Volume Liquidity Trend [ChartPrime]Volume Liquidity Trend
🔶 OVERVIEW
Standard trend indicators track price direction but completely ignore the volume profile structural footprints left behind during the trend's development. The Volume Liquidity Trend indicator solves this by combining advanced mathematical smoothing with a dynamic, trend-isolated Volume Node Mapping Engine .
This script filters price streams through a stabilization algorithm to establish a core trend, tracks the exact duration of that trend lifecycle, and continuously projects significant historical volume anchors into the future as active liquidity levels until price completely invalidates or "mitigates" them.
🔶 HOW IT WORKS
The indicator executes its calculations through a multi-tiered pipeline:
Kalman-Based Trend Filter: The indicator filters a user-defined price source using an adaptive stabilization equation. It calculates volatility bands relative to this smoothed average (using a 2 x ATR boundary). A close above the upper band establishes a Bullish Trend , while a close below the lower band triggers a Bearish Trend .
Trend-Isolated Volume Mapping: When a trend changes, a clean data sweep resets the history array. The script tracks every single candle inside the active trend and identifies the absolute highest transaction point (the 100% Peak Volume Anchor).
Normalized Liquidity Vectors: Every candle within the trend has its volume calculated relative to that peak volume anchor (0% to 100%). If a historical level passes your volume cutoff threshold, the script maps a horizontal liquidity line from that candle's average price (HLC3) out into the future margin space.
Automated Mitigation Tracking: The script continuously tests these horizontal volume tracks against historical price action. If subsequent candle bodies cross through an established volume line, that line is marked as "mitigated" (crossed) and automatically stripped from the screen to keep your chart uncluttered.
🔶 KEY FEATURES
Adaptive Vector Widths & Gradients: Unmitigated volume lines feature a dynamic visual profile. Lines are automatically thicker and more heavily saturated based on their relative volume strength. Furthermore, lines dynamically shift color depending on whether price is trading above (Bullish Support) or below (Bearish Resistance) the volume node.
Anomalous 100% Peak Tracker: Includes a specialized alert line that forces the historical 100% transaction anchor to remain visible as a bright dashed line only after price has broken through it, signaling a breached institutional base.
Real-Time Trend Analytics Panel: A sleek UI dashboard positioned at the top right tracking:
• Current Trend Status: Active market direction matching the volatility bands.
• Trend Duration: Exact bar runtime age since the initial structural breakout.
• 100% Vol Level: The exact price coordinate where the heaviest volume anomaly occurred during the current sequence.
🔶 TRADING APPLICATIONS
High-Volume Pullback Entries: During a strong trend, look for pullback entries directly into unmitigated lines that have high volume percentages (75% - 95%). These thick vector nodes represent massive resting buy/sell block clusters where institutions are likely to defend their positions.
Breakout Confirmation Diamonds: The trend reversal points are highlighted on your chart with sharp diamond markers. A breakout accompanied by an immediate generation of high-percentage liquidity trails suggests an institutional backed expansion.
Support & Resistance Confluence Trim: When multiple volume lines cluster closely together at a specific price zone, it builds a structural wall of institutional liquidity, marking a prime zone for target take-profits or reversal entries.
🔶 SETTINGS
Stabilization Coefficient: Controls the responsiveness of the underlying filtering mechanism. Lower values yield exceptionally smooth lines that are highly tolerant of short-term volatility spikes.
Volume Cutoff Threshold: The sensitivity slider for plotting liquidity vectors (0.0 to 1.0). A higher setting like 0.50 filters out quiet trading periods and only draws lines for bars with significant volume footprints.
Extend Lines Into Future: Determines the number of bars to project active unmitigated volume tracks into the right-hand margin blank space.
🔶 CONCLUSION
The Volume Liquidity Trend indicator offers an institutional perspective by integrating volume data directly into a trailing trend model. By isolating volume profile nodes specifically to the lifetime of the current trend and introducing adaptive coloring based on price positioning, it ensures your support and resistance targets perfectly match real-time market participant behavior. Indicator
Liquidity Heatmap 3D - Volume Density POC CVDLIQUIDITY HEATMAP 3D — the order-flow heatmap look, rebuilt for PulseWire.
This indicator brings the volume-density heatmap visual to any PulseWire chart, with a twist no other heatmap here has: a real 3D relief shader. Instead of flat colour tiles, every cell is lit by a virtual light source (emboss lighting computed in the colour math), and the strongest liquidity walls extrude as 3D blocks with shaded side faces and lit top caps.
━━━ HOW IT WORKS ━━━
PulseWire provides no order book and no historical tick data, so this is an honest volume-density heatmap: each bar's volume is distributed across the price zones its range covered. Dense zones are the liquidity walls where the market actually spent volume. The engine normalises against the 85th percentile of the column maxima, so one hot spike never blanks out the rest of the map.
━━━ WHAT IS ON THE CHART ━━━
· Heatmap grid up to 22 x 28 zones, rebuilt live on every bar
· 3D RELIEF SHADER — emboss lighting, specular glints on the wall tops, adjustable strength
· 3D WALL EXTRUSION — the strongest cells pop out as shaded blocks (toggle)
· 7 PALETTES — GOLD 3D (default), TWILIGHT, FIRE & ICE (buy/sell split), OCEAN, INFERNO, EMERALD, MONO
· POC LINE — the highest-volume price of the window, with its volume readout
· WALL DETECTION — the two strongest active liquidity walls, labelled with their strength in percent
· VOLUME PROFILE — profile bars on the right, POC highlighted in gold
· TRADE BUBBLES — volume-spike bubbles sized by their ratio against the average, buy blue / sell magenta
· CVD STRIP — cumulative volume delta (bar proxy) along the bottom, mint and red
· COCKPIT PANEL — engine checklist, POC box and a BUY / SELL flow signal line
· Optional dark chart theme: navy background with mint / red bars
━━━ HOW TO USE IT ━━━
1. Watch the golden walls: price often reacts at dense volume zones — support and resistance built by traded volume rather than by drawn lines.
2. The POC is the fairest price of the window and acts as a mean-reversion magnet in ranges.
3. CVD rising while price holds a wall below it is an absorption long idea; CVD falling at a wall above is a distribution short idea.
4. Bubbles mark the bars where outsized volume hit. Combine them with wall touches for confluence.
━━━ SETTINGS ━━━
Grid size, bars per column, cutoff, gamma, tile transparency, relief strength, wall threshold and bubble threshold are all adjustable. Works on every symbol and timeframe; if a symbol carries no volume the engine falls back to time-at-price density and says so in the panel.
━━━ HONEST LIMITS ━━━
This is not level-2 order book data — PulseWire does not provide it. The map shows where volume actually traded, not resting limit orders. The 3D effect is a rendering technique, not extra data.
━━━ NOTE ON LOADING ━━━
Right after adding the indicator, or after changing a setting, give it a few seconds: the engine creates its object pools and runs the first build. A brief flicker during that warm-up is normal and stops once the first refresh is done. After that the persistent engine updates in place with no flicker.
Open source — read it, change it, learn from it. This indicator is a study tool, not financial advice.
WHY THESE PARTS BELONG TOGETHER
The heatmap, the point of control and the cumulative delta strip are three views of one question:
where is volume sitting, which price is defending it, and who is doing the trading. The heatmap
shows the distribution, the point of control marks its centre of gravity, and the delta strip says
whether that distribution is being built by buyers or sellers. Read on their own each of the three
is ambiguous; read together they describe one order-flow picture.
Indicator
Liquidity HeatmapLiquidity Heatmap – POC and Value Area.
A rolling volume-density profile rendered directly onto the price chart. Over a configurable lookback window the indicator distributes each historical bar's volume across every price bin its high-low range covered, then draws the resulting distribution as color-graded horizontal lines at each bin's midpoint. Point of Control and Value Area (70 % of total volume) are computed automatically, and a compact right-side histogram mirrors the profile in the future-offset zone. Built for intraday and swing traders who want a live, minimal read of where the market actually did business — the real liquidity anchors, not manual pivots.
How it works:
The indicator recalculates every N bars (default 5). On each recalc it finds the highest and lowest price of the lookback window, splits that range into a configurable number of bins (default 40), and iterates through every bar in the window. For each bar its volume — or a unit weight if volume weighting is disabled — is added to every bin whose price range the bar crossed. The result is a density array: the more time price stayed inside a bin and the higher the volume of those bars, the larger its density value. Bins are drawn as thin horizontal lines at their midpoints, with color and transparency scaled by the ratio of bin density to peak density.
The Point of Control is the bin with the largest total. Value Area is grown outward from POC, alternately taking whichever adjacent side holds more volume, until 70 % of the entire distribution is covered — VAH becomes the upper boundary of that region and VAL the lower. A right-side density histogram in the chart's offset zone re-renders the same profile in bar-chart form, and the level labels (POC / VAH / VAL) sit past the histogram so they never overlap the main heatmap. The information panel in the top-right corner shows the numeric price of each level and its signed percentage delta to the current close, color-coded green when the level sits above price, red when below, gray at parity.
What it calculates:
- Volume density per price bin over the lookback window
- POC — Point of Control, the bin with peak accumulated volume
- VAH — Value Area High, upper boundary of the 70 % volume region
- VAL — Value Area Low, lower boundary of the 70 % volume region
- Signed delta from current close to POC / VAH / VAL, in percent
Key features:
- Rolling recalculation every N bars for tunable CPU / responsiveness balance
- Volume weighting (default) or touch-count mode as a per-price frequency map — useful when volume data is unreliable
- Four-stop plasma color gradient (deep navy → violet → magenta → amber), every stop user-overridable via input.color
- Constant 1-pixel line width across all bins; visual weight is carried entirely by color intensity and transparency
- POC solid line and label placed past the offset histogram for readability
- VAH / VAL dashed lines extended all the way to their labels so the eye follows the level continuously
- Compact right-side density histogram in the future-offset area, mirroring the main profile in bar-chart form
- Top-right information panel with POC / VAH / VAL price and signed percentage delta to the current close, colored by side (green above / red below / gray at parity)
- Independent visibility toggles for POC and Value Area
- Adaptive bin geometry — resolution scales automatically with the price range of the lookback window
- Runs on any timeframe and any instrument; no external data sources required
Who it's for:
Intraday scalpers, swing traders, order-flow and Market Profile practitioners who need to see the true volume anchors of the current regime instead of hand-drawn horizontals. The color-graded strips make dominant liquidity walls, thin gaps and Value Area boundaries visually obvious at a glance, so attention goes to execution rather than to marking up the chart. Indicator
Liquidation Magnet [Quantum Algo]Liquidation Magnet
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🔶 OVERVIEW
Liquidation Magnet estimates where over-leveraged long and short positions are likely to be liquidated, builds decaying volume-weighted clusters at those levels, and renders them as heat ladders directly on your chart. A gold magnet beam locks onto the strongest nearby pool, purge flashes mark the moment price sweeps through a cluster, and a statistics panel tracks how often those sweeps actually reverse on the exact symbol and timeframe you are trading.
The idea is simple and powerful: price does not wander randomly — it is drawn toward liquidity. The largest pockets of forced orders sit where crowded positions get liquidated. This tool maps those pockets, weighs them, and watches them get consumed.
Important honesty note, up front: every level in this indicator is an ESTIMATE derived from price structure and typical leverage tiers. This script does not read exchange liquidation feeds or order-book data, and no indicator on this platform can. Anyone claiming otherwise is guessing with extra steps. This tool guesses transparently — and then measures itself.
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🔶 WHAT IS A LIQUIDATION MAGNET?
When traders open leveraged positions near a swing high or swing low, their liquidation prices sit at fixed, mathematically determined distances from their entries. A crowd of 25x longs opened near a swing low will be liquidated roughly four percent below it. A crowd of 50x shorts opened near a swing high will be liquidated roughly two percent above it.
Those liquidation prices are where forced market orders wait. Forced orders are fuel. Markets are drawn toward fuel — sweep the pool, fill the orders, and very often reverse once the fuel is spent. That pull is the "magnet."
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🔶 WHY IS THIS ORIGINAL?
1. Cluster model, not static lines. Swing anchors project liquidation estimates through four leverage tiers (10x, 25x, 50x, 100x, each toggleable). Nearby estimates MERGE into clusters whose mass grows with the volume behind the anchoring swing — scattered guesses become weighted zones.
2. Living decay engine. Positions close, stops move, the crowd rotates. Every cluster loses mass each bar and dies when it fades — or the instant price sweeps through it and consumes it. The map you see is current, never a museum of stale lines.
3. Purge detection with self-auditing statistics. When price trades through a pool, the tool prints a purge flash and then measures what happened next. The dashboard reports the ten-bar reversal rate after upward and downward purges — computed on your chart, shrunk toward neutral at small sample sizes, with a Wilson lower bound available in tooltips. The indicator grades its own thesis in public.
4. The magnet beam. Among all pools within reach, the strongest (mass discounted by distance) is highlighted with a gold beam from live price — a single glance answers "where is the nearest large pocket of fuel?"
5. Radical transparency in a genre full of implication. Every tooltip, the dashboard footer, and this description state plainly that levels are structural estimates, not exchange data.
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🔶 HOW IT WORKS
— Swing anchors: confirmed pivot highs and lows define where crowds of entries concentrate.
— Tier projection: each anchor projects liquidation estimates at the distances implied by common leverage tiers (about 1%, 2%, 4%, and 10% from entry).
— Mass: each projection carries mass scaled by the volume z-score at the anchor — swings formed on climactic volume imply larger crowds.
— Clustering: projections landing near an existing cluster merge into it, shifting its weighted center and adding mass.
— Decay and death: mass decays every bar; weak clusters are pruned; swept clusters are consumed immediately.
— Rendering: each cluster draws a trailing heat band across the chart plus a three-layer intensity ladder at the right edge — length and brightness scale with mass; the strongest pool burns gold.
— Purge statistics: after each sweep, the ten-bar outcome is recorded in first-in-first-out sample sets, and reversal rates are displayed with sample counts.
Everything is computed on confirmed bars. Signals and clusters do not repaint. All drawings are capped for performance.
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🔶 HOW TO USE IT
— Directional context: a heavy pool overhead with light fuel below suggests the path of least resistance is up (toward the fuel), and the Net Pull row quantifies this bias.
— Sweep-and-reversal trading: the classic use. Wait for price to purge a strong pool, check the dashboard's historical reversal rate for that direction on your symbol, and treat the purge as a candidate exhaustion point for your own entry method.
— Target selection: strong pools are natural take-profit magnets — many traders exit into the fuel rather than after it is spent.
— Risk placement: avoid resting stops just beyond a hot ladder; that is exactly where the market has an incentive to reach.
— Works on any symbol, but the leverage-tier logic is designed for crypto perpetual futures, where liquidation mechanics dominate intraday movement. Best on 15m to 4H.
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🔶 SETTINGS
— Swing Anchor Length: pivot size defining the anchoring swings.
— Leverage Tiers: toggle 10x / 25x / 50x / 100x projections independently.
— Maximum Clusters, Merge Tolerance, Mass Decay: control the density and lifespan of the map.
— Purge flashes, heat ladders, magnet beam, and ladder length are individually toggleable.
— Statistics: sample cap, minimum samples to grade, shrinkage strength, Wilson z-score.
— Full color and dashboard customization.
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🔶 ALERTS
— Approaching Magnet — price within half an Average True Range of an estimated pool.
— Upward Purge — an estimated short-liquidation pool was swept.
— Downward Purge — an estimated long-liquidation pool was swept.
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🔶 FAQ
Q: Is this real liquidation data from exchanges?
A: No — and this matters. PulseWire indicators cannot access exchange liquidation feeds or order books. Every level here is an estimate computed from price structure and the fixed mathematics of leverage. The tool is honest about this everywhere, and it compensates by measuring its own hit rate on your chart.
Q: Why do the estimated levels often line up with where price actually reverses?
A: Because liquidation math is public and mechanical. Everyone's 50x liquidation sits roughly two percent from entry, so crowded swings reliably produce crowded liquidation pockets — no private data required.
Q: Does it repaint?
A: No. Clusters form on confirmed pivots, purges are detected on confirmed bars, and consumed clusters stay consumed.
Q: Which markets and timeframes?
A: Designed for crypto perpetual futures on 15m–4H. The structural logic works elsewhere, but the leverage-tier assumptions are crypto-native.
Q: What do the reversal statistics mean?
A: After each purge, the tool records whether price moved back against the sweep over the next ten bars. Rates are shrunk toward fifty percent at low sample counts so early numbers cannot overstate the edge. They describe this chart's history only — they are not predictions.
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🔶 CREDITS
The liquidation-level mapping concept was popularized by crypto derivatives analytics platforms; pivot structure detection is classical technique; the Wilson score interval is by Edwin B. Wilson (1927). The cluster model, volume-weighted mass and decay engine, purge state machine, self-auditing statistics, and all code in this script are original work. No third-party or open-source script code was reused.
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🔶 LIMITATIONS
— All levels are estimates; actual liquidation prices vary with margin mode, maintenance margin, fees, and funding.
— The statistics describe historical behavior on the current chart only; past frequencies never guarantee future outcomes.
— On illiquid symbols or very low timeframes, swing anchors are noisier and clusters less meaningful.
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🔶 DISCLAIMER
This indicator is a research and charting tool provided for educational purposes. It is not financial advice, and no statistic shown is a promise of future performance. Trading leveraged instruments involves substantial risk of loss. Always do your own analysis and manage risk responsibly. Indicator
Liquidity Sweep Hunter Algo [AlgoAlpha]🟠 OVERVIEW
Liquidity Sweep Hunter Algo identifies liquidity highs and lows across three different lookback periods and keeps them active until they are mitigated. This creates a persistent view of where resting liquidity has formed instead of only showing the latest swing points.
The indicator also displays a heatmap that highlights the relative strength of active liquidity levels and generates reversal signals after price sweeps multiple visible liquidity bands before reclaiming them. Optional trade drawings project a stop loss, reward target, and intermediate target levels directly on the chart.
🟠 CONCEPTS
Liquidity Level — A price extreme detected from fast, medium, and slow lookback windows. Matching levels are merged so nearby highs or lows are treated as the same liquidity area.
Liquidity Heatmap — A visual strength map where colour represents the relative strength of each active liquidity level compared to the other visible levels.
Multi-Level Liquidity Sweep — A reversal condition where price sweeps at least two visible liquidity bands and then closes back beyond the reclaim level within a limited number of bars. An optional strength filter can require the swept levels to exceed a minimum average strength.
🟠 FEATURES
Liquidity Heatmap — Displays active liquidity levels using a colour gradient that reflects their relative strength.
Multi-Level Sweep Signals — Plots bullish and bearish reversal labels after confirmed liquidity sweep and reclaim events.
Trade Projection Boxes — Draws entry, stop loss, reward zone, and target milestone levels after each signal.
Trade Progress Display — Fills the target area as price reaches successive target levels and marks completed trades with a check mark.
🟠 HOW TO USE
Watch the heatmap to identify where stronger liquidity has accumulated around current price.
Wait for a bullish or bearish sweep signal after price clears multiple liquidity bands and reclaims the area.
Use the optional trade projection as a visual reference for the calculated stop loss, reward target, and target milestones.
Increase the lookback values to focus on broader liquidity zones or decrease them to detect more local levels.
Adjust the sweep strength filter if you want signals only when stronger liquidity zones are involved.
🟠 CONCLUSION
Liquidity Sweep Hunter Algo combines persistent liquidity mapping, a relative strength heatmap, and multi-level liquidity sweep detection in a single indicator. It also provides optional trade projections that remain on the chart after each signal. Together these features help traders monitor where liquidity has formed, when it has been swept, and where price has reclaimed the area. Indicator
Ultravol Matrix - volume spike heatmap [GF4M]Ultravol Matrix - cross-exchange volume spike heatmap
❗️Reason for displaying two indicators together on the main chart:
🔗 Use together for reading volume — Ultravol, Ultravol Matrix are originally built as one indicator, split in two due to Pine's 64-plot limit & multi-pane drawing limit. (same language by UV-scaled color): Ultravol Matrix reads vol spike history, Ultravol reads live.
❗️Per PulseWire's policy that each script's description must be self-contained on its own, the Ultravol engine description common to both Ultravol and Ultravol Matrix is repeated across both indicators' descriptions.
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🔶 PROBLEM
On a standard chart, volume is just numbers and bars, so to know how much weight is behind the current candle's move, you have to scan the whole chart yourself and judge relative size. Doing that instantly during live trading takes intuition built through long training. This problem is worse in crypto: since the same asset trades on dozens of exchanges at once, looking at a single exchange's volume alone doesn't show where the real volume spike actually is. I came to think there were two important points.
1. (Common) How much does this volume mean in the market as a whole?
Every asset has a normal, average scale at which it typically trades. If far more trading is happening than that, the asset is drawing attention right now. Conversely, even when candles look active and volume keeps increasing, if it stays below the whole-market average, it is actually a minor move. In other words, it should be readable instantly against the whole market — not against the immediately preceding period.
2. (Multi-exchange asset) Is this a market-wide event, or a local event on one exchange?
For an asset traded on dozens of exchanges at once, as in crypto, even a very large exchange's volume spike alone won't move the price much — because the remaining exchanges still hold volume that can't be ignored. The same spike means something completely different depending on whether it happens across many exchanges at once or only locally — and neither a single exchange's volume, nor a simple aggregate of them, shows this difference clearly (it ends up buried under the pattern of whichever pair has overwhelming volume, like Binance).
🔷 SOLUTION
1. (Common) The whole chart's accumulated average volume is extracted as a base line, and each bar's ratio to it is standardized into a common UV-scaled color. For crypto, one step further — the volumes of 12 major exchange pairs are each weighted by importance and composited into one Final Synthetic UV volume, used as the main volume. This way, every visual element on the chart can be drawn based on one common scale. This is Ultravol.
2. (Multi-exchange asset) The volume spike history of each of those same 12 sources, before Ultravol composites them into one, is decomposed along the time axis using the same UV-scaled color, so you can see at a glance whether the current spike spans the whole market or is local. This is Ultravol Matrix. (Originally one indicator, but split into two because the number of plots needed exceeded Pine's limit (64-plot) — the core engine is the same.)
Volume can now be perceived instantly. Candles carrying below-average volume stay dark and featureless; candles carrying above-average energy render brighter and more intense. The screen looks quiet when the market is quiet, and busy when it is busy. And this color grammar reads the same way on any asset, any timeframe — because the reference is always that market's own whole-history average. This indicator set can fully replace ordinary candles and volume charts.
🔷 Ultravol Core Engine: Processing Diagram
🟣 Full engine mechanics (Master GATE scheduling, coin-unit correction, per-exchange trust weighting, auto listing-join) are documented in the Appendix — see origin indicator .
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Ultravol Matrix - cross-exchange volume spike heatmap
✨ Gives you an insight into hidden, cross-exchange volume spike flow — by color, instantly!
Across many crypto exchanges, Ultravol Matrix curates 12 pairs (spot + perp) — Each exchange's volume, reverted to native base. → normalized to its own signature. → Rendered on the same UV-defined color scale. → Spike flow patterns (not absolute volume) can be compared directly across history in one matrix.
📘 Strong trends begin with cascading vol spikes across all exchanges.
📗 A perp vol spike with no spot participation (all or a single perp pair) is often just a futures liquidation cascade.
📙 Track vol spike trends by exchange. Who is trending? Alone? User base? Region? Spot or Perp? All together?
📕 Trending vol spike sequence — drop to lower TF (1m or seconds) to read the order in detail.
✨ Ultravol Matrix Engine:
Its own unique method. 12-pair per-exchange UV-scaled color leveling is crypto-exclusive.
🔹 How to read it
🔗 The time-axis extension of Ultravol — same language by UV-scaled color: Ultravol Matrix reads history, Ultravol reads live.
🔹 You can easily spot mass volume that's concentrated in a single exchange.
🔹 All together or single spike trending.
🔹 For altcoins, even on the 5m and 15m timeframes, persistent long spikes tend to occur on only a few individual exchanges. This behavior is less frequent in major cryptocurrencies like BTC or ETH. (It is recommended to familiarize yourself with the volume spike patterns of your specific trading pairs in advance.)
Setup Panel
☑ 📱 : Mobile friendly UI setup
• Source : Ultravol (Auto) fixed
• Rescale : Only for extremes, too 🔥 or too ⚫️
Especially for altcoins, the market heats up significantly during trending phases. Consequently, if the heatmap temperature rises to a point where chart variations become difficult to distinguish, lowering the rescale option by -1 or -2 makes it easier to discern the intensity differences on the screen. (In this case, the adjusted value is temporarily displayed in the bottom-right corner.)
🔸 Hover over the nametag for symbol info.
🔸 Maximize the pane (or drag it taller) for detailed matrix flow.
Matrix's volume spectrum is compressed using a separate log-based clamp to fit within a low-height panel. Read it only as relative magnitude — judge volume spikes by color, not by bar height.
⚠️ Required setting: In order to vertically align the Name tag (on matrix)
⚙︎ > Chart option > Canvas > Margins > Top: 0% Bottom: 0% Rights: 50bars
Indicator
Ultravol - correct market volume [GF4M]Ultravol - correct market volume
❗️Reason for displaying two indicators together on the main chart:
🔗 Use together for reading volume — Ultravol, Ultravol Matrix are originally built as one indicator, split in two due to Pine's 64-plot limit & multi-pane drawing limit. (same language by UV-scaled color): Ultravol Matrix reads vol spike history, Ultravol reads live.
❗️Per PulseWire's policy that each script's description must be self-contained on its own, the Ultravol engine description common to both Ultravol and Ultravol Matrix is repeated across both indicators' descriptions.
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🔶 PROBLEM
On a standard chart, volume is just numbers and bars, so to know how much weight is behind the current candle's move, you have to scan the whole chart yourself and judge relative size. Doing that instantly during live trading takes intuition built through long training. This problem is worse in crypto: since the same asset trades on dozens of exchanges at once, looking at a single exchange's volume alone doesn't show where the real volume spike actually is. I came to think there were two important points.
1. (Common) How much does this volume mean in the market as a whole?
Every asset has a normal, average scale at which it typically trades. If far more trading is happening than that, the asset is drawing attention right now. Conversely, even when candles look active and volume keeps increasing, if it stays below the whole-market average, it is actually a minor move. In other words, it should be readable instantly against the whole market — not against the immediately preceding period.
2. (Multi-exchange asset) Is this a market-wide event, or a local event on one exchange?
For an asset traded on dozens of exchanges at once, as in crypto, even a very large exchange's volume spike alone won't move the price much — because the remaining exchanges still hold volume that can't be ignored. The same spike means something completely different depending on whether it happens across many exchanges at once or only locally — and neither a single exchange's volume, nor a simple aggregate of them, shows this difference clearly (it ends up buried under the pattern of whichever pair has overwhelming volume, like Binance).
🔷 SOLUTION
1. (Common) The whole chart's accumulated average volume is extracted as a base line, and each bar's ratio to it is standardized into a common UV-scaled color. For crypto, one step further — the volumes of 12 major exchange pairs are each weighted by importance and composited into one Final Synthetic UV volume, used as the main volume. This way, every visual element on the chart can be drawn based on one common scale. This is Ultravol.
2. (Multi-exchange asset) The volume spike history of each of those same 12 sources, before Ultravol composites them into one, is decomposed along the time axis using the same UV-scaled color, so you can see at a glance whether the current spike spans the whole market or is local. This is Ultravol Matrix. (Originally one indicator, but split into two because the number of plots needed exceeded Pine's limit (64-plot) — the core engine is the same.)
Volume can now be perceived instantly. Candles carrying below-average volume stay dark and featureless; candles carrying above-average energy render brighter and more intense. The screen looks quiet when the market is quiet, and busy when it is busy. And this color grammar reads the same way on any asset, any timeframe — because the reference is always that market's own whole-history average. This indicator set can fully replace ordinary candles and volume charts.
🔷 Ultravol Engine: Processing Diagram
🟣 Check the Appendix — (16 live feeds/candle · coin-unit correction (1000x-listed coins) · USDT/USDC reference price conversion · Master GATE calc scheduling · per-exchange trust weighting · auto listing-join. Full mechanics + reusable code.)
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Ultravol - correct market volume
✨ Gives you a trained trader's sense for volume — by color, instantly!
📘 Reveal key market energy areas through volume-encoded candles, spectrum layer, v-ray, energy flux, and spike panel by color. A full legacy candle & volume chart replacement.
📗 Final synthetic UV — Across many crypto exchanges, Ultravol curates 12 (spot + perp) — reverted to native base → normalized & weighted by custom criteria, spot summed and perp summed separately (used as Energy Flux source), then combined into one — to read the unified volume flow across the whole market.
📙 Per-exchange UV level on the panel — Each exchange's volume, normalized to its own signature. → Rendered on the same UV-defined color scale. → Current candle's volume spike level (not raw volume) can be compared across exchanges at a glance.
✨ Ultravol engine:
Its own unique method. Synthetic UV (12-pair fusion) and Per-exchange UV-scaled color mark are crypto-exclusive — UV-scaled coloring works on any chart.
🔷 How to read it
It is recommended to check the color reference scheme in the settings panel to understand how candle colors are represented. Once you are familiar with these patterns, you can instantly gauge the intensity of current movements during live trading.
Refer to the historical patterns where rare, massive volume occurred (indicated by sky blue, blue, and purple - When similar volume occurs later, frequently become the Top or Bottom.)
Massive volume spike levels frequently act as strong S/R.
🔷 Basic Screen - check volume by color.
Spike Panel
This panel simultaneously displays the live candle volume in two ways: 1) as an absolute value in the base unit, and 2) as a UV-scaled mark. Users can quickly identify which exchange is experiencing a volume spike based solely on the colored emoji characters.
Status Label
The working mode automatically adjusts based on the selected symbol type and information, with the current status displayed via the label in the bottom-right corner.
Panel setup
☑ 📱 : Mobile friendly UI setup
• Source : Use Ultravol (Auto) normally
• Rescale : Only for extremes, too 🔥 or too ⚫️
☑ V-Ray : Vertical highlight marks on big spike.
☑ Energy Flux : 8 Spot(U), 4 Perp(L)
+ Trending energy balance (Spot vs Perp)
☑ Candles : Chart candle × UV fusion.
Each element—Volume, Volume-encoded Candlesticks (Up/Dn), and Ruler—features its own independent color scheme.
No volume chart color
☑ Spectrum : Synthetic UV from 12 vol src.
+ Instant energy read by UV-scaled color
+ Max height. Move to a pane first.
☑ Panel : Exchange's raw vol (number)
+ Current UV-scaled spike (color mark)
☑ s Smaller UI ☑ ↓ Center-right
☑ ! Wait Long · Act Fast (#1 principle)
🔸 Hover over the panel for detailed info.
Vol src info. & current status notice
Volume spike marking by unique UV-scaled color
Works together as one.
You can see historical spike flow and current spike details at the same time.
🔗 Ultravol Matrix reads vol spike history, Ultravol reads live.
⚠️ Ultravol must be placed at the very front.
(To ensure the correct z-layer order of all graphics, including hybrid override candles, is displayed exactly as intended. )
HELP: Check a tooltip on the setup panel & spike panel.
🟣 APPENDIX — A few notes on what happens inside UV engine.
💊 Master GATE (Calculation scheduling)
This indicator reads 16 external data sources in real time: the volumes of 12 exchange pairs, plus market cap, two stablecoin exchange rates, and the market average price. The computation that follows these calls is substantial. But volume is a simple cumulative value — I do not see immediate tick-by-tick recomputation as essential. So the work is divided into what happens when a candle opens (new), while it is in progress (realtime), and when it closes (confirmed) — and the heavy computation was judged reasonable to run only at fixed intervals during the candle. It is the internal scheduler that keeps the whole indicator responsive, and a precondition for this indicator to work at all.
// 🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦
// MASTER GATE - throttling setup
var bool uv_throttleGATE_required = uv_chart_symbol_crypto_basequotetickvol_flg
varip bool bar_NOTLIVE_flg = false
varip bool bar_GATEbypass_flg = false
bar_NOTLIVE_flg := uv_throttleGATE_required
and barstate.isrealtime and (timenow - (time_close + ((time_close - time)*2)) > 0)
bar_GATEbypass_flg := not (uv_throttleGATE_required and barstate.isrealtime and not bar_NOTLIVE_flg)
const int UV_MASTERGATE_RATE_T_VAL = 160 // ms
varip int uv_MasterGATE_last_t = na // Last GATE Open time = LINUX time ms
varip bool uv_MasterGATEopen_flg = false
uv_MasterGATEopen_flg := bar_GATEbypass_flg
or na(uv_MasterGATE_last_t)
or (timenow - uv_MasterGATE_last_t >= UV_MASTERGATE_RATE_T_VAL)
or barstate.isconfirmed
if not bar_GATEbypass_flg and uv_MasterGATEopen_flg
uv_MasterGATE_last_t := timenow
// MASTER GATE - throttling setup End
// 🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦🟧🟦
You can make this simple throttling GATE. After configuring the GATE operating conditions as shown above, you can apply them to the actual indicator calculation section by utilizing uv_MasterGATEopen_flg like below. It is simple yet effective. (Caution: Given how Pine Script executes, this GATE mechanism provides reasonable computational savings rather than perfect scheduling. For precise control, use it alongside barstate.isnew / isrealtime / isconfirmed)
if uv_MasterGATEopen_flg
s1_color_x := f_src_uv_lv_coloring(s1_uv_lv)
s2_color_x := f_src_uv_lv_coloring(s2_uv_lv)
s3_color_x := f_src_uv_lv_coloring(s3_uv_lv)
s4_color_x := f_src_uv_lv_coloring(s4_uv_lv)
s5_color_x := f_src_uv_lv_coloring(s5_uv_lv)
s6_color_x := f_src_uv_lv_coloring(s6_uv_lv)
s7_color_x := f_src_uv_lv_coloring(s7_uv_lv)
s8_color_x := f_src_uv_lv_coloring(s8_uv_lv)
p1_color_x := f_src_uv_lv_coloring(p1_uv_lv)
p2_color_x := f_src_uv_lv_coloring(p2_uv_lv)
p3_color_x := f_src_uv_lv_coloring(p3_uv_lv)
p4_color_x := f_src_uv_lv_coloring(p4_uv_lv)
🏁 Compositing the 12 exchange pairs
The volumes of 8 spot and 4 perpetual pairs are each converted into base-currency units, then merged into a single weighted volume. Ultravol shows the merged value; Ultravol Matrix shows the per-exchange values before merging, on the same color standard. The list stops at 12 because the volume figures of lower-ranked exchanges are often inflated, and would contaminate the result rather than improve it — the top 12 alone carry roughly 80% of real volume. This part is admittedly subjective; it was curated based on general exchange reputation in the market.
🏁 Unifying coin display units
Some coins — 1000PEPE, 1000SATS — are listed by different exchanges at 1000× or 10000× units (typically the case for extremely low-priced assets). Without reverting these to their original common unit, summing volumes across exchanges loses its meaning. There is no published reference for which exchange lists which coin at which multiple, so each case was verified one by one and built into an internal exception table, matched against the crypto name of the current chart. The symbol tickers used to call the 12 volumes are composed in two ways: (a) coins present in the low-volume table use the values defined there; (b) all other coins are composed per-symbol from 12 predefined symbol templates.
💊 This simple function extract crypto-name from any symbols with 1000x 1000000x
f_crypto_symbol_corekey(_tickerid, _basecurrency) =>
_tickerid_upper = str.upper(_tickerid)
_key = str.upper(_basecurrency)
if str.contains(_tickerid_upper, ":1000000BOB")
_key := '1000000BOB'
else
_prefix = str.match(_key, "^(?:1000000|10000|1000)")
_suffix = str.match(_key, "(?:1000000|10000|1000)$")
if _prefix != ''
_key := str.substring(_key, str.length(_prefix))
if _suffix != ''
_key := str.substring(_key, 0, str.length(_key) - str.length(_suffix))
_key
💊 This simple function extract the multiple number from symbol.
f_crypto_symbol_multiple(_fullname, _corekey) =>
_f = str.upper(_fullname)
_k = str.upper(_corekey)
_k_pos = (na(_k) or _k == '') ? na : str.pos(_f, _k)
_multiple = 1.0
if not na(_k_pos)
_colon_pos = str.pos(_f, ':')
_prefix_start = na(_colon_pos) ? 0 : _colon_pos + 1
_between = str.substring(_f, _prefix_start, _k_pos)
_after = str.substring(_f, _k_pos + str.length(_k))
_pre_num = str.match(_between, "^(?:1000000|10000|1000)$")
_suf_num = str.match(_after, "^(?:1000000|10000|1000)")
_raw = _pre_num != '' ? str.tonumber(_pre_num) : _suf_num != '' ? str.tonumber(_suf_num) : 1
_multiple := na(_raw) ? 1.0 : _raw
_multiple
💊 Coin name exceptions
The crypto names used by PulseWire's CRYPTO: and CRYPTOCAP: feeds quite often differ from the names exchanges actually use (this happens among smaller coins — SLC → SLCS, HYPE → HYPEH, and the like). Each time one was found, it was manually verified to be the same coin and added to an exception list. That exception table is pre-checked on the actual M.CAP and Avg. Price security calls.
This simple function maps standard exchange crypto names to PulseWire's native CRYPTO: , CRYPTOCAP: chart names.
f_crypto_cryptocap_tv_ticker(_uv_chart_crypto_tickerhead_str) =>
// CRYPTO: CRYPTOCAP:
//────────────────────────────────────────────---
// EXCHANGES => CRYPTOCAP // Cypto name
//────────────────────────────────────────────---
result_ticker = switch _uv_chart_crypto_tickerhead_str
'SLC' => 'SLCS' // Silencio
'BABY' => 'BABYL' // Babylon
'HYPER' => 'HYPERL' // Hyperlane
'HYPERL' => 'HYPERL' // 〃
'HYPE' => 'HYPEH' // Hyperliquid
'BOB' => 'BOBBUIL' // Build On Bitcoin
'BOBBOB' => 'BOBBUIL' // 〃
'TAG' => 'TAGG' // Tagger
'TAO' => 'TAOB' // TAO
'TOSHI' => 'TOSHI3' // Toshi
'NEIROCTO' => 'NEIROF' // First Neiro On Ethereum
'NEIRO' => 'NEIROF' // 〃
'NEX' => 'NEXUS5' // Nexus
'RATS' => 'RATS2' // Rats
'CHEEMS' => 'CHEEMSC' // Cheems
'SATS' => 'SATSO' // SATS (Ordinals)
'CAT' => 'CATSI' // Simon's Cat
'TRUMP' => 'TRUMPOF' // Trump official
'USDS' => 'USDS2' // USDS
'MOVE' => 'MOVEM' // Movement
'MOCA' => 'MOCAV' // Mocaverse
'ZORA' => 'ZORA2' // Zora
'BARD' => 'BARDL' // Lombard
'ATH' => 'ATHAE' // Aethir
'SONIC' => 'SONICSV' // Sonic SVM
'KNC' => 'KNC' // Kyber Network
'ZRO' => 'ZROL' // LayerZero
'AMP' => 'AMP2' // AMP
'CHIP' => 'CHIPUS' // USD.AI
'RAVE' => 'RAVED' // RaveDAO
'PROS' => 'PROSPH' // Pharos
=> _uv_chart_crypto_tickerhead_str
result_ticker
💊 G-Index px (Reference market price)
A mix of the current chart's price and the whole-market average price. It is a buffer that keeps the base line from being dragged around by a momentary price jump on a single exchange. G-Index Price operates only when the current chart uses USDT, USDC, or USD as its base unit. -> takes the avg. price provided by TV -> converts it to the current chart's unit by exchange rate.
//⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜
// G-Index PX
//
varip bool g_index_px_works = false
varip float g_index_px = na
var float chart_current_multiple = not uv_chart_symbol_crypto_basequotetickvol_flg ?
1.0 : f_crypto_symbol_multiple(uv_chart_tikerid_str, uv_chart_crypto_tickerhead_str)
var string chart_current_currency = syminfo.currency
float USD2USDT_avg_rate = request.security("CRYPTO:USDTUSD", timeframe.period, ta.sma(hlc3, 3))
float USD2USDC_avg_rate = request.security("CRYPTO:USDCUSD", timeframe.period, ta.sma(hlc3, 3))
bool USDT_is_DEPEG = math.abs(USD2USDT_avg_rate - 1.0) * 100 >= 0.1
bool USDC_is_DEPEG = math.abs(USD2USDC_avg_rate - 1.0) * 100 >= 0.2
var int chart_currency_convert_mode = switch chart_current_currency
'USD' => 1
'USDT' => 2
'USDC' => 3
=> 0
float g_avg_chart_ratio = switch chart_currency_convert_mode
1 => 1.0
2 => (1.0 / USD2USDT_avg_rate)
3 => (1.0 / USD2USDC_avg_rate)
0 => 0.0
var bool chart_currency_convert_no_need = (uv_chart_crypto_tickerhead_str == 'USDT')
or (uv_chart_crypto_tickerhead_str == 'USDC')
or (uv_chart_crypto_tickerhead_str == 'USDS')
or (uv_chart_crypto_tickerhead_str == 'PYUSD')
or (uv_chart_crypto_tickerhead_str == 'USDP')
var string g_index_px_crypto_ticker = 'CRYPTO:' + f_crypto_cryptocap_tv_ticker(uv_chart_crypto_tickerhead_str) + 'USD'
if chart_currency_convert_mode != 0
g_index_px := (request.security(g_index_px_crypto_ticker,timeframe.period, close * g_avg_chart_ratio,gaps=barmerge.gaps_on, ignore_invalid_symbol=true) * chart_current_multiple )
if not g_index_px_works and not na(g_index_px) and uv_volmode_ultravol_task_flg and not chart_currency_convert_no_need
g_index_px_works := true
if g_index_px_works and na(g_index_px) and na(g_index_px )
g_index_px_works := false
//G-Index - end
//⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜🟥⬜
🏁 Listing detection and exception reporting
An exchange that was absent early in the chart and began trading midway is automatically included in the calculation from that point on, and appears on the panel. The top-right panel shows the current bar's volume both as an absolute number (in base units) and as per-pair UV-scaled markings. When an exception occurs — some data not provided on a particular timeframe, for instance — you can hover over the panel to see exactly how the indicator is operating right now. Better to show what is happening than to behave strangely in silence.
🏁 You can check the uv engine (marking area like below) inside code.
// ⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜
// Ultravol Core Engine
// ⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜
Indicator
Indian Sectors HeatMapA real-time NSE sector dashboard built for intraday traders. Tracks 3 benchmark indices (Nifty 50, Bank Nifty, Midcap 100) and 13 sector indices in a single color-coded table.
Each row shows the last price, daily change%, and gap% (today's open vs yesterday's close) with a green/red gradient so you can instantly spot sector strength and weakness.
Sectors covered: Auto, Financial Services, FMCG, IT, Media, Metal, Pharma, PSU Bank, Realty, Energy, Commodities, Private Bank, Oil & Gas.
Fully customizable — Sort by highest/lowest change or alphabetically, reposition the table anywhere on the chart, and adjust colors to match your theme. Indicator
Regression Market Profile [BOSWaves]Regression Market Profile - Curve-Following Distribution Analysis with TPO Letters, Heatmap, and Profile Modes
Overview
Regression Market Profile is a regression-anchored market profile system that maps the distribution of price activity relative to a best-fit regression curve rather than within fixed horizontal price boundaries, where row assignment, POC identification, value area construction, and interior visualization are all derived from how far actual price deviated from the regression prediction on each bar rather than from absolute price levels.
Instead of constructing a profile against a static price range, this system fits either a linear or polynomial regression to recent price history and measures each bar's deviation from the fitted curve, distributing that activity into horizontal rows centered on the regression line. As the curve bends and trends through price space, the entire profile follows it, revealing where price consistently clustered above or below the regression prediction and identifying the deviation offset with the highest time-at-price concentration as a dynamic POC that moves with the trend rather than anchoring to a fixed session boundary.
This creates a market profile framework that adapts to the prevailing directional structure of price rather than imposing a fixed container. The interior visualization communicates distribution in three configurable modes: a heatmap that reveals how the distribution migrated across time columns, a profile extending from the right edge showing the cumulative distribution shape, and TPO letter boxes that follow the regression curve encoding chronological time progression through gradient coloring. Standard deviation bounds, value area boundaries, and a dual-line POC glow all follow the curve simultaneously, providing a complete structural reference system that moves with the trend rather than remaining static.
Price is therefore evaluated not for its absolute level but for its position relative to the regression expectation, with the profile revealing which deviation offsets attracted the most sustained activity throughout the regression window.
Conceptual Framework
Regression Market Profile is founded on the principle that meaningful participation clustering should be measured relative to the expected price path defined by recent price history rather than within arbitrary time or price containers that carry no relationship to the actual directional structure of the market.
Traditional market profile approaches anchor distributions to calendar sessions or fixed price ranges, producing profiles that reflect where price traded within a time box rather than where it clustered relative to its own trend. This framework replaces fixed-container profiling with regression-relative distribution measurement, where each bar's contribution to the profile is determined by how far actual price deviated from the best-fit curve rather than where it sat in absolute price space. The profile therefore reveals the structural tendencies of price relative to its own trend dynamics rather than its behavior within an externally imposed boundary.
Three core principles guide the design:
Profile distribution should be measured as deviation from a fitted regression curve rather than as absolute price position, ensuring the profile captures participation clustering relative to trend expectation rather than within arbitrary price boundaries.
The interior visualization mode should be configurable between temporal migration analysis, cumulative distribution shape, and chronological letter encoding, allowing the same structural data to be interpreted through different analytical lenses depending on the trader's workflow.
All structural reference elements including POC, value area, standard deviation bounds, and centerline should follow the regression curve continuously rather than anchoring to static horizontal levels, maintaining relevance to the current trend structure throughout the regression window.
This shifts market profile analysis from session-bounded horizontal distribution tracking into regression-relative participation mapping where the profile reveals structural clustering tendencies within the context of the prevailing trend curvature.
Theoretical Foundation
The indicator combines matrix-based polynomial and linear regression fitting to recent HL2 price data, rolling standard deviation for channel scaling and SD bound construction, deviation-based row assignment for distribution building, POC identification through maximum row count, value area expansion from POC outward, and three distinct interior visualization systems that present the same distribution data through different geometric representations following the regression curve.
The regression is computed using ordinary least squares matrix operations: the design matrix is constructed with powers of bar index up to the polynomial degree, transposed and multiplied to form the normal equations, inverted, and multiplied by the price vector to produce regression coefficients, which are then applied to generate the full prediction array. Standard deviation of the HL2 series over the regression window provides the channel scaling unit and drives the SD bound envelopes. Row assignment divides the channel height by the number of rows and places each bar's deviation from its predicted value into the corresponding row bin. POC and value area use the same maximum-count and outward-expansion logic as conventional market profile, applied to the curved row counts.
Four internal systems operate in tandem:
Regression Engine : Computes linear or polynomial best-fit predictions for all bars in the lookback window using matrix least squares, providing the curved baseline that all distribution measurements, row positioning, and visual elements follow.
Distribution Construction System : Measures each bar's deviation from its regression prediction, assigns it to a horizontal row within the standard deviation channel, accumulates row counts across the full window, and derives POC and value area from the resulting distribution.
Interior Visualization Engine : Renders the distribution data inside the channel in one of three modes: curved polygon cells per time column normalized independently for heatmap temporal migration display, curved profile bars extending from the right edge scaled to global row counts for distribution shape display, or TPO letter boxes positioned at the regression-relative row boundaries with gradient chronological coloring for time period encoding.
Structural Reference System : Draws the dual-line POC glow following the regression curve at the POC row offset, value area boundary polylines at the VA top and bottom offsets, standard deviation envelope polylines at one through three sigma above and below the curve, and a dashed centerline following the regression prediction directly.
This design ensures the distribution and all structural reference elements continuously adapt to the regression curve while the three interior modes provide complementary analytical perspectives on the same underlying participation data.
How It Works
Regression Market Profile evaluates price through a sequence of regression-aware distribution and visualization processes:
Regression Calculation : On the last bar, the design matrix is constructed from bar index values raised to polynomial powers up to the configured degree. Ordinary least squares solves for the coefficient vector and applies it to produce a prediction array covering all bars in the lookback window.
Channel Scaling : The standard deviation of HL2 over the regression window multiplied by the configured channel width defines the maximum deviation distance, establishing the vertical extent of the distribution channel centered on the regression curve.
Row Assignment and Count Accumulation : Each bar's actual HL2 is compared to its regression prediction and the deviation is assigned to a horizontal row bin derived from the channel height divided by the row count. Row counts accumulate across all bars in the window.
POC Identification : The row with the maximum accumulated count is identified as the Point of Control, representing the deviation offset from the regression curve where price spent the most time during the lookback window.
Value Area Construction : Starting from the POC row, adjacent rows are added in order of greater count until the cumulative total reaches the configured value area percentage of all bar counts, defining the high-activity zone around the POC.
Interior Rendering - Heatmap Mode : The lookback window is divided into time columns and each column builds its own per-row counts, normalized independently so each column's internal distribution is shown on its own scale. Curved polygon cells are rendered for each occupied cell with hot-cold gradient coloring by normalized density.
Interior Rendering - Profile Mode : Each row's global count is expressed as a fraction of the maximum row count and scaled to a configurable proportion of the total regression length. Curved polygon bars extend leftward from the right edge by the scaled bar length, forming a profile shape that follows the regression curve.
Interior Rendering - Letters Mode : Each bar is assigned a sequential alphabetical letter based on its time period index relative to the TPO timeframe. Letters are accumulated per row and rendered as individual boxes positioned at the regression-relative row boundaries, with gradient coloring that progresses from cold to hot as the letter index advances chronologically.
POC Polyline Rendering : A wide low-opacity glow polyline and a thinner full-opacity core polyline follow the regression curve at the POC deviation offset, providing a continuously curving reference for the maximum activity level throughout the window.
Value Area and SD Bound Rendering : Dotted polylines follow the regression curve at the value area high and low offsets and at one, two, and three standard deviation distances above and below the curve, with opacity increasing with distance from the curve.
Together, these elements form a continuously recomputed regression-relative distribution system where every visual element adapts to the current curve shape and all three interior modes present the same participation data from different analytical perspectives.
Interpretation
Regression Market Profile should be interpreted as a regression-relative structural distribution system where clustering above or below the fitted curve reveals directional bias tendencies and participation concentration within the prevailing trend:
Regression Centerline : The dashed curve following the best-fit prediction represents the trend's expected price path. Price consistently above it indicates sustained positive deviation bias; price consistently below indicates sustained negative deviation bias.
POC Line : The dual glow and core polyline following the curve at the maximum activity offset marks the deviation level where price spent the most time relative to the regression prediction, representing the most accepted deviation from expected trend behavior during the window.
Value Area Boundaries : Dotted polylines above and below the POC line mark the deviation range containing the configured percentage of total activity, identifying the zone of concentrated acceptance around the POC.
Standard Deviation Bounds : One, two, and three sigma dotted envelopes around the curve mark statistically extreme deviation distances, with progressively greater opacity indicating greater statistical rarity of price reaching those offsets.
Heatmap Mode : Each time column displays its own normalized distribution, with hot colors indicating the most active deviation level within that column and cold colors indicating less active levels. Reading across columns from left to right reveals how the distribution migrated as the window progressed.
Profile Mode : Curved bars extending from the right edge show the cumulative distribution shape across the full window, with longer bars indicating deviation levels with greater total activity and hot coloring marking the densest regions.
Letters Mode : Sequential alphabet letters fill the channel rows at their regression-relative positions, with gradient coloring from cold early-window letters to hot late-window letters encoding chronological time progression. Single-letter rows indicate price visited that deviation level in only one time period, functioning as regression-relative single prints.
POC Offset Interpretation : A POC positioned above the regression centerline indicates that price has consistently traded at a positive deviation from expectations, reflecting bullish structural bias within the window. A POC below the centerline indicates bearish structural bias.
POC offset direction, value area extent, distribution shape across modes, and SD bound interactions collectively provide more structural context than any element in isolation.
Signal Logic & Visual Cues
Regression Market Profile does not generate discrete buy or sell signals but provides continuous structural reference through distribution-derived levels:
POC Reaction : Price returning to the deviation level corresponding to the POC polyline encounters the most accepted level within the regression window, frequently acting as magnetic reference for reversion or continuation assessment.
Value Area Boundary Interaction : Price moving outside the value area boundaries enters statistically less accepted deviation territory, suggesting either trend extension beyond typical participation or the beginning of structural repositioning relative to the regression curve.
Standard deviation bound interactions provide additional reference for statistically extreme deviation events that historically attract mean reversion activity back toward the regression curve and POC.
Strategy Integration
Regression Market Profile fits within regression-informed structural analysis and distribution-based approaches:
POC Reversion Framing : Use the POC polyline as a dynamic reversion target when price has extended to the outer standard deviation bounds, with the curved POC providing a continuously updating level that reflects the trend's accepted center rather than a static price.
Value Area Acceptance Testing : Monitor whether price is trading within or outside the value area boundaries to assess whether current price activity represents accepted trend behavior or extended deviation warranting mean reversion consideration.
Heatmap Migration Analysis : Use temporal migration visible in heatmap mode to assess whether distribution is shifting toward positive or negative deviation over the course of the window, providing directional bias evidence from the distribution's evolution rather than from price alone.
Profile Shape Assessment : Use profile mode to assess distribution symmetry around the regression curve. A distribution skewed above the centerline suggests persistent positive bias; skew below suggests persistent negative bias. A symmetric bell shape suggests balanced acceptance around the regression expectation.
Single Print Monitoring in Letters Mode : Treat single-letter rows in letters mode as regression-relative thin participation levels that price is likely to revisit, analogous to single prints in conventional market profile.
Regression Mode Selection : Use Linear mode for markets trending in a consistent direction where a straight best-fit line accurately represents the price path. Use Polynomial mode for markets with visible curvature in their trend structure where the quadratic bend better fits the actual price trajectory.
Technical Implementation Details
Regression Engine : Matrix OLS computation using design matrix construction, normal equation formation, matrix inversion, and coefficient application for linear or polynomial curve fitting to HL2
Channel Construction : Rolling standard deviation-scaled channel with configurable width multiplier providing deviation row boundaries
Distribution System : Deviation-based row assignment with global count accumulation, POC maximum identification, and outward value area expansion
Heatmap Engine : Per-column count normalization with curved polygon cell rendering using hot-cold gradient by normalized density
Profile Engine : Global count-scaled curved bar polylines extending from the right edge by proportional bar length
Letters Engine : TPO timeframe-ratio letter assignment with per-row accumulation and gradient chronological box rendering at regression-relative boundaries
Structural System : Dual-line POC glow, dotted VA boundary polylines, three-sigma dotted SD envelopes, and dashed centerline all following the regression curve via chart.point arrays
Performance Profile : All rendering triggered only on the last bar with full object cleanup and rebuild on each update, polyline-based curved geometry for all structural elements
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Intraday regression profiling with shorter length and tighter channel for fast-adapting curve that captures intraday trend structure
15 - 60 min : Session-level distribution analysis with balanced length and moderate channel width for meaningful participation mapping across typical session trends
4H - Daily : Swing-level regression profiling with longer lookback and polynomial mode for curve-following distribution across multi-session directional structures
Suggested Baseline Configuration:
Length : 200
Mode : Polynomial
Channel Width (SD×) : 3.0
Inner Display : Letters
Rows : 12
TPO Timeframe : 30
Value Area % : 70
Show POC : Enabled
Show Value Area : Enabled
Show SD Bounds : Enabled
These suggested parameters should be used as a baseline; their effectiveness depends on the instrument's trend characteristics, volatility profile, and preferred distribution granularity, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Curve fits too loosely to recent price : Decrease Length to shorten the regression window, producing a curve that adapts more quickly to recent price structure. Switch to Polynomial mode if the trend has visible curvature that a linear fit cannot capture.
Curve too reactive to short-term price movement : Increase Length to smooth the regression across more history, producing a more stable curve that reflects longer-term directional structure and reduces sensitivity to recent fluctuations.
Channel too narrow or wide : Adjust Channel Width to scale the standard deviation multiplier, expanding the channel to capture more price activity within the distribution or contracting it to focus on the core deviation range.
Distribution too coarse or granular : Adjust Rows to increase or decrease the number of horizontal price bins, calibrating vertical resolution to the channel height and the instrument's typical deviation behavior within the regression window.
Heatmap columns too few or many : Adjust Heatmap Columns to control the time resolution of the migration display, with fewer columns showing broader temporal patterns and more columns revealing finer migration detail at the cost of visual density.
Profile bars too short or long : Adjust Profile Width to scale the maximum bar length as a fraction of the regression window, calibrating how far the longest bars extend from the right edge relative to the available chart space.
Too few or many letters per row : Adjust TPO Timeframe to change the time period each letter represents. Higher timeframes produce fewer, broader letters; lower timeframes produce more letters with finer time resolution.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Trending markets where the regression curve accurately represents the directional price path and the distribution reveals consistent deviation bias that reflects genuine structural tendencies
Instruments with smooth, curving price trends where polynomial mode produces a better-fitting curve than a straight line and the distribution around the curve is more meaningful than a session-anchored profile
Market profile-informed approaches that benefit from a continuously adapting POC and value area that follow the trend rather than anchoring to fixed session boundaries
Distribution analysis workflows where heatmap temporal migration or profile shape provides directional bias evidence from participation patterns rather than from price indicators alone
Reduced Effectiveness:
Choppy, directionless markets where the regression curve has no clear shape and the distribution is uniform across rows, reducing the interpretive value of POC location and value area extent
Markets with frequent sharp reversals where the regression window spans multiple opposing structural moves, producing a curve that represents none of them accurately and a distribution without meaningful clustering
Extremely short lookback windows where the matrix regression calculation is underdetermined or the distribution contains too few bars per row to produce statistically meaningful counts
Instruments with discontinuous price action including frequent gaps where the HL2 series used for regression produces curves that follow gap-distorted price paths rather than genuine trend structures
Integration Guidelines
Confluence : Combine with BOSWaves structural tools, momentum oscillators, or volume analysis to validate POC and value area interactions with broader analytical context before acting on regression-relative distribution levels
POC Offset Bias : Monitor the position of the POC relative to the centerline across successive sessions as a structural bias indicator. A POC consistently above the centerline across multiple regression windows suggests a persistent positive deviation tendency in the current trend phase.
Mode Selection by Objective : Use Letters mode for structural time-at-price analysis analogous to conventional market profile. Use Heatmap mode to assess how distribution shifted over the regression period. Use Profile mode to quickly assess distribution shape and skew relative to the centerline.
Regression Mode Discipline : Commit to a regression mode based on the instrument's observed trend curvature rather than switching between modes reactively. Polynomial mode adds a second degree of freedom that can overfit short-term noise if the lookback window is too short.
Window Length Stability : Maintain a consistent regression length when using the POC and value area as ongoing structural references. Changing the length significantly shifts the curve and redistributes the profile, making successive POC comparisons unreliable.
Disclaimer
Regression Market Profile is a professional-grade regression-relative distribution and market profile analysis tool. It uses ordinary least squares curve fitting with deviation-based participation mapping but does not predict future price movements. Results depend on market conditions, instrument trend characteristics, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates order flow context, structural analysis, and comprehensive risk management. Indicator
RSI Core Levels Heatmap [BigBeluga]🔵 OVERVIEW
The RSI Core Levels Heatmap turns the standard Relative Strength Index (RSI) indicator into powerful support and resistance lines drawn directly on your main price chart. Instead of forcing you to constantly look down at a separate oscillator window, this script automatically finds hidden momentum levels and projects them right where you trade, helping you spot key reversal floors and ceilings instantly.
🔵 FEATURES
The system uses a smart layout tracking engine to map momentum without cluttering your screen:
1 — Momentum-Mapped Support & Resistance Lines
Signal Line Crossover Alerts: The indicator tracks momentum changes using a smooth Signal Line Length . When the raw RSI line crosses above or below this signal line, it triggers a setup.
Smart Price Capture: The moment a crossover happens, the engine looks back at the last 10 candles. If it is a bullish bounce, it finds the low price; if it is a bearish drop, it grabs the high price.
Direct Chart Overlay: It takes those key prices and draws clean support or resistance lines right on your main chart with clear labels.
2 — No-Clutter Overlap Protection Logic
Collision Checker: To stop your chart from looking like a messy spiderweb, the indicator checks if a new line is being drawn too close to an old one.
Duplicate Blocking: If a new level lands directly on top of an existing active zone, the script blocks it automatically to keep your trading area perfectly clean.
// Strict Collision Box Overlap Detection Matrix
is_overlapping_existing_block(high_val, low_val) =>
overlap = false
if array.size(activeBlocks) > 0
for i = 0 to array.size(activeBlocks) - 1
BlockLevel item = array.get(activeBlocks, i)
if (high_val <= item.topPrice and high_val >= item.botPrice) or (low_val >= item.botPrice and low_val <= item.topPrice) or (high_val >= item.topPrice and low_val <= item.botPrice)
overlap := true
break
overlap
3 — Active Line Lifecycle & FIFO System
Automatic Extension: All active, unbroken support and resistance lines automatically stretch forward on every new candle so they stay fresh.
Broken Line Changes: When price actions breaks through a line, the script instantly changes its style to a thin, grey dashed line and stops tracking it. This shows you exactly where historical levels failed.
Levels Heat Color: Each support and resistance level color intense is based on the rsi value at the moment level was created.
FIFO (First-In, First-Out) Lag Protection: To keep your PulseWire running fast without any lag, you can set a Max Active Levels & Labels limit. When you reach this cap, the oldest lines drop off the chart first (First-In, First-Out) to make room for new ones.
// Object Array State Lifecycle Management Snippet
if array.size(activeBlocks) > 0
for i = array.size(activeBlocks) - 1 to 0
BlockLevel item = array.get(activeBlocks, i)
bool broken = item.isBull ? (close < item.botPrice) : (close > item.topPrice)
if broken
label.delete(item.lvlLabel)
line.set_style(item.lvlLine, line.style_dashed)
line.set_color(item.lvlLine, color.gray)
line.set_width(item.lvlLine, 1)
array.remove(activeBlocks, i)
else
line.set_x2(item.lvlLine, bar_index)
label.set_x(item.lvlLabel, bar_index)
4 — Gradient Heatmap Ribbon & Proximity Dashboard
Color-Changing Ribbon blocks: The bottom sub-pane features a smooth gradient ribbon that tracks market extremes. It lights up bright green during deep oversold conditions, bright red when overbought, and turns yellow during tight consolidations ( Show Midline Squeeze Zone ).
Distance Telemetry HUD Table: A clean on-screen table calculates exactly how close the current price is to your nearest active support or resistance level in points and exact percentages.
🔵 HOW TO USE
Using this simple multi-layer blueprint helps you manage setups step-by-step:
Trading Reversals and Bounces: Watch the chart when price falls down toward a green support line. If the Dashboard Table shows the distance getting very close to 0% and the bottom ribbon is flashing deep green (oversold), look for a long bounce trade off the level.
Managing Risk and Trailing Stops: If you enter long at a support line, use that level as your risk floor. If price flushes below it, the indicator will instantly turn the line grey and dashed, letting you know the setup is invalid and it is time to cut the trade.
Spotting Squeeze Breakouts: When the bottom ribbon stays yellow, it means the market is squeezing sideways. Watch your distance dashboard closely; when price breaks out of the squeeze and flies toward your outer lines, you can ride the explosive momentum expansion.
🔵 NOTES
Why this implementation is unique:
It saves screen space by turning abstract momentum data from an oscillator below into highly accurate, tradeable price targets up on your main chart.
The overlap blocker prevents multiple lines from bunching together, keeping your chart clean and easy to read.
The automated FIFO memory cleaning system makes sure the script stays fast and lightweight, no matter how many bars are loaded on your chart.
Indicator
Footprint Master Pane [ZynAlgo]Overview
ZynAlgo Footprint Master Pane is an order-flow and footprint-style volume analysis indicator designed to help traders study micro-liquidity behavior inside each candlestick.
The tool displays intrabar volume-side activity as a matrix-style Footprint Profile in a separate pane. Instead of only observing open, high, low, and close movement, traders can study where buying and selling pressure appears across different price levels inside recent candles.
This can help users evaluate:
Intrabar volume concentration
Buy-side and sell-side pressure
Delta behavior inside each candle
Point of Control placement
Liquidity concentration at candle highs and lows
Potential absorption or exhaustion behavior
Chart example:
How to Read the Footprint Matrix
Each data block on the chart is displayed in this format:
Bid | Ask
Price Level
The price level represented by that row of the footprint matrix.
Bid - Left Number
Represents sell-side volume activity classified by the script for that price level.
Ask - Right Number
Represents buy-side volume activity classified by the script for that price level.
Background Color - Heatmap
The higher the volume at a price level, the stronger the heatmap intensity.
Default color logic:
Cyan: buy-side activity is dominant at that price level.
Pink: sell-side activity is dominant at that price level.
Gray: low or inactive liquidity area.
Key Highlights
POC - Point of Control
The Point of Control is the price level with the highest total trading volume within the selected candlestick.
It is displayed as the gold zone and represents the main volume concentration area for that candle.
Footer Metrics
The bottom of each footprint column displays summary data for the candle.
Delta
Delta represents the net difference between buy-side and sell-side volume activity.
A positive delta indicates that buy-side pressure is dominant. A negative delta indicates that sell-side pressure is dominant.
Total Volume
Total volume represents the combined volume activity for the entire candlestick.
Configuration Settings
1. Order Flow Engine
Intrabar Timeframe
Defines the lower timeframe used by the tool to extract intrabar volume information.
Lower intrabar timeframes can provide more detailed footprint construction, while higher intrabar timeframes may produce a smoother and lighter display.
Stack Levels - Height
Controls how many price levels each candlestick is divided into.
Higher values:
Show more footprint detail
Create a finer price-level breakdown
May increase chart processing load
Lower values:
Create a simpler footprint view
Reduce visual density
May run more smoothly on slower charts
Auto Detect Asset - Smart Grid
When enabled, the system attempts to measure the current asset's volatility and calculate an appropriate grid size automatically.
This is useful when switching between markets such as gold, crypto, forex, indices, or stocks.
Manual Tick Size
When Auto Detect Asset is disabled, users can manually define the tick or grid size.
This can be useful when a symbol requires a custom footprint scale.
2. Pane Visuals
Recent Bars to Render
Controls how many recent candles are displayed in detailed footprint form.
Limiting the number of rendered candles can help keep the chart responsive on PulseWire.
Color Customization
Users can customize the colors for:
Buy-side activity
Sell-side activity
Point of Control zone
Heatmap display
This allows the footprint pane to match different chart themes and visual preferences.
Basic Analytical Applications
1. Absorption Observation
When price approaches a key support or resistance area, footprint data can help traders study whether one side of the market is being absorbed.
For example, if a bearish candle shows positive delta and large volume near the lower part of the candle, it may suggest that sell pressure is being absorbed by buy-side participation.
2. POC Migration
Point of Control migration can help traders evaluate where value is shifting across consecutive candles.
In an uptrend, POC zones that continue to migrate higher may suggest that market participation is accepting higher prices.
3. Liquidity at Highs and Lows
Traders can inspect volume activity near candle highs and lows to study exhaustion behavior.
For example, if price reaches a new high but the top levels show very low participation, that may indicate weaker continuation pressure.
How to Use
Add the indicator to the chart.
Choose an intrabar timeframe suitable for the chart timeframe and market.
Adjust stack levels to control footprint detail.
Use the heatmap to identify price levels with stronger participation.
Monitor the POC to study where volume concentration forms inside each candle.
Compare delta and total volume to evaluate buy-side or sell-side pressure.
Combine footprint observations with market structure, support and resistance, liquidity zones, and risk planning.
Best Use Cases
This indicator may be useful for:
Order-flow style analysis
Footprint chart reading
Intrabar volume analysis
Delta observation
Point of Control tracking
Absorption study
Exhaustion analysis
Liquidity-zone confirmation
Limitations
Footprint values depend on the intrabar data available from PulseWire for the selected symbol and timeframe.
The Bid and Ask display is based on the script's volume-side classification logic and should be interpreted as analytical volume-side data.
Lower intrabar timeframes may provide more detail but can increase processing load.
A footprint imbalance does not guarantee price continuation or reversal.
The indicator does not provide automatic trade entries, exits, or position management.
Past order-flow or footprint behavior does not guarantee future results.
Important Note
This indicator is an analysis tool only. It does not provide financial advice, investment advice, or guaranteed trading results. Users are responsible for their own trading decisions and risk management.
Indicator
Endogenous Macro Heatmap [invincible3] Endogenous Macro Heatmap
The Endogenous Macro Heatmap is a multi-factor macroeconomic dashboard designed to show the internal economic condition of a selected country in a compact table format directly on the chart.
Unlike cross-country or exogenous comparison models, this indicator focuses on domestic macro conditions : growth, production, demand, liquidity, rates, inflation, employment, fiscal position, debt pressure, and central bank balance sheet behavior.
The goal is to help traders, investors, and macro analysts quickly assess whether a country’s internal economic backdrop is improving, neutral, weakening, or entering a stress phase.
The indicator uses a heatmap structure so that changes in the macro environment can be understood visually. Stronger readings are shown through the positive color gradient, weaker readings through the negative color gradient, and balanced or transition zones through the neutral color.
What This Indicator Measures
The heatmap tracks a broad set of endogenous macro variables, including:
GDP year-over-year growth
Manufacturing production / manufacturing index
New orders or capacity utilization
Building permits, construction output, construction orders, or housing starts depending on the selected country
Retail sales year-over-year
Money supply
10-year government bond yield
Interest rate
Inflation year-over-year
Employment-related data
Debt-to-GDP
Government budget
Central bank balance sheet
Because macro data availability differs across countries, the script automatically substitutes certain fields where required. For example, some countries may use construction output, construction orders, housing starts, or capacity utilization depending on what is available in the PulseWire economic database.
Supported Countries
The dashboard currently supports:
United States
United Kingdom
Euro Area
Germany
France
Italy
Canada
Japan
China
Australia
South Korea
New Zealand
Each country uses its corresponding PulseWire economic code where available.
Composite Macro Score
The final Score column converts multiple macro readings into a single composite score from 0 to 100.
The score is grouped into four macro blocks:
1. Growth Block
Includes GDP, manufacturing, new orders, construction/building activity, retail sales, and employment.
This block has the largest weight because real economic momentum is the primary driver of macro regime strength.
2. Liquidity Block
Includes money supply and central bank balance sheet data.
This block helps identify whether domestic liquidity conditions are expanding or contracting.
3. Tightness Block
Includes 10-year yield and interest rate conditions.
This block helps measure whether financial conditions are becoming easier or tighter.
4. Stability Block
Includes inflation, debt/GDP, and government budget data.
This block helps detect macro pressure from inflation, fiscal stress, or excessive debt burden.
The composite score is weighted as follows:
Growth: 45%
Liquidity: 20%
Tightness: 20%
Stability: 15%
Score Interpretation
The score is displayed as a clean numeric value without extra symbols, making the table easier to read.
General interpretation:
70–100: Strong macro condition
55–69: Positive / improving condition
45–54: Neutral / transition condition
30–44: Weak condition
Below 30: Stress condition
The score should not be interpreted as a direct buy or sell signal. It is a macro regime filter designed to provide context.
Heatmap Color Logic
The table uses a simple and consistent three-color structure:
Positive color: stronger or favorable macro readings
Neutral color: balanced or mid-range readings
Negative color: weaker or unfavorable macro readings
The color system is intentionally matched with the Exogenous Heatmap style, allowing both dashboards to be used together with a consistent visual language.
Each macro field also includes an **Up Good** setting. This allows the user to define whether higher values are favorable or unfavorable for each metric.
For example:
Higher GDP growth is generally positive.
Higher manufacturing activity is generally positive.
Higher liquidity can be positive.
Higher inflation, debt, or rates may be interpreted differently depending on the user’s macro framework.
This flexibility allows the heatmap to be adapted for different economic regimes and analytical preferences.
Auto and Manual Scaling
The indicator includes an automatic macro gradient scale.
When auto scaling is enabled, the heatmap normalizes each metric based on the visible historical table range. This makes the table visually adaptive and easier to compare across different periods.
Manual scaling is also available for users who prefer fixed macro ranges.
This is useful when comparing the same country across different time periods or when the user wants a stable visual reference.
Timeframe and History Controls
Users can select the table period:
Yearly
Quarterly
Monthly
Weekly
Daily
The data can be fetched by:
A fixed number of periods
A selected start date
This gives flexibility for short-term macro monitoring as well as longer-term economic cycle analysis.
Table Customization
The dashboard includes several table display settings:
Show or hide table
Select table position
Select table size
Customize positive, neutral, and negative colors
The table automatically adapts to the chart background and foreground colors for better readability on both dark and light chart themes.
How to Use
This indicator is best used as a macro context tool.
A practical workflow:
1. Select the country you want to analyze.
2. Choose the table period, such as monthly or quarterly.
3. Review the color trend across the macro fields.
4. Watch whether growth, liquidity, tightness, and stability are improving or deteriorating together.
5. Use the composite score as a broad internal macro regime filter.
6. Combine the macro backdrop with price action, trend, liquidity, sector rotation, and risk management.
For example:
A rising score with improving growth and liquidity may support a risk-on environment.
A falling score with weakening growth and tightening conditions may warn of macro deterioration.
A neutral score may indicate a transition period where markets can become more sensitive to new economic data.
Suggested Use Cases
This heatmap can be useful for:
Macro regime analysis
Country-level economic monitoring
Risk-on / risk-off context
Equity index analysis
Bond market context
Currency market macro background
Sector rotation research
Long-term investment cycle analysis
Comparing domestic conditions with external macro pressure when used together with an exogenous heatmap
Important Notes
Economic data can be revised, delayed, or unavailable depending on the country and PulseWire’s data coverage.
Some fields may not exist for every country, so the script uses alternative fields where possible.
The heatmap is designed for macro analysis and educational research. It does not predict price direction by itself and should not be used as a standalone trading system.
Always combine macro signals with technical analysis, market structure, liquidity conditions, and proper risk management.
Disclaimer
This script is for educational and analytical purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any asset.
Markets are influenced by many factors beyond macroeconomic data, including positioning, liquidity, earnings, policy changes, geopolitical events, and sentiment. Use this tool as one layer of a broader decision-making process.
Indicator
Whale Absorption Profile [JOAT]WHALE ABSORPTION PROFILE
The flagship orderflow visual in the JOAT suite. A complete institutional-grade footprint dashboard — heatmap candle strips, horizontal volume profile, delta ladder, side histogram, POC/VAH/VAL lines, and whale / absorption / imbalance glyphs — all driven by the same underlying lower-timeframe-reconstructed intrabar data and rendered in a curated asthetics. Built to give you the entire auction picture in one indicator, on chart, without a dedicated orderflow platform.
Six visual layers, one engine
Every layer reads from the same intrabar data pipeline. The pipeline uses request.security_lower_tf at a configurable LTF (1m / 3m / 5m / 15m / 30m) to sample sub-bar prints, classifies each via the standard tick rule, then buckets the classified volume into a price-binned profile (configurable rows, default 50). Every layer below reads from those bins.
Heatmap candle strips — the body of each recent chart candle is overlaid with horizontal heat slices coloured along an absorption-intensity ramp (deep blue → indigo → violet → magenta → gold). At a glance you can see where, inside each bar, the auction happened.
Horizontal volume profile — a classic side profile of total volume per bin, rendered with split buy/sell colour so you can read which side dominated each price.
Delta ladder column — a vertical ladder of per-bin delta (buy − sell), positionable to any of nine corners on the chart. Drawn as a horizontal-going-left-to-right cell array so it never collides with the dashboard.
Side volume histogram — a compact buy/sell volume histogram aligned to the profile bins, for traders who want a second view of side-share that is not contaminated by total volume.
POC / VAH / VAL lines — the Point of Control, Value Area High, and Value Area Low computed from the profile and rendered as horizontal lines that extend right of the latest bar.
Whale / Absorption / Imbalance glyphs — three separate detection layers (described below) each render a distinct on-chart glyph at the bin where their condition fires.
A Lite Mode toggle disables the heaviest layers (heatmap strips + side histogram) for low-end machines or multi-indicator stacking.
Three orthogonal detection layers
Whale Print — a bin qualifies as a whale row when total bin volume is above a configurable percentile (default 95th of the bin distribution) and is above the whale-delta threshold (default 70%). Both gates: large and one-sided.
Absorption Zone — score = min(buy, sell) / (priceMovement + ε) . High when both sides traded heavily but price did not move — the classic limit-order-absorption signature. A bin qualifies when its absorption score exceeds the configurable percentile (default 90th).
Imbalance Spike — a bin qualifies when one side's volume is at least N× the other (default 3.0×). The standard footprint imbalance ratio.
These three are deliberately separate — a single price can be a whale row, an absorption zone, and an imbalance spike at once, in which case all three glyphs fire and you have a textbook stacked-signature read.
POC shift alert
The Point of Control's bar-to-bar bin-distance is tracked. When the POC jumps more than the configurable POC Shift: Bin Distance Trigger (default 2 bins) between consecutive bars, the POC Shift alert fires — the auction's value has rotated price levels, which is the most actionable single regime-change signal a profile produces.
Visual aesthetic
A locked institutional palette: cyan-teal bull (#5CF0D7), magenta bear (#FF4D75), and a signature absorption ramp — deep void → ultramarine → indigo → violet → magenta → gold — designed to read like a heat-mapped orderbook on a deep-space background (#02011A). The four multi-stop gradients drive heatmap, absorption, delta, and whale layers independently, so the chart never looks visually flat.
Dashboard
Monospaced table, positionable to any of nine corners, with row-fade gradient. Surfaces:
Current POC price + bin distance from previous POC.
VAH / VAL price levels.
Cumulative bar delta.
Whale print count, absorption zone count, imbalance spike count in the lookback.
Current row classifications for the active price (Whale / Absorption / Imbalance).
LTF in use and bin count.
Alerts
Four alert conditions, each independently controllable:
Whale Print
Absorption Zone
Imbalance Spike
POC Shift (bin distance > threshold)
How to read it
Three reads, in order of conviction:
Stacked detection at the same bin — when a bin fires Whale + Absorption + Imbalance simultaneously, the auction has experienced a complete event: large size, both sides traded heavily, and the side imbalance was extreme. These are the rarest and strongest reads the script produces.
POC Shift through a previous structural level — value migration. The auction's centre of gravity has just moved through your S/R; the rest of the session usually follows.
Heatmap candle strip + delta ladder agreement — when the heatmap concentration sits at the same price the delta ladder shows one-sided imbalance, the bar is institutionally meaningful regardless of the candle shape.
Suggested settings
Defaults (1m LTF, 50 bins, 40-bar lookback, 95th percentile gates) are tuned for 5m–15m on liquid futures and crypto. For 1m scalping, drop bins to 30 and lookback to 20 to keep the script responsive. For 1H+ HTF, raise lookback to 100 and bins to 60. Lite Mode is recommended when stacking with other heavy indicators.
Originality
The implementation — the unified intrabar pipeline that feeds six independent visual layers, the percentile-gated whale detector, the min(buy,sell) / priceMovement absorption score, the diagonal-imbalance row detector, the multi-stop absorption gradient (six-stop signature ramp), the configurable delta ladder with nine-corner positioning, the POC bin-distance shift detector, and the grade composite palette — is JOAT-original. No third-party code reused. The footprint vocabulary (POC, VAH/VAL, imbalance, absorption, whale) is public-domain auction-theory language; this implementation is purpose-built for Pine v6 with bar data only.
Limitations
Reconstructed intrabar data is an approximation — the tick rule is the accepted public-market inference but it is not a direct read of bid/ask. Sub-minute LTFs require a PulseWire Premium or Ultimate plan. The script renders many polylines, boxes, and labels — Pine's max_polylines_count / max_boxes_count / max_labels_count caps apply. Lite Mode exists specifically for low-spec / multi-indicator scenarios. POC, VAH, VAL, and detection layers are computed from confirmed intrabar data so they update on bar-by-bar close (non-repainting beyond the current developing bar).
—
-made with passion by jackofalltrades
Indicator
Leverage Pressure Map [BOSWaves]Leverage Pressure Map - Volume-Weighted Liquidation Level Projection with Thermal Heatmap Visualization
Overview
Leverage Pressure Map is a leveraged position liquidation estimation system that projects where open leveraged positions would be force-liquidated based on current price and volume activity, where heatmap intensity, level density, and distribution sidebar are driven by accumulated volume-weighted contract estimates at each price band rather than arbitrary fixed grid overlays or static percentage calculations.
Instead of displaying a generic liquidation grid at fixed intervals, the system builds its heatmap organically from price action, projecting liquidation zones from each bar's close in the direction that would liquidate the positions opened on that bar, weighting each level by the bar's volume and by the leverage multiple configured, and accumulating contract estimates over time to reveal where the greatest concentration of leveraged exposure has built up relative to current price.
This creates a continuously evolving pressure map where bands closest to price reflect the most recently opened leveraged positions, higher-leverage bands cluster tighter to price than lower-leverage equivalents, thermal coloring from the base color through yellow to white reveals the most dangerous liquidation clusters at a glance, and a sidebar distribution profile summarizes the full pressure landscape across the visible price range in a compact bar chart.
Price is therefore evaluated not just directionally but against a constantly updating picture of where forced selling and forced buying from leveraged liquidations is likely to cascade if price reaches those levels.
Conceptual Framework
Leverage Pressure Map is founded on the principle that leveraged market participation leaves a predictable spatial footprint in price space, and that estimating the distribution of that footprint from volume and price data provides actionable information about where cascading liquidation events are most likely to concentrate.
In leveraged markets, positions opened at any given price carry a liquidation distance determined by their leverage multiple. A 100x long position opened at the close of a bullish bar will liquidate approximately one percent below that close. A 10x position will liquidate approximately ten percent below. By projecting these distances from the close of each bar, weighting by volume as a proxy for participation size, and accumulating those estimates across all recent bars, the map builds a statistical picture of where the most leveraged exposure is concentrated without requiring access to exchange order book data.
Three core principles guide the design:
Liquidation levels should be projected from the close of each directional bar at the mathematically correct distance for each configured leverage multiple, weighted by volume to reflect the relative size of participation at each price point.
Thermal coloring should normalize all levels against the global maximum contract estimate, producing a relative intensity map that immediately identifies the highest-pressure clusters regardless of absolute contract values.
A sidebar distribution profile should aggregate the full heatmap into a compact price-by-pressure bar chart, providing a summary view of the total liquidation landscape without requiring the full heatmap to be analyzed row by row.
This shifts market analysis from directional price reading into leveraged exposure mapping where the spatial distribution of forced liquidation risk is continuously estimated and visualized alongside price action.
Theoretical Foundation
The indicator combines per-bar liquidation price calculation for configurable leverage multiples, volume-weighted contract accumulation at snapped price bands, global maximum normalization for thermal color mapping, sweep detection for removing levels that price has already passed through, and a sidebar bin aggregation system that compresses all active levels into a configurable number of price rows for distribution visualization.
Liquidation prices for long positions are calculated as close multiplied by one minus one divided by leverage, projecting below the close at a distance inversely proportional to the leverage multiple. Short liquidation prices are calculated as close multiplied by one plus one divided by leverage, projecting above the close. Each projected price is snapped to the nearest band boundary defined by the tick-scaled level height, ensuring levels accumulate at consistent grid positions rather than scattering across continuous price space. Leverage weights are assigned proportionally, with higher leverage multiples receiving greater weight reflecting their more aggressive risk profile.
Four internal systems operate in tandem:
Liquidation Projection Engine : On each bar with volume, calculates liquidation prices for all configured leverage multiples in both directions, snaps each price to the nearest level band, and either adds contract weight to an existing band or creates a new band at that position.
Sweep and Extension System : On each bar, extends all active level bands rightward to the current bar and removes any long liquidation bands that price has fallen through or short liquidation bands that price has risen through, keeping the heatmap current with price movement.
Thermal Color Engine : Normalizes each level's accumulated contracts against the global maximum and maps the result through a four-stage thermal gradient that progresses from a transparent base color at low concentration through the full base color to yellow and finally to near-white at peak concentration.
Sidebar Distribution System : On the last bar, aggregates all active long and short liquidation levels into configurable price bins spanning the recent high-low range extended to cover all active levels, draws proportional horizontal bars for each bin based on its relative contract sum, and plots a peak level line at the highest-concentration bin.
This design allows the heatmap to build organically from price action while the sidebar provides a continuous summary view of the full liquidation pressure distribution.
How It Works
Leverage Pressure Map evaluates price through a sequence of projection and accumulation processes:
Level Band Sizing : The minimum tick multiplied by the configured level scale produces the height of each liquidation band, controlling the granularity of the pressure grid relative to the instrument's tick size.
Leverage Table Construction : On the first bar, enabled leverage multiples are loaded into arrays with their corresponding weights calculated as the leverage value divided by 25, giving higher leverage multiples proportionally greater contract weight.
Long Liquidation Projection : On each bullish bar with volume, the liquidation price for each enabled leverage multiple is calculated as close multiplied by one minus one divided by leverage. Each price is snapped to its level band and the bar's volume multiplied by the leverage weight is added to the band's contract accumulation.
Short Liquidation Projection : On each bearish bar with volume, the liquidation price for each enabled leverage multiple is calculated as close multiplied by one plus one divided by leverage. Each price is snapped and weighted identically to the long projection process.
Band Deduplication : When projecting to a band that already exists in the active level array, contracts are added to the existing band rather than creating a duplicate, building cumulative pressure at each price level over time.
Sweep Removal : Long liquidation levels with their bottom boundary at or below the current bar's low are deleted and removed from the array. Short liquidation levels with their top boundary at or above the current bar's high are deleted, reflecting that those positions have already been liquidated.
Global Maximum Normalization : The maximum contract accumulation across all active long and short levels is calculated and used to normalize every level's contracts to a 0-1 range for thermal color assignment.
Thermal Color Assignment : Normalized values above 0.85 receive near-white coloring. Values between 0.65 and 0.85 gradient from yellow to white. Values between 0.35 and 0.65 gradient from the base color to yellow. Values below 0.35 graduate from a highly transparent base color to the full base color, producing a four-stage thermal effect that intensifies with concentration.
Sidebar Construction : On the last bar, the price range spanning the 200-bar high-low extended to cover all active level extremes is divided into the configured number of rows. Each active level's midpoint determines its bin assignment and its contracts are added to that bin's sum. Bins are drawn as horizontal bars proportional to their relative sum, colored by whether they sit below or above current price.
Peak Level Rendering : The sidebar bin with the maximum contract sum has a horizontal line drawn across the full visible range and a price label placed to the right, marking the single level of highest total liquidation pressure across all active levels.
Together, these elements form a continuously updating liquidation pressure landscape where the heatmap exposes per-level concentration and the sidebar summarizes the full distribution in a single compact view.
Interpretation
Leverage Pressure Map should be interpreted as a probabilistic liquidation pressure distribution tool rather than a precise order book representation:
Heatmap Bands (Long, Teal) : Horizontal bands below price representing estimated long position liquidation levels. These levels would trigger forced selling if price declines to them, potentially amplifying downside momentum.
Heatmap Bands (Short, Red) : Horizontal bands above price representing estimated short position liquidation levels. These levels would trigger forced buying if price rises to them, potentially amplifying upside momentum.
Thermal Intensity : Band color intensity reflects the relative concentration of estimated contracts at each level. Near-white bands represent the highest-pressure clusters. Yellow bands represent elevated but secondary concentrations. Dimmer base-colored bands represent lower-pressure background levels.
Band Density Near Price : Higher leverage multiples project their liquidation distances closer to price, producing denser band clustering near current price. Wider spacing further from price reflects the lower leverage multiples that require larger adverse moves to trigger liquidation.
Sidebar Distribution : The horizontal bar chart to the right of price summarizes total liquidation pressure at each price level across both long and short levels, providing an immediate overview of where the greatest cumulative exposure sits without analyzing individual heatmap bands.
Peak Level Line : The horizontal white line drawn across the chart at the sidebar's maximum-pressure bin marks the single most concentrated liquidation level across the entire active heatmap, representing the price at which the greatest estimated volume of leveraged positions would be forced to close.
Swept Levels : When price passes through a band, the band is removed from the display, reflecting that those positions have already been liquidated and no longer represent pending pressure.
Heatmap thermal intensity, peak level proximity to current price, and sidebar distribution shape collectively provide more information about leveraged market risk than any element in isolation.
Signal Logic & Visual Cues
Leverage Pressure Map does not generate discrete buy or sell signals. Instead it provides a continuous spatial representation of estimated liquidation pressure with two primary reference outputs:
Peak Level Line : The highest-concentration liquidation level across the full active heatmap, updated on every bar, marking where a price move is most likely to encounter cascading forced position closures.
Thermal Intensity Clusters : Near-white or yellow bands identify areas of elevated liquidation pressure that price is approaching, providing anticipatory context for potential momentum amplification or absorption events as price enters high-concentration zones.
The sidebar distribution provides a continuous summary reference for assessing whether liquidation pressure is concentrated near price or distributed across a wide range, informing both directional bias and risk management decisions.
Strategy Integration
Leverage Pressure Map fits within liquidity-aware and leveraged market structure approaches:
Liquidation Cascade Target Identification : Use high-intensity heatmap clusters as anticipatory targets for directional moves, particularly in leveraged crypto or futures markets where cascade events frequently drive price to liquidation cluster levels before reversing.
Peak Level Reference : Monitor the peak level line as a dynamic reference for the single highest-concentration liquidation zone. Directional moves approaching this level may accelerate as they trigger forced closures and then reverse sharply once the liquidation cascade exhausts.
Pressure Asymmetry Analysis : Compare the density and intensity of long liquidation bands below price against short liquidation bands above price using the sidebar distribution. Greater pressure on one side suggests a directional bias toward the path that would trigger the larger cascade.
Momentum Amplification Context : Use thermal cluster proximity as a context layer for evaluating whether a developing directional move is approaching a zone that would amplify momentum through forced closures or whether the path ahead is relatively clear of concentrated liquidation pressure.
Leverage Multiple Configuration : Configure leverage multiples to reflect the typical leverage profile of the target market. Crypto perpetual markets with common 100x and 50x usage benefit from the default configuration while futures markets with lower typical leverage may be better represented by adjusting multiples toward 20x, 10x, and 5x.
Multi-Timeframe Pressure Context : Apply the indicator on a higher timeframe to establish the broader liquidation pressure landscape while using a lower timeframe for entry timing, ensuring directional decisions are informed by the macro liquidation distribution rather than only the immediate price vicinity.
Technical Implementation Details
Projection Engine : Per-leverage close-derived liquidation price calculation with mintick-scaled band snapping and volume-weighted contract accumulation
Data Structure : Custom type array management for long and short level arrays with deduplication on existing band addresses
Sweep System : Per-bar directional price breach testing with immediate band deletion and array removal for swept levels
Thermal Color : Four-stage normalized gradient from transparent base through full base color to yellow to near-white
Sidebar : Last-bar price-range bin aggregation with proportional width bars and peak bin identification
Peak Level : Highest sidebar bin horizontal line with price label updated on every last bar render
Performance Profile : Configurable maximum level count per side with oldest level removal enforcing object count management
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Intraday liquidation pressure mapping for scalping in high-leverage crypto markets with responsive level accumulation and fine level scale for precise cluster identification
15 - 60 min : Session-level pressure distribution monitoring with balanced level count and moderate scale for intraday cascade target identification
4H - Daily : Swing-level liquidation landscape mapping with higher level scale for broader band visibility across larger price ranges
Suggested Baseline Configuration:
Max Levels Per Side : 100
Level Scale : 50
Leverage 1 : 100
Leverage 2 : 50
Leverage 3 : 25
Leverage 4 : 10
Show Distribution : Enabled
Show Peak Level : Enabled
Sidebar Width : 20
Sidebar Rows : 75
These suggested parameters should be used as a baseline; their effectiveness depends on the typical leverage profile of the target market, instrument tick size, and preferred heatmap granularity, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Bands too thin to see : Increase Level Scale to produce taller bands that are more visible at normal zoom levels, accepting reduced price resolution in exchange for improved visual clarity.
Bands too thick and overlapping : Decrease Level Scale toward 10 for finer band resolution, producing a more precise pressure grid at the cost of reduced visual prominence per band.
Too many levels cluttering the chart : Reduce Max Levels Per Side to limit the number of active bands per direction, with the oldest levels removed first as the cap is enforced.
Heatmap not reflecting market's leverage profile : Adjust the four leverage multiples to match the typical leverage tiers used by participants in the target market. Setting a leverage multiple to zero disables that tier entirely.
Sidebar too narrow to read : Increase Sidebar Width to extend the maximum bar length of the distribution profile, making the relative pressure differences between price levels more visually distinguishable.
Sidebar resolution too coarse : Increase Sidebar Rows for finer price-level resolution in the distribution profile, producing more granular pressure mapping across the visible range.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
High-leverage perpetual crypto markets where 25x to 100x positions are common and liquidation cascade events regularly drive price to cluster levels before reversing
Futures markets with identifiable leverage tier participation where volume-weighted projection produces meaningful pressure estimates relative to actual open interest distribution
Momentum trading approaches where liquidation cluster proximity provides anticipatory context for potential acceleration or reversal around high-pressure zones
Risk management frameworks that benefit from understanding where cascading forced closures are most likely to amplify directional moves beyond fundamental price drivers
Reduced Effectiveness:
Spot-only markets without leverage participation where liquidation mechanics are absent and the projection model loses its theoretical basis
Low-volume instruments where volume-weighted contract estimates become unreliable due to thin and erratic participation
Markets with very low typical leverage where default leverage multiples project liquidation distances beyond the normal trading range, producing bands that are rarely relevant to near-term price action
Instruments with extreme tick sizes relative to their price where mintick-scaled band heights produce either excessively coarse or excessively granular level grids that do not align with meaningful price structure
Integration Guidelines
Confluence : Combine with BOSWaves order flow tools, structural indicators, or momentum oscillators to validate whether price approaching a high-intensity liquidation cluster is doing so with the participation and conviction needed to trigger a cascade
Peak Level Respect : Monitor price behavior approaching the peak level line as the highest-probability cascade trigger zone. Price reaching this level may accelerate sharply through it as cascading liquidations fire, then reverse once the forced closure sequence exhausts.
Pressure Side Awareness : Assess whether greater pressure sits above or below current price using the sidebar. A heavier distribution of short liquidation pressure above price suggests upside moves may be self-amplifying, while heavier long liquidation pressure below suggests downside moves may cascade further than directional indicators alone would imply.
Level Sweep Interpretation : When price sweeps through a concentration of bands and they are removed, interpret the clearing as a liquidation event having occurred. The subsequent behavior of price after clearing a major cluster is often directionally informative about whether the move was primarily liquidation-driven or backed by genuine directional conviction.
Model Limitations : This indicator estimates liquidation pressure from volume and price data and does not access exchange-level open interest, funding rates, or actual leveraged position data. All readings represent probabilistic estimates rather than verified exposure measurements and should be treated as context rather than precise quantitative inputs.
Disclaimer
Leverage Pressure Map is a professional-grade liquidation pressure estimation and visualization tool. It uses volume-weighted leverage projection with thermal heatmap rendering but does not access real exchange open interest data or actual leveraged position information. All liquidation level estimates are approximations derived from OHLCV data and configured leverage multiples. Results depend on market leverage profile, instrument volume characteristics, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates order flow context, structural analysis, and comprehensive risk management. Indicator
Liquidity Heatmap MTF [JOAT]LIQUIDITY HEATMAP MTF
A weighted multi-timeframe liquidity-zone heatmap that aggregates pivot-based resting liquidity from up to four higher timeframes (1H / 4H / 1D / 1W by default), decays old pivots over a configurable half-life, and projects the resulting hot bins as a right-side colour strip plus optional horizontal lines that extend back across the chart so the key levels are visible on price. Adds an estimated liquidation-level layer on top — the price ranges where leveraged positions get unwound — and warns when price approaches one.
Why MTF aggregation matters
Single-timeframe liquidity maps miss the structural reality that institutional flow operates on multiple horizons simultaneously. A daily pivot high carries more resting liquidity than a 1H pivot high, but both contribute. Liquidity Heatmap MTF lets you turn on / off each of four timeframes (1H, 4H, 1D, 1W) independently and assign each a weight so the contribution to the heatmap is proportional to your conviction about how much that timeframe matters.
Defaults:
1H weight 1.0×
4H weight 1.5×
1D weight 2.5×
1W weight 4.0× (off by default; enable for macro reads)
Pivots are detected in each HTF context using configurable left/right lookbacks. Each pivot contributes intensity proportional to the volume traded on its bar (with optional log compression for instruments that have rare extreme prints).
Decay — half-life modelled
A pivot from 200 bars ago should not contribute equally to today's heatmap. The script applies an exponential decay:
intensity = volume × exp(−ln(2) × age / halfLife)
The Decay Half-Life input (default 180 bars) sets how quickly old pivots fade. After one half-life, an old pivot contributes half as much; after two, a quarter; and so on. This is the principled way to weight history — it never drops contributions discontinuously and it never lets ancient liquidity poison the current read.
Heatmap grid + hot-zone classification
The price range over the visible lookback (configurable, default 500 bars + 2% padding) is divided into N bins (default 60, capped at 200 by Pine's max_boxes_count). Each pivot's decayed intensity is accumulated into the bin closest to its level. Bins are then normalised against the hottest bin and any bin above the Hot Zone Threshold (default 70% of max) is tagged HOT.
The heatmap is rendered as a vertical strip on the right of the chart (configurable width and gap from latest bar) with bins coloured along a deep-ocean blue gradient — cold bins are near-invisible (transparency floor), hot bins are vivid cyan.
Hot-zone projection across chart (JOAT enhancement)
This is the headline visual: the top hot bins are projected back across the chart as horizontal lines (configurable count, default 5) with price labels, extending back a configurable number of bars (default 120). So you do not just see the heatmap as a right-side strip — you see the key levels on the chart at the price levels they actually occupy. Toggleable.
Estimated liquidation levels (the second layer)
On top of the liquidity heatmap, an optional liquidation layer estimates where leveraged positions get stopped out. Each significant HTF pivot extreme gets a projected liquidation level at:
liq_level = pivot ± (ATR × liqPad)
Configurable liqPad (default 0.5 ATR). Configurable caps on liquidation lines above (default 4) and below (default 4) the current price. Lines extend right by a configurable bar count. When price comes within liqAtrMult × ATR of a liquidation line, the !LIQ alert fires and the line is rendered in the accent colour (the only off-family colour in the palette — bright orange).
The liquidation logic is intentionally conservative — pivots provide the structural anchor; the ATR pad is the only configurable variable; lines are capped to avoid clutter.
Dashboard
Monospaced table positionable to any of nine corners. Surfaces:
Active timeframes and their weights.
Total pivots tracked.
Hottest bin price and intensity %.
Hot-zone count.
Liquidation lines above / below current price counts.
Distance (in ATR units) to nearest liquidation line.
Last hot-zone activation with bar-age.
Visual system
Heat strip (toggleable width / gap / transparency).
HOT tags on hottest bins (toggleable).
Optional strip border.
Horizontal hot-zone lines extending back across the chart (toggleable, capped, configurable length).
Liquidation level lines above and below (toggleable, capped).
LIQ labels (toggleable).
A locked Deep Ocean palette (bathypelagic blue gradient on near-black, with the bright orange #FF6B00 reserved exclusively for liquidation warnings) gives the chart a distinct institutional liquidity-map identity.
Alerts
Three alert conditions, each independently controllable, each cooldown-gated:
Hot Zone Activated — fires when a new bin crosses the hot threshold.
Approaching Liq Level — fires when price comes within liqAtrMult × ATR of a liquidation line.
New HTF Pivot Added — fires when a new HTF pivot is detected and added to the cache.
A configurable cooldown (default 8 bars) prevents back-to-back alert spam.
How to read it
Three reads, in order of conviction:
Approaching Liq Level alert — the most actionable single signal. Price is within striking distance of estimated leveraged-position stop-out levels. Liquidations tend to be self-fulfilling on the way in (cascade through stops) and exhaustive at the extreme (no more sellers / buyers left after the cascade).
Multi-timeframe hot zone — when a hot bin is contributed to by more than one HTF, it is by definition more significant. The hot line projections show you which levels are MTF-confluent.
New HTF Pivot in 1D or 1W context — these are the slowest-moving structural events. A new daily or weekly pivot reshapes the heatmap meaningfully.
Suggested settings
Defaults (1H/4H/1D enabled, weights 1.0/1.5/2.5, decay half-life 180, hot threshold 70%) are tuned for intraday-to-swing trading on liquid futures, FX, and crypto. For pure scalping, disable 1D / 1W and raise 1H weight. For pure macro, enable 1W and raise its weight; reduce 1H to 0.5×. The liqPad default 0.5× ATR is conservative — raise to 1.0× for more cautious liquidation projections.
Originality
The implementation — the MTF pivot aggregation pipeline with per-TF weights, the exponential half-life decay model, the bin-grid heatmap with hot-zone threshold, the cross-chart hot-line projection layer, the ATR-based liquidation level estimator with above/below caps, the cooldown-gated multi-alert engine, and the deep-ocean palette with the orange liquidation accent — is JOAT-original. No third-party code reused. The "liquidity map" concept comes from professional desks; the implementation here is purpose-built for Pine v6 with bar data only.
Limitations
Estimated liquidation levels are an inference from pivots and ATR — Pine cannot read actual leverage data or aggregated futures funding/open-interest. The lines mark where stop clusters are statistically likely to sit, not where they actually do. Pine's max_boxes_count caps the grid at 200 bins; the script clamps to 200 max even though the input allows higher requests. MTF pivots use request.security in non-lookahead mode, so they are non-repainting once confirmed at their HTF.
—
-made with passion by jackofalltrades
Indicator
Volumetric Regression Heatmap [LuxAlgo]The Volumetric Regression Heatmap indicator is a sophisticated market analysis tool that combines dynamic linear regression with volume profile density to visualize fair value and liquidity zones. By projecting volume-weighted heatmaps within a trend-following channel, it allows traders to identify where the bulk of trading activity has occurred relative to the current price trajectory.
🔶 USAGE
The indicator provides a multi-layered view of market structure. The central heatmap shows the "hottest" areas of volume concentration, acting as a magnet for price, while the outer bands represent statistical extremes.
🔹 Mean Reversion Signals
The script includes a built-in signal system designed for sideways or "flat" markets. When the indicator detects a "Contraction" state (determined by the ratio of channel height to standard deviation), it plots small circles at the +2/-2 standard deviation levels.
Green Circles: Potential long opportunities when price crosses below the lower signal band during a flat market.
Red Circles: Potential short opportunities when price crosses above the upper signal band during a flat market.
🔹 Future Projections & Profile
The heatmap extends beyond the current bar, providing a "Future Projection" zone. This allows traders to anticipate where support and resistance levels will be in the coming sessions. To the right of the projection, a Bookmap-style volume profile histogram displays the total volume distribution, helping to identify high-volume nodes (HVN) and low-volume nodes (LVN) at a glance.
🔶 DETAILS
🔹 Dynamic Auto-Adjusting Period
Unlike standard regression channels that use a fixed lookback, this tool features an adaptive engine. It calculates the ratio between short-term and long-term volatility (ATR).
In high-volatility environments, the channel period shrinks to become more reactive.
In low-volatility or ranging environments, the period expands to capture a broader structural view.
🔹 Volumetric Delta Histograms
The script calculates the approximate buying and selling volume for every candle within the lookback period. This data is visualized as histograms extending from the outer bands:
Top Band (Green): Displays buying pressure delta.
Bottom Band (Red): Displays selling pressure delta.
This allows traders to see not just where price is, but the intensity of the volume driving it toward the channel extremes.
🔶 SETTINGS
🔹 Core Settings
Source: The price source used for the regression calculation.
Base Period: The anchor length for the regression fit.
Dynamic Auto-Adjusting Period: Enables/disables the volatility-based adaptive lookback.
🔹 Heatmap Settings
Grid Rows Each Side: Determines the vertical resolution of the heatmap bands.
Gradient Smoothing: Applies a smoothing algorithm to the volume distribution for a cleaner visual gradient.
Colors 1-5: Customizable colors ranging from low-volume areas to high-volume "hot" zones.
🔹 Mean Reversion Signals
Signal Band (SD Multiplier): The standard deviation level required to trigger a signal.
Flat Slope Threshold: Controls how "flat" the channel must be to allow signals to appear, preventing counter-trend signals in strong trending markets.
🔹 Delta Histograms
Histogram Height Scale: Adjusts the vertical magnitude of the delta bars.
Histogram Bar Width: Sets the thickness of the individual delta lines.
🔹 Style & Options
Future Projection Length: How many bars to project the heatmap into the future.
Show Volume Profile Histogram: Toggles the right-sided volume distribution boxes.
🔹 Dashboard
Dashboard: Toggles the on-screen analytics panel.
Position/Size: Adjusts the location and scale of the dashboard UI.
Indicator
Exogenous Heatmap [invincible3]Exogenous Heatmap
The Exogenous Heatmap is a multi-country macro and market-performance dashboard designed to help traders and investors monitor external economic forces that may influence currencies, equities, commodities, and broader risk sentiment.
Instead of focusing only on price action from the current chart, this indicator visualizes key exogenous variables across major economies in a clean historical heatmap format. Users can compare countries by interest rates, GDP growth, balance of trade, foreign exchange reserves, and major stock index performance.
The indicator supports two calculation modes:
1. Raw Value
Displays the actual macroeconomic value or stock index performance for each country.
2. Differential vs Base
Compares each country against a selected base country. This is useful for identifying relative macro strength or weakness. For example, if the base country is set to the USA, the indicator shows how Australia, Japan, the UK, Europe, China, and other countries compare against the United States.
The heatmap includes the following datasets:
Interest Rates and Differentials
Displays policy interest rates or interest-rate differentials between countries. This is especially useful for forex analysis because higher relative interest rates can influence capital flows and currency strength.
GDP and Differentials
Displays GDP year-over-year growth or GDP growth differentials. This helps identify which economies are expanding faster or slower relative to the selected base country.
Balance of Trade and Differentials
Displays trade balance data. A stronger trade surplus may indicate external demand strength, while a deficit may reflect import pressure or weaker export competitiveness.
Reserves and Differentials
Displays foreign exchange reserve levels. This can help assess external liquidity strength and a country’s ability to manage currency or balance-of-payment stress.
Stock Index Performance and Differentials
Displays the performance of major stock indexes from leading economies. This adds a global risk-on/risk-off component to the indicator. Strong equity index performance may reflect improving investor sentiment, while weak performance may signal risk aversion.
The default stock index symbols include:
Australia: ASX 200
Canada: TSX Composite
China: Shanghai Composite
Europe: Euro Stoxx 50
Japan: Nikkei 225
New Zealand: NZX 50
Switzerland: SMI
United Kingdom: FTSE 100
United States: S&P 500
Users can manually change these symbols from the settings panel if they prefer alternative benchmarks.
Example 1: Interest Rate Differential
Suppose the selected dataset is Interest Rates and Differentials and the base country is set to USA .
If:
USA interest rate = 5.50%
Japan interest rate = 0.50%
Then Japan’s differential versus the USA is:
0.50% - 5.50% = -5.00 pp
This means Japan’s policy rate is 5.00 percentage points lower than the USA. In the heatmap, this would appear as a negative differential and would be colored toward the negative side of the gradient.
Example 2: Stock Index Performance Differential
Suppose the selected dataset is Stock Index Performance and Differentials and the timeframe is set to Monthly .
If:
USA S&P 500 monthly return = +4.20%
Japan Nikkei 225 monthly return = +2.10%
Then Japan’s stock index performance differential versus the USA is:
2.10% - 4.20% = -2.10 pp
This means Japan’s equity market underperformed the USA by 2.10 percentage points during that monthly period.
Example 3: Raw Stock Index Performance
If the calculation mode is set to Raw Value , the indicator displays each country’s own index return for the selected period.
For example:
USA: +4.20%
Japan: +2.10%
UK: -1.30%
Europe: +0.80%
This allows users to quickly identify which regions are leading or lagging in global equity performance.
Color Interpretation
Positive values are shown using the positive color gradient.
Negative values are shown using the negative color gradient.
Neutral or near-zero values are shown near the neutral color.
The indicator includes both automatic and manual color scaling. Auto Scale adjusts the heatmap based on the strongest visible value, while Manual Scale lets the user set a fixed range for more consistent comparisons.
How Traders Can Use It
Forex traders can use interest-rate and GDP differentials to evaluate relative currency strength.
Macro traders can use trade balance and reserve data to identify external economic pressure or resilience.
Equity and index traders can use global stock index performance to track international risk sentiment.
Commodity traders can use the dashboard as a macro backdrop because global growth, rates, and risk appetite often influence commodity demand and capital flows.
Important Notes
For percentage-based datasets such as interest rates, GDP growth, and stock index returns, differential values are displayed in percentage points, abbreviated as “pp.”
For balance of trade and reserves, raw values may often be more meaningful than differentials because countries may report values in different scales or currencies.
This indicator is designed as a macro and risk-sentiment visualization tool. It should be used together with technical analysis, fundamental analysis, and proper risk management.
Indicator
Supertrend Parameter Sensitivity 3D [LuxAlgo]The Supertrend Parameter Sensitivity 3D indicator is a powerful optimization tool that executes 100 simultaneous Supertrend backtests bar-by-bar to visualize how different ATR Lengths and Multipliers impact performance across various metrics.
By projecting this data onto a 3D surface and a heatmap dashboard, it allows traders to identify "stable" parameter zones and avoid over-optimized "peaks" that may lead to curve-fitting.
🔶 USAGE
This tool is designed to help traders find the most robust settings for the Supertrend indicator on any given timeframe or asset. Instead of manually guessing settings, users can see a holistic view of the parameter space.
🔹 3D Surface Projection
The 3D surface is rendered directly on the chart, where the X-axis represents the Multiplier, the Y-axis represents the ATR Length, and the Z-axis (height) represents the chosen performance metric.
Gold Highlight: Marks the absolute "Best" parameter combination based on the selected metric.
Blue Highlight: Marks the "Stable Area," which is the region where the average performance of a 3x3 parameter window is highest. This helps identify settings that remain profitable even if market conditions shift slightly.
🔹 Optimization Dashboard
The dashboard provides a detailed heatmap of the 100 tested combinations.
Value Distribution: An ASCII histogram at the top shows the distribution of all results, helping you understand if the "best" setting is an outlier or part of a consistent trend.
Heatmap Matrix: Displays the exact values for every combination. Hovering over any cell in the table reveals a tooltip with specific data, including the total number of trades for that combination.
Color Scaling: The colors are normalized relatively. Green represents the best results in the current set, while red represents the worst, allowing for clear visual distinction even if all results are negative or positive.
🔶 DETAILS
🔹 Bar-by-Bar Evaluation
The script manages 100 independent Supertrend states simultaneously. On every bar, it calculates the ATR and trailing stop levels for every combination in the sensitivity matrix. It simulates "Always-in-Market" trades (flipping long/short on direction changes) to track performance data without needing a separate strategy execution.
🔹 Optimization Metrics
Users can choose from 9 different metrics to optimize the 3D surface and Dashboard:
Win Rate: Percentage of trades that resulted in a profit.
Net Profit: Total gross profit minus total gross loss.
Profit Factor: Ratio of gross profit to gross loss.
Total Trades: The raw volume of signals generated.
Average Trade: The mean percentage return per trade.
Reward/Risk Ratio: The average win divided by the average loss.
Gross Profit: Total sum of all winning trades.
Total Wins: The absolute count of profitable trades.
Win/Loss Ratio: The count of wins divided by the count of losses.
🔶 SETTINGS
🔹 Main Indicator
ATR Length: The length used for the primary Supertrend line plotted on the chart.
Multiplier: The multiplier used for the primary Supertrend line plotted on the chart.
🔹 Sensitivity Ranges
Length Start: The starting ATR length for the 10x10 matrix.
Length Step: The increment added to the length for each subsequent row.
Multiplier Start: The starting Multiplier for the 10x10 matrix.
Multiplier Step: The increment added to the multiplier for each subsequent column.
🔹 Optimization
Metric: Selects the performance data used to determine the Z-height of the surface and the colors of the heatmap.
🔹 3D Surface Style
High/Low/Wire/Stable Colors: Customize the visual appearance of the 3D projection.
X/Y/Z Spacing & Scale: Adjusts the physical dimensions and height of the 3D surface on the chart.
🔹 Dashboard
Enable Dashboard: Toggles the visibility of the heatmap table.
Position/Size: Controls where the dashboard appears and how large it is on the screen.
Indicator
Indicator
Sessions Flow [Cartel Console] Sessions Flow
# Overview
Sessions Flow is a session-based market activity visualization tool designed to provide a detailed view of how trading volume is distributed throughout the major global forex and index trading sessions.
Rather than displaying volume as a single aggregated value, the indicator breaks each session into multiple price levels and visualizes where trading activity was concentrated during that session. This allows traders to study session structure, identify high-participation and low-participation areas, and compare how different sessions interact with price.
The indicator automatically tracks and analyzes the four major trading sessions:
• Sydney Session
• Tokyo Session
• London Session
• New York Session
Each session is processed independently and displayed directly on the chart using volume distribution heatmaps, volume profiles, Point of Control calculations, and Value Area measurements.
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# Core Features
## Session Detection
The indicator automatically identifies the start and end of each selected trading session and creates a dedicated session structure on the chart.
Users can enable or disable individual sessions and customize session times according to their preferences.
Supported sessions include:
• Sydney
• Tokyo
• London
• New York
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### Session Heatmap
Each session contains a heatmap that displays the relative distribution of trading activity throughout the session range.
The heatmap highlights:
• Areas with greater participation
• Areas with moderate participation
• Areas with lower participation
This provides a quick visual overview of where the market spent the most and least volume during a session.
Heatmap density and transparency settings can be fully customized.
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### Session Volume Profile
For every session, the indicator constructs a volume profile based on price distribution inside the session range.
The profile is displayed as a side histogram showing how activity was distributed vertically across different price levels.
This can help traders observe:
• High-volume areas
• Low-volume areas
• Session acceptance regions
• Session rejection regions
The profile width and display settings are adjustable.
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## Point of Control (POC)
The Point of Control represents the price level that accumulated the highest amount of volume during a session.
The indicator automatically calculates and plots the POC for each completed session.
POC levels often serve as useful reference points when reviewing historical session activity and market structure.
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### Value Area Analysis
The indicator calculates a configurable Value Area based on the percentage of session volume selected by the user.
Displayed levels include:
• Value Area High (VAH)
• Value Area Low (VAL)
These levels help visualize the region where the majority of session activity occurred.
The default setting uses a 70% Value Area, but users may customize this value.
---
### Historical Session Management
To maintain chart performance, the indicator includes controls for:
• Maximum detailed sessions displayed
• Historical session lookback period
• Simplified rendering of older sessions
Recent sessions can retain full heatmap and profile information while older sessions transition into lightweight background structures.
This allows extensive historical analysis without excessive chart clutter.
---
### Active Session Dashboard
A built-in dashboard displays the currently active trading sessions in real time.
The dashboard provides:
• Active session names
• Live session status indicators
This makes it easy to determine which global markets are currently open without leaving the chart.
---
## Customization Options
The indicator includes a wide range of configurable settings:
### Session Settings
• Individual session visibility
• Custom session times
### Heatmap Settings
• Heatmap resolution
• Number of price bins
• Density visualization controls
### Volume Profile Settings
• Histogram width
• Detailed session limits
### Value Area Settings
• Value Area percentage
• VA visibility controls
### Styling Settings
• Session colors
• Border transparency
• Historical session appearance
• Dashboard position
---
## Intended Usage
Sessions Flow is designed for traders who want to study how market activity develops during different trading sessions.
It can be used for:
• Session analysis
• Market structure observation
• Historical session review
• Volume distribution study
• Contextual chart analysis
The indicator focuses on visualization and analysis rather than signal generation.
---
## Disclaimer
This indicator is intended for educational and analytical purposes only. It does not provide financial advice, trading recommendations, or guaranteed outcomes. Trading involves risk, and users should perform their own analysis before making trading decisions.
Indicator
Markov Forecaster PRO🟦 Markov Forecaster PRO is a regime-classification and probability-forecasting engine built on a discrete-time Markov chain over three states — Bull, Bear, Sideways. Every bar is labelled from its rolling N-bar log return; the labels feed a 3×3 transition matrix that is power-iterated for the stationary distribution and exponentiated for forward-probability cones (P¹, P³, P⁵, P^horizon). Unlike the dozens of textbook Markov indicators on PulseWire, this one layers four original refinements on top of the standard chain construction — each addressing a well-known weakness of the memoryless Markov assumption.
The indicator integrates seven analytical layers — adaptive regime classification, semi-Markov duration tracking, sample-size disclosure, pending-regime early warning, forward-probability forecasting, look-ahead-free backtesting with fees and slippage, and multi-timeframe confluence — each rendered on a single overlay chart through a regime ribbon, three-layer neon glow signals, and four theme-aware dashboard panels.
Built with statistical honesty in mind. The backtest charges configurable commission and slippage on every entry and exit, the transition matrix flags rows with insufficient data, the duration-conditional probabilities are shown alongside the unconditional ones, and the documentation is explicit about what the model can and cannot predict.
🟦 HOW THE CORE ENGINE WORKS
**Regime Classification**
Each bar, the engine measures the rolling N-bar log return:
logRet = log(close / close )
The bar is labelled by comparing this return against the configured boundary:
- `logRet > +threshold` → BULL
- `logRet < −threshold` → BEAR
- otherwise → SIDEWAYS
The classification runs every bar with no look-ahead. The choice of threshold determines how reactive the regime label is, and this is where the first refinement enters.
**Adaptive Threshold (k · σ · √N)**
Traditional Markov regime indicators use a fixed percentage cut — e.g. "±5 % over 20 bars". This collapses on real markets: the same 5 % is trivial in a 2017 mania and never reached in 2023 chop. The fix is to scale the boundary with realised volatility:
threshold_adaptive = k × σ × √N
where σ is the per-bar log-return standard deviation over a configurable window (default 100 bars). Under a random walk, k = 1.0 cuts at the 16th / 84th percentiles; k = 2.0 at the 2.5th / 97.5th percentiles. The default k = 1.5 reproduces classic ±1.5-sigma thresholds.
Fixed-percentage mode is still available for users who want to lock the threshold deliberately.
**Regime Confidence**
Once classified, the move's strength is normalised relative to the active boundary:
confidence = |logRet| / threshold
| Confidence | Tier | Visual |
|---|---|---|
| < 1.0× | weak | ▱▱▱ |
| 1.0× – 2.0× | moderate | ▰▱▱ |
| 2.0× – 3.0× | strong | ▰▰▱ |
| ≥ 3.0× | stretched | ▰▰▰ |
The confidence value drives the ribbon transparency (in Adaptive Intensity mode), feeds the High Confidence alert (≥ 2.5× trigger), and is reported in the Status dashboard.
🟦 SEMI-MARKOV DURATION BUCKETS
**The Memoryless Problem**
A standard Markov chain says: "Given I'm in Bull, the probability of staying Bull tomorrow is X — regardless of whether Bull started yesterday or 200 bars ago." This is the memoryless property, and on real markets it's wrong. A 200-day-old Bull regime carries different mean-reversion risk than a 5-day-old one.
**The Refinement**
Markov Forecaster PRO additionally builds two CONDITIONAL transition matrices:
- `P_young` — transitions counted when the source regime's age was below its empirical average duration
- `P_mature` — transitions counted when the source regime's age was at or above the average
Both matrices are constructed in parallel with the main P, using the same per-bar bucketing logic and updated continuously. The self-transition probabilities for the current regime are then surfaced in the Status dashboard:
P young / mature 91% / 64%
The user reads this as: "When this regime was young (under its avg duration), it continued 91 % of the time. When mature, only 64 %." On a long-running regime this is the canonical signal that mean-reversion risk is rising — without the rest of the chain math being polluted.
A minimum of 10 samples per bucket is required before a value is shown; below that the cell reports "—" rather than display an unreliable probability.
🟦 FORWARD PROBABILITY CONE
**Matrix Exponentiation**
The 3×3 transition matrix P encodes one-bar-ahead probabilities. To project further out, the matrix is multiplied by itself:
P¹ = P — next bar
P³ = P × P × P — 3 bars out
P⁵ = P × P × P × P × P — 5 bars out
P^h = repeated h times — user-configured horizon
The Forecast Cone panel renders all four horizons for each of the three destination regimes, conditioned on the current regime. A trader reading the row "BULL" sees the probability the market will be in Bull at each horizon, given the current regime.
**Stationary Distribution**
Power-iterating the matrix to convergence yields the stationary distribution — the long-run probability of being in each regime, independent of starting state. With 50 iterations (default), any well-behaved 3×3 stochastic matrix is essentially converged.
stat + stat + stat = 1.0
This is rendered as the "long-run" row in the Forecast panel and the "Long-run share" cell in the Status panel.
**Honest Limitation**
The cone uses the UNCONDITIONAL matrix (averaged over all regime ages). For duration-conditional probabilities, the Status panel's P cell is the relevant readout. This split is explicit in both the cone footer label and the Forecast input tooltip.
🟦 SAMPLE-SIZE DISCLOSURE
A probability is only as reliable as the data behind it. Markov Forecaster PRO surfaces sample size in three places:
**Per-row sample count in the Transition Matrix**
A fifth column "n" in the matrix panel reports the number of transitions from each source regime. The cell is colored by reliability tier:
| Sample N | Tier | Color |
|---|---|---|
| ≥ 100 | high | foreground |
| 30 – 99 | moderate | dim |
| < 30 | low | divergent (warning) |
A row with fewer than 30 transitions is flagged because three-decimal probabilities derived from sparse data are noise, not signal.
**Total Sample N in the Status panel**
The Status dashboard's "Sample N" cell sums all transition counts and reports a global reliability tier:
| Total N | Tier |
|---|---|
| ≥ 200 | high (full color) |
| 50 – 199 | moderate (foreground) |
| < 50 | low (divergent warning) |
**Matrix footer**
The matrix panel's footer also shows the total N in compact notation (e.g. "N = 1.8k") for at-a-glance check.
The goal of this layer is honesty: a freshly-loaded chart with 30 bars of history should NOT display the same matrix as a 10-year chart, and the reliability tier makes the difference obvious without the user having to inspect counts manually.
🟦 PENDING-REGIME EARLY WARNING
**The Lookback Lag**
Because the regime is classified from log(close / close ), the official regime label inherently lags — by the time the threshold is crossed, the move is already N bars old. This is a structural feature of the model, not a bug, but it can be partially mitigated.
**Pending Logic**
Inside Sideways, when the log return reaches 70 % of either boundary, the dashboard fires an early-warning cue:
distance_fraction = max(|logRet| / threshold, ...)
isPending = (regime == SIDE) AND (distance_fraction ≥ 0.70)
The Status panel's "Pending" cell displays the direction the return is leaning toward and the current fraction:
⚠ ▲ BULL 87%
Color matches the leaning regime. The Pending Regime alert (default OFF, opt-in) fires on the first bar a pending state is entered.
This is not a regime change signal — it's a "watch this" cue, triggered roughly 30 % before the official threshold is crossed. Used alongside the official regime change, it gives the user advance notice without compromising the threshold's strictness.
🟦 LOOK-AHEAD-FREE BACKTEST
**The Look-Ahead Trap**
`regime` is derived from `log(close / close )`, which contains today's close. Allocating today's return to today's regime is look-ahead bias — the strategy would "know" today's regime before today's close, which is impossible in real-time trading. Most published Markov backtests have this bug.
**The Fix**
Markov Forecaster PRO allocates positions on the PRIOR bar's confirmed regime:
regForAlloc = regime // yesterday's confirmed regime
If yesterday's regime was Bull, we are long today. The strategy is realisable in real time because the previous bar's regime is known when the current bar opens.
This means the strategy is delayed by one bar relative to the regime label — and that's the correct, honest treatment. If a Bull→Bear flip happens on bar t, the strategy takes bar t's loss (still long from regime =Bull) and exits at bar t+1.
**Fees and Slippage**
Every Bull entry and exit pays the configured per-fill cost:
costFrac = feesPct/100 + slippageBps/10000
costPerFill = log(1 − costFrac) // negative log-space cost
The cumulative cost is debited from the Bull log-return total:
Bull gross = exp(bullLogR) − 1
Bull net = exp(bullLogR + bullCostLogR) − 1
A round-trip pays the fee + slippage twice. With defaults (0.10 % fee, 5 bps slippage), each round-trip costs roughly 0.30 % of equity in log space.
**Display**
The Backtest panel renders:
| Field | Value |
|---|---|
| Per-regime rows | GROSS cumulative log return (no fees) |
| Strategy row | NET cumulative (fees applied) vs Buy-and-Hold |
| Methodology footer | trade count · fee % · slippage bps |
The headline strategy result is the NET number — the realistic outcome a trader would have experienced. The gross numbers are kept for diagnostic comparison.
**What This Is Not**
This is a diagnostic backtest, not a tradable strategy. There is no position sizing, no risk management, no overnight financing, no shorting. It tells you whether "long when prior bar was Bull, flat otherwise" would have beaten buy-and-hold after fees — nothing more.
🟦 MULTI-TIMEFRAME CONFLUENCE
The same regime logic runs on a user-configured higher timeframe via `request.security` with `lookahead = barmerge.lookahead_off` and `gaps = barmerge.gaps_off` (anti-repaint mandatory). The result is reported in the Status dashboard's HTF block:
| State | Display | Color |
|---|---|---|
| HTF regime matches LTF regime | ✓ ALIGNED | bull |
| HTF regime differs from LTF | ⚠ DIVERGENT | bear |
| Insufficient HTF data | — | foreground |
Divergent regimes are common at trend turns — the LTF flips before the HTF catches up. Aligned regimes carry higher conviction. A separate alert ("MTF Confluence") fires on regime entries only when the HTF agrees.
Recommended pairings:
| Chart | HTF |
|---|---|
| 1H | D |
| 4H | W |
| D | W |
Use at least 3× your chart timeframe — anything closer and the two regimes track each other with no information gain.
🟦 VISUAL LAYER
**Regime Ribbon**
The chart background is tinted to the current regime color with three style options:
| Style | Behaviour |
|---|---|
| Subtle | Fixed 92 % transparency (price stays hero) |
| Bold | Fixed 75 % transparency (easy to scan from far) |
| Adaptive Intensity | Transparency scales with confidence (60 % – 95 %) |
In Adaptive Intensity mode, a strong directional move (confidence ≥ 3×) renders the ribbon at full intensity; a weak move stays faint. The ribbon doubles as a visual confidence meter.
**Three-Layer Neon Glow Signals**
On every confirmed regime change (after the Min Hold filter), the indicator drops a three-layer halo on the chart:
| Layer | Size | Transparency | Purpose |
|---|---|---|---|
| Outer | size.large | 80 % | Soft halo |
| Middle | size.normal | 50 % | Mid-glow |
| Core | size.small | 0 % | Bright center |
Bull markers (▲) render below the bar; Bear (▼) and Sideways (◆) render above. The Min Hold input (default 4 bars) requires a new regime to persist before its flip is drawn — kills label spam in choppy zones without affecting the underlying transition counts.
**Confidence Tags (optional)**
An off-by-default toggle adds the confidence multiplier to each signal arrow ("BULL 2.3×"), useful for screen captures and analysis.
🟦 DASHBOARDS
Four theme-aware panels, each independently togglable and positionable:
**Status Panel** (default: Bottom Left)
Compact live readout — current regime, age, confidence, pending direction, average duration, young/mature bucket, P young vs mature, expected remaining bars, long-run share, sample size, and HTF alignment. 16 rows base, 19 with HTF block enabled.
**Transition Matrix Panel** (default: Top Right)
3×3 next-bar P matrix with diagonal-highlighted self-transition cells. The fifth column reports per-row sample size with reliability tier coloring. Matrix footer shows total N.
**Forecast Cone Panel** (default: Middle Right)
Forward probability for each destination regime at horizons +1, +3, +5, and +configured. Steady-state row shows the long-run distribution. Current regime is reported at the bottom for context.
**Backtest Panel** (default: Bottom Right)
Per-regime gross cumulative return, average per-bar, and the bar count. Strategy row shows NET return vs buy-and-hold. Methodology footer lists trade count, fee, and slippage.
All four panels share the same theme palette and adapt to Dark / Light display mode. Text size is independently configurable (Tiny / Small / Normal / Large).
🟦 COLOR THEMES
Ten cohesive palettes tuned to the Apex design system, each defining three regime axes (Bull, Bear, Sideways):
| Theme | Character | Bull | Bear | Sideways |
|---|---|---|---|---|
| Prism | Classic | Forest green | Crimson | Slate grey |
| Focus | Default | Cyan steel | Deep orange | Cool blue-grey |
| Solar | Warm | Amber | Indigo red | Lavender grey |
| Frost | Cool | Sky blue | Soft lavender | Pale steel |
| Laser | Neon | Lime green | Hot crimson | Charcoal grey |
| Aurora | Bright | Gold | Scarlet | Warm beige |
| Plasma | Electric | Aqua | Magenta | Slate teal |
| Bloom | Soft | Mint | Hot pink | Blue-grey |
| Eclipse | Deep | Navy | Dark crimson | Steel grey |
| Carbon | Minimal | Near-white | Mid-grey | Dark grey |
One theme selection drives every visual component: ribbon, glow signals, all four dashboard headers, regime-colored cells, diagonal matrix highlights, and HTF alignment color.
**Dark / Light Display Mode**
Dashboard chrome (background, foreground, borders, section dividers) flips between dark-on-bright and bright-on-dark. The regime axis colors remain consistent across modes — only the panel chrome changes.
🟦 ALERT SYSTEM
Six alert conditions, each independently togglable:
| Alert | Condition |
|---|---|
| Bull Regime Entry | Regime flipped to BULL (after Min Hold confirmation) |
| Bear Regime Entry | Regime flipped to BEAR |
| Sideways Regime Entry | Regime flipped to SIDEWAYS (default OFF) |
| High Confidence | confidence ≥ 2.5× threshold, first bar of crossing |
| MTF Confluence | Regime change + HTF agrees |
| Pending Regime | Inside Sideways, log return ≥ 70 % of either boundary (default OFF) |
All alerts fire on confirmed bar close and use the standard `alertcondition` mechanism. The Min Hold filter applies to entry alerts — a new regime must persist Min Hold bars before its entry alert fires, matching the on-chart glow markers.
The Sideways and Pending alerts are default-off because they can fire more frequently than the other types — opt-in by design.
🟦 SETTINGS REFERENCE
**Theme**
- Theme — One of 10 Apex palettes. Default: Focus
- Display Mode — Dark / Light. Default: Dark
**Regime Logic**
- Threshold Mode — Adaptive (k·σ·√N) / Fixed (%). Default: Adaptive
- Lookback Window — Bars for the rolling log return. Default: 20
- Adaptive k — Sigma multiplier. Default: 1.5
- Fixed Bull Threshold — Used only in Fixed mode. Default: 5.0 %
- Fixed Bear Threshold — Used only in Fixed mode. Default: 5.0 %
- Volatility Window — Bars for the per-bar stdev. Default: 100
- Min Hold — Bars a new regime must persist for label drawing. Default: 4
**Forecast**
- Forecast Horizon — Bars projected by the right-most cone column. Default: 10
- Stationary Power — Power-iteration count. Default: 50
**Regime Ribbon**
- Show Regime Ribbon — Toggle. Default: ON
- Ribbon Style — Subtle / Bold / Adaptive Intensity. Default: Adaptive Intensity
**Signal Labels**
- Show Regime Change Signals — Toggle. Default: ON
- Glow Effect — Three-layer halo toggle. Default: ON
- Show Confidence on Signal — Adds multiplier tag (e.g. "BULL 2.3×"). Default: OFF
**Multi-Timeframe**
- Enable HTF Confluence — Toggle. Default: ON
- HTF Resolution — Higher timeframe. Default: D
**Backtest**
- Trading Fee (% per fill) — Per-side commission. Default: 0.10 %
- Slippage (bps per fill) — Per-side slippage in basis points. Default: 5
**Dashboards**
- Show Status / Matrix / Forecast / Backtest — Independent toggles. Default: all ON
- Dashboard Size — Tiny / Small / Normal / Large. Default: Small
**Panel Positions**
- Status Panel — 9-position grid. Default: Bottom Left
- Matrix Panel — Default: Top Right
- Forecast Panel — Default: Middle Right
- Backtest Panel — Default: Bottom Right
**Alerts**
- Bull / Bear / Sideways Regime Entry — Independent toggles
- High Confidence — Default: ON
- MTF Confluence — Default: ON
- Pending Regime — Default: OFF
🟦 COMPATIBILITY
Works on all asset classes and all timeframes in PulseWire Pine Script v6.
- Crypto: Spot, futures, perpetual contracts
- Forex: All pairs
- Equities: Stocks, ETFs, indices
- Commodities: Metals, energy, agriculture
- Timeframes: 1m through Monthly
The adaptive threshold normalises by per-bar realised volatility, making the regime classification volatility-agnostic across assets without manual recalibration. The same default settings work on BTCUSDT daily, SPY weekly, and EURUSD 4H — only the HTF resolution input should be adjusted to match the chart timeframe.
🟦 TECHNICAL NOTES
- Pine Script v6
- `max_labels_count = 500`, `max_lines_count = 100`, `max_bars_back = 5000`
- No repainting — all regime classifications are computed on confirmed bar close. The HTF request uses `lookahead = barmerge.lookahead_off` and `gaps = barmerge.gaps_off`
- Regime change debouncing uses `ta.barssince` to avoid runtime-indexed history reads (which can trip "cannot determine max_bars_back" in Pine v6)
- Heavy computation (matrix exponentiation, stationary distribution, dashboard rendering) is gated on `barstate.islast` to run once per chart render
- Transition counting uses `barstate.isconfirmed` to avoid double-counting the live bar
- Backtest accumulators charge fees at trade boundaries — entries and exits detected by `regForAlloc != regForAlloc `
- Duration buckets use the SOURCE regime's age at the time of transition for classification; the threshold is the empirical average duration of that regime, computed continuously
- Matrix multiplication is implemented as an unrolled 3×3 flat-array routine for portability and speed
- Empty-row fallback to uniform 1/3 in the transition matrix prevents NaN propagation when a regime has not appeared in visible history
🟦 LIMITATIONS — READ THIS
This indicator is statistically honest about what it can and cannot do. Three known limitations:
1. **The Markov assumption is partially violated.** Markets are not memoryless. The duration buckets (Section: Semi-Markov Duration Buckets) mitigate this but do not eliminate it.
2. **Forward probabilities are not predictions.** They are conditional probabilities under the chain assumption. A "Bull 58 % at +10 bars" reading does not mean "58 % chance the next 10 bars are bullish" — it means "given a long-run sample of similar starting states, 58 % were in Bull at +10 bars". Use the cone as ONE input alongside other analysis.
3. **The regime label lags by N bars.** This is structural — the rolling log return necessarily looks back. The Pending early warning partially mitigates this but cannot eliminate the lag. Treat the official regime change as a confirmation, not a leading signal.
🟦 DISCLAIMER
This indicator is provided for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. The hypothetical backtest is a diagnostic tool — there is no position sizing, no risk management, and no consideration of overnight financing, dividends, or other real-world frictions beyond the configured fee and slippage. Always conduct your own analysis and apply proper risk management. Indicator
Volatility Heatmap Bands [PickMyTrade]━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
WHAT IT DOES
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Volatility Heatmap Bands fits a log-normal distribution to recent price returns and draws a statistically calibrated price envelope — then colours every bar by where it sits inside that envelope.
Simple version: the red band at the top is the "overbought wall." The cyan band at the bottom is the "oversold wall." When bars turn red, price is statistically stretched toward the top. When bars turn cyan, price is statistically stretched toward the bottom. The colour tells you whether a move is normal or extreme — without reading a single number.
Three layers power every calculation:
▸ Log-Normal Drift (μ) — rolling mean of log-returns, representing the direction price is diffusing
▸ Volatility (σ) — rolling standard deviation of log-returns, updated every bar
▸ Itô Correction (−½σ²) — converts the arithmetic mean to a geometric mean, required for continuous-time price models. Without this, the envelope is systematically biased upward
The result is a probability corridor that widens in volatile markets and tightens in calm ones — automatically, with no manual adjustment.
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THE HEATMAP EXPLAINED
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Each bar is coloured by a single value: the normalised position of close within the 10th–90th percentile envelope.
position = (close − 10th band) / (90th band − 10th band)
0.0 → close is at or below the 10th band → deep cyan
0.5 → close is at the midpoint → neutral
1.0 → close is at or above the 90th band → deep red
This is not a momentum oscillator and not RSI. It is a spatial measure of where price sits inside its own forward-projected distribution. A deep-red bar means the current close is in the top decile of the statistically projected range — not that it is rising fast, but that it has reached a zone that is historically reached only 10% of the time.
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SIGNALS — ▲ LONG / ▼ SHORT
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A breakout signal fires when price exits the N-bar channel:
▲ Long — close breaks above the highest close of the last N bars
▼ Short — close breaks below the lowest close of the last N bars
An optional trend filter (slow EMA gate) removes counter-trend signals:
• Longs only when close is above the trend EMA
• Shorts only when close is below the trend EMA
Signals appear as small triangles on the chart. They are not trade recommendations — they mark a structural breakout that coincides with a momentum expansion, for the trader to act on within their own framework.
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VOLATILITY REGIME DETECTION
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σ is compared to its own rolling distribution via a percentile rank:
≥ 75th percentile of σ → High Vol regime (subtle orange background)
25th – 75th → Normal regime (no tint)
< 25th percentile of σ → Low Vol regime (subtle blue background)
Why it matters: the same breakout signal in a High Vol regime carries a wider envelope and therefore a different risk profile than the same breakout in Low Vol. The background tint makes the regime visible at a glance.
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WHAT MAKES IT DIFFERENT
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Most volatility bands (Bollinger, Keltner, Donchian) are constructed from past price movement around a moving average. They describe where price has been.
VHB projects forward. The envelope is calculated at the current close and extended H bars into the future using the fitted distribution. The bands show where price is statistically likely to be in H bars — not where it has been.
Consequence: in a trending market the bands tilt with the drift. In a mean-reverting market the bands remain flat. The geometry of the envelope changes with market character, not with arbitrary multiplier choices.
The Itô correction is not a cosmetic detail. In continuous-time finance, the expected log-price grows at μ − ½σ², not μ. Omitting the correction causes the upper band to overstate likely price levels by an amount that grows with σ² — small in calm markets, significant during volatility expansion. VHB applies the correction on every bar.
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HOW TO USE IT
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1. Apply to any liquid instrument — futures (MNQ, NQ, ES, CL, GC), forex pairs, crypto
2. Choose your timeframe:
• 1m / 5m — scalping, intraday momentum
• 15m / 1H — intraday swing
• 4H / Daily — positional
3. Read the heatmap first:
• Cyan bars near the lower band → price is statistically cheap relative to its own distribution
• Red bars near the upper band → price is statistically expensive
4. Wait for a signal ▲ / ▼ to confirm directional intent
5. Use the info panel (bottom-right) to monitor CDF Score, σ/bar, regime, and band levels in real time
6. Set alerts via the Alerts tab for Long Signal, Short Signal, or Regime changes
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SETTINGS REFERENCE
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| Input | Default | Purpose |
|---|---|---|
| Fit Lookback | 100 | Bars used to estimate μ and σ |
| Holding Horizon | 10 | Bars forward the distribution is projected |
| Breakout Channel | 20 | N-bar high/low for signal detection |
| Trend Filter | ON | EMA gate — removes counter-trend signals |
| Trend EMA Length | 200 | Slow EMA period for directional gate |
| Show Outer Bands | ON | 10th and 90th percentile lines |
| Show Median | ON | 50th percentile — Itô-corrected drift line |
| Show Inner Bands | OFF | 25th and 75th percentile lines |
| Fill Band | ON | Dark fill between 10th and 90th |
| Heatmap Bar Colour | ON | Cyan–red gradient by envelope position |
| Highlight Regime | ON | Subtle background tint by volatility regime |
| Show Info Panel | ON | Live σ, CDF score, drift, bands, signal |
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NOTES
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• Requires at least Fit Lookback bars of history before the first band appears
• Works on any asset class; continuous instruments (futures, forex) show the cleanest log-return distribution
• The indicator does not repaint — all band values are calculated from confirmed closed bars
• Signals use close for channel calculation — no lookahead bias
• This tool is for research and educational purposes only. It is not financial advice.
Indicator
Whale Liquidity and Absorption Profile [AlgoAlpha]🟠 OVERVIEW
The Whale Liquidity and Absorption Profile maps intrabar buying, selling, delta, and absorption activity into stacked horizontal profiles. It samples lower timeframe volume data inside each chart candle, then groups that activity into price bins to show where aggressive participation and absorption occurred across a configurable lookback range.
The script separates strong and weak activity using a percentile-based strength filter. It also builds a delta heatmap, absorption profile, historical absorption heatmap, and local absorption zones. Together, these components help traders identify where liquidity entered the market, where imbalance formed, and where price may react again.
🟠 CONCEPTS
Intrabar Sampling — Lower timeframe volume and directional data are requested using request.security_lower_tf() to reconstruct buying and selling activity inside each chart candle.
Strength Filter — Intrabar volume samples are ranked by percentile. Volumes above the selected percentile threshold are classified as strong activity while lower values are treated as weak activity.
Delta Profile — Buy volume minus sell volume calculated per price bin. Positive delta shows aggressive buying while negative delta shows aggressive selling.
Absorption Volume — Bullish volume occurring in upper wicks and bearish volume occurring in lower wicks. This is used to estimate where opposing liquidity absorbed incoming pressure.
Price Bins — The full price range inside the lookback is divided into vertical bins. All volume, delta, and absorption calculations are aggregated into these bins.
Absorption Peaks — Local highs in the absorption profile compared against neighboring bins. These areas are drawn as support and resistance zones.
🟠 FEATURES
Multi-Layer Volume Profile — Displays stacked buying and selling activity across price levels.
• Separates strong bullish, weak bullish, weak bearish, and strong bearish volume.
• Optional strong-only mode hides weak participation and normalizes the profile using only strong activity.
Delta Heatmap — Displays signed delta values directly inside each profile cell.
• Positive delta highlights dominant buying pressure.
• Negative delta highlights dominant selling pressure.
Absorption Profile — Aggregates wick-based absorption activity into a separate horizontal profile. (Buys at high wicks, Sells at low wicks)
Historical Absorption Heatmap — Creates rolling 5-bar heatmap snapshots to show where historical absorption accumulated over time.
Absorption Zones — Detects local absorption peaks and projects them across the chart as potential reaction areas.
Strong Activity Bubbles — Marks the strongest intrabar buying and selling events directly on price using percentile-ranked bubble tiers.
🟠 HOW TO USE
Load 2 instances of the indicator to bypass box drawing limits and use both the Absorption heatmap and the profiles.
Watch for stacked strong bullish volume combined with positive delta — this can show aggressive participation entering a price region.
Watch for stacked strong bearish volume combined with negative delta — this can show heavy selling pressure dominating a level.
Use absorption zones as areas where price previously encountered opposing liquidity — these zones may act as future reaction points.
Compare delta against absorption — strong positive delta with heavy upper-wick absorption can indicate trapped buyers or resistance.
Use the historical absorption heatmap to locate repeated liquidity interaction zones that price continues to respect over time.
Increase profile resolution for tighter price detail and reduce it for broader structural zones.
Enable strong-only mode to isolate high-participation liquidity events and remove weaker intrabar activity from the profile.
🟠 CONCLUSION
Whale Liquidity and Absorption Profile combines intrabar volume profiling, delta analysis, and wick-based absorption detection into a single structured framework. The indicator separates strong and weak participation while mapping where liquidity was absorbed across price levels. This gives traders a clearer view of imbalance, participation strength, and potential reaction zones inside the current market structure. Indicator
