XRayXRay is a comprehensive earnings analysis table for TradingView that displays historical quarterly earnings data, year-over-year growth trends, and future estimates in an easy-to-read format directly on your chart.
Column & Description
✅ Date - Earnings report date (MMM-YY format)
✅ EPS ($) - Actual earnings per share in dollars
✅ %Chg (YoY) - EPS year-over-year percentage change
✅ Sales (Mil) - Total revenue in millions
✅ %Chg (YoY) - Sales year-over-year percentage change
✅ Price - Configurable: earnings day close, next trading day close, or current price
✅ %Chg (YoY) - Stock price year-over-year percentage change
Benefits:
✅ All-in-one earnings dashboard - No need to leave your chart
✅ Smart visual encoding - Color, bold, symbols make patterns obvious
✅ Flexible configuration - Adapts to your trading style
✅ Future-looking - Includes analyst estimates for next quarter
Use Cases:
✅ Quick earnings screening - Instantly see growth trends across multiple quarters
✅ Fundamental analysis - Track sales and earnings consistency
✅ Growth acceleration detection - Spot companies accelerating or decelerating
✅ Earnings quality assessment - Compare actual vs. estimates
✅ Position sizing decisions - Evaluate risk based on earnings volatility
✅ Long-term trend analysis - See up to 20 quarters of historical performance
Heatmap
ZenAlgo - SqueezeThis indicator is a separate-pane tool that reads the current chart symbol (treated as the traded instrument, typically a perpetual) and optionally reads a second symbol used as a comparison reference. It can operate in two broad modes:
Basis on - the script attempts to obtain a "spot or reference" close and compares the chart close against it.
Basis off - all basis related parts are disabled and only the on-chart derived components remain.
The comparison reference can be selected via presets (dominance and market cap style tickers, BTC perpetual, etc.) or via a manual symbol selector. There is also an optional second comparison line that is visual-only and does not influence the squeeze logic.
Spot and reference selection, including safety and fallback
When basis mode is enabled, the script needs a valid comparison close series. It supports three ways to obtain it:
Manual selection - you choose a specific reference symbol or one of the provided presets.
Auto spot from the chart symbol - the script strips the ".P" suffix from the chart ticker to guess a spot ticker (fast, but can be invalid on some symbols or spread charts).
Exchange fallback chain - if the manual request fails to return data, the script tries a hardcoded sequence of exchanges for the same base pair (same exchange prefix first, then Binance, then Bybit, then MEXC, then Bitget). It uses requests that ignore invalid symbols so the script fails gracefully into the next option. Spread-style synthetic tickers are detected and excluded from this fallback process.
Why this matters: basis style comparisons are only meaningful when the reference series is actually available and aligned to the same timeframe. The script spends a lot of logic on preventing runtime failures and preventing accidental "fake basis" on unsupported tickers.
VWAP with standard deviation bands on multiple reset schedules
The next major block computes anchored VWAP states for several higher-level periods. The core approach is:
It performs a running, volume-weighted accumulation of typical price for the anchor period.
It simultaneously accumulates the second moment needed to estimate dispersion around VWAP, producing a standard deviation estimate around the anchored VWAP.
On each reset boundary (daily, weekly, monthly, quarterly, semiannual, yearly), the accumulators reset and begin a new anchored VWAP segment.
Why this matters: anchored VWAP is treated here as a rolling "fair value" for the current period. The dispersion estimate is used to convert distance from VWAP into discrete states (premium, discount, etc.) instead of relying on raw price distance, which varies widely across assets.
Smoothed average line used as a slower trend filter
Alongside the anchored VWAPs, the script builds a slow baseline from the chart close using a two-stage smoothing process. This baseline is then used as a slower reference for trend qualification.
Why this matters: the trend logic requires alignment between price, the daily anchored VWAP, and this slower baseline, plus confirmation that both the daily VWAP and the slow baseline are rising or falling. This avoids classifying trend from price position alone.
Trend classification used for context labeling
Trend is classified as:
Bull trend when price is above the daily anchored VWAP, the daily anchored VWAP is above the slow baseline, and both the daily VWAP and the slow baseline are rising.
Bear trend when price is below the daily anchored VWAP, the daily anchored VWAP is below the slow baseline, and both are falling.
If neither is true, the script treats trend as neutral for its table and for squeeze sub-labeling.
Why this matters: the script later distinguishes events that align with the prevailing trend versus those that run against it.
VWAP state mapping and heatmap rows
For each anchored VWAP (D, W, M, Q, S, Y), the script assigns a discrete state label based on where price is relative to VWAP and how many dispersion units away it is. The state labels include:
Above, Below
Premium and Discount tiers
"Super" and "Mega" tiers for more extreme distances
These states are turned into colors using a selected palette preset. The script then draws horizontal "heat" lines at fixed Y offsets inside the indicator pane, one row per anchor timeframe, plus optional row-letter labels that also show whether the anchored VWAP is rising, falling, or stable.
How to interpret:
The heatmap is not a price plot. It is a categorical summary of where current price sits relative to each anchored VWAP and its dispersion.
Multiple rows allow you to see whether price is simultaneously extended on short anchors but neutral on long anchors, or vice versa.
Normalized metrics used for squeeze detection and plots
The script computes several standardized (z-scored) series over a fixed lookback length:
Chart close z-score - how far the current close is from its recent mean in standardized units.
Reference close z-score - same standardization on the chosen comparison series (only when basis is enabled and reference exists).
Basis percentage z-score - derived from the ratio between chart close and the reference close, transformed into percent difference, then standardized.
Delta proxy z-score - a signed volume proxy that assigns positive weight on up candles, negative weight on down candles, and zero on unchanged candles, then standardized. For symbols with missing volume, it can fall back to a constant weight of 1 depending on settings.
Why this matters:
The use of z-scores makes thresholds portable across assets and regimes. Instead of using raw basis percent or raw volume, the script detects whether each component is unusually large relative to its own recent distribution.
Squeeze event conditions and "continuation vs countertrend" labeling
The core squeeze events are defined by three simultaneous conditions, each compared to a fixed threshold:
Price is moving fast enough (rate-of-change threshold).
Basis deviation is large enough in one direction (basis z-score threshold).
Delta proxy deviation is large enough in the same direction (delta z-score threshold).
When these align to the upside, the script calls it a short squeeze event (upward acceleration with positive basis and positive delta proxy abnormality). When they align to the downside, it calls it a long squeeze event (downward acceleration with negative basis and negative delta proxy abnormality).
Volume availability handling:
You can hard-disable squeeze detection on symbols where volume is missing.
Or you can allow it, in which case the delta proxy uses a fallback weight so the pipeline still functions.
Continuation vs countertrend:
Each squeeze event is classified relative to the trend state described earlier.
A squeeze that agrees with the trend is marked as continuation.
A squeeze that opposes the trend is marked as countertrend.
Visual output tied to squeezes:
Optional dots are plotted near the top or bottom of the pane to indicate event type (short vs long, continuation vs countertrend).
Optional candle coloring is applied only during squeeze states, using separate colors for continuation bull, continuation bear, and countertrend.
Basis vs chosen comparison relationship on fixed timeframes
In addition to the main squeeze logic, the script evaluates how the basis z-score compares to the chosen reference z-score on four fixed intraday timeframes (5m, 15m, 1h, 4h). For each timeframe it assigns a simple state:
Basis standardized value above the reference standardized value
Basis standardized value below the reference standardized value
Equal or unavailable
These states are primarily used to color table cells as a compact multi-timeframe context readout.
Why this matters: it provides a quick view of whether the basis deviation is leading or lagging the chosen reference across multiple granularities, without changing the main squeeze definitions.
Cross between basis and chosen reference
When enabled and basis is available, the script detects crosses between:
Basis z-score line
Chosen reference z-score line
It can plot small up or down triangles on the basis plot when the basis standardized value crosses above or below the reference standardized value. The triangle color is tied to the daily VWAP heat color so the marker inherits the daily premium/discount context.
Why this matters: it isolates regime changes where the basis deviation becomes stronger or weaker than the reference series in standardized terms, which can be used as a context shift rather than a standalone entry indication.
Pane plots, fills, and thresholds
The indicator pane can show:
The chart close z-score line (perp series).
The chosen reference z-score line (compare series, when available).
The basis z-score line.
The optional second comparison z-score line.
A background fill is drawn between the chart close z-score and the reference z-score to visualize which is higher at the moment. Horizontal reference lines are also drawn for:
The basis z-score thresholds used for squeeze logic.
The delta proxy z-score thresholds used for squeeze logic.
Zero line and additional guide lines at several standardized levels.
How to interpret values:
The plotted values are standardized units relative to each series’ own recent distribution.
A value around 0 indicates "near recent average."
Large positive or negative values indicate "unusually above or below recent average" for that specific series.
Table readout and derived bias score
A table can be shown in the top-right of the pane, summarizing:
Current mode (basis off, auto spot, or which preset/manual reference is in use).
Whether basis data is valid.
Trend state and a slope warning/ok flag.
Daily and weekly anchored VWAP numeric values and their premium/discount state coloring.
A daily vs weekly VWAP difference state.
Price rate-of-change state.
Basis percent value and basis z-score state.
Delta proxy z-score state.
Chart close z-score state.
Reference z-score state.
A composite bias score and text label.
The four timeframe basis-vs-reference relationship states (5m, 15m, 1h, 4h).
The score is then mapped to labels from strong bearish through neutral to strong bullish, optionally appending the most recent squeeze classification when present.
Right-side value tags
On the last bar, the script can draw short horizontal lines and labels to the right showing the latest values for:
Chart close z-score
Reference z-score
Basis z-score
Optional second comparison z-score
These tags are offset a user-selected number of bars into the future so they remain readable.
"Best" block and alert conditions
A final logic layer uses:
Two fixed thresholds on the basis z-score (one associated with an "up" cross and one with a "down" cross).
A count of how many enabled VWAP heatmap rows are currently in "hot" states (above or premium tiers) vs "cold" states (below or discount tiers).
A recent-squeeze filter that checks whether any squeeze event happened within a defined lookback window.
It then plots:
Small circles for threshold crosses when at least a minimum hot/cold alignment exists.
Diamonds when alignment exists, optionally larger when alignment count is higher.
Separate diamonds when the threshold cross happens without a recent squeeze.
Alert conditions are provided for:
Strong "best" diamonds when alignment meets a higher minimum.
Optional alerts for "best" threshold crosses without recent squeezes.
Optional alerts for basis-vs-reference z-score crosses.
Why this matters: it gates threshold events by broader multi-anchor context, attempting to avoid treating a single standardized cross as equally meaningful in every macro positioning regime.
Added value over common free indicators
This script combines several components that are often separate in typical tools, and it enforces explicit data-availability safeguards:
Anchored VWAP states across multiple calendar resets with an internal dispersion estimate and a compact heatmap summary.
Basis style comparison that can be driven by multiple preset market references, with a fallback chain across exchanges and explicit spread-chart protection.
Squeeze detection that requires simultaneous agreement across price acceleration, basis deviation, and a signed volume proxy deviation, then labels the event by trend alignment.
A unified pane where standardized series, thresholds, heatmap context, and table diagnostics are all consistent with the same internal state.
Disclaimers and where it can fall short
If the chosen reference symbol is unavailable or returns gaps, basis-dependent outputs can be unavailable or may switch to fallback sources depending on settings. This can change the basis series behavior compared to a strictly fixed reference feed.
The delta component is a proxy based on candle direction and volume, not an exchange order-flow delta. On symbols with unreliable volume, enabling fallback weighting can keep the indicator running but reduces the meaning of "volume-driven" parts.
Standardized values depend on the chosen lookback. In highly non-stationary regimes, what is "unusual" can shift quickly.
Anchored VWAP states depend on reset definitions in UTC. If your trading session expectations are tied to different session boundaries, interpret anchor transitions accordingly.
How to best use it
Start by verifying Basis OK in the table when basis mode is enabled. If it shows an error state, either switch reference mode, disable basis, or enable fallback if appropriate for your symbol.
Use the heatmap rows to understand whether price is extended relative to multiple anchored baselines simultaneously or only on short anchors.
Treat squeeze dots and candle coloring as event markers, then use the trend label (continuation vs countertrend) and the VWAP states to decide whether the event aligns with your broader plan.
Use basis vs chosen crosses and the basis-vs-reference multi-timeframe states as context shifts, not as isolated triggers.
If you enable alerts, prefer those that include the multi-row hot/cold alignment gating when you want fewer, more context-filtered notifications.
NSE: N50, BN, MIDCAP, FINNIFTY HEATMAP Jitendra
Overview Summary of This Indicator
This indicator displays Heatmap Style Table, showing Top Gaining and Losing stocks Across Major NSE Derivatives indices.
It Has Option for NIFTY 50, BANK NIFTY, FINANCIAL NIFTY, MIDCAP SELECT That available For Index Derivatives Trading.
It is Divided in to Symbol Groups
In Setting Under Select Symbol Option categorized with Options
Nifty Top 39 -High Weight Stocks
Nifty Rest 11-Remaining 11 Nifty stocks Low Weightage
Bank Nifty
Financial Services
Midcap Select
All Stock Used in Script is As per Latest Data Published by NSE, you can also check by clicking below link
www.niftyindices.com
Key Features / What This Indicator Does
It Has Two Display Modes
Full Table = Shows each stock’s name and its daily % change, sorted from top gainer to top loser.
Compact Count Table = Shows just total number of gainers vs losers.
It Helps identify Index Leader Looser Script and Overall Sentiment
Quickly spot momentum stocks for intraday trades
Saves time — no need to scan multiple charts
Customization Options
Select Index group
Choose sorting order
Switch % or point change
Table position control
Text size control
Enable/Disable full table or compact panel
Setting Details Snapshot / Image
Heatmap Table in Point Change View
Summary: Data Fetch in Table Code
Multi-Symbol Processing
All symbols are stored in predefined arrays (Nifty, Bank Nifty, Financials, Midcaps, etc.)
The script loops through the selected symbol list
Each stock is processed using request.security() independently
For every stock in the selected index or sector list, the script requests:
Current Close Price
Previous Day Close Price
This ensures that Data is always based on Daily candles
Values remain consistent across all chart timeframes
= request.security(symbol, "D", [close, close ])
Change Calculation
Depending on user selection, the script computes either:
Percentage Change
percentChange = (close - prevClose) / prevClose * 100
Point Change
pointChange = close - prevClose
Market Breadth Calculation
Gainers and losers are counted during the data loop
gainers += change > 0 ? 1 : 0
losers += change < 0 ? 1 : 0
Thanks
Trading View Community
Pivot-Anchored Liquidity Heatmap
**PLEASE READ: After adding indicator to chart, right click on indicator or click on "more"(3 dots to right of indicator name), hover over "pin to scale", and select "Pinned to right scale**
The indicator tries to show you where price has repeatedly reacted (pivoted) and treats those prices like liquidity shelves (places where lots of orders tend to sit).
It scans the last Calculated Bars and builds a price range it cares about, then splits that range into Bins (price slices). Every time price makes a local swing high or swing low, it drops that event into the nearest bin and adds weighted volume to that bin (bigger/more convincing rejections count more). Bins with enough activity become significant levels using one rule: % above the average bin (30% = more levels, 50% = default balance, 75% = only the biggest shelves). That same rule also controls alerts.
What you see on the chart:
* Profile bars (the little horizontal blocks) = strength at that price bin.
* Heatmap lines (horizontal lines extending left) = those same levels projected across time.
* Color: green-ish = support side (below price), red-ish = resistance side (above price). Stronger = more intense.
* Opacity + thickness: stronger levels look more solid and thicker; weaker levels are faint.
* POC (if on) = the single strongest bin (most activity) highlighted in white. Acts as a magnet. Especially important when it shifts above or below price.
* Bin text can show raw volume or notional ($ value approx = volume × price), or nothing.
Two “smart” behaviors (learning):
* Pressure Context: watches candle behavior (body size, volume vs average, CMF-like flow, volatility regime) to guess whether buying or selling pressure is dominant, then boosts levels that align with that pressure and dampens levels that fight it.
* Pulled Orders Simulation: if price gets close to a level and pressure suggests it won’t hold, the indicator temporarily shrinks that level (as if orders were pulled). If price backs off or pressure aligns again, it rebuilds.
Alerts:
* Fires when price touches a significant level (based on the same significance threshold), optionally only on bar close.
Simple Rules:
* Monitor the "POC". It is especially important to pay attention when it shifts above or below price as the level tends to act as a magnet.
* Treat bright/thick levels as decision zones, not exact lines: price often wicks through then reacts.
* If price is below a strong red level → expect resistance (pullbacks/rejections).
* If price is above a strong green level → expect support (bounces/holds).
* Best beginner play: wait for reaction + confirmation (bounce candle at support / rejection candle at resistance), not just a touch.
* If a level fades/shrinks as price approaches, that’s the tool hinting: this shelf may be getting “pulled” and could break; be cautious about blindly buying/selling the first touch.
Malama's Institutional Liquidity & Price Action Concepts [ILPAC]Malama's Institutional Liquidity & Price Action Concepts is a comprehensive trading suite that unifies the three pillars of institutional analysis: Market Structure (Context), Liquidity (Targets), and Momentum (Triggers).
Justification for this Combination (The Mashup): Many traders clutter their screens with separate indicators for BOS/CHoCH, Liquidity Runs, and RSI divergences. This fragmentation makes it difficult to see the full narrative. ILPAC solves this by fusing these concepts into a single logic engine. By combining structure with liquidity heatmaps, the script allows you to see where price is going (Liquidity) and when the trend has shifted (Structure) without conflicting visual noise.
Optimizations & Fixes in This Version:
Unified Garbage Collection: Previous iterations of complex scripts often suffer from memory leaks. This version runs a global cleanup function every bar to manage lines and labels, ensuring smooth performance even on lower timeframes.
State-Machine BOS Logic: The Break of Structure (BOS) logic has been upgraded to a state machine. It tracks "Active Pivot Levels" and only fires a signal when a level is physically broken by a close, preventing repainting or flickering signals during live candles.
Physical Liquidity Sweeps: The Liquidity Heatmap now calculates the physical height of the zone in ticks. A zone is only considered "Swept" (mitigated) if price penetrates the interior of the box, not just touches the edge.
Deduplicated Psychological Levels: The logic for round numbers (Psychological Levels) now scans existing drawings to prevent stacking duplicate lines on top of each other when price consolidates around a key level.
Concepts & Underlying Calculations:
Market Structure: Identifies Swing Highs and Lows using a customizable lookback. A "Change of Character" (CHoCH) is flagged when the trend state flips from Bullish to Bearish (or vice versa), while a "Break of Structure" (BOS) indicates trend continuation.
Liquidity Heatmap: Automatically identifies unmitigated swing points where stop-losses are likely clustered. These are drawn as dynamic boxes that extend until price sweeps them.
FOMO Bubbles: A proprietary momentum filter that combines RSI extremes (Overbought/Oversold) with Volume Spikes (Volume > 2x Average). These bubbles highlight moments of retail panic or euphoria, often marking local tops or bottoms.
Auto-Trendlines: Connects the most recent non-breached pivots to project dynamic support and resistance channels.
How to Use:
Identify the Trend: Look for the Market Structure labels (HH, LL) and the colored structure lines (Green for Bullish, Red for Bearish).
Find the Target: Look for the Gold (High) or Blue (Low) Liquidity Zones. Price often gravitates toward these areas to clear liquidity before reversing.
Spot the Trigger: Use the FOMO Bubbles or Trendline Breakouts as your entry confirmation once price reaches a liquidity zone.
Disclaimer: This indicator is for educational analysis only. Past performance does not guarantee future results.
Professional Multi-Asset Market Dashboard [Heatmap]Description:
This comprehensive Market Dashboard provides traders with a high-level overview of the entire financial landscape in a single, organized table. Designed to replicate institutional-grade market scanners, this tool allows you to monitor 30+ assets across multiple categories (Commodities, Global Equities, Indices, and Sectors) without switching charts.
It is specifically optimized for Essential (Pro) plans and above, utilizing efficient coding to fit within the request.security limits while delivering maximum data density.
Key Features
4-Section Layout: Automatically organizes data into clear categories:
Equity Alternatives: Commodities, Bonds, Currencies (DXY), and Crypto.
Global Equities: Emerging Markets, International, and European stocks.
US Equity Indices: Major US benchmarks (SPY, QQQ, DIA, IWM) and factors.
Sectors: A complete breakdown of US sectors (Energy, Tech, Financials, etc.).
Heatmap Visualization:
Bullish (Green): Indicates positive performance or strong trends.
Bearish (Red): Indicates negative performance or weak trends.
Neutral (Gray): Indicates choppy or sideways action.
Advanced Metrics:
% Chg: Daily percentage move.
ATRΔ (Volatility): Measures today's range relative to the 14-day Average True Range. A value > 1.0 means higher than average volatility.
DCR (Daily Closing Range): Shows where the price closed relative to the day's high/low. (0% = Low of day, 100% = High of day).
52WR: Position within the 52-week range.
MAx: Distance from the 20-day Moving Average.
Trend Codes:
ST (Short Term): Based on the 20 SMA.
LT (Long Term): Based on the 200 SMA.
100% Customizable:
Toggle Rows: Use checkboxes in the settings to hide/show specific assets.
Custom Symbols: Change any ticker to fit your personal watchlist.
Design Control: Customize colors, text size, and table position on the chart.
How to Use
Add to Chart: The dashboard defaults to a "Bottom Center" position.
Interpret the Trend:
Look for the ST (Short Term) and LT (Long Term) columns.
"1A" indicates a confirmed Bullish Trend (Price > SMA).
"4C" indicates a confirmed Bearish Trend (Price < SMA).
Analyze Breadth: Use the color coding to instantly gauge if the market is "Risk On" (mostly green) or "Risk Off" (mostly red).
Volatility Check: Use the ATRΔ column to spot assets that are moving significantly more than their average daily range.
Settings Configuration
Inputs Tab: Uncheck the box next to any symbol to hide it from the table. You can also rename the headers or change the tickers to your preferred assets (e.g., swapping Futures for ETFs).
Style Tab: Adjust the table size (tiny, small, normal) to fit your screen resolution.
Disclaimer: This indicator is for informational purposes only and does not constitute financial advice. Past performance is not indicative of future results.
Unmitigated MTF High Low Pro - Cave Diving Bookmap Heatmap Plot
Unmitigated MTF High Low Pro - Cave Diving Bookmap Heatmap Plot
---
## 📖 Table of Contents
1. (#what-this-indicator-does)
2. (#core-concepts)
3. (#visual-components)
4. (#the-cave-diving-framework)
5. (#how-to-use-it-for-trading)
6. (#settings--customization)
7. (#best-practices)
8. (#common-scenarios)
---
## What This Indicator Does
The **Unmitigated MTF High Low v2.0** tracks unmitigated (untouch) high and low levels across multiple timeframes, helping you identify key support and resistance zones that the market hasn't revisited yet. Think of it as a sophisticated memory system for price action - it remembers where price has been, and more importantly, where it *hasn't been back to*.
### Why "Unmitigated" Matters
In futures trading, especially on instruments like NQ and ES, the market has a tendency to revisit levels where liquidity was left behind. An "unmitigated" level is one that hasn't been touched since it was formed. These levels often act as magnets for price, and understanding their age and proximity gives you a significant edge in:
- **Entry timing** - Waiting for price to approach tested levels
- **Exit planning** - Taking profits before ancient resistance/support
- **Risk management** - Avoiding entries when approaching multiple old levels
- **Liquidity mapping** - Visualizing where orders likely cluster
---
## Core Concepts
### 1. **Sessions & Age**
The indicator uses **New York trading sessions** (6:00 PM to 5:59 PM NY time) as the primary time measurement. This aligns with how futures markets naturally segment their activity.
**Age Categories:**
- 🟢 **New (0-1 sessions)** - Fresh levels, recently formed
- 🟡 **Medium (2-3 sessions)** - Tested by time, gaining significance
- 🔴 **Old (4-6 sessions)** - Highly significant, survived multiple days
- 🟣 **Ancient (7+ sessions)** - Extreme significance, major support/resistance
The longer a level remains unmitigated, the more significant it becomes. Think of it like compound interest - time adds weight to these zones.
### 2. **Multi-Timeframe Tracking**
You can set the indicator to track high/low levels from any timeframe (default is 15 minutes). This means you're watching for unmitigated 15-minute highs and lows while trading on, say, a 1-minute or 5-minute chart.
**Why this matters:**
- Higher timeframe levels have more weight
- You can see multiple timeframe structure simultaneously
- Helps you avoid fighting larger timeframe momentum
### 3. **Mitigation**
A level becomes "mitigated" (deactivated) when price touches it:
- **High levels** are mitigated when price reaches or exceeds them
- **Low levels** are mitigated when price reaches or goes below them
Once mitigated, the level disappears from view. The indicator only shows you the untouch levels that still matter.
---
## Visual Components
### 📊 The Dashboard Table
Located in the corner of your chart (configurable), the table shows:
```
┌─────────┬───────────┬────────┬─────┬───────┐
│ Level │ Price │ Points │ Age │ % │
├─────────┼───────────┼────────┼─────┼───────┤
│ ↑↑↑↑↑ │ 21,450.25 │ +45.50 │ 8 │ +0.21%│ ← 5th High (Ancient)
│ ↑↑↑↑ │ 21,430.00 │ +25.25 │ 5 │ +0.12%│ ← 4th High (Old)
│ ↑↑↑ │ 21,420.50 │ +15.75 │ 3 │ +0.07%│ ← 3rd High (Medium)
│ ↑↑ │ 21,412.00 │ +7.25 │ 1 │ +0.03%│ ← 2nd High (New)
│ ↑ ⚠️ │ 21,408.25 │ +3.50 │ 0 │ +0.02%│ ← 1st High (Proximity Alert!)
├─────────┼───────────┼────────┼─────┼───────┤
│ 15 mins │ 🟢 │ Δ 8.75 │ 2U │ │ ← Status Row
├─────────┼───────────┼────────┼─────┼───────┤
│ ↓ ⚠️ │ 21,399.50 │ -5.25 │ 0 │ -0.02%│ ← 1st Low (Proximity Alert!)
│ ↓↓ │ 21,395.00 │ -9.75 │ 2 │ -0.05%│ ← 2nd Low (Medium)
│ ↓↓↓ │ 21,385.25 │ -19.50 │ 4 │ -0.09%│ ← 3rd Low (Old)
│ ↓↓↓↓ │ 21,370.00 │ -34.75 │ 6 │ -0.16%│ ← 4th Low (Old)
│ ↓↓↓↓↓ │ 21,350.75 │ -54.00 │ 9 │ -0.25%│ ← 5th Low (Ancient)
├─────────┼───────────┼────────┼─────┼───────┤
│ 📊 15↑ / 12↓ │ ← Statistics (optional)
└─────────┴───────────┴────────┴─────┴───────┘
```
**Reading the Table:**
- **Level Column**: Number of arrows indicates position (1-5), color shows age
- **Price**: The actual price level
- **Points**: Distance from current price (+ for highs, - for lows)
- **Age**: Number of full sessions since creation
- **%**: Percentage distance from current price
- **⚠️**: Proximity alert - price is within threshold distance
- **Status Row**: Shows timeframe, direction (🟢 bullish/🔴 bearish), tunnel width (Δ), and Strat pattern
### 📈 Visual Elements on Chart
**1. Level Lines**
- Horizontal lines showing each unmitigated level
- **Color-coded by age**: Bright colors = new, darker = older, deep purple/teal = ancient
- **Line style**: Customizable (solid, dashed, dotted)
- Automatically turn **yellow** when price gets close (proximity alert)
**2. Price Labels**
- Show the exact price and age: "21,450.25 (8d)"
- Fixed at small size for clean readability
- Positioned with configurable offset from current bar
**3. Bands (Optional)**
- Shaded zones between pairs of unmitigated levels
- Default: Between 1st and 2nd levels (the "tunnel")
- Can switch to 1st-3rd, 2nd-3rd, or disable entirely
- **Upper band** (pink/maroon) - Between unmitigated highs
- **Lower band** (blue/teal) - Between unmitigated lows
- These represent the "no man's land" or consolidation zones
---
## The Cave Diving Framework
This indicator is designed around the **Cave Diving Trading Framework** - a psychological and technical approach that maps cave diving safety protocols to futures trading risk management.
### 🤿 The Core Metaphor
**Cave diving has clear danger zones based on depth and overhead environment. Your trading should too.**
#### Shallow Water (New Levels, 0-1 Sessions)
- **Light**: Bright colors (bright red highs, bright green lows)
- **Psychology**: Fresh territory, recently tested
- **Trading**: Be aware but not overly concerned
- **Cave Diving Parallel**: You can see the surface, easy exit
#### Penetration Depth (Medium Levels, 2-3 Sessions)
- **Light**: Medium intensity colors
- **Psychology**: Building significance, market memory forming
- **Trading**: Start respecting these levels for entries/exits
- **Cave Diving Parallel**: Deeper in, need to track your line back
#### Deep Dive Zone (Old Levels, 4-6 Sessions)
- **Light**: Dark colors (deep maroon, dark blue)
- **Psychology**: Highly tested support/resistance
- **Trading**: Major decision points, plan accordingly
- **Cave Diving Parallel**: Significant overhead, careful navigation required
#### Overhead Environment (Ancient Levels, 7+ Sessions)
- **Light**: Very dark, purple/deep teal
- **Psychology**: Extreme caution required, major liquidity zones
- **Trading**: These are your "turn back" signals - don't fight ancient levels
- **Cave Diving Parallel**: Maximum danger, no room for error
### 🎯 The Proximity Alert System
Just like a cave diver's depth gauge that warns at critical thresholds, the proximity alerts (⚠️) tell you when you're entering a danger zone. When price gets within your configured threshold (default 5 points), the indicator:
- Highlights the level in **yellow** on the chart
- Shows **⚠️** in the table
- Signals: "You're entering a high-significance zone - adjust your position accordingly"
This prevents the trading equivalent of going deeper into a cave without checking your air supply.
---
## How to Use It for Trading
### 🎯 Entry Strategies
**1. The "Bounce Setup" (Mean Reversion)**
- Wait for price to approach an old or ancient unmitigated level
- Look for confluence: multiple levels nearby, bands narrowing
- Enter when price shows rejection (reversal candle patterns)
- **Example**: Price drops to a 6-session-old low, shows bullish engulfing → Long entry
**2. The "Break and Retest" (Trend Following)**
- Wait for price to break through an unmitigated level (mitigates it)
- Enter on the retest of the newly broken level
- **Example**: Price breaks above 4-session-old high → Wait for pullback to that level → Long entry
**3. The "Tunnel Trade" (Range Trading)**
- When bands are active, trade the range between 1st-2nd levels
- Short near upper band resistance, long near lower band support
- Exit at opposite side or when bands break
### 🚨 Risk Management Rules
**The Ancient Level Rule**
> Never fight ancient levels (7+ sessions). If you're long and approaching an ancient high, take profits. If you're short and approaching an ancient low, take profits.
These levels have survived a full trading week without being touched - there's likely significant liquidity and institutional interest there.
**The Proximity Exit Rule**
> When you see ⚠️ proximity alerts on multiple levels above/below your position, tighten stops or scale out.
This is your "overhead environment" warning. You're in dangerous territory.
**The New Level Filter**
> Be cautious taking positions based solely on new levels (0-1 sessions). Wait for them to age or combine with other confluence.
Fresh levels haven't been tested by time. They're like unconfirmed support/resistance.
### 📊 Reading Market Structure
**Bullish Structure (🟢 in status row)**
- Unmitigated lows are aging and holding
- Price respecting the lower band
- Old lows below acting as strong support
- **Bias**: Look for long entries at lower levels
**Bearish Structure (🔴 in status row)**
- Unmitigated highs are aging and holding
- Price respecting the upper band
- Old highs above acting as strong resistance
- **Bias**: Look for short entries at higher levels
**The Tunnel Compression**
- When the Δ (delta) in the status row is small, levels are tight
- This often precedes a breakout
- **Trading**: Wait for breakout direction, then trade the break
### 🔄 Strat Integration
The indicator shows Strat patterns in the status row:
- **1** - Inside bar (consolidation)
- **2U** - Broke high only (bullish)
- **2D** - Broke low only (bearish)
- **3** - Broke both (wide range, volatility)
Use these with the unmitigated levels:
- **2U near old high** → Potential resistance, watch for rejection
- **2D near old low** → Potential support, watch for bounce
- **3 pattern** → High volatility, respect wider stops
---
## Settings & Customization
### 📅 Session & Timeframe Settings
**HL Interval** (Default: 15 minutes)
- The timeframe for high/low calculation
- **Lower (1m, 5m)**: More levels, more noise, good for scalping
- **Higher (30m, 1H, 4H)**: Fewer levels, stronger significance, good for swing trading
- **Recommendation for NQ/ES**: 15m or 30m for day trading, 1H for swing trading
**Session Age Threshold** (Default: 2)
- How many sessions before a level is considered "old"
- Lower = more levels classified as old
- Higher = stricter definition of significance
### 📊 Level Display Options
**Show Level Lines**
- Toggle: Display horizontal lines for each level
- **Turn off** if you prefer a cleaner chart and only want the table
**Show Level Labels**
- Toggle: Display price labels on the chart
- **Turn off** for minimal visual clutter
**Label Offset**
- Distance (in bars) from current price bar to place labels
- Increase if labels overlap with price action
**Level Line Width & Style**
- Customize visual appearance
- **Thin solid**: Minimal distraction
- **Thick dashed**: High visibility
### 🎨 Age-Based Color Coding
Customize colors for each age category (high and low separately):
- **New (0-1 sessions)**: Default bright red/green
- **Medium (2-3 sessions)**: Default medium intensity
- **Old (4+ sessions)**: Default dark red/blue
- **Ancient (7+ sessions)**: Default deep purple/teal
**Color Strategy Tips:**
- Keep ancient levels in highly contrasting colors
- Use opacity (transparency) if you want subtler lines
- Match your chart's color scheme for aesthetic coherence
### 🎯 Band Settings
**Band Mode**
- **1st-2nd** (Default): The primary "tunnel" between most recent levels
- **1st-3rd**: Wider band, more room for price action
- **2nd-3rd**: Band between less immediate levels
- **Disabled**: No bands, lines only
**Band Colors & Borders**
- Customize fill color and border separately
- **Tip**: Keep bands very transparent (90-95% transparency) to avoid obscuring price action
### ⚠️ Proximity Alert Settings
**Enable Proximity Alerts**
- Toggle: Turn on/off the warning system
- When enabled, levels within threshold distance show ⚠️ and turn yellow
**Alert Threshold** (Default: 5.0 points)
- Distance in points to trigger the alert
- **For NQ**: 5-10 points is reasonable
- **For ES**: 2-5 points is reasonable
- **For MES/MNQ**: Scale down proportionally
**Alert Highlight Color**
- The color lines/labels turn when proximity is triggered
- Default: Yellow (high visibility)
### 📋 Table Settings
**Show Table**
- Toggle: Display the dashboard table
**Table Location**
- Top Left, Top Right, Bottom Left, Bottom Right
- Choose based on your chart layout and other indicators
**Text Size**
- Tiny, Small, Normal, Large
- **Recommendation**: Normal for 1080p monitors, Small for 4K
**Show % Distance**
- Toggle: Add percentage distance column to table
- Useful for comparing relative distances across different price ranges
**Show Statistics Row**
- Toggle: Show total count of unmitigated highs/lows
- Format: "📊 15↑ / 12↓" (15 unmitigated highs, 12 unmitigated lows)
- Useful for gauging overall market structure
### ⚡ Performance Settings
**Enable Level Cleanup**
- Automatically remove very old levels to maintain performance
- **Keep on** unless you want unlimited history
**Max Lookback Levels** (Default: 10,000)
- Maximum number of levels to track
- 10,000 ≈ 6+ months of 15-minute bars
- **Increase** if you want more history
- **Decrease** if experiencing performance issues
**Max Boxes Per Band** (Default: 245)
- TradingView limit is 500 total boxes
- With 2 bands, 245 each = 490 total (safe maximum)
---
## Best Practices
### 🎯 Position Management
**1. Scaling In Near Old Levels**
```
Price approaching 5-session-old low:
- First position: 30% size at proximity alert (⚠️)
- Second position: 40% size at exact level
- Third position: 30% size if it shows strong rejection
```
**2. Scaling Out Near Ancient Levels**
```
Holding long position, approaching 8-session-old high:
- Exit 50% at proximity alert (⚠️)
- Exit 30% at exact level
- Trail stop on remaining 20%
```
### 🧠 Trading Psychology Integration
Drawing from principles in *The Mountain Is You*, this indicator helps you:
**1. Recognize Self-Sabotage Patterns**
- **The Premature Entry**: Entering before price reaches your planned level
- **Solution**: Set alerts at unmitigated levels, wait for proximity warnings
- **The Profit-Taking Problem**: Exiting too early from fear
- **Solution**: Identify the next unmitigated level and commit to holding until proximity alert
- **The Loss Holding**: Refusing to exit losing trades
- **Solution**: When price breaks through and mitigates your entry level, it's telling you the structure changed
**2. Building Better Habits**
The color-coded age system trains your brain to:
- Respect levels that have proven themselves over time
- Distinguish between noise (new levels) and structure (old levels)
- Make decisions based on objective data, not fear or greed
**3. Emotional Regulation**
The proximity alerts serve as:
- **Circuit breakers** - Forcing you to re-evaluate before dangerous zones
- **Permission to act** - Giving you objective signals to exit without second-guessing
- **Validation** - Confirming when you're in alignment with market structure
### 📝 Pre-Market Routine
**Daily Setup Checklist:**
1. ✅ Identify the 3 nearest unmitigated highs above current price
2. ✅ Identify the 3 nearest unmitigated lows below current price
3. ✅ Note which are ancient (7+) - these are your "no-go" zones
4. ✅ Check the tunnel width (Δ in status row) - tight or wide?
5. ✅ Set alerts at the 1st high and 1st low for proximity warnings
6. ✅ Plan: "If we go up, I exit at ___. If we go down, I enter at ___."
### 🔄 Timeframe Confluence
**Multi-Timeframe Strategy:**
Run the indicator on **three instances**:
- **15-minute** (short-term structure)
- **1-hour** (intermediate structure)
- **4-hour** (major structure)
**Strong Setup**: When all three timeframes show unmitigated levels converging at the same price zone.
**Example:**
- 15m: Old low at 21,400
- 1H: Ancient low at 21,398
- 4H: Ancient low at 21,395
- **Result**: 21,395-21,400 is a monster support zone
### ⚠️ What This Indicator Doesn't Do
**Not a Crystal Ball**
- It doesn't predict where price will go
- It shows you where price *hasn't been* and how long it's been avoided
- The trading decisions are still yours
**Not an Entry Signal Generator**
- It provides context and structure
- You need to combine it with your entry methodology (price action, indicators, order flow, etc.)
**Not Foolproof**
- Ancient levels get broken
- Proximity alerts can trigger early in strong trends
- The market doesn't "owe" you a reversal at any level
---
## Common Scenarios
### Scenario 1: "Level Cluster Ahead"
**Situation**: You're long at 21,400. The table shows:
- 1st High: 21,425 (2 sessions old)
- 2nd High: 21,428 (3 sessions old)
- 3rd High: 21,435 (6 sessions old)
**Interpretation**: There's a resistance cluster just 25-35 points away. The 6-session-old level is particularly significant.
**Action**:
- Set first profit target at 21,420 (before the cluster)
- Set second target at 21,426 (between 1st and 2nd)
- Trail remaining position, but be ready to exit on rejection at 21,435
**Cave Diving Analogy**: You're approaching an overhead section with limited clearance. Lighten your load (reduce position) before entering.
---
### Scenario 2: "Ancient Level Approaches"
**Situation**: The market is grinding higher. You see ⚠️ appear next to a 9-session-old high at 21,500.
**Interpretation**: This level has survived over a week without being touched. Massive potential liquidity zone.
**Action**:
- If long, this is your absolute exit zone. Take profits before or at level.
- If looking to short, wait for clear rejection (price taps and reverses)
- Don't try to buy the breakout until it clearly breaks and retests
**Cave Diving Analogy**: Your dive computer is beeping - you've reached your planned turn-back depth. No matter how interesting it looks ahead, honor your plan.
---
### Scenario 3: "Mitigated Levels Create New Structure"
**Situation**: Price breaks and mitigates the 1st High. The previous 2nd High becomes the new 1st High.
**Interpretation**: The structure just shifted. What was the 2nd level is now most relevant.
**Action**:
- Watch how price reacts to the newly-mitigated level
- If it holds below (acts as resistance), bearish
- If it reclaims and holds above (acts as support), bullish
- The NEW 1st High is your next target/resistance
**Cave Diving Analogy**: You've passed through a restriction - the cave layout ahead is different now. Update your mental map.
---
### Scenario 4: "Tight Tunnel, Upcoming Breakout"
**Situation**: The Δ in the status row shows 3.25 points (very tight). Bands are converging.
**Interpretation**: Price is consolidating between very close unmitigated levels. Breakout likely.
**Action**:
- Don't try to predict direction
- Set alerts above 1st High and below 1st Low
- When break occurs, trade the retest
- Expect volatility - use wider stops
**Cave Diving Analogy**: You're in a narrow passage. Movement will be sudden and directional once it starts.
---
### Scenario 5: "Imbalanced Structure"
**Situation**: The statistics row shows "📊 22↑ / 7↓"
**Interpretation**: There are many more unmitigated highs than lows. This suggests:
- Price has been declining (hitting lows, leaving highs behind)
- Potential bullish reversal zone (lots of overhead supply mitigated)
- Or continued bearish structure (resistance everywhere above)
**Action**:
- Look at the age of those 22 highs
- If mostly new (0-2 sessions): Just a recent downmove, not significant yet
- If many old/ancient: Strong overhead resistance, be cautious on longs
- Compare to price action: Is price respecting the remaining lows?
**Cave Diving Analogy**: You've swam deeper than your starting point - most of your markers are above you now. Are you planning the ascent or going deeper?
---
## Final Thoughts: The Philosophy
This indicator is built on a simple but powerful principle: **The market has memory, and that memory has weight.**
Every unmitigated level represents:
- Liquidity left behind
- Orders waiting to be filled
- Institutional interest potentially parked
- Psychological significance for participants
The longer a level remains unmitigated, the more "charged" it becomes. When price finally revisits it, something significant usually happens - either a strong reversal or a definitive break.
Your job as a trader isn't to predict which outcome will occur. Your job is to:
1. **Recognize** when you're approaching these charged zones
2. **Respect** them by adjusting position size and risk
3. **React** appropriately based on how price behaves at them
4. **Remember** that ancient levels (like ancient wisdom) deserve extra reverence
The Cave Diving Framework embedded in this indicator serves as a constant reminder: Trading, like cave diving, requires rigorous respect for environmental hazards, meticulous planning, and the discipline to turn back when your limits are reached.
**Every proximity alert is the market asking you**: *"Do you really want to go deeper?"*
Sometimes the answer is yes - when your setup, confluence, and risk management all align.
Often, the answer should be no - and that's the trader avoiding the accident that would have happened to the gambler.
---
### 🎯 Quick Reference Card
**Color System:**
- 🟢 Bright colors = New (0-1 sessions) = Shallow water
- 🟡 Medium colors = Medium (2-3 sessions) = Penetration depth
- 🔴 Dark colors = Old (4-6 sessions) = Deep dive zone
- 🟣 Deep dark colors = Ancient (7+ sessions) = Overhead environment
**Symbols:**
- ↑ ↑↑ ↑↑↑ ↑↑↑↑ ↑↑↑↑↑ = High levels (1st through 5th)
- ↓ ↓↓ ↓↓↓ ↓↓↓↓ ↓↓↓↓↓ = Low levels (1st through 5th)
- ⚠️ = Proximity alert (danger zone)
- 🟢 = Bullish structure
- 🔴 = Bearish structure
- Δ = Tunnel width (distance between 1st high and 1st low)
**Critical Rules:**
1. Never fight ancient levels (7+ sessions)
2. Respect proximity alerts (⚠️)
3. Scale out near old/ancient resistance
4. Wait for confluence when entering
5. Let mitigated levels prove their new role
---
**Remember**: The indicator gives you structure. The trading edge comes from your discipline in respecting that structure.
Trade safe, trade smart, and always know your exit before your entry. 🎯
---
*"You don't become your best self by denying your patterns. You become your best self by recognizing them, understanding them, and choosing differently." - Adapted from The Mountain Is You*
In trading: You don't become profitable by ignoring market structure. You become profitable by recognizing it, understanding it, and choosing your entries accordingly.
FVG Heatmap [Hash Capital Research]FVG Map
FVG Map is a visual Fair Value Gap (FVG) mapping tool built to make displacement imbalances easy to see and manage in real time. It detects 3-candle FVG zones, plots them as clean heatmap boxes, tracks partial mitigation (how much of the zone has been filled), and summarizes recent “fill speed” behavior in a small regime dashboard.
This is an indicator (not a strategy). It does not place trades and it does not publish performance claims. It is a market-structure visualization tool intended to support discretionary or systematic workflows.
What this script detects
Bullish FVG (gap below price)
A bullish FVG is detected when the candle from two bars ago has a high below the current candle’s low.
The zone spans from that prior high up to the current low.
Bearish FVG (gap above price)
A bearish FVG is detected when the candle from two bars ago has a low above the current candle’s high.
The zone spans from the current high up to that prior low.
What makes it useful
Heatmap zones (clean, readable FVG boxes)
Bullish zones plot below price. Bearish zones plot above price.
Partial fill tracking (mitigation progress)
As price trades back into a zone, the script visually shows how much of the zone has been filled.
Mitigation modes (your definition of “filled”)
• Full Fill: price fully trades through the zone
• 50% Fill: price reaches the midpoint of the zone
• First Touch: price touches the zone one time
Optional auto-cleanup
Optionally remove zones once they’re mitigated to keep the chart clean.
Fill-Speed Regime Dashboard
When zones get mitigated, the script records how many bars it took to fill and summarizes the recent environment:
• Average fill time
• Median fill time
• % fast fills vs % slow fills
• Regime label: choppy/mean-revert, trending/displacement, or mixed
How to use
Use FVG zones as structure, not guaranteed signals.
• Bullish zones are often watched as potential support on pullbacks.
• Bearish zones are often watched as potential resistance on rallies.
The fill-speed dashboard helps provide context: fast fills tend to appear in more rotational conditions, while slow fills tend to appear in stronger trend/displacement conditions.
Alerts
Bullish FVG Created
Bearish FVG Created
Notes
FVGs are not guaranteed reversal points. Fill-speed/regime is descriptive of recent behavior and should be treated as context, not prediction. On realtime candles, visuals may update as the bar forms.
DCT - Liquidity Heatmap - ProDCT - Liquidity Heatmap - Pro
Overview
This indicator maps liquidity concentration zones by analyzing volume distribution across price levels. It identifies areas where significant trading activity has accumulated, potentially indicating zones of interest for future price interaction.
Methodology
Volume Intensity Calculation
Each price level accumulates a normalized volume score calculated as:
- Volume Intensity = Current Bar Volume / SMA(Volume, lookback period)
- This normalization allows comparison across different volatility regimes and trading sessions
Level Construction
- Price levels are distributed symmetrically above and below current price using percentage-based spacing
- Each level maintains cumulative volume data, tracking both raw volume and normalized intensity
- Levels are visualized as zones with height proportional to the spacing parameter
Sweep Detection Logic
A level is marked as "swept" when price action crosses through it:
- Condition: Low ≤ Level Price AND High ≥ Level Price
- Swept levels stop accumulating new volume and can be styled differently (fade, hide, or preserve)
Color Intensity Grading
Zones are color-coded based on their normalized volume relative to the maximum observed:
- Purple: < 25% of max intensity
- Yellow: 25-50% of max intensity
- Orange: 50-75% of max intensity
- Red: > 75% of max intensity
Optional CVD (Cumulative Volume Delta) Mode
When enabled, directional volume is estimated using candle structure:
- Bullish candles: Buy pressure weighted by (Close - Open) / (High - Low)
- Bearish candles: Sell pressure weighted by (Open - Close) / (High - Low)
- Levels display green/red bias based on accumulated directional volume ratio
Adaptive System
The indicator includes a three-layer adaptive system:
1. Timeframe adaptation: Spacing, level count, and retention automatically adjust for M5 through Daily charts
2. Volatility adaptation: ATR-based adjustments widen spacing during high volatility and tighten during consolidation
3. Market type adaptation: Different imbalance thresholds for BTC/ETH, large altcoins, and small caps
Imbalance Detection
Buy/sell imbalance markers appear when the ratio of accumulated buy volume to sell volume exceeds a configurable threshold (default 1.5x for BTC/ETH, 2.0x for small caps).
What Makes This Implementation Unique
- Dollar-denominated liquidity display: Labels show estimated liquidity in USD (K/M/B format) rather than abstract values
- Three-layer adaptive logic: Combines timeframe, volatility (ATR), and asset-class adjustments simultaneously
- Memory-optimized architecture: Automatic cleanup of old swept levels prevents performance degradation on extended charts
- Forward projection: Active levels extend into future bars for cleaner visualization
- Granular visibility controls: Each intensity tier can be toggled independently
Settings Guide
- Dynamic: Enable adaptive adjustments (recommended)
- Spacing: Distance between levels as % of price
- Levels: Number of levels above/below price
- CVD: Enable directional volume analysis
- Forward: Project levels ahead by specified bars
Usage Notes
- Works on both Perpetual and Spot crypto markets
- Optimized for crypto assets; results may vary on other instruments
- Higher timeframes show broader liquidity structure; lower timeframes show granular detail
- Combine with your own analysis framework
Disclaimer
This indicator visualizes historical volume distribution and does not predict future price movement. Not financial advice. Use appropriate risk management.
Simulated Liquidation Heatmap [QuantAlgo]🟢 Overview
This indicator visualizes where clusters of stop-loss orders and liquidation levels are likely located, displayed as a 'heatmap'. It's based on the concept of market structure liquidity: large groups of stop orders tend to gather around obvious technical levels (like swing highs and lows), and these pools of orders often attract price movement from institutional traders. The indicator uses a fractal-based algorithm to identify these high-probability liquidation zones and displays them as dynamic, color-coded boxes.
The key feature is the thermal color gradient, which indicates the freshness (age) and therefore the relative relevance of the liquidity zone. Hot colors (e.g., Red/Yellow) represent fresh clusters that have just formed, suggesting strong and immediate liquidity interest. Cold colors (e.g., Blue/Purple) represent aged or decaying clusters that are becoming less relevant over time. This visualization allows traders to anticipate potential liquidity sweeps (stop hunts) and understand areas of significant retail and institutional positioning.
🟢 Key Features
1. Liquidity Zone Heatmap
The core function is the identification of swing high and swing low price points using a user-defined Lookback period. These points are where retail traders are statistically most likely to place their stop-loss orders. The indicator simulates the clustering of these orders by drawing a zone (box) around the detected swing point, with the vertical size controlled by the Stop/Liquidation Zone Width (%) setting.
▶ Cluster Lookback: Defines the sensitivity of swing point detection. Lower values detect frequent, minor zones (scalping/intraday); higher values detect major, stronger swing points (swing trading).
▶ Zone Width (%): Sets the percentage range above and below the swing point where stops are simulated to cluster, accounting for slippage and typical stop placement spread.
▶ Liquidity Decay: Zones gradually fade in color intensity and are eventually removed after the user-defined Liquidity Decay Period (Bars), ensuring the heatmap only displays relevant, current liquidity areas.
▶ Round Number Filter: An optional filter that limits the display to liquidity zones occurring only at psychologically significant round numbers (e.g., $100, $1,500.00), which typically attract higher concentrations of orders.
2. Thermal Color Gradient
The heatmap's color is a direct function of the zone's age, providing a visual proxy for immediate relevance.
▶ Freshness: Newly created zones are displayed in the Hot Color (high relevance).
▶ Decay: As bars pass, the zone color transitions along the gradient toward the Cold Color and increased transparency (lower relevance), until it is removed entirely.
▶ Color Schemes: Multiple pre-configured and custom color schemes are available to optimize the visualization for different chart themes and color preferences.
3. Liquidity Heat Thermometer
An optional visual thermometer is displayed on the chart to provide an instant, overall assessment of the current liquidation heat level in the immediate vicinity of the price.
▶ Calculation: The thermometer calculates an aggregate heat score based on the age and proximity of all liquidity zones within a user-defined Zone Detection Range (%) of the current price.
▶ Visual Feedback: A marker (triangle) points to the corresponding level on the thermometer's color gradient (Hot to Cold). A high reading indicates price is close to fresh, dense stop clusters, suggesting high volatility or an imminent liquidity sweep is probable. A low reading indicates price is in a low-density or aged liquidity area.
▶ Customization: The thermometer's resolution, position, and text size are fully customizable for optimal chart placement and readability.
🟢 Practical Applications
▶ Anticipate Sweeps: Prioritize trading in the direction of Hot (fresh) liquidity zones. For example, a hot low-side zone suggests strong sell-side liquidity (stop-losses) is available for large buyers to sweep.
▶ Filter Noise: Use the Round Number Filter to focus only on the highest probability liquidation zones, which are often at clean, psychological price levels.
▶ Validate Entries: Combine the Heat Thermometer with price action analysis. A rising heat level indicates increasing proximity to a major stop cluster, signaling a potential turn or an aggressive market move to sweep those stops.
▶ Risk Management: Understand that price often acts dynamically around these zones. High heat levels imply high risk/reward setups; stops should be placed strategically beyond the defined Liquidation Zone Width.
▶ Multi-Timeframe Context: Higher timeframes (e.g., Daily, 4-Hour) often reveal more significant, major liquidity zones. Use this indicator on lower timeframes (e.g., 5-min, 15-min) for execution, but prioritize zones that align with higher-timeframe structures.
Relative Strength Heatmap [BackQuant]Relative Strength Heatmap
A multi-horizon RSI matrix that compresses 20 different lookbacks into a single panel, turning raw momentum into a visual “pressure gauge” for overbought and oversold clustering, trend exhaustion, and breadth of participation across time horizons.
What this is
This indicator builds a strip-style heatmap of 20 RSIs, each with a different length, and stacks them vertically as colored tiles in a single pane. Every tile is colored by its RSI value using your chosen palette, so you can see at a glance:
How many “fast” versus “slow” RSIs are overbought or oversold.
Whether momentum is concentrated in the short lookbacks or spread across the whole curve.
When momentum extremes cluster, signalling strong market pressure or exhaustion.
On top of the tiles, the script plots two simple breadth lines:
A white line that counts how many RSIs are above 70 (overbought cluster).
A black line that counts how many RSIs are below 30 (oversold cluster).
This turns a single symbol’s RSI ladder into a compact “market pressure gauge” that shows not only whether RSI is overbought or oversold, but how many different horizons agree at the same time.
Core idea
A single RSI looks at one length and one timescale. Markets, however, are driven by flows that operate on multiple horizons at once. By computing RSI over a ladder of lengths, you approximate a “term structure” of strength:
Short lengths react to immediate swings and very recent impulses.
Medium lengths reflect swing behaviour and local trends.
Long lengths reflect structural bias and higher timeframe regime.
When many lengths agree, for example 10 or more RSIs all above 70, it suggests broad participation and strong directional pressure. When only a few fast lengths stretch to extremes while longer ones stay neutral, the move is more fragile and more likely to mean-revert.
This script makes that structure visible as a heatmap instead of forcing you to run many separate RSI panes.
How it works
1) Generating RSI lengths
You control three parameters in the calculation settings:
RS Period – the base RSI length used for the shortest strip.
RSI Step – the amount added to each successive RSI length.
RSI Multiplier – a global scaling factor applied after the step.
Each of the 20 RSIs uses:
RSI length = round((base_length + step × index) × multiplier) , where the index goes from 0 to 19.
That means:
RSI 1 uses (len + step × 0) × mult.
RSI 2 uses (len + step × 1) × mult.
…
RSI 20 uses (len + step × 19) × mult.
You can keep the ladder dense (small step and multiplier) or stretch it across much longer horizons.
2) Heatmap layout and grouping
Each RSI is plotted as an “area” strip at a fixed vertical level using histbase to stack them:
RSI 1–5 form Group 1.
RSI 6–10 form Group 2.
RSI 11–15 form Group 3.
RSI 16–20 form Group 4.
Each group has a toggle:
Show only Group 1 and 2 if you care mainly about fast and medium horizons.
Show all groups for a full spectrum from very short to very long.
Hide any group that feels redundant for your workflow.
The actual numeric RSI values are not plotted as lines. Instead, each strip is drawn as a horizontal band whose fill color represents the current RSI regime.
3) Palette-based coloring
Each tile’s color is driven by the RSI value and your chosen palette. The script includes several palettes:
Viridis – smooth green to yellow, good for subtle reading.
Jet – strong blue to red sequence with high contrast.
Plasma – purple through orange to yellow.
Custom Heat – cool blues to neutral grey to hot reds.
Gray – grayscale from white to black for minimalistic layouts.
Cividis, Inferno, Magma, Turbo, Rainbow – additional scientific and rainbow-style maps.
Internally, RSI values are bucketed into ranges (for example, below 10, 10–20, …, 90–100). Each bucket maps to a unique colour for that palette. In all schemes, low RSI values are mapped to the “cold” or darker side and high RSI values to the “hot” or brighter side.
The result is a true momentum heatmap:
Cold or dark tiles show low RSI and oversold or compressed conditions.
Mid tones show neutral or mid-range RSI.
Warm or bright tiles show high RSI and overbought or stretched conditions.
4) Bull and bear breadth counts
All 20 RSI values are collected into an array each bar. Two counters are then calculated:
Bull count – how many RSIs are above 70.
Bear count – how many RSIs are below 30.
These are plotted as:
A white line (“RSI > 70 Count”) for the overbought cluster.
A black line (“RSI < 30 Count”) for the oversold cluster.
If you enable the “Show Bull and Bear Count” option, you get an immediate reading of how many of the 20 horizons are stretched at any moment.
5) Cluster alerts and background tagging
Two alert conditions monitor “strong cluster” regimes:
RSI Heatmap Strong Bull – triggers when at least 10 RSIs are above 70.
RSI Heatmap Strong Bear – triggers when at least 10 RSIs are below 30.
When one of these conditions is true, the indicator can tint the background of the chart using a soft version of the current palette. This visually marks stretches where momentum is extreme across many lengths at once, not just on a single RSI.
What it plots
In one oscillator window, the indicator provides:
Up to 20 horizontal RSI strips, each representing a different RSI length.
Color-coded tiles reflecting the current RSI value for each length.
Group toggles to show or hide each block of five RSIs.
An optional white line that counts how many RSIs are above 70.
An optional black line that counts how many RSIs are below 30.
Optional background highlights when the number of overbought or oversold RSIs passes the strong-cluster threshold.
How it measures breadth and pressure
Single-symbol breadth
Breadth is usually defined across a basket of symbols, such as how many stocks advance versus decline. This indicator uses the same concept across time horizons for a single symbol. The question becomes:
“How many different RSI lengths are stretched in the same direction at once?”
Examples:
If only 2 or 3 of the shortest RSIs are above 70, bull count stays low. The move is fast and local, but not yet broadly supported.
If 12 or more RSIs across short, medium and long lengths are above 70, the bull count spikes. The move has broad momentum and strong upside pressure.
If 10 or more RSIs are below 30, bear count spikes and you are in a broad oversold regime.
This is breadth of momentum within one market.
Market pressure gauge
The combination of heatmap tiles and breadth lines acts as a pressure gauge:
High bull count with warm colors across most strips indicates strong upside pressure and crowded long positioning.
High bear count with cold colors across most strips indicates strong downside pressure and capitulation or forced selling.
Low counts with a mixed heatmap indicate neutral pressure, fragmented flows, or range-bound conditions.
You can treat the strong-cluster alerts as “extreme pressure” signals. When they fire, the market is heavily skewed in one direction across many horizons.
How to read the heatmap
Horizontal patterns (through time)
Look along the time axis and watch how the colors evolve:
Persistent hot tiles across many strips show sustained bullish pressure and trend strength.
Persistent cold tiles across many strips show sustained bearish pressure and weak demand.
Frequent flipping between hot and cold colours indicates a choppy or mean-reverting environment.
Vertical structure (across lengths at one bar)
Focus on a single bar and read the column of tiles from top to bottom:
Short RSIs hot, long RSIs neutral or cool: early trend or short-term fomo. Price has moved fast, longer horizons have not caught up.
Short and long RSIs all hot: mature, entrenched uptrend. Broad participation, high pressure, greater risk of blow-off or late-entry vulnerability.
Short RSIs cold but long RSIs mid to high: pullback in a higher timeframe uptrend. Dip-buy and continuation setups are often found here.
Short RSIs high but long RSIs low: countertrend rallies within a broader downtrend. Good hunting ground for fades and short entries after a bounce.
Bull and bear breadth lines
Use the two lines as simple, numeric breadth indicators:
A rising white line shows more RSIs pushing above 70, so bullish pressure is expanding in breadth.
A rising black line shows more RSIs pushing below 30, so bearish pressure is expanding in breadth.
When both lines are low and flat, few horizons are extreme and the market is in mid-range territory.
Cluster zones
When either count crosses the strong threshold (for example 10 out of 20 RSIs in extreme territory):
A strong bull cluster marks a broadly overbought regime. Trend followers may see this as confirmation. Mean-reversion traders may see it as a late-stage or blow-off context.
A strong bear cluster marks a broadly oversold regime. Downtrend traders see strong pressure, but the risk of sharp short-covering bounces also increases.
Trading applications
Trend confirmation
Use the heatmap and breadth lines as a trend filter:
Prefer long setups when the heatmap shows mostly mid to high RSIs and the bull count is rising.
Avoid fresh shorts when there is a strong bull cluster, unless you are specifically trading exhaustion.
Prefer short setups when the heatmap is mostly low RSIs and the bear count is rising.
Avoid aggressive longs when a strong bear cluster is active, unless you are trading reflexive bounces.
Mean-reversion timing
Treat cluster extremes as exhaustion zones:
Look for reversal patterns, failed breakouts, or order flow shifts when bull count is very high and price starts to stall or diverge.
Look for reflexive bounce potential when bear count is very high and price stops making new lows or shows absorption at the lows.
Use the palette and counts together: hot tiles plus a peaking white line can mark blow-off conditions, cold tiles plus a peaking black line can mark capitulation.
Regime detection and risk toggling
Use the overall shape of the ladder over time:
If upper strips stay warm and lower strips stay neutral or warm for extended periods, the market is in an uptrend regime. You can justify higher risk for long-biased strategies.
If upper strips stay cold and lower strips stay neutral or cold, the market is in a downtrend regime. You can justify higher risk for short-biased strategies or defensive positioning.
If colours and counts flip frequently, you are likely in a range or choppy regime. Consider reducing size or using more tactical, short-term strategies.
Multi-horizon synchronization
You can think of each RSI length as a proxy for a different “speed” of the same market:
When only fast RSIs are stretched, the move is local and less robust.
When fast, medium and slow RSIs align, the move has multi-horizon confirmation.
You can require a minimum bull or bear count before allowing your main strategy to engage.
Spotting hidden shifts
Sometimes price appears flat or drifting, but the heatmap quietly cools or warms:
If price is sideways while many hot tiles fade toward neutral, momentum is decaying under the surface and trend risk is increasing.
If price is sideways while many cold tiles climb back toward neutral, selling pressure is decaying and the tape is repairing itself.
Settings overview
Calculation Settings
RS Period – base RSI length for the shortest strip.
RSI Step – the increment added to each successive RSI length.
RSI Multiplier – scales all generated RSI lengths.
Calculation Source – the input series, such as close, hlc3 or others.
Plotting and Coloring Settings
Heatmap Color Palette – choose between Viridis, Jet, Plasma, Custom Heat, Gray, Cividis, Inferno, Magma, Turbo or Rainbow.
Show Group 1 – toggles RSI 1–5.
Show Group 2 – toggles RSI 6–10.
Show Group 3 – toggles RSI 11–15.
Show Group 4 – toggles RSI 16–20.
Show Bull and Bear Count – enables or disables the two breadth lines.
Alerts
RSI Heatmap Strong Bull – fires when the number of RSIs above 70 reaches or exceeds the configured threshold (default 10).
RSI Heatmap Strong Bear – fires when the number of RSIs below 30 reaches or exceeds the configured threshold (default 10).
Tuning guidance
Fast, tactical configurations
Use a small base RS Period, for example 2 to 5.
Use a small RSI Step, for tight clustering around the fast horizon.
Keep the multiplier near 1.0 to avoid extreme long lengths.
Focus on Group 1 and Group 2 for intraday and short-term trading.
Swing and position configurations
Use a mid-range RS Period, for example 7 to 14.
Use a moderate RSI Step to fan out into slower horizons.
Optionally use a multiplier slightly above 1.0.
Keep all four groups enabled for a full view from fast to slow.
Macro or higher timeframe configurations
Use a larger base RS Period.
Use a larger RSI Step so the top of the ladder reaches very slow lengths.
Focus on Group 3 and Group 4 to see structural momentum.
Treat clusters as regime markers rather than frequent trading signals.
Notes
This indicator is a contextual tool, not a standalone trading system. It does not model execution, spreads, slippage or fundamental drivers. Use it to:
Understand whether momentum is narrow or broad across horizons.
Confirm or filter existing signals from your primary strategy.
Identify environments where the market is crowded into one side.
Distinguish between isolated spikes and truly broad pressure moves.
The Relative Strength Heatmap is designed to answer a simple but powerful question:
“How many versions of RSI agree with what I am seeing on the chart?”
By compressing those answers into a single panel with clear colour coding and breadth lines, it becomes a practical, visual gauge of momentum breadth and market pressure that you can overlay on any trading framework.
Smart RSI MTF Matrix [DotGain]Summary
Are you tired of trading trend signals, only to miss the bigger picture because you are focused on a single timeframe?
The Smart RSI MTF Matrix is the ultimate "Cockpit View" for momentum traders. Unlike chart overlays that can sometimes clutter your price action, this indicator organizes RSI conditions across 10 different timeframes simultaneously into a clean, separate Heatmap pane.
It monitors everything from the 5-minute chart all the way up to the 12-Month view , giving you a complete X-ray vision of the market's momentum structure instantly.
⚙️ Core Components and Logic
The Smart RSI MTF Matrix relies on a sophisticated hierarchy to deliver clear, actionable context:
Multi-Timeframe Engine: The script runs 10 independent RSI calculations in the background, organized in rows from bottom (Short Term) to top (Long Term).
Classic RSI Thresholds:
Overbought (> 70): Indicates price may be extended to the upside.
Oversold (< 30): Indicates price may be extended to the downside.
Smart Visibility System (The "Secret Sauce"): Not all signals are equal. A 5-minute signal is "noise" compared to a Yearly signal. This indicator automatically applies Transparency to differentiate importance. The visibility increases by 10% for each higher timeframe slot (Row).
🚦 How to Read the Matrix
The indicator plots dots in 10 stacked rows. The position and opacity tell you the direction and significance:
🟥 RED DOTS (Overbought Condition)
Trigger: RSI is above 70 on that specific timeframe.
Meaning: Potential bearish reversal or pullback.
🟩 GREEN DOTS (Oversold Condition)
Trigger: RSI is below 30 on that specific timeframe.
Meaning: Potential bullish reversal or bounce.
⚪ GRAY DOTS (Neutral)
Trigger: RSI is between 30 and 70.
Meaning: No extreme momentum present.
👻 TRANSPARENCY (Signal Strength)
The visibility of the dot tells you exactly which Timeframe (Row) is triggered. The higher the row, the more solid the color:
Faint (10-30% Visibility): Rows 1-3 (5m, 15m, 1h). Used for scalping entries.
Medium (40-60% Visibility): Rows 4-6 (4h, 1D, 1W). Used for swing trading context.
Solid (70-100% Visibility): Rows 7-10 (1M, 3M, 6M, 12M). Used for identifying major macro cycles.
Visual Elements
Structure: Row 1 (Bottom) represents the 5-minute timeframe. Row 10 (Top) represents the 12-Month timeframe.
Vertical Alignment: If you see a vertical column of Red or Green dots, it indicates Multi-Timeframe Confluence —a highly probable reversal point.
Key Benefit
The goal of the Smart RSI MTF Matrix is to keep your main chart clean while providing maximum information. You can instantly see if a short-term pullback (Faint Green Dot) is happening within a long-term uptrend (Solid Gray/Red Dot), allowing for precision entries.
Have fun :)
Disclaimer
This "Smart RSI MTF Matrix" indicator is provided for informational and educational purposes only. It does not, and should not be construed as, financial, investment, or trading advice.
The signals generated by this tool (both "Buy" and "Sell" indications) are the result of a specific set of algorithmic conditions. They are not a direct recommendation to buy or sell any asset. All trading and investing in financial markets involves substantial risk of loss. You can lose all of your invested capital.
Past performance is not indicative of future results. The signals generated may produce false or losing trades. The creator (© DotGain) assumes no liability for any financial losses or damages you may incur as a result of using this indicator.
You are solely responsible for your own trading and investment decisions. Always conduct your own research (DYOR) and consider your personal risk tolerance before making any trades.
Monthly Trend Heatmap – Price Change by MonthThis indicator analyzes multi-year monthly price seasonality and displays it as a clear table of percentage returns for each month, from 2013 to the current year. By calculating the monthly open-to-close percentage change, it helps traders quickly identify recurring seasonal trends, positive or negative months, and long-term behavioral patterns of the selected market.
The goal of this tool is to make seasonal analysis accessible to everyday traders by presenting the data visually in a simple, structured, and easy-to-interpret format.
How It Works
The script must be used on a 1-Month chart.
For each month and each year, the indicator calculates:
Monthly return = (Monthly Close – Monthly Open) / Monthly Open × 100
The result is plotted inside a table, with green for positive months and red for negative months.
Data auto-updates as new monthly candles form.
This tool is not a signal generator and does not tell you when to buy or sell. It is a statistical seasonality visualizer meant to enhance decision-making.
The information provided is for educational and informational purposes only and should not be interpreted as financial, investment, or trading advice. Trading and investing in the stock market involve a high level of risk, including the potential loss of capital. Past performance does not guarantee future results, and no strategy or analysis can assure profits or prevent losses.
All examples, charts, scripts, indicators, or market discussions are strictly for demonstration, learning, and analytical purposes. No warranties or guarantees are made regarding accuracy, completeness, or future performance.
Liquidity Heatmap Concepts [sma] Overview
Liquidity Heatmap Concepts is a sophisticated visualization tool that maps potential liquidation zones for leveraged positions across multiple timeframes. It calculates and displays where high-volume liquidations might occur at various leverage levels (25x, 50x, 100x, 150x), helping traders identify potential support/resistance zones created by cascading liquidations. Additionally, it includes a quarterly volume profile to show historical price distribution and Point of Control levels.
### Volume-Based Trigger System
Lines are only drawn when volume exceeds a threshold:
1. Calculates 14-period simple moving average of volume
2. Applies configurable multiplier (default 1.2x) to determine significance
3. Only plots liquidation levels when current volume > (Volume SMA × Multiplier)
4. This filters out low-volume noise and focuses on meaningful zones
### Visual Intensity System
The indicator uses a gradient coloring system based on relative volume:
- **Peak Volume (White)**: When current bar has maximum volume in the dataset
- Line width: 3 pixels
- Brightest color intensity
- **Above Average Volume**: Volume exceeds average but isn't peak
- Line width: 2 pixels
- Medium color intensity
- **Standard Volume**: Exceeds threshold but below average
- Line width: 1 pixel
- Base color intensity
### Line Extension & Management
- Lines extend horizontally to the right until price crosses them
- Automatic cleanup removes lines after maximum count (default 500)
- Lines persist until invalidated by price action crossing the level
- Oldest lines are removed first when limit is reached
### Quarterly Volume Profile
An optional fixed-range volume profile that:
1. **Automatic Quarter Detection**: Identifies Q1 (Jan-Mar), Q2 (Apr-Jun), Q3 (Jul-Sep), Q4 (Oct-Dec)
2. **Price Distribution Analysis**: Divides the quarter's price range into configurable rows (default 20)
3. **Volume Aggregation**: Accumulates volume at each price level throughout the quarter
4. **POC Identification**: Highlights the price level with highest volume (Point of Control)
5. **Value Area**: Shows the price range containing 70% (configurable) of total volume
6. **Profile Drawing**: At the start of each new quarter, draws the previous quarter's profile as horizontal bars
The volume profile can be positioned on either left or right side of the quarter range with adjustable width.
## Key Features
- **Multi-Leverage Display**: Toggle between 25x, 50x, 100x, and 150x leverage levels independently
- **Dual Side Tracking**: Separate visualization for long and short liquidation zones
- **Volume-Weighted Importance**: Visual intensity correlates with volume significance
- **Gradient Coloring**: Color intensity reflects relative volume magnitude
- **Smart Line Management**: Automatic cleanup prevents chart clutter
- **Historical Context**: Quarterly volume profile shows where price spent most time
- **Fully Customizable**: All colors, thresholds, and display options are adjustable
- **HD Mode**: Uses absolute volume for more precise visualization
## Parameters
### Leverage Selection
- **25x, 50x, 100x, 150x Toggles**: Enable/disable specific leverage levels
- Each level can be controlled independently
### Volume Configuration
- **Minimum Volume Multiplier** (default 1.2): Threshold above volume SMA to trigger lines
- Higher values = fewer but more significant levels
- Lower values = more levels but increased noise
### Advanced Settings
- **Maximum Lines** (default 500, range 50-500): Memory management limit
- Controls how many historical liquidation lines are maintained
### Quarterly Volume Profile
- **Show Previous Q Volume Profile** (default on): Toggle profile visibility
- **Number of Rows** (default 20, range 10-50): Price distribution granularity
- **Profile Width** (default 30%): Visual width as percentage of quarter range
- **Value Area** (default 70%): Percentage of volume for value area calculation
- **Position** (Left/Right): Profile placement relative to quarter
- **Show Values** (default off): Display POC volume label
- **Colors**: Customizable base and POC colors
### Color Customization
- **Long Colors**: Individual colors for each leverage level (25x, 50x, 100x, 150x)
- **Short Colors**: Separate color scheme for short liquidation zones
- **VP Colors**: Base color and POC highlight color for volume profile
## Interpretation
### Liquidation Clusters
- **Dense Line Areas**: Multiple overlapping liquidation levels suggest strong magnetic zones
- **High-Volume Lines**: Brighter/thicker lines indicate more significant potential liquidations
- **Line Breaks**: Price crossing multiple liquidation lines may trigger cascade effects
### Trading Applications
- **Support/Resistance**: Liquidation clusters often act as temporary support/resistance
- **Stop Hunt Zones**: Areas where price may spike to trigger liquidations before reversing
- **Momentum Acceleration**: Breaking through dense clusters can indicate strong directional moves
- **Risk Management**: Avoid placing stops directly at obvious liquidation levels
### Volume Profile Usage
- **POC (Point of Control)**: Price level with highest volume - often acts as strong support/resistance
- **Value Area**: Where most trading activity occurred - indicates fair value range
- **Profile Shape**:
- Balanced profile (bell curve) = ranging market
- Skewed profile = trending market with acceptance at extremes
- **Profile Gaps**: Low volume areas suggest price may move quickly through these zones
### Combined Analysis
- Liquidation lines near quarterly POC create extra-strong zones
- Price returning to value area from outside often finds support/resistance
- Liquidation clusters at value area edges suggest potential reversal points
## Technical Implementation
This indicator features:
- **Custom Type Structures**: Uses type definitions for organized data storage
- `BarData`: Stores OHLCV and index information
- `LiquidityBin`: Manages arrays of line objects for each leverage level
- `VolumeProfileData`: Handles profile boxes, labels, and range data
- **Dynamic Line Objects**: Creates, updates, and deletes line primitives programmatically
- **Array-Based History**: Maintains volume history for gradient calculations
- **Intelligent Cleanup**: Automatic memory management prevents performance degradation
- **Mathematical Precision**: Leverage-based liquidation formulas ensure accurate price levels
- **Quarterly Aggregation**: Efficient volume accumulation with automatic period detection
- **Box Drawing System**: Dynamic profile visualization using box primitives
## Originality Statement
This indicator presents a unique approach to liquidity visualization:
- Implements leverage-specific liquidation price calculations based on mathematical formulas
- Uses volume-weighted gradient coloring system that adapts to relative volume significance
- Combines real-time liquidation mapping with historical volume profile analysis
- Features intelligent line lifecycle management with automatic extension and cleanup
- Integrates quarterly volume profile with configurable value area and POC detection
- Employs multi-layer visual hierarchy (line width + color intensity) for information density
- Uses custom data structures to efficiently manage hundreds of line objects simultaneously
The combination of mathematical liquidation pricing, volume-based filtering, gradient visualization, and quarterly volume distribution creates a comprehensive liquidity analysis tool.
## Best Practices
- Use on liquid markets (major cryptocurrencies, forex pairs) for best accuracy
- Lower timeframes (1m-15m) for day trading and scalping
- Higher timeframes (1h-4h) for swing trading context
- Combine with volume profile to identify high-probability reversal zones
- Watch for price reactions when approaching dense liquidation clusters
- Increase volume multiplier in choppy markets to reduce noise
- Reduce maximum lines on lower timeframes to maintain performance
- Use quarterly volume profile to understand longer-term fair value
## Important Notes
- Liquidation prices are estimates based on leverage ratios
- Actual exchange liquidation prices may vary due to:
- Maintenance margin requirements
- Mark price vs last price calculations
- Individual exchange liquidation engines
- Insurance fund mechanisms
- This tool shows potential zones, not guaranteed liquidation prices
- Volume profile resets each quarter automatically
---
Works on all timeframes and asset classes. Designed for crypto/forex leverage markets. For educational purposes only. Not financial advice.
Malama's Heat MapOverview
Malama's Heat Map is an overlay indicator that visualizes historical liquidity as a dynamic heatmap aligned with the price chart, using volume as a proxy to map activity across time (X-axis) and price levels (Y-axis). It constructs a grid of up to 5000 cells via a matrix, distributing bar volume into discrete price bins to highlight concentration zones, creating a color-graded visualization from cool (low activity) to hot (high liquidity). This aids in identifying "Type II" fair value areas, support/resistance from past volume clusters, or potential imbalances without order book access. Built for v6 compatibility with efficiency in mind—computations run solely on the last bar, includes object limit enforcement, and offers two intra-bar volume distribution methods for flexible approximation.
Core Mechanics
The indicator generates a trailing heatmap through binning, accumulation, and box-based rendering:
Grid Setup: Configurable lookback (bars back, default 100) sets horizontal time span; bins (price divisions, default 50) define vertical resolution, limited to 5000 total cells to prevent errors. Bin height dynamically = max(mintick, (lookback high - low) / bins).
Y-Axis Stabilization: Anchors boundaries to the prior bar's high/low (if available) for a flicker-free view during live bar updates. All historical bar data (high/low/close/volume) is clipped to these bounds.
Volume Distribution Proxy:
Even: Divides bar volume equally across spanned bins (straightforward uniform spread).
POC Weighted (Inverse): Treats bar close as POC proxy; applies inverse distance weighting (1/(|bin - POC bin| + 1), normalized) to emphasize volume near the estimated control point, simulating clustered intra-bar trading.
Matrix Building: On last bar only, loops backward over lookback bars (newest right-aligned). For each, computes low/high bin indices, distributes volume per selected method into the matrix (columns=time, rows=price bins from low to high).
Scaling & Palette: Extracts max matrix value for relative normalization (0-1); maps to a 5-tier stepped color scheme (user-customizable: blue 90% transp. low → red 50% transp. high) for non-linear intensity.
Rendering: Clears old boxes, then iterates matrix to draw only non-zero cells as thin boxes: X spans one bar width (left=historical index from bar_index, right=next bar), Y fills bin height. Borderless for seamless heatmap effect.
The result is a right-leaning, chart-scrolling visualization emphasizing recent liquidity buildup.
Why This Adds Value & Originality
While session-based volume profiles exist, this heatmap captures ongoing multi-bar liquidity evolution ("Type II" style), revealing horizontal value areas or gaps dynamically. Originality shines in the custom inverse-weighting for POC realism (no ta.* dependencies), matrix-driven persistence for quick redraws, and stabilization to eliminate repaints—issues plaguing similar scripts. v6 adaptations (e.g., custom clamp, matrix recreation on input change) ensure broad compatibility without bloat. It condenses complex liquidity scanning into one tool: spot red "hot" bands as magnets, blue voids as FVGs. Unlike generic heatmaps, the proxy options and limit-aware design scale across timeframes/assets (e.g., forex vs. crypto), reducing the need for layered indicators.
How to Use
Setup: Apply as overlay. Defaults suit ~4-day 1H view; tune lookback/bins (e.g., 50x100 for intraday fine-detail, but watch 5000 cap—errors auto-flag excesses). Select "POC Weighted" for nuanced clustering, "Even" for simplicity. Customize palette (e.g., desaturate for dark themes).
Reading the Heatmap:
X-Axis (Time): Left=older (fainter context), right=recent focus; tracks evolving liquidity trails.
Y-Axis (Price): Bottom=range low, top=high; vertical density shows price-level attraction.
Colors: Faint blue (sparse volume, possible inefficiencies) → vivid red (dense activity, likely SR). Horizontal streaks = sustained value zones.
Trading Insights: Price wicking into red? Anticipate fills/reversals. Blue gaps post-break? Targets for retraces. Ideal on 5M–Daily; layer with candlesticks off for purity.
Example: In BTCUSD 4H, a yellow-red band at $60K from prior consolidation → treat as dynamic support for longs on dips.
Tips
Balance settings: High bins = sharper verticals but cap lookback (e.g., 80x60=4800 cells). Test on volatile pairs first.
"POC Weighted" excels in ranging markets; switch to "Even" for trending (avoids close-bias skew).
For deeper analysis, screenshot/export or pair with divergence tools; add manual alerts via box counts if extended.
Efficiency: Last-bar only keeps it snappy; refresh on input tweaks.
Limitations & Disclaimer
Visualization is historical/proxy-based—lagging by one bar, no forward projection or tick-level precision (close-as-POC is estimate). Clipping may trim outlier wicks; low-volume bars dilute globally. Stepped colors are relative (max scales per redraw), potentially compressing extremes. Exceeds 5000 cells? Runtime error halts—no fallback resize. Not real liquidity (volume ≠ depth); best as visual aid, not quantitative. Updates post-close only. Backtest zones on specific symbols—correlation ≠ causation. Not advice; trade responsibly. Ideas in comments!
MILLION MEN - MatrixWhat it is
MILLION MEN – Matrix is a confluence tool that blends a multi-horizon directional heatmap (10→120 windows, LinReg/Slope) with a refined VZO-style volume oscillator to highlight accumulation vs. overbought regimes and print concise BUY/SELL labels only when both sides align. It’s designed for visual clarity and discretionary workflows—not a black-box signal engine.
How it works (high level)
Directional heatmap: 12 windows (10..120). Counts positive vs. negative slopes.
Accumulation zone: negCnt ≥ threshold (default 12-level threshold).
Overbought zone: posCnt ≥ threshold.
Optional bar coloring with transparency.
VZO-style engine: volume direction via price delta, linear-regression normalization, optional smoothing/noise filter, and explicit repaint toggle for intrabar responsiveness.
Confluence signals:
BUY when heatmap = accumulation and VZO makes a bullish triangle (crossover from below a lower band).
SELL when heatmap = overbought and VZO makes a bearish triangle (crossunder from above an upper band).
Quality-of-life: a cyan CONFOR dot marks “green→neutral + bullish body” near recent BUY; a compact profit panel tracks entry, live/max %, TP1/TP2/TP3 stamps, and a special Exit 100% event.
How to use
Treat signals as contextual prompts. Accumulation+VZO upturn hints at potential mean-reversion/expansion; Overbought+VZO downturn warns of exhaustion. Calibrate: heatmap threshold, VZO length/bands, smoothing/noise, and the repaint setting (on = faster intrabar feedback; off = close-confirmed).
Originality & value
Instead of a simple mashup, Matrix enforces dual confirmation: breadth across 12 directional windows plus a normalized volume-pressure oscillator. The result is a stable, readable regime map with minimal labels and a built-in progress panel—useful as a primary bias filter or an add-on to your setups.
Tested markets
Primarily tested on Gold (XAUUSD) and major crypto assets (BTC, XRP, ETH, BNB, LTC).
Behavior on other symbols may vary—validate before use.
Designed for analysis on the Daily timeframe (1D). Non-standard chart types are not supported for
Limitations & transparency
Strong trends can keep regimes extended; add structure/HTF/volume confirmation.
Repaint option can change intrabar labels; use close-confirmed mode if you prefer stability.
Non-standard bar types aren’t supported for signal logic.
No future data is used. This is not financial advice.
Arabic summary (optional)
أداة “Matrix” تجمع خريطة اتجاه متعددة الآفاق (10→120) مع مذبذب حجمي محسّن بأسلوب VZO لإبراز مناطق تجميع مقابل تشبّع/ارتفاع مبالغ، وتطبع BUY/SELL فقط عند توافق الشرطين. مُجرّبة أساسًا على الذهب (XAUUSD) والعملات الرئيسية (BTC, XRP, ETH, BNB, LTC). يُنصح بالتحقق في الأسواق الأخرى وباستخدام وضع الإغلاق لمنع أي تغيّر لحظي (repaint)
: مُصمّم للتحليل على الإطار اليومي (1D). أنواع الشموع غير القياسية غير مدعومة للإشارات.
Volume Heatmap + Buy/Sell splitits the most powerful volume based heatmap you can see on this platform. It tells you when the high volume is coming into the market with clear signs.
Sell - You will see the red bar below the split to confirm its a sell and the strength or the sell you can see above the split line in various colors e.g. lite green (low) to Dark red (extra high).
Buy - If there is a Buying trade being registered, it will appear above the spit line in opaque green with the heatmap colors to show the strength of volume.
This tool will help you identify the volume strength and based on that you can plan your trade.
PS, its always recommended to not to rely on a single oscillator and combine few. I would recommend you to use RSI and S/R lines with this for better decision.
Note, this tool has been put together for educational purposes and I do not take any responsibility of your trade.
Range Oscillator (Zeiierman)█ Overview
Range Oscillator (Zeiierman) is a dynamic market oscillator designed to visualize how far the price is trading relative to its equilibrium range. Instead of relying on traditional overbought/oversold thresholds, it uses adaptive range detection and heatmap coloring to reveal where price is trading within a volatility-adjusted band.
The oscillator maps market movement as a heat zone, highlighting when the price approaches the upper or lower range boundaries and signaling potential breakout or mean-reversion conditions.
Highlights
Adaptive range detection based on ATR and weighted price movement.
Heatmap-driven coloring that visualizes volatility pressure and directional bias.
Clear transition zones for detecting trend shifts and equilibrium points.
█ How It Works
⚪ Range Detection
The indicator identifies a dynamic price range using two main parameters:
Minimum Range Length: The number of bars required to confirm that a valid range exists.
Range Width Multiplier: Expands or contracts the detected range proportionally to the ATR (Average True Range).
This approach ensures that the oscillator automatically adapts to both trending and ranging markets without manual recalibration.
⚪ Weighted Mean Calculation
Instead of a simple moving average, the script calculates a weighted equilibrium mean based on the size of consecutive candle movements:
Larger price changes are given greater weight, emphasizing recent volatility.
⚪ Oscillator Formula
Once the range and equilibrium mean are defined, the oscillator computes:
Osc = 100 * (Close - Mean) / RangeATR
This normalizes price distance relative to the dynamic range size — producing consistent readings across volatile and quiet periods.
█ Heatmap Logic
The Range Oscillator includes a built-in heatmap engine that color-codes each oscillator value based on recent price interaction intensity:
Strong Bullish Zones: Bright green — price faces little resistance upward.
Weak Bullish Zones: Muted green — uptrend continuation but with minor hesitation.
Transition Zones: Blue — areas of uncertainty or trend shift.
Weak Bearish Zones: Maroon — downtrend pressure but soft momentum.
Strong Bearish Zones: Bright red — strong downside continuation with low resistance.
Each color band adapts dynamically using:
Number of Heat Levels: Controls granularity of the heatmap.
Minimum Touches per Level: Defines how reactive or “sensitive” each color zone is.
█ How to Use
⚪ Trend & Momentum Confirmation
When the oscillator stays above +0 with green coloring, it suggests sustained bullish pressure.
Similarly, readings below –0 with red coloring, it suggests sustained bearish pressure.
⚪ Range Breakouts
When the oscillator line breaks above +100 or below –100, the price is exceeding its normal volatility range, often signaling breakout potential or exhaustion extremes.
⚪ Mean Reversion Trades
Look for the oscillator to cross back toward zero after reaching an extreme. These transitions (often marked by blue tones) can identify early reversals or range resets.
⚪ Divergence
Use oscillator peaks and troughs relative to price action to spot hidden strength or weakness before the next move.
█ Settings
Minimum Range Length: Number of bars needed to confirm a valid range.
Range Width Multiplier: Expands or contracts range width based on ATR.
Number of Heat Levels: Number of gradient bands used in the oscillator.
Minimum Touches per Level: Sensitivity threshold for when a zone becomes “hot.”
-----------------
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.
Historical Matrix Analyzer [PhenLabs]📊Historical Matrix Analyzer
Version: PineScriptv6
📌Description
The Historical Matrix Analyzer is an advanced probabilistic trading tool that transforms technical analysis into a data-driven decision support system. By creating a comprehensive 56-cell matrix that tracks every combination of RSI states and multi-indicator conditions, this indicator reveals which market patterns have historically led to profitable outcomes and which have not.
At its core, the indicator continuously monitors seven distinct RSI states (ranging from Extreme Oversold to Extreme Overbought) and eight unique indicator combinations (MACD direction, volume levels, and price momentum). For each of these 56 possible market states, the system calculates average forward returns, win rates, and occurrence counts based on your configurable lookback period. The result is a color-coded probability matrix that shows you exactly where you stand in the historical performance landscape.
The standout feature is the Current State Panel, which provides instant clarity on your active market conditions. This panel displays signal strength classifications (from Strong Bullish to Strong Bearish), the average return percentage for similar past occurrences, an estimated win rate using Bayesian smoothing to prevent small-sample distortions, and a confidence level indicator that warns you when insufficient data exists for reliable conclusions.
🚀Points of Innovation
Multi-dimensional state classification combining 7 RSI levels with 8 indicator combinations for 56 unique trackable market conditions
Bayesian win rate estimation with adjustable smoothing strength to provide stable probability estimates even with limited historical samples
Real-time active cell highlighting with “NOW” marker that visually connects current market conditions to their historical performance data
Configurable color intensity sensitivity allowing traders to adjust heat-map responsiveness from conservative to aggressive visual feedback
Dual-panel display system separating the comprehensive statistics matrix from an easy-to-read current state summary panel
Intelligent confidence scoring that automatically warns traders when occurrence counts fall below reliable thresholds
🔧Core Components
RSI State Classification: Segments RSI readings into 7 distinct zones (Extreme Oversold <20, Oversold 20-30, Weak 30-40, Neutral 40-60, Strong 60-70, Overbought 70-80, Extreme Overbought >80) to capture momentum extremes and transitions
Multi-Indicator Condition Tracking: Simultaneously monitors MACD crossover status (bullish/bearish), volume relative to moving average (high/low), and price direction (rising/falling) creating 8 binary-encoded combinations
Historical Data Storage Arrays: Maintains rolling lookback windows storing RSI states, indicator states, prices, and bar indices for precise forward-return calculations
Forward Performance Calculator: Measures price changes over configurable forward bar periods (1-20 bars) from each historical state, accumulating total returns and win counts per matrix cell
Bayesian Smoothing Engine: Applies statistical prior assumptions (default 50% win rate) weighted by user-defined strength parameter to stabilize estimated win rates when sample sizes are small
Dynamic Color Mapping System: Converts average returns into color-coded heat map with intensity adjusted by sensitivity parameter and transparency modified by confidence levels
🔥Key Features
56-Cell Probability Matrix: Comprehensive grid displaying every possible combination of RSI state and indicator condition, with each cell showing average return percentage, estimated win rate, and occurrence count for complete statistical visibility
Current State Info Panel: Dedicated display showing your exact position in the matrix with signal strength emoji indicators, numerical statistics, and color-coded confidence warnings for immediate situational awareness
Customizable Lookback Period: Adjustable historical window from 50 to 500 bars allowing traders to focus on recent market behavior or capture longer-term pattern stability across different market cycles
Configurable Forward Performance Window: Select target holding periods from 1 to 20 bars ahead to align probability calculations with your trading timeframe, whether day trading or swing trading
Visual Heat Mapping: Color-coded cells transition from red (bearish historical performance) through gray (neutral) to green (bullish performance) with intensity reflecting statistical significance and occurrence frequency
Intelligent Data Filtering: Minimum occurrence threshold (1-10) removes unreliable patterns with insufficient historical samples, displaying gray warning colors for low-confidence cells
Flexible Layout Options: Independent positioning of statistics matrix and info panel to any screen corner, accommodating different chart layouts and personal preferences
Tooltip Details: Hover over any matrix cell to see full RSI label, complete indicator status description, precise average return, estimated win rate, and total occurrence count
🎨Visualization
Statistics Matrix Table: A 9-column by 8-row grid with RSI states labeling vertical axis and indicator combinations on horizontal axis, using compact abbreviations (XOverS, OverB, MACD↑, Vol↓, P↑) for space efficiency
Active Cell Indicator: The current market state cell displays “⦿ NOW ⦿” in yellow text with enhanced color saturation to immediately draw attention to relevant historical performance
Signal Strength Visualization: Info panel uses emoji indicators (🔥 Strong Bullish, ✅ Bullish, ↗️ Weak Bullish, ➖ Neutral, ↘️ Weak Bearish, ⛔ Bearish, ❄️ Strong Bearish, ⚠️ Insufficient Data) for rapid interpretation
Histogram Plot: Below the price chart, a green/red histogram displays the current cell’s average return percentage, providing a time-series view of how historical performance changes as market conditions evolve
Color Intensity Scaling: Cell background transparency and saturation dynamically adjust based on both the magnitude of average returns and the occurrence count, ensuring visual emphasis on reliable patterns
Confidence Level Display: Info panel bottom row shows “High Confidence” (green), “Medium Confidence” (orange), or “Low Confidence” (red) based on occurrence counts relative to minimum threshold multipliers
📖Usage Guidelines
RSI Period
Default: 14
Range: 1 to unlimited
Description: Controls the lookback period for RSI momentum calculation. Standard 14-period provides widely-recognized overbought/oversold levels. Decrease for faster, more sensitive RSI reactions suitable for scalping. Increase (21, 28) for smoother, longer-term momentum assessment in swing trading. Changes affect how quickly the indicator moves between the 7 RSI state classifications.
MACD Fast Length
Default: 12
Range: 1 to unlimited
Description: Sets the faster exponential moving average for MACD calculation. Standard 12-period setting works well for daily charts and captures short-term momentum shifts. Decreasing creates more responsive MACD crossovers but increases false signals. Increasing smooths out noise but delays signal generation, affecting the bullish/bearish indicator state classification.
MACD Slow Length
Default: 26
Range: 1 to unlimited
Description: Defines the slower exponential moving average for MACD calculation. Traditional 26-period setting balances trend identification with responsiveness. Must be greater than Fast Length. Wider spread between fast and slow increases MACD sensitivity to trend changes, impacting the frequency of indicator state transitions in the matrix.
MACD Signal Length
Default: 9
Range: 1 to unlimited
Description: Smoothing period for the MACD signal line that triggers bullish/bearish state changes. Standard 9-period provides reliable crossover signals. Shorter values create more frequent state changes and earlier signals but with more whipsaws. Longer values produce more confirmed, stable signals but with increased lag in detecting momentum shifts.
Volume MA Period
Default: 20
Range: 1 to unlimited
Description: Lookback period for volume moving average used to classify volume as “high” or “low” in indicator state combinations. 20-period default captures typical monthly trading patterns. Shorter periods (10-15) make volume classification more reactive to recent spikes. Longer periods (30-50) require more sustained volume changes to trigger state classification shifts.
Statistics Lookback Period
Default: 200
Range: 50 to 500
Description: Number of historical bars used to calculate matrix statistics. 200 bars provides substantial data for reliable patterns while remaining responsive to regime changes. Lower values (50-100) emphasize recent market behavior and adapt quickly but may produce volatile statistics. Higher values (300-500) capture long-term patterns with stable statistics but slower adaptation to changing market dynamics.
Forward Performance Bars
Default: 5
Range: 1 to 20
Description: Number of bars ahead used to calculate forward returns from each historical state occurrence. 5-bar default suits intraday to short-term swing trading (5 hours on hourly charts, 1 week on daily charts). Lower values (1-3) target short-term momentum trades. Higher values (10-20) align with position trading and longer-term pattern exploitation.
Color Intensity Sensitivity
Default: 2.0
Range: 0.5 to 5.0, step 0.5
Description: Amplifies or dampens the color intensity response to average return magnitudes in the matrix heat map. 2.0 default provides balanced visual emphasis. Lower values (0.5-1.0) create subtle coloring requiring larger returns for full saturation, useful for volatile instruments. Higher values (3.0-5.0) produce vivid colors from smaller returns, highlighting subtle edges in range-bound markets.
Minimum Occurrences for Coloring
Default: 3
Range: 1 to 10
Description: Required minimum sample size before applying color-coded performance to matrix cells. Cells with fewer occurrences display gray “insufficient data” warning. 3-occurrence default filters out rare patterns. Lower threshold (1-2) shows more data but includes unreliable single-event statistics. Higher thresholds (5-10) ensure only well-established patterns receive visual emphasis.
Table Position
Default: top_right
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the 56-cell statistics matrix table. Position to avoid overlapping critical price action or other indicators on your chart. Consider chart orientation and candlestick density when selecting optimal placement.
Show Current State Panel
Default: true
Options: true, false
Description: Toggle visibility of the dedicated current state information panel. When enabled, displays signal strength, RSI value, indicator status, average return, estimated win rate, and confidence level for active market conditions. Disable to declutter charts when only the matrix table is needed.
Info Panel Position
Default: bottom_left
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the current state information panel (when enabled). Position independently from statistics matrix to optimize chart real estate. Typically placed opposite the matrix table for balanced visual layout.
Win Rate Smoothing Strength
Default: 5
Range: 1 to 20
Description: Controls Bayesian prior weighting for estimated win rate calculations. Acts as virtual sample size assuming 50% win rate baseline. Default 5 provides moderate smoothing preventing extreme win rate estimates from small samples. Lower values (1-3) reduce smoothing effect, allowing win rates to reflect raw data more directly. Higher values (10-20) increase conservatism, pulling win rate estimates toward 50% until substantial evidence accumulates.
✅Best Use Cases
Pattern-based discretionary trading where you want historical confirmation before entering setups that “look good” based on current technical alignment
Swing trading with holding periods matching your forward performance bar setting, using high-confidence bullish cells as entry filters
Risk assessment and position sizing, allocating larger size to trades originating from cells with strong positive average returns and high estimated win rates
Market regime identification by observing which RSI states and indicator combinations are currently producing the most reliable historical patterns
Backtesting validation by comparing your manual strategy signals against the historical performance of the corresponding matrix cells
Educational tool for developing intuition about which technical condition combinations have actually worked versus those that feel right but lack historical evidence
⚠️Limitations
Historical patterns do not guarantee future performance, especially during unprecedented market events or regime changes not represented in the lookback period
Small sample sizes (low occurrence counts) produce unreliable statistics despite Bayesian smoothing, requiring caution when acting on low-confidence cells
Matrix statistics lag behind rapidly changing market conditions, as the lookback period must accumulate new state occurrences before updating performance data
Forward return calculations use fixed bar periods that may not align with actual trade exit timing, support/resistance levels, or volatility-adjusted profit targets
💡What Makes This Unique
Multi-Dimensional State Space: Unlike single-indicator tools, simultaneously tracks 56 distinct market condition combinations providing granular pattern resolution unavailable in traditional technical analysis
Bayesian Statistical Rigor: Implements proper probabilistic smoothing to prevent overconfidence from limited data, a critical feature missing from most pattern recognition tools
Real-Time Contextual Feedback: The “NOW” marker and dedicated info panel instantly connect current market conditions to their historical performance profile, eliminating guesswork
Transparent Occurrence Counts: Displays sample sizes directly in each cell, allowing traders to judge statistical reliability themselves rather than hiding data quality issues
Fully Customizable Analysis Window: Complete control over lookback depth and forward return horizons lets traders align the tool precisely with their trading timeframe and strategy requirements
🔬How It Works
1. State Classification and Encoding
Each bar’s RSI value is evaluated and assigned to one of 7 discrete states based on threshold levels (0: <20, 1: 20-30, 2: 30-40, 3: 40-60, 4: 60-70, 5: 70-80, 6: >80)
Simultaneously, three binary conditions are evaluated: MACD line position relative to signal line, current volume relative to its moving average, and current close relative to previous close
These three binary conditions are combined into a single indicator state integer (0-7) using binary encoding, creating 8 possible indicator combinations
The RSI state and indicator state are stored together, defining one of 56 possible market condition cells in the matrix
2. Historical Data Accumulation
As each bar completes, the current state classification, closing price, and bar index are stored in rolling arrays maintained at the size specified by the lookback period
When the arrays reach capacity, the oldest data point is removed and the newest added, creating a sliding historical window
This continuous process builds a comprehensive database of past market conditions and their subsequent price movements
3. Forward Return Calculation and Statistics Update
On each bar, the indicator looks back through the stored historical data to find bars where sufficient forward bars exist to measure outcomes
For each historical occurrence, the price change from that bar to the bar N periods ahead (where N is the forward performance bars setting) is calculated as a percentage return
This percentage return is added to the cumulative return total for the specific matrix cell corresponding to that historical bar’s state classification
Occurrence counts are incremented, and wins are tallied for positive returns, building comprehensive statistics for each of the 56 cells
The Bayesian smoothing formula combines these raw statistics with prior assumptions (neutral 50% win rate) weighted by the smoothing strength parameter to produce estimated win rates that remain stable even with small samples
💡Note:
The Historical Matrix Analyzer is designed as a decision support tool, not a standalone trading system. Best results come from using it to validate discretionary trade ideas or filter systematic strategy signals. Always combine matrix insights with proper risk management, position sizing rules, and awareness of broader market context. The estimated win rate feature uses Bayesian statistics specifically to prevent false confidence from limited data, but no amount of smoothing can create reliable predictions from fundamentally insufficient sample sizes. Focus on high-confidence cells (green-colored confidence indicators) with occurrence counts well above your minimum threshold for the most actionable insights.
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.
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.
