Current):**
- ✅ Fixed alignment issues during extended hours and weekends
- ✅ Eliminated repainting in backtesting
- ✅ Added gap-filling technology for continuous display
- ✅ Improved data synchronization across all timeframes
- ✅ Enhanced NA value handling for data integrity
- ✅ Added advanced settings group for user control
## Support
For questions, suggestions, or feedback, please comment on the publication or message the author.
---
**Disclaimer:** This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always perform your own analysis and implement proper risk management before making trading decisions.
インジケーター
Volumetric Compressed MAVCMA (Volumetric Compressed Moving Average) uses the compressor and weighted standard deviation functions originally translated to pinescript by @gorx1 to plot moving averages in order to use for entry confirmation.
🔹 Concepts and Idea:
When we do music we always use different kinds of filters (low-pass, high pass, etc) for equalization and filtering itself. That stuff we use in finance as well. What we also always use in music are compressors, there dynamic processors that automatically adjust volume so it will be more consistent. Almost all the cool music you hear is compressed (both individual instruments (especially vocals) and the whole track afterwards), otherwise stuff will be too quite and too weak to flex on it, and also DJing it would be a nightmare.
🔹 Model:
I don't wanna explain it all in statistical / DSP way for once.
First of all, I think the population of volumes is log-normally distributed, so let's take logs of volumes, now we have a ~ normally distributed data. We take linearly weighted mean, add and subtract linearly weighted standard deviation from it, these would be our thresholds, the borders between different kinds of volumes explained before.
The upper threshold is for downward compression, that will not let volume pass it higher.
The lower threshold is for upward compression, all the volumes lower than this threshold will be brought up to the threshold's level.
Then we apply multipliers to the thresholds in order to adjust em and find the sweet spots. We do it the same way as in sound engineering when we don't aim for overcompression, we adjust the thresholds until they start to touch the signal and all good.
Afterwards, we delete all the number 1 and number 3 volume, leaving us exclusively with the clear main component, ready to be processed further.
We return the volumes to dem real scale.
For more info on Volume Compression it's highly advised to check @gorx1's initial script Volume Compressor
🔹 Settings:
MA Type: Moving average type to be used for comparison after calculating the compressed version of volume. This creates the second line after the compression line, so we can consider crossovers for confirmation entries.
Upward threshold: Upward threshold where the compression of volume is calculated. Increasing usually causes smoother lines.
Downward threshold: Downward threshold where the compression of volume is calculated. Decreasing usually causes smoother lines.
Compression Lookback: The Main lookback window of a volume that is used for compression. Increasing this would provide smoother lines but might cause delayed signals. Decreasing means more signals, but might cause whiplash and distorted signals.
Comparative Lookback: This is our lookback to be used with our ma type selection. There is no static better or worse lookback value for this indicator. It should be adjusted based on the pair.
🔹 Where to use:
This indicator should be used as another confirmation tool for your entry signals in your existing strategy/market following combination. Green dots (crossovers) mean bullish movement is expected, and red dots (crossbounders) mean bearish movement is expected. Automated crossover alerts are available. A reminder is that this kind of indicator should not be used on its own for trading, but rather should be used as a confirmation along with your trend detection and main entry indicators to provide additional confidence.
If you want to know under the hood, read the How it works section below.
🔹 How it works:
//This is our main compression calculation, which is used for the first line.
Compressed_out = compressor(volume, len_window, up_thresh, down_thresh)
//This is the secondary ratio calculation that we use for the second line.
Comp_ma = ma(ma_type, close * compressed_out, len_ml) / ma(ma_type, compressed_out, len_ml)
Vwma = ma(ma_type, close, len_window)
We calculate the ratio of the compressed volume and plot it against the base MA. Base MA's length is determined by the Compression Lookback input compared to the Comperative Lookback that is used for the compressed version. This provides us with another possible confirmation indicator that can be used to take advantage of volume ranges. インジケーター
VWAP Multi-TimeframeThis is a multi-timeframe VWAP indicator that provides volume weighted average price calculations for the following time periods:
15min
30min
1H
2H
4H
6H
8H
12H
1D
1W
1M
3M
6M
1Y
You can use the lower timeframes for short term trend control areas and use the longer timeframes for long term trend control areas. Trade in the direction of the trend and watch for price reactions that you can trade when price gets close to or touches any of these levels.
This indicator will provide a data plot value of 1 for bullish when price is above all VWAPs that are turned on, -1 for bearish when price is below all VWAPs that are turned on and 0 for neutral when price is not above or below all VWAPs. Use this 1, -1, 0 value as a filter on your signal generating indicators so that you can prevent signals from coming in unless they are in the same direction as the VWAP trend.
Features
Trend direction value of 1, -1 or 0 to send to external indicators so you can filter your signal generating indicators using the VWAP trend.
Trend table that shows you whether price is above or below all of the major VWAPs. This includes the daily, weekly, monthly and yearly VWAPs.
Trend coloring between each VWAP and the close price of each candle so you can easily identify the trend direction.
Customization
Set the source value to use for all of the VWAP calculations. The default is HLC3.
Turn on or off each VWAP.
Change the color of each VWAP line.
Change the thickness of each VWAP line.
Turn on or off labels for each VWAP or turn all labels on or off at once.
Change the offset length from the current bar to the label text.
Change the label text color.
Turn on or off trend coloring for each VWAP.
Change the color for up trends and down trends.
Turn on or off the trend direction display table.
Change the location of the trend direction display table.
Adjust the background and text colors on the trend direction display table.
How To Use The Trend Direction Filtering Feature
The indicator will provide a data plot value of 1 for bullish when price is above all of the VWAPs that are turned on, a value of -1 for bearish when price is below all of the VWAPS that are turned on and a value of 0 for neutral when price is above and below some of the VWAPs that are turned on.
The name of the value to use with your external indicators will show up as: VWAP Multi-Timeframe: Trend Direction To Send To External Indicators
Make sure to use that as your source on your external indicators to get the correct values.
This 1, -1 or 0 value can then be used by another external indicator to tell the indicator what is allowed to do. For instance if you have another indicator that provides buy and sell signals, you can use this trend direction value to prevent your other indicator from giving a sell signal when the VWAP trend is bullish or prevent your other indicator from giving a buy signal when the VWAP trend is bearish.
You will need to program your other indicators to use this trend filtering feature, but this indicator is already set up with this filtering code so you can use it with any other indicator that you choose to filter(if you know how to customize pine script).
Markets You Can Use This Indicator On
This indicator uses volume and price to calculate values, so it will work on any chart that provides volume and price data.
インジケーター
