Project Pegasus SideMap • VRP Heatmap • Volume Node DetectionDescription CME_MINI:NQ1!
Project Pegasus – Volume SideMap V 1.0 builds a right-anchored horizontal volume heatmap silhouette, visualizing buy/sell participation per price level over any chosen lookback or visible range. It automatically detects Low-Volume Nodes (LVN), Medium-Volume Nodes (MVN), and High-Volume Nodes (HVN), while also marking Top Volume Peaks, POI Lines (Most-Touched Levels), and complete Value Area Levels (POC / VAH / VAL) including optional session highs/lows.
What’s Unique
Right-Fixed Rendering – All profile rows are anchored to the chart’s right edge, creating a consistent visual reference during live trading.
Gap-Free Silhouette – Each price row blends seamlessly with its neighbors, producing a clean and continuous volume shape.
Triple-Tier Node Detection (LVN / MVN / HVN) – Automatically highlights zones of rejection, transition, and acceptance based on relative volume strength.
Dynamic Binning System – Adapts to price range and lookback while preserving proportional per-row volume distribution.
POI Finder (Most Touches) – Highlights price rows that have been touched most frequently by bars (traffic clusters).
Top-N Peaks – Sorts and draws the strongest single-price clusters by total volume while respecting minimum spacing.
Integrated Value Area Metrics – Calculates and plots POC, VAH, and VAL with optional session High/Low markers.
Color Modes – Choose between heatmap intensity (volume-based) or buy/sell ratio blending for directional context.
Performance Optimized – Rebuilds only when structure changes, ensuring smooth operation even with large histories.
Technical Overview
1. Binning & Aggregation
The full price range is divided into a user-defined number of rows (bins) of equal height.
For each bar, traded volume is distributed across all intersecting bins proportionally to price overlap.
A buy/sell proxy is estimated based on candle close position, producing per-row Buy, Sell, and Total Volume arrays.
2. Silhouette Rendering
Each row’s strength = total volume ÷ maximum volume.
Two color modes:
• Volume Mode → intensity scales by relative volume (heatmap).
• Ratio Mode → blend between sell and buy base colors based on dominance (close position).
Weak or neutral rows can be faded or forced to minimum width via strength and ratio-deviation filters.
3. Node Detection (LVN / MVN / HVN)
Relative bands are defined by lower/upper % thresholds.
Consecutive rows meeting criteria are grouped into “bands.”
Optional gap-merge unifies nearby bands separated by small gaps (in ticks).
Quality filters:
• Min. Average in Band (%) → enforces minimum average participation.
• Min. Prominence vs. Neighbors (%) → compares contrast against adjacent volume peaks.
Enforces minimum center distance (in ticks) to prevent overlap.
Each valid band draws a Top/Bottom line pair and optional mid-label (LVN/MVN/HVN).
4. Volume Peaks
Ranks all rows by total volume (descending) and selects top N peaks with spacing filters.
Drawn as horizontal lines or labeled markers (P1, P2, etc.).
5. POI Lines (Most Touches)
During aggregation, each row counts how many bars overlap it.
The top X rows with highest touch counts are drawn as POI lines—often strong participation or mean-retest zones.
6. Value Area (POC / VAH / VAL)
POC = row with highest total volume.
Expands outward symmetrically until the configured Value Area % of total volume is covered.
VAH and VAL mark the acceptance range; optional High/Low lines outline total range boundaries.
7. Right-Fix Layout
All components are rendered relative to the chart’s rightmost bar.
Width dynamically scales with visible bars × % width setting, ensuring proportional scaling across zoom levels.
How to Use
Read market structure:
HVNs = high acceptance or balance areas → likely mean-reversion zones.
LVNs = thin participation → breakout or rejection points (“air pockets”).
MVNs = transition areas between acceptance and rejection.
Trade around POC / VAH / VAL:
These levels represent fair-value boundaries and rotational pivots.
POI & Peaks:
Use them as strong reference lines for responsive trading decisions.
Ratio-Color Mode:
Exposes directional imbalance and potential absorption zones visually.
Best practice:
Live trading → right-fix active, moderate row count.
Post-session analysis → higher granularity, LVN/HVN/MVN and peaks enabled with labels.
Key Settings
Core
Lookback length or visible-range mode
Row count (granularity)
Profile width (% of visible bars)
Right offset, minimum box width, transparency
Date Filter
Aggregate only bars from a defined start date onward.
Coloring
Buy/Sell ratio mode toggle
Base colors for buy and sell volume
Filters
Minimum ratio deviation (±) → ignore nearly balanced rows
Minimum volume strength (%) → fade weak rows
LVN / MVN / HVN Detection
Independent enable toggles
Lower/upper % thresholds
Minimum band height (rows)
Merge small gaps (ticks)
Minimum average in band (%)
Minimum prominence vs. neighbors (%)
Minimum distance between bands (ticks)
Line color, width, style, and label options
Peaks
Number of peaks (0–20)
Minimum distance between peaks (ticks)
Color, width, style, label placement
POI Lines
Enable toggle
POI count (1–5)
Minimum gap between POIs (rows)
Color, width, style, label offset
Value Levels (POC / VAH / VAL)
Show/hide Value Area Levels
Value Area % coverage
POC / VAH / VAL line styles, widths, colors
Optional Session High/Low lines
Notes & Limitations
Optimized for intraday and swing data; accuracy depends on chart volume granularity.
Large lookbacks with high row counts and all detection layers enabled may impact performance—adjust parameters for balance.
Buy/Sell ratio is a visual approximation based on candle structure, not actual order-book delta.
Designed as a contextual visualization tool, not a trade signal generator.
Disclaimer
For educational and informational purposes only.
Not financial advice.
Heatmap
Tick-Based Delta Volume BubblesTICK-BASED DELTA VOLUME BUBBLES
OVERVIEW
A real-time order flow indicator that displays volume delta at the tick level, helping traders identify buying and selling pressure as it develops during live market hours. Unlike traditional volume delta indicators that rely on bar close data, this indicator captures actual tick-by-tick volume changes and directional bias, providing granular insight into market dynamics.
HOW IT WORKS
The indicator monitors live tick data during real-time trading by tracking volume increases between consecutive price updates. Each time volume increments, the script calculates the volume delta, determines price direction, assigns directional bias to the volume, and accumulates net delta for each bar.
This methodology is identical to the tick detection mechanism used in professional cumulative volume delta tools, ensuring accuracy and reliability.
FEATURES
Real-Time Tick Detection
- Captures genuine tick-by-tick volume flow using varip persistence
- Not estimated from OHLC data
- Processes actual market ticks as they occur
Adaptive Bubble Sizing
- Bubbles scale based on delta strength relative to a customizable moving average (default 20 bars)
- Highlights significant order flow imbalances
- Five size levels from tiny to huge
Dual Display Modes
- Normal Mode: Sized bubbles with optional volume labels positioned at bar midpoint
- Minimal Mode: Clean dots above/below bars for unobtrusive delta visualization
Flow Classification
- Aggressive Buy (bright green): Strong positive delta with greater than 1.2x strength
- Aggressive Sell (bright red): Strong negative delta with greater than 1.2x strength
- Passive Buy (light green): Moderate positive delta
- Passive Sell (light red): Moderate negative delta
Intensity Mode (Optional)
- Gray: Low intensity (less than 0.5x average)
- Blue: Medium intensity (0.5-1.0x average)
- Orange: High intensity (1.0-2.0x average)
- Red: Extreme intensity (greater than 2.0x average)
Smart Filtering
- Percentile-based filters (customizable) ensure only significant delta events are displayed
- Reduces chart clutter while highlighting important order flow
- Separate thresholds for bubble display and numeric labels
Data Collection Status
- Optional progress box in top-right corner
- Shows real-time bar collection progress
- Displays percentage completion and bars remaining
- Automatically hides when sufficient data is collected
Hide Until Ready Option
- Suppresses bubble display until the averaging period is complete
- Prevents misleading signals from incomplete data
- Default requires 20 bars before displaying bubbles
SETTINGS
Delta Average Length (1-200, default 20)
- Lookback period for calculating delta strength baseline
- Higher values = longer-term delta comparison
- Lower values = more sensitive to recent changes
Hide Bubbles Until Enough Data
- Prevents display until averaging period completes
- Ensures reliable delta strength calculations
Show Data Collection Status Box
- Displays progress indicator during initialization
- Can be disabled if you understand the warmup period
Minimal Mode
- Switches to simple dot display above/below bars
- Green dots above bars = positive delta
- Red dots below bars = negative delta
- Maintains color intensity or flow type classification
Show Bubbles
- Master toggle for bubble display
Bubble Volume Percentile (0-100, default 60)
- Minimum percentile rank required to display bubble
- Higher values = fewer, more significant bubbles
- Lower values = more bubbles displayed
Show Numbers in Bubbles
- Toggle delta value labels
- Only appears in normal mode
- Disabled automatically in minimal mode
Label Volume Percentile (0-100, default 90)
- Higher threshold for displaying numeric labels
- Typically set higher than bubble percentile
- Reduces label clutter on chart
Intensity Mode
- Switch from flow-type coloring to magnitude-based coloring
- Useful for identifying volume spikes regardless of direction
IMPORTANT NOTES
Real-Time Only: This indicator processes live tick data and does not provide historical analysis. It begins collecting data when added to a live chart.
Volume Required: Symbol must have volume data available. Will not function on symbols without volume (most forex pairs from retail brokers).
Initialization Period: Requires the specified number of bars (default 20) to calculate accurate delta strength. Use the "Hide Until Ready" option to prevent premature signals.
Market Hours: Only collects data during live market hours. Does not backfill historical data.
CREDITS
Tick detection methodology inspired by the Kioseff Trading Tick CVD indicator. This implementation adapts the same core tick-level volume delta calculation for bubble-style visualization and per-bar delta analysis.
Seasonality Heatmap [QuantAlgo]🟢 Overview
The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns.
🟢 How It Works
1. Monthly Heatmap
How % Return is Calculated:
The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month:
(Current Month Price - Previous Month Price) / Previous Month Price × 100
Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view
Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns
What Averages Mean:
The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.)
This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average
Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months
Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed
What Months Up % Mean:
Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month)
Calculated as:
(Number of Months with Positive Returns / Total Months) × 100
Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months
Example: If October shows "64%", then 64% of all historical Octobers had positive returns
What Consistency Score Means:
A 1-10 rating that measures how predictable and stable a month's returns have been
Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency
High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year
Medium scores (5-7, gray): Moderate consistency with some variability
Low scores (1-4, red): High variability with unpredictable behavior across different years
Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation
What Best Means:
Shows the highest percentage return achieved for that specific month, along with the year it occurred
Reveals the maximum observed upside and identifies outlier years with exceptional performance
Useful for understanding the range of possible outcomes beyond the average
Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain
What Worst Means:
Shows the most negative percentage return for that specific month, along with the year it occurred
Reveals maximum observed downside and helps understand the range of historical outcomes
Important for risk assessment even in months with positive averages
Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss
2. Day-of-Week Heatmap
How % Return is Calculated:
Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection)
Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.)
Each cell shows the average performance for that specific day-month combination across all historical data
Formula:
(Current Day Price - Previous Day Close) / Previous Day Close × 100
What Averages Mean:
The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday
Identifies broad weekly patterns across the entire dataset
Calculated by summing all daily returns for that weekday across all months and dividing by total observations
Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset
What Days Up % Mean:
Shows the percentage of historical occurrences where that weekday had a positive return
Calculated as:
(Number of Positive Days / Total Days Observed) × 100
Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days
Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns
What Consistency Score Means:
A 1-10 rating measuring how stable that weekday's performance has been across different months
Based on the coefficient of variation of daily returns for that weekday across all 12 months
High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month
Medium scores (5-7, gray): Moderate consistency with some month-to-month variation
Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month
Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year
What Best Means:
Shows which calendar month had the strongest average performance for that specific weekday
Identifies favorable day-month combinations based on historical data
Format shows the month abbreviation and the average return achieved
Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset
What Worst Means:
Shows which calendar month had the weakest average performance for that specific weekday
Identifies historically challenging day-month combinations
Useful for understanding which month-weekday pairings have shown weaker performance
Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset
3. Optimal Timing Table/Summary Table
→ Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower
Based on the observation that buying during historically weaker months may position for subsequent recovery
Shows the month name, its average return, and color-coded performance
Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period
→ Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher
Based on historical strength patterns in that month
Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains
→ 2nd Best Month to BUY: The second-lowest performing month based on average returns
Provides an alternative timing option based on historical patterns
Offers flexibility for staged entries or when the primary month doesn't align with strategy
Example: Identifies the next-most favorable historical buying period
→ 2nd Best Month to SELL: The second-highest performing month based on average returns
Provides an alternative exit timing based on historical data
Useful for staged profit-taking or multiple exit opportunities
Identifies the secondary historical strength period
Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days).
🟢 Examples
Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency
Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year.
Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern
An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent.
Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality
A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
Volume Cluster Heatmap [BackQuant]Volume Cluster Heatmap
A visualization tool that maps traded volume across price levels over a chosen lookback period. It highlights where the market builds balance through heavy participation and where it moves efficiently through low-volume zones. By combining a heatmap, volume profile, and high/low volume node detection, this indicator reveals structural areas of support, resistance, and liquidity that drive price behavior.
What Are Volume Clusters?
A volume cluster is a horizontal aggregation of traded volume at specific price levels, showing where market participants concentrated their buying and selling.
High Volume Nodes (HVN) : Price levels with significant trading activity; often act as support or resistance.
Low Volume Nodes (LVN) : Price levels with little trading activity; price moves quickly through these areas, reflecting low liquidity.
Volume clusters help identify key structural zones, reveal potential reversals, and gauge market efficiency by highlighting where the market is balanced versus areas of thin liquidity.
By creating heatmaps, profiles, and highlighting high and low volume nodes (HVNs and LVNs), it allows traders to see where the market builds balance and where it moves efficiently through thin liquidity zones.
Example: Bitcoin breaking away from the high-volume zone near 118k and moving cleanly through the low-volume pocket around 113k–115k, illustrating how markets seek efficiency:
Core Features
Visual Analysis Components:
Heatmap Display : Displays volume intensity as colored boxes, lines, or a combination for a dynamic view of market participation.
Volume Profile Overlay : Shows cumulative volume per price level along the right-hand side of the chart.
HVN & LVN Labels : Marks high and low volume nodes with color-coded lines and labels.
Customizable Colors & Transparency : Adjust high and low volume colors and minimum transparency for clear differentiation.
Session Reset & Timeframe Control : Dynamically resets clusters at the start of new sessions or chosen timeframes (intraday, daily, weekly).
Alerts
HVN / LVN Alerts : Notify when price reaches a significant high or low volume node.
High Volume Zone Alerts : Trigger when price enters the top X% of cumulative volume, signaling key areas of market interest.
How It Works
Each bar’s volume is distributed proportionally across the horizontal price levels it touches. Over the lookback period, this builds a cumulative volume profile, identifying price levels with the most and least trading activity. The highest cumulative volume levels become HVNs, while the lowest are LVNs. A side volume profile shows aggregated volume per level, and a heatmap overlay visually reinforces market structure.
Applications for Traders
Identify strong support and resistance at HVNs.
Detect areas of low liquidity where price may move quickly (LVNs).
Determine market balance zones where price may consolidate.
Filter noise: because volume clusters aggregate activity into levels, minor fluctuations and irrelevant micro-moves are removed, simplifying analysis and improving strategy development.
Combine with other indicators such as VWAP, Supertrend, or CVD for higher-probability entries and exits.
Use volume clusters to anticipate price reactions to breaking points in thin liquidity zones.
Advanced Display Options
Heatmap Styles : Boxes, lines, or both. Boxes provide a traditional heatmap, lines are better for high granularity data.
Line Mode Example : Simplified line visualization for easier reading at high level counts:
Profile Width & Offset : Adjust spacing and placement of the volume profile for clarity alongside price.
Transparency Control : Lower transparency for more opaque visualization of high-volume zones.
Best Practices for Usage
Reduce the number of levels when using line mode to avoid clutter.
Use HVN and LVN markers in conjunction with volume profiles to plan entries and exits.
Apply session resets to monitor intraday vs. multi-day volume accumulation.
Combine with other technical indicators to confirm high-probability trading signals.
Watch price interactions with LVNs for potential rapid movements and with HVNs for possible support/resistance or reversals.
Technical Notes
Each bar contributes volume proportionally to the price levels it spans, creating a dynamic and accurate representation of traded interest.
Volume profiles are scaled and offset for visual clarity alongside live price.
Alerts are fully integrated for HVN/LVN interaction and high-volume zone entries.
Optimized to handle large lookback windows and numerous price levels efficiently without performance degradation.
This indicator is ideal for understanding market structure, detecting key liquidity areas, and filtering out noise to model price more accurately in high-frequency or algorithmic strategies.
Volume Profile Two-Tone - Hit Counter - Meter V1 Volume Profile Two-Tone - Hit Counter - Meter V1
Overview
The Volume Profile Two-Tone - Hit Counter - Meter V1 is a Pine Script v6 indicator for TradingView, designed to visualize buy and sell activity distribution across price levels within a user-defined window or intraday session. It plots a dual-color horizontal histogram showing buying (green) and selling (red) volume intensity, along with optional hit-count numbers and meter overlays. The profile dynamically updates as new bars form, providing an intuitive picture of where market participants are most active.
The enhanced V1 edition introduces persistent hit counts, real-time adaptive row rebuilding, and improved memory management for smoother performance in both rolling-window and session modes.
How It Works
The indicator divides the selected range into rows (price bins) and aggregates trade volume (or tick volume) per bar.
Each bin separately sums up bullish and bearish contributions based on candle direction and delta logic, then draws side-by-side histogram bars:
• Buy Volume (green): Total volume from bullish bars within the bin.
• Sell Volume (red): Total volume from bearish bars within the bin.
A rolling or session-based window determines how many recent bars are analyzed. Value Area (VA), Point of Control (POC), and total hits per bin are computed continuously. The display auto-adjusts as price moves, keeping the profile anchored to the latest visible bars.
Behind the scenes, optimized arrays manage active boxes, lines, and labels for each bin. Functions like ensure_rows() rebuild buffers only when necessary, guaranteeing efficiency without repainting past data. Persistent hit-tracking ensures each price level maintains its count even when temporarily hidden.
Key Features
• Dual-Tone Volume Histogram: Buy/sell split with distinct colors for immediate visual contrast.
• Rolling or Session Profiles: Choose between continuous rolling windows or intraday session resets.
• Persistent Hit Counts: Displays total touches per bin, remaining stored even when bins refresh.
• Adaptive Row Management: Automatic rebuilding when zooming, scrolling, or changing resolution.
• Value Area + POC Detection: Highlights the most active price levels and volume concentration zones.
• Meter Overlay Option: Adds gradient bars or directional meters for quick trend context.
• Performance Optimized: Uses lightweight arrays and cached line handles for minimal CPU load.
• Custom Color Control: Editable buy/sell colors, opacity, row count, and profile width.
• Full Persistence Mode: Profiles remain visually consistent across bar updates without redraw gaps.
What It Displays
The Volume Profile Two-Tone - Hit Counter - Meter V1 presents an adaptive horizontal histogram beside the chart’s candles, revealing how volume is distributed across price.
• Green segments show dominant buying interest; red segments reveal selling pressure.
• POC line identifies the highest-volume price.
• Hit-count numbers quantify how often price traded at each level.
• Optional meters display relative directional strength within the same range.
This visual layering helps traders quickly identify supply/demand zones, balance areas, and developing auction profiles across intraday or multi-session contexts.
Originality
The Pine Script v6 indicator uses efficient array management (array.new_*, array.set, array.get) and native math operations for rendering.
It avoids external dependencies, relying only on built-in TradingView functions like request.security, box.new, line.new, and label.new for dynamic plotting.
Common Ways People Use It
• Scalpers: Study short-term imbalances or high-activity levels to time entries/exits.
• Day Traders: Track evolving session volume and POC migration.
• Swing Analysts: Compare rolling distributions to identify value shifts over multiple days.
• Volume Profilers: Combine with VWAP or order-flow tools for deeper context.
Configuration Notes
Profile Mode: Select Rolling Window (bars) or Session (intraday).
Rows and Width: Default = 72 rows, 44 bars width.
Colors and Opacity: Adjust to match chart theme.
Performance Mode: Choose Accurate or Fast (approximate) for speed control.
Show Hits / Meter: Enable hit-count numbers and gradient meters for added context.
Legal Disclaimer
For informational and educational purposes only—not investment, financial, or trading advice. Past performance does not guarantee future results; trading involves significant risk. Provided “as is,” without warranties. Consult a qualified professional before making decisions. By using, you accept all risks and agree to this disclaimer.
Cumulative Volume Delta Profile and Heatmap [BackQuant]Cumulative Volume Delta Profile and Heatmap
A multi-view CVD workstation that measures buying vs selling pressure, renders a price-aligned CVD profile with Point of Control, paints an optional heatmap of delta intensity, and detects classical CVD divergences using pivot logic. Built for reading who is in control, where participation clustered, and when effort is failing to produce result.
What is CVD
Cumulative Volume Delta accumulates the difference between aggressive buys and aggressive sells over time. When CVD rises, buyers are lifting the offer more than sellers are hitting the bid. When CVD falls, the opposite is true. Plotting CVD alongside price helps you judge whether price moves are supported by real participation or are running on fumes.
Core Features
Visual Analysis Components
CVD Columns - Plot of cumulative delta, colored by side, for quick read of participation bias.
CVD Profile - Price-aligned histogram of CVD accumulation using user-set bins. Shows where net initiative clustered.
Split Buy and Sell CVD - Optional two-sided profile that separates positive and negative CVD into distinct wings.
POC - Point of Control - The price level with the highest absolute CVD accumulation, labeled and line-marked.
Heatmap - Semi-transparent blocks behind price that encode CVD intensity across the last N bars.
Divergence Engine - Pivot-based detection of Bearish and Bullish CVD divergences with optional lines and labels.
Stats Panel - Top level metrics: Total CVD, Buy and Sell totals with percentages, Delta Ratio, and current POC price.
How it works
Delta source and sampling
You select an Anchor Timeframe that defines the higher time aggregation for reading the trend of CVD.
The script pulls lower timeframe volume delta and aggregates it to the anchor window. You can let it auto-select the lower timeframe or force a custom one.
CVD is then accumulated bar by bar to form a running total. This plot shows the direction and persistence of initiative.
Profile construction
The recent price range is split into Profile Granularity bins.
As price traverses a bin, the current delta contribution is added to that bin.
If Split Buy and Sell CVD is enabled, positive CVD goes to the right wing and negative CVD to the left wing.
Widths are scaled by each side’s maximum so you can compare distribution shape at a glance.
The Point of Control is the bin with the highest absolute CVD. This marks where initiative concentrated the most.
Heatmap
For each bin, the script computes intensity as absolute CVD relative to the maximum bin value.
Color is derived from the side in control in that bin and shaded by intensity.
Heatmap Length sets how far back the panels extend, highlighting recurring participation zones.
Divergence model
You define pivot sensitivity with Pivot Left and Right .
Bearish divergence triggers when price confirms a higher high while CVD fails to make a higher high within a configurable Delta Tolerance .
Bullish divergence triggers when price confirms a lower low while CVD fails to make a lower low.
On trigger, optional link lines and labels are drawn at the pivots for immediate context.
Key Settings
Delta Source
Anchor Timeframe - Higher TF for the CVD narrative.
Custom Lower TF and Lower Timeframe - Force the sampling TF if desired.
Pivot Logic
Pivot Left and Right - Bars to each side for swing confirmation.
Delta Tolerance - Small allowance to avoid near-miss false positives.
CVD Profile
Show CVD Profile - Toggle profile rendering.
Split Buy and Sell CVD - Two-sided profile for clearer side attribution.
Show Heatmap - Project intensity panels behind price.
Show POC and POC Color - Mark the dominant CVD node.
Profile Granularity - Number of bins across the visible price range.
Profile Offset and Profile Width - Position and scale the profile.
Profile Position - Right, Left, or Current bar alignment.
Visuals
Bullish Div Color and Bearish Div Color - Colors for divergence artifacts.
Show Divergence Lines and Labels - Visualize pivots and annotations.
Plot CVD - Column plot of total CVD.
Show Statistics and Position - Toggle and place the summary table.
Reading the display
CVD columns
Rising CVD confirms buyers are in control. Falling CVD confirms sellers.
Flat or choppy CVD during wide price moves hints at passive or exhausted participation.
CVD profile wings
Thick right wing near a price zone implies heavy buy initiative accumulated there.
Thick left wing implies heavy sell initiative.
POC marks the strongest initiative node. Expect reactions on first touch and rotations around this level when the tape is balanced.
Heatmap
Brighter blocks indicate stronger historical net initiative at that price.
Stacked bright bands form CVD high volume nodes. These often behave like magnets or shelves for future trade.
Divergences
Bearish - Price prints a higher high while CVD fails to do so. Effort is not producing result. Potential fade or pause.
Bullish - Price prints a lower low while CVD fails to do so. Capitulation lacks initiative. Potential bounce or reversal.
Stats panel
Total CVD - Net initiative over the window.
Buy and Sell volume with percentages - Side composition.
Delta Ratio - Buy over Sell. Values above 1 favor buyers, below 1 favor sellers.
POC Price - Current control node for plan and risk.
Workflows
Trend following
Choose an Anchor Timeframe that matches your holding period.
Trade in the direction of CVD slope while price holds above a bullish POC or below a bearish POC.
Use pullbacks to CVD nodes on your profile as entry locations.
Trend weakens when price makes new highs but CVD stalls, or new lows while CVD recovers.
Mean reversion
Look for divergences at or near prior CVD nodes, especially the POC.
Fade tests into thick wings when the side that dominated there now fails to push CVD further.
Target rotations back toward the POC or the opposite wing edge.
Liquidity and execution map
Treat strong wings and heatmap bands as probable passive interest zones.
Expect pauses, partial fills, or flips at these shelves.
Stops make sense beyond the far edge of the active wing supporting your idea.
Alerts included
CVD Bearish Divergence and CVD Bullish Divergence.
Price Cross Above POC and Price Cross Below POC.
Extreme Buy Imbalance and Extreme Sell Imbalance from Delta Ratio.
CVD Turn Bullish and CVD Turn Bearish when net CVD crosses zero.
Price Near POC proximity alert.
Best practices
Use a higher Anchor Timeframe to stabilize the CVD story and a sensible Profile Granularity so wings are readable without clutter.
Keep Split mode on when you want to separate initiative attribution. Turn it off when you prefer a single net profile.
Tune Pivot Left and Right by instrument to avoid overfitting. Larger values find swing divergences. Smaller values find micro fades.
If volume is thin or synthetic for the symbol, CVD will be less reliable. The script will warn if volume is zero.
Trading applications
Context - Confirm or question breakouts with CVD slope.
Location - Build entries at CVD nodes and POC.
Timing - Use divergence and POC crosses for triggers.
Risk - Place stops beyond the opposite wing or outside the POC shelf.
Important notes and limits
This is a price and volume based study. It does not access off-book or venue-level order flow.
CVD profiles are built from the data available on your chart and the chosen lower timeframe sampling.
Like all volume tools, readings can distort during roll periods, holidays, or feed anomalies. Validate on your instrument.
Technical notes
Delta is aggregated from a lower timeframe into an Anchor Timeframe narrative.
Profile bins update in real time. Splitting by side scales each wing independently so both are readable in the same panel.
Divergences are confirmed using standard pivot definitions with user-set tolerances.
All profile drawing uses fixed X offsets so panels and POC do not swim when you scroll.
Quick start
Anchor Timeframe = Daily for intraday context.
Split Buy and Sell CVD = On.
Profile Granularity = 100 to 200, Profile Position = Right, Width to taste.
Pivot Left and Right around 8 to 12 to start, then adapt.
Turn on Heatmap for a fast map of interest bands.
Bottom line
CVD tells you who is doing the lifting. The profile shows where they did it. Divergences tell you when effort stops paying. Put them together and you get a clear read on control, location, and timing for both trend and mean reversion.
Anchored Session Volume Profile • Heatmap Profiles • Asia/EU/US Description
This indicator builds Anchored Session Volume Profiles for Asia, EU, and US sessions on intraday charts and renders them as right-docked line histograms (heatmap or classic style). Each session computes its own POC, VAH, VAL and optional Session High/Low lines. An optional per-price-bin Delta overlay estimates buy/sell pressure inside the profile rows for quick order-flow context.
What’s unique
Three independent session anchors (Asia/EU/US) with custom start/end times, bin size in ticks, and Value Area %.
Right-fixed live rendering or post-close persistence (draw levels only after the session closes).
Adaptive width: profile width scales with elapsed session length (anchor → now/end) within user limits.
Heatmap profile: row tint scales by relative volume; or Classic single-color with optional gradient.
Per-row Delta ticks (outside/inside, configurable direction) derived from bar delta and overlap with each price bin.
Clean POC/VAH/VAL line styling, optional ray extension, and Session High/Low rays per session.
How it works (technical)
Binning: Rows are built with a user-defined bin height in ticks. Arrays expand/shrink as price extends; the base is shifted when new lows appear to keep bins aligned.
Accumulation: For each bar within the active session window, traded volume is distributed to intersecting bins proportionally to the price overlap with that bin.
Value Area: POC is the highest-volume bin. VA is grown symmetrically around the POC until the selected coverage (VA%) is reached.
Delta per bin (optional): A bar-level delta proxy volume * (close − open) / range (clamped) is split into buy/sell and allocated to bins proportionally to the same overlap share, producing a per-row delta magnitude for rendering ticks.
Rendering modes:
Right fixed: refreshes each bar; lines/histogram are docked at the anchor X-position.
Draw Levels after Session Close: on close, only POC/VAH/VAL (and optional Session High/Low) are persisted.
No lookahead: All computations use confirmed bars; levels are deterministic on close.
How to use
Use the Asia/EU/US profiles to read participation hand-offs and session-driven rotations.
Trade off POC/VAH/VAL as acceptance/rejection references; confluence with session High/Low often marks responsive flows.
Employ Delta ticks per row to spot absorption, one-sided stacking, or fading participation inside the profile without leaving TradingView.
Prefer right-fixed during live trading and post-close when you want persistent session levels.
Key settings
General per session: Start/End (hh:mm), Bin size (ticks), Value Area %, toggle POC/VAH/VAL lines.
Rendering: Heatmap vs. Classic, orientation (Left/Right), gradient on/off, row thickness, right offset, adaptive width limits.
Delta (per price bin): global on/off, per-session on/off, tick width, max tick length (bars), outside/inside placement, direction (sign-based / always left / always right), colors.
Levels: POC/VAH/VAL styles (solid/dashed/dotted), widths, colors, extend right (ray).
Session High/Low: per-session on/off, style, width, colors, optional right-ray extension.
Notes & limitations
Designed for intraday data; accuracy depends on the feed’s volume granularity.
Large histories + small bins + delta ticks can be heavy; tune bin size, adaptive width, and delta max length for performance.
Timezone for anchors is set internally to Europe/Berlin.
Educational tool — not a signal generator.
Disclaimer
For educational and informational purposes only. Not financial advice.
Liquidity Zones - Joe v1This script lets you plot liquidity/order levels (similar to what you see on Bookmap) directly on your TradingView chart.
It is designed to help traders spot support/resistance levels where large limit orders sit and to visualize whether those liquidity pools are still active, already taken, or being replenished.
Key Features
Session-based
Works during a defined trading session.
Resets automatically at the first bar of the session.
Up to 8 Liquidity Zones, each of which includes:
Price level
Size (affects line thickness)
Status (Active, Taken, Re-Stocking, or Automatic).
Zone Statuses
Active → Untouched liquidity (potential support/resistance).
Taken → Liquidity consumed after price trades through it.
Re-Stocking → Level is being reloaded with fresh orders.
Automatic → Updates dynamically (switches to Taken when crossed, otherwise stays Active).
Visual Representation
Zones are drawn as horizontal lines.
Labels show price + size (e.g., 4010 (200k)).
Customizable line styles and colors:
Active = solid red
Taken = gray dashed
Re-Stocking = purple dotted
Dynamic Updates
Levels automatically update during the session.
If price crosses a zone → it’s marked as Taken.
Labels, line styles, and colors adjust live.
Line thickness = zone size ÷ 10 → visually represents liquidity strength.
How this indicator is Used
Upon market open, the order book tends to fill with limit orders. Using Bookmap, you can see where these orders are placed at each relative price point, along with their sizes. The most important ones to focus on are the larger levels, which are typically highlighted in reddish tones (depending on your Bookmap settings).
I then manually enter these levels into this indicator. It only takes a few seconds, and since there’s no direct way to connect TradingView to Bookmap, this method works as an effective workaround. Once entered, the levels will stay visible on your TradingView chart.
This seemingly simple script is very powerful and provides a strong edge. More often than not, price action gravitates toward these larger liquidity levels. Remember, the price of a security is influenced by market makers whose role is to fill orders and earn commissions on transactions. They have little interest in arbitrarily pushing price higher or lower; instead, their primary function is to guide price toward liquidity—where the large orders sit.
Of course, this is a general principle, and many other variables can affect price movement. Still, by keeping this concept in mind, you’ll often find yourself on the right side of the market.
Extreme Pressure Zones Indicator (EPZ) [BullByte]Extreme Pressure Zones Indicator(EPZ)
The Extreme Pressure Zones (EPZ) Indicator is a proprietary market analysis tool designed to highlight potential overbought and oversold "pressure zones" in any financial chart. It does this by combining several unique measurements of price action and volume into a single, bounded oscillator (0–100). Unlike simple momentum or volatility indicators, EPZ captures multiple facets of market pressure: price rejection, trend momentum, supply/demand imbalance, and institutional (smart money) flow. This is not a random mashup of generic indicators; each component was chosen and weighted to reveal extreme market conditions that often precede reversals or strong continuations.
What it is?
EPZ estimates buying/selling pressure and highlights potential extreme zones with a single, bounded 0–100 oscillator built from four normalized components. Context-aware weighting adapts to volatility, trendiness, and relative volume. Visual tools include adaptive thresholds, confirmed-on-close extremes, divergence, an MTF dashboard, and optional gradient candles.
Purpose and originality (not a mashup)
Purpose: Identify when pressure is building or reaching potential extremes while filtering noise across regimes and symbols.
Originality: EPZ integrates price rejection, momentum cascade, pressure distribution, and smart money flow into one bounded scale with context-aware weighting. It is not a cosmetic mashup of public indicators.
Why a trader might use EPZ
EPZ provides a multi-dimensional gauge of market extremes that standalone indicators may miss. Traders might use it to:
Spot Reversals: When EPZ enters an "Extreme High" zone (high red), it implies selling pressure might soon dominate. This can hint at a topside reversal or at least a pause in rallies. Conversely, "Extreme Low" (green) can highlight bottom-fish opportunities. The indicator's divergence module (optional) also finds hidden bullish/bearish divergences between price and EPZ, a clue that price momentum is weakening.
Measure Momentum Shifts: Because EPZ blends momentum and volume, it reacts faster than many single metrics. A rising MPO indicates building bullish pressure, while a falling MPO shows increasing bearish pressure. Traders can use this like a refined RSI: above 50 means bullish bias, below 50 means bearish bias, but with context provided by the thresholds.
Filter Trades: In trend-following systems, one could require EPZ to be in the bullish (green) zone before taking longs, or avoid new trades when EPZ is extreme. In mean-reversion systems, one might specifically look to fade extremes flagged by EPZ.
Multi-Timeframe Confirmation: The dashboard can fetch a higher timeframe EPZ value. For example, you might trade a 15-minute chart only when the 60-minute EPZ agrees on pressure direction.
Components and how they're combined
Rejection (PRV) – Captures price rejection based on candle wicks and volume (see Price Rejection Volume).
Momentum Cascade (MCD) – Blends multiple momentum periods (3,5,8,13) into a normalized momentum score.
Pressure Distribution (PDI) – Measures net buy/sell pressure by comparing volume on up vs down candles.
Smart Money Flow (SMF) – An adaptation of money flow index that emphasizes unusual volume spikes.
Each of these components produces a 0–100 value (higher means more bullish pressure). They are then weighted and averaged into the final Market Pressure Oscillator (MPO), which is smoothed and scaled. By combining these four views, EPZ stands out as a comprehensive pressure gauge – the whole is greater than the sum of parts
Context-aware weighting:
Higher volatility → more PRV weight
Trendiness up (RSI of ATR > 25) → more MCD weight
Relative volume > 1.2x → more PDI weight
SMF holds a stable weight
The weighted average is smoothed and scaled into MPO ∈ with 50 as the neutral midline.
What makes EPZ stand out
Four orthogonal inputs (price action, momentum, pressure, flow) unified in a single bounded oscillator with consistent thresholds.
Adaptive thresholds (optional) plus robust extreme detection that also triggers on crossovers, so static thresholds work reliably too.
Confirm Extremes on Bar Close (default ON): dots/arrows/labels/alerts print on closed bars to avoid repaint confusion.
Clean dashboard, divergence tools, pre-alerts, and optional on-price gradients. Visual 3D layering uses offsets for depth only,no lookahead.
Recommended markets and timeframes
Best: liquid symbols (index futures, large-cap equities, major FX, BTC/ETH).
Timeframes: 5–15m (more signals; consider higher thresholds), 1H–4H (balanced), 1D (clear regimes).
Use caution on illiquid or very low TFs where wick/volume geometry is erratic.
Logic and thresholds
MPO ∈ ; 50 = neutral. Above 50 = bullish pressure; below 50 = bearish.
Static thresholds (defaults): thrHigh = 70, thrLow = 30; warning bands 5 pts inside extremes (65/35).
Adaptive thresholds (optional):
thrHigh = min(BaseHigh + 5, mean(MPO,100) + stdev(MPO,100) × ExtremeSensitivity)
thrLow = max(BaseLow − 5, mean(MPO,100) − stdev(MPO,100) × ExtremeSensitivity)
Extreme detection
High: MPO ≥ thrHigh with peak/slope or crossover filter.
Low: MPO ≤ thrLow with trough/slope or crossover filter.
Cooldown: 5 bars (default). A new extreme will not print until the cooldown elapses, even if MPO re-enters the zone.
Confirmation
"Confirm Extremes on Bar Close" (default ON) gates extreme markers, pre-alerts, and alerts to closed bars (non-repainting).
Divergences
Pivot-based bullish/bearish divergence; tags appear only after left/right bars elapse (lookbackPivot).
MTF
HTF MPO retrieved with lookahead_off; values can update intrabar and finalize at HTF close. This is disclosed and expected.
Inputs and defaults (key ones)
Core: Sensitivity=1.0; Analysis Period=14; Smoothing=3; Adaptive Thresholds=OFF.
Extremes: Base High=70, Base Low=30; Extreme Sensitivity=1.5; Confirm Extremes on Bar Close=ON; Cooldown=5; Dot size Small/Tiny.
Visuals: Heatmap ON; 3D depth optional; Strength bars ON; Pre-alerts OFF; Divergences ON with tags ON; Gradient candles OFF; Glow ON.
Dashboard: ON; Position=Top Right; Size=Normal; MTF ON; HTF=60m; compact overlay table on price chart.
Advanced caps: Max Oscillator Labels=80; Max Extreme Guide Lines=80; Divergence objects=60.
Dashboard: what each element means
Header: EPZ ANALYSIS.
Large readout: Current MPO; color reflects state (extreme, approaching, or neutral).
Status badge: "Extreme High/Low", "Approaching High/Low", "Bullish/Neutral/Bearish".
HTF cell (when MTF ON): Higher-timeframe MPO, color-coded vs extremes; updates intrabar, settles at HTF close.
Predicted (when MTF OFF): Simple MPO extrapolation using momentum/acceleration—illustrative only.
Thresholds: Current thrHigh/thrLow (static or adaptive).
Components: ASCII bars + values for PRV, MCD, PDI, SMF.
Market metrics: Volume Ratio (x) and ATR% of price.
Strength: Bar indicator of |MPO − 50| × 2.
Confidence: Heuristic gauge (100 in extremes, 70 in warnings, 50 with divergence, else |MPO − 50|). Convenience only, not probability.
How to read the oscillator
MPO Value (0–100): A reading of 50 is neutral. Values above ~55 are increasingly bullish (green), while below ~45 are increasingly bearish (red). Think of these as "market pressure".
Extreme Zones: When MPO climbs into the bright orange/red area (above the base-high line, default 70), the chart will display a dot and downward arrow marking that extreme. Traders often treat this as a sign to tighten stops or look for shorts. Similarly, a bright green dot/up-arrow appears when MPO falls below the base-low (30), hinting at a bullish setup.
Heatmap/Candles: If "Pressure Heatmap" is enabled, the background of the oscillator pane will fade green or red depending on MPO. Users can optionally color the price candles by MPO value (gradient candles) to see these extremes on the main chart.
Prediction Zone(optional): A dashed projection line extends the MPO forward by a small number of bars (prediction_bars) using current MPO momentum and acceleration. This is a heuristic extrapolation best used for short horizons (1–5 bars) to anticipate whether MPO may touch a warning or extreme zone. It is provisional and becomes less reliable with longer projection lengths — always confirm predicted moves with bar-close MPO and HTF context before acting.
Divergences: When price makes a higher high but EPZ makes a lower high (bearish divergence), the indicator can draw dotted lines and a "Bear Div" tag. The opposite (lower low price, higher EPZ) gives "Bull Div". These signals confirm waning momentum at extremes.
Zones: Warning bands near extremes; Extreme zones beyond thresholds.
Crossovers: MPO rising through 35 suggests easing downside pressure; falling through 65 suggests waning upside pressure.
Dots/arrows: Extreme markers appear on closed bars when confirmation is ON and respect the 5-bar cooldown.
Pre-alert dots (optional): Proximity cues in warning zones; also gated to bar close when confirmation is ON.
Histogram: Distance from neutral (50); highlights strengthening or weakening pressure.
Divergence tags: "Bear Div" = higher price high with lower MPO high; "Bull Div" = lower price low with higher MPO low.
Pressure Heatmap : Layered gradient background that visually highlights pressure strength across the MPO scale; adjustable intensity and optional zone overlays (warning / extreme) for quick visual scanning.
A typical reading: If the oscillator is rising from neutral towards the high zone (green→orange→red), the chart may see strong buying culminating in a stall. If it then turns down from the extreme, that peak EPZ dot signals sell pressure.
Alerts
EPZ: Extreme Context — fires on confirmed extremes (respects cooldown).
EPZ: Approaching Threshold — fires in warning zones if no extreme.
EPZ: Divergence — fires on confirmed pivot divergences.
Tip: Set alerts to "Once per bar close" to align with confirmation and avoid intrabar repaint.
Practical usage ideas
Trend continuation: In positive regimes (MPO > 50 and rising), pullbacks holding above 50 often precede continuation; mirror for bearish regimes.
Exhaustion caution: E High/E Low can mark exhaustion risk; many wait for MPO rollover or divergence to time fades or partial exits.
Adaptive thresholds: Useful on assets with shifting volatility regimes to maintain meaningful "extreme" levels.
MTF alignment: Prefer setups that agree with the HTF MPO to reduce countertrend noise.
Examples
Screenshots captured in TradingView Replay to freeze the bar at close so values don't fluctuate intrabar. These examples use default settings and are reproducible on the same bars; they are for illustration, not cherry-picking or performance claims.
Example 1 — BTCUSDT, 1h — E Low
MPO closed at 26.6 (below the 30 extreme), printing a confirmed E Low. HTF MPO is 26.6, so higher-timeframe pressure remains bearish. Components are subdued (Momentum/Pressure/Smart$ ≈ 29–37), with Vol Ratio ≈ 1.19x and ATR% ≈ 0.37%. A prior Bear Div flagged weakening impulse into the drop. With cooldown set to 5 bars, new extremes are rate-limited. Many traders wait for MPO to curl up and reclaim 35 or for a fresh Bull Div before considering countertrend ideas; if MPO cannot reclaim 35 and HTF stays weak, treat bounces cautiously. Educational illustration only.
Example 2 — ETHUSD, 30m — E High
A strong impulse pushed MPO into the extreme zone (≥ 70), printing a confirmed E High on close. Shortly after, MPO cooled to ~61.5 while a Bear Div appeared, showing momentum lag as price pushed a higher high. Volume and volatility were elevated (≈ 1.79x / 1.25%). With a 5-bar cooldown, additional extremes won't print immediately. Some treat E High as exhaustion risk—either waiting for MPO rollover under 65/50 to fade, or for a pullback that holds above 50 to re-join the trend if higher-timeframe pressure remains constructive. Educational illustration only.
Known limitations and caveats
The MPO line itself can change intrabar; extreme markers/alerts do not repaint when "Confirm Extremes on Bar Close" is ON.
HTF values settle at the close of the HTF bar.
Illiquid symbols or very low TFs can be noisy; consider higher thresholds or longer smoothing.
Prediction line (when enabled) is a visual extrapolation only.
For coders
Pine v6. MTF via request.security with lookahead_off.
Extremes include crossover triggers so static thresholds also yield E High/E Low.
Extreme markers and pre-alerts are gated by barstate.isconfirmed when confirmation is ON.
Arrays prune oldest objects to respect resource limits; defaults (80/80/60) are conservative for low TFs.
3D layering uses negative offsets purely for drawing depth (no lookahead).
Screenshot methodology:
To make labels legible and to demonstrate non-repainting behavior, the examples were captured in TradingView Replay with "Confirm Extremes on Bar Close" enabled. Replay is used only to freeze the bar at close so plots don't change intrabar. The examples use default settings, include both Extreme Low and Extreme High cases, and can be reproduced by scrolling to the same bars outside Replay. This is an educational illustration, not a performance claim.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Markets involve risk; past behavior does not guarantee future results. You are responsible for your own testing, risk management, and decisions.
Options Max Pain Calculator [BackQuant]Options Max Pain Calculator
A visualization tool that models option expiry dynamics by calculating "max pain" levels, displaying synthetic open interest curves, gamma exposure profiles, and pin-risk zones to help identify where market makers have the least payout exposure.
What is Max Pain?
Max Pain is the theoretical expiration price where the total dollar value of outstanding options would be minimized. At this price level, option holders collectively experience maximum losses while option writers (typically market makers) have minimal payout obligations. This creates a natural gravitational pull as expiration approaches.
Core Features
Visual Analysis Components:
Max Pain Line: Horizontal line showing the calculated minimum pain level
Strike Level Grid: Major support and resistance levels at key option strikes
Pin Zone: Highlighted area around max pain where price may gravitate
Pain Heatmap: Color-coded visualization showing pain distribution across prices
Gamma Exposure Profile: Bar chart displaying net gamma at each strike level
Real-time Dashboard: Summary statistics and risk metrics
Synthetic Market Modeling**
Since Pine Script cannot access live options data, the indicator creates realistic synthetic open interest distributions based on configurable market parameters including volume patterns, put/call ratios, and market maker positioning.
How It Works
Strike Generation:
The tool creates a grid of option strikes centered around the current price. You can control the range, density, and whether strikes snap to realistic market increments.
Open Interest Modeling:
Using your inputs for average volume, put/call ratios, and market maker behavior, the indicator generates synthetic open interest that mirrors real market dynamics:
Higher volume at-the-money with decay as strikes move further out
Adjustable put/call bias to reflect current market sentiment
Market maker inventory effects and typical short-gamma positioning
Weekly options boost for near-term expirations
Pain Calculation:
For each potential expiry price, the tool calculates total option payouts:
Call options contribute pain when finishing in-the-money
Put options contribute pain when finishing in-the-money
The strike with minimum total pain becomes the Max Pain level
Gamma Analysis:
Net gamma exposure is calculated at each strike using standard option pricing models, showing where hedging flows may be most intense. Positive gamma creates price support while negative gamma can amplify moves.
Key Settings
Basic Configuration:
Number of Strikes: Controls grid density (recommended: 15-25)
Days to Expiration: Time until option expiry
Strike Range: Price range around current level (recommended: 8-15%)
Strike Increment: Spacing between strikes
Market Parameters:
Average Daily Volume: Baseline for synthetic open interest
Put/Call Volume Ratio: Market sentiment bias (>1.0 = bearish, <1.0 = bullish) It does not work if set to 1.0
Implied Volatility: Current option volatility estimate
Market Maker Factors: Dealer positioning and hedging intensity
Display Options:
Model Complexity: Simple (line only), Standard (+ zones), Advanced (+ heatmap/gamma)
Visual Elements: Toggle individual components on/off
Theme: Dark/Light mode
Update Frequency: Real-time or daily calculation
Reading the Display
Dashboard Table (Top Right):
Current Price vs Max Pain Level
Distance to Pain: Percentage gap (smaller = higher pin risk)
Pin Risk Assessment: HIGH/MEDIUM/LOW based on proximity and time
Days to Expiry and Strike Count
Model complexity level
Visual Elements:
Red Line: Max Pain level where payout is minimized
Colored Zone: Pin risk area around max pain
Dotted Lines: Major strike levels (green = support, orange = resistance)
Color Bar: Pain heatmap (blue = high pain, red = low pain/max pain zones)
Horizontal Bars: Gamma exposure (green = positive, red = negative)
Yellow Dotted Line: Gamma flip level where hedging behavior changes
Trading Applications
Expiration Pinning:
When price is near max pain with limited time remaining, there's increased probability of gravitating toward that level as market makers hedge their positions.
Support and Resistance:
High open interest strikes often act as magnets, with max pain representing the strongest gravitational pull.
Volatility Expectations:
Above gamma flip: Expect dampened volatility (long gamma environment)
Below gamma flip: Expect amplified moves (short gamma environment)
Risk Assessment:
The pin risk indicator helps gauge likelihood of price manipulation near expiry, with HIGH risk suggesting potential range-bound action.
Best Practices
Setup Recommendations
Start with Model Complexity set to "Standard"
Use realistic strike ranges (8-12% for most assets)
Set put/call ratio based on current market sentiment
Adjust implied volatility to match current levels
Interpretation Guidelines:
Small distance to pain + short time = high pin probability
Large gamma bars indicate key hedging levels to monitor
Heatmap intensity shows strength of pain concentration
Multiple nearby strikes can create wider pin zones
Update Strategy:
Use "Daily" updates for cleaner visuals during trading hours
Switch to "Every Bar" for real-time analysis near expiration
Monitor changes in max pain level as new options activity emerges
Important Disclaimers
This is a modeling tool using synthetic data, not live market information. While the calculations are mathematically sound and the modeling realistic, actual market dynamics involve numerous factors not captured in any single indicator.
Max pain represents theoretical minimum payout levels and suggests where natural market forces may create gravitational pull, but it does not guarantee price movement or predict exact expiration levels. Market gaps, news events, and changing volatility can override these dynamics.
Use this tool as additional context for your analysis, not as a standalone trading signal. The synthetic nature of the data makes it most valuable for understanding market structure and potential zones of interest rather than precise price prediction.
Technical Notes
The indicator uses established option pricing principles with simplified implementations optimized for Pine Script performance. Gamma calculations use standard financial models while pain calculations follow the industry-standard definition of minimized option payouts.
All visual elements use fixed positioning to prevent movement when scrolling charts, and the tool includes performance optimizations to handle real-time calculation without timeout errors.
Volume Bubbles & Liquidity Heatmap [LuxAlgo]The Volume Bubbles & Liquidity Heatmap indicator highlights volume and liquidity clearly and precisely with its volume bubbles and liquidity heat map, allowing to identify key price areas.
Customize the bubbles with different time frames and different display modes: total volume, buy and sell volume, or delta volume.
🔶 USAGE
The primary objective of this tool is to offer traders a straightforward method for analyzing volume on any selected timeframe.
By default, the tool displays buy and sell volume bubbles for the daily timeframe over the last 2,000 bars. Traders should be aware of the difference between the timeframe of the chart and that of the bubbles.
The tool also displays a liquidity heat map to help traders identify price areas where liquidity accumulates or is lacking.
🔹 Volume Bubbles
The bubbles have three possible display modes:
Total Volume: Displays the total volume of trades per bubble.
Buy & Sell Volume: Each bubble is divided into buy and sell volume.
Delta Volume: Displays the difference between buy and sell volume.
Each bubble represents the trading volume for a given period. By default, the timeframe for each bubble is set to daily, meaning each bubble represents the trading volume for each day.
The size of each bubble is proportional to the volume traded; a larger bubble indicates greater volume, while a smaller bubble indicates lower volume.
The color of each bubble indicates the dominant volume: green for buy volume and red for sell volume.
One of the tool's main goals is to facilitate simple, clear, multi-timeframe volume analysis.
The previous chart shows Delta Volume bubbles with various chart and bubble timeframe configurations.
To correctly visualize the bubbles, traders must ensure there is a sufficient number of bars per bubble. This is achieved by using a lower chart timeframe and a higher bubble timeframe.
As can be seen in the image above, the greater the difference between the chart and bubble timeframes, the better the visualization.
🔹 Liquidity Heatmap
The other main element of the tool is the liquidity heatmap. By default, it divides the chart into 25 different price areas and displays the accumulated trading volume on each.
The image above shows a 4-hour BTC chart displaying only the liquidity heatmap. Traders should be aware of these key price areas and observe how the price behaves in them, looking for possible opportunities to engage with the market.
The main parameters for controlling the heatmap on the settings panel are Rows and Cell Minimum Size. Rows modifies the number of horizontal price areas displayed, while Cell Minimum Size modifies the minimum size of each liquidity cell in each row.
As can be seen in the above BTC hourly chart, the cell size is 24 at the top and 168 at the bottom. The cells are smaller on top and bigger on the bottom.
The color of each cell reflects the liquidity size with a gradient; this reflects the total volume traded within each cell. The default colors are:
Red: larger liquidity
Yellow: medium liquidity
Blue: lower liquidity
🔹 Using Both Tools Together
This indicator provides the means to identify directional bias and market timing.
The main idea is that if buyers are strong, prices are likely to increase, and if sellers are strong, prices are likely to decrease. This gives us a directional bias for opening long or short positions. Then, we combine our directional bias with price rejection or acceptance of key liquidity levels to determine the timing of opening or closing our positions.
Now, let's review some charts.
This first chart is BTC 1H with Delta Weekly Bubbles. Delta Bubbles measure the difference between buy and sell volume, so we can easily see which group is dominant (buyers or sellers) and how strong they are in any given week. This, along with the key price areas displayed by the Liquidity Heatmap, can help us navigate the markets.
We divided market behavior into seven groups, and each group has several bubbles, numbered from 1 to 17.
Bubbles 1, 2, and 3: After strong buyers market consolidates with positive delta, prices move up next week.
Bubbles 3, 4, and 5: Strength changes from buyers to sellers. Next week, prices go down.
Bubbles 6 and 7: The market trades at higher prices, but with negative delta. Next week, prices go down.
Bubbles 7, 8, and 9: Strength changes from sellers to buyers. Next weeks (9 and 10), prices go up.
Bubbles 10, 11, and 12: After strong buyers prices trade higher with a negative delta. Next weeks (12 and 13) prices go down.
Bubbles 12, 14, and 15: Strength changes from sellers to buyers; next week, prices increase.
Bubbles 15 and 16: The market trades higher with a very small positive delta; next week, prices go down.
Current bubble/week 17 is not yet finished. Right now, it is trading lower, but with a smaller negative delta than last week. This may signal that sellers are losing strength and that a potential reversal will follow, with prices trading higher.
This is the same BTC 1H chart, but with price rejections from key liquidity areas acting as strong price barriers.
When prices reach a key area with strong liquidity and are rejected, it signals a good time to take action.
By observing price behavior at certain key price levels, we can improve our timing for entering or exiting the markets.
🔶 DETAILS
🔹 Bubbles Display
From the settings panel, traders can configure the bubbles with four main parameters: Mode, Timeframe, Size%, and Shape.
The image above shows five-minute BTC charts with execution over the last 3,500 bars, different display modes, a daily timeframe, 100% size, and shape one.
The Size % parameter controls the overall size of the bubbles, while the Shape parameter controls their vertical growth.
Since the chart has two scales, one for time and one for price, traders can use the Shape parameter to make the bubbles round.
The chart above shows the same bubbles with different size and shape parameters.
You can also customize data labels and timeframe separators from the settings panel.
🔶 SETTINGS
Execute on last X bars: Number of bars for indicator execution
🔹 Bubbles
Display Bubbles: Enable/Disable volume bubbles.
Bubble Mode: Select from the following options: total volume, buy and sell volume, or the delta between buy and sell volume.
Bubble Timeframe: Select the timeframe for which the bubbles will be displayed.
Bubble Size %: Select the size of the bubbles as a percentage.
Bubble Shape: Select the shape of the bubbles. The larger the number, the more vertical the bubbles will be stretched.
🔹 Labels
Display Labels: Enable/Disable data labels, select size and location.
🔹 Separators
Display Separators: Enable/Disable timeframe separators and select color.
🔹 Liquidity Heatmap
Display Heatmap: Enable/Disable liquidity heatmap.
Heatmap Rows: select number of rows to be displayed.
Cell Minimum Size: Select the minimum size for each cell in each row.
Colors.
🔹 Style
Buy & Sell Volume Colors.
DeltaFlow Volume Profile [BigBeluga]🔵 OVERVIEW
The DeltaFlow Volume Profile builds a compact volume profile next to price and enriches every bin with flow context : bullish vs. bearish participation (%), a per-bin Delta % , an optional Delta Heat Map , and a PoC band with the bin’s absolute volume. This lets you see not just where volume clustered, but who (buyers or sellers) dominated inside each price slice.
🔵 CONCEPTS
Binned Volume Profile : Price range over a user-defined LookBack is split into Bins ; each bin aggregates traded volume.
Bull/Bear Split : Within every bin, volume is separated by candle direction into Bull Volume and Bear Volume , then normalized to % of the bin’s displayed size.
Delta % : The difference between Bull % and Bear % for the bin. Positive = buyer dominance; negative = seller dominance.
Delta Heat Map : Bin background shading that scales with both total volume strength and delta bias.
PoC (Point of Control) : The most significant bin gets a PoC band and a label with its absolute volume.
🔵 FEATURES
Profile with Flow : A clean horizontal volume bar per bin plus stacked Bull % and Bear % .
Per-Bin Delta Label : A readable “Δ xx%” tag at the start of each bin shows dominance at a glance.
Delta Heat Map : Optional gradient that intensifies with higher volume and stronger delta.
PoC Highlight : Optional PoC band colored separately, labeled with absolute volume (e.g., “1.23M”).
Configurable Inputs : LookBack, number of Bins (10–100), toggles for Delta, Heat Map, Volume Bars, and PoC color.
Readable Colors : Separate inputs for bullish (volume +) and bearish (volume –) hues.
🔵 HOW TO USE
Set the window : Choose LookBack and Bins to balance detail vs. performance (more bins = finer resolution).
Enable “Volume Bars” to display the bull/bear split as two stacked percent bars inside each bin.
High Bull % near support → constructive demand.
High Bear % near resistance → active supply.
Use Δ labels (toggle “Delta”) to quickly spot bins with clear buyer/seller control; combine with price position for confluence.
Turn on Delta Heat Map to prioritize areas with both large volume and strong imbalance.
Watch the PoC : The PoC band marks the most traded (and often magnet) level; its label shows absolute size for context.
Trade ideas :
Breakout continuation when Δ stays positive across consecutive upper bins.
Reversion risk when price enters a large bearish-Δ cluster below.
Manage risk around the PoC; reactions there can be sharp.
🔵 CONCLUSION
DeltaFlow Volume Profile upgrades a classic profile with flow intelligence. The bull/bear split, explicit Δ %, heat-weighted backdrop, and PoC volume label make dominant participation and key price shelves obvious. Use it to filter levels, time entries with imbalance, and validate breakouts or fades with objective volume-flow evidence.
Correlation Heatmap Matrix [TradingFinder] 20 Assets Variable🔵 Introduction
Correlation is one of the most important statistical and analytical metrics in financial markets, data mining, and data science. It measures the strength and direction of the relationship between two variables.
The correlation coefficient always ranges between +1 and -1 : a perfect positive correlation (+1) means that two assets or currency pairs move together in the same direction and at a constant ratio, a correlation of zero (0) indicates no clear linear relationship, and a perfect negative correlation (-1) means they move in exactly opposite directions.
While the Pearson Correlation Coefficient is the most common method for calculation, other statistical methods like Spearman and Kendall are also used depending on the context.
In financial market analysis, correlation is a key tool for Forex, the Stock Market, and the Cryptocurrency Market because it allows traders to assess the price relationship between currency pairs, stocks, or coins. For example, in Forex, EUR/USD and GBP/USD often have a high positive correlation; in stocks, companies from the same sector such as Apple and Microsoft tend to move similarly; and in crypto, most altcoins show a strong positive correlation with Bitcoin.
Using a Correlation Heatmap in these markets visually displays the strength and direction of these relationships, helping traders make more accurate decisions for risk management and strategy optimization.
🟣 Correlation in Financial Markets
In finance, correlation refers to measuring how closely two assets move together over time. These assets can be stocks, currency pairs, commodities, indices, or cryptocurrencies. The main goal of correlation analysis in trading is to understand these movement patterns and use them for risk management, trend forecasting, and developing trading strategies.
🟣 Correlation Heatmap
A correlation heatmap is a visual tool that presents the correlation between multiple assets in a color-coded table. Each cell shows the correlation coefficient between two assets, with colors indicating its strength and direction. Warm colors (such as red or orange) represent strong negative correlation, cool colors (such as blue or cyan) represent strong positive correlation, and mid-range tones (such as yellow or green) indicate correlations that are close to neutral.
🟣 Practical Applications in Markets
Forex : Identify currency pairs that move together or in opposite directions, avoid overexposure to similar trades, and spot unusual divergences.
Crypto : Examine the dependency of altcoins on Bitcoin and find independent movers for portfolio diversification.
Stocks : Detect relationships between stocks in the same industry or find outliers that move differently from their sector.
🟣 Key Uses of Correlation in Trading
Risk management and diversification: Select assets with low or negative correlation to reduce portfolio volatility.
Avoiding overexposure: Prevent opening multiple positions on highly correlated assets.
Pairs trading: Exploit temporary deviations between historically correlated assets for arbitrage opportunities.
Intermarket analysis: Study the relationships between different markets like stocks, currencies, commodities, and bonds.
Divergence detection: Spot when two typically correlated assets move apart as a possible trend change signal.
Market forecasting: Use correlated asset movements to anticipate others’ behavior.
Event reaction analysis: Evaluate how groups of assets respond to economic or political events.
❗ Important Note
It’s important to note that correlation does not imply causation — it only reflects co-movement between assets. Correlation is also dynamic and can change over time, which is why analyzing it across multiple timeframes provides a more accurate picture. Combining correlation heatmaps with other analytical tools can significantly improve the precision of trading decisions.
🔵 How to Use
The Correlation Heatmap Matrix indicator is designed to analyze and manage the relationships between multiple assets at once. After adding the tool to your chart, start by selecting the assets you want to compare (up to 20).
Then, choose the Correlation Period that fits your trading strategy. Shorter periods (e.g., 20 bars) are more sensitive to recent price movements, making them suitable for short-term trading, while longer periods (e.g., 100 or 200 bars) provide a broader view of correlation trends over time.
The indicator outputs a color-coded matrix where each cell represents the correlation between two assets. Warm colors like red and orange signal strong negative correlation, while cool colors like blue and cyan indicate strong positive correlation. Mid-range tones such as yellow or green suggest correlations that are close to neutral. This visual representation makes it easy to spot market patterns at a glance.
One of the most valuable uses of this tool is in portfolio risk management. Portfolios with highly correlated assets are more vulnerable to market swings. By using the heatmap, traders can find assets with low or negative correlation to reduce overall risk.
Another key benefit is preventing overexposure. For example, if EUR/USD and GBP/USD have a high positive correlation, opening trades on both is almost like doubling the position size on one asset, increasing risk unnecessarily. The heatmap makes such relationships clear, helping you avoid them.
The indicator is also useful for pairs trading, where a trader identifies assets that are usually correlated but have temporarily diverged — a potential arbitrage or mean-reversion opportunity.
Additionally, the tool supports intermarket analysis, allowing traders to see how movements in one market (e.g., crude oil) may impact others (e.g., the Canadian dollar). Divergence detection is another advantage: if two typically aligned assets suddenly move in opposite directions, it could signal a major trend shift or a news-driven move.
Overall, the Correlation Heatmap Matrix is not just an analytical indicator but also a fast, visual alert system for monitoring multiple markets at once. This is particularly valuable for traders in fast-moving environments like Forex and crypto.
🔵 Settings
🟣 Logic
Correlation Period : Number of bars used to calculate correlation between assets.
🟣 Display
Table on Chart : Enable/disable displaying the heatmap directly on the chart.
Table Size : Choose the table size (from very small to very large).
Table Position : Set the table location on the chart (top, middle, or bottom in various alignments).
🟣 Symbol Custom
Select Market : Choose the market type (Forex, Stocks, Crypto, or Custom).
Symbol 1 to Symbol 20: In custom mode, you can define up to 20 assets for correlation calculation.
🔵 Conclusion
The Correlation Heatmap Matrix is a powerful tool for analyzing correlations across multiple assets in Forex, crypto, and stock markets. By displaying a color-coded table, it visually conveys both the strength and direction of correlations — warm colors for strong negative correlation, cool colors for strong positive correlation, and mid-range tones such as yellow or green for near-zero or neutral correlation.
This helps traders select assets with low or negative correlation for diversification, avoid overexposure to similar trades, identify arbitrage and pairs trading opportunities, and detect unusual divergences between typically aligned assets. With support for custom mode and up to 20 symbols, it offers high flexibility for different trading strategies, making it a valuable complement to technical analysis and risk management.
Bollinger Heatmap [Quantitative]Overview
The Bollinger Heatmap is a composite indicator that synthesizes data derived from 30 Bollinger bands distributed over multiple time horizons, offering a high-dimensional characterization of the underlying asset.
Algorithm
The algorithm quantifies the current price’s relative position within each Bollinger band ensemble, generating a normalized position ratio. This ratio is subsequently transformed into a scalar heat value, which is then rendered on a continuous color gradient from red to blue. Red hues correspond to price proximity to or extension below the lower band, while blue hues denote price proximity to or extension above the upper band.
Using default parameters, the indicator maps bands over timeframes increasing in a pattern approximating exponential growth, constrained to multiples of seven days. The lower region encodes relationships with shorter-term bands spanning between 1 and 14 weeks, whereas the upper region portrays interactions with longer-term bands ranging from 15 to 52 weeks.
Conclusion
By integrating Bollinger bands across a diverse array of time horizons, the heatmap indicator aims to mitigate the model risk inherent in selecting a single band length, capturing exposure across a richer parameter space.
Correlation HeatMap [TradingFinder] Sessions Data Science Stats🔵 Introduction
n financial markets, correlation describes the statistical relationship between the price movements of two assets and how they interact over time. It plays a key role in both trading and investing by helping analyze asset behavior, manage portfolio risk, and understand intermarket dynamics. The Correlation Heatmap is a visual tool that shows how the correlation between multiple assets and a central reference asset (the Main Symbol) changes over time.
It supports four market types forex, stocks, crypto, and a custom mode making it adaptable to different trading environments. The heatmap uses a color-coded grid where warmer tones represent stronger negative correlations and cooler tones indicate stronger positive ones. This intuitive color system allows traders to quickly identify when assets move together or diverge, offering real-time insights that go beyond traditional correlation tables.
🟣 How to Interpret the Heatmap Visually ?
Each cell represents the correlation between the main symbol and one compared asset at a specific time.
Warm colors (e.g. red, orange) suggest strong negative correlation as one asset rises, the other tends to fall.
Cool colors (e.g. blue, green) suggest strong positive correlation both assets tend to move in the same direction.
Lighter shades indicate weaker correlations, while darker shades indicate stronger correlations.
The heatmap updates over time, allowing users to detect changes in correlation during market events or trading sessions.
One of the standout features of this indicator is its ability to overlay global market sessions such as Tokyo, London, New York, or major equity opens directly onto the heatmap timeline. This alignment lets traders observe how correlation structures respond to real-world session changes. For example, they can spot when assets shift from being inversely correlated to moving together as a new session opens, potentially signaling new momentum or macro flow. The customizable symbol setup (including up to 20 compared assets) makes it ideal not only for forex and crypto traders but also for multi-asset and sector-based stock analysis.
🟣 Use Cases and Advantages
Analyze sector rotation in equities by tracking correlation to major indices like SPX or DJI.
Monitor altcoin behavior relative to Bitcoin to find early entry opportunities in crypto markets.
Detect changes in currency alignment with DXY across trading sessions in forex.
Identify correlation breakdowns during market volatility, signaling possible new trends.
Use correlation shifts as confirmation for trade setups or to hedge multi-asset exposure
🔵 How to Use
Correlation is one of the core concepts in financial analysis and allows traders to understand how assets behave in relation to one another. The Correlation Heatmap extends this idea by going beyond a simple number or static matrix. Instead, it presents a dynamic visual map of how correlations shift over time.
In this indicator, a Main Symbol is selected as the reference point for analysis. In standard modes such as forex, stocks, or crypto, the symbol currently shown on the main chart is automatically used as the main symbol. This allows users to begin correlation analysis right away without adjusting any settings.
The horizontal axis of the heatmap shows time, while the vertical axis lists the selected assets. Each cell on the heatmap shows the correlation between that asset and the main symbol at a given moment.
This approach is especially useful for intermarket analysis. In forex, for example, tracking how currency pairs like OANDA:EURUSD EURUSD, FX:GBPUSD GBPUSD, and PEPPERSTONE:AUDUSD AUDUSD correlate with TVC:DXY DXY can give insight into broader capital flow.
If these pairs start showing increasing positive correlation with DXY say, shifting from blue to light green it could signal the start of a new phase or reversal. Conversely, if negative correlation fades gradually, it may suggest weakening relationships and more independent or volatile movement.
In the crypto market, watching how altcoins correlate with Bitcoin can help identify ideal entry points in secondary assets. In the stock market, analyzing how companies within the same sector move in relation to a major index like SP:SPX SPX or DJ:DJI DJI is also a highly effective technique for both technical and fundamental analysts.
This indicator not only visualizes correlation but also displays major market sessions. When enabled, this feature helps traders observe how correlation behavior changes at the start of each session, whether it's Tokyo, London, New York, or the opening of stock exchanges. Many key shifts, breakouts, or reversals tend to happen around these times, and the heatmap makes them easy to spot.
Another important feature is the market selection mode. Users can switch between forex, crypto, stocks, or custom markets and see correlation behavior specific to each one. In custom mode, users can manually select any combination of symbols for more advanced or personalized analysis. This makes the heatmap valuable not only for forex traders but also for stock traders, crypto analysts, and multi-asset strategists.
Finally, the heatmap's color-coded design helps users make sense of the data quickly. Warm colors such as red and orange reflect stronger negative correlations, while cool colors like blue and green represent stronger positive relationships. This simplicity and clarity make the tool accessible to both beginners and experienced traders.
🔵 Settings
Correlation Period: Allows you to set how many historical bars are used for calculating correlation. A higher number means a smoother, slower-moving heatmap, while a lower number makes it more responsive to recent changes.
Select Market: Lets you choose between Forex, Stock, Crypto, or Custom. In the first three options, the chart’s active symbol is automatically used as the Main Symbol. In Custom mode, you can manually define the Main Symbol and up to 20 Compared Symbols.
Show Open Session: Enables the display of major trading sessions such as Tokyo, London, New York, or equity market opening hours directly on the timeline. This helps you connect correlation shifts with real-world market activity.
Market Mode: Lets you select whether the displayed sessions relate to the forex or stock market.
🔵 Conclusion
The Correlation Heatmap is a robust and flexible tool for analyzing the relationship between assets across different markets. By tracking how correlations change in real time, traders can better identify alignment or divergence between symbols and gain valuable insights into market structure.
Support for multiple asset classes, session overlays, and intuitive visual cues make this one of the most effective tools for intermarket analysis.
Whether you’re looking to manage portfolio risk, validate entry points, or simply understand capital flow across markets, this heatmap provides a clear and actionable perspective that you can rely on.
Institutional HeatmapHeatmap Range - Volume Profile Visualization Indicator
What This Indicator Does
The Heatmap Range indicator provides a sophisticated volume profile visualization that displays price levels with the highest trading activity using color-coded heatmaps directly on your chart. Unlike traditional volume indicators, this tool shows WHERE the most significant trading occurred within specific price ranges over a customizable lookback period.
Advanced Volume Analysis
Volume-Weighted Price Levels: Calculates and displays up to 20 price levels based on actual trading volume
Customizable Time Period: Analyze volume distribution over 10-500 bars (default: 180 bars)
Smart Bin Sizing: Adjustable pip range (0.1-50 pips) for precise level identification
Peak Detection: Automatically identifies and centers display around highest volume areas
Visual Customization
3 Color Patterns:
Inverted Heat (Orange to Dark Red)
Inverted Cool (Orange to Dark Blue)
Inverted Purple (Light Pink to Dark Purple)
Transparency Control: 0-95% transparency for optimal chart readability
Adaptive Display: Shows most relevant levels centered around peak volume
Multi-Asset Support
Forex Pairs (EUR/USD, GBP/USD, etc.)
Precious Metals (Gold/XAUUSD, Silver/XAGUSD)
Futures (NQ, ES, YM, etc.)
Cryptocurrencies
Stock Indices
Customizable Parameters
Histogram Period (10-500, Default: 180) Bars to analyze for volume distribution
Bin Range (0.1-50 pips, Default: 5.0) Price range for each volume level
Color Pattern (1-3, Default: 1) Visual color scheme selection
Average Volume Period (10-200, Default: 100) Period for volume normalization
Max Display Levels (5-20, Default: 20) Maximum price levels to show
Transparency (0-95%, Default: 50%) Opacity of heatmap display
How to Use
For Day Traders
Identify key support/resistance levels based on actual volume
Spot high-probability reversal zones
Plan entries/exits around significant volume levels
For Swing Traders
Analyze longer-term volume distribution patterns
Identify major accumulation/distribution zones
Confirm breakout levels with volume validation
For Scalpers
Quick identification of intraday volume hotspots
Real-time volume level updates
Precise entry/exit timing around volume clusters
Visual Interpretation
Darker Colors: Higher volume concentration (stronger levels)
Lighter Colors: Lower volume concentration
Color Intensity: Directly correlates to volume strength at that price level
Level Positioning: Automatically centers around peak volume areas
Technical Specifications
Pine Script Version: v5
Chart Overlay: Yes
Max Bars Back: 1000
Performance Optimized: Limited to 200 bins for smooth operation
Real-time Updates: Dynamic calculation on each bar close
Getting Started
Add to Chart: Apply indicator to any supported timeframe
Adjust Period: Set histogram period based on your trading style
Choose Colors: Select color pattern that suits your chart theme
Fine-tune Levels: Adjust bin range and max levels for optimal display
Set Transparency: Balance visibility with chart clarity
Important Notes
Minimum Data Requirement: Needs at least 10 bars of history to function
Performance: Higher periods and smaller bin ranges require more processing
Volume Dependency: Most effective on instruments with consistent volume data
Timeframe Agnostic: Works on all timeframes from 1-minute to monthly
Status Information
The indicator includes a real-time information table showing:
Current settings (Period, Bin Range, Color Pattern, Transparency)
Indicator status (Active/Loading)
Disclaimer: This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and risk management before making trading decisions.
Compatible with TradingView's Pine Script v5 | Optimized for all market conditions | Professional-grade volume analysis
MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal.
Purpose of the Indicator
MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior.
Why a Trader Should Use It
Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky.
Why These Components Were Chosen
Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise.
Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1.
Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale.
Market Mode (Regime) : Based on those ranks, MERV classifies the market:
Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity.
Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market.
Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy.
The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral.
Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions.
What Makes MERV Stand Out
Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique.
Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers.
Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds.
Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals.
Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other.
Recommended Timeframes
MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice:
Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends.
Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles.
Scalpers might find MERV too “slow” unless input lengths are set very low.
In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas.
How the Scoring/Logic Works (Step-by-Step)
Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy.
Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are.
Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on .
Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line.
Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action.
Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value.
Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only.
Oscillator Plot – How to Read It
The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element:
Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed.
Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength.
Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close.
Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero.
Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable.
Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime.
Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star).
Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance.
Dashboard (Fixed Corner Panel)
MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows:
Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high).
Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line.
Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle.
Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly.
Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color.
Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low.
Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe.
In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state.
Real-Life Example
Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case.
Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve.
Example: How It Looks in Action
Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m)
What it means:
The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume.
Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h)
What it means:
This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success.
Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m)
What it means:
The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping.
Settings and Inputs
The script is fully open-source; here are key inputs the user can adjust:
Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity.
Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect.
Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action.
Show Heatmap : Toggles the entropy background coloring on/off.
Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red).
Show Mode Bar : Turn the bottom mode bar on/off.
Show Dashboard : Turn the fixed table panel on/off.
Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired.
Oscillator Interpretation (Recap)
Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile).
Fill : Orange tinted area between them (for visual emphasis).
Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom).
Star Line : White star = ideal conditions, Gold = good but not ideal.
Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric.
Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly.
Disclaimer
This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly.
-BullByte
RSI Divergence (Nikko)RSI Divergence by Nikko
🧠 RSI Divergence Detector — Nikko Edition This script is an enhanced RSI Divergence detector built with Pine Script v6, modified for better visuals and practical usability. It uses linear regression to detect bullish and bearish divergences between the RSI and price action — one of the most reliable early signals in technical analysis.
✅ Improvements from the Original:
- Clean divergence lines using regression fitting.
- Optional label display to reduce clutter (Display Labels toggle).
- Adjustable line thickness (Display Line Width).
- A subtle heatmap background to highlight RSI overbought/oversold zones.
- Uses max accuracy with high calc_bars_count and custom extrapolation window.
🔍 How It Works: The script applies linear regression (least squares method) on both RSI data, and Price (close) data.
It then compares the direction of RSI vs. direction of Price over a set length. If price is making higher highs while RSI makes lower highs, it's a bearish divergence. If price is making lower lows while RSI makes higher lows, it's a bullish divergence. Additional filters (e.g., momentum and slope thresholds) are used to validate only strong divergences.
🔧 Input Parameters: RSI Length: The RSI period (default: 14). RSI Divergence Length: The lookback period for regression (default: 25). Source: Which price data to calculate RSI from (default: close). Display Labels: Show/hide “Bullish” or “Bearish” labels on the chart. Display Line Width: Adjusts how thick the plotted divergence lines appear.
📣 Alerts: Alerts are built-in for both RSI Buy (bullish divergence) and RSI Sell (bearish divergence) so you can use it in automation or notifications.
🚀 Personal Note: I’ve been using this script daily in my own trading, which is why I took time to improve both the logic and visual clarity. If you want a divergence tool that doesn't clutter your chart but gives strong signals, this might be what you're looking for.
Heatmap Trailing Stop with Breakouts (Zeiierman)█ Overview
Heatmap Trailing Stop with Breakouts (Zeiierman) is a trend and breakout detection tool that combines dynamic trailing stop logic, Fibonacci-based levels, and a real-time market heatmap into a single, intuitive system.
This indicator is designed to help traders visualize pressure zones, manage stop placement, and identify breakout opportunities supported by contextual price–derived heat. Whether you're trailing trends, detecting reversals, or entering on explosive breakouts — this tool keeps you anchored in structure and sentiment.
It projects adaptive trailing stop levels and calculates Fibonacci extensions from swing-based extremes. These levels are then colored by a market heatmap engine that tracks price interaction intensity — showing where the market is "hot" and likely to respond.
On top of that, it includes breakout signals powered by HTF momentum conditions, trend direction, and heatmap validation — giving you signals only when the context is strong.
█ How It Works
⚪ Trailing Stop Engine
At its core, the script uses an ATR-based trailing stop with trend detection:
ATR Length – Defines volatility smoothing using EMA MA of true range.
Multiplier – Expands/retracts the trailing offset depending on market aggression.
Real-Time Extremum Tracking – Uses local highs/lows to define Fibonacci anchors.
⚪ Fibonacci Projection + Heatmap
With each trend shift, Fibonacci levels are projected from the new swing to the current trailing stop. These include:
Fib 61.8, 78.6, 88.6, and 100% (trailing stop) lines
Heatmap Coloring – Each level'slevel's color is determined by how frequently price has interacted with that level in the recent range (defined by ATR).
Strength Score (1–10) – The number of touches per level is normalized and averaged to create a heatmap ""score"" displayed as a colored bar on the chart.
⚪ Breakout Signal System
This engine detects high-confidence breakout signals using a higher timeframe candle structure:
Bullish Breakout – Strong bullish candle + momentum + trend confirmation + heatmap score threshold.
Bearish Breakout – Strong bearish candle + momentum + trend confirmation + heatmap score threshold.
Cooldown Logic – Prevents signals from clustering too frequently during volatile periods.
█ How to Use
⚪ Trend Following & Trail Stops
Use the Trailing Stop line to manage positions or time entries in line with trend direction. Trailing stop flips are highlighted with dot markers.
⚪ Fibonacci Heat Zones
The projected Fibonacci levels serve as price magnets or support/resistance zones. Watch how price reacts at Fib 61.8/78.6/88.6 levels — especially when they're glowing with high heatmap scores (more glow = more historical touches = stronger significance).
⚪ Breakout Signals
Enable breakout signals when you want to trade breakouts only under strong context. Use the "Heatmap Strength Threshold" to require a minimum score (1–10).
█ Settings
Stop Distance ATR Length – ATR period for volatility smoothing
Stop Distance Multiplier – Adjusts the trailing stop'sstop's distance from price
Heatmap Range ATR Length – Defines how far back the heatmap scans for touches
Number of Heat Levels – Total levels used in the heatmap (more = finer resolution)
Minimum Touches per Level – Defines what counts as a ""hot"" level
Heatmap Strength Threshold – Minimum average heat score (1–10) required for breakouts
Timeframe – HTF source used to evaluate breakout momentum structure
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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.
Ultra VolumeVisualizes volume intensity using dynamic color gradients and percentile thresholds. Includes optional SMA, bar coloring, and adaptive liquidity boxes to highlight high- and low-volume zones in real time.
Introduction
The Ultra Volume indicator enhances volume analysis by categorizing volume bars into percentile-based intensity levels. It uses color-coded gradients to quickly identify periods of unusually high or low activity. The script also includes an optional simple moving average (SMA), bar coloring, and visual box overlays to highlight zones of significant liquidity shifts.
Detailed Description
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Volume Classification
Volume is segmented into five tiers: Extra High, High, Medium, Normal, and Low, using percentile ranks calculated over a dynamically adjusted historical window. This segmentation adapts based on the chart's timeframe – using 100 bars for daily and 1440/minutes for intraday – allowing for consistent behavior across resolutions.
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Color Gradients
Each volume bar is colored based on its percentile category, smoothly transitioning between thresholds for visual clarity. This makes it easy to spot volume spikes or droughts relative to recent history.
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Simple Moving Average (SMA)
An optional SMA can be plotted on top of the volume bars for trend comparison and baseline reference. Its length and color are fully customizable.
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Bar Coloring
You can optionally color the chart's candlesticks to reflect the same volume intensity as the histogram bars, reinforcing visual cues across the chart.
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Liquidity Boxes
Two adaptive box systems highlight zones of increased or decreased liquidity:
High Liquidity Boxes expand upward when price exceeds the previous box’s top.
Low Liquidity Boxes expand downward when price breaks the previous box’s bottom.
These boxes persist and auto-adjust over time unless reset, helping traders spot key zones of volume-driven price action.
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Box Indexing
A configurable index shift determines how far back in the chart the boxes originate. Setting this to 501 makes them "stick" to the candle where they were first created.
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Data Handling
A safety check ensures the script throws an error if volume data is unavailable (e.g., for some crypto or CFD symbols).
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Summary
Ultra Volume is a practical tool for traders who want more than just raw volume bars. With intelligent percentile-based classification, real-time adaptive liquidity zones, and fully customizable visual elements, it turns volume into a highly readable, actionable signal.
Liquidation Heatmap ║ BullVision 🧠Overview
The Liquidation Heatmap ║ BullVision 💥 is a high-precision visualization tool engineered to highlight probable liquidation levels in crypto markets. It leverages multi-exchange Open Interest data, real-time volume dynamics, and structure-aware volatility signals to reveal where leveraged traders are most at risk of forced position closures.
📖 What Are Liquidations?
In leveraged derivatives markets, a liquidation occurs when a trader’s margin becomes insufficient to maintain their position, triggering an automatic force-close by the exchange. These events are typically clustered around price levels where large volumes of overleveraged positions accumulate. When breached, they often result in sharp, aggressive price movements — also known as liquidation cascades.
This indicator is designed to detect and project such high-risk zones before they trigger, giving traders an edge in visualizing hidden pressure points in the market.
🧠 How It Works
The core engine aggregates real-time ∆OI (Open Interest delta) data from multiple major exchanges and applies a layered filtering system that considers:
Relative Open Interest shifts, normalized against an adaptive moving average baseline
Volume acceleration patterns, compared to a rolling historical benchmark
Market structure context, identifying meaningful directional breaks and failed retests
Leverage-tier modeling, using probabilistic distance rules to simulate where liquidations from 5x to 100x positions would be triggered
Each qualifying liquidation level is rendered using dynamic gradient lines and optional glow-enhanced zone visuals. The display adapts in real time to structural confirmation, volatility regime, and liquidity depth.
Exemple of Liquidation cascades
Exemple of Liquidation rejection
🔍 Key Features
🔗 Multi-Exchange OI Aggregation: Binance, OKX, BitMEX, Kraken (toggleable)
📊 Leverage-Tier Mapping: 5x, 10x, 25x, 50x, 100x projections
🎨 Gradient Zones: Custom color ramps reflect level significance
🧱 Structure-Sensitive Filtering: Noise reduction via multi-condition confirmation logic
🧠 Contextual Directional Bias: Zones filtered based on recent bullish/bearish transitions
⚙️ Fully Customizable: User-defined intensity thresholds, color palette, and range filtering
🧩 Why It’s Worth Paying For
This is not a mashup of public indicators. The script introduces an original, multi-layered architecture combining real-time Open Interest dynamics, structural analysis, and custom liquidation modeling.
Unlike speculative support/resistance plots or volume-only heatmaps, this tool is built to:
Detect liquidation zones before they cascade
React dynamically to market shifts
Filter noise through structural confirmation
Retain historical zones for visual learning and backtesting
✅ Compliance & Originality
This script was developed entirely in-house with original detection logic. No reused open-source components are included. Data requests are made through TradingView’s native .P_OI feeds, and all calculations, signal conditions, and visual logic were coded from scratch for this script.
⚠️ Risk Disclaimer & Access Policy
This script is a visual risk-awareness tool, not a signal generator or financial advice mechanism. No guarantee is made regarding future price action, liquidation triggers, or trading performance.
Use at your own discretion, with proper position sizing, risk management, and awareness of the market's inherent uncertainty.
🔒 Why This Script Is Invite-Only and Closed-Source
To protect its proprietary detection engine, this script is both closed-source and invite-only. The algorithm uses original methods to:
Aggregate real-time Open Interest delta across exchanges
Simulate leverage-based liquidation zones
Dynamically filter zones using structure and volatility layers
Opening the source would expose core detection logic to copycats or misuse. Likewise, access is limited to ensure the tool is used responsibly by serious traders and not distributed or repackaged unethically.
This model preserves the script’s quality, originality, and intended value.
Cointegration Heatmap & Spread Table [EdgeTerminal]The Cointegration Heatmap is a powerful visual and quantitative tool designed to uncover deep, statistically meaningful relationships between assets.
Unlike traditional indicators that react to price movement, this tool analyzes the underlying statistical relationship between two time series and tracks when they diverge from their long-term equilibrium — offering actionable signals for mean-reversion trades .
What Is Cointegration?
Most traders are familiar with correlation, which measures how two assets move together in the short term. But correlation is shallow — it doesn’t imply a stable or predictable relationship over time.
Cointegration, however, is a deeper statistical concept: Two assets are cointegrated if a linear combination of their prices or returns is stationary , even if the individual series themselves are non-stationary.
Cointegration is a foundational concept in time series analysis, widely used by hedge funds, proprietary trading firms, and quantitative researchers. This indicator brings that institutional-grade concept into an easy-to-use and fully visual TradingView indicator.
This tool helps answer key questions like:
“Which stocks tend to move in sync over the long term?”
“When are two assets diverging beyond statistical norms?”
“Is now the right time to short one and long the other?”
Using a combination of regression analysis, residual modeling, and Z-score evaluation, this indicator surfaces opportunities where price relationships are stretched and likely to snap back — making it ideal for building low-risk, high-probability trade setups.
In simple terms:
Cointegrated assets drift apart temporarily, but always come back together over time. This behavior is the foundation of successful pairs trading.
How the Indicator Works
Cointegration Heatmap indicator works across any market supported on TradingView — from stocks and ETFs to cryptocurrencies and forex pairs.
You enter your list of symbols, choose a timeframe, and the indicator updates every bar with live cointegration scores, spread signals, and trade-ready insights.
Indicator Settings:
Symbol list: a customizable list of symbols separated by commas
Returns timeframe: time frame selection for return sampling (Weekly or Monthly)
Max periods: max periods to limit the data to a certain time and to control indicator performance
This indicator accomplishes three major goals in one streamlined package:
Identifies stable long-term relationships (cointegration) between assets, using a heatmap visualization.
Tracks the spread — the difference between actual prices and the predicted linear relationship — between each pair.
Generates trade signals based on Z-score deviations from the mean spread, helping traders know when a pair is statistically overextended and likely to mean revert.
The math:
Returns are calculated using spread tickers to ensure alignment in time and adjust for dividends, splits, and other inconsistencies.
For each unique pair of symbols, we perform a linear regression
Yt=α+βXt+ε
Then we compute the residuals (errors from the regression):
Spreadt=Yt−(α+βXt)
Calculate the standard deviation of the spread over a moving window (default: 100 samples) and finally, define the Cointegration Score:
S=1/Standard Deviation of Residuals
This means, the lower the deviation, the tighter the relationship, so higher scores indicate stronger cointegration.
Always remember that cointegration can break down so monitor the asset over time and over multiple different timeframes before making a decision.
How to use the indicator
The heatmap table:
The indicator displays 2 very important tables, one in the middle and one on the right side. After entering your symbols, the first table to pay attention to is the middle heatmap table.
Any assets with a cointegration value of 25% is something to pay attention to and have a strong and stable relationship. Anything below is weak and not tradable.
Additionally, the 40% level is another important line to cross. Assets that have a cointegration score of over 40% will most likely have an extremely strong relationship.
Think about it this way, the higher the percentage, the tighter and more statistically reliable the relationship is.
The spread table:
After finding a good asset pair using heatmap, locate the same pair in the spread table (right side).
Here’s what you’ll see on the table:
Spread: Current difference between the two symbols based on the regression fit
Mean: Historical average of that spread
Z-score: How far current spread is from the mean in standard deviations
Signal: Trade suggestion: Short, Long, or Neutral
Since you’re expecting mean reversion, the idea is that the spread will return to the average. You want to take a trade when the z-score is either over +2 or below -2 and exit when z-score returns to near 0.
You will usually see the trade suggestion on the spread chart but you can make your own decision based on your risk level.
Keep in mind that the Z-score for each pair refers to how off the first asset is from the mean compared to the second one, so for example if you see STOCKA vs STOCKB with a Z-score of -1.55, we are regressing STOCKB (Y) on STOCKA (X).
In this case, STOCKB is the quoted asset and STOCKA is the base asset.
In this case, this means that STOCKB is much lower than expected relative to STOCKA, so the trade would be a long position on stock B and short position on stock A.
Liqudation HeatMap [BigBeluga]🔵 OVERVIEW
An advanced liquidity visualization tool that plots horizontal heat zones to highlight where potential liquidations and volume clusters are most likely hiding beneath price action.
Liqudation HeatMap scans historical price movements for local highs and lows with elevated volume or candle range. It then draws dynamic heatmap boxes—shaded from lime (low interest) to yellow (high interest)—revealing potential zones of trapped positions or stop clusters. A vertical scale on the right shows you the relative strength of volume behind each level, from 0 to the highest detected.
🔵 CONCEPTS
Maps areas of potential liquidity using volume or candle range (if volume is unavailable).
Identifies swing highs/lows (pivots) and extends heatmap boxes outward from these levels. Colors each zone based on the relative strength of volume concentration.
Fades or removes zones once price crosses their midpoints, simulating the idea of liquidity being “consumed.”
Displays a live vertical scale that shows the volume range for quick reference.
🔵 FEATURES
Dynamic Heatmap Zones:
Draws few boxes above and after pivot highs and below pivot lows, each shaded based on volume concentration.
Smart Coloring System:
Uses a gradient from lime (low) to yellow (high) to visually distinguish between weak and strong liquidity zones.
Adaptive ATR Widths:
Automatically adjusts zone thickness based on volatility (ATR), scaling intelligently across timeframes.
Liquidity Consumption Logic:
Zones are stope extending once price interacts with them—mimicking the behavior of real liquidation sweeps.
Volume Scale Legend:
A real-time scale is plotted on the right side, showing the min-max range of volume used for heat calculations.
🔵 HOW TO USE
Look for thick yellow zones to identify areas of concentrated stop losses or liquidation triggers.
Use these levels to anticipate mean reversion points or high-volatility zones.
Combine with your trend or structure tools to trade into or fade these liquidity pools.
On lower timeframes, use this tool to confirm entries around sweeps or deviations.
Use the right-side scale to compare relative zone strength instantly.
🔵 CONCLUSION
Liqudation HeatMap is a powerful visualization tool that uncovers where liquidity likely resides on the chart. By highlighting hidden traps and reactive levels in real-time, it gives traders a significant edge when it comes to spotting stop hunts, mean reversions, and areas of institutional interest. Whether you’re scalping or swing trading, this heatmap provides unmatched context on the market’s hidden intent.
