Institutional Polynomial Regression MatrixInstitutional Polynomial Regression Matrix
www.tradingview.com
Institutional Polynomial Regression Matrix is a professional statistical market analysis indicator designed to help traders understand trend structure, price equilibrium, institutional participation, and volume concentration using an advanced polynomial regression model. Instead of relying only on traditional moving averages or basic trendlines, this indicator builds a dynamic mathematical regression curve and combines it with multi-layer standard deviation channels, volume profile distribution, Point of Control analysis, and an institutional information dashboard.
The objective of this indicator is to provide traders with a structured analytical framework that explains where price is trading relative to its statistical trend, how far price has deviated from equilibrium, where the highest concentration of traded volume exists, and whether current market conditions favor trend continuation, equilibrium, or potential exhaustion.
The indicator continuously analyzes historical market data over a configurable regression period and calculates an optimized regression curve that adapts to changing market behavior. Depending on user preference, the regression engine can operate in either Linear Regression mode or Polynomial Regression mode, allowing traders to study both straight trending markets and naturally curved market structures that frequently appear during accumulation, distribution, expansion, and reversal phases.
Unlike conventional regression channels that display only a few outer boundaries, this indicator constructs a complete statistical channel matrix composed of multiple dynamic regression layers. These layers visualize the complete distribution of price around the regression center, allowing traders to observe how price behaves within different statistical regions instead of relying on a single trend line.
As the market evolves, every channel automatically updates to reflect the newest statistical information. This enables the regression structure to remain synchronized with changing market conditions while maintaining mathematical consistency throughout the calculation window.
One of the most important analytical components is the integrated Point of Control calculation. The indicator builds a volume distribution around the regression structure and determines the price region where the greatest amount of trading activity has occurred during the selected lookback period. This Point of Control represents the area where market participation has been strongest and where institutional positioning often becomes most visible.
The Point of Control is displayed directly on the regression structure together with its corresponding traded volume. Since large market participants frequently transact significant positions around high-liquidity regions, this information helps traders identify important equilibrium zones where price may consolidate, react, or continue trending.
The indicator also produces a complete Standard Deviation channel framework extending both above and below the regression curve. These statistical boundaries provide objective measurements of how far current price has deviated from its expected regression value.
When price remains close to the regression center, market conditions generally indicate equilibrium and balanced participation.
As price approaches higher standard deviation levels, traders can evaluate whether momentum is strong enough to justify continuation or whether statistical exhaustion may begin to develop.
Likewise, movement toward lower deviation zones may indicate discounted pricing relative to the regression curve and can provide valuable context when combined with other confirmation techniques.
Because these boundaries are derived mathematically rather than manually drawn, they offer a consistent statistical framework for measuring volatility and trend expansion.
Another important feature is the dynamic volume profile visualization integrated directly into the regression channel. Rather than displaying a traditional fixed horizontal profile, this indicator projects volume distribution along the regression path itself. Every profile segment is weighted according to traded volume and rendered using gradient intensity that highlights high participation regions while visually reducing lower participation areas.
This approach enables traders to immediately recognize where institutional activity has been concentrated throughout the trend instead of observing volume independently from price structure.
The indicator also includes a comprehensive analytical dashboard positioned directly on the chart. This dashboard summarizes the current statistical state of the market and provides real-time information including market direction, Point of Control level, Point of Control volume, regression value, channel boundaries, channel width, standard deviation position, regression mode, volume distribution, trend strength, regression slope, market equilibrium status, and several additional statistical measurements.
By presenting these calculations in a structured format, the dashboard eliminates the need for traders to manually interpret multiple chart elements simultaneously.
The regression curve itself acts as the mathematical equilibrium of the current market. Price trading above the regression center generally indicates positive statistical positioning, while price remaining below the regression curve reflects weaker market positioning relative to historical behavior. Combined with channel boundaries and Point of Control analysis, traders obtain a comprehensive statistical perspective of current market conditions.
This indicator was created for traders who prefer objective mathematical analysis over subjective chart drawing. Every calculation is generated automatically using statistical regression methods and continuously adapts to evolving market conditions without requiring manual adjustments.
Institutional Polynomial Regression Matrix can be applied to Forex, Indices, Commodities, Cryptocurrencies, Stocks, Futures, and other liquid financial markets. It can also be used across multiple timeframes depending on each trader's analytical approach.
The indicator is designed primarily for market analysis, trend evaluation, volatility measurement, institutional participation analysis, statistical price positioning, and identifying areas where price is statistically balanced or significantly extended relative to its underlying regression model.
Rather than generating automatic buy or sell signals, the indicator provides a professional analytical environment that allows traders to evaluate market structure using statistical probabilities together with their own trading methodology, confirmation techniques, and risk management rules.
Author Verification
This indicator has been independently researched, engineered, designed, and implemented by Forex_Market_Insights. Every mathematical model, regression calculation, statistical workflow, visualization system, dashboard architecture, volume profile methodology, and analytical component has been developed through an original software engineering process specifically for TradingView Pine Script. The project represents an independently engineered analytical framework focused on institutional market structure, statistical regression analysis, professional visualization, and advanced market interpretation.
Original Indicator Script Implementation Verification
The complete Pine Script implementation is an original software development project created entirely from the ground up. It is not a copied, extracted, converted, translated, reverse-engineered, modified, or redistributed version of any existing TradingView script, commercial indicator, open-source publication, private strategy, or third-party software. While concepts such as regression analysis, standard deviation channels, statistical modeling, and volume profiling are publicly recognized analytical techniques used throughout financial markets, the mathematical implementation, processing workflow, source code architecture, visualization methodology, optimization logic, rendering system, dashboard structure, calculation sequence, and execution flow contained within this indicator have been independently designed and programmed specifically for this project.
Developer Declaration
The verification section should remain preserved within the script documentation and publication as part of the project's development history. It confirms that the indicator represents an independent engineering effort and original software implementation. Any future enhancements, feature additions, performance optimizations, or analytical improvements should continue following the same independent development principles while preserving the integrity, originality, and maintainability of the codebase.
Author Declaration
Forex_Market_Insights confirms that this indicator has been developed through independent research, mathematical design, software engineering, testing, optimization, and implementation. The purpose of this project is to provide traders with a professional statistical analysis framework for studying market behavior using regression modeling, institutional volume distribution, volatility analysis, and advanced visualization techniques. This publication is intended solely as an educational and analytical trading tool. It does not constitute financial, investment, portfolio management, or trading advice. Every trader remains fully responsible for evaluating market conditions, applying appropriate risk management practices, and making independent trading decisions.
Implementation Integrity Statement
The complete implementation reflects an independently engineered TradingView Pine Script solution emphasizing originality, computational efficiency, mathematical consistency, visual clarity, long-term maintainability, and professional analytical functionality. Any similarities to other market analysis tools are limited exclusively to publicly recognized financial concepts that are widely used throughout technical analysis and quantitative market research. Those concepts themselves are not proprietary. The specific implementation, software architecture, regression engine, visualization framework, statistical workflow, volume processing system, dashboard design, optimization methodology, and complete source code contained within this project remain independently developed by Forex_Market_Insights.
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Candlestick Edge Auto-Preset MTF Self-CalibratingCandlestick Edge only fires a candlestick pattern when it is "rightly placed" — confirmed by a higher-timeframe trend AND by where price sits in the developing volume profile. Then it does what most pattern tools don't: it forward-tests every signal and reports the MEASURED edge per pattern, so you read realized performance instead of a marketing claim.
WHY THIS IS ONE TOOL (not a bundle)
The parts answer one question about one candle: "is this pattern in a place that has historically paid, and does it beat a coin-flip here?"
PATTERN detection says WHAT printed (24 classic candlestick patterns).
HTF ALIGNMENT says whether the bigger trend agrees.
VOLUME-PROFILE POSITIONING says WHERE it printed — reversals only at value-area edges, naked POC, HVN support/resistance, or liquidity sweeps; continuations only through low-volume voids or on a value breakout.
The CALIBRATION SPINE forward-resolves each signal with a triple barrier and reports Hit% vs a matched Base% (Edge) with a Wilson confidence interval, so a placed-and-confirmed pattern can be told apart from a small-sample fluke.
One pattern substrate, one location read, one calibration spine.
MEASUREMENT (the differentiator)
Each signal opens at close with target = ±TP·ATR, stop = ∓SL·ATR, over a fixed horizon. The first barrier touched decides win/loss (same-bar tie counts as the stop — conservative). Base% is the unconditional same-barrier win-rate for that direction. Edge = Hit% − Base%; a "*" marks rows whose Wilson 95% lower bound clears the base rate. A leave-one-out row prices each filter's marginal contribution, and a footer lists only the patterns that are green AND have enough samples to trust in the current configuration.
AUTO PRESET (default on)
Candlestick edges are timeframe-specific. Auto Preset reads the chart's timeframe and switches on the pattern subset plus higher-timeframe distance that performed best for that timeframe in the author's study of NSE index futures, and forces the two filters on. Turn it OFF for full manual research mode: all 24 patterns selectable, filters and HTF distance (3x / 5x / 15x / custom) under your control. Nothing is ever removed — the preset only curates which patterns are active by default per timeframe.
HOW TO USE
Leave Auto Preset on and read the labelled signals (teal = bullish, red = bearish, each tagged with the pattern name). Open "Show scoreboard" to see measured Edge per pattern — trust the EDGE column and the "*", never a raw hit-rate. Best behaviour is on intraday timeframes (1H and below).
ORIGINALITY
Standard techniques are credited below. What is original is the combination: a location-gated pattern engine whose every signal is forward-calibrated, a timeframe-adaptive auto-preset, a leave-one-out filter attribution, and an auto-surfaced tradeable set — measured edge, not asserted.
NON-REPAINT
Signals open on confirmed bars; triple-barrier outcomes resolve on bars AFTER the trigger; all higher-timeframe / lower-timeframe / prior-day-POC requests use lookahead_off and confirmed intrabars. Pivots used by sweeps confirm first.
DATA & MARKETS
Runs on any symbol that reports volume; the developing profile needs volume to be meaningful. Defaults are tuned for intraday index futures. On the Enhanced data tier the delta read uses intrabar aggregation (richer on paid plans) and auto-falls-back to an OHLCV proxy when intrabars aren't served — safe to leave on for any plan.
CONCEPT CREDITS (methods operationalized — original Pine re-derivations)
Candlestick patterns — Nison; pattern-performance framing per Bulkowski
Market / auction profile, POC / Value Area — Steidlmayer; Dalton
Bulk Volume Classification — Easley, Lopez de Prado & O'Hara (2012)
Triple-barrier labelling — Lopez de Prado
Wilson score interval — Wilson (1927)
HONESTY / LIMITS
The profile is an ATR-binned developing session profile (not tick POC). Delta is an estimate (proxy or intrabar reconstruction), not true bid/ask. Reported edge is context measured on loaded history — not a prediction or a promise. The preset defaults were tuned on one instrument over a recent window, so treat them as a well-measured hypothesis, not proven alpha.
Educational tool. Not financial advice — you alone are responsible for your trading decisions. Indicador
Potential Well MapOverview
A volume or time profile tells you where price spent time. Potential Well Map tells you the forces acting at each level. It models the market as a particle drifting in a one-dimensional energy landscape and estimates that landscape directly from recent price action — the local drift (average next move) and diffusion (variance of the next move) at each price level — then integrates them into a potential curve. Its valleys are attractors (dynamical support/resistance that pulls price in); its peaks are barriers (levels price is repelled from). Two levels with identical occupancy can be opposite in dynamics — one an attractor, one a barrier — and this map tells them apart. It is a descriptive structure-and-risk map, not a predictive signal.
Why these components are ONE tool (mashup justification)
This is a four-stage chain where each stage produces something the previous one can't, and the honesty layer keeps the whole thing accountable:
Drift + diffusion per level — the raw forces. For every price bin, exponentially-decayed accumulators track the count, sum, and sum-of-squares of the next one-bar move that started there, giving the conditional first two moments (drift and diffusion) with recent regime weighted most. This is O(N) per bar — no window rebuild, no timeout.
The potential curve — the integral of drift ÷ diffusion. This turns the raw forces into a landscape whose valleys and peaks are attractors and barriers. It is the object an occupancy profile fundamentally cannot produce, because occupancy measures time spent, not the pull at a level.
Escape pressure — a bounded 0–100 breakout gauge derived from the remaining wall height between price and the nearest barrier. Because the potential is already diffusion-normalized, the escape factor is a clean exponential of the wall height, and it concentrates toward 100 as price approaches a wall.
The calibration harness — the honesty layer. When a barrier escape is flagged, did price actually travel that way more often than the unconditional base rate? It reports Hit / Base / Edge, resolved forward on confirmed bars only. The forces are a picture; the harness is the proof. Remove any one stage and the map either asserts structure it never tested, or shows a level with no dynamics behind it.
How it works
Price is detrended into a coordinate x = ln(price) − ln(slow anchor) so the distribution stays roughly centred as price trends. A grid of x-bins spans a few volatility units either side of zero. For each bin, the decayed accumulators build drift and diffusion; neighbour bins are sample-weighted-smoothed; the force (drift ÷ diffusion) is integrated into the potential; valleys and peaks that clear a prominence margin are marked as wells and barriers; and the escape pressure to each adjacent barrier is computed. Bins with too few effective samples are greyed out rather than trusted.
How to use it
Read the landscape as context. The green valley line is the active attractor — a mean-revert target. The dashed red lines are the barriers above and below. The shaded box is the expected range of a stiff well. In the dashboard, the escape pressures rise toward 100 as price nears a wall; a pin (fade-to-mean) is flagged only when price sits mid-well in a stiff, bounded valley, and an escape is flagged when price crosses a barrier after that side's pressure was already elevated. Watch the Edge row: a positive, matured Edge means escapes have led price on this instrument; near-zero means treat the map as structure only, not a trigger. It is never a standalone signal.
Universal & non-repainting
The source is an input and everything is self-scaling (vol-scaled grid, detrended coordinate), so it runs on any symbol and timeframe; defaults suit a liquid index/futures intraday chart. All statistics use closed past bars only — both the drift/diffusion accumulators and the calibration harness update solely on confirmed bars, so their numbers never inflate intrabar. The displayed landscape naturally evolves bar to bar because it is a live estimate, not a fixed level; confirmed escape and pin marks settle on the close of their bar. Edge figures are in-sample, close-to-close, with no costs — a study aid, not a backtest.
Originality
The building blocks are public physics and statistics: stochastic drift-diffusion dynamics, conditional-moment estimation of the drift and diffusion coefficients, and escape-rate theory. What's original is the application to a price series as a live, decayed, per-level energy landscape — the detrended coordinate, the exponential-memory conditional-moment accumulators, the diffusion-normalized potential integral, the prominence-gated well/barrier detection, the escape-pressure gauge, and the forward-calibration harness that scores escapes against their base rate. This is a clean-room implementation; no third-party Pine code is reused.
Concept credits
Stochastic drift-diffusion (Langevin) dynamics and the Fokker–Planck description of a probability landscape — Paul Langevin, Adriaan Fokker, Max Planck
Estimating drift and diffusion from the conditional moments of increments (Kramers–Moyal expansion) — Hendrik Kramers, José Enrique Moyal; exposition after Hannes Risken
Barrier escape / escape-rate theory — Kramers' escape-rate framework
Forward base-rate calibration discipline — standard out-of-sample evaluation practice
Disclaimer
Research and educational tool only. Not financial advice, no recommendation, no guarantee of results. It is an effective, empirical 1-D approximation of a memoryful, multi-factor market — treat "escape pressure" as a relative, normalized gauge, not a literal probability. Estimates are noisy where samples are sparse (the greyed bins). Indicators describe past behaviour; they do not predict the future. Trading carries risk of loss. Test out-of-sample and make your own decisions. The author accepts no liability. Indicador
Pivot Support & Resistance Matrix [ChartPrime]Pivot Support & Resistance Matrix
🔶 OVERVIEW
Traders often struggle to identify which support and resistance levels are truly critical and which ones are just temporary market noise. The Pivot Support & Resistance Matrix solves this by combining automated, proximity-filtered structural lines with a real-time, volume-cleared Polyline Pivot Profile Engine .
Instead of cluttering your chart with every single minor pivot, this script utilizes an ATR-based buffer system to only track key structural levels. Furthermore, it pools all historical pivot points into a customized histogram matrix displayed right in your margin, pinpointing the absolute **Pivot Point of Control (POC)** where historical order blocks are most heavily clustered.
🔶 HOW IT WORKS
The script processes market structure through a multi-tiered calculation architecture:
Proximity-Filtered S/R Generation: The script monitors classic structural highs and lows ($Pivot\ High / Low$). To prevent messy line stacking, it implements an automated proximity filter using an NYSE:ATR \times Multiplier$ threshold. A fresh Support or Resistance line will only spawn if there isn't an active, unbroken line already sitting within that price buffer.
Dynamic Breakout Conversion & Volume Logging: Active lines automatically extend forward in time. The exact moment price closes past a level, the script transforms its state: it turns into a dashed, neutral-colored broken level, and replaces its price label with the exact transaction volume that occurred on the breakout candle (formatted cleanly as K or M).
Polyline Profile Matrix: At the right edge of your screen, the script divides the high-to-low calculation lookback window into a customized array of price bins. It then scans through all historical pivots, plotting a seamless, shaded polyline histogram based on pivot density.
Pivot Point of Control (POC): The single price bin that contains the highest concentration of historical pivot touches is highlighted across your entire chart as a solid red **Pivot POC Line**, displaying exactly how many times institutions used that precise level for market reversals.
🔶 KEY FEATURES
Smart ATR Density Filtering: Prevents redundant lines from overlapping in tightly consolidated ranges, providing clean, high-conviction key levels instead of generic lines on every candle.
Post-Breakout Volume Memory: Instead of deleting broken lines, they switch to a dashed visual state while logging the breakout volume. This tells you instantly whether a level was smashed with heavy institutional backup or weakly drifted through.
Adaptive Profile Theme Coloring: The polyline histogram dynamically matches the current market state. If more historical support pivots have been registered than resistance levels inside your lookback window, the profile automatically adopts the Support color theme, signaling a bullish structural baseline (and vice versa).
Bin Smoothing Radius Configuration: To account for minor market fluctuations, each pivot point distributes its structural weight to adjacent price bins based on a user-defined radius, creating a smooth, professional-grade market profile.
🔶 TRADING APPLICATIONS
High-Volume Breakout Validation: When an established support or resistance line is broken, check the volume tag left on the line. A break showing high volume (e.g., $4.5M$) indicates a high-probability trend continuation or verified Market Structure Shift.
Pivot POC Magnet Re-entries: The red Pivot POC line acts as a major institutional fair-value anchor. When price expands far away from it, it serves as an excellent structural target; conversely, during macro retracements, it behaves as the strongest anticipated bounce zone.
Profile Value Area Exits: Use the outer limits of the polyline histogram to judge market extensions. If price stretches completely beyond the top or bottom boundaries of the pivot profile, it indicates highly overextended conditions, alerting you to tighten stop losses or secure open profits.
🔶 SETTINGS
Pivot Left/Right Bars: Sets the lookback structural count required to verify a local swing high or swing low. Higher values isolate macro key levels, while lower values target scalping ranges.
Calculation Lookback Window: Restricts profile tracking and line management to a strict historical window (e.g., last 600 bars), preserving processing speeds and focusing your data on recent market developments.
ATR Proximity Multiplier: The minimum distance required between horizontal lines. Increase this multiplier to dramatically clean up your chart and leave only the most prominent structural boundaries.
Number of Bins & Smoothing Radius: Controls the resolution of your polyline profile. Higher bins provide finer price accuracy, while a higher smoothing radius blends adjacent bins for a cleaner visual histogram.
🔶 CONCLUSION
The Pivot Support & Resistance Matrix indicator completely modernizes standard support and resistance trading. By combining price-filtered line tracking with a structural density profile, it allows traders to clearly see where major liquidity walls stand and precisely how much volume was required to break them down. Indicador
Indicador
Volume Force FieldVolume Force Field — TradingView publication kit
Volume Force Field turns a volume profile into a force map. A normal profile shows you where value is. This overlay shows you the net pull on price at every level — the slope of the volume landscape toward the nearest magnet — and then it measures, on your own history, whether that pull actually leads price. One plain-language panel tells a non-technical trader what it means at a glance.
What it plots
The force field — coloured bands across price. Green means price at that level is being drawn up toward a high-volume magnet; red means drawn down. Band opacity scales with how much volume sits there.
POC and magnets — the yellow line is the Point of Control (the single strongest magnet); green lines are secondary magnets; dashed red lines are low-volume ridges that price tends to cross quickly.
Value Area — the shaded band holding your chosen % of volume around the POC: the range where trade has been accepted.
Value centre ± band — a moving equilibrium (rolling VWAP / adaptive MA / EMA) with a σ band: the drift level price is pulled back toward.
Guidance panel — plain English: the current bias (pulling up / down / balanced), location vs value (inside / stretched above / stretched below), the nearest magnet and distance, and one line on what to watch.
Past signal marks — small triangles wherever the net pull historically turned strongly up or down, so you can eyeball how the field has behaved.
Why these components are one tool (not several indicators stacked)
Each part answers a question the others cannot, and removing any one breaks the read:
Volume kernel density builds a smooth value landscape whose peaks are magnets. Optional lower-timeframe slicing distributes each bar's volume across its true intrabar path; an optional half-life lets recent volume outweigh old, so the field is a living map, not a flat lookback.
The density gradient turns that landscape into a force — the direction and steepness of attraction at each level, which a plain density cloud never exposes.
The Value Area frames where price is accepted versus stretched, so the force is read in context.
The moving value centre adds the mean-reversion pull toward equilibrium.
The calibration harness back-measures the whole thesis: when the pull is strong, did price actually travel toward the magnet more often than the base rate? It reports Hit %, Base % and Edge.
Density is a picture; the gradient makes it a force; the Value Area frames it; the centre adds drift; the harness keeps it honest. Together they are one decision object.
How to use it
Read the guidance panel first — it states the bias, where price sits versus value, the nearest magnet, and what to watch. On the chart, treat green bands as upward pull toward the magnet above and red as downward pull; the POC and magnet lines are targets; dashed lines are fast low-volume gaps; the Value Area is the accepted range; the centre ± band is the drift equilibrium. Turn on the Calibration table and read Edge: a strong pull with a positive, matured Edge is the context this tool is built to surface. An Edge near zero means the attraction is not exploitable on that symbol/timeframe — that is useful information, not a trade trigger. This is a context map, not a signal generator; combine it with your own risk and execution rules.
Universal across markets
Price source and volume feed are inputs, so it runs on any symbol. Instruments without real volume fall back automatically to a price-density field. Default settings target an index-futures 1-minute chart; change the lookback, centre and slice resolution to suit other assets and timeframes.
Originality
The building blocks are standard and credited below; the original work is the coupling and the rendering — a volume kernel density whose gradient is drawn as a directional force field, fused with a Value Area and a moving value centre, with magnet/ridge extraction and a forward base-rate harness that reports each strong-pull setup's realised Edge instead of asserting that magnets work. No third-party Pine code is reused.
Concept credit
Kernel density estimation — Emanuel Parzen (1962) and Murray Rosenblatt (1956); bandwidth rule — B. W. Silverman (1986). Point of Control / Value Area / Market Profile — J. Peter Steidlmayer. Moving-equilibrium ("price in a moving potential") market models — Hideki Takayasu, Takayuki Mizuno and Tsutomu Watanabe. Not affiliated with, nor endorsed by, any third party.
Honesty / limitations
No tick or order-book tape is available to scripts, so the density is built from OHLCV and optional lower-timeframe slices — a proxy, not the true traded distribution. Lower-timeframe slices exist only for recent bars; older bars use bar price automatically. "Force" is a hypothesis the Edge stat exists to falsify. The harness uses a light proxy of the field (the full grid cannot be recomputed on every bar), so it tests the idea rather than the exact drawn object. Like any volume profile, the last (forming) bar's field refreshes in real time; on closed bars it is fixed. Edge figures are in-sample, close-to-close, without costs — a study aid, not a verified backtest. Nothing here predicts price.
Disclaimer
For research and educational purposes only. This script is not financial advice, not a recommendation, and not a guarantee of future results. Indicators describe past behaviour; they do not predict the future. Trading carries risk of loss. Test on out-of-sample data and make your own decisions. The author accepts no liability for any use of this script. Indicador
Auction & Liquidity Command Center Volume Profile, MeasuredAuction & Liquidity Command Center — Volume Profile, Measured
The levels traders already use — prior POC, value area, naked POCs, prior day high/low, session AVWAP, HVN/LVN — each scored by its measured reaction on this chart: how often price rejects vs breaks, and what the fade has been worth in R. Levels with evidence, not levels with vibes. Never a buy or sell.
What it does
Every structure tool draws levels. None of them measures what happens when price gets there. This tool builds the session-anchored auction map with profile-grade accuracy, detects qualified touches of every level, resolves each touch through a triple-barrier outcome, and pools the results by level TYPE into a live scoreboard: pPOC +0.01R · rej 50% · n156. You see not just where the levels are, but which kinds of levels have actually meant something on this chart — and which are coin flips.
The components, and why they are combined
This is a deliberate synthesis of four parts, each covering the previous one's weakness:
A profile-grade level engine (Market Profile — J. P. Steidlmayer). Nine level types from the session volume-at-price profile and session extremes: prior POC, prior VAH/VAL (classical two-row 70% expansion), naked POCs (prior POCs never revisited), prior day high/low, the session's anchored VWAP, and HVN/LVN volume nodes (prominence-filtered local extremes). Accuracy choices: each bar's volume is distributed range-proportionally across the rows it overlaps (not binned at one point); POC ties break toward the session center. Weakness left open: a drawn level says nothing about whether it matters.
A qualified-touch detector. A level must be ARMED — price fully away from it by at least k×ATR — before a touch of it can count, and it disarms after every touch. Chop sitting on a line cannot enter the record. Approach direction is stored with every event. Weakness left open: a touch is not an outcome.
Triple-barrier outcome resolution (outcome labelling — M. López de Prado). From each touch: REJECT if price moves m×ATR back the way it came first, BREAK if it moves m×ATR through first, TIMEOUT after T bars. Purity rules: barriers are fixed at the ATR of the touch moment; evaluation starts the bar after the touch; a bar hitting both barriers is a timeout, never a guess. Weakness left open: one level's history is n = 1.
Per-TYPE pooling with honesty gates. Statistics pool by level type, never by individual line — a type is a real sample. A type shows no score until a minimum number of its touches have resolved (default 20); until then it reads BUILDING with its count. Timeouts are reported in n but excluded from the reject/break ratio. Fade expectancy = (rejects − breaks) / (rejects + breaks), in R.
How to read it
Rails are colored and styled by type (solid profile levels, dashed day levels, dotted volume nodes, violet naked POCs); each label carries its type's live score or its BUILDING count.
Evidence on the chart: a gray • at every qualified touch, then ○ (teal) where the touch rejected and ✕ (amber) where it broke. Every number on the scoreboard can be audited against the chart.
Dashboard: nearest level and its score, with a plain-language verdict (tends to hold / coin flip / tends to break) so the read needs no statistics background; per-type scoreboard (fade R · reject % · n) for all nine types; touch counts; the exact engine settings in the NOTE row.
Honest expectations: most types on most charts score near zero — that is the truthful baseline, and seeing it protects you from folklore. The value is in the exceptions this chart's own history reveals (for example, day extremes often carry a modest positive fade expectancy while POC retests are a coin flip), and in knowing the difference.
How to use it
Use the scoreboard to weight your own playbook: give more respect to touches of types that have measured well here, less to types that grade as noise — and size accordingly. The "Touch of a MEASURED level" alert fires only when price reaches a type with a real sample behind it. This is context about where price reactions have had structure — never a direction, never an entry signal.
Non-repaint & universality
Profiles, POC/VA/nodes and day levels commit only at session close on confirmed bars; touches and outcomes resolve on confirmed bars; the AVWAP is cumulative within its session. Nothing repaints. The script requests no external data of any kind — no lower timeframes, no security calls — so it runs identically on every plan and every symbol with volume.
Use on any market
Volume source, profile rows, value-area %, node thresholds, arm distance, barriers and sample gates are all inputs. Defaults suit liquid intraday index futures; intraday timeframes give the engine the most touches to learn from.
Originality & credits
The synthesis — a range-proportional session profile, qualified-touch detection, touch-time-ATR triple-barrier outcomes, and per-type pooled reaction statistics displayed as a live scoreboard — is original work for this publication. Concept credits: Market Profile / point of control / value area — J. Peter Steidlmayer; naked (virgin) POC — market-profile literature; anchored VWAP — as popularised in modern trading literature; triple-barrier outcome labelling — M. López de Prado. Implementation and charting design are the author's own.
Disclaimer
Research and education only. NOT financial advice, NOT a signal service, NOT a guarantee of future results. Reaction statistics are empirical frequencies from this chart's limited history, pooled per level type; they change with regime and sample, and a positive expectancy is not a promise. Validate independently and manage your own risk. Indicador
Naked POC Magnetism Fill Probability & Median WaitNaked POC Magnetism — Fill Probability & Median Wait
What it is
A naked POC is the highest-volume price of a past session that price has not revisited since. Traders treat them as magnets — but "it usually gets filled" is folklore until it's measured. This tool measures it. Every historical naked level on your chart becomes a data point (how many sessions it survived before being touched, or whether it never was), and a survival model (discrete-hazard life table) turns that history into, for each live naked level: the probability it fills within the next N sessions and the median wait. Levels are drawn with their measured magnetism, not just their location.
How the statistics work — and their honest limits
Each session's volume-at-price profile is built from that session's bars; at session close the peak-volume price (POC) becomes a naked level.
A level is filled the first time a later bar's range touches it; its age in sessions at that moment is one observation. Levels removed unfilled (history cap) are censored at their age — counted as "survived this long," never as fills. This is the standard treatment of incomplete observations from survival analysis (Kaplan–Meier 1958; classical life tables).
Hazard at age j = fills at age j ÷ levels at risk at age j. Survival multiplies (1 − hazard) across ages; fill-probability within a horizon and the median wait follow directly.
Reliability gates, enforced not footnoted: no probability is displayed until a minimum number of levels have resolved (input, default 20) — until then the tool says BUILDING and shows only counts. And hazard estimates at ages with fewer than 5 at-risk observations are truncated rather than trusted, per standard life-table convention.
Probabilities are empirical frequencies from this symbol and timeframe's own history — they change with regime and sample, and a 70% is not a promise.
Seeing the evidence
Every historical fill prints a small ◈ marker where a naked level was touched — the resolved observations the probabilities are measured from, visible on the chart rather than hidden in a table.
The dashboard shows both the NEAREST level and the STRONGEST magnet (highest fill probability) — they are often not the same level, and the strongest one is the better answer to "where is price most drawn".
An honest design note: this tool deliberately has NO multi-timeframe stack and NO state-debounce, unlike its siblings in this suite — sessions are the model's clock regardless of chart timeframe (a higher-timeframe copy would measure the same sessions with coarser bins), and nothing here chatters (levels are born at session close and resolve on touch). Features are added where they inform, not everywhere.
How to use it
Add to a liquid intraday chart; 5m–15m gives the model the most sessions to learn from. Let it run until the dashboard reads MEASURED.
Each rail is labelled like "NPOC 24512 · 68% /5s · med 3s" — the measured chance it fills within the horizon and the median sessions historically needed. Warm, saturated rails = strong magnets; faded = weak or unrated.
The dashboard shows the nearest level's read and — deliberately — the sample size behind every number.
Use magnetism as context about where price is drawn (targets, fade zones, expectations management), never as an entry signal by itself.
What makes it original
Naked-POC indicators draw lines. This one attaches a measured fill-probability and expected wait to each line, estimated with a proper survival model that handles censoring and refuses to show numbers it can't support. Turning a folklore level into a level with a live, honest statistic is the contribution.
Concept credits
Market Profile / point of control — J. Peter Steidlmayer. Naked (virgin) POC — market-profile trading literature. Survival estimation from incomplete observations — E. L. Kaplan & P. Meier (1958); classical life-table method. Implementation and charting design are the author's own.
Important disclaimer
Research and education only. Not financial advice, not a signal service, not a guarantee of future results. Fill probabilities are empirical frequencies measured on this chart's limited history. Validate independently and manage your own risk. Indicador
Adaptive Consensus Trail Structure, Regime & SelfAdaptive Consensus Trail — Structure, Regime & Self-Test
A trailing stop that sits on the agreement of several structural references, adapts to the market regime, and forward-tests its own signals so the numbers it shows are measured, not asserted.
What it is
Most trailing stops follow one idea — an ATR band, a SuperTrend, a moving average. This one places the stop where a small committee of independent structural references agree, reads how confident that agreement is, widens or tightens itself according to the market regime, and then continuously audits its own flips and reports the edge it actually produced on your data.
The committee has five members, each locating support/resistance from a different lens:
Anchored VWAP band — fair value for the session/week/month
Session / naked volume Point-of-Control — the price the most volume traded at, carried forward until revisited
Fair-Value-Gap midpoint — unfilled imbalance
Swing pivot — structural memory
Order-flow absorption — where aggressive buying/selling was absorbed (via Bulk Volume Classification)
Why these parts belong in one script (mashup justification)
Each reference alone whipsaws on an index, and each is right in different conditions. They are combined because they correct one another, and the entire value of the script is in that interaction — not in any single line:
A reliability layer scores every reference's historical respect rate with a Wilson lower bound, so a reference that keeps getting ignored loses its vote instead of dragging the stop around.
A consensus layer keeps only the densest agreeing cluster of references, so the stop sits on genuine agreement rather than on an average nobody respects, and far-apart references never force a permanent "no signal."
A regime layer (efficiency ratio + ADX + band-width + a volatility-cluster read + a Hurst persistence estimate) widens the band and tightens the flip confirmation in chop — this is what removes the whipsaw.
A self-test layer forward-scores every flip and recalibrates the confidence number so it means what it says.
Split apart, these are five overlays that each mislead in a range. Wired together, they are one self-correcting, self-auditing trail. That is the reason for combining them.
How it works (six layers)
References are computed on the bar close.
Reliability — rolling-capped respect counts per reference give a Wilson lower-bound "trust." POC is a magnet, so it is judged by forward reaction (did price reject away before breaking through?), not a same-bar close, which keeps its trust honest.
Consensus — the densest agreeing cluster within an ATR band becomes the trail's target; the envelope and confidence are measured on that cluster only.
Adaptive backbone — an efficiency-ratio / regime-adaptive band (Adaptive, Chandelier, or Blend) that widens in chop.
The trail — high confidence pulls the stop toward structure (floored a minimum ATR off price); low confidence rides the wide band, so it flips less in noise.
Self-test — every flip is forward-resolved by triple-barrier first-touch against an unconditional base rate, split by strength tier and by regime, with a walk-forward in-sample→out-of-sample check, a runs test of independence, a Brier score, and a confidence recalibration.
How to use it
Read the top banner for the one-line bias — BULLISH / BEARISH / WAIT — and the READ legend for what to do. The coloured line is your stop: support in an uptrend, resistance in a downtrend. BUY / SELL labels print only on confirmed, sufficiently-confident, higher-timeframe-aligned flips.
The dashboard gives detail top-down: each reference's level and trust, the consensus, raw → calibrated confidence, regime (with Hurst and ADX), the higher-timeframe invalidation stop, and a FULL / HALF / STAND-ASIDE suggestion.
Before sizing, open the Self-Test panel and read the Edge column (hit% − base%), not the raw hit-rate. A ★ means the edge's confidence interval clears the base rate. Prefer signals where the walk-forward change isn't badly negative and the runs test isn't "streaky." Being honest about it: on many indices this tool shows real edge in range and volatile regimes on higher timeframes and little-to-none on very low timeframes or once a trend is already confirmed — the panel makes that transparent so you can pick your spots.
Works on any market
Set the Price source, and for symbols with no native volume set a Borrow-volume proxy (e.g. a futures contract). The panel theme adapts to your chart background automatically. Backbone: Adaptive / Chandelier / Blend. Absorption: order-flow (BVC) or simple. An optional intrabar resolution builds a finer volume profile where available.
Originality
The committee-of-references design, the cluster-not-average consensus, the reliability weighting that lets references lose their vote, the forward-reaction POC respect test, and the confidence self-calibration are the author's own work. The underlying techniques are standard and fully credited below.
Non-repaint
References, regime, consensus and the trail all evaluate on the close of the bar; the live bar is provisional and settles on close. Self-test events are logged and resolved only on confirmed bars and resolve on bars after their trigger at fixed barriers, so hit / base / edge use no look-ahead. The higher-timeframe stop uses a lookahead-off request.
Concept credits
Wilson score interval (E. B. Wilson); efficiency ratio (P. Kaufman); ADX / DMI / ATR / volatility-stop lineage (J. W. Wilder); anchored VWAP (industry standard); volume profile / value area / point-of-control — Market Profile (J. P. Steidlmayer, developed by J. F. Dalton); triple-barrier first-touch labelling (M. López de Prado); runs test of randomness (A. Wald & J. Wolfowitz); rescaled-range / Hurst exponent (H. E. Hurst); Brier score (G. W. Brier); Bulk Volume Classification / VPIN (D. Easley, M. López de Prado & M. O'Hara); reliability-bin (isotonic-style) calibration is standard forecasting practice.
Limitations & disclaimer
"Absorption" is a volume proxy — base data has no true tick order flow, so the buy/sell split is estimated from bar moves, not measured. Confidence is context, not a promise of profit. The self-test is descriptive of past behaviour on the loaded symbol (fixed barriers, no costs or slippage) — a study aid, not a backtest and not a guarantee. A measured edge is what flips did historically here, not a forecast.
This script is for research and education only. It is not financial advice, not a recommendation to buy or sell, and not a guarantee of any outcome. Trading carries risk of loss; your decisions are your own. Test on your own data and use independent risk management before relying on it. Indicador
Hidden Liquidity Profile [Alpha Extract]A sophisticated liquidity-mapping and support/resistance profiling framework that analyzes historical candle structure, volume, wick behaviour, and price distribution to identify hidden supply and demand zones across the chart. Hidden Liquidity Profile is designed to reveal where meaningful liquidity may be concentrated by separating sell-side and buy-side pressure into price bins, then projecting those zones forward as heat boxes, horizon lines, key price tags, and a real-time support/resistance dashboard.
Rather than relying on simple pivot highs and lows, the system evaluates how volume interacted with candle ranges, upper wicks, lower wicks, candle bodies, and recency weighting. This creates a dynamic liquidity profile that highlights where price may encounter resistance, support, absorption, or reaction zones.
🔶 Hidden Liquidity Profiling Engine
Builds separate supply and demand profiles across the selected lookback range. The system divides price into configurable bins, then distributes liquidity strength into those bins based on volume, candle range, wick size, body size, and age decay.
energy = vol * rng * decay
sellStrength = energy * (upWick * wickWeight + body * bodyWeight * sellBias)
buyStrength = energy * (dnWick * wickWeight + body * bodyWeight * buyBias)
This allows the indicator to estimate where sell liquidity and buy liquidity are most likely concentrated rather than only marking obvious visible highs and lows.
🔶 Supply & Demand Separation
The profile separates upper-wick and lower-wick pressure into two distinct liquidity maps.
Upper wick activity contributes to the supply profile, helping identify areas where sellers may have previously absorbed price movement. Lower wick activity contributes to the demand profile, helping identify zones where buyers may have previously defended price.
This separation gives traders a clearer view of whether nearby levels are more likely to behave as resistance, support, or balanced liquidity.
🔶 Age-Weighted Liquidity Decay
Applies a recency decay model so newer candles have stronger influence than older candles. This keeps the profile focused on liquidity that is more relevant to the current market environment while still preserving broader historical context.
The Age Decay Power setting controls how aggressively older liquidity fades. Higher values emphasize recent price action more strongly, while lower values retain more historical structure.
🔶 Price Bin Distribution System
Divides the analyzed price range into configurable price bins and assigns liquidity strength into each level. The Price Bins setting controls the resolution of the profile.
More bins create a finer, more detailed liquidity map. Fewer bins create a smoother, broader view of major supply and demand areas.
🔶 Distribution Radius Smoothing
Uses a configurable distribution radius to spread liquidity strength around nearby bins. This prevents the profile from becoming too fragmented and helps form smoother liquidity clusters.
This is especially useful on volatile assets where important liquidity zones often form across small ranges rather than at one exact tick.
🔶 Liquidity Heat Box Visualization
Displays supply and demand as horizontal heat boxes projected to the right side of the chart.
Supply liquidity is shown on the sell side using the selected sell color, while demand liquidity is shown on the buy side using the selected buy color. Wider and brighter boxes represent stronger normalized liquidity at that price level.
This creates a visual depth-style map that helps traders quickly identify where meaningful liquidity may be stacked above and below current price.
🔶 Forward Horizon Lines
Projects stronger liquidity levels forward using horizontal lines. These lines act as future reference zones where price may react, pause, reject, or accelerate through.
The Line Trigger setting controls how strong a liquidity level must be before it is projected. The Line Width Scale setting adjusts how visually dominant stronger levels appear.
🔶 Key Level Detection Framework
Identifies the strongest supply and demand levels from the profile and labels them directly on the chart.
The system can prioritize local peaks, helping avoid overcrowding and ensuring that selected levels represent distinct liquidity clusters rather than multiple nearby bins from the same zone.
This scoring model favors levels with strong dominant liquidity while still accounting for total combined activity.
🔶 Supply HVN & Demand HVN Labels
Marks high-volume liquidity nodes as Supply HVN or Demand HVN depending on which side of the profile dominates at that price.
Each label includes the level type, normalized strength percentage, and exact price. This allows traders to quickly identify the most important liquidity levels without manually reading the full heat map.
🔶 Nearest Support & Resistance Logic
Calculates the most relevant resistance above price and support below price using both liquidity strength and distance from current price.
Levels closer to current price receive more practical importance, while still needing enough liquidity strength to qualify. This helps the dashboard focus on actionable nearby zones instead of simply displaying the strongest level anywhere in the lookback range.
🔶 Aura Point Of Control
Identifies the strongest combined liquidity level across the profile. This Aura POC represents the price zone with the highest combined supply and demand activity.
The POC can act as a major reference point for balance, rotation, acceptance, rejection, or future retests.
🔶 Liquidity Pressure Balance
Compares total normalized demand against total normalized supply to estimate the broader pressure bias across the analyzed range.
When demand is meaningfully stronger, the dashboard shows a demand bias. When supply dominates, it shows a supply bias. When the two sides are close, the market is classified as balanced.
🔶 Real-Time S/R Dashboard
Includes a compact dashboard showing the most important liquidity information directly on the chart:
• Nearest resistance level
• Nearest support level
• Aura POC
• Supply, demand, or balanced pressure
• Active liquidity level count
• Current ticker reference
This gives traders a quick summary of where the strongest nearby reaction zones are and whether the broader liquidity profile is tilted toward supply or demand.
🔶 Customizable Visual Controls
Provides flexible display controls for heat boxes, horizon lines, key level tags, dotted key level lines, and the dashboard.
Traders can adjust the number of analyzed bars, price bin resolution, liquidity smoothing, projection distance, box width, line width, and trigger thresholds to match different assets and timeframes.
🔶 Clean Overlay Design
The full liquidity map is displayed directly on price without requiring a separate oscillator pane. Heat boxes appear to the right of the chart, while key levels and labels extend across the active lookback area.
This keeps the chart readable while still providing a detailed view of hidden supply and demand structure.
🔶 Why Choose Hidden Liquidity Profile ?
Hidden Liquidity Profile provides a more advanced way to identify potential support, resistance, and liquidity reaction zones by analyzing volume-weighted candle structure across the full price range. Instead of marking only visible swing highs and lows, it evaluates where supply and demand pressure may be concentrated based on wick behaviour, candle body participation, volume energy, and recency-weighted price distribution.
The heat boxes reveal liquidity density, the horizon lines project important levels forward, the HVN labels highlight the strongest zones, and the dashboard summarizes nearest support, resistance, POC, and pressure bias in real time.
Perfect for liquidity traders, support/resistance traders, intraday traders, swing traders, and market structure analysts who want a cleaner way to visualize hidden supply and demand zones directly on the chart. Indicador
Volume Profile - AccurateCore Architecture
1. Lower-Timeframe Precision Engine Traditional volume profiles on TradingView can be inaccurate because they guess the volume distribution within a daily candle. This script actually pulls raw data from a lower Source TF (default 5-minute) using request.security_lower_tf and mathematically reconstructs the exact volume traded at every single price tick for the entire day.
2. The Histogram (The Profile itself) It divides the entire price range of the period into a set number of horizontal rows (default 24). It then sorts the lower timeframe volume into these rows, painting a histogram (horizontal bars) on the side of the chart.
Key Trading Features
1. Point of Control (POC) The script mathematically isolates the single row with the absolute highest traded volume for the period.
Action: It projects a solid red line across the chart at this exact price level. The POC acts as the ultimate "fair value" price where buyers and sellers agreed the most, making it a massive magnet for future price action and a strong support/resistance level.
2. Value Area (VA) It calculates the core range where the majority of the trading took place (default is 68% of all volume, representing one standard deviation).
Action: It plots the Value Area High (VAH) and Value Area Low (VAL) as blue lines, and dynamically fills the background between them. Trading outside the Value Area represents an imbalance, while trading inside it represents balance.
3. Advanced Node Detection (HVN & LVN) This is where the script shines. It doesn't just plot the profile; it uses an algorithm to scan the shape of the profile and identify specific structural anomalies:
HVN (High Volume Nodes): Peaks in the profile (other than the POC). The script automatically draws red dashed lines and boxes at these levels. They act as localized support/resistance ledges.
LVN (Low Volume Nodes): Valleys or "gaps" in the profile where price moved so fast that almost zero volume was traded.
LVN Areas: The script goes a step further and intelligently groups adjacent LVNs together to create an "LVN Area" box (default Lime Green). Because there is no historical volume here to stop the price, if price enters an LVN Area, it will usually slice right through it like a hot knife
through butter.
Visual Control
It uses Pine Script's array-based object management (array, array) to dynamically clean up and redraw the profile flawlessly on every tick. You have full control in the settings over where the profile draws (Left/Right), its width, the color of the Value area vs outside the Value area, and toggles for every single specific node. Indicador
Adaptive Volumetric Reversion Channel Fade ValidatorAdaptive Volumetric Reversion Channel — Fade Validator (AVRC)
What it is
AVRC is an anchored, volume-weighted regression channel that frames mean-reversion ("fade") setups and then gates, scores and validates them — so you can see whether fading stretched price actually has an edge on your symbol and timeframe instead of taking it on faith. It is a study / analysis framework, not a strategy and not a signal service.
Why these components are combined (the mashup rationale)
Fading an extreme asks three different questions, and no single classic tool answers all three. AVRC coordinates several non-redundant lenses on one shared geometry (an anchored regression channel) and one shared volatility unit (residual σ), so each lens can check the others rather than echoing it:
WHERE is price stretched? A volume-weighted regression centerline with residual-σ bands is drawn against a slower macro trend-relative volume map — volume binned by σ-distance from a longer regression line. Whether the tactical band sits in a thin (fast-traversed) or thick (heavily-traded) macro node tells you if a fade is likely clean or absorbed. This cross-read is the connective tissue between the two layers.
Is a reversion ACTUALLY firing? Independent "tells" at the band — a close-back rejection, a band-confluent momentum divergence, an equal-high/low liquidity sweep, and the macro-density read. Because these tells are correlated, their agreement is shrunk by a design-effect correction so echoes can't masquerade as independent confirmation.
Is the market in a reverting STATE? A regime gate (variance-ratio test + a reversion-trust correlation) only passes fades when price increments offset rather than compound. An entry-time ride-risk score (macro-trend alignment, the two-centerline spread, an already-walking band, momentum, mean-reversion half-life, and multi-timeframe trend consensus) flags fades likely to be "walked" rather than reverted.
The components share one geometry and one volatility unit, and each can veto the others. The goal is to suppress low-quality fades more than to generate them.
How the validation layer works (what makes this more than a drawing)
Every fade is logged and, a fixed horizon later, resolved: its forward return is measured in ATR units and tabulated Gate ON vs Gate OFF — follow-through %, a Wilson 95% interval, whipsaw %, and mean R per fade. Outcomes are additionally split Reverted vs Rode, by macro node (thin/thick), and by ride-risk (low/high at the running median). The panel's Edge line synthesizes this into a single read: is Gate ON's follow-through interval clearing the ungated baseline with positive mean R and enough samples? Per-fade rows also export to the Data Window for your own analysis. Every filter has to earn its place against the ungated baseline.
How to use it
Set the Price source (top of settings). Defaults are tuned for an intraday index future; the source is user-selectable so the framework runs on any symbol or market. Volume-based parts (heatmap, profile, POC) need a real volume feed.
Read the panel top-down: Now (live setup) → State (regime + spread + compression) → the A/B scoreboard (Gate OFF, Gate ON, Revert, Ride) → Edge verdict.
A fade arms when price tags the outer band and at least one tell prints, then passes only if the regime (and optional ride-risk) gate agrees. Target is the centerline or the nearest untested POC.
If Gate ON does not beat Gate OFF on follow-through and mean R with non-overlapping intervals and enough samples, the edge isn't there on this symbol/timeframe — change them, don't force it. The signal is clearest on higher intraday timeframes; 1-minute is mostly noise.
What is original here
The original work is the coordination: a shared-σ, timeframe-adaptive regression channel used as a reversion frame; a trend-relative volume map cross-read against the band; decorrelated tells fused by a design-effect shrink; a statistical regime gate; an entry-time ride-risk score; and a built-in A/B + forward-return validation harness — combined so each lens can veto the others and the tool reports its own hit rate. It is not a re-skin of any single indicator.
Concept credits (techniques are standard; this implementation is original)
Volume-weighted least-squares & polynomial regression; residual-σ channels; anchored VWAP (all standard); Volume Profile / Value Area / Point of Control — Market Profile (Steidlmayer / CBOT); Variance-Ratio test — Lo & MacKinlay (1988); design effect / effective sample size — Kish (1965); proportion confidence interval — Wilson (1927); mean-reversion half-life — Ornstein–Uhlenbeck process; ATR, RSI, Parabolic SAR — Wilder; Stochastic — Lane; Supertrend (classic, MTF context). Builds on established open-source regression-channel and anchored-VWAP techniques.
Settings (all defaults are on; tuned for an intraday index future)
Data/Source · Volatility unit · Macro volume heatmap · Tactical channel & bands · Interrelation & band-walk · Ride-risk filter · Density cross-read · Reversion tells · Regime gate · POC targets · Fade signal · Validation & export · Dashboard & theme (auto light/dark) · MTF trend context. The two signal-suppression gates (walk-gate, ride-gate) ship off so the indicator shows its signals and lets the validation panel tell you whether enabling them helps.
Disclaimer
For research and education only. NOT financial advice, NOT a recommendation, and NOT a guarantee of future results. All statistics shown are in-sample on loaded history, close-to-close at the horizon, without costs or slippage — a study aid, not a backtest. Mean reversion fails in trends and during regime breaks. Do your own research and manage your own risk. Indicador
Anchored VWAP Reversion ChannelAnchored VWAP Reversion Channel — Regime-Gated Fade Framework
## What this script does
This is an **analytical study** that frames mean-reversion ("fade") setups around an **anchored, volume-weighted regression channel**, then **gates** those setups by a statistical market-state test and **scores** them against their own forward outcomes. It does not place orders and it is not a signal service — its purpose is to let you see, on your own instrument and timeframe, whether fading a stretched move actually has an edge, instead of assuming it does.
It plots one channel (a centre line plus inner/outer residual-σ bands), marks fade setups at the outer band, draws supporting context (volume-profile POC / value area, untested prior-session POCs, momentum divergences, liquidity sweeps, and multi-timeframe trend lines), and reports a compact validation panel.
## Why these components are combined (mashup rationale)
Fading an extreme is really three separate questions, and no single classic indicator answers all three. Stacking look-alike indicators just echoes one input, so this tool deliberately combines **three non-redundant lenses and makes them check each other**:
1. **WHERE is price stretched?** — A **volume-weighted polynomial regression** anchored at the most recent swing pivot, with **residual-σ bands**. Because the curve tilts with the active leg, an outer-band tag stays meaningful even inside a trend, where a flat cumulative VWAP would not. A **volume profile** anchored to the *same* window supplies POC and value area, and prior-session POCs that have never since been traded through become **reversion targets**.
2. **Is a reversion actually firing here?** — Three orthogonal **tells** evaluated only at the band: a **close-back rejection**, a **band-confluent momentum divergence**, and an **equal-high/low liquidity sweep** (stop-run). Crucially, all three are derived from the same stretch, so their agreement is shrunk by a **design-effect correction** (effective-sample-size): three correlated echoes are not allowed to masquerade as three independent confirmations.
3. **Is the market in a reverting state at all?** — A **regime gate** combining a **variance-ratio test** and a **reversion-trust correlation** only lets a fade through when recent increments are offsetting (mean-reverting) rather than compounding (trending).
The pieces are not bolted together side by side: they share **one geometry** (the anchored channel) and **one volatility unit** (residual σ / ATR), and each can veto the others. A band tag with no tell does nothing; a tell with no reverting regime does nothing. The design goal is to **suppress** low-quality fades — into a trend, mid-range, or backed by a single echoed tell — more than to generate them.
## The honesty layer (what makes this more than a drawing)
Every fade that fires is logged and, a fixed horizon later, **resolved**: its forward return is measured in ATR units and tabulated **with the regime gate ON versus OFF**, reporting follow-through %, whipsaw %, a Wilson 95% confidence interval, and the **mean return per fade**. A per-fade series also exports to the Data Window so you can study the full return distribution offline. The gate has to **beat its own ungated baseline** to justify itself — the framework is built to be tested, not trusted blindly.
## How to use it
1. Set the **Price source** (group 01). It works on any symbol and any market; volume-based parts need a real volume feed.
2. A fade **arms** when price tags the outer band **and** at least one tell prints, then **passes** only if the regime gate reports a reverting state. Solid triangles are gated fades; the target is the centre line or the nearest untested POC.
3. Read the panel top-down: does **Gate ON** beat **Gate OFF** on both follow-through and mean R, with non-overlapping intervals and a reasonable sample size? If not, the edge is not present on this symbol/timeframe — change them rather than forcing the trade.
4. The signal lives on **higher intraday timeframes**; one-minute data is mostly noise.
## Defaults
Shipped tuned for **NSE:NIFTY** index futures on intraday timeframes (sources, pivot lengths, value-area %, and the Tuesday-style weekly session context reflect that instrument). Every value is exposed as an input — change the **Price source** and the relevant lengths to run the framework on any other instrument or market.
## What is original
The original work is the **coordination**, not any single formula: an anchored polynomial-regression channel used as a reversion frame, three decorrelated band tells fused by a design-effect shrink, a statistical regime gate, and a built-in A/B + forward-return validation harness — combined so each lens can veto the others and the whole thing reports its own hit rate. It is not a re-skin of one indicator.
## Concept credits (techniques are standard; this implementation is original)
Anchored VWAP (standard); volume-weighted least-squares / polynomial regression (standard); residual-σ channel (standard); Volume Profile, Value Area and POC — Market Profile, Steidlmayer / CBOT; Variance-Ratio test — Lo & MacKinlay (1988); design effect / effective sample size — Kish (1965); proportion confidence interval — Wilson (1927); ATR trailing stop / Supertrend (classic, used for the multi-timeframe context lines); RSI — Wilder; Stochastic — Lane.
## Disclaimer
For research and education only. This is an analytical study, **not** financial advice, **not** a recommendation, and **not** a guarantee of future results. All statistics shown are **in-sample** on loaded history, close-to-close, without costs or slippage — a study aid, not a backtest. Mean reversion fails in trends and through regime breaks. Do your own research and manage your own risk.
Indicador
Liquidity Map & Execution Cost# Liquidity Map & Execution Cost
## What this script does
LMX answers three execution questions most indicators ignore: **how expensive is it to get in and out right now, how hard would it be to move size, and where on the chart will price struggle versus travel freely.** It reads only the chart's own price and volume — no symbol is hardcoded, so it runs on any asset and any market (equities, futures, FX, crypto, indices) — and turns the answers into a plain-language trade check: liquidity state, suggested position size, order type, estimated slippage, and a colour-coded map of support, resistance, walls and open gaps.
## Why these components are combined (mashup justification)
This is not several indicators stacked together — it is one liquidity model whose parts each answer a question the others cannot, and they are designed to be read together. Removing any one leaves a specific blind spot:
1. **Cost to cross — effective spread.** Estimated with the EDGE estimator (Ardia, Guidotti & Kroencke 2024) from open/high/low/close, cross-checked against Abdi-Ranaldo (2017) and Corwin-Schultz (2012). This tells you the round-trip cost of entering, which spread-blind tools cannot show. Alone, it says nothing about moving size or about levels.
2. **Cost to move size — price impact.** The Amihud (2002) illiquidity ratio with a high-low refinement, plus a rolling Kyle (1985) lambda computed as a true regression slope. This tells you how far your own order would push price — the question that matters for sizing, and one a spread estimate cannot answer.
3. **Direction of pressure — order imbalance.** A close-location signed-volume imbalance and its persistence. This tells you which side is leaning now, adding direction that the cost measures lack.
4. **The spatial map — volume at price.** A time-decay-weighted, range-distributed volume profile that yields the Point of Control and Value Area (standard 70% method), rendered as directional zones: green support below price, red resistance above, solid = a wall price struggles at, faint = an open gap price slides through. This converts the abstract cost/impact numbers into *locations* on the chart.
5. **Anchored VWAP — fair value.** A volume-weighted average anchored to your chosen reference (last major swing by default; or session/week/month open, or the highest-volume bar), drawn as a trend-coloured line. It is the dynamic counterpart to the static profile: where the average participant is positioned, and whether price is rich or cheap versus that.
Together they form one decision: the spread and impact set the **cost and size**, the imbalance and VWAP set the **direction and fair value**, and the map sets the **location** — so the output is "trade full size with market orders, buyers in control, room to run up to the gap above," not five separate readings.
## How a reading is produced
Each estimator is normalised to a percentile of its own history so thresholds adapt to every symbol and timeframe. The inverted spread, inverted impact and depth combine into a 0–100 **Liquidity Score**, classified as Deep / Normal / Thin / Stressed (a sudden impact spike forces Stressed). The score drives the suggested size multiplier, the order-type advice and the slippage estimate. The map is rebuilt on the last bar from the volume-at-price profile.
## How to use it
- Apply to any symbol. Set the price source and, if you trade very low intraday timeframes, optionally fix the calc timeframe (e.g. Daily) so the spread estimators stay stable. On symbols without real volume the volume modules disable automatically and the score leans on the spread estimators (the panel shows "price-only").
- **Simple mode (default)** gives plain-language guidance: Liquidity, Trade cost, Pressure, Position size, Orders, Watch-out, Fair value, and a one-line verdict. **Pro mode** exposes the full readout (spread in bps, Amihud and Kyle percentiles, depth, imbalance, flow persistence, value-area levels).
- On the chart: trade toward green support, expect resistance at red, size down where the map is thin (price moves fast there), and read the trend-coloured fair-value line for rich/cheap context.
- Alerts: liquidity-state change and sudden liquidity withdrawal.
## Originality
The combination is the original contribution: a single overlay that fuses low-frequency **spread**, **impact** and **imbalance** estimators with a **time-decay, range-distributed volume profile** and an anchored fair-value line, then translates all of it into sizing/order/slippage decisions in plain language. The building blocks are public-domain methods (EDGE, Abdi-Ranaldo, Corwin-Schultz, Amihud, Kyle, volume-profile Value Area, anchored VWAP), each used for the specific job described above and cited in the script header.
## Limitations (please read)
- These are **low-frequency estimators** of quantities normally measured from quote/tick data. They approximate — they do not measure — the true spread, depth, or dealer book.
- Volume-based modules require a real volume feed; they disable on symbols without one.
- Spread estimators were validated on daily-type bars; on very fast intraday timeframes they are noisier — use the calc-timeframe option if needed.
- The on-panel statistics are computed on the loaded chart history.
- This is an analysis tool, **not financial advice.** Test before use and trade at your own risk.
Indicador
Delta by Price (Delta Volume Profile)🔹 Introduction
This indicator, Delta by Price (Delta Volume Profile), takes the familiar concept of a volume profile and replaces raw traded volume with net directional volume (delta) at each price level. Instead of showing how much volume traded at a price, it shows which side was more aggressive at that price — buyers or sellers.
The idea is straightforward: if a price level absorbed significantly more aggressive buying than selling (or vice versa), that level likely represents a meaningful shift in who was in control of the auction at that point in the range.
One thing to be upfront about: true tick-by-tick delta isn't available to Pine scripts. This indicator approximates delta by pulling lower-timeframe bars within each higher-timeframe bar and classifying each LTF bar's volume as buy-side or sell-side based on whether it closed above or below its open. It's a proxy, not a recording of the actual order book — but it's the same proxy nearly all publicly available delta tools use, and it tends to track real aggressor flow reasonably well over meaningful sample sizes.
🔹 The Premise / Background Theory
🔸 Volume tells you "how much," delta tells you "who pushed"
A standard volume profile answers one question: how much volume traded at each price? It's useful for finding high-volume nodes (areas of acceptance) and low-volume nodes (areas of rejection), but it's directionally blind. A price level with 1,000 contracts could be 500 aggressive buys and 500 aggressive sells — pure equilibrium — or it could be 950 buys and 50 sells, meaning that level was overwhelmingly bought into.
Delta separates these two scenarios. A delta profile takes that same volume and splits it by aggressor side, then nets it. The result is a histogram that shows not just where volume concentrated, but which direction the pressure leaned at every price.
🔸 A concrete example
Assume price moves through a range from 5,000 to 5,010 over a session.
At the 5,002 level, three separate visits occur. On the first visit, an LTF bar closes higher than it opened with volume of 200 — classified as buy-side. On the second visit, another bar closes lower than it opened with volume of 150 — sell-side. On the third visit, a bar closes higher with volume of 300 — buy-side.
Net delta at 5,002 = +200 − 150 + 300 = +350.
Total volume at 5,002 = 200 + 150 + 300 = 650.
A standard volume profile would just show "650 contracts traded here." The delta profile shows +350 net buying — meaning roughly 54% more buy-side aggression than sell-side at that exact price. If you saw a level like this near the low of a range, it might suggest buyers stepped in there with conviction, not just that "a lot happened" there.
🔸 Why distribute delta across a bar's range instead of just its close
Each higher-timeframe bar has a high and a low, and the LTF bars that compose it trade across that entire range — not just at the close. This indicator takes each HTF bar's net delta and spreads it proportionally across every price bin the bar's high-to-low range touches.
This is an assumption, not a measurement. In reality, delta within a single bar isn't evenly distributed across its range — more of it likely occurred near where price spent the most time. But without LTF-by-LTF price-level tracking (which would be computationally heavy and hit Pine's lower-timeframe data limits quickly), even distribution across the bar's range is the most defensible simplification available. Wider bars contribute a thinner "smear" of delta per price bin; narrow bars concentrate their delta into fewer bins. Over a large enough sample, this tends to average out reasonably well.
🔹 How It Works
🔸 Profile Range: Session vs. Rolling Lookback
The indicator builds its profile from one of two data windows, selectable in settings.
Session mode mirrors how a session volume profile works — it resets at the start of each new session (defined by the session time input) and accumulates only the bars within that session. This is the natural choice if you want to see, for example, today's regular trading hours delta distribution reset cleanly each day, the same way you'd look at a daily session volume profile.
Rolling Lookback mode instead uses a fixed number of the most recent closed bars (configurable, default 200), regardless of session boundaries. This is useful for a continuously updating view of recent delta structure that isn't tied to calendar sessions — helpful for instruments or sessions that don't fit a clean daily reset (e.g. 24-hour futures markets).
There are limitations here worth noting. Session mode depends on the session time input matching how you actually think about your trading day. If you trade through multiple sessions (e.g. Asian, London, NY) and only select one as your "session," the profile will reset and rebuild only around that window — bars outside it are ignored entirely.
🔸 Number of Price Rows
This setting controls how finely the price range is divided into bins — effectively the "resolution" of the profile. A higher row count gives more granular price-level detail but spreads the available delta across more bins, making each individual bin's bar shorter and potentially noisier. A lower row count aggregates more price action into each bin, producing a smoother, more visually digestible profile but losing some precision about exactly where within a price cluster the delta concentrated.
This is a resolution-versus-noise tradeoff — there's no universally correct setting, and it's worth adjusting based on the instrument's typical range and tick size.
🔸 Extend Direction
The profile can be drawn extending to the right of the current bar (the default, useful when you want the profile visible without obscuring recent price action to the left) or to the left, anchored at the start of the lookback/session window — placing it where the data actually begins, similar to how some volume profile tools anchor to the left edge of the range being measured.
This is purely a visual/layout preference and doesn't change any underlying calculation — it only affects where the horizontal delta bars are drawn relative to price.
🔸 Point of Control (POC)
When enabled, a label marks the price bin with the highest total absolute volume (buy-side + sell-side combined, not net delta) — analogous to the POC on a standard volume profile. This identifies where the most total activity occurred, regardless of which direction it leaned. It's possible — and informative — for the POC bin to have a relatively small net delta despite high total volume, which would indicate that level saw heavy two-sided participation rather than one-sided conviction.
🔸 Custom Lower Timeframe
By default, the indicator automatically selects a lower timeframe for delta calculation based on your chart's timeframe (1-second charts use 1S, intraday charts use 1-minute, daily charts use 5-minute, and anything larger uses 60-minute). You can override this manually.
The tradeoff here is precision versus data availability. A finer LTF gives a more granular delta classification per HTF bar, but request.security_lower_tf() has practical limits on how many LTF bars it can return per HTF bar — on very large lookbacks with a very fine LTF relative to your chart timeframe, you may not get the full intrabar picture for older bars.
🔹 Closing Remarks
A delta-by-price profile doesn't tell you why buyers or sellers were more aggressive at a given level — only that they were, based on a reasonable proxy for aggressor classification. Large net-delta clusters don't guarantee future support or resistance. They're best treated as a layer of context: a way of seeing whether the volume that built a price level was directionally lopsided or balanced, which can complement (not replace) your read of structure, location, and broader order flow.
Used alongside the rest of your framework, it's another lens for asking the same underlying question every footprint-based approach asks: was this level built by conviction, or by indecision? Indicador
Volume Profile Composite, Naked POC & Value-AreaVolume Profile — Composite, Naked POC & Value-Area
==================================================
WHAT IT IS
A volume-at-price profile built for depth and decisions. It measures where trade
actually concentrated across the loaded history, distils that distribution into
the levels traders use — Point of Control (POC), Value Area (VAH/VAL), High and
Low Volume Nodes (HVN/LVN), and untested "naked" prior-session POCs — and then
converts those levels into a plain-language read of where price sits in the
auction (premium, discount, or inside value; balancing or migrating).
It is a study for chart analysis and education. It plots levels and context; it
does not place orders and does not output buy/sell signals.
HOW IT WORKS (ENGINE)
Volume is accumulated bar by bar into a price-keyed map on a fine grid (the
symbol's minimum tick multiplied by a user factor), then re-aggregated to the
chosen number of display rows. Because the engine uses a map rather than a fixed
lookback array, the profile can span every loaded bar instead of only a recent
window, and it is not limited by the historical bar-reference ceiling.
Each bar's volume is distributed across that bar's high-low range over a capped
number of samples, and tagged buy or sell by bar direction, producing a two-tone
histogram and a per-level delta. Where intrabar (lower-timeframe) data is
available, recent history can optionally be refined from it; older bars fall back
to the bar-range method. The Value Area is grown outward from the POC bin until
the chosen percentage of total volume is captured. Prior-day, prior-week and
full-history composite levels reuse the same value-area routine on their own maps.
The heavy redraw runs on bar open/close rather than on every realtime tick, to
keep live charts responsive.
WHY THESE COMPONENTS ARE COMBINED (MASHUP JUSTIFICATION)
This is one volume-profile engine, not a stack of independent indicators. Every
layer is computed FROM THE SAME accumulated volume map, and each one exists to
remove a specific blind spot of the raw histogram. A bare histogram only answers
"where did volume happen"; it cannot tell you whether price is rich or cheap,
which level matters next, or whether the market is balancing or trending. The
combined layers answer those questions, and they work together as follows:
- POC and Value Area transform the raw distribution into a fair-value frame, so
every other reading can be expressed as premium, discount, or inside value.
- HVN and LVN classify each price level produced by that same distribution as
acceptance (a volume shelf where reactions are more likely) or a thin gap
(where price tends to move quickly). This tells you how a level is likely to
behave, which the POC/Value Area alone do not.
- Naked prior-session POCs carry acceptance forward in time: they are POCs from
earlier sessions that price has not yet traded back through, derived from the
same per-session maps, and they act as revisit references.
- Value migration is simply the sequence of those session POCs read as a
direction, turning the profile history into a balancing-versus-trending read.
- The composite overlay keeps the full-history POC and Value Area in view while
you work a shorter, more legible recent window, so context is never lost.
- VWAP, Initial Balance, an expected-move band, and cumulative-volume-delta
divergence are confluence layers. They are optional and each degrades
gracefully if its data is absent. They are included because volume-profile
levels are used in context: VWAP gives the session's volume-weighted mean,
Initial Balance gives the opening reference, the expected-move band frames a
realistic day's range, and CVD-versus-price flags exhaustion. Each one answers
"does independent volume/price information agree with what the profile shows
here?", which is exactly how these levels are traded in practice.
- The Auto-Read is the synthesis step: it does not add new data, it ranks the
levels the engine already produced by distance to price and states the auction
context in words.
In short, the histogram is the raw material and every other element is a
transformation of that same data into a level, a classification, a confluence
check, or a written read. That shared derivation is the reason they belong in a
single script rather than as separate indicators.
WHAT IT PLOTS
- Buy/sell two-tone histogram, drawn in the clear space to the right of price so
candles stay visible.
- POC, Value Area (VAH/VAL, adjustable percentage), HVN/LVN nodes.
- Naked daily POCs, with a creation-time check that skips levels already traded
through and an optional age-out so the list stays meaningful.
- Polarity flip: a prior-day Value Area edge that price closes decisively beyond
and holds changes role (broken VAH becomes support; broken VAL becomes
resistance) and feeds the support/resistance read.
- Prior-day and prior-week POC/Value Area, full-history composite overlay,
developing POC.
- VWAP with standard-deviation bands, Initial Balance, expected-move band,
cumulative-volume-delta divergence, buy/sell imbalance shelves, poor highs/lows,
single-print gaps.
- Higher-timeframe POC bias (a light proxy — see Limitations).
- Auto-Read dashboard (full or compact), one-line headline, and an on-chart
identity strip showing the script name, symbol and timeframe.
HOW TO USE
1. Choose a scope: Rolling (default), Composite (all history), From date, or
Fixed range. The composite overlay keeps the big-picture levels visible.
2. Read location first from the headline or dashboard: inside value, premium, or
discount, and whether value is migrating up, down, or flat.
3. Treat the levels as a map, not a signal. POC acts as a mean-revert magnet;
Value Area edges are balance boundaries; HVN suggests stalls; LVN suggests
fast moves; a naked POC is a revisit reference.
4. Look for confluence with VWAP, Initial Balance, and prior-session levels, and
treat CVD divergence as a caution flag.
5. Detail presets (Simple / Standard / Pro) gate how much is shown. A compact
dashboard toggle trims the table to the key decision fields.
WHAT MAKES IT ORIGINAL
- Full-history depth via the price-keyed map, beyond a fixed lookback window.
- A built-in, past-only calibration of the profile's own claims: it logs
value-edge and POC-stretch reversion events against the prior-day Value Area
(which exists on every bar, so the measurement backfills over history), waits a
fixed horizon, and reports the realised hit-rate with a 95% confidence
interval. This is descriptive of past behaviour on the specific instrument; it
is explicitly not a backtest and not a forecast.
- A decision-ordered, plain-language Auto-Read derived entirely from the engine's
own levels.
DATA SOURCE AND ANY-MARKET USE
The volume source is user-selectable (Settings > Data source), so the profile can
be built from the symbol's own volume or from any other series your feed
provides. For symbols that report no native volume (some cash indices and FX
feeds), an optional "borrow volume" field lets you supply a volume-bearing proxy
for the same instrument; it only activates when the charted symbol genuinely has
no volume. The volatility-index symbol for the expected-move band is also
user-set and falls back to a daily-ATR band when left blank. An optional
asset-class auto-tune adapts the grid and node percentiles to the detected class.
All of these are blank or off by default, so nothing is tied to one market.
CALIBRATION NOTE
The calibration panel is descriptive only. It reports how often, in the past, on
the current symbol, price followed through after the logged events. Small samples
are flagged. It is not a probability of future results.
LIMITATIONS (HONEST)
- This uses a BAR-RANGE volume distribution (optionally refined by lower-timeframe
bars). It approximates where volume traded within each bar. It is NOT exchange
price-by-price volume, tick data, or order-flow/footprint, and it cannot see
bid/ask.
- It needs real volume. Cash indices often report none — use the matching future
or continuous contract, or the borrow-volume field.
- The higher-timeframe POC is a light single-bar proxy (the price of the
highest-volume higher-timeframe bar over a lookback), not a full higher-
timeframe profile.
- All readings are probabilistic context, not predictions.
DISCLAIMER
This script is a study/indicator for chart analysis and education only. It is NOT
a strategy, NOT a recommendation, and NOT financial advice. It places no orders
and guarantees no result. Trading involves substantial risk; a level's past
behaviour does not assure future behaviour. Do your own research and manage your
own risk.
Indicador
Anchored VWAP ChannelAnchored VWAP Channel — Regime, Confluence & Reversals
What it is
This is a single overlay that builds a complete read of price around one Anchored VWAP. Instead of just drawing a VWAP line, it wraps the VWAP in a volatility channel and then layers the context a discretionary trader normally checks by eye — where price sits versus fair value, whether the move is trending or stretched, where high-volume and Fibonacci levels line up, and where the edges are getting rejected. Everything is derived from the same anchor and measured in the same volatility unit (one standard deviation, σ), so the pieces describe one structure rather than competing with each other.
It runs on any asset class and any timeframe. On instruments that carry real volume (stocks, futures, crypto, etc.) the VWAP, the channel, and the volume profile are fully volume-weighted; on feeds without real volume it falls back gracefully and flags the change in the table (see "Notes and limitations").
Why these components are combined (and how they work together)
This is intentionally a mashup, and the parts are chosen because they answer different questions about the same reference point:
• The Anchored VWAP is the fair-value anchor — the volume-weighted average price since a chosen pivot.
• The channel turns dispersion around that anchor into a measurable unit: the bands are the AVWAP ± k·σ, where σ is the volume-weighted standard deviation of price about the VWAP. This converts "how far is price from fair value" into a number (σ-distance) every other module can reuse.
• The regime read uses that σ-distance together with the VWAP slope and the band behaviour to label continuation vs reversal — so the same channel that draws the bands also tells you whether to trust a band tag or fade it.
• The volume profile (Point of Control + Value Area) is computed over the same anchored window, so the high-volume price and the value range are measured on exactly the data the VWAP is built from — not an arbitrary separate lookback.
• The Fibonacci grid is drawn on the active swing leg and is only emphasised where a level coincides with the VWAP, a band, or the POC. The channel and profile are what make a fib level meaningful here; on their own the fib levels would be just lines.
• The reversal signals fire on outer-band rejections, and the optional confluence filter suppresses them while the regime is strongly trending (when band tags tend to continue) — i.e. one module gates another.
In short: the channel produces a σ-distance, and the regime, profile, fib confluence, reversal logic, divergence and squeeze modules all consume that single shared measurement. That shared plumbing is the reason these are bundled into one script instead of run as six separate indicators.
What it plots
• Anchored VWAP centerline with a glow halo, colored by slope direction.
• Channel bands at ±1σ and ±2σ. The fill can be a "reversion heat" gradient (denser toward the outer band, red above the VWAP, green below) or a neutral glow, or off.
• Volume profile drawn as a translucent Value Area box (VAL→VAH) with a distinct POC line — kept visually and positionally separate from the fib lines so the two are never confused.
• Fibonacci grid (active-leg retracement, plus optional swing-to-swing), with confluence levels marked by a star and a brighter tone.
• Signals: trend-shift triangles on VWAP reclaim/loss; solid reversal labels on band rejections; diamonds and connecting lines for σ-distance divergence; a marker on volatility-squeeze release.
• Status table (single panel): regime, bias, σ-distance, AVWAP, POC, Value Area, squeeze state, divergence, a reversion stop/target/RR template, a data-health row, multi-timeframe regime agreement, and a built-in legend.
• Optional forward projection cone and an optional self-calibration panel that scores how past signals resolved.
Anchor modes
Rolling (fixed bar window), Swing Low, Swing High, or Dual (auto — anchors to the more recent significant pivot). Pivot detection uses bar-count lookbacks (8/13/21/34/55/89), so the entire tool self-scales to any timeframe.
How to use it
1. Read the table first: regime + σ-distance tell you whether price is trending or stretched, and how far from fair value it is.
2. Use the bands as context — near the centerline is fair value; the ±2σ edge is where reversion risk is highest (and the heat fill shades it).
3. Treat reversal labels as fade-the-stretch signals, strongest when the regime is not trending and when a divergence diamond agrees.
4. Use trend-shift triangles (VWAP reclaim/loss) for continuation context.
5. Use fib-confluence stars and the Value Area box / POC as the levels most likely to react.
6. Check multi-timeframe agreement in the table before acting.
7. Optionally turn on the calibration panel to see, on your own symbol and timeframe, how often each signal type has historically followed through.
What makes it original
• A single shared σ framework: bands, regime, divergence, reversals and risk template all read from one volume-weighted standard-deviation measurement around one anchor, rather than bolting unrelated indicators together.
• Reversion-heat channel fill that encodes reversion risk as color density.
• Confluence-filtered reversals — band rejections gated by regime/divergence.
• Volume profile rendered as a separated zone so it never blends into the fib levels.
• A transparent self-calibration panel that scores the script's own signals against a follow-through threshold (descriptive, not a backtest).
Key settings
• Calculation Source — works on any asset/market; default hlc3, switchable to close, hl2, ohlc4, etc.
• Anchor mode and pivot/rolling length.
• Inner/outer band multipliers and fill style.
• Signal sensitivity, session-open filter, reversal-confirmation strictness.
• Table position / text size / legend, and toggles for every module.
Notes and limitations
• Signals are evaluated on closed bars; the σ-distance divergence confirms a few bars after a pivot by design, so it prints late (this is normal for pivot-based divergence and is not repainting of confirmed history).
• Last-bar drawings (profile, fib, projection cone) are redrawn on each new bar and will shift forward — that is expected.
• Asset classes / volume: runs on any market and any timeframe. On instruments that carry real volume (stocks, futures, crypto, etc.) the Anchored VWAP, the volume-weighted σ channel, and the Volume Profile (POC / Value Area) are all fully volume-weighted as intended. On feeds with no real volume (e.g. spot forex, some indices / CFDs) the script still works but degrades gracefully: the VWAP becomes a simple anchored mean, the channel uses an unweighted standard deviation, and the profile becomes a time-at-price distribution. The Data row in the table flags this state as "no-vol / DEGRADED" so you always know which mode you are in.
• The multi-timeframe dashboard uses higher-timeframe requests; you can turn it off to reduce load.
• This is an analysis/visualization tool, not a strategy — it does not place orders and is not optimized or backtested for entries/exits.
Disclaimer
This script is provided for educational and informational purposes only and is not financial, investment, or trading advice. It does not predict future prices. Markets carry risk and you can lose money. Past behaviour of any signal (including the calibration panel) does not guarantee future results. Always do your own research and consider consulting a licensed financial professional before trading. You are solely responsible for your decisions and their outcomes.
Indicador
Ribbon Conviction SystemRibbon Conviction System — Trend, Flow, Value and Adaptive Stop
Overview
This is a single decision-support system for intraday traders. It answers three questions on one chart: which way is the trend, how much conviction is behind the current move, and where a logical trailing stop sits. A moving-average ribbon defines direction, a conviction score from 0 to 100% grades every signal, and an adaptive volatility stop marks risk. The components are designed to work together as one filtered signal, not as a loose collection of separate indicators.
Why these components are combined
A moving-average crossover on its own fires constantly in sideways markets and gives no sense of whether a cross is meaningful. Each part added here exists to fix a specific weakness of the part before it, so the result is one filtered signal rather than several indicators stacked on a chart.
Ribbon (direction). Five Fibonacci-length averages — 8, 13, 21, 34, 55 — using a mix of Hull, EMA and Kaufman Adaptive Moving Average (KAMA). The KAMA anchors deliberately flatten in choppy conditions, so the ribbon stops giving direction when there is no trend. Weakness it leaves open: a crossover can still fire on a weak, low-conviction move.
Conviction score (filter). Instead of taking every crossover, each signal is graded 0–100% by blending four independent readings of the same bar, chosen because they measure different things rather than repeat each other:
Buy/sell flow — net buying versus selling pressure, inferred from lower-timeframe price-and-volume behaviour.
Effort vs move — how far price travelled for the volume spent; absorption and churn are penalised.
Trend quality — Kaufman Efficiency Ratio: directional travel divided by total path, separating trend from noise.
Price location — is price on the right side of value? Blends session VWAP slope, a swing-anchored VWAP, the session volume-profile value area (VAH/VAL/POC), and the prior session's VWAP and unfilled POC.
A flow-toxicity proxy (VPIN-style) then lowers the score when flow looks one-sided and unstable. Weakness it leaves open: all four readings come from the chart timeframe, so they can agree for the wrong reason.
Higher-timeframe agreement (independent confirmation). The same volatility-stop direction is computed on 3×, 5× and 15× the chart timeframe and folded in as a multiplier, not a fifth blended input. It is kept separate precisely because it is the one genuinely independent check on the chart-timeframe score: full agreement raises conviction, disagreement lowers it.
Adaptive volatility stop (risk). A Chande-style volatility stop whose ATR period and multiplier adapt through the Efficiency Ratio, so the stop tightens in clean trends and widens in chop. This turns the tool from "where is the signal" into "where is my risk if I take it."
How they work together
Direction (ribbon) decides the side. The conviction score decides whether a crossover on that side is worth showing and how strongly. Higher-timeframe agreement scales that conviction up or down. The adaptive stop shows the exit reference. Every signal is the product of all four stages working in sequence.
What it plots
The five-average ribbon with shaded bands; the 55 line is the bold trend-reference band.
Signal badges at qualifying crossovers, labelled with the band crossed and the conviction percent (for example "21 65%").
Optional value references: session VWAP, swing-anchored VWAP with bands, volume-profile VAH/VAL/POC, and the prior session's VWAP and POC.
The adaptive volatility stop as a step line with a live distance label.
A compact dashboard summarising trend, conviction and each component, higher-timeframe agreement, the stop, and the data mode.
A small higher-timeframe agreement ribbon.
How to use
Add it to an intraday chart. The defaults suit index futures, but direction works on any symbol.
Spot vs futures: many spot indices publish no real volume, which the flow, value-area and toxicity parts depend on. Under "Data source" the script auto-detects this and switches the volume-based parts to a time-at-price method so everything still works; you can also set the mode manually. The dashboard "Data" row shows which mode is active.
Trade in the ribbon's direction. Prefer signals with a higher conviction percent and higher-timeframe agreement, and treat low-conviction crosses as noise. Use "Hide signals weaker than" to suppress them.
Use the adaptive stop as a trailing-risk reference, sized to your own plan.
The "Look & size" group controls signal size, dashboard size and position, a "Minimal" preset (ribbon + signals + stop only), and band lightness.
Originality
The individual techniques — adaptive moving averages, the Efficiency Ratio, effort-versus-result, VWAP, volume profile and volatility stops — are publicly documented. What is original here is the integration: a single conviction score that fuses chart-timeframe flow, effort, efficiency and value, damps it by flow toxicity, and scales it by independent higher-timeframe agreement, then gates an adaptive-stop-aware signal on that score. The components were selected so each covers a distinct weakness, and redundant filters were deliberately left out to keep one clear signal.
Credits
Perry Kaufman — Adaptive Moving Average and Efficiency Ratio. Tushar Chande — Volatility Stop concept. The effort-versus-result component is an original, compact reimplementation inspired by the publicly described effort-versus-result method from the volume-spread-analysis lineage.
Disclaimer
This script is for education and information only. It is not financial, investment or trading advice and does not guarantee any outcome. Signals describe current conditions; they do not predict the future. Markets carry substantial risk of loss. Volume-based readings depend on the data feed and are unreliable on instruments without real volume. Always test on your own market and timeframe, and manage risk with your own stops and position sizing. The author is not a licensed financial advisor; consult a qualified professional before making financial decisions. You are solely responsible for your own trading decisions. Indicador
Polynomial/Linear Regression Volume Profile [BigBeluga]Polynomial/Linear Regression Volume Profile is a state-of-the-art charting framework that blends advanced statistical modeling with localized volume distribution analysis. By evolving past traditional, static horizontal volume profiles, this indicator dynamically curves the volume profile matrix around mathematical trend baselines, giving you a hyper-localized view of value zones, support, and resistance across the trend’s lifecycle.
Equipped with a switchable Ordinary Least Squares (OLS) calculation engine, traders can analyze price distribution relative to a straight path (Linear) or an adaptive structural arc (Polynomial).
🔵 RECURSIVE REGRESSION BASELINES
Adaptive Curve Fitting Engine: Choose between a straight-line trend tracking framework (Linear) or an advanced second-degree curved path (Polynomial). This non-linear baseline curves dynamically to track real institutional momentum shifts, avoiding the lag or rigid delays typical of standard moving averages.
Symmetric Grid Segmentation: The indicator slices the regression space into dynamic parallel layers above and below the center line. These tracking cells act as a structural map of the trend, automatically expanding or contracting based on the mathematical bounds of the lookback period.
Standard Deviation Wave Bands: Plots dedicated tracking envelopes at 1, 2, and 3 Standard Deviations. This maps statistical extremes instantly, highlighting key valuation zones directly on the chart.
🔵 CURVED ORDER FLOW PROFILE
Dynamic Trend-Anchored Volume Profile: Traditional volume profiles are anchored strictly to vertical price grids. This framework bends the profile horizontally along the path of the regression curve. This ensures volume is localized directly relative to the trend's value matrix rather than arbitrary static prices.
Dynamic Point of Control Matrix (POC): The tool calculates cumulative transaction weights across each regression row. The absolute highest volume cluster is highlighted across the entire lookback window as a vivid Point of Control (POC) baseline, serving as a primary target magnet for price discovery.
Gradient Density Mapping: Volume bins are colored with a responsive heat-map gradient. Low-volume zones fade into deep baseline tones, while high-volume institutional interest areas light up dynamically, reflecting heavy positional accumulation.
🔵 DATA INTERFACE & CONTROLS
Regression Matrix Dashboard (Top-Right): A neat information center providing live metrics, including current trend direction (Bullish/Bearish), the numerical value of the POC level, the exact transactional volume resting at that key node, and structural $\pm3\text{ SD}$ channel limits.
Precision Profile Scaling: Adjust the profile width parameters to limit or extend how far back profile bins stretch across your chart space to prevent layout clutter.
Complete Style Personalization: Individualized visual controls allow you to switch line architectures (Solid, Dashed, Dotted) across baselines, boundaries, and POC paths.
🔵 STRATEGIC APPLICATION
Trading the Trend Value Nodes: Treat the dynamic POC line as a trend anchor. In a strong bullish trend, pullback entries occurring at a highly concentrated, heat-mapped POC node represent low-risk, high-probability entry criteria.
Mean Reversion at Statistical Boundaries: When price extends completely out to the dynamic outer channel limit and volume density in that outer bin thins out, look for a swift mean-reversion snapback toward the baseline.
Volume Profile Breakouts: Low-volume zones (gaps in the curved profile) indicate price levels that the market skipped quickly due to high momentum. If price breaks past a thick volume node into a low-volume zone, it is likely to sprint quickly toward the next major heat-mapped node.
Structural Regime Tracking: Use the upper-right dashboard to instantly evaluate macro status. If the matrix shifts between Bullish and Bearish while price hovers consistently near a high-volume POC, it implies heavy institutional distribution is occurring before the next major expansion.
Polynomial/Linear Regression Volume Profile redefines volume structure. By wrapping the laws of order flow directly around mathematical curves, it gives trend traders an elite perspective to trade with precision, statistical logic, and institutional order flow visibility. Indicador
Indicador
Price Density Clouds [EXCAVO]Continuous Kernel-Density Map of Where Price Has Actually Traded
The Price Density Clouds builds a smooth, continuous probability density of
price over a lookback window and paints it as gradient clouds directly behind
the candles. Dense, saturated clouds mark value zones - the equilibrium levels
where the market has spent the most time and where price tends to stall and
revert. Thin, transparent gaps mark inefficiency zones - levels price travels
through quickly. A dashed POC line marks the single highest-probability price,
and the Value Area High / Low bracket the core of the distribution.
This is not a bin-based volume profile. Instead of chopping price into discrete
buckets, KDE sums a smooth gaussian kernel around every price point, producing a
continuous density curve with no bin-edge artefacts. The bandwidth is set
automatically by Silverman's rule, so the smoothing adapts to the instrument's
own volatility.
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▸ HOW TO USE
Step 1 → Add the indicator. Gradient clouds appear behind the candles
over the lookback window, brightest at the highest-probability
levels and fading out toward thin zones.
Step 2 → Read the clouds. Saturated bands = value / equilibrium where
price tends to stall and mean-revert. Faint gaps = inefficiency
where price moves fast - natural travel targets.
Step 3 → Use the POC. The dashed POC line is the single most-traded
level - a robust magnet and support / resistance anchor. Price
far from POC has a statistical pull back toward it.
Step 4 → Use the Value Area. The dotted Value Area High / Low bracket
the core of the distribution (default 70%). Acceptance inside the
area is balance; rejection outside it is imbalance worth trading.
Step 5 → Check the side profile. The gradient density profile on the
right of the last bar is the same density rotated 90 degrees - a
quick read of the full distribution shape at a glance.
Step 6 → Combine with structure. Clouds are context, not direction.
They pair well with trend, sweep, and breakout tools - a breakout
into a thin zone tends to run; a breakout into a dense zone tends
to stall.
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▸ HOW IT CALCULATES
◆ Gaussian Kernel Density
Every close in the lookback window contributes a gaussian bell curve centred at
its own price. The curves are summed across the price range to produce a single
continuous density function: density(x) = sum over j of exp(-0.5 x ((x - price_j)
/ h)^2). Levels where many bars cluster get tall, overlapping kernels and a high
density; isolated levels get a low density.
◆ Silverman Bandwidth
The kernel width h controls smoothness. It is set automatically by Silverman's
rule of thumb: h = 1.06 x sigma x n^(-1/5), where sigma is the stdev of the
lookback prices and n is the sample size. The Bandwidth Multiplier input scales
this for sharper or smoother clouds. Auto-bandwidth means the same settings
adapt across instruments and timeframes.
◆ Normalisation and POC
The density is evaluated at Resolution levels between the lookback high and low,
then normalised so the peak equals 1.0. That peak level is the POC (Point of
Control) - the single highest-probability price. Cloud opacity and colour are
driven by each level's normalised density.
◆ Value Area
Starting at the POC, the algorithm expands outward, each step absorbing the
denser of the two neighbouring levels, until the enclosed density reaches the
Value Area % of the total (default 70). The price extent reached becomes the
Value Area High and Low.
◆ Gradient Rendering
Each density band of the cloud is drawn as a horizontal box tinted by a
two-colour gradient: the Low Density Color at thin levels through to the High
Density Color at the POC, with opacity ramping in parallel. Adjacent bands tile
continuously, so the cloud reads as a smooth heat-map rather than discrete
blocks. The same gradient drives the right-side density profile, whose width
per level scales with density - at the default resolution the edge reads as a
near-smooth wave while keeping the per-level gradient colour.
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▸ WHAT MAKES IT DIFFERENT
◆ Continuous Density, Not Bins
Standard volume / price profiles split price into discrete bins, so the result
depends heavily on bin size and shows hard edges. KDE produces a smooth
continuous curve - no bin-edge artefacts, no arbitrary bucket count, just the
true shape of where price has traded.
◆ Auto-Adaptive Bandwidth
Silverman's rule sizes the smoothing from the instrument's own volatility and
sample size. The clouds stay meaningful on BTC, EURUSD, gold or an index with
the same default settings.
◆ Value Structure In One View
POC, Value Area High / Low and the full density shape are all on the chart at
once, with a matching side profile - the complete market-profile read without a
separate pane or a session reset.
◆ Premium Gradient Visual
A smooth two-colour density gradient behind the candles with parallel opacity
ramp, a clean dashed POC, dotted value-area lines, and a right-side profile
histogram. The clouds sit behind price as context and never clutter the read.
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▸ DASHBOARD
Real-time panel (top right) with the current value read:
POC - price of the highest-density level
Value Area High - upper bound of the value area
Value Area Low - lower bound of the value area
Price Zone - whether price is Above Value, In Value, or Below Value
Lookback - bars used to build the distribution
Legend table (bottom left) explains every colour. Both panels toggle in the
Dashboard settings.
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▸ SETTINGS
Engine
Lookback Period - 200 (bars used to build the price distribution)
Resolution - 120 (number of horizontal density bands; higher = smoother gradient and profile edge, up to 200)
Bandwidth Multiplier - 1.0 (smoothness; 1.0 = Silverman auto, higher = broader clouds)
Value Area % - 70 (percentage of total density that defines the value area)
Visualization
Low Density Color - blue (thin / inefficiency end of the gradient)
High Density Color - orange (dense / value end of the gradient)
POC Line Color - near-white (high contrast against the dense orange cloud the POC sits in)
Min Cloud Opacity - 8 (opacity of the lowest-density band; keeps empty zones faint)
Max Cloud Opacity - 65 (opacity of the POC band)
Show POC Line - ON
Show Value Area - ON (dotted Value Area High / Low lines)
Value Area Highlight - ON (boosts band opacity inside the value area so the 70% core pops)
Show Side Profile - ON
Profile Outline - ON (thin bright line tracing the right edge of the profile for a crisp silhouette)
Cloud Forward Extend - 10 (bars the clouds extend right of the last bar)
Dashboard
Show Dashboard - ON
Dashboard Position - Top Right
Show Legend - ON
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Best regards,
EXCAVO
Disclaimer
Trading involves significant risk. This indicator is a technical analysis tool
and does not constitute financial advice, investment recommendations, or a
guarantee of future results. Past indicator behavior does not guarantee future
performance. Always use proper risk management and your own judgment.
Indicador
Confluence Zone Engine [CZE]# Confluence Zone Engine
A structural analysis indicator that identifies support and resistance zones by clustering Anchored VWAPs and Anchored Volume Profile levels across the chart timeframe and up to three higher timeframes. Each zone is rated 1 to 5 stars based on how many independent sources cluster at the level and how diverse those sources are.
This is a structural analysis tool. It marks where multiple independent technical references agree at a price. It does not place trades or suggest entries, exits, targets, stops, or position sizes.
---
## What this script does
The engine runs a six-stage pipeline on every confirmed bar:
**Stage 1 — Pivot detection.** Detects pivot highs and pivot lows at Fibonacci-spaced lengths (3, 5, 8, 13, 21, 34, 55, 89). Each pivot becomes an "anchor" point. Default enabled tiers are 8, 21, and 34 — selected to give fast / medium / slow coverage without redundancy. The full Fibonacci set is configurable.
**Stage 2 — Per-anchor calculations.** For every anchor, the engine maintains:
- An Anchored VWAP (volume-weighted average price since the anchor bar)
- An Anchored Volume Profile, which produces a Point of Control (POC = most-traded price since anchor) and a Value Area (VAH and VAL = upper and lower edges of the 70% volume zone)
So a single pivot generates up to 4 contributor levels: AVWAP, POC, VAH, VAL.
**Stage 3 — Higher-timeframe replication.** The same pipeline (stages 1 and 2) re-runs on up to three configurable higher timeframes via non-repainting `request.security` calls. This produces a multi-timeframe view of structural anchors — pivots and AVWAPs from a 1H chart inform what the 5m engine treats as a higher-timeframe reference.
**Stage 4 — Cluster building.** All contributor levels from all enabled timeframes are collected. The cluster builder walks them in price order, merging any that fall within a configurable tolerance (default 0.08% of current price; preset-adjusted per asset class). A cluster with at least the minimum-count threshold becomes a candidate zone.
**Stage 5 — Star rating.** Each zone is rated 1 to 5 stars based on:
- Total contributor count
- Source-type diversity (how many of the 4 source categories — PH-AVWAPs, PL-AVWAPs, POCs, VAH/VAL — are present)
- HTF agreement (whether contributors from multiple timeframes align)
A "Premium" tier flag fires when top stars combine with HTF agreement.
**Stage 6 — State machine.** Each zone is tracked through a lifecycle:
- **Active** (forming, amber): the zone is currently accumulating contributors
- **Pending** (blue): contributor activity has paused; waiting for price to resolve the level
- **Resolved Support** (green), **Resistance** (red), or **Chop** (gray): determined by whether price moved decisively up, decisively down, or stayed range-bound after the zone activated
- **Tested** (dashed border): price entered the resolved zone but has not closed past the defending edge
- **Broken** (dashed orange + "Broken" label): price has closed past the defending edge
- **Flipped**: if a Broken state confirms over multiple closes past a threshold, the zone repaints to the opposite role (broken Resistance becomes Support, broken Support becomes Resistance)
---
## Why this indicator is original (not a simple mashup)
This is not "AVWAP indicator + Volume Profile indicator + multi-timeframe wrapper." Three design choices distinguish it from existing public indicators:
**1. Anchored at every Fibonacci pivot, not at a single user-selected point.** Standard AVWAP indicators require the user to manually click an anchor point. Standard Volume Profile indicators use either a fixed session or a single anchor. This engine automatically detects pivots at multiple Fibonacci lengths and runs an AVWAP + Volume Profile from each one. The number of active anchors at any time is typically 6 to 20, generating 24 to 80 contributor levels — far more than a manually-anchored tool can produce.
**2. Cross-timeframe clustering, not separate per-timeframe overlays.** The engine does not draw 5 separate AVWAPs from a 1H chart, plus 5 from a 4H, plus 5 from a daily. Instead, levels from all timeframes are collected into one pool and clustered in price space. A 1H AVWAP at 23,720 and a daily POC at 23,718 merge into a single zone marked as "two contributors from two timeframes." This produces structural information neither timeframe shows alone.
**3. Compositional bias from the contributor mix.** The cluster builder records *which type* of contributor formed each zone — pivot-high AVWAPs (trapped sellers' breakevens), pivot-low AVWAPs (trapped buyers' breakevens), POCs (acceptance), VAH or VAL (fair-value edges). The directional implication of each type is summed into a "compositional bias" score. A zone built mostly from PL-AVWAPs and VAL contributions leans support; one built from PH-AVWAPs and VAH contributions leans resistance. This is an analytical lens not present in standard S/R indicators, which generally treat all levels as direction-agnostic.
---
## Mashup justification — how the components work together
The four classes of technical analysis used (pivots, AVWAP, Volume Profile, multi-timeframe analysis) are not chosen arbitrarily. Each contributes a dimension the others do not, and the value comes from how they interact:
**Pivots provide the anchors.** Without pivots, AVWAP needs a manual anchor and Volume Profile needs an arbitrary session. Pivots at multiple Fibonacci lengths give the engine *automatic structural anchors* spanning timescales — short-term swings, intraday swings, session-level swings. The Fibonacci spacing (3, 5, 8, 13, 21, 34, 55, 89) ensures the anchors are non-redundant: each tier has a different bar requirement and catches different swings.
**AVWAP measures participant breakeven from each anchor.** This is the "where might trapped participants defend" dimension. An AVWAP from a pivot high is the volume-weighted breakeven for everyone who entered after that high (mostly net-short positions). An AVWAP from a pivot low is the breakeven for everyone who entered after that low (mostly net-long). When price returns to one of these AVWAPs, structurally those participants are at breakeven and have incentive to act.
**Volume Profile measures acceptance from each anchor.** This is the "what price has been most-accepted by volume" dimension. POC is the most-traded price; VAH/VAL are the edges of the 70%-volume range. AVWAP and POC measure different things — average price vs most-accepted price — and frequently disagree. When they *do* agree at a level, that's two independent signals saying "this price matters."
**Multi-timeframe replication tests for structural agreement.** A zone that exists only on the chart timeframe is one-timeframe noise. A zone where chart-TF contributors *agree with* higher-TF contributors at the same price is structural — the same level shows up no matter which timescale you measure from. The engine treats HTF agreement as a primary input to the star rating: HTF-aligned zones can earn an extra star (capped to prevent inflation).
**The clustering is where the value emerges.** Individually, none of these components produce reliable levels. AVWAP gets broken constantly. POC migrates. Pivot levels get violated. But when the engine sees that the 21-pivot AVWAP, the 34-pivot POC, the 8-pivot VAL, and a 1H AVWAP all land within 0.08% of each other at the same price, that's a confluence of independent references measuring different things — and that *coincidence* is what produces structural significance. The star rating quantifies how much agreement is present.
This is the mashup's purpose: not to combine indicators for their own sake, but to use convergence as a filter that turns individually noisy components into a rated structural signal.
---
## How to use the indicator
**Step 1: Apply to any chart timeframe.** All settings have sensible defaults. The asset-class preset (NSE Index Futures, NSE Stock, US Future, US ETF, US Stock, Commodity, Crypto, or Custom) auto-adjusts cluster tolerance and pivot defaults. Auto-selected higher timeframes scale with the chart — a 5m chart defaults to 15m/60m/240m HTFs, while a daily chart defaults to weekly/monthly HTFs.
**Step 2: Read the status panel (bottom-right).** This is the actionable summary:
- "Sup" row: nearest resolved Support below current price, with point distance
- "Res" row: nearest resolved Resistance above current price, with point distance
- "Top zone": the highest-rated zone overall
- "Data": indicator health (OK / Degraded / Critical) — if the underlying volume data is sparse, ratings are capped
**Step 3: Scan the chart for "Broken" labels.** Any zone in dashed orange with a "Broken" label is currently being violated. Watch for either recovery (border returns solid) or polarity flip confirmation (zone repaints to opposite role).
**Step 4: Find the active amber zone.** This is the current forming confluence. Look at the triangle shape: ▲ means the composition leans support, ▼ means it leans resistance, ◆ means neutral. The number next to the triangle is the star rating. A premium "★" prefix means HTF agreement is present.
**Step 5: Use the Major S/R lines as forward references.** Bold horizontal lines mark the top 2 strongest support levels below current price and top 2 strongest resistance levels above. Labels show price, stars, and distance.
**Step 6: Use the Range band as context.** The translucent aqua band marks the recent trading envelope (default last 50 bars). A narrow band means consolidation; a wide band means trending.
**Step 7: Hover any element for the full breakdown.** Every box, triangle, and line has a tooltip showing total contributors, type counts, HTF alignment, state, and history.
---
## How NOT to use the indicator
- **Do not treat the bias arrow as a trade signal.** It is a compositional description of contributors, not a directional forecast. A zone with a ▲ bias can still resolve as resistance.
- **Do not treat a "Broken" label as a trade trigger.** It tells you a known level is failing — not that you should enter a position in either direction.
- **Do not assume higher stars mean higher profit probability.** Stars measure the diversity and density of contributors, not historical performance or expected return.
- **Do not rely on it for low-volume instruments.** If the data-health badge shows "Degraded" or "Critical," the engine has capped ratings and may suppress zones entirely. This is a feature; the indicator is most accurate on liquid, volume-rich instruments (index futures, large-cap stocks, major crypto).
---
## How to read the star rating
Stars are a descriptive summary of confluence quality. They are not a probability of profit.
- 1 to 2 stars: minimum cluster; one or two source types. Background context.
- 3 stars: at least 5 contributors with 2 or more source types. Recurring intraday levels.
- 4 stars: at least 7 contributors with 3 or more source types, OR 3-star with HTF agreement.
- 5 stars: at least 10 contributors with all 4 source types present. Often boosted by HTF alignment.
By default, only 4-star and 5-star zones get triangle markers and qualify for Top-N or Major S/R lines. This is adjustable.
---
## Visual primitives
- **Confluence zones** — colored boxes marking each cluster. Boxes recolor as zones resolve. Border style indicates compromised state.
- **Triangle markers** — ▲ ▼ ◆ at each formation bar. Shape encodes direction. Color encodes lifecycle state.
- **Top-N S/R lines** — top 4 resolved zones by strength and recency project forward.
- **HTF confluence bands** — semi-transparent bands per higher timeframe (cyan, purple, orange).
- **Major S/R lines** — bold lines for top 2 supports below and top 2 resistances above current price.
- **Range band** — translucent band marking recent trading range with HI / LO labels.
- **Current price line** — thin dotted line at current price.
- **Status panel** — bottom-right summary.
---
## Technical notes
- Pine Script v6
- Non-repainting: all `request.security` calls use `barmerge.lookahead_off`
- Asset-class presets adjust cluster tolerance and pivot defaults
- Built-in data-integrity layer caps ratings when volume data is sparse or stale
- Seven alert conditions: new zone formed, high-quality (4 to 5 star) zone, HTF aligned, price entered support, price entered resistance, data health degraded, polarity flip
---
## Important risk disclosure
This indicator is provided for educational and informational purposes only and is not financial advice. Trading and investing involve substantial risk of loss, including the possible loss of all invested capital. The zones, ratings, bias shapes, and lines are descriptive summaries of structural confluence — they are not predictions of future price movement, indications of profitability, win rate, or expected return.
No backtested or hypothetical performance is claimed or implied. Past zones identified by the indicator are not indicative of future results.
You are solely responsible for any decisions you make. Consult a qualified, licensed financial advisor before trading. Past performance does not guarantee future results.
Indicador
