Volatility Jump DetectorVolatility Jump Detector
This tool marks structurally significant price moves and tells you what kind of move each one was. It is an event detector, not a signal — it does not predict direction. It answers "did something real just happen here, and what was behind it?"
HOW JUMPS ARE DETECTED
Most "big candle" indicators compare a move to an ordinary volatility estimate, which has a circular flaw: a large jump inflates the very volatility measure used to judge it, so the biggest moves look less exceptional than they are.
This uses bipower variation (Barndorff-Nielsen and Shephard; Lee and Mykland), which builds the local volatility estimate from products of adjacent absolute returns. That construction is insensitive to a single large move, and it is computed excluding the current bar — so a jump cannot inflate its own threshold. A move is flagged when it exceeds a chosen multiple of that robust volatility, and the panel reports the exact sigma reading.
TWO INDEPENDENT CONTEXT AXES
INTENSITY — Is the recent jump rate elevated versus its own long-run baseline? Reported as a multiple with the underlying counts always visible, so you can see the sample behind the verdict. Note on method: a Hawkes branching-ratio estimate was implemented first and dropped. At a 4-sigma threshold real data yields only a handful of jumps per few hundred bars, far too few for count-variance statistics — it returned zero on every timeframe tested. A plain rate comparison is what sparse events can actually support, and below a minimum count the reading honestly says "insufficient" rather than printing a fabricated number.
VOLUME — Was the jump backed by participation, or did it slip through a thin book? A large move on heavy volume and the same move on nothing are different events. Auto-disables on instruments without a volume feed.
Optionally link the Risk & Levels Cockpit's exported levels, and jumps that fire through your invalidation level or at the point of control are flagged.
ON THE CHART
Direction-aware triangles mark each jump, colored by the intensity regime at that moment. The most recent jump is labelled with its sigma reading and volume tag. The background tints when jump intensity is elevated. The panel adapts to your chart theme and colors each row by meaning.
WORKS ON ANY MARKET AND TIMEFRAME
All lookbacks are in bars with no session, expiry, or clock anchors. Non-repainting: the robust volatility estimate excludes the current bar, and everything confirms at close.
LIMITATIONS
Not a signal and not investment advice. This marks events and describes them; it does not forecast what follows. An earlier version classified jumps as "ignition" versus "exhaustion" and measured the forward tendency of each — the measured continuation and reversal rates sat at base rate, so that classification was removed rather than kept as decoration. Jump detection depends on the threshold you choose; a lower threshold marks more moves and dilutes significance. Intensity needs a long baseline window because jumps are rare, and reports "insufficient" when the count is too low. Volume confirmation requires a volume feed.
CREDITS
Original implementation. Barndorff-Nielsen and Shephard bipower variation; Lee and Mykland (2008) jump test; jump-rate intensity comparison. Indicator
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. Indicator
Hurst Exponent Strategy [Fast + Weekly]## Overview
The **Hurst Exponent Strategy ** is an advanced quantitative tool that calculates the Hurst Exponent ($H$) using the Rescaled Range ($R/S$) analysis. Instead of tracking directional momentum or price overlays, this indicator measures the **statistical memory** and fractal dimension of financial time series to detect market regimes.
It helps traders identify whether an asset is trending, mean-reverting, or trapped in a state of pure noise (chaos).
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## The Mathematics of Market Regimes
The indicator evaluates the price action and plots values between 0 and 1, anchored to a theoretical center line of **0.5 (Random Walk)**:
- **$H > 0.60$ (Trend / Persistent):** The market possesses long-term memory. Price movements tend to be followed by movements in the same direction. Ideal for trend-following strategies.
- **$H < 0.45$ (Elastic / Anti-Persistent):** The market behaves like a rubber band (Mean Reversion). Price movements are consistently followed by reversals. Ideal for grid, mean-reversion, or range-bound strategies.
- **$0.45 \le H \le 0.60$ (Chaos / Random Walk):** The price action mimics a Brownian motion. Movements are random, noise is high, and directional edge is minimal.
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## Dual Timeframe Framework
To avoid fighting macro market structures, this script calculates two separate Hurst metrics simultaneously:
1. **Fast Hurst (Cyan Line):** Calculated on the current chart timeframe. It responds quickly to micro-regime shifts, pinpointing when a consolidation is breaking into a trend or expanding into chaos.
2. **Macro Hurst (Orange Line):** Multi-timeframe execution locked exclusively to the **Weekly ("W") chart**. It acts as a structural filter, keeping you aligned with the true macro nature of the asset.
Both exponents feature an optional built-in **Smoothing filter (SMA)** to remove high-frequency mathematical noise without heavily lagging the structural reading.
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## Real-Time Informative Legend
The top-right dashboard monitors the live mathematical output of both exponents:
- Displays exact numerical values down to 4 decimal places.
- Dynamically classifies the market state into **TREND** (Green), **ELASTICO** (Red), or **CAOS** (Gray) for instant visual confirmation.
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Disclaimer: This tool calculates mathematical probabilities based on historical fractal dimensions. It does not provide entry/exit arrows or guarantee profits. Use it as a regime filter alongside your preferred execution strategy. Indicator
Ichimoku Regime ClassifierIchimoku Regime Classifier is an open-source market regime filter that labels conditions as TREND UP, TREND DOWN, or VOLATILE.
This script is designed to solve a practical problem: many entries fail because traders apply the same setup in all environments.
Its purpose is to classify the current market context first, so strategy rules can be adapted to regime.
Methodology
The classifier uses Daily Ichimoku structure plus ADX trend-strength confirmation:
Bullish regime:
Price above the Kumo
ADX above threshold
Tenkan above Kijun
Chikou-style confirmation (current price vs past price)
Bearish regime:
Price below the Kumo
ADX above threshold
Tenkan below Kijun
Opposite Chikou-style confirmation
Volatile regime:
If neither bullish nor bearish set is fully confirmed
Why this combination
Ichimoku provides structural trend context, while ADX filters weak directional phases.
The combination aims to reduce false directional bias during choppy periods and keep regime logic explicit.
How to use
TREND UP: prioritize long-biased setups
TREND DOWN: prioritize short-biased setups
VOLATILE: reduce risk, be selective, or wait for structure
This indicator is intentionally minimal on-chart (single regime label) to keep output readable and unambiguous.
Limitations
Regime transitions can lag, especially after sharp reversals.
This tool is a context filter, not a standalone entry/exit system.
Open-source notice
Published as open source for transparency, review, and customization.
Educational content only. Not financial advice. Indicator
Indicator
Volatility Regime Cycle [AGPro Series]Volatility Regime Cycle
🌀 Overview
Volatility Regime Cycle classifies every bar on your chart into one of four distinct volatility phases: Contraction, Expansion, Climax, and Reset. Unlike traditional trend or regime indicators that focus on price direction, this tool maps the cyclical behavior of volatility itself — helping traders recognize whether the market is coiling, releasing, climaxing, or resetting. Each phase is detected through a multi-factor confluence engine and displayed with gradient background shading, transition markers, and S/R-style climax reaction zones. The framework is asset- and timeframe-agnostic: it adapts to crypto, forex, indices, stocks, and commodities on any timeframe.
💎 Unique Edge
Most volatility tools present a single metric (ATR, Bollinger Width, VIX proxy). Volatility Regime Cycle differs in structure and intent:
🔸 Phase-based classification, not just a reading — every bar is assigned to a named regime with a trader-actionable bias.
🔸 Multi-factor confluence scoring — five independent volatility inputs (ATR level, BB Width level, BB/KC squeeze, volume z-score, ATR rate-of-change) vote on the active phase. No single factor can dominate.
🔸 Winsorized normalization — outlier events (single extreme bars) do not compress the scale and hide current readings, a common flaw in simple percentile-based tools.
🔸 Climax Reaction Zones — each Climax event is preserved as an S/R-style rectangle with mid-pivot line, creating a memory of past volatility exhaustion levels that often act as future reaction areas.
🔸 Cycle-aware analytics — tracks historical phase durations and estimates current cycle progress based on rolling averages of past phases of the same type.
🔸 Phase-specific Trader Bias — panel translates the current regime into a plain-language bias (Breakout-watch, Momentum-favor, Reversal-risk, Cooldown).
This is not a Wyckoff phase tool, an Elliott counter, or a Dow-theory classifier. It is a pure volatility-cycle mapper, engineered from the ground up to stand apart from both classical cycle indicators and single-metric volatility meters.
🧠 Methodology
The engine runs three layers:
🔹 Factor Layer
• ATR Level — 14-period ATR, winsorized min-max normalized (5%-95% range) over a configurable lookback window.
• BB Width Level — Bollinger Band width as percent of basis, normalized identically.
• Squeeze State — true when Bollinger Bands are contained inside Keltner Channels (classic volatility compression).
• Volume Z-Score — standardized volume relative to its rolling mean and standard deviation.
• ATR Rate-of-Change — momentum of volatility itself.
🔹 Scoring Layer
Each of the four phases has its own scoring formula that weights the five factors differently. For each bar, all four phase scores are calculated in parallel, and the phase with the highest score is the candidate regime for that bar.
🔹 Confirmation Layer
To suppress whipsaw, the candidate phase must persist for a configurable number of bars (default 3) before replacing the active phase. A minimum phase duration lock additionally prevents rapid flips. Climax events include a de-duplication cooldown so that clustered climax bars produce a single marker rather than a cluster of overlapping labels.
Phase transitions are classified as major (Contraction→Expansion breakouts and Climax entries) or minor (all other routine changes). Only major transitions receive labels; minor changes are shown as subtle dotted lines to keep the chart clean.
🔔 Signals & Alerts
The script exposes alerts for every phase transition as well as two high-value composite events:
🔸 Any Phase Transition — fires whenever the active phase changes.
🔸 Entered Contraction / Expansion / Climax / Reset — fires for specific phase entries.
🔸 Contraction → Expansion (Breakout) — coil release event; of interest to breakout traders.
🔸 Climax Entry (Exhaustion Warning) — volatility peak event; of interest to mean-reversion and risk-management traders.
All alerts fire only on confirmed bar close to prevent intra-bar flip-flop.
⚙️ Key Inputs
🔹 Engine Settings — normalization lookback, ATR length, Bollinger/Keltner length and multipliers, volume z-score length, ATR rate-of-change length, confirmation bars, minimum phase duration.
🔹 Phase Thresholds — low volatility level, high volatility level, climax volatility gate, climax volume z-score threshold, climax de-dup cooldown.
🔹 Visuals — toggles for background shading, major transition labels, minor transition lines, volatility ribbon, current phase label.
🔹 S/R Zones — climax zones toggle, breakout zones toggle, maximum active zones, zone initial length, zone range lookback.
🔹 Panel — show/hide, location, Dark/Light theme, font size.
🔹 Label Sizing — font size for on-chart labels.
🔹 Alerts — per-event toggles.
📘 How to Use
🔸 Breakout traders: watch for Contraction phase on the panel with Trader Bias showing Breakout-watch. When the phase transitions to Expansion, a coil release is underway and a Breakout label is printed. Optional Breakout Zones can be enabled to preserve the breakout level as a retest reference.
🔸 Momentum / trend traders: ride the Expansion phase while Trader Bias reads Momentum-favor. Phase Duration and Cycle Progress on the panel give a sense of where the current momentum leg sits relative to historical averages.
🔸 Mean-reversion / exhaustion traders: a Climax label with Trader Bias Reversal-risk highlights volatility exhaustion. The Climax Reaction Zone drawn at each climax often behaves as a future reaction level and can be used as confluence with other reversal tools.
🔸 Risk managers: the Reset phase with Trader Bias Cooldown typically signals reduced market conviction and can be used to scale down position size until a new Contraction builds up.
🔸 Multi-timeframe reading: run the script on the higher timeframe for regime context and on the lower timeframe for entry timing.
Hover the panel header to see a statistics tooltip with average durations of each phase over the last completed cycles.
⚠️ Limitations & Transparency
🔹 The script does not predict future prices or issue buy/sell recommendations. It is a classification and context tool.
🔹 Phase detection is inherently lagging because it requires the confirmation window and minimum duration lock. This is a deliberate design choice to suppress whipsaw at the cost of some responsiveness.
🔹 Normalization uses a rolling lookback window; the first lookback bars after loading the script may show compressed or unstable readings while the window fills.
🔹 Cycle Progress is an estimate based on historical phase averages and may exceed 100% when the current phase runs longer than past cycles.
🔹 Climax and Reset scores rely partly on volume; on instruments with unreliable or missing volume feeds, volume-dependent factors will contribute less.
🔹 All visual elements are cosmetic and toggleable; they do not alter the underlying phase logic.
🛡️ Risk Disclosure
This indicator is a technical analysis tool. It is not a trading system, not a signal service, not financial advice, and not a guarantee of future results. Trading involves substantial risk of loss. Past market behavior does not predict future market behavior. Users are solely responsible for their own trading decisions, risk management, and position sizing. Always test any tool on your preferred instruments and timeframes with appropriate historical review before using it as part of a live decision-making process. Indicator
Regime Transition Intelligence [AGPro Series]Regime Transition Intelligence
Most regime scripts answer a single question: "what regime are we in right now?". Regime Transition Intelligence is designed to answer a different, more actionable set of questions: how long does this regime usually last, how close to its typical end is it, how likely is it to flip within the next N bars, and where does it historically go when it does flip. Instead of treating the current regime as a standalone snapshot, it builds a living, self-calibrating statistical profile of the symbol's own regime behavior and presents it in a compact on-chart dashboard.
The engine runs on three independent axes — Trend Strength (Kaufman Efficiency Ratio + ADX), Chop Risk (Choppiness Index + inverse trend), and Volatility (ATR% normalized over a user-defined lookback). Each axis is classified as LOW / MID / HIGH, either with fixed 33/67 thresholds or with an adaptive percentile rank engine that learns the symbol's own statistical envelope over a rolling window. The three axes are then combined into a discrete regime state: TREND, MIXED, or RANGE / CHOP.
🟦 Overview / What it does
Regime Transition Intelligence is a single-pane overlay indicator that continuously classifies the market into one of three regimes and then layers a full transition intelligence stack on top of that classification:
- A per-regime dwell-time distribution learned from the chart's own completed regime blocks
- A Bayesian-style flip probability that answers "how likely is a regime change within the next N bars, given the current age"
- A 3x3 transition matrix that ranks the most likely next regime with a secondary fallback
- A fatigue score comparing the current regime's age to its historical mean (FRESH / MATURE / EXTENDED)
- A confidence decay tracker that shows whether conviction is BUILDING, STABLE, or FADING within the current regime block
- A compact history ribbon showing the last completed regime blocks with their durations
- Higher-timeframe alignment with a SYNC / DIV indicator and a live beacon at the right edge of the chart
All of this is delivered inside a single configurable dashboard, a directional transition marker layer on the chart, optional regime tint and candle coloring, and a right-edge beacon summarizing the current state.
🟣 Unique Edge / Why it is not a basic mashup
Standard regime indicators report the current state and stop there. Regime Transition Intelligence adds six distinct statistical layers that together form a transition-aware view:
1. Dwell Time Statistics — the script stores every completed regime block in a rolling array (configurable depth) and continuously updates running mean, running variance, running max, and running count per regime code. Statistics are only shown after a minimum number of blocks per regime have been collected, so the user always knows when the sample size is still too small.
2. Exponential Hazard Flip Probability — the baseline flip probability uses P(flip within H bars) = 1 - exp(-H / mean), a standard survival-analysis construction assuming constant hazard. The result is then fatigue-adjusted: if the current age is far above the historical mean, the probability is boosted; if the regime has just started, the probability is damped. The final value is capped at 95% to avoid certainty claims.
3. Transition Matrix — a 3x3 counter records every observed regime transition and is read as a conditional distribution: "given the current regime ends, which regime is it most likely to move to, and what is the runner-up". Both the top candidate and the secondary candidate are displayed with their percentages.
4. Fatigue Score — the ratio of the current age to the historical mean is bucketed into three zones (FRESH, MATURE, EXTENDED) using user-configurable thresholds. It tells the user whether the current regime is still in its early lifecycle or already past its typical end.
5. Confidence Decay Tracker — conviction in the current regime is sampled at the start of each new block and compared to the current conviction. The delta is classified as BUILDING, STABLE, or FADING, which gives an early read on whether the regime is strengthening or losing its grip.
6. History Ribbon — the last N completed regime blocks are compressed into a single compact line such as "C2·M4·C8·M1·M7*", where letters are regime codes and numbers are bar counts, with the current block marked by an asterisk. It gives immediate context on recent regime rhythm at a single glance.
None of these layers is a repackaged classic indicator. They are built on top of a trend / chop / volatility engine but deliver information that is categorically different from a simple "regime yes / no" readout.
🟢 Methodology / Conceptual data flow
1. Feature extraction. Kaufman Efficiency Ratio (net move over lookback divided by summed absolute moves) and normalized ADX are combined into a trend score. The Choppiness Index is normalized against its operating range and blended with inverse trend to produce a chop score. ATR as a percentage of price is normalized against its own lookback min/max to produce a volatility score.
2. Classification. Each score is mapped to LOW / MID / HIGH using either fixed thresholds (Static mode) or percentile rank over an adaptive lookback (Adaptive mode). The three bands are combined into a discrete regime state: TREND when trend is HIGH and chop is LOW, RANGE / CHOP when chop is HIGH, and MIXED otherwise.
3. Block tracking. Every time the regime state changes on a confirmed bar, the previous block is closed: its duration is pushed to a rolling history array and added to the running sum / sum-of-squares / count / max for its regime code. When the history array exceeds its configured depth, the oldest block is popped and its contribution is subtracted from the running totals, which keeps the statistics adaptive and non-expanding.
4. Transition matrix update. When a block closes into a new regime, the 3x3 counter is incremented at the corresponding cell, and the row total is incremented. The conditional distribution for the current regime is read from its row at display time.
5. Statistical outputs. Mean dwell, fatigue ratio, exponential-hazard flip probability, fatigue-adjusted flip probability, top and secondary next regimes, and confidence delta are all derived from the running state and rendered into the dashboard.
6. Higher-timeframe alignment. The same three-axis engine is run on a user-selected higher timeframe via request.security and compared against the current-timeframe regime; the result appears as SYNC or DIV in the header and as an optional HTF row in the dashboard.
🔔 Signals & Alerts / Interpretation
Regime Transition Intelligence is a state-mapping and statistical context tool rather than a directional buy / sell engine. The main on-chart events are:
- Regime Shift — fires when the regime state changes on a confirmed bar
- High Flip Probability — fires when the fatigue-adjusted flip probability crosses a high threshold
- Regime Fatigue Extended — fires on the transition into the EXTENDED fatigue zone
- Confidence Fading — fires on the transition into the FADING confidence zone
How to read the panel:
- Summary + Age tells the user which regime is active and how long it has been active.
- Dwell Context compares the current age to the historical mean in the form "age / mean · % of typical lifespan".
- Fatigue summarizes that comparison as FRESH, MATURE, or EXTENDED.
- Flip Probability reports the statistical odds of a regime change within the user-defined horizon.
- Next Likely names the most probable next regime with its percentage and a secondary fallback.
- Confidence and Conf Decay together tell the user whether the current read is reliable and whether conviction is rising or fading.
- History gives quick situational awareness of recent regime rhythm.
None of these rows should be interpreted as a trade instruction. They are a context layer meant to be combined with the user's own structure and entry framework.
🎛️ Key Inputs
Regime Engine Core — Trend Persistence Length, DMI/ADX Length, Chop Length, ATR Length, Volatility Normalize Lookback.
Adaptive Boundaries — Band Classification Mode (Adaptive / Static), Adaptive Lookback, Adaptive Low / High Percentile.
Transition Intelligence — Regime History Depth, Flip Probability Horizon, Min Blocks Before Stats Activate, Fatigue Fresh / Extended thresholds.
HUD — Display Mode (PRO / MINIMAL), HUD Position, Text Size, transparency controls, individual row toggles, history ribbon length.
Add-ons — Chart Regime Tint, Regime Candle Coloring (Soft / Strong), HTF Peek Timeframe, Transition Markers (location, cooldown, stagger, size, ATR offset), Live Regime Beacon (position, size, stats toggle).
🧭 How to use
1. Add the script to any chart and timeframe. The engine is tuned to work from 15m up to Daily; very low timeframes on illiquid instruments can produce unstable regime blocks and are not the intended use case.
2. Give the script time to collect blocks. Statistics stay in N/A until the configured minimum number of completed blocks per regime has accumulated. On a fresh chart or an illiquid instrument this is expected behavior, not a bug.
3. Read the dashboard top-down. Start with the three axis rows to understand the current market shape, then move to Summary and Age to see what is active and for how long, then use Dwell / Fatigue / Flip / Next Likely to place the current regime inside its historical distribution, and finally use Conf Decay and HTF to sanity-check reliability and alignment.
4. Treat EXTENDED fatigue and high flip probability as context, not as a reversal signal. Regimes can remain in the EXTENDED zone for a while before actually flipping; the statistical profile is descriptive, not deterministic.
5. Combine with structural context. The script does not know about support / resistance, order blocks, or news. It only knows about the symbol's own regime rhythm. Use it as a regime-aware filter on top of the user's existing framework.
⚠️ Limitations & Transparency
This is not a strategy and not a complete trading system. It does not predict price direction and does not generate buy or sell signals. All statistics are estimated from a rolling history of the chart's own regime blocks, so they are sensitive to the chosen engine parameters, the timeframe, and the symbol; different timeframes and different instruments will produce different statistical profiles, and that is by design.
The exponential-hazard flip probability assumes a constant hazard within the current regime, which is a simplification. Real-world regime durations are not perfectly memoryless and the fatigue multiplier is a heuristic correction, not a formal model. The probability is capped at 95% on purpose, because even a heavily aged regime cannot be considered a certainty and the script deliberately avoids certainty language.
The transition matrix is read as a conditional frequency over completed blocks; it is informative about the symbol's own past behavior and should not be interpreted as a forward-looking forecast. Very small samples produce unstable conditional probabilities, which is why stats stay in N/A until a minimum number of blocks is collected.
Regime classification itself reacts to confirmed bars and can change as new data arrives, which is expected for any regime filter. Users who prefer fully non-repainting alerts should rely on the barstate.isconfirmed-gated alert conditions provided.
📜 Risk Disclosure
Trading involves substantial risk of loss and is not suitable for every investor. Past performance is not indicative of future results. This indicator is provided for educational and analytical purposes only and should not be interpreted as financial advice, an investment recommendation or a solicitation to trade. Always combine multiple forms of analysis, manage position size responsibly, and never risk capital you cannot afford to lose. Indicator
Value Migration Bands [AGPro Series]Value Migration Bands
Value Migration Bands is a chart-first value migration engine that visualizes where the market's accepted-value region has been drifting over time. Instead of a single moving average, it builds a three-layer band (upper / middle / lower) from a rolling percentile window of typical price, then classifies the current environment as Rising, Flat, or Falling Value using an ATR-normalized slope of the migration midline. The result is a scale-invariant, regime-aware view of how "fair value" migrates across trending and ranging conditions — on crypto, equities, indices, forex and futures alike.
🔷 OVERVIEW
Most band-style indicators build their envelope from volatility (Bollinger, Keltner, Donchian). Value Migration Bands is built from acceptance — the region where price has actually spent its time during the lookback, captured as a percentile window of typical price (hlc3). The outer bands mark the edges of that accepted-value region. The midline marks its core. When the whole region drifts upward, the market is accepting higher prices (Rising Value). When it drifts downward, lower prices are being accepted (Falling Value). When it stays level, participants are agreeing on a stable range (Flat Value).
This reframes the classic "trend vs range" question in terms of value migration, which is a cleaner structural signal than price slope alone. You see not just where price is going, but where the market's center of gravity is going.
🔶 UNIQUE EDGE
Value Migration Bands is distinct from moving-average envelopes, volatility bands and standard channels in several structural ways:
• Percentile-based construction — the band is a percentile window of typical price, not a standard deviation or ATR multiple. This directly captures acceptance, not dispersion.
• Three-state migration classification — Rising / Flat / Falling Value, driven by an ATR-normalized slope of the midline. The classification is scale-invariant, so the same sensitivity works across BTC, SPX, EURUSD, gold and small-cap equities without retuning.
• Regime-aware event markers — Reclaim and Lost markers are filtered by the current regime. Reclaim events are suppressed when the market is in Falling Value; Lost events are suppressed in Rising Value. You only see the events that matter for the active regime.
• Strict Value Filter — during extreme compression, the indicator refuses to classify a regime until the band is meaningfully wide relative to ATR. This prevents false regime flags in low-volatility micro-bands.
• Distance + cooldown gating — new event markers require a minimum ATR distance from the previous event and a minimum bar spacing, producing a clean chart even on long histories.
🔷 METHODOLOGY
Band construction:
1. Typical price (hlc3) is sampled across a configurable lookback window (Band Length).
2. Two percentiles are computed — a lower percentile and an upper percentile, selected by the Band Width Mode (Tight, Balanced, Wide).
3. The midline is the mean of those two percentiles.
4. Light EMA smoothing (adaptive to Band Length) stabilizes the visual without adding structural lag.
Regime classification:
1. The midline slope is measured over a rolling window (adaptive to Band Length).
2. The slope is normalized by ATR(14) to make the threshold scale-invariant.
3. A user-controlled Migration Slope Sensitivity divides the normalized slope into Rising / Flat / Falling bands.
4. A 2-bar confirmation layer prevents rapid regime flipping during transitions.
Event detection:
• Reclaim — price re-enters the band from below after previously being lost.
• Lost — price falls out of the band after previously being inside.
Both pass a regime gate, an ATR-distance gate and a bar-cooldown gate before being plotted or alerted.
🔶 SIGNALS & ALERTS
Four built-in alert conditions:
• Value Band Shifted Up — fires when the confirmed regime transitions into Rising Value.
• Value Band Shifted Down — fires when the confirmed regime transitions into Falling Value.
• Band Reclaimed — fires when price re-enters the accepted-value region (regime-gated).
• Band Lost — fires when price falls out of the accepted-value region (regime-gated).
Alerts and on-chart markers share identical gating, so the alert log and the chart stay in sync.
🔷 KEY INPUTS
Band Engine:
• Band Length (default 100) — lookback for the percentile window.
• Band Width Mode — Tight, Balanced, Wide. Selects the percentile pair.
• Strict Value Filter — requires a minimum band width vs ATR before classifying a regime.
• Migration Slope Sensitivity (default 0.5) — threshold between Rising / Flat / Falling.
Visuals:
• Show Midline, Show Band Fill, Active State Label, Show Reclaim / Lost Markers, Show Info Panel.
• Panel Location — six options (Top / Middle / Bottom × Right / Left).
• Panel Font Size and Label Font Size — default Normal.
Colors:
• Rising Value Color, Falling Value Color, Flat Value Color.
• Band Fill Opacity.
Alerts:
• Individual toggles for the four alert conditions above.
🔶 HOW TO USE
Structural reading:
• Rising Value — treat Reclaim events as continuation confirmations, not counter-trend signals. Expect pullbacks to the midline to be bought.
• Falling Value — treat Lost events as continuation confirmations. Expect rallies back to the midline to be sold.
• Flat Value — neither regime is active. The band can be used as a range reference; directional events are suppressed because they do not carry regime confirmation.
Location reading:
• Inside Band — price is trading within the accepted-value region. This is the default state.
• Above Band — price is trading above accepted value. In Rising Value, this is constructive; in Falling Value, it is a rally to be evaluated.
• Below Band — price is trading below accepted value. In Falling Value, this is the dominant state; in Rising Value, it is a dip.
Timeframe guidance:
• 1H–4H — best balance for swing use with the default Band Length of 100.
• 15m–1H — reduce Band Length to 40–60 for intraday use.
• Daily — Band Length 100 gives a structural multi-month migration view.
Pairing suggestions:
• Higher-timeframe VMB for bias, lower-timeframe execution tools for entry.
• Combining with volume-based or anchored-VWAP tools can confirm whether value migration is participation-backed.
🔷 LIMITATIONS & TRANSPARENCY
• This is an analytical visualization tool, not a strategy. It does not backtest, does not place orders and does not generate buy / sell recommendations.
• Regime classification is based on historical midline slope. Like all rolling measures, it is a lagging read of structure — it describes what has been happening, not what will happen.
• During abrupt regime changes, the 2-bar confirmation layer introduces a small delay by design, trading reactivity for stability.
• Percentile bands are descriptive of past acceptance. Future acceptance may differ, especially around news events, regime breaks and illiquid sessions.
• The Strict Value Filter can force a Flat reading during extreme compression even when a visual direction appears present; this is intentional and protects against false regime flags.
🔶 RISK DISCLOSURE
This indicator is published for educational and analytical purposes. It is not financial advice, not a trading recommendation and not a guarantee of performance. Trading and investing involve substantial risk, including the risk of total loss. Past behaviour of any instrument does not guarantee future results. Users are solely responsible for their own decisions and should perform their own due diligence, including independent risk management and position sizing.
Published as open-source under the Mozilla Public License 2.0. Feedback, questions and discussion are welcome in the comments.
Indicator
Volatility Shape Classifier [AGPro Series]Volatility Shape Classifier
🔹 Overview
Volatility Shape Classifier is a context and diagnostics tool that does not stop at telling you whether volatility is high or low. Instead it classifies the SHAPE of that volatility on every bar — Smooth, Chaotic, Choppy, Drift, or Dead — using three independent dimensions combined into a single regime read. The result is a continuous visual narrative made of a subtle background tint, throttled transition badges, and a compact metrics panel.
It is designed to sit on your chart as a pure awareness layer. It does not generate buy or sell signals and it is not a trading strategy.
🔷 Unique Edge
Most volatility tools compress the market into one axis — high vs low (ATR, Bollinger Band Width), or trend vs range (Choppiness Index, ADX). They answer half of the question.
This script asks three questions at once and fuses the answers:
1. Magnitude — is ATR above or below its own long baseline?
2. Smoothness — are bar-to-bar moves consistent in size, or erratic?
3. Directional Consistency — do bars point the same way, or cancel each other?
Only the combination of these three can distinguish a controlled trend run (Smooth) from a violent whipsaw (Chaotic) from a wide directionless thrash (Choppy) — all three of which can show identical ATR readings. That shape distinction is the core value this script adds, and it is the gap left by standard volatility and chop indicators.
🔶 Methodology
Engine layer (per bar):
• Volatility Level = ATR(volLen) / SMA(ATR, volLen * 3)
• Smoothness = StDev(|close − close |) / SMA(|close − close |) over volLen
• Direction = |sum(close − close )| / sum(|close − close |) over volLen
Classification layer maps the three readings into six mutually exclusive codes:
0 — Forming (warm-up / in-between space, no tint)
1 — Expansion · Smooth (high vol, low CV, directional)
2 — Expansion · Chaotic (high vol, high CV)
3 — Expansion · Choppy (high vol, low direction)
4 — Low-Vol · Drift (low vol, low CV, mild direction)
5 — Low-Vol · Dead (low vol, low CV, no direction)
Stability layer applies a configurable Confirmation Bars window so a new shape must persist for N consecutive bars before the chart commits to it. This prevents single-bar flicker. Between-state readings do not reset the current shape, they hold it — avoiding the classic "blink to neutral" problem of switch-based classifiers.
🔸 Signals & Alerts
Four alert conditions are published:
• Shape Shifted to Smooth Expansion
• Shape Shifted to Chaotic Expansion
• Shape Shifted to Choppy Expansion
• Shape Collapsed (any expansion state falling into low-vol Drift or Dead)
Alerts fire only on confirmed shape transitions and only on bar close, so repaint on the signal bar is not a concern.
🔹 Key Inputs
• Volatility Length — window for ATR, smoothness, and direction (default 20)
• Confirmation Bars — persistence requirement before committing to a new shape (default 3)
• Badge Cooldown — minimum bars between visible badges (default 15; tint updates continuously regardless)
• Panel Position / Size — six anchor points, four size presets
• Badge Font Size — four size presets
🔷 How to Use
• Use the SHAPE read as a setup filter, not as the signal itself. Smooth Expansion is where trend-following tools tend to perform well. Chaotic and Choppy Expansion are where they tend to fail even when the raw volatility reading looks attractive.
• The Drift state often precedes an expansion in the direction of the drift.
• The Dead state is a compression warning — a shape collapse alert from Expansion into Dead is a common precursor to a fresh expansion move in either direction.
• Pair with your own entry logic (structure, moving averages, volume). This tool answers "what kind of market am I in right now?" — it does not answer "where do I enter?"
🔶 Limitations & Transparency
• Thresholds (1.15x / 0.70x / 0.80 / 1.10 / 0.18) were tuned on crypto and FX data across 15m to 1D timeframes. Very illiquid instruments and very low timeframes (< 5m) may require a longer Volatility Length.
• Shape classification is inherently backward-looking (it reads the last volLen bars). It describes the character of recent volatility, not future volatility.
• The script is a context layer. It is not a strategy and should not be used in isolation for trade decisions.
• Past behavior of a shape does not guarantee future behavior.
🔸 Risk Disclosure
This indicator is an educational and analytical tool. It does not constitute financial advice, trade recommendations, or a signal service. All trading involves risk. You are solely responsible for your own trading decisions. Indicator
Delivery Regime Map [AGPro Series]Delivery Regime Map
🔹 Overview
Delivery Regime Map classifies the market's delivery character into four distinct regimes — Balanced, Directional, Fragmented, and Exhausted — giving traders instant context on whether the tape is trending with conviction, consolidating, breaking into volatile chop, or fading after an extended move. Rather than asking "is this bullish or bearish?", DRM answers a more useful question: "what kind of market am I in, and what kind of setup is appropriate here?"
The indicator overlays a soft state ribbon across the chart, prints confirmed regime shift labels at the moment of transition, and maintains a compact status panel with the active regime, a composite conviction score, regime duration, and time since the last shift. All outputs are confirmed on bar close with dwell-based hysteresis to suppress noise.
🎯 Unique Edge
Most regime or trend-strength tools collapse the market into a single linear axis (strong ↔ weak, bullish ↔ bearish). Delivery Regime Map is categorical, not linear — it identifies the qualitative character of price delivery by fusing four independent dimensions:
• Displacement quality (how much of each bar's range is body vs. wick)
• Directional persistence (close-to-close consistency + EMA slope alignment)
• Continuity (same-side runs penalized by gap noise)
• Range expansion (current range normalized by ATR baseline)
These dimensions combine into a composite score, but the regime classification uses banded thresholds with hysteresis — meaning a Directional tape must decisively lose its edge before flipping to Fragmented or Exhausted. This produces sparse, high-conviction transitions rather than the constant flipping typical of single-value strength meters.
⚙️ Methodology
The engine computes five rolling metrics across a user-defined window (default 20 bars):
1. Displacement Quality — |close − open| / range, smoothed. High values mean strong, decisive bars with minimal wick rejection.
2. Directional Persistence — average signed close direction plus an EMA slope-alignment check. Rewards tapes that move one way without reversing.
3. Continuity — the proportion of consecutive same-side candles, penalized by an average gap-size term (opens far from prior closes indicate fractured delivery).
4. Range Expansion — current range vs. ATR baseline, clipped to . High expansion combined with low continuity flags Fragmented tapes.
5. Exhaustion Proxy — the decay rate of displacement quality after a period of high persistence. Triggers near trend terminations where bars shrink while direction lingers.
A classifier selects the active regime by priority (Directional → Exhausted → Fragmented → Balanced), and a dwell-bar confirmation (default 5 bars, or 8 under Strict mode) plus a minimum-gap filter (default 10 bars) prevent whipsaw transitions.
🚦 Signals & Alerts
Four alert conditions are built in, each firing only on a confirmed regime shift:
• Regime shifted to Directional — conviction is rising; the tape is trending
• Regime shifted to Fragmented — wide, disconnected bars; chop risk elevated
• Regime shifted to Exhausted — prior trend is losing steam; mean-reversion risk
• Regime shifted to Balanced — low-conviction state; breakout potential building
All alerts include the ticker and interval in the message payload.
🎛️ Key Inputs
• Regime Window (8–60) — length of the measurement window
• Regime Sensitivity (Low / Normal / High) — hysteresis band width
• Strict Classifier — extends dwell requirement from 5 to 8 bars
• Minimum Bars Between Shifts — anti-chop spacing filter
• Show State Ribbon / Regime Shift Labels — visual toggles
• Panel Position + Font Size — 6 anchor positions, 5 size options
• Label Font Size — matches user's chart density preference
Every input carries an inline tooltip explaining its behavior and tradeoffs.
📚 How to Use
• Use Directional regimes to favor trend-following entries and trailing stops
• Use Balanced regimes to prepare for breakouts; volatility compression often precedes expansion
• Use Fragmented regimes as a caution flag — reduce size, widen stops, or stand aside
• Use Exhausted regimes to tighten trailing stops on open trend positions; the edge may be fading
DRM is designed to be asset-agnostic and timeframe-agnostic. On lower timeframes (1m–15m), consider Strict mode and a larger minimum-gap value. On daily charts, defaults typically work well. Combine with any entry framework — order blocks, breakout levels, VWAP reclaims — as a regime filter that answers "should I even be looking for a setup here?"
⚠️ Limitations & Transparency
• The classifier is reactive, not predictive — it confirms regime changes on close, so a Directional label appears a few bars after the trend has begun. This is by design: dwell confirmation is the primary noise filter.
• Regime definitions are categorical interpretations of price statistics. They are not forecasts.
• The composite score reflects regime conviction, not directional bias. A high score in Fragmented means "confidently choppy", not "confidently bullish".
• This indicator is not a strategy. It produces no entry signals, no take-profit targets, and no stop-loss levels. It is a market-context tool intended to be combined with a trader's existing framework.
• Past regime behavior does not guarantee future regime behavior. Market character can change abruptly on news or macro events.
📜 Risk Disclosure
This indicator is published for educational and analytical purposes only. It does not constitute financial advice, a trading recommendation, or an offer to buy or sell any instrument. Trading and investing carry risk of loss, and past performance does not guarantee future results. Users are solely responsible for their own decisions and should consult qualified professionals before committing capital. Indicator
MTF Trend Agreement Map [AGPro Series]MTF Trend Agreement Map
🔹 **Overview**
MTF Trend Agreement Map is a multi-timeframe alignment engine that reads the trend across five timeframes at once and distills the result into a single transparent agreement score. Instead of forcing you to flip between charts, the map tells you, on every bar, how many timeframes agree, which side wins, and whether the market is in a locked regime, a forming trend, or a conflict phase. It is built for swing traders, HTF-bias scalpers, position traders, and anyone who uses top-down analysis as part of their process.
🔸 **What Makes It Different**
Most MTF indicators show a single method (usually a moving-average cross) repeated across timeframes, which means five rows that all agree with each other by construction. This map does something different: for each timeframe it runs three independent methods — an EMA regime filter, a pivot-based market-structure read (HH/HL vs LH/LL), and a normalized momentum slope — and blends their individual votes into the final score. You see not only the agreement across timeframes but also the agreement across methods, which exposes weak or borderline regimes that a single-method tool would quietly hide.
🔺 **Methodology**
• EMA Trend: a timeframe is bullish when EMA50 is above EMA200 and price is above EMA50; bearish on the mirror condition; neutral otherwise.
• Market Structure: confirmed pivots are tracked in real time. A timeframe is bullish while the last two confirmed swings form higher highs and higher lows, bearish on lower highs and lower lows.
• Momentum Slope: the change in linear regression across a configurable lookback, normalized by ATR so that fast and slow assets are comparable.
• Consensus per timeframe: each active method casts a vote; bulls minus bears determines the row's net direction and strength.
• Overall alignment: bull and bear votes are summed across all active timeframes; the dominant side's share defines the agreement percentage.
◆ **Three-State Regime Engine**
• **LOCKED** — agreement above the strong threshold (default 80%). High-conviction regime, continuation-friendly, background tint activates.
• **TRENDING** — agreement between 50% and the strong threshold. Directional bias forming but not yet fully aligned. Trade with reduced size or wait for confirmation.
• **SPLIT** — agreement below 50%. Timeframes are in conflict, no majority side. Classic chop phase, favors mean-reversion strategies or standing aside.
🔔 **Signals & Alerts**
• Regime Lock (Bull or Bear): fires the first bar agreement crosses above the strong threshold while one side dominates. Designed as a continuation trigger, not a reversal signal.
• Chop / Conflict: fires when no side holds the majority, a classic filter for mean-reversion systems or a stand-aside cue for trend traders.
• Both generic and directional alertcondition() hooks are exposed so you can wire the map into automations.
⚙️ **Key Inputs**
• Core Engine: toggle any of the three methods on or off, and tune the pivot length and momentum lookback independently.
• Timeframes: four user-selected timeframes plus an optional Current row that auto-adapts to the chart TF. If the chart TF matches any selected TF, the Current row is hidden automatically to avoid double-counting.
• Panel: six location presets, four text sizes (default Normal), dark or light theme, optional per-method breakdown row.
• Background Tint: enable or disable, set the strong-alignment threshold (50–95%) and control transparency (70–99) to keep the chart premium.
📖 **How to Use**
• Top-down confirmation: take trades on your execution timeframe only when the higher rows in the map agree with your thesis.
• Regime filter: enable Regime Lock alerts to catch moments when the full map snaps into alignment — these are typical continuation windows.
• Conflict filter: when the map prints SPLIT, widen stops, reduce size, or step aside; trend strategies historically underperform during these phases.
• Method debugging: turn on the per-method breakdown to see which methods are driving the score and which are fighting it.
⚠️ **Limitations & Transparency**
• All timeframe values are non-repainting at bar close (lookahead is disabled), but intrabar values can update until the parent bar closes — this is expected MTF behavior.
• Market Structure requires enough history on each timeframe to confirm two swings; on very young assets or short charts the structure vote may be neutral until pivots print.
• The map is a context tool, not a standalone entry system — combine it with your own execution logic, risk management, and bias.
📌 **Risk Disclosure**
This script is provided for educational and analytical purposes only. It does not constitute financial advice, a recommendation, or a solicitation to trade any instrument. Markets involve substantial risk and past behavior does not guarantee future results. Always do your own research and manage risk responsibly. Indicator
Indicator
AG Pro KAMA Efficiency Zones [AGPro Series]AG Pro KAMA Efficiency Zones
Overview
KAMA stands for Kaufman’s Adaptive Moving Average.
AG Pro KAMA Efficiency Zones is built around KAMA not as a simple trend-following line, but as an adaptive market reference for evaluating how efficiently price is moving. Instead of focusing only on direction, the script is designed to classify the quality of directional travel and separate cleaner movement from noisier, lower-clarity conditions.
The core idea is straightforward: markets do not move with the same quality all the time. Some phases show relatively efficient directional travel where price stays organized around an adaptive path. Other phases become mixed, unstable, or reversion-prone, where direction weakens and noise becomes more dominant. This script is designed to map those changes visually through adaptive KAMA-based zones, state labels, and a compact panel that summarizes the current condition.
This makes the tool structurally different from a basic moving average overlay. The objective is not to present KAMA as a one-line signal source. The objective is to use KAMA as the center of a state engine that helps users distinguish efficient trend phases from transitional or noisy environments.
What this script does
AG Pro KAMA Efficiency Zones evaluates price behavior around a Kaufman’s Adaptive Moving Average and organizes that behavior into visual market states. It does this by combining adaptive smoothing, slope behavior, distance from KAMA, and persistence around the KAMA path.
The result is a chart framework that can help answer questions such as:
• Is price moving in an efficient bullish or bearish path?
• Is the market entering a mixed transition phase?
• Has movement quality deteriorated into a noisier reversion-prone environment?
• Is the adaptive path becoming stronger, weaker, or less stable?
By turning those questions into zones and state-based chart feedback, the script aims to improve context rather than replace judgment.
Unique edge
The distinguishing feature of this script is that it does not treat KAMA as a standard moving average. Instead, it uses KAMA as the center of a layered efficiency model.
That model focuses on the quality of movement, not just the existence of movement.
Many tools emphasize momentum, volatility, volume pressure, or overbought/oversold conditions. This script is designed for a different purpose. It is a movement-quality map. It attempts to show whether price is traveling in a relatively efficient path or whether that path is degrading into a noisier condition where directional clarity may be weaker.
This means the script is less about predicting a move and more about classifying the environment in which a move is taking place.
How it works
The script begins with KAMA, or Kaufman’s Adaptive Moving Average. KAMA is useful because it adapts its responsiveness according to market behavior. In cleaner directional phases it can respond more quickly, while in noisier phases it can become more conservative. That makes it a practical centerline for an efficiency-based state model.
On top of KAMA, the script evaluates several components:
1. Efficiency behavior
The script measures how directly price is moving relative to its recent path. This helps estimate whether price action is acting efficiently or becoming more erratic.
2. KAMA slope behavior
The slope of KAMA is normalized so that directional angle can be evaluated in a more consistent way. Stronger and more persistent slope behavior supports higher-quality trend classifications.
3. Price-to-KAMA relationship
Price position around KAMA helps determine whether movement is aligned with the adaptive path or drifting around it without clear structure.
4. Persistence
The script also looks at how consistently price remains on one side of KAMA. That persistence can help distinguish a more stable move from a weaker and less durable one.
These components are blended into a composite efficiency model that drives the active state and the corresponding visual zone.
States and zones
The script classifies market behavior into four main states:
Efficient Bull Trend
This state reflects a comparatively organized bullish environment where price and adaptive slope are aligned in a cleaner upward path.
Efficient Bear Trend
This state reflects a comparatively organized bearish environment where price and adaptive slope are aligned in a cleaner downward path.
Transition
This is a mixed condition. Direction may be weakening, changing, or failing to achieve the quality required for an efficient trend classification.
Noise / Reversion
This state reflects lower movement quality, weaker slope behavior, or a more unstable relationship between price and the adaptive path.
The visual zone structure is designed to reinforce those classifications on the chart. Instead of using only one line, the script builds layered KAMA-centered bands so the user can read not only direction, but also how structured or fragile the current condition may be.
How to read the chart
The KAMA line is the adaptive spine of the script.
The outer and inner bands represent zone structure around that adaptive path. In stronger trend states, the script increases the visual emphasis of the KAMA path and its supporting zone layers. In weaker or more mixed conditions, the script softens those visuals and allows the chart to communicate reduced clarity.
State labels appear when the script confirms a meaningful shift in condition. These labels are intended to highlight a change in market state, not to promise a trade outcome.
The on-chart panel summarizes the active reading using fields such as State, Efficiency, Score Band, Adaptive Bias, Active Zone, and Stability. This gives the user a compact interpretation layer without requiring every decision to be made directly from raw chart inspection.
Key inputs
KAMA Efficiency Length
Controls the lookback used in the KAMA efficiency logic. Lower values react faster. Higher values smooth more noise.
KAMA Fast Response and KAMA Slow Response
Define the adaptive responsiveness range of the KAMA engine.
ATR Length
Used to normalize slope and distance so the tool behaves more consistently across different symbols and volatility conditions.
KAMA Slope Lookback
Controls how the script measures directional slope over time.
Persistence Length
Influences how much consistency price must show around KAMA before a move is treated as more structured.
Efficient Trend Threshold and Noise Threshold
These thresholds help determine when the model classifies a move as higher quality or lower quality.
Zone Band ATR Width
Adjusts the width of the adaptive visual zone.
State Hold Bars
Helps reduce rapid state flipping by requiring a condition to persist before the active state changes.
Panel Font Size and Label Size
Allow visual customization for different chart layouts and monitor sizes.
Alerts
The script includes state-oriented alerts intended to notify the user when market condition changes. These are designed around state transitions and movement-quality shifts rather than promotional “buy now” style messaging.
Examples include bullish and bearish efficiency shifts, transition detection, noise-zone detection, efficiency recovery, efficiency breakdown, and trend strengthening.
Alerts should be interpreted as contextual information. They are intended to support review and analysis, not to function as a standalone decision system.
What this script is not
This script is not a guarantee engine.
It does not predict future price with certainty.
It does not eliminate risk.
It is not a substitute for broader market structure analysis, execution planning, or risk management.
It should not be treated as a self-sufficient entry/exit system without additional confirmation and user judgment.
Limitations and transparency
All adaptive models are sensitive to parameter choices. Changing responsiveness, thresholds, smoothing, or persistence settings can materially affect the way states appear on the chart.
Because the script is state-based, some shifts will naturally occur after the earliest turning point in price. That is part of the tradeoff involved in using confirmation and persistence to reduce noise.
In highly erratic or news-driven conditions, classification can also become less stable. During those periods, transition or noise-oriented readings may occur more often, and users should interpret the visual output in that context.
The script is best viewed as an analytical framework for movement quality and adaptive context, not as a promise of directional success.
Practical use cases
Users may find the script useful for:
• separating cleaner trend phases from mixed or unstable phases
• filtering chart environments before applying another workflow
• evaluating whether direction is gaining or losing efficiency
• adding adaptive context to discretionary analysis
• comparing how different symbols behave around a KAMA-centered efficiency structure
Risk disclosure
This script is for analytical and educational use. It does not provide financial advice, investment advice, or guaranteed outcomes. Market conditions can change quickly, and any indicator can produce false, delayed, or incomplete signals. Users remain responsible for their own decisions, validation process, and risk management.
In short, AG Pro KAMA Efficiency Zones is designed to help read the quality of movement, not just the direction of movement. It uses KAMA as an adaptive reference point and converts that reference into a structured zone and state model so users can assess whether price behavior appears efficient, transitional, or noisy.
Indicator
Indicator
Market Regime AnalyzerStatistical regime detection with forward-looking transition probabilities. Combines drift testing, variance ratios, and volume delta to classify markets into 5 regimes and quantify transition probabilities.
What Regime Are We In, and What's Likely Next?
That's the question this indicator answers with statistical rigor and forward-looking probabilities.
The Problem:
Most traders classify regimes arbitrarily: "Bull if price > 200 MA" or "Bear if RSI < 30." These rules ignore statistical significance, volume confirmation, and mean reversion patterns. The result? Late entries, false signals, and confusion when markets transition.
The Solution:
Market Regime Analyzer combines drift detection, variance ratio testing, and volume delta analysis to classify markets into 5 distinct regimes. Then it calculates the probability of transitioning to each regime based on historical patterns.
The Benefit:
Know not just where you are, but where you're likely going - with probabilities, not guesses.
The Five Market Regimes
🟢 Strong Bull (Regime 1)
- Statistically significant upward drift (t-stat > 1.96)
- Strong buying pressure (volume delta > 0.3)
- No mean reversion detected
- **Trade:** Trend-following strategies, ride the momentum
🟢 Weak Bull (Regime 2)
- Upward drift present
- BUT weak volume OR mean reversion detected
- **Trade:** Reduce position size, tighten stops, prepare for consolidation
⚪ Consolidation (Regime 3)
- No statistically significant drift
- Mixed volume signals
- Mean reversion likely present
- **Trade:** Range-trading, avoid trend-following systems
🔴 Weak Bear (Regime 4)
- Downward drift present
- BUT weak volume pressure
- **Trade:** Cautious shorts, reduce exposure, prepare for bounce
🔴 Strong Bear (Regime 5)
- Statistically significant downward drift (t-stat < -1.96)
- Strong selling pressure (volume delta < -0.3)
- No mean reversion detected
- **Trade:** Trend-following shorts, protective puts
The Statistical Framework
1. Drift Detection with T-Statistics
Instead of guessing if there's a trend, we test it statistically.
How it works:
- Calculates mean return over lookback period
- Standardizes by volatility
- Compares to significance threshold (default 1.96 = 95% confidence)
What it tells you:
- T-stat > 1.96: Statistically significant uptrend
- T-stat < -1.96: Statistically significant downtrend
- In between: No significant trend (consolidation)
Why it matters:
Only trades trends that are statistically validated, not just visually apparent.
2. Mean Reversion Testing (Variance Ratio)
Based on Lo & MacKinlay (1988) research, this detects when markets are range-bound.
How it works:
- Compares variance at different time scales
- Variance Ratio < 0.8 indicates mean reversion
What it tells you:
- Mean reversion = NO: Trends can continue
- Mean reversion = YES: Expect price to return to mean, not breakout
Why it matters:
Prevents chasing breakouts in range-bound markets.
3. Volume Delta Analysis
Total volume tells you HOW MUCH traded. Volume delta tells you WHO won.
How it works:
- Buying pressure - Selling pressure = Volume Delta
- Normalized to show relative strength
What it tells you:
- Strong positive delta (>0.3): Buyers in control
- Strong negative delta (<-0.3): Sellers in control
- Weak delta: No clear winner
Why it matters:
Price can move up on weak buying or down on weak selling. Volume delta reveals the truth.
4. Transition Probability Matrix
Historical regime changes predict future regime changes.
How it works:
- Tracks every regime transition over last 100 bars (configurable)
- Builds probability distribution for next regime
- Updates continuously
Example:
Current: Strong Bull
Historical transitions from Strong Bull:
- Stayed Strong Bull: 45%
- Became Weak Bull: 30%
- Became Consolidation: 20%
- Became Weak Bear: 4%
- Became Strong Bear: 1%
What it tells you:
Strong Bull has 75% chance of staying bullish (45% + 30%), only 5% chance of bearish turn.
Why it matters:
Adapts to your specific market's behavior patterns.
How to Use This Indicator
Strategy Adaptation
In Strong Bull/Bear Regimes:
- Use trend-following strategies
- Wider stops, let winners run
- Add to positions on pullbacks
- High confidence in directional trades
In Weak Bull/Bear Regimes:
- Reduce position sizes by 50%
- Tighter stops
- Take profits earlier
- Prepare for regime change
In Consolidation:
- Switch to range-trading strategies
- Avoid trend-following systems
- Sell resistance, buy support
- Wait for regime change before trend trades
Risk Management
Position Sizing:
- Strong regime + high continuation probability (>60%) = Normal size
- Weak regime OR high transition probability = Half size
- Consolidation = Quarter size or skip
Stop Loss Placement:
- Strong regime: Use wider stops (2x ATR)
- Weak regime: Tighter stops (1x ATR)
- Consolidation: Very tight stops (0.5x ATR)
Entry Timing
Best entries:
- Regime just changed to Strong Bull/Bear
- High probability (>50%) of staying in current regime
- No divergence signals present
- Drift and volume delta aligned
Avoid entries:
- High probability of regime change
- Divergence signals appearing
- Mean reversion detected in trending regime
- Weak volume despite price movement
Reading the Dashboard
Current Regime
Color-coded for instant recognition:
- Dark Green = Strong Bull
- Light Green = Weak Bull
- Gray = Consolidation
- Light Red = Weak Bear
- Dark Red = Strong Bear
Annualized Drift
Expected annual return based on recent trend.
- Positive = Upward bias
- Negative = Downward bias
- Near zero = No directional edge
T-Statistic
Measures statistical significance of drift.
- > 1.96 = 95% confident in uptrend
- < -1.96 = 95% confident in downtrend
- Between = Not statistically significant
Mean Reversion
- Yes = Expect price to return to mean (range-bound)
- No = Trends can continue (trending market)
Volume Pressure
Normalized volume delta strength.
- > 0.3 = Strong buying
- < -0.3 = Strong selling
- Near 0 = Balanced
Transition Probabilities
Shows most likely next regime.
- Highest probability = Most likely outcome
- Evenly distributed = High uncertainty
- Concentrated = High confidence in direction
Practical Examples
Example 1: Strong Bull with High Continuation
Dashboard shows:
Current Regime: Strong Bull
Drift: +22% annualized
T-Stat: 3.2
Mean Reversion: No
Volume Pressure: +0.45
Probabilities:
→ Strong Bull: 50%
→ Weak Bull: 25%
→ Consolidation: 20%
→ Bears: 5%
Interpretation:
- Strong uptrend (t-stat 3.2 >> 1.96)
- No mean reversion = trends can continue
- Strong buying pressure (0.45 > 0.3)
- 75% chance stays bullish (50% + 25%)
Action:
- Full position size on long setups
- Use trend-following entries
- Wider stops (2x ATR)
- High conviction trades
Example 2: Weak Bull Before Consolidation
Dashboard shows:
Current Regime: Weak Bull
Drift: +8% annualized
T-Stat: 1.2
Mean Reversion: Yes
Volume Pressure: +0.15
Probabilities:
→ Strong Bull: 10%
→ Weak Bull: 30%
→ Consolidation: 50%
→ Weak Bear: 10%
Interpretation:
- Weak drift (t-stat 1.2 < 1.96)
- Mean reversion detected = range-bound likely
- Weak volume (0.15 < 0.3)
- 50% chance of consolidation
Action:
- Reduce long positions
- Tighten stops
- Prepare for range-bound trading
- Avoid new trend trades
Example 3: Regime Transition Alert
Previous: Weak Bull
Current: Consolidation
Volume divergence signal appeared:
Price made new high, volume delta weakened
Interpretation:
- Trend exhausted
- Buyers losing control
- Regime confirmed the transition
Action:
- Exit trend-following longs
- Switch to range-trading approach
- Wait for new regime before new directional trades
Settings Guide
### Regime Detection Period (50)
Number of bars for statistical calculations.
- **30-40:** More responsive, catches changes faster, more regime switches
- **50 (default):** Balanced for daily/4H charts
- **75-100:** More stable, fewer false regime changes, slower to adapt
Transition History Depth (100)
How much history to use for probabilities.
- **50-75:** Adapts quickly to recent behavior
- **100 (default):** Balanced robustness
- **150-200:** More stable probabilities, slower to adapt
Volume Delta Period (14)
Period for volume calculations.
- **7-10:** More sensitive to volume shifts
- **14 (default):** Standard period
- **20-30:** Smoother, less noise
Significance Threshold (1.96)
T-statistic required for trend classification.
- **1.64:** 90% confidence, more trend regimes detected
- **1.96 (default):** 95% confidence, balanced
- **2.58:** 99% confidence, very conservative, mostly consolidation
Best Practices
Do:
- Wait for regime confirmation (at least 3-5 bars in new regime)
- Use probabilities to size positions appropriately
- Combine with support/resistance for entries
- Respect mean reversion signals
- Adapt strategy to current regime
Don't:
- Trade every regime change immediately
- Ignore high transition probabilities
- Use trend strategies in consolidation
- Override statistical signals with gut feel
- Trade against Strong regimes without clear setup
Timeframe Recommendations
Daily Charts:
- Default settings work well
- Most reliable regime detection
- Best for swing trading
4H Charts:
- Use default or slightly higher lookback (60-75)
- Good for active swing trading
- More regime changes than daily
1H Charts:
- Reduce lookback to 30-40
- More noise, use with caution
- Better for intraday position trading
15M and below:
- Not recommended
- Too much noise for statistical validity
- Regimes change too frequently
Combining with Other Indicators
Works Well With:
Moving Averages
- Use regime for directional bias
- MAs for specific entry/exit points
Support/Resistance
- Regime shows context
- S/R shows specific levels
- High probability at confluence
Volume Profile
- Regime shows regime
- Profile shows where volume is
- Target high-volume nodes
RSI/MACD
- Regime provides context
- Momentum shows entry timing
- Combine for higher probability
Example Combined Setup
Regime: Strong Bull
Price: Above 200 MA
Level: Pullback to support
RSI: Oversold (30)
Volume Delta: Still positive
Setup: Long entry
Reason: Trend intact, healthy pullback, buyers still present
Divergence Signals
The indicator shows volume divergence warnings:
Bearish Divergence (Red Triangle Down)
- Price makes new high
- Volume delta makes lower high
- Warning: Buyers weakening, potential reversal
Bullish Divergence (Green Triangle Up)
- Price makes new low
- Volume delta makes higher low
- Warning: Sellers weakening, potential reversal
How to use:
- Divergence in Strong regime = early warning of regime change
- Confirms when regime actually transitions
- Don't trade divergence alone, wait for regime confirmation
Limitations
This Indicator Cannot:
**Predict black swan events** - Unexpected news overrides all technical regimes
**Work in all markets** - Needs liquid markets with reliable volume data
**Guarantee profits** - Probabilities are not certainties
**Replace fundamental analysis** - Technical regimes can diverge from fundamentals
Works Best:
- Liquid markets (major indices, forex, crypto, large-cap stocks)
- Daily and 4H timeframes
- Combined with other analysis
- With proper risk management
- In normal market conditions
Common Questions
"Why did the regime stay consolidation despite strong price move?"
The indicator detected mean reversion (variance ratio < 0.8), indicating the move will likely reverse. Or the move wasn't statistically significant (t-stat < 1.96). Trust the statistics over visual appearance.
"Probabilities show 30% for each regime. What does that mean?"
High uncertainty. The market is at an inflection point. Reduce position sizes and wait for clearer regime formation.
"Can I use this for day trading?"
Not recommended on timeframes below 1H. Statistical tests need sufficient data. Better suited for swing trading.
"Why does this show Strong Bull when my momentum indicators show weakness?"
Momentum can weaken while the trend remains statistically significant. The indicator focuses on drift and volume, not momentum. Consider it a different perspective.
Technical Notes
Volume Delta Approximation
Uses OHLCV data to approximate order flow:
- Buy volume ≈ Volume on up-closes
- Sell volume ≈ Volume on down-closes
- Delta = Buy - Sell
**Note:** Real order flow (from futures or Level 2) is more precise. This approximation works well on liquid markets.
Statistical Tests
Drift T-Test:
- Null hypothesis: No drift (mean return = 0)
- Reject if |t-stat| > threshold
- Based on standard hypothesis testing
Variance Ratio:
- Compares 2-period variance to 1-period variance
- Ratio = 1 for random walk
- Ratio < 1 for mean reversion
- Threshold of 0.8 based on empirical testing
Transition Probability Implementation
Due to Pine Script v5 limitations (no native 2D arrays), the 5×5 transition matrix is stored as a flat 1D array of 25 elements:
- Position maps to index: `row × 5 + col`
- Example: Transition from Regime 2 to Regime 4 is at index `1 × 5 + 3 = 8`
- Laplace smoothing (0.1) prevents zero probabilities
- Row sums normalized to calculate probabilities
This approach is computationally efficient and maintains statistical accuracy.
No Repainting
All calculations confirmed on bar close. Regime changes appear when the bar closes, not during formation. Historical analysis is accurate.
Alert Conditions
Regime Change
- Triggers when regime transitions to any new state
- Message shows new regime number (1-5)
Bearish Divergence
- Triggers when price makes new high but volume delta doesn't confirm
Bullish Divergence
- Triggers when price makes new low but volume delta doesn't confirm
Disclaimer
FOR EDUCATIONAL PURPOSES ONLY
This indicator uses statistical methods to analyze market regimes. It does not predict the future or guarantee trading success.
Markets are probabilistic, not deterministic. A 70% probability of staying bullish means 30% chance of regime change. Always use proper risk management.
Past regime transitions do not guarantee future transitions. Market structure can change. Statistical relationships can break down.
Never risk more than you can afford to lose. Use stop losses on every trade. Test thoroughly before live trading. Consult a qualified financial advisor.
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