Empiece

Market-regime

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.
Indicador Pine Script®
por AGProLabs
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.
Indicador Pine Script®
por AGProLabs
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.
Indicador Pine Script®
por AGProLabs
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.
Indicador Pine Script®
por AGProLabs
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.
Indicador Pine Script®
por AGProLabs
AOC Market Regime ClassifierHow it works The indicator combines three core components: EMA Structure (21 / 55) → measures directional bias ATR (volatility normalization) → evaluates movement relative to market activity Range Analysis (highest/lowest window) → detects compression and breakout conditions Using these inputs, the script calculates: Trend strength → distance between EMAs normalized by ATR Range tightness → price compression relative to volatility Breakout conditions → price escaping recent highs/lows Regime Classification The market is dynamically classified into four states: TREND → Strong directional movement with sustained structure RANGE → Low volatility, compressed price action BREAKOUT → Price expansion beyond recent range TRANSITION → Mixed or unclear conditions between regimes Each regime is color-coded directly on the chart for quick visual interpretation. What makes it useful Helps filter trades based on market context Prevents using the wrong strategy in the wrong environment Highlights compression → expansion cycles Keeps analysis simple and adaptive How to use Focus on trend-following strategies during TREND phases Use mean-reversion approaches in RANGE conditions Watch BREAKOUT for potential expansion opportunities Be cautious during TRANSITION phases (lower conviction environment) Key idea Markets change behavior your strategy should too. This tool helps you stay aligned with current conditions instead of applying a one-size-fits-all approach.
Indicador Pine Script®
por aioncharts
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.
Indicador Pine Script®
por AGProLabs
1
Quant Market Predictor v3 (No Signals)Quant Market Predictor – Lite is a streamlined version of the full Quant Market Predictor model. This version focuses purely on market structure analysis and statistical forecasting, without generating trading signals. The indicator combines multiple quantitative techniques commonly used in financial modeling to provide a clearer view of trend dynamics, volatility regimes, and short-term price projections. It is designed for traders and analysts who want model-driven market context while making their own discretionary decisions. Core Models 1. Kalman Filter Trend A recursive Kalman filter smooths price data to estimate the underlying trend. This approach reduces noise while remaining more responsive than traditional moving averages. 2. Adaptive AR(2) Price Model An autoregressive model estimates short-term price momentum using recent price changes. The coefficients adapt to volatility conditions to prevent overreaction during unstable markets. 3. GARCH-Inspired Volatility Model A simplified volatility estimator tracks conditional variance similar to GARCH models. This allows the indicator to identify high-volatility trend regimes and low-volatility consolidation regimes. 4. Multi-Bar Forecast The AR model generates a short-term projection path for the next few bars. The forecast gradually decays to reflect increasing uncertainty further into the future. What the Lite Version Shows • Kalman trend line (dynamic trend estimate) • Volatility bands derived from conditional variance • Regime background highlighting trend vs. consolidation environments • Short-term statistical forecast path • Information table displaying model diagnostics Important This Lite version does not produce buy or sell signals. It is intended as an analytical tool to help interpret market conditions rather than a complete trading system. Typical Use Cases • Understanding whether the market is in a trend or mean-reversion regime • Visualizing volatility expansion and contraction • Viewing a probabilistic short-term forecast path • Supporting discretionary trading decisions
Indicador Pine Script®
por liebmann_
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. © 2026 | Open Source Statistical rigor meets practical application
Indicador Pine Script®
por DavidEH
Price density [Measuring Market Noise:Take advantage]$$ Market noise can be problematic to some types of trading strategies yet beneficial to others. By measuring noise using the 'Price Density' can enable us to improve our trading edge and turn noise to our advantage. Robust analysis of noise can inform us when it is best to avoid trend-following systems (when noise is too high), and vice versa for systems based on a mean-reverting trading premise (when market noise is low). __________________________________________________________________________ Using Noise to our advantage * Two techniques: -Measure Noise and trade when suitable for the system ~ High noise = avoid trend-following ~ Low noise = avoid mean-reversion -Match assets to strategies ~ Only trade 'noisy assets' with Mean-reversion Strategies ~ Only trade 'efficient assests' with Trend-following Strategies ## Price density:- High values = High noise Low values = Low noise ___________________________________________________________________________ Disclaimer!! Do your own research
Indicador Pine Script®
por Unknown_TracerBUNNY