Rolling Z Score Reversion Map [Pineify]Rolling Z Score Reversion Map
Overview
This map keeps rolling price Z-score visible while separating reversion-eligible extremes from trend-aligned extremes. It describes context; it does not forecast returns or issue trades.
Problem Definition
Z-score measures distance from a rolling mean in deviation units. Fixed lines such as +2 and -2 treat every extreme alike. That fails when the mean moves: positive Z can persist with a rising mean, so a contrarian reading confuses extension with disequilibrium. The script preserves raw Z and asks separately whether aligned trend and range pressure should withhold a reversion watch.
Design Rationale
Raw Z remains unchanged so its units stay interpretable. Mean slope is expressed as ATR per bar for cross-market comparison. ATR uses a prior-only percentile to avoid fixed price units and candidate self-ranking. Sign alignment isolates positive deviation with rising mean and its negative mirror. High ATR rank adds pressure but cannot dominate alone. A finite closed-bar watch preserves event order; permanent extreme marks would duplicate events. Lag and confirmation delay are accepted for auditable states.
Key Features
Raw Z-score with symmetric rails.
ATR-normalized slope, prior-only ATR rank, and direction gate.
Confirmed watch with mean, pressure, data, and time exits.
Optional visuals, table, and two alerts.
How It Works
The script computes a rolling mean and deviation of closes. Raw Z is their price difference divided by deviation; a near-zero denominator returns no value.
ATR defines range scale. Its percentile is a midrank against N prior ATR values: lower samples vote one and ties half. Current ATR is excluded. Mean change over the slope span is divided by ATR and bar count to obtain ATR per bar.
The gate tests whether Z and slope share a sign. Pressure combines 65% aligned trend strength, 20% upper-half ATR expansion, and 15% trend-volatility interaction, bounded from zero to one. An extreme qualifies when absolute Z reaches its rail and pressure stays below the gate.
A newly qualified close freezes watch side and entry Z. The watch ends on a crossing of the evolving mean, expiry, invalid data, or an invalidation-rail extreme with excessive pressure. A crossing is only observed, not caused. Warm-up covers all windows and rank history. Live colors can change; watches, markers, and alerts update on confirmed bars.
How Multiple Indicators Work Together
The components form one filter. Z supplies distance but not reference motion. ATR-normalized slope supplies motion; sign alignment relates it to the deviation. Prior ATR rank adds portable range context. Together they decide whether an extreme starts a watch. Without slope, the fixed-threshold failure returns; without ATR, calm and expansion are alike; without the watch, event chronology disappears.
Trading Ideas and Insights
Use the map to organize observation, not assume reversal. Cyan means pressure is below the gate and an extreme can start a confirmed watch. Orange means the same raw distance has stronger continuation context, so a contrarian label is withheld. A gold zero-axis marker records a later mean crossing. Compare states to find where fixed Z thresholds misdescribe context.
Unique Aspects
The contribution is separating measurement from interpretation. Many filters rescale an oscillator, preventing comparison with ordinary Z rails. Here raw distance stays intact while a bounded, direction-sensitive, range-relative gate classifies events. The watch preserves sequence: qualification occurs first; later bars cross the evolving mean or invalidate. No result is moved backward and no probability is implied.
How to Use
After warm-up, read height as raw Z and color as context. Cyan marks a candidate or active watch, orange a higher-pressure extreme, and gray a balanced or unavailable state. Diamonds and alerts mark confirmed entry. A zero circle records a watched crossing; an orange cross records invalidation. Use 15-minute to weekly charts and Once Per Bar Close alerts. These are states, not trade instructions.
Customization
Z window sets reference horizon; Extreme threshold sets event distance. ATR window and rank length set range context and history needs. Slope span smooths motion; Full trend pressure maps ATR-per-bar slope to full strength. Lower Maximum pressure tightens qualification. Invalidation Z and Maximum watch bars bound observation life. Visual layers can be disabled independently while raw Z and rails remain. Colors support varied themes.
Assumptions and Limitations
Rolling statistics change as samples enter and leave; Z implies neither normality nor stationarity. ATR rank is empirical, not probability, and needs complete history. Weights are design choices, not optimized constants. Slope lags; gaps can outrun it. The watch targets an evolving mean, not the entry mean. Live visuals are provisional, and confirmed events still depend on feed history. Inputs, adjustments, and synthetic charts can change results. Execution, costs, sizing, news, structure, and future returns are outside scope. Pineify checks syntax, not market behavior.
Conclusion
The map adds auditable context without changing Z-score units. Distance remains distance; trend, volatility, and watch state change only its label. Keep lag, sensitivity, and scope explicit.
指标
Regime Gated Confluence Score [Pineify]Regime Gated Confluence Score
Overview
This pane indicator combines trend, momentum, and volume after a four-state gate selects meaning and weight. The main score and dashboard reconcile signed contributions.
Problem Definition
Fixed-weight confluence hides a regime error. Positive RSI may confirm a trend but mark extension in a range. EMA separation can persist after efficient travel ends. Relative volume shows participation, not acceptance. A permanent sum can stay strong when path efficiency is low, factors disagree, or ATR leaves its baseline, so users cannot tell whether magnitude reflects agreement or one dominant input.
Design Rationale
ATR-normalized EMA separation and slope measure trend across price scales. Centered RSI supplies momentum; RANGE reverses it to express a fade. Volume pressure combines capped relative volume with close location without claiming aggressor flow. EMA spread and path efficiency classify structure; ATR versus baseline identifies displacement. Lower hold thresholds add hysteresis. A trained model would add hidden data assumptions, while fixed weights preserve the failure. Explicit rules accept sensitivity and lag for auditability.
Key Features
Four regimes with hysteresis.
Standardized trend, RSI, and participation factors.
Regime weights, range inversion, missing-volume renormalization, conflict attenuation, exact contribution totals, and confirmed alerts.
How It Works
EMA spread and fast-EMA change are normalized by ATR, blended 65/35, and clipped to -1 through +1. RSI is centered at 50, divided by 25, and clipped. Volume multiplies close location inside the bar by relative volume capped at 2.5 times baseline, then smooths it. If fewer than 80% of volume-window bars are usable, volume is omitted.
Trend strength is absolute normalized EMA spread. Path efficiency divides net movement by total one-bar movement. ATR relative to baseline measures displacement. VOLATILE has priority until its lower hold level clears. Otherwise, strong separation and efficiency enter TREND, weak evidence enters RANGE, and unresolved evidence is TRANSITION.
Trend/momentum/volume weights are 55/30/15 in TREND, 15/60/25 in RANGE, 40/35/25 in VOLATILE, and 35/40/25 in TRANSITION. RANGE reverses only RSI. Missing volume removes its weight and renormalizes the others. Agreement divides absolute net contribution by total absolute contribution and sets a 0.55-to-1 gate; VOLATILE adds an ATR penalty. Gated components sum to the score. Warm-up or invalid threshold and EMA ordering blocks output with a diagnostic.
How Multiple Indicators Work Together
Trend estimates structure, momentum locates bounded pressure, and volume tests participation plus bar acceptance. The regime interprets them before combination. Without range inversion, extension becomes a continuation vote; without trend, brief momentum can dominate; without volume, weights must be renormalized. Agreement converts remaining conflict into lower magnitude rather than hiding it.
Trading Ideas and Insights
Use the score as context, not an order. A confirmed threshold cross during TREND identifies aligned conditions. In RANGE, check whether trend or volume opposes inverted momentum before considering a fade. In VOLATILE, a compressed gate shows ATR displacement discounting the raw sum. A strong component beside a modest total indicates conflict.
Unique Aspects
The contribution is the sequence of classification, interpretation change, weighting, and attenuation. RANGE reverses momentum while other factors can veto it; hysteresis separates trend entry from persistence; missing volume is removed; and agreement scales every component so the ledger equals the score. The halo shows magnitude, the background shows regime, and the table exposes construction.
How to Use
Start with defaults and compare the regime label with visible path behavior. Wait for warm-up. Keep the ledger visible to see whether structure, oscillator pressure, or participation drives direction. Use confirmed alerts when closing-state transitions matter. Contribution lines are diagnostic; the halo and background form the primary view. Omitted volume means a disclosed two-factor score.
Customization
EMA lengths and slope lookback control structural response; RSI length controls momentum sensitivity. Volume baseline and smoothing trade speed for stability. Regime length changes path efficiency and the ATR baseline. Entry thresholds must exceed hold thresholds. Raising the score threshold reduces alert frequency but does not establish better forecasting. Visual switches change display only.
Assumptions and Limitations
The script uses chart OHLC and reported volume. Exchange, tick, and absent volume differ; close-location volume is only a proxy. EMA, ATR, RSI, and rolling baselines lag. RANGE can fade a breakout, hysteresis can delay exits, and attenuation can suppress an early shock.
Realtime factors, regime, colors, and score can change before close; alerts require confirmation. No request calls, future data, pivots, or negative offsets are used. The script does not model liquidity, news, sizing, entries, stops, or exits. Thresholds do not establish expected return. Sparse bars and unreliable volume can distort evidence.
Conclusion
This replaces a fixed sum with an inspectable state process. The score and ledger show weights, conflict attenuation, and missing-data effects. Keep separate risk and execution rules.
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指标
AI SuperTrend [PickMyTrade]THE PROBLEM WITH A FIXED MULTIPLIER
Every standard SuperTrend applies the same ATR multiplier across all market conditions — the same constant during a strong trending breakout, a narrow choppy range, and a volatility spike. A value calibrated for one regime is miscalibrated for the others. Most traders compensate by manually switching timeframes or parameters. This script automates that decision.
The question it asks: what if the ATR multiplier were selected from historical bars that most resembled the current market regime — matched by Hurst state and volatility rank — rather than set by the user as a fixed constant?
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THREE AI LAYERS
Layer 1 — Hurst Exponent (Regime Gate)
The Hurst Exponent is computed via Rescaled Range (R/S) Analysis. It measures the degree of long-range dependence (memory) in the price series:
H ≥ 0.55 → Persistent (trending) — SuperTrend active, signals enabled
H ≈ 0.50 → Random walk — candles turn gray, no signal generated
H ≤ 0.45 → Anti-persistent (mean-reverting) — signals suppressed
The Hurst gate is the first filter. Signals only fire when market structure is historically associated with persistence — not randomness or mean-reversion.
Layer 2 — Garman-Klass Volatility Rank
Garman-Klass (1980) estimates realized volatility from OHLC prices rather than close-to-close returns, capturing intrabar price range and making it more sensitive to volatility changes. The current reading is percentile-ranked against recent history (0–100%) and used as the second feature dimension for the KNN search.
Layer 3 — KNN Multiplier Optimizer
K-Nearest Neighbors searches a rolling memory bank of feature pairs from previous bars. For each current bar it finds the K most similar historical bars by Euclidean distance in that 2D feature space. From those neighbors it retrieves the ATR multipliers that were in effect — weighted by the profitability of the bar that followed. The result is the AI Multiplier: a context-aware value drawn from the most similar past conditions, not a fixed constant.
────────────────────────────────────────
WHAT YOU SEE ON THE CHART
Candle color — the defining visual. Orange = bull trend regime, blue = bear trend regime, gray = random walk or mean-reverting. The regime state is readable on every bar without checking the table.
Signals — ● (circle) marks trend flips with Hurst ≥ 0.65, the high-conviction threshold. ▲▼ (triangle) marks standard threshold crossings. No signal fires in gray (random or mean-reverting) regimes.
SL / TP lines — dashed lines drawn automatically at each signal bar, sized from current ATR × the AI Multiplier active at that bar.
Info table (top right) — live display of Hurst value, Regime label, Direction, AI Multiplier, Vol Rank, and KNN memory bar count. Shows WARMUP until KNN has stored enough bars to begin optimizing.
────────────────────────────────────────
HOW TO USE
A signal requires all three conditions to be true simultaneously:
KNN is warmed up (table shows ● LIVE)
Hurst confirms a trending regime (H ≥ Trend Threshold input)
Price is on the correct side of the EMA filter
Circle signals (●) indicate Hurst has exceeded 0.65 — stronger persistence than the standard threshold. Triangle signals (▲▼) are at the user-defined threshold. Gray candles indicate the market is not in a trending regime; reducing exposure or standing aside is appropriate during those periods.
The regime background shading (faint orange or blue fill) shows when the SuperTrend is in an active directional state.
────────────────────────────────────────
INPUTS
AI Engine — Hurst Lookback, KNN Neighbors (K), KNN Memory (bars), Trend Threshold, Mean-Revert Threshold
SuperTrend — ATR Length, Base Multiplier, Volatility Window, EMA Period
Visual — Bull/Bear colors, SL/TP lines toggle, SL ATR Multiplier, Risk:Reward ratio, Regime Background
Display — Zen Mode (hides labels and table), Show Info Table
ALERTS
Three alert conditions: Long Signal, Short Signal, Any Signal.
────────────────────────────────────────
NOTES
KNN requires warmup equal to the KNN Memory setting before the AI Multiplier activates. During warmup the base multiplier scaled by Hurst and volatility rank is used instead.
No repainting. All signals are confirmed on bar close. KNN stores lagged values only.
Garman-Klass citation: Garman, M. & Klass, M. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business , 53(1), 67–78.
指标
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.
指标
Covenant Regime Atlas [JOAT]Covenant Regime Atlas
Introduction
Covenant Regime Atlas is an open-source Pine Script v6 market-regime indicator built to classify directional state through trend, expansion, persistence, and retest quality. Its purpose is not to predict the next trade by itself, but to create a durable bias layer that tells the trader whether the market is developing a bullish regime, a bearish regime, or a maturing directional environment worth respecting.
The problem this script solves is context instability. Many traders can spot a moving-average crossover or a burst in ATR, but that alone does not answer whether the regime is actually mature, whether momentum has real separation, or whether recent retests are behaving consistently with the dominant trend. Covenant Regime Atlas addresses this by blending multiple regime components into one overlay and dashboard.
The script uses a dual-mid framework derived from EMA and HMA references, ATR-scaled cloud and envelope bands, persistence measurement, heat normalization, slope impulse, and retest memory. This lets it move beyond a simple bullish-versus-bearish cross and instead describe whether the regime is developing, mature, expanding efficiently, or internally cooling.
The result is an indicator for traders who want a cleaner read of bias before interpreting any trigger tool. It is especially useful as a regime filter for execution indicators and strategies that should behave differently in mature directional flow versus unstable transition periods.
Core Concepts
1. Directional Mid Versus Structural Mid
The script creates a fast directional midpoint and a slower structural midpoint using blended EMA and HMA references. The spread between those two curves forms the backbone of regime direction.
float directionalMid = math.avg(emaFast, hmaFast)
float structuralMid = math.avg(emaSlow, hmaSlow)
bool trendBull = directionalMid > structuralMid
This gives the regime engine more shape than a single moving average crossover. The directional mid measures active flow. The structural mid measures slower context.
2. Regime Strength Through Separation And Heat
Regime strength is calculated from ATR-normalized spread plus the distance of normalized heat from its midpoint. In other words, the regime is strongest when the fast and slow structures are well separated and price is also positioned decisively within its recent range.
This helps avoid overvaluing tiny directional crosses that occur with little actual separation or energy.
3. Persistence And Maturity
Every regime needs time to prove itself. The script counts how long the current directional condition has been intact and compares that against a user-defined persistence floor. Once the threshold is met, the regime is treated as mature rather than merely developing.
This matters because a fresh directional flip is different from a directional condition that has held for many bars and survived multiple retest opportunities.
4. Retest Memory
After a mature regime forms, the indicator watches for controlled retests of the directional midpoint. Bull retests occur when price revisits the midline from above and closes back above it. Bear retests use the opposite condition. The last retest is stored as a dotted line and extended forward until it becomes irrelevant.
This gives the trader a simple memory of where the market most recently confirmed trend participation.
5. Pulse, Expansion, And Efficiency
The script also measures volatility expansion, slope impulse, heat drift, trend separation percentage, and directional travel efficiency. These metrics allow the dashboard to distinguish between a mature regime that is expanding forcefully and one that is mature but internally cooling or grinding.
Features
Bull and bear regime classification: Uses fast-versus-slow blended midpoints to define directional control
Maturity logic: Distinguishes developing regimes from mature ones using persistence counting
ATR-scaled cloud and envelope: Frames the current directional corridor directly on the chart
Retest memory engine: Stores the latest mature-regime retest level for forward reference
Initiation band: Preserves the regime start envelope so traders can judge distance from the original launch zone
Pulse ribbon: Adds a compact visual band around price to reflect internal heat conditions
Regime backdrop shading: Tints the chart according to the active directional state
Detailed dashboard: Displays strength, heat, persistence, expansion, slope pulse, retest distance, maturity, efficiency, and more
Confirmed-bar alerts: Includes mature bias, retest, expansion, continuation, efficient trend, and heat-reset conditions
Data-window outputs: Exposes regime internals for systematic reading or comparison
Visual Elements
Directional cloud: The gap between the fast and slow regime mids shows whether the market is operating with clean separation
Envelope bands: ATR-based boundaries help frame the active directional corridor around price
Initiation band: The regime launch area stays visible so users can measure how far the trend has traveled from origin
Retest line memory: The latest confirmed retest is preserved as a direct chart reference
Backdrop and pulse ribbon: Context shading and the pulse band make regime character readable without overloading the chart
Best Practices
Treat mature regimes differently from developing ones because the same trigger can behave very differently in each state
Watch heat drift when a regime remains mature but starts losing internal energy
Use retest memory to frame participation zones rather than chasing every extension away from the midline
Give more weight to regimes that show both persistence and expansion instead of one without the other
Use the atlas as a context engine first and an alert source second
Input Parameters
Trend Engine:
Fast Length: Sets the faster directional reference
Slow Length: Sets the slower structural reference
Heat Window: Defines the range-normalization window for heat calculations
ATR Length: Controls volatility normalization
Cloud Width Factor: Sets the width of the directional cloud and envelope
Retest Engine:
Show Retest Memory: Toggles retest storage and line rendering
Retest Cooldown Bars: Prevents retests from firing too frequently
Persistence Floor: Sets how many bars are required before a regime is considered mature
Show Initiation Band: Displays the preserved start range of the current regime
Maturity Window: Controls maturity scaling and travel-efficiency measurements
Display:
Show Dashboard toggle
Show Regime Backdrop toggle
Show Pulse Ribbon toggle
Independent bull, bear, neutral, and panel colors
How to Use This Indicator
Step 1: Read Regime Tag And Strength
Begin with the dashboard’s regime tag. It tells you whether the market is bullish or bearish and whether that state is still developing or already mature. Pair that with the strength reading to avoid confusing a weak directional bias with a strong one.
Step 2: Check Persistence And Expansion
Persistence tells you how long the regime has survived. Expansion tells you whether volatility is supporting the move. A mature regime with positive expansion usually deserves more respect than a new regime with weak expansion.
Step 3: Use Retest Memory As A Structural Anchor
When the retest line is present, it marks the last meaningful participation check inside the trend. That line can help frame whether the current move is still building from a healthy base or drifting too far away from supportive structure.
Step 4: Watch Heat Drift And Efficiency
Heat drift helps show whether the regime is internally warming or cooling. Efficiency tells you whether directional travel has been orderly. These readings are helpful when deciding whether the trend still looks clean or is becoming unstable.
Step 5: Use It As The Bias Layer For Other Tools
Covenant Regime Atlas is best used as a bias filter. It helps define whether you should be thinking continuation, pullback participation, or caution. Pair it with your own trigger logic rather than using the regime alone as a full trading plan.
Indicator Limitations
A developing regime can fail before reaching maturity, especially in choppy markets
Retest memory is useful for context, but the stored retest level is not guaranteed to hold on future tests
Efficiency and heat drift are descriptive metrics, not predictive guarantees of continuation
The indicator can still classify a directional state during periods where execution conditions are poor for actual trading
Originality Statement
Covenant Regime Atlas is original in the way it blends trend separation, maturity, retest memory, expansion, and efficiency into a unified regime overlay. It is not just a moving-average cloud with added cosmetics:
It separates directional identity from maturity, allowing the user to distinguish developing and established regimes
It stores retest memory as a living structural feature instead of relying only on static crossover logic
It combines heat, slope, expansion, and efficiency into one dashboard so regime quality can be judged from multiple dimensions
It preserves the initiation band of the current regime, which gives context that typical trend overlays do not maintain
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Regime readings describe current market structure and internal state based on historical prices. They do not guarantee future movement or profitable trading decisions. Always use independent judgment and proper risk management.
-Made with passion by jackofalltrades
指标
Delta Pressure Ledger [JOAT]Delta Pressure Ledger
Introduction
Delta Pressure Ledger is an open-source lower-pane pressure model built entirely from chart-derived proxies. It combines anchored VWAP context, candle pressure, volume impulse, crowding stretch, volatility pressure, and settlement skew into a normalized composite ledger that classifies whether pressure is balanced, directional, crowded, or stressed.
The problem this script solves is hidden market pressure. Many traders rely on unavailable data feeds or vendor-only metrics to estimate crowding or liquidation risk. Delta Pressure Ledger uses only chart-accessible inputs and standardizes them through z-score normalization so pressure states can still be read in a consistent way across instruments.
Core Concepts
1. Chart-Derived Pressure Proxy
The script estimates directional pressure from candle settlement, intrabar range occupation, and volume impulse rather than external order flow feeds.
2. Anchored VWAP Context
Pressure is interpreted relative to anchored value, allowing the user to distinguish directional expansion from overstretched crowding.
3. Z-Score Normalization
All sub-engines are normalized over a configurable lookback, which makes the composite reading more portable across symbols and timeframes.
4. Crowding and Stress Logic
The script tracks when price and derived sentiment become stretched enough to imply elevated liquidation or unwind risk.
5. Composite Verdict
Pressure, crowding, volatility, and skew are merged into one verdict state so the user can quickly determine whether the market is orderly, imbalanced, or stressed.
Features
Anchored VWAP context: Session, weekly, or monthly value anchor
Pressure engine: Candle and volume-derived directional pressure model
Crowding engine: Stretch and behavioral excess detection
Volatility and skew layers: Pressure quality and instability are separated from raw direction
Normalized composite score: All sub-engines standardized into one comparable ledger
Risk meter: Liquidation-style stress estimate derived from crowding and instability
Confirmed-bar transitions: State changes and alerts are held to confirmed bars
Top-right dashboard: Regime, pressure, crowding, volatility, risk, composite score, and last confirmed flip
How to Use This Indicator
Step 1: Read the composite verdict
The verdict gives the fastest summary of whether the market is balanced, directionally pressured, or entering a crowded stress state.
Step 2: Separate pressure from crowding
A bullish pressure reading with low crowding is different from a bullish pressure reading with extreme crowding and high risk.
Step 3: Respect risk transitions
When the risk meter moves into elevated territory, directional continuation setups deserve more caution.
Indicator Limitations
This script uses chart-derived proxies rather than exchange-level liquidation or true open-interest feeds
Normalized readings can still behave differently across asset classes with unusual volume structure
Stress conditions can remain elevated for extended periods during strong trends
The script classifies pressure and risk context; it does not execute trades by itself
Originality Statement
Delta Pressure Ledger is original in the way it builds a portable, chart-derived pressure and crowding framework without depending on unavailable external feeds, while still organizing the result into a normalized composite and risk ledger.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Derived pressure and crowding models can be wrong, especially during atypical market events. Use proper risk management and independent judgment.
指标
ROC Regime Filter [HYPR-run]DESCRIPTION:
A reliable universal regime filter across all assets, all timeframes. Rate of change filter that classifies price action into regime states. A suite of smoothed EMAs feeds a layered ROC engine that detects when fast momentum aligns with, or diverges from, slow structure. The filter measures; it doesn't predict. When all ROC layers stack in the same direction (parallel alignment), the trend is confirmed by arithmetic. When fast ROC diverges from slow, the regime shifts. The lag is the cost of certainty. Sweet spot is 1hr to 1D; lower timeframes get noisy.
DISCOVERING EDGE
In order to gain a persistent, mechanical edge in which trades are permitted and which are filtered out, we explored a more meaningful expression of regime classification using layered multiple ROC periods to detect when fast momentum aligns with or diverges from slow structure. This resilient regime filter has been the backbone for our automated strategies since 2021.
LAYERED ROC vs SINGLE-INDICATOR REGIME
A single RSI or ADX reading flattens the market into binary (trending/not trending). Layered ROC alignment separates six distinct states, each with different permissible trade types, so the filter matches the complexity of what the market is actually doing. Six regime states gate every decision; the combination of regime color + ROC slope is the trade filter, not either one alone. Phase transitions (green to yellow, orange to green) are the actionable signals; static states just confirm what's already happening. Webhook alerts fire on macro pivots (accumulation/distribution inflections) at the regime transition, not after the move has run.
FEATURES
- Six regime states from layered ROC alignment (see color legend below)
- Early trend detection when all layers accelerate in parallel
- ROC 200 line with regime-colored gradient fill
- Macro pivot detection: strong trend exhausting into sideways, scored by where ROC 200 sits relative to its all-time range
- Accumulation/distribution context in dashboard
- ROC 200 pivot high/low divergence markers on main chart
- Consolidation markers with conviction scoring (normal vs extreme)
- Gradient candle overlay (ROC Sticks; toggle on/off)
- Two-row dashboard: row 1 = macro context (accumulation/distribution), row 2 = current regime state with directional qualifier and slope
- Dashboard dark/light theme toggle for any chart background
- Full ROC stack in data window for manual analysis
- Webhook alerts on macro pivots (accumulation/distribution)
HOW IT WORKS
ROC alignment is the core signal. When all layers stack in the same direction, that's strong trend territory (green). When fast ROC diverges from the slower layers while slow structure still holds, the engine reclassifies from strong trend to sideways (yellow), flagging a pullback rather than trend failure. Deeper corrections where intermediate layers fall below the structural anchor fire orange, indicating a correction within the primary trend. Macro pivots fire at the inflection: strong trend exhausting into sideways for the first time. The consolidation score layers this with where ROC 200 sits in its all-time range. Consolidation at extreme ROC readings (bright green/red dots) is the highest-conviction signal for reversal.
HOW TO USE
Read the regime color, not the price. Green = strong trend long, red = strong trend short, orange = deeper correction, yellow = short pullback, white = directionless. Use regimes as a directional gate: longs during green, shorts during red. Yellow flags a pullback within trend; wait for resolution back to green/red before re-entering. Orange is a deeper correction; patience or fade with confirmation from other tools. The highest-edge signals come from regime transitions, not static states. Watch for: green breaking into yellow (macro pivot, potential reversal), extended yellow resolving back to green (continuation re-entry), and the ROC slope within a regime (slope rising in orange = trend about to resume). The data window shows the full ROC stack across all layers. When fast ROC diverges from slow, that signals continuation or reversion.
MACRO CONTEXT (Dashboard Row 1)
REGIME COLOR LEGEND (Dashboard Row 2)
ALERTS
Macro pivot long fires when accumulation is detected (bull inflection). Macro pivot short fires when distribution is detected (bear inflection). Create alert: condition = this indicator, "Any alert() function call". Paste your webhook URL, set Open-ended, create. Alert payload is built into the script; works with any webhook receiver.
CREDITS
Advance/Decline gradient function: LucF 指标
指标
