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Accumulation

Accumulation

XAUUSD Institutional Volume [MatsukazeAlgo]🇬🇧 ENGLISH Price moves before retail sees it. This indicator detects when institutions are quietly accumulating or distributing Gold, before the breakout happens. It uses tick volume anomalies and candle structure (VSA + momentum) to identify clusters of institutional activity, then draws zones with internal volume profiles. When price breaks out of a zone on expanded volume, it signals the trade. Based on Institutional Accumulation & Distribution Detector by PhenLabs . Gold-optimized with 6 additions. Optimized for 15m. Also effective on 1H. How It Detects Institutional Activity Two candle types are classified on every bar: Momentum candles: Large body + high relative volume. Directional conviction. Institutions pushing price. Absorption candles: Large wick + high volume + close in opposite half. Institutions absorbing supply or demand without moving price. This is the stealth signature. When 3 or more of these candles cluster within 15 bars, a zone is confirmed. Session-Adaptive RVOL (Gold addition) Gold's volume profile varies drastically by session. Asia session has naturally lower volume, so a standard 1.8x RVOL threshold misses quiet accumulation. Asia: RVOL threshold 1.5x. Catches institutional positioning during low-liquidity hours. This is where Gold's biggest moves are seeded. London / NY: RVOL threshold 1.8x. Standard detection for high-liquidity sessions. Daily and higher timeframes use the London/NY threshold regardless of session. Quality Scoring with Gold Bonuses Each zone receives a base score from 0 to 5: RVOL strength above 2.5x, VSA absorption candles present, tight consolidation within 2x ATR, candle count well above minimum, strong directional bias above 75%. Gold bonuses add up to 2 additional points (capped at 5 total): Asia session accumulation gets +1. This is the highest-value pattern in Gold: quiet positioning before London. DXY confirmation gets +1. Accumulation while USD weakens means macro-aligned institutional buying. Default minimum score is 4. Only zones with real institutional conviction appear on the chart. Volume Profile Inside Zones Each zone includes an internal volume profile showing where the most volume was transacted: POC (Point of Control): The price level with highest volume inside the zone. This is the institutional average entry. HVN (High Volume Node): The price band where most activity concentrated. When price returns to the POC after a breakout, it often finds support or resistance. This is institutions defending their position. DXY Bias Markers Breakout signals and zone labels display a "$" marker when the DXY trend confirms the direction. A long breakout with weakening USD is macro-confirmed. The "$" tells you institutions have macro wind at their back. Breakout Targets When price breaks out of a zone on RVOL above 1.2x, the indicator projects ATR-based targets at 1R, 2R, and 3R, with a stop loss at the opposite zone boundary. Psych Level Awareness (off by default) When enabled, zones near $50 or $100 round numbers receive a bonus point and a ★ marker. Institutional accumulation at $3,300 carries more weight than at $3,317. Credits Original institutional detection framework, dual-type candle classification, volume profile engine, and no-repaint architecture by PhenLabs . Session-adaptive RVOL, quality score bonuses (session + DXY + psych), Gold-specific tuning by MatsukazeAlgo. --- 🇯🇵 日本語価格が動く前に、機関投資家は静かにポジションを構築している。このインジケーターは、ゴールドにおける機関投資家の蓄積・分配の痕跡をブレイクアウト前に検出する。 Tick Volumeの異常とローソク足構造（VSA + モメンタム）を使って機関投資家の活動クラスターを特定し、内部Volume Profileを含むゾーンを描画する。ゾーンからのブレイクアウト時にシグナルを発生。 PhenLabsのInstitutional Accumulation & Distribution Detectorをベースに、ゴールド専用の6つの改良を追加。15分足に最適化。1時間足でも有効。検出ロジック 2種類のキャンドルを分類：モメンタム型：大実体 + 高Volume = 方向性を伴った確信。吸収型：大ヒゲ + 高Volume + 反対側で引け = 価格を動かさずに需給を吸収するステルスシグネチャー。 15バー以内にこれが3本以上 = ゾーン確定。セッション別RVOL閾値アジア：RVOL 1.5x。低流動性の時間帯での静かな蓄積を検出。ゴールドの大きな動きの種はここで撒かれる。ロンドン/NY：RVOL 1.8x。標準の検出閾値。品質スコア + ゴールドボーナス基礎スコア0〜5点（RVOL強度/吸収キャンドル/レンジ圧縮/参加率/方向性）。ゴールドボーナス（最大+2、上限5）：アジアセッションの蓄積 = +1。ロンドン前の静かなポジション構築。ゴールドで最も価値が高いパターン。 DXY確認 = +1。USD弱 + 蓄積 = マクロ整合の機関投資家買い。デフォルト最低スコア4。本物の機関投資家確信のあるゾーンのみ表示。ゾーン内Volume Profile POC：ゾーン内で最もVolumeが集中した価格帯 = 機関投資家の平均エントリー。 HVN：高Volume集中帯。 DXYバイアスマーカーブレイクアウトシグナルに「$」マーカー。DXYトレンドが方向を確認。ブレイクアウトターゲット ATRベースの1R/2R/3R + SL。RVOL 1.2x以上のブレイクアウトで発動。心理的価格帯（デフォルトOFF） $50/$100付近のゾーンにボーナス + ★マーカー。

Pine Script® Indikator

von MatsukazeAlgo

Market Pressure Market Pressure — Description & Usage Market Pressure is a normalized oscillator designed to characterize whether buying or selling pressure is dominating the market, and how persistent that pressure is over time. It does not attempt to predict price or generate signals. Instead, it measures the consistency of directional behavior by combining where price closes within each bar, the strength of the candle body, the level of volume participation, and alignment with trend. These components are smoothed and scaled into a range between -100 and +100, allowing the user to quickly assess who is in control and how strong that control is relative to recent conditions. Values above zero indicate net buying pressure, while values below zero indicate net selling pressure. The most important region is the neutral zone around zero, defined by the user, which represents a balanced market where neither side has clear control. When the histogram remains within this neutral range, price action is typically rotational and prone to false moves. When the indicator moves and sustains itself outside of that range, it reflects a shift toward directional control. Strong readings toward the extremes suggest persistent and coordinated pressure, often associated with trend continuation rather than random movement. This indicator is best used as a contextual filter rather than an entry tool. When Market Pressure is positive and holding above the neutral boundary, it suggests focusing only on long opportunities and avoiding shorts. When it is negative and holding below the neutral boundary, the opposite applies. When it is inside the neutral zone, the most effective action is often to stand aside, as the market lacks a dominant participant. The behavior of the histogram also provides insight into the quality of a move. Expanding values indicate strengthening pressure, while contracting values suggest that the dominant side may be losing control. Because the indicator is normalized using a rolling lookback window, all readings are relative to recent history rather than fixed absolute levels. This allows it to adapt across different markets and timeframes, but also means that extremes represent the strongest pressure observed within that window, not an absolute threshold. The result is a flexible tool that highlights when the market is trending with conviction, when it is losing momentum, and when conditions are best avoided altogether.

Pine Script® Indikator

Aktualisiert

Wyckoff Accumulation Phase Map [AGPro Series]Wyckoff Accumulation Phase Map 🟢 OVERVIEW Wyckoff Accumulation Phase Map is the bullish counterpart of the Wyckoff Distribution Phase Map and completes the AGPro Wyckoff structural cycle. It is a retrospective structural mapping tool that locates and labels the seven core accumulation events — Preliminary Support (PS), Selling Climax (SC), Automatic Rally (AR), Secondary Test (ST), Spring, Last Point of Support (LPS) and Sign of Strength (SOS) — only after a bullish Change of Character (CHoCH) confirms that the prior downtrend has structurally broken. The indicator frames the active trading range as a shaded zone, plots SC and AR horizontal references, tracks the current phase (A, B, C, D, E) in a dedicated info panel, and introduces three accumulation-specific layers absent from the distribution companion: a Spring Quality Score, a Cause-to-Effect markup projection and a rolling volume footprint classifier. 🟢 COMPANION TO THE DISTRIBUTION PHASE MAP This indicator is intentionally designed as the symmetric counterpart of Wyckoff Distribution Phase Map . The two scripts share a unified AGPro visual language and a CHoCH-gated reveal philosophy, but they operate on opposite market regimes and different event sets: - Distribution map works on uptrends and draws PSY, BC, AR, UT, SOW and LPSY after a bearish CHoCH. - Accumulation map works on downtrends and draws PS, SC, AR, ST, Spring, LPS and SOS after a bullish CHoCH. - Distribution projects a potential markdown line from LPSY. - Accumulation projects a Cause-to-Effect markup target from SOS. - Accumulation additionally provides a 0-100 Spring Quality Score, which has no structural equivalent in the distribution schematic. Both tools are standalone. Users running the full AGPro Wyckoff workflow can apply them together for complete cycle coverage, but neither depends on the other. 🟢 WHAT MAKES IT DIFFERENT Most Wyckoff scripts on TradingView react to every elevated swing low during a downtrend and label PS / SC / Spring on every modest dip. The result is a noisy chart, often with contradictory events stacked on top of each other. This indicator takes the opposite approach. During a qualified downtrend, the chart remains completely clean. Rolling trackers silently maintain candidate values for SC, PS and AR in memory, while a live Watching row in the panel shows what the engine is currently monitoring. Events are only drawn on the chart after a bullish CHoCH locks the schematic, at which point PS, SC and AR appear together as a confirmed retrospective bundle. ST, Spring, LPS and SOS then populate as post-CHoCH structure unfolds. A multi-tier expiry system closes both incomplete and fully-played-out accumulations, ensuring the active schematic on screen always reflects current market structure and not stale history. 🟢 METHODOLOGY The engine runs in three coordinated layers. Layer one qualifies a prior downtrend. A valid Wyckoff accumulation precondition requires four concurrent factors: structural lower highs and lower lows, a minimum ATR-multiple depth from the lookback-window high, a duration sustained across the full lookback window, and price currently located in the lower portion of that window. All four conditions must hold before any candidate can form. Layer two rolls candidate values during that qualified downtrend. SC candidate is the running lowest pivot low with elevated or climactic volume. PS candidate is the prior elevated swing low that predates the SC. AR candidate is the highest post-SC swing high that remains within a structurally reasonable distance from SC. Candidates are automatically invalidated if price drifts far above the SC without a structural break or if the candidate ages beyond a configurable maximum. Layer three watches for a bullish Change of Character, defined as the first bar that closes above the qualified AR candidate. On CHoCH confirmation, PS, SC and AR are snapshotted as labeled events, the trading range is drawn, and the state machine advances to forward detection. ST, Spring, LPS and SOS are then detected in sequence using a combination of price-to-SC, price-to-AR and volume-to-average filters. Volume context is computed against a configurable moving-average baseline with separate climactic, elevated and weak thresholds. The Spring Quality Score blends four components into a 0-100 rating: penetration depth below SC, volume dry-up on the sweep bar, recovery strength measured by close position within the candle range, and close location relative to SC. The Cause-to-Effect projection draws a symmetrical markup target from the SOS bar using the trading range height. 🟢 SIGNALS AND ALERTS The indicator fires three categories of alerts, all reserved for confirmed structural events: - CHoCH Confirmation alert triggers when the structural break locks in, including the resolved SC and AR levels. - Spring alert fires when the Spring is detected, including the Spring Quality score. - Sign of Strength alert fires when SOS confirms with climactic volume above AR. No alerts are emitted during the forming phase. This keeps notification volume low and focused on decisive structural moments. 🟢 KEY INPUTS Core Engine inputs control swing lookback sensitivity, candidate maximum age, post-CHoCH timeout, prior downtrend lookback, minimum downtrend depth in ATR multiples, and the near-lows threshold used in downtrend qualification. Volume Analysis exposes the moving-average length and three separate multipliers for climactic, elevated and weak volume classification. Visual inputs toggle the trading range zone, SC and AR horizontal levels, the CHoCH dashed break line, the Cause-to-Effect projection, the floating summary label and the keep-historical-events mode, with full control over font size and zone transparency. The info panel can be repositioned to six anchor points and switched between dark and light themes. 🟢 HOW TO USE Apply the indicator to any liquid instrument and any timeframe. During downtrends, observe the Watching row in the panel to monitor the forming SC candidate. When CHoCH prints, the full PS, SC and AR bundle appears and the trading range is shaded. From that point, use the Next Expected row to track what the engine is waiting for. The Confidence score progresses from 70 at CHoCH to 97 at SOS. The Spring Quality Score becomes populated when a Spring is detected and quantifies the character of the sweep. The Volume Footprint row rolls through Range forming, Supply exhausting, Weak hands shaken, Supply absorbed and Demand in control as the schematic matures. The floating summary label on the right edge of the chart provides an at-a-glance status even when the primary event labels are scrolled off to the left. The indicator works standalone but is designed to complement any market structure, order flow or supply-and-demand workflow. 🟢 LIMITATIONS AND TRANSPARENCY This tool is a pattern-recognition and labeling engine, not a strategy or a trading signal generator. All events are detected retrospectively after their confirming bar has closed plus the swing lookback period. This is by design to eliminate redrawing. The Wyckoff schematic is a framework, not a deterministic forecast. Not every accumulation completes the full seven-event sequence, and markets frequently fail schematics entirely and resume the prior downtrend. The volume analysis assumes reliable reported volume, so thin or fragmented markets may produce weaker classification. The Spring Quality Score and Confidence score are internal heuristics tied to event progression and are not statistical probabilities. The Cause-to-Effect projection is a classical Wyckoff reference line derived from range height, not a mechanical target guaranteed to be reached. Past schematic completions do not predict future market behavior. 🟢 RISK DISCLOSURE This indicator is published for educational and analytical purposes only. It does not constitute financial advice, a trading recommendation or an investment solicitation. Trading any financial instrument involves substantial risk, including the potential loss of principal. Past performance does not guarantee future results. Users are solely responsible for their own trading decisions, risk management and independent research. Always backtest thoroughly and trade within a risk framework you understand.

Pine Script® Indikator

Institutional Session Profiler [JOAT]Institutional Session Profiler Introduction The Institutional Session Profiler builds a real-time volume-by-price distribution for each of the three major trading sessions — Asia (Tokyo, 01–09 UTC), London (07–16 UTC), and New York (13–22 UTC). For each session, it calculates the Point of Control (POC — the price level with the highest traded volume), the Value Area High (VAH) and Value Area Low (VAL) encompassing 70% of session volume, and a net buy/sell delta that reveals directional institutional participation within the session. Profile shapes are rendered as smooth polyline waves via Catmull-Rom cubic spline interpolation, giving the profiles a clean, readable curve rather than a jagged bar histogram. The core problem this solves: standard volume profile tools display a single aggregated profile for an arbitrary lookback. Institutional traders operate within defined session windows — Asia sets the range, London typically engineers liquidity, New York resolves direction. Mapping volume distribution per session reveals where institutions are genuinely active versus where price is simply passing through thin volume. Core Concepts 1. Lower-Timeframe Volume Accumulation To build accurate price-level histograms on any chart timeframe, 1-minute (or user-specified lower timeframe) bars are requested via Pine Script's security_lower_tf function. Each sub-bar's volume is classified as buy-side or sell-side, then placed into the session's price bins: array ltf_c = request.security_lower_tf("", i_ltf, close) array ltf_v = request.security_lower_tf("", i_ltf, volume) for i = 0 to ltf_c.size() - 1 float p = ltf_c.get(i) float v = ltf_v.get(i) int idx = int(math.floor((p - s_asia.lo) / bin_size)) s_asia.bins.set(idx, s_asia.bins.get(idx) + v) This means the profile represents actual sub-bar traded volume distributed across price, not a simple tick count or approximation from chart-timeframe candles. 2. Point of Control and Value Area The POC is the bin index with the highest accumulated volume. The Value Area is computed by iteratively expanding from the POC outward, adding the higher-volume neighbor bin at each step until 70% of total session volume is captured: float target = total_vol * VA_PCT // VA_PCT = 0.70 float accum = bins.get(poc_idx) int lo_i = poc_idx int hi_i = poc_idx while accum < target // expand toward whichever neighbor bin has more volume The resulting VAH and VAL define the zone where the majority of institutional volume transacted. Price inside the value area is "accepted" — price outside it is either in premium or discount relative to session fair value. 3. Catmull-Rom Spline Profile Rendering Rather than rendering a stepped histogram, the volume bins are smoothed with a double-pass averaging and then connected via Catmull-Rom cubic splines into a polyline. This produces the signature smooth profile wave that is readable at a glance without the visual noise of raw histogram bars: // Control point generation for cubic interpolation float cx0 = x0, cy0 = y0 float cx1 = x1 + (x2 - x0) / 6, cy1 = y1 + (y2 - y0) / 6 // ... polyline rendered via array 4. Session Delta Each session accumulates a running buy/sell delta (buy volume minus sell volume across all sub-bars). The dashboard displays the session delta as a signed value with color coding — positive delta in the Asia session followed by a bullish London opening is a meaningful institutional convergence signal. Features Three Simultaneous Session Profiles: Asia, London, and New York built in parallel, each with its own color Point of Control Line: Horizontal line at the highest-volume price level per session, extended across the full session range Value Area Box: Shaded box from VAL to VAH representing the 70% volume concentration zone Volume Wave: Smooth Catmull-Rom spline profile rendered as a polyline — showing the full shape of volume distribution Buy/Sell Delta: Net directional volume per session displayed in the dashboard Session Range Box: Outer boundary box showing the full session high-to-low range 9-Row Dashboard: Displays session status (open/closed), POC price, VAH, VAL, session range, delta, and total session volume for each active session Alerts: Asia session open, London session open, NY session open, price enters value area, price exits value area Input Parameters Sessions: Asia (01–09 UTC): Toggle Asia session profiling (default: on) London (07–16 UTC): Toggle London session profiling (default: on) New York (13–22 UTC): Toggle NY session profiling (default: on) Volume Profile: LTF for Volume: Lower timeframe to use for sub-bar volume accumulation (default: 1m). Must be smaller than chart timeframe. Profile Bins: Number of price levels in each session distribution (default: 35, range: 10–100). More bins = finer resolution. Show Value Area (70%): Toggle VAH/VAL box rendering (default: on) Visualization: Asia / London / NY Colors: Independent session color selection Box Transparency: Base transparency of session range and value area boxes (default: 85) Show Volume Wave: Toggle Catmull-Rom spline profile rendering (default: on) Dashboard: Position: Top Right, Top Left, Bottom Right, Bottom Left (default: Top Right) How to Use This Indicator Step 1: Locate the POC and Value Area The POC is the single most important price level in each session — it represents the highest institutional agreement. Value Area (VAH to VAL) is where the majority of volume transacted. Price above VAH is premium; price below VAL is discount. Step 2: Identify Session Transitions The London open (07 UTC) frequently engineers liquidity above or below the Asia range. If London takes out the Asia high and then reverses, the Asia POC becomes a magnetic target. The NY open at 13 UTC is the resolution event — watch for which side of the London value area price is trading on at that open. Step 3: Read the Session Delta A session with strong positive delta (more buy volume than sell volume) combined with price closing near the VAH suggests institutional accumulation. Negative delta closing near VAL suggests distribution. Divergence between price direction and delta direction is a key reversal signal. Step 4: Use VAH/VAL as Dynamic S/R After a session closes, its VAH and VAL remain on chart as reference levels. These levels frequently act as support or resistance in the following session because institutional participants remember where the majority of volume transacted. Originality Statement This indicator is original in its combination of per-session volume profile construction using lower-timeframe data with Catmull-Rom spline visual rendering and real-time delta tracking across three simultaneous sessions. Its publication is justified because: Volume profiles are typically computed for arbitrary user-defined time windows or fixed periods. Per-session profiling maps institutional behavior to the actual time windows in which institutions operate — Asia, London, and New York — creating contextually meaningful distributions rather than arbitrary aggregations Catmull-Rom spline interpolation of the bin array produces a smooth, continuous profile shape that preserves the true distribution topology while being readable without histogram visual noise Real-time lower-timeframe volume decomposition into price bins on any chart timeframe gives accurate sub-bar volume placement that chart-timeframe-only calculations cannot produce Simultaneous three-session display with independent POC, VAH, VAL, and delta tracking per session enables cross-session analysis that no single-profile tool can provide Limitations LTF data requests consume additional computation. On very high timeframe charts (4H+), 1-minute LTF data pulls are large. Consider using 5m LTF on higher timeframes to reduce computation. The buy/sell volume classification (close >= open = buy) is an approximation at the 1-minute level. True tick-direction is not available in Pine Script. Session times are fixed UTC offsets. Daylight saving time transitions may shift the actual institutional open by one hour depending on the exchange. Value Area calculation uses 70% of session volume by default. This follows the standard Market Profile convention but the threshold is not universally agreed upon. On assets with very low volume (illiquid instruments), the profile bins will be sparse and the spline shape may not be representative of meaningful distribution. Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any instrument. All trading involves risk of loss. Session volume patterns do not guarantee future price behavior. Always use proper risk management. -Made with passion by jackofalltrades

Pine Script® Indikator

von officialjackofalltrades

Volumetric Structure Engine [JOAT]Volumetric Structure Engine Introduction The Volumetric Structure Engine is an institutional market structure tracker that fuses swing-point classification with real-time buy/sell volume delta analysis. Every confirmed swing high and swing low is measured not only by price, but by the net volume composition of the leg that produced it — revealing whether a structural move was driven by genuine institutional buying or selling, or whether it was a low-conviction, thin-volume probe. The indicator classifies market structure as HH/HL (bullish) or LH/LL (bearish), detects Break of Structure (BOS) and Change of Character (ChoCH) events on bar close, and renders each swing zone with a color gradient that reflects the underlying volume delta of that leg. The core problem this solves: most market structure tools draw lines or arrows at swing points but say nothing about the quality of that swing. A break of structure on rising volume is categorically different from one on declining volume — the first signals institutional participation, the second suggests a liquidity grab. VSE quantifies that difference on every bar. Core Concepts 1. Non-Repainting Swing Detection Swings are confirmed using a lookback comparison pattern that resolves only on bar close: float H = ta.highest(high, i_len) float L = ta.lowest(low, i_len) bool new_sh = high == H and high < H bool new_sl = low == L and low > L A swing high at bar N-1 is confirmed when bar N closes lower, meaning the prior bar's high was the highest in the lookback window. This approach never repaints because it always references the closed bar to the left. 2. Volume Delta Accumulation Per Leg Between each confirmed swing, running buy and sell volume totals accumulate. On each bar, if close >= open the bar's volume is classified as buy-side; otherwise it is sell-side. When a new swing is detected, the accumulated totals are saved to that swing node, and the counters reset for the next leg: if new_sh or new_sl run_buy := 0.0 run_sell := 0.0 if close >= open run_buy += volume else run_sell += volume The delta percentage (buy minus sell divided by total volume) determines the color and transparency of each swing zone box. A leg with 80% buy delta renders as a vivid bull green; a leg with 20% buy delta renders as a vivid bear red. Neutral legs render in the neutral color. 3. BOS and ChoCH Detection Break of Structure fires when confirmed price closes through the most recent confirmed swing extreme in the opposite direction. Change of Character fires when the first break occurs against the established trend — the earliest signal that the dominant structure may be shifting. Both signals are barstate.isconfirmed, preventing any lookahead. 4. Structure Cloud A fill between the last confirmed swing high and swing low creates a visual structure range that updates dynamically. The cloud color matches the current trend direction and serves as an at-a-glance bias indicator for the session. Features Swing Zone Boxes: ATR-scaled zone boxes at every confirmed swing, colored by the net buy/sell delta of the producing leg Volume Delta Gradient: Zone colors range from deep bull green (high buy delta) to deep bear red (high sell delta), with transparency encoding conviction BOS Lines: Dashed horizontal lines drawn at the level where a Break of Structure closes, with text label ChoCH Highlight: Change of Character events highlighted with a distinct yellow-amber color to distinguish them from continuation BOS signals Structure Connection Lines: Lines connecting consecutive swing nodes, colored by the delta of each leg Structure Cloud: Gradient fill between the last swing high and low showing current structural range Candle Coloring: Optional candle tinting by current trend direction 9-Row Dashboard: Displays trend bias, last swing high/low price levels, structure range percentage, BOS bull/bear counts, ChoCH count, last leg delta percentage, and total swing node count Alerts: BOS bullish, BOS bearish, ChoCH bullish, ChoCH bearish Input Parameters Structure Detection: Swing Length: Lookback bars for swing high/low detection (default: 20, range: 5-200). Higher values identify fewer, stronger structural swings. Lower values are more reactive. Show BOS Lines: Toggle BOS line rendering (default: on) Show ChoCH: Toggle Change of Character highlighting (default: on) Structure Cloud: Toggle the fill between swing high and low (default: on) Visualization: Bullish / Bearish / Neutral / ChoCH colors: Fully customizable Zone Transparency: Control the base transparency of swing zone boxes (default: 78) Color Candles: Optional candle tinting by structural trend (default: off) Dashboard: Position: Top Right, Top Left, Bottom Right, Bottom Left (default: Top Right) How to Use This Indicator Step 1: Read the Current Structure The dashboard shows the current trend bias (BULLISH / BEARISH / NEUTRAL), the last confirmed swing high and low prices, and the structural range as a percentage. This gives you the directional context at a glance. Step 2: Interpret Zone Colors Zones colored in vivid green (high buy delta) represent legs driven by institutional buying. Zones colored in vivid red (high sell delta) represent institutional selling pressure. Faded or gray zones represent low-conviction legs — useful for identifying weak structure that is more likely to be swept. Step 3: Trade BOS and ChoCH Events A BOS in the direction of the existing trend is a continuation signal. A ChoCH (against the trend) is a structural shift signal and often marks the beginning of a reversal. Volume delta on the breaking leg adds conviction: a BOS on a high-buy-delta leg is more reliable than one on a low-delta leg. Step 4: Use Swing Zones as S/R Each swing zone box represents a price area where a structural pivot occurred. Institutional order flow often returns to these levels. High-delta zones in particular tend to act as meaningful support or resistance. Originality Statement This indicator is original in its combination of confirmed non-repainting swing structure with per-leg volume delta measurement. While market structure tools and volume analysis tools each exist independently, this indicator is justified because: Volume delta is computed per structural leg — not per candle and not as a global indicator — creating a direct mapping between market structure quality and institutional participation The swing confirmation method using the lookback comparison pattern eliminates repainting while maintaining responsiveness to genuine structural changes Zone color encoding with delta-driven gradient creates an immediate visual hierarchy — strong zones versus weak zones — without requiring separate panels or indicators BOS and ChoCH detection with volume delta context provides a more complete signal than either alone Limitations The buy/sell volume classification (close >= open = buy) is an approximation. True tick-level direction is not available in Pine Script. On very short timeframes where volume is sparse, classification may be imprecise Swing length selection significantly affects structure quality. Too short produces noise; too long misses intermediate structure. Users should calibrate to their timeframe and instrument BOS and ChoCH are confirmed on bar close, so they are identified one bar after the actual breakout candle closes. This is a deliberate trade-off for accuracy over speed The indicator does not predict direction — it classifies the current structural state. A bullish structure can break down without warning Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any instrument. All trading involves risk of loss. Past structural patterns do not guarantee future results. Always use proper risk management. -Made with passion by jackofalltrades

Pine Script® Indikator

von officialjackofalltrades

AG Pro Chaikin Money Flow Pressure [AGPro Series]AG Pro Chaikin Money Flow Pressure Overview / What it does AG Pro Chaikin Money Flow Pressure is a chart-overlay indicator built to translate Chaikin Money Flow behavior into a more structured view of buying and selling pressure on the price chart itself. Instead of presenting CMF only as a standalone oscillator around a zero line, this script converts money-flow behavior into visible pressure zones, a backbone line, selective event labels, and a compact decision panel. The goal is to make pressure conditions easier to read in context with price rather than in a separate pane. The script is designed to help users judge whether positive or negative money-flow pressure is merely appearing, becoming more persistent, expanding with price support, or losing quality. In practical terms, it focuses on how pressure behaves through time, not only on whether CMF is above or below zero on a single bar. This distinction is important because many CMF readings are technically positive or negative while still being structurally weak, transitional, or unstable. This publication is an indicator, not a strategy. It does not place orders, does not simulate broker execution, and does not claim to predict future price direction. Its purpose is to organize CMF-derived pressure information into a chart-readable framework that can be used for analysis, filtering, or confluence with a user’s existing process. Unique Edge The distinctive design choice in this script is that it treats Chaikin Money Flow as a pressure-structure input rather than as a simple zero-cross oscillator. The script evaluates pressure using a combination of directional bias, persistence, slope behavior, and exhaustion characteristics, then maps those conditions into an overlay format. That makes it materially different from tools that focus primarily on: - classic CMF zero-line interpretation, - MFI-style overbought/oversold framing, - OBV-style cumulative flow interpretation, - divergence-first logic, - or trend/momentum tools that derive most of their signal from price structure rather than money-flow persistence. Within the broader AG Pro catalog, some scripts are centered on momentum, reaction quality, divergence behavior, or trend-state interpretation. This one is specifically built around CMF-derived pressure persistence. In other words, it is less about identifying a single trigger event and more about showing whether accumulation or distribution pressure is building, holding, fading, or reverting toward balance. Methodology The script begins with the standard Chaikin Money Flow foundation: money flow is derived from the close’s location within the bar range and weighted by volume across the selected CMF lookback. That raw series can then be smoothed to reduce short-term noise. From there, the script classifies pressure through several layers: 1) Bias Positive and negative CMF conditions establish the directional pressure side. This is the base layer, but it is not used alone. 2) Persistence The script tracks how long positive or negative pressure has been maintained. Short-lived readings are treated differently from more persistent runs. 3) Expansion The slope of the smoothed CMF series helps distinguish strengthening pressure from flatter or compressing conditions. 4) Exhaustion risk When pressure remains extended but begins to weaken internally, the script can shift into a fading or exhaustion-sensitive interpretation instead of treating every positive or negative reading as equally strong. These components are then summarized into: - a state, - a phase, - a pressure score, - a backbone-based pressure map, - and selective event labels. The overlay uses an EMA backbone and ATR-scaled zones to visualize where pressure is concentrated around price. Outer and core zones help separate broad pressure environment from tighter pressure concentration. A lightweight bridge effect is used to connect confirmed pressure conditions to price in a restrained way so the visual hierarchy remains readable. Signals & Alerts The script uses a state/condition framework rather than a direct buy/sell promise. Core states include: - Accumulation - Distribution - Balanced - Exhaustion Risk Phase interpretation includes: - Building - Holding - Fading - Neutral Selective chart labels are intentionally limited to higher-quality transitions such as: - ACCUM - DIST - FADE - FLIP Available alert conditions are designed around pressure behavior, not outcome guarantees: - Pressure Building - Pressure Holding - Pressure Weakening - Pressure Flip Risk - Accumulation Regime Confirmed - Distribution Regime Confirmed These alerts are best understood as structural notifications about pressure behavior. They are not instructions to enter or exit positions by themselves. Key Inputs Important settings include: - CMF Length: controls the main money-flow lookback. - CMF Smoothing: reduces noise in the base CMF series. - Neutral Band: defines when pressure is treated as balanced rather than directional. - Strong Pressure Band: helps scale the pressure score and zone intensity. - Exhaustion Band: helps identify stretched but weakening pressure conditions. - Persistence Confirmation Bars: sets how long pressure should persist before confirmation. - Backbone EMA Length: controls the central overlay structure. - ATR settings: control the width of the pressure zones. - Label filters and cooldowns: reduce repeated labels and keep the chart cleaner. These inputs allow users to make the script more responsive or more selective depending on timeframe, asset behavior, and chart density. Limitations & Transparency This script does not measure real order-book flow, exchange-specific footprint data, or trade-by-trade delta. It is a CMF-based analytical model built from OHLCV data available on TradingView. As with any derived indicator, its output depends on the quality and characteristics of the underlying market data. The pressure score is not a prediction score and should not be interpreted as a probability of success. It is a normalized summary of current pressure quality based on the script’s internal framework. A higher score means the current pressure structure is stronger by the script’s rules; it does not mean the next move is guaranteed. Like other pressure or flow-based tools, this script can become less reliable in choppy, thin, or event-driven conditions where pressure quickly alternates and persistence breaks down. It should also be expected that different assets and timeframes will respond differently to the same parameter set. Users should evaluate settings in the market context where they intend to use the indicator. This publication is meant to explain what the script measures and how it organizes that information. It is not presented as a black-box promise, and it is not intended to replace independent chart reading, risk control, or broader market context. Risk Disclosure This script is provided for educational and analytical use. It does not constitute financial advice, investment advice, or a solicitation to buy or sell any financial instrument. No indicator can remove uncertainty from markets, and no visual state, score, zone, or alert should be treated as a guarantee of future results. Users should make their own decisions, test their own process, and apply appropriate risk management. This tool is best used as a structured market-reading aid and as part of a broader analytical framework rather than as a standalone decision engine.

Pine Script® Indikator

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Market Cycle Projection Engine Market Cycle Projection Engine WHAT IT DOES Market Cycle Projection Engine (MCPE) is a fully original indicator built in Pine Script v6 that automatically identifies the current market cycle phase, draws key structural levels, and projects the next expected price movement all on a single overlay chart. Unlike traditional indicators that react to price, MCPE analyzes the internal structure of market behavior using a four-phase cycle model inspired by Wyckoff methodology, combined with a linear regression slope engine and volatility expansion/contraction logic. WHAT MAKES IT ORIGINAL Most cycle indicators either repaint, rely on subjective drawing, or require manual input. MCPE does none of these. The core innovation is a three-factor phase classification engine: 1. Linear Regression Slope measures the true directional momentum of price over the cycle lookback period, normalized by ATR to make it comparable across all assets and timeframes. 2. ATR Ratio (Volatility State) compares current ATR to its own slow average to detect whether volatility is expanding (trending phase) or contracting (consolidation phase). 3. Price Position in Cycle Range determines whether price is in the lower 40% (potential accumulation) or upper 60% (potential distribution) of the cycle's high/low range. These three factors combine to produce a four-phase classification that updates automatically on every bar without any repainting. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ THE FOUR CYCLE PHASES 🔵 ACCUMULATION Slope is flat. Volatility is contracting. Price is in the lower portion of the cycle range. This is where institutions quietly build long positions before the markup phase. Candles colored cyan. 🟢 MARKUP Slope is rising. Volatility is expanding. This is the trending upward phase the reward for accumulation patience. Candles colored green. 🟠 DISTRIBUTION Slope is flat again. Volatility is contracting. Price is now in the upper portion of the cycle range. Smart money is offloading positions to retail buyers. Candles colored orange. 🔴 MARKDOWN Slope is falling. Volatility is expanding downward. The cycle completes its rotation back toward accumulation. Candles colored red. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ HOW TO USE Step 1 Read the Phase Look at the current candle color and the Dashboard panel (top-right). The Cycle Phase row tells you exactly where the market is in its current rotation. Step 2 Check Cycle Position % The Cycle Position metric shows where price sits within the current cycle range (0% = bottom, 100% = top). Below 30% = potential accumulation opportunity. Above 70% = potential distribution / caution zone. Step 3 Use the Projection Arrow When a phase transition occurs, MCPE draws a directional projection line showing the expected next move. The arrow length is calculated from the average of the previous two cycle swing ranges and expressed as a percentage of current price. This is NOT a price prediction it is a probabilistic projection based on historical cycle amplitude. Step 4 Respect the Key Levels Three horizontal levels are always visible: Cycle High upper boundary of the current cycle range. Cycle Low lower boundary of the current cycle range. Mid the equilibrium level between the two. Price returning to Mid after an extreme move is a common mean-reversion setup. Step 5 Confirm with Volatility and Volume The Dashboard shows Volatility Status and Volume reading. Strong signals occur when phase transitions align with expanding volatility and elevated volume simultaneously. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ CALCULATION LOGIC Phase Classification: lr_slope = linreg(close, cycle_len, 0) - linreg(close, cycle_len, 1) lr_slope_norm = lr_slope / ATR(14) atr_ratio = ATR(14) / ATR(cycle_len) price_pos = (close - cycle_low) / cycle_range Markup : lr_slope_norm > 0.1 AND atr_ratio > 1.1 Markdown : lr_slope_norm < -0.1 AND atr_ratio > 1.1 Accumulation: slope flat AND price_pos < 0.4 Distribution: slope flat AND price_pos >= 0.4 Projection Amplitude (Last Cycle method): avg_range = (|meso_high - meso_low| + |prev_high - prev_low|) / 2 target = last_pivot + avg_range (bull) or - avg_range (bear) Volatility Status: High when ATR(14) > SMA(ATR(14), 20) * 1.3 Cycle Strength (0-100): Measures how far price deviates from the cycle midpoint, expressed as a percentage of the total cycle range. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SETTINGS Cycle lookback (bars) Controls how many bars define one full cycle. Increase for macro analysis, decrease for shorter-term cycles. Recommended: 50 for daily, 30 for 4H, 20 for 1H. S/R pivot lookback Controls how far back the indicator looks for key support and resistance pivot points. Projection bars How many bars into the future the projection line extends. Projection basis Three methods available: Cycle Average uses average of last two swing ranges. Last Cycle uses 75% of the most recent cycle range. ATR Multiple uses ATR × 30 as a fixed projection size. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ COMPATIBILITY Works on all assets Crypto, Forex, Stocks, Indices, Futures. Works on all timeframes. Best results on Daily and 4H charts for swing trading. For intraday use, reduce cycle_len to 20-30. No repainting. All signals calculated on bar close. No lookahead bias. No request.security() with lookahead. No Heikin Ashi or non-standard chart dependency. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ALERTS INCLUDED Phase: Accumulation detected Phase: Markup detected Phase: Distribution detected Phase: Markdown detected ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DISCLAIMER This indicator is provided for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any asset. Past cycle patterns do not guarantee future results. Markets are inherently unpredictable. Always apply your own analysis and use proper risk management before placing any trade. The author is not responsible for any trading losses incurred from use of this indicator. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Pine Script® Indikator

OBV Linear Regression Multi-Slope [HYPR-run]DESCRIPTION: Three linear regression slopes fitted to On-Balance Volume. Measures whether accumulation or distribution is accelerating, decelerating, or reversing across short, medium, and long lookbacks simultaneously. Raw OBV tells you the cumulative direction of volume flow. Fitting a linear regression to it gives you the rate of change: the slope. Three slopes at different lookbacks show the structure of volume commitment. When all three agree, volume flow is structurally committed in one direction. When they disagree, the timeframes are in conflict. DISCOVERING EDGE Dual and triple slope alignment has proven to be a staple confirmation signal in our most reliable automated strategies for both entries and exits. When two or three independent lookbacks agree on the direction of volume flow, the commitment is structural, not noise. When alignment breaks, the first slope to flip tells you exactly where conviction cracked. We built this indicator to surface that alignment as a first-class signal rather than something you eyeball across separate panes. THREE LR SLOPES vs RAW OBV LINE Three slopes at different lookbacks show whether all timeframes of volume flow agree or conflict. Dual alignment (short + long) is the entry signal; triple (all three) confirms later for pyramids. When triple breaks, that's the exit. Values above 0.3 mean the slope is steeper than one standard deviation per bar (very strong trend). Sigma/bar above 0.1 means the slope is statistically strong; below 0.05 is weak. FEATURES - Three linear regression slope lines on OBV (short 9, medium 26, long 50) - Optional adaptive short lookback (ATR-scaled for low timeframes) - Slope alignment detection: dual (short+long) and triple (all three) - Universal angle normalization (slope/sigma x 45 degrees) - Sigma/Bar ratio: slope strength relative to OBV noise - Auto-adjusts all lookbacks by timeframe (weekly/monthly compress) - Webhook alerts on slope flip or triple alignment - Full bar filter rejects doji/wick-heavy bars - Dashboard with lookback, angle, and sigma/bar for all three lines HOW IT WORKS Linear regression calculates the best-fit line through OBV values over a lookback window. The slope of that line is the rate of volume flow. Positive slope = accumulation accelerating. Negative slope = distribution accelerating. The universal angle normalizes raw slope by OBV standard deviation so the dashboard reads consistently across any asset (BTC's OBV in millions, a low-cap's in thousands, same angle scale). UNIVERSAL ANGLE Slope divided by OBV standard deviation per bar, multiplied by 45. A value of 45 degrees means the slope equals one standard deviation per bar. Makes angle comparable across any asset and timeframe: 30 degrees on BTC means the same relative strength as 30 degrees on SOL. ALERT MODES Slope Flip: fires when selected lookback crosses zero. Negative to positive = accumulation starting (LONG). Positive to negative = distribution starting (SHORT). Triple Alignment: fires when all three slopes agree on direction. Fewer signals, higher conviction. Alert payload is built into the script as JSON; works with any webhook receiver. CREDITS On-Balance Volume: Joseph Granville, Granville's New Key to Stock Market Profits (1963)

Pine Script® Indikator

Aktualisiert

ROC Regime Filter [HYPR-run]DESCRIPTION: A reliable universal regime filter across all assets, all timeframes. Rate of change filter that classifies price action into regime states. A suite of smoothed EMAs feeds a layered ROC engine that detects when fast momentum aligns with, or diverges from, slow structure. The filter measures; it doesn't predict. When all ROC layers stack in the same direction (parallel alignment), the trend is confirmed by arithmetic. When fast ROC diverges from slow, the regime shifts. The lag is the cost of certainty. Sweet spot is 1hr to 1D; lower timeframes get noisy. DISCOVERING EDGE In order to gain a persistent, mechanical edge in which trades are permitted and which are filtered out, we explored a more meaningful expression of regime classification using layered multiple ROC periods to detect when fast momentum aligns with or diverges from slow structure. This resilient regime filter has been the backbone for our automated strategies since 2021. LAYERED ROC vs SINGLE-INDICATOR REGIME A single RSI or ADX reading flattens the market into binary (trending/not trending). Layered ROC alignment separates six distinct states, each with different permissible trade types, so the filter matches the complexity of what the market is actually doing. Six regime states gate every decision; the combination of regime color + ROC slope is the trade filter, not either one alone. Phase transitions (green to yellow, orange to green) are the actionable signals; static states just confirm what's already happening. Webhook alerts fire on macro pivots (accumulation/distribution inflections) at the regime transition, not after the move has run. FEATURES - Six regime states from layered ROC alignment (see color legend below) - Early trend detection when all layers accelerate in parallel - ROC 200 line with regime-colored gradient fill - Macro pivot detection: strong trend exhausting into sideways, scored by where ROC 200 sits relative to its all-time range - Accumulation/distribution context in dashboard - ROC 200 pivot high/low divergence markers on main chart - Consolidation markers with conviction scoring (normal vs extreme) - Gradient candle overlay (ROC Sticks; toggle on/off) - Two-row dashboard: row 1 = macro context (accumulation/distribution), row 2 = current regime state with directional qualifier and slope - Dashboard dark/light theme toggle for any chart background - Full ROC stack in data window for manual analysis - Webhook alerts on macro pivots (accumulation/distribution) HOW IT WORKS ROC alignment is the core signal. When all layers stack in the same direction, that's strong trend territory (green). When fast ROC diverges from the slower layers while slow structure still holds, the engine reclassifies from strong trend to sideways (yellow), flagging a pullback rather than trend failure. Deeper corrections where intermediate layers fall below the structural anchor fire orange, indicating a correction within the primary trend. Macro pivots fire at the inflection: strong trend exhausting into sideways for the first time. The consolidation score layers this with where ROC 200 sits in its all-time range. Consolidation at extreme ROC readings (bright green/red dots) is the highest-conviction signal for reversal. HOW TO USE Read the regime color, not the price. Green = strong trend long, red = strong trend short, orange = deeper correction, yellow = short pullback, white = directionless. Use regimes as a directional gate: longs during green, shorts during red. Yellow flags a pullback within trend; wait for resolution back to green/red before re-entering. Orange is a deeper correction; patience or fade with confirmation from other tools. The highest-edge signals come from regime transitions, not static states. Watch for: green breaking into yellow (macro pivot, potential reversal), extended yellow resolving back to green (continuation re-entry), and the ROC slope within a regime (slope rising in orange = trend about to resume). The data window shows the full ROC stack across all layers. When fast ROC diverges from slow, that signals continuation or reversion. MACRO CONTEXT (Dashboard Row 1) REGIME COLOR LEGEND (Dashboard Row 2) ALERTS Macro pivot long fires when accumulation is detected (bull inflection). Macro pivot short fires when distribution is detected (bear inflection). Create alert: condition = this indicator, "Any alert() function call". Paste your webhook URL, set Open-ended, create. Alert payload is built into the script; works with any webhook receiver. CREDITS Advance/Decline gradient function: LucF

Pine Script® Indikator

Aktualisiert

Velocity Acceleration Momentum [VAM]Velocity Acceleration Momentum Overview VAM is a multi-layered momentum indicator that measures how fast price is moving (Velocity), whether that speed is increasing or decreasing (Acceleration), and how strong the underlying trend is (ADX). Rather than just telling you the direction of price, VAM tells you the quality and phase of the move you're in. How It's Calculated Velocity measures the percentage rate of change of price over a lookback period (default: 14 bars), then smooths it with a 3-period EMA. It answers: "How fast is price moving relative to where it was?" Acceleration is the change in Velocity over a secondary smoothing window (default: 5 bars), also EMA-smoothed. It answers: "Is momentum speeding up or slowing down?" Signal Line is an EMA of Velocity (default: 9 bars) — similar in concept to the MACD signal line. When Velocity crosses above/below the Signal Line, it can indicate momentum shifts. ADX Histogram uses Pine's built-in DMI/ADX calculation. When DI+ > DI−, bars plot positively (green); when DI− > DI+, bars plot negatively (red). The color opacity is gradient-mapped to ADX strength — vivid bars mean a strong trend, faded bars mean a weak/ranging market. Reading the Velocity Line Colors (Regime Detection) The Velocity line changes color based on the combination of Velocity and Acceleration: ColorConditionMeaning🟢 LimeVelocity > 0, Acceleration > 0Rocket — momentum is up and accelerating🟡 YellowVelocity > 0, Acceleration < 0Topping — still positive but losing steam🔴 RedVelocity < 0, Acceleration < 0Freefall — momentum is down and worsening🟠 OrangeVelocity < 0, Acceleration > 0Bottoming — still negative but recovering How to Trade With It High level Buy when Velocity Line Green 🟢sell when Velocity drops hard and is Red 🔴 + ADX BARS TELL YOU THE TREND AND THE TREND STRENTH (COMBINE THIS AND THE VELOCITY LINE) + ACCELERATION PUROPLE AND YELLOW WAVE TELLS YOU SHARP DROPS OR ADVANCES IN ACCELERATION Trend Entries: Look for the Velocity line turning Lime (🟢) with the ADX histogram printing vivid green bars above the +25 line. This is the highest-confidence long setup — price is accelerating upward with confirmed trend strength. Caution / Exit Signals: When Velocity turns Yellow (🟡) and sharply drops, momentum is fading even if price is still rising. Consider tightening stops or taking partial profits. Short / Bearish Bias🔴 : Red Velocity + vivid red ADX bars below −25 signal a strong downtrend in Freefall. Avoid longs; look for short setups. Potential Reversals: Orange Velocity (Bottoming) combined with ADX bars beginning to fade and shift green can be an early signal that a bottom is forming — useful for scaling into longs cautiously. Signal Line Crosses: When the Velocity line crosses above the white Signal Line, momentum is picking up. Crosses below suggest weakening. Best used as a confirmation filter, not a standalone trigger. The ±25 Reference Lines mark the ADX threshold commonly used to separate trending (above) from ranging (below) markets. ADX histogram bars inside the ±25 zone suggest low trend conviction — reduce position sizing or wait for confirmation. Inputs Source — Price input (default: Close) Velocity Length — Lookback period for rate-of-change calculation (default: 14) Acceleration Smooth — Smoothing window for acceleration (default: 5) Signal Line Length — EMA period for the signal line (default: 9) ADX Length — Period for DMI/ADX calculation (default: 14) Show Signal Line — Toggle the white signal line on/off Show Zone Backgrounds — Toggle ADX-strength background shading Show ADX Histogram — Toggle the ADX directional histogram

Pine Script® Indikator

von MasterTonyTA

Range Finder & Profile [UAlgo]Range Finder & Profile is a structured market range detection tool that combines pivot based range discovery with an embedded volume profile. Its purpose is to identify areas where price begins to rotate inside a defined boundary, track whether that balance remains intact, and then summarize how volume was distributed inside the completed range once price finally exits it. The script starts by using pivot highs and pivot lows to define potential horizontal boundaries. When a valid upper and lower reference exist, and price is trading inside those bounds without already breaking them, the script opens a candidate range. From that point onward, it keeps monitoring the structure bar by bar, checking whether the range survives long enough to become confirmed and whether price remains accepted inside it. What makes this indicator especially useful is that it does not stop at simply drawing a box around consolidation. Once a range becomes confirmed, it also builds a row based internal profile of all activity inside that zone. When the range eventually breaks, the script calculates Point of Control, Value Area High, and Value Area Low, then draws a compact profile directly inside the range. This transforms a simple horizontal box into a more informative market acceptance map. The result is a tool that can help traders study balance, distribution, and eventual expansion. It is useful for identifying clean consolidation structures, understanding where the heaviest participation occurred inside a range, and interpreting whether the breakout happened after meaningful internal acceptance or after a less developed structure. 🔹 Features 🔸 Pivot Based Range Discovery The script uses pivot highs and pivot lows to establish potential range boundaries. This creates a structure that reacts to meaningful swing points rather than arbitrary rolling highs and lows. As a result, the detected ranges tend to reflect actual market rotation more naturally. 🔸 Clean Range Validation A new range is only created when price is already trading inside the proposed top and bottom boundaries and when no bar in the candidate history has already closed outside those levels. This helps prevent invalid or already broken ranges from being accepted. 🔸 Overlap Protection The script tracks where the last completed range ended and avoids creating a new one that starts inside an already closed structure. This reduces repeated overlap and keeps the chart cleaner. 🔸 Minimum Range Confirmation Not every detected range is immediately treated as valid. The structure must survive for a minimum number of bars before it becomes confirmed. This helps filter out weak or short lived consolidations. 🔸 Embedded Volume Profile Each confirmed range contains its own internal volume profile. The vertical height of the range is divided into configurable rows, and every bar contributes volume into the relevant price segments. This creates a compact distribution map inside the actual range boundaries. 🔸 Proportional Volume Allocation The script does not simply drop full bar volume into a single row unless the bar has no height. Instead, when a candle spans multiple rows, its volume is distributed proportionally across the overlapped sections. This produces a more realistic representation of participation across the range. 🔸 Point of Control Detection After the range is complete, the script finds the profile row with the highest accumulated volume. This row becomes the Point of Control, giving the user a quick view of the price area with the strongest concentration of activity. 🔸 Value Area Calculation The script expands outward from the Point of Control and accumulates neighboring rows until the selected percentage of total range volume is reached. This produces Value Area High and Value Area Low, which highlight the area where most participation occurred. 🔸 Gradient Range Background The active and completed range is drawn with a multi slice background gradient between the upper and lower colors. This improves readability and gives the zone a more polished visual structure. 🔸 Histogram Inside the Range When a range is confirmed and completed, the script draws horizontal histogram bars inside the zone. Rows inside the value area use a dedicated color, while rows outside the value area use a separate profile color. This makes internal acceptance easy to read visually. 🔸 Live Active Range Updates While the range is still active and not yet broken, the background extends forward in time with every new bar. Once the range becomes confirmed, profile and value area calculations are refreshed continuously until the breakout occurs. 🔸 Practical Market Structure Use This makes the indicator useful for consolidation analysis, acceptance and rejection studies, and breakout context. A trader can see not only where price paused, but also how volume built inside that pause before expansion occurred. 🔹 Calculations 1) Pivot Detection for Range Anchors float ph = ta.pivothigh(high, lengthInput, lengthInput) float pl = ta.pivotlow(low, lengthInput, lengthInput) if not na(ph) recentPH := ph recentPHIndex := bar_index if not na(pl) recentPL := pl recentPLIndex := bar_index This is the starting point of the whole script. The code asks TradingView to detect a pivot high and a pivot low using the selected swing length. A pivot high appears only after enough bars have formed on both sides of the swing, and the same logic applies to a pivot low. Because of that, pivots are confirmed reference points rather than instant highs or lows. When a valid pivot high is found, the script stores two things. The pivot price itself in recentPH The bar index where that pivot actually occurred in recentPHIndex The same is done for pivot lows through recentPL and recentPLIndex . This means the script always keeps track of the latest confirmed upper swing and the latest confirmed lower swing. Those two swing references become the raw ingredients for a possible trading range. 2) Candidate Range Creation Logic bool canCreateRange = na(activeRange) and not na(recentPH) and not na(recentPL) if canCreateRange float top = math.max(recentPH, recentPL) float bot = math.min(recentPH, recentPL) if top > bot and close <= top and close >= bot int sIndex = math.min(recentPHIndex, recentPLIndex) int barsBack = bar_index - sIndex This block decides whether the script is even allowed to start a new range. First, canCreateRange requires three conditions: there must be no currently active range, there must be a recent pivot high, and there must be a recent pivot low. If those conditions are met, the script builds a provisional upper bound and lower bound using the greater and smaller of the two pivot prices. Then it checks whether current price is actually inside that proposed range. This is important because it prevents the script from creating a range that price has already escaped. The code also finds sIndex , which is the earlier of the two pivot bar indices. That earlier point becomes the true starting location of the range. Then barsBack measures how many bars ago the range began. So at this stage, the script has a full candidate structure: an upper price, a lower price, and a starting point in time. 3) Overlap Prevention and Broken History Check bool isOverlapping = false if sIndex <= lastClosedRangeEndIndex isOverlapping := true if not isOverlapping bool broken = false if barsBack > 0 for i = 0 to barsBack if close > top or close < bot broken := true break This section filters out bad candidates before a range is created. First, the script checks whether the proposed start index falls inside or before the end of the last completed range. If it does, the new candidate is marked as overlapping and rejected. This keeps the indicator from repeatedly generating new boxes on top of old structures. Next, even if there is no overlap, the script scans every bar from the proposed start point up to the present. It checks whether any close moved above the top boundary or below the bottom boundary. If that happened, the candidate is marked as broken. This is a very important quality filter. It means the script does not simply connect two pivots and call that a range. It also verifies that price actually stayed accepted inside those boundaries over the full candidate history. 4) Initializing the Range Object activeRange := RangeData.new( startIndex = sIndex, startTime = time , endIndex = bar_index, endTime = time, topPrice = top, bottomPrice = bot, isActive = true, isConfirmed = false, totalVolume = 0.0, pocPrice = na, pocVolume = 0.0, pocIndex = -1, vah = na, val = na, bgBoxes = na, histBoxes = na, pocLine = na, vahLine = na, valLine = na, pocLabel = na, vahLabel = na, valLabel = na ) activeRange.initProfile(profileRows) Once the script is satisfied that the candidate is valid, it creates a new RangeData object. This object stores all important information about the range: where it starts, where it currently ends, its top price, its bottom price, whether it is still active, whether it is confirmed, and all profile related values such as total volume, Point of Control, Value Area High, and Value Area Low. Immediately after creating the object, the script calls initProfile(profileRows) . That method prepares the internal volume profile rows that will later hold the distribution data. So this is the moment where the script moves from pure detection into active tracking. 5) Building the Internal Profile Rows method initProfile(RangeData this, int rowsCount) => float step = (this.topPrice - this.bottomPrice) / rowsCount this.profile := array.new() for i = 0 to rowsCount - 1 float pBottom = this.bottomPrice + (i * step) float pTop = pBottom + step this.profile.push(ProfileRow.new(pTop, pBottom, 0.0)) This method divides the height of the range into a fixed number of rows. First, it calculates step , which is the height of one profile row. That is simply the total range height divided by the selected number of profile rows. Then it creates an empty profile array and fills it row by row. Each row stores: its upper price, its lower price, and the total volume accumulated in that row. At this moment, every row starts with zero volume. The profile is just an empty framework waiting to receive bar by bar contributions. This design is important because the script is not using a prebuilt TradingView volume profile function. It is constructing the profile manually, row by row, inside the exact range boundaries. 6) Adding Volume Into the Profile method addVolume(RangeData this, float bHigh, float bLow, float bVol) => float overlapHigh = math.min(bHigh, this.topPrice) float overlapLow = math.max(bLow, this.bottomPrice) if bHigh == bLow and bHigh <= this.topPrice and bHigh >= this.bottomPrice for i = 0 to this.profile.size() - 1 ProfileRow row = this.profile.get(i) if bHigh >= row.priceBottom and bHigh <= row.priceTop row.volumeTotal += bVol this.totalVolume += bVol break else if overlapHigh > overlapLow float overlapHeight = overlapHigh - overlapLow float totalHeight = bHigh - bLow float effectiveVol = totalHeight > 0 ? bVol * (overlapHeight / totalHeight) : bVol for i = 0 to this.profile.size() - 1 ProfileRow row = this.profile.get(i) float rowOverlapHigh = math.min(overlapHigh, row.priceTop) float rowOverlapLow = math.max(overlapLow, row.priceBottom) if rowOverlapHigh > rowOverlapLow float rowOverlapHeight = rowOverlapHigh - rowOverlapLow float rowRatio = rowOverlapHeight / overlapHeight float addedVol = effectiveVol * rowRatio row.volumeTotal += addedVol this.totalVolume += addedVol This is one of the most important calculations in the whole script. The goal here is to take a candle and distribute its volume into the profile rows that the candle actually overlaps. First, the script limits the candle to the range boundaries using overlapHigh and overlapLow . This ensures that only the part of the candle inside the range contributes to the profile. Then two cases are handled. If the candle has no height, meaning bHigh == bLow , the full volume is assigned to the single row that contains that exact price. If the candle does have height, the script calculates how much of the candle actually overlaps the range. That overlapping height becomes the valid section for profile allocation. Then, for each profile row, the script measures how much of that valid section overlaps the row. Volume is distributed proportionally according to that overlap share. This is much more accurate than placing the full candle volume into a single row. It means tall candles contribute volume across the price levels they truly passed through, which creates a more realistic internal distribution. 7) Filling the New Range With Historical Volume if barsBack >= 0 for i = 0 to barsBack float bVol = na(volume ) ? 1.0 : volume activeRange.addVolume(high , low , bVol) Right after a new range is created, the script goes back through all bars that belong to that range from its start until the current bar. For each of those bars, it reads the volume and sends the bar high, bar low, and volume into addVolume . This step is essential because it backfills the profile immediately. Without it, the range would start with an empty volume profile and would only accumulate data from future bars. Instead, the script reconstructs the whole internal history of the range as soon as the range is created. Also notice the fallback 1.0 when volume data is missing. That ensures the script can still function on symbols where actual volume may not be available. 8) Range Confirmation and Break Detection bool isBroken = close > activeRange.topPrice or close < activeRange.bottomPrice if (bar_index - activeRange.startIndex) >= minRangeLen activeRange.isConfirmed := true Once a range is active, the script keeps evaluating two key questions on every bar. The first question is whether the range is broken. If the current close moves above the top or below the bottom, the range is considered finished. The second question is whether the range has lasted long enough to be trusted. If the number of bars since the range started is at least the user selected minimum, isConfirmed becomes true. This creates a useful distinction between a candidate range and a confirmed range. A short structure can exist visually for a while, but it only becomes analytically meaningful after it survives long enough. 9) Live Updating While the Range Is Active if not justCreated float barVol = na(volume) ? 1.0 : volume activeRange.addVolume(high, low, barVol) if activeRange.isConfirmed activeRange.calcValueArea(valAreaPct) activeRange.drawProfile(colorBgTop, colorBgBot, colorProfile, colorProfileVA, colorPOC, colorVA) else activeRange.updateBgRight(time, colorBgTop, colorBgBot, colorBorder) This block explains how the range evolves in real time. If the current bar is not the same bar where the range was created, the script adds the latest candle volume into the profile. That keeps the internal distribution up to date bar by bar. Then the script behaves differently depending on confirmation state. If the range is already confirmed, it recalculates the value area and redraws the full profile. This means Point of Control, Value Area High, Value Area Low, and the histogram are all updated continuously as long as price remains inside the range. If the range is not yet confirmed, the script only extends the background box to the current time. In other words, the market structure is still being monitored, but the full profile is not drawn until the range has proven itself. 10) Point of Control Discovery float maxVol = -1.0 int pIndex = -1 for i = 0 to this.profile.size() - 1 ProfileRow row = this.profile.get(i) if row.volumeTotal > maxVol maxVol := row.volumeTotal pIndex := i this.pocIndex := pIndex this.pocVolume := maxVol ProfileRow pocRow = this.profile.get(pIndex) this.pocPrice := (pocRow.priceTop + pocRow.priceBottom) / 2.0 This is the first phase inside the value area calculation. The script scans every profile row and looks for the one with the largest accumulated volume. That row becomes the Point of Control row. Once that row is found, the script stores: the row index in pocIndex , the largest row volume in pocVolume , and the row midpoint price in pocPrice . So the Point of Control is not guessed from the center of the range or from price action alone. It is derived directly from the heaviest profile row. 11) Expanding to Build the Value Area float targetVol = this.totalVolume * (pct / 100.0) float currentVol = maxVol int upIndex = pIndex + 1 int downIndex = pIndex - 1 while currentVol < targetVol and (upIndex < this.profile.size() or downIndex >= 0) float upVol = upIndex < this.profile.size() ? this.profile.get(upIndex).volumeTotal : -1.0 float downVol = downIndex >= 0 ? this.profile.get(downIndex).volumeTotal : -1.0 if upVol == -1.0 and downVol == -1.0 break Here the script begins with the Point of Control row and tries to accumulate enough neighboring volume to reach the selected percentage of total range volume. First, it calculates targetVol , which is the amount of total volume required for the value area. For example, if the input is 70 percent, the target is 70 percent of the full profile volume. The process then starts from the Point of Control row. currentVol begins at the Point of Control volume itself. From there, the script looks one row up and one row down and keeps expanding until the target is reached or no more rows remain. This is the classic logic of building a value area around the highest participation zone. 12) Choosing Whether to Expand Up or Down bool addUp = false if upVol > downVol addUp := true else if downVol > upVol addUp := false else int distUp = upIndex - pIndex int distDown = pIndex - downIndex if distUp < distDown addUp := true else if distDown < distUp addUp := false else addUp := true This section decides which side should be added next to the value area. If the row above the current zone has more volume than the row below, the script expands upward. If the row below has more volume, it expands downward. If both sides have the same volume, the script breaks the tie by comparing distance from the Point of Control. If distance is also equal, it defaults upward. This matters because value area construction should not be arbitrary. It should expand toward the heaviest nearby participation first. That keeps the final value area centered around the most meaningful volume concentration. 13) Final VAH and VAL Calculation int finalUp = math.min(upIndex - 1, this.profile.size() - 1) int finalDown = math.max(downIndex + 1, 0) this.vah := this.profile.get(finalUp).priceTop this.val := this.profile.get(finalDown).priceBottom After expansion is complete, the script converts the final upper and lower included rows into actual price boundaries. vah becomes the top of the highest included row. val becomes the bottom of the lowest included row. These two values form the value area envelope, showing the price zone that contains the selected percentage of all volume traded inside the range. So the final value area is not a fixed distance from Point of Control. It adapts to the actual row by row distribution. 14) Drawing the Gradient Range Background method drawBg(RangeData this, color cBgTop, color cBgBot, color cBorder, int rTime) => if not na(this.bgBoxes) for b in this.bgBoxes b.delete() this.bgBoxes := array.new() int bgSlices = 10 float sliceStep = (this.topPrice - this.bottomPrice) / bgSlices for i = 0 to bgSlices - 1 float bBot = this.bottomPrice + (i * sliceStep) float bTop = bBot + sliceStep this.bgBoxes.push(box.new(this.startTime, bTop, rTime, bBot, border_color=na, bgcolor=sliceCol, xloc=xloc.bar_time)) This method handles the visual background of the range. Before drawing anything new, the script deletes previously drawn background boxes. Then it splits the range vertically into ten slices. Each slice receives an interpolated color between the selected bottom background color and top background color. Finally, each slice is drawn as a time based box from the range start to the chosen right edge time. The result is a smooth vertical color transition across the range body, which makes the zone easier to read and visually separates upper and lower sections. 15) Drawing the Histogram, POC, VAH, and VAL if this.isConfirmed float maxVol = this.pocVolume if maxVol > 0 int rangeTimeWidth = math.max(rightTime - this.startTime, 1000) int maxTimeWidth = math.round(rangeTimeWidth * 0.35) for i = 0 to this.profile.size() - 1 ProfileRow row = this.profile.get(i) if row.volumeTotal > 0 float widthRatio = row.volumeTotal / maxVol int boxTimeWidth = math.round(maxTimeWidth * widthRatio) int boxLeftTime = rightTime - boxTimeWidth bool inVA = (row.priceTop <= this.vah and row.priceBottom >= this.val) color finalHistCol = inVA ? histVaCol : histCol this.histBoxes.push(box.new(boxLeftTime, t, rightTime, b, border_color=na, bgcolor=finalHistCol, xloc=xloc.bar_time)) this.pocLine := line.new(this.startTime, this.pocPrice, rightTime, this.pocPrice, color=pocCol, style=line.style_solid, width=2, xloc=xloc.bar_time) this.vahLine := line.new(this.startTime, this.vah, rightTime, this.vah, color=vaCol, style=line.style_dashed, width=1, xloc=xloc.bar_time) this.valLine := line.new(this.startTime, this.val, rightTime, this.val, color=vaCol, style=line.style_dashed, width=1, xloc=xloc.bar_time) This is the drawing engine for the completed profile. For each row with volume, the script calculates a width ratio relative to the Point of Control volume. Rows with more volume receive wider histogram boxes. Rows with less volume receive narrower boxes. That width is converted into time space, so the histogram grows leftward from the right edge of the range. This creates a compact in range horizontal profile. The script also checks whether each row lies inside the value area. If it does, the row uses the value area histogram color. If it does not, it uses the normal profile color. This makes the high participation area visually distinct. Finally, the script draws three key lines across the full width of the range: Point of Control, Value Area High, and Value Area Low. These lines convert the internal profile data into easy to read structure references on the chart. 16) What Happens When the Range Breaks if isBroken activeRange.isActive := false activeRange.endIndex := bar_index activeRange.endTime := time if not activeRange.isConfirmed if not na(activeRange.bgBoxes) for b in activeRange.bgBoxes b.delete() else activeRange.calcValueArea(valAreaPct) activeRange.drawProfile(colorBgTop, colorBgBot, colorProfile, colorProfileVA, colorPOC, colorVA) lastClosedRangeEndIndex := bar_index activeRange := na This block defines the final lifecycle of a range. When price closes outside the range boundaries, the active structure is terminated. The script records the ending bar and ending time, then checks whether the range had ever become confirmed. If the range was never confirmed, its background is deleted and the structure is discarded. This prevents weak or short lived ranges from leaving unnecessary clutter. If the range was confirmed, the script performs a final value area calculation and profile draw on the completed structure. It also stores the ending index so future ranges do not overlap with this one. Then the active range is cleared from memory, which allows the script to start searching for the next valid structure.

Pine Script® Indikator

Hidden Markov Reversal Finder [UAlgo]Hidden Markov Reversal Finder is a regime aware reversal detection indicator that uses a compact 3 state Hidden Markov style filter with online adaptation to classify market conditions and highlight potential top and bottom rotations. The script models price behavior as transitions between three regimes: - Bull Expansion - Balance - Bear Stress Instead of running a heavy Baum Welch retraining loop, this version is designed as a lightweight real time filter. It updates regime probabilities using a transition matrix plus a two dimensional Gaussian emission model built from two normalized observations: Return observation as a smoothed log return z score Volatility observation as a realized volatility z score The indicator runs in its own pane ( overlay=false ) but can optionally paint chart bars and place reversal labels on price using force overlay. It also includes a clean dashboard panel showing the current state, confidence, observation values, score, posterior probabilities, stretch, and the current setup classification. The reversal engine is built around a top rotation and bottom rotation concept. It looks for a probability peak in a regime, then a fade from that peak, combined with momentum flip conditions and a stretch filter measured in ATR units relative to a baseline EMA. Signals are gated by a confidence threshold and a cooldown period to reduce repetitive prints. This makes the indicator useful as a regime driven reversal framework that integrates: State probabilities and confidence Regime score and momentum flip ATR based stretch extremes Peak fade rotation logic Clean visual markers and dashboard transparency 🔹 Features 🔸 1) Three Regime Model The script uses three explicit regimes with distinct roles: Bull Expansion, intended to represent positive drift conditions Balance, intended to represent neutral or mixed drift Bear Stress, intended to represent negative drift and higher stress conditions Each regime has its own mean and variance assumptions for return and volatility, which are then adapted online. 🔸 2) Two Dimensional Observation System (Return and Volatility) The model does not rely on only returns. It uses both: A normalized return feature A normalized volatility feature This helps distinguish clean bullish trends from choppy balance periods, and balance periods from bearish stress regimes. 🔸 3) Transition Matrix with Persistence Controls Users can control how sticky each regime is through persistence settings: Bull persistence Balance persistence Bear persistence The transition matrix is constructed so that most probability remains in the same regime, while the remainder flows into other regimes using asymmetric weights that reflect realistic behavior. 🔸 4) Real Time Bayesian Filter Update Each bar, the model performs: Prediction step using the transition matrix Update step using Gaussian emissions Posterior normalization Active state selection by arg max This produces a smooth probability based regime tracker suitable for live use. 🔸 5) Adaptation After filtering, the model adapts its internal means and variances using a learning rate scaled by posterior responsibility. This allows the state distributions to slowly adjust to changing market conditions without full retraining. This keeps the indicator responsive while still stable. 🔸 6) Regime Score Output The main score line is: Bull posterior minus Bear posterior This produces a continuous signal that ranges between negative and positive values and functions as a regime tilt meter. A confidence ribbon is also plotted as an area band derived from the dominant posterior. 🔸 7) Confidence Gating and Visual Strength Confidence is defined as the largest posterior probability among the three regimes. The script uses confidence to: Gate reversal signals Determine bar tint transparency when bar coloring is enabled Decide whether state shift tags should be printed This reduces noise during low clarity periods. 🔸 8) Rotation Style Reversal Engine The reversal finder is built on rotation logic: A top rotation occurs after a Bull probability peak fades while Bear probability begins to rise A bottom rotation occurs after a Bear probability peak fades while Bull probability begins to rise This is a probabilistic rotation concept rather than a simple oscillator crossover. 🔸 9) Momentum Flip Confirmation Signals require momentum confirmation through: Regime score change direction Return observation crossing a flip threshold This is designed to reduce premature top and bottom calls when the regime probabilities shift but price momentum has not actually flipped. 🔸 10) ATR Based Stretch Filter The script computes stretch as distance from an EMA baseline measured in ATR units. Signals require: Top signals only when stretch is above a positive threshold Bottom signals only when stretch is below a negative threshold This ensures reversal signals occur when price is extended, not when it is near equilibrium. 🔸 11) Cooldown Control A cooldown setting prevents consecutive buy or sell reversal signals from printing too frequently. This is especially useful when the market chops around an extreme and repeatedly triggers partial rotation conditions. 🔸 12) Dashboard Panel A table dashboard displays key information on the last bar: Active state name Confidence Return z score and volatility z score Regime score Posterior probabilities Stretch in ATR units Current setup text such as BUY REVERSAL, SELL REVERSAL, TOP WATCH, BOTTOM WATCH, WAIT This makes the indicator transparent and easy to interpret. 🔸 13) State Tags and Reversal Labels on Chart When enabled, the script prints: State tags such as BULL, BASE, BEAR with arrows Reversal markers with a vertical guide line and bold letter B or S Tooltips include confidence, peak probability, stretch, and current posterior probabilities. 🔸 14) Optional Probability Curves and Bar Coloring Users can toggle: State probability plots Signal markers and dots Dashboard visibility State tag visibility Bar coloring by regime with confidence adjusted transparency This makes the indicator adaptable for minimalist or fully informational workflows. 🔹 Calculations 1) Return Observation Construction The script uses log returns: float logReturn = math.log(close / nz(close , close)) It smooths return with an EMA: float smoothedReturn = ta.ema(logReturn, returnSmoothLength) Then normalizes by the return standard deviation: float returnStdev = math.max(nz(ta.stdev(logReturn, returnZLength), EPS), EPS) float returnObs = clampFloat(smoothedReturn / returnStdev, -obsClamp, obsClamp) Interpretation: Return observation is a clamped z score like feature, where positive values represent bullish return pressure and negative values represent bearish return pressure. 2) Volatility Observation Construction Realized volatility is measured as the standard deviation of log returns: float realizedVol = nz(ta.stdev(logReturn, volLength), EPS) Then it is normalized relative to a baseline EMA and baseline standard deviation: float volMean = nz(ta.ema(realizedVol, volBaselineLength), realizedVol) float volStdev = math.max(nz(ta.stdev(realizedVol, volBaselineLength), EPS), EPS) float volObs = clampFloat((realizedVol - volMean) / volStdev, -obsClamp, obsClamp) Interpretation: Volatility observation is a clamped z score like feature, where higher values indicate volatility expansion relative to baseline. 3) Warmup Logic The model waits for enough history to compute stable normalized observations: int warmupBars = math.max(returnZLength, volBaselineLength) + volLength bool ready = bar_index > warmupBars and not na(returnObs) and not na(volObs) Before ready, the script avoids producing live signals and uses the initial posterior distribution. 4) Transition Matrix Configuration The transition matrix uses persistence values and asymmetric drift splits: From Bull, most drift flows to Balance and a smaller portion to Bear From Bear, most drift flows to Balance and a smaller portion to Bull From Balance, drift splits evenly between Bull and Bear Core setup: this.setTransition(STATE_BULL, STATE_BALANCE, bullDrift * 0.78) this.setTransition(STATE_BULL, STATE_BEAR, bullDrift * 0.22) ... this.setTransition(STATE_BEAR, STATE_BALANCE, bearDrift * 0.78) this.setTransition(STATE_BEAR, STATE_BULL, bearDrift * 0.22) This design makes Balance act like a bridge regime and reduces unrealistic direct flip frequency. 5) Emission Model: 2D Gaussian Density Each state computes an emission probability from return and volatility observations using a 2D Gaussian likelihood: float exponent = -0.5 * ((retDeviation * retDeviation) / retVariance + (volDeviation * volDeviation) / volVariance) float normalizer = 1.0 / (2.0 * math.pi * math.sqrt(retVariance * volVariance)) math.max(normalizer * math.exp(math.max(exponent, -24.0)), EPS) Variances are floored at 0.12 to prevent collapse. 6) Prediction Step The model predicts next probabilities using the transition matrix: predictedProbability += posterior * transition(fromState, toState) Then normalizes the predicted vector so it sums to 1. 7) Filter Update Step The posterior is updated by multiplying predicted probabilities by emission likelihoods: nextPosterior = predicted * emission(state, retObs, volObs) Then normalized. The active state is the arg max of the posterior. 8) Online Adaptation The model updates state means and variances using posterior responsibility times learning rate: float responsibility = posterior * learningRate Means update by moving toward the current observation: nextMuRet = oldMuRet + responsibility * retError nextMuVol = oldMuVol + responsibility * volError Variances update toward squared error: nextVarRet = oldVarRet + responsibility * (retError * retError - oldVarRet) nextVarVol = oldVarVol + responsibility * (volError * volError - oldVarVol) All parameters are clamped to stability ranges so the model does not explode. 9) Regime Score and Confidence Score is defined as: posterior - posterior Confidence is the maximum posterior: posterior These values drive visuals and signal gating. 10) Stretch Calculation in ATR Units Stretch uses an EMA basis of price and measures distance in ATR units: float basis = ta.ema(close, stretchLength) float atrValue = math.max(ta.atr(14), syminfo.mintick) float stretch = (close - basis) / atrValue Top stretch requires: stretch >= stretchThreshold Bottom stretch requires: stretch <= -stretchThreshold This ensures reversals occur when price is statistically extended relative to recent volatility. 11) Probability Peak and Fade Logic The script measures recent peaks for bull and bear probabilities: float bullPeak = ta.highest(bullProb , peakLookback) float bearPeak = ta.highest(bearProb , peakLookback) Fade is peak minus current: bullFade = bullPeak - bullProb bearFade = bearPeak - bearProb Top rotation condition requires: Bull peak above threshold Bull fade above minimum Bear probability rising Bottom rotation requires the mirrored conditions. This captures the idea of regime dominance peaking, then fading as the opposite side begins to regain influence. 12) Momentum Flip Confirmation Momentum down requires: Regime score decreasing Return observation strongly negative below a flip threshold Momentum up requires: Regime score increasing Return observation strongly positive above the flip threshold This prevents signals when probabilities fade but momentum remains neutral. 13) Signal Gating and Cooldown Signals require confidence above the threshold and a cooldown to avoid repeated triggers: confidenceValue >= confidenceThreshold bar_index - lastSignalBar > cooldownBars 14) Buy and Sell Reversal Signals Buy reversal: Bottom rotation Momentum up Bottom stretch Confidence filter Cooldown filter Sell reversal: Top rotation Momentum down Top stretch Confidence filter Cooldown filter A Balance signal is also triggered when the state changes to Balance with sufficient confidence. 15) Visual Outputs The indicator plots: Regime score line with area fill around zero Confidence ribbon as an area band Optional posterior curves for Bull, Balance, Bear Normalized stretch line scaled by the stretch threshold Optional dots on the chart for reversal events Optional bar coloring on the main chart It also prints: Reversal labels B and S with stretch, confidence, and peak probability tooltips State tags on regime shifts A dashboard panel summarizing live state and setup context

Pine Script® Indikator

Institutional Liquidity Flow Engine [JOAT]Institutional Liquidity Flow Engine Introduction The Institutional Liquidity Flow Engine is an advanced open-source volume analysis indicator that combines relative volume monitoring, buyer/seller strength analysis, multi-timeframe alignment detection, and comprehensive flow metrics into a unified institutional-grade tool. This indicator helps traders identify when institutional money is entering or exiting positions by analyzing volume patterns, pressure dynamics, and liquidity conditions across multiple timeframes. Unlike basic volume indicators that simply show volume bars, this engine dissects volume into actionable intelligence: relative volume (RVOL) to identify unusual activity, buyer/seller strength ratios to determine who controls the market, accumulation/distribution trends to track smart money positioning, and multi-timeframe alignment to confirm directional conviction. The indicator is designed for traders who understand that volume precedes price and that institutional footprints can be detected through systematic volume analysis. Why This Indicator Exists This indicator addresses a critical gap in retail trading: the ability to detect institutional activity in real-time. Institutional traders move large positions that create detectable volume signatures. By combining multiple volume analysis methodologies, this indicator reveals: Relative Volume Analysis: Identifies when volume is significantly above or below average, signaling potential institutional activity Buyer/Seller Strength: Quantifies the balance of power between buyers and sellers using volume-weighted calculations Multi-Timeframe Alignment: Confirms whether volume patterns align across 1m, 5m, 15m, 30m, 1h, 2h, 4h, Daily, and Weekly timeframes Flow Metrics: Tracks Money Flow Index (MFI), On-Balance Volume (OBV), Accumulation/Distribution (A/D), and VWAP deviation Liquidity Classification: Categorizes market conditions as Strong Buying, Strong Selling, Balanced, or Thin liquidity Each component provides a different lens on volume behavior. RVOL shows intensity, buyer/seller strength shows direction, MTF alignment shows conviction, flow metrics show institutional positioning, and liquidity classification shows market conditions. Together, they create a comprehensive view of institutional activity. Core Components Explained 1. Relative Volume (RVOL) Analysis RVOL is calculated as current volume divided by the average volume over a specified period (default 20 bars): avgVolume = ta.sma(volume, volumeLength) relativeVolume = avgVolume > 0 ? volume / avgVolume : 1.0 The indicator classifies RVOL into five categories: Extreme (RVOL >= 3.0): Institutional-level activity, potential climax moves High (RVOL >= 1.5): Above-average activity, significant interest Normal (RVOL >= 1.0): Average activity, typical market conditions Low (RVOL >= 0.5): Below-average activity, reduced interest Very Low (RVOL < 0.5): Minimal activity, thin liquidity RVOL thresholds are customizable. Higher RVOL often precedes significant price moves as institutions accumulate or distribute positions. 2. Buyer/Seller Strength Analysis The indicator calculates buyer and seller strength using volume-weighted analysis: buyerVolume = close > open ? volume : 0 sellerVolume = close < open ? volume : 0 buyerStrength = ta.sma(buyerVolume, volumeLength) sellerStrength = ta.sma(sellerVolume, volumeLength) Strength ratios are calculated as percentages: Buyer Ratio: (buyerStrength / totalStrength) * 100 Seller Ratio: (sellerStrength / totalStrength) * 100 When buyer ratio exceeds 70%, bullish pressure dominates. When seller ratio exceeds 70%, bearish pressure dominates. The indicator also integrates ATR-based strength calculations to filter for significant moves and RSI-based strength classification (Strong/Moderate/Weak) for additional context. 3. Multi-Timeframe Alignment The indicator requests RVOL data from three customizable timeframes (default: 5m, 15m, 60m) and calculates alignment: mtf1_bullish = rvol_mtf1 > 1.0 and vol_mtf1 > ta.sma(vol_mtf1, 20) mtfAlignment = (mtf1_bullish ? 1 : 0) + (mtf2_bullish ? 1 : 0) + (mtf3_bullish ? 1 : 0) Alignment status: Strong Aligned (3/3): All timeframes show elevated volume - high conviction Aligned (2/3): Majority timeframes show elevated volume - moderate conviction Weak (1/3): Only one timeframe shows elevated volume - low conviction No Alignment (0/3): No timeframes show elevated volume - no conviction Strong alignment across multiple timeframes indicates institutional participation at scale, as large orders are often split across timeframes to minimize market impact. 4. Flow Metrics Suite Money Flow Index (MFI): Volume-weighted RSI that measures buying and selling pressure: mfi = ta.mfi(close, volumeLength) MFI > 80 indicates overbought conditions with high volume, MFI < 20 indicates oversold conditions with high volume. On-Balance Volume (OBV): Cumulative volume indicator that adds volume on up days and subtracts on down days: obv = ta.cum(math.sign(ta.change(close)) * volume) obvTrend = obv > obvMA ? "Bullish" : obv < obvMA ? "Bearish" : "Neutral" OBV divergences from price often signal reversals. Accumulation/Distribution (A/D): Measures the cumulative flow of money into and out of a security: ad = ta.cum(close == high and close == low or high == low ? 0 : ((2 * close - low - high) / (high - low)) * volume) Rising A/D with rising price confirms uptrend, falling A/D with rising price signals distribution. VWAP Deviation: Measures how far price is from volume-weighted average price: vwap = ta.vwap(close) vwapDeviationPercent = vwap != 0 ? ((close - vwap) / vwap) * 100 : 0 Large deviations often mean-revert as institutions take advantage of inefficient pricing. 5. Volume Speed & Acceleration The indicator calculates volume momentum and acceleration: Volume ROC: Rate of change in volume over 5 periods Volume Acceleration: Change in volume ROC (second derivative) Volume Momentum: Current volume minus 10-period SMA Volume Trend: Increasing or Decreasing based on EMA crossover Accelerating volume often precedes breakouts or breakdowns as institutional orders hit the market. 6. Liquidity Classification System The indicator classifies current liquidity conditions: Strong Buying: High RVOL + positive net pressure (buyer strength > seller strength) Strong Selling: High RVOL + negative net pressure (seller strength > buyer strength) Balanced: Normal RVOL with relatively equal buyer/seller strength Thin: Low RVOL indicating reduced liquidity and potential for slippage Pressure intensity is calculated as: pressureLevel = math.abs(netPressure) / avgVolume pressureIntensity = pressureLevel >= 2.0 ? "Extreme" : pressureLevel >= 1.0 ? "High" : pressureLevel >= 0.5 ? "Moderate" : "Low" Visual Elements RVOL Histogram: Main plot showing relative volume with color-coded intensity (extreme = magenta, high = yellow, normal = green, low = gray) Reference Lines: Horizontal lines at 1.0 (average), 1.5 (high threshold), and 3.0 (extreme threshold) Buyer Pressure Fill: Background fill showing buyer pressure ratio (0-100%) Volume Oscillator: Histogram overlay showing short-term vs long-term volume momentum MFI Line: Thick line overlay showing Money Flow Index with gradient colors Information Table: Comprehensive dashboard displaying all metrics in real-time The table displays 15 metrics: 1. RVOL (current relative volume) 2. Status (Extreme/High/Normal/Low/Very Low) 3. Volume Trend (Increasing/Decreasing) 4. Pressure (Bullish/Bearish/Neutral) 5. Buyer Strength (percentage) 6. Seller Strength (percentage) 7. RSI (current value) 8. Liquidity (Strong Buying/Strong Selling/Balanced/Thin) 9. MTF Alignment (Strong Aligned/Aligned/Weak/No Alignment) 10. A/D Trend (Accumulation/Distribution/Neutral) 11. OBV Trend (Bullish/Bearish/Neutral) 12. MFI (current value) 13. VWAP Deviation (percentage) 14. Volume Momentum (percentage) Input Parameters Volume Analysis: Volume MA Length: Period for volume moving average (default: 20) High RVOL Threshold: Multiplier for high volume detection (default: 1.5) Extreme RVOL Threshold: Multiplier for extreme volume detection (default: 3.0) Multi-Timeframe Settings: Show Multi-Timeframe Analysis: Toggle MTF calculations (default: enabled) Timeframe 1/2/3: Customizable timeframes for alignment analysis (default: 5m, 15m, 60m) Buyer/Seller Strength: ATR Length: Period for ATR calculation (default: 14) RSI Length: Period for RSI calculation (default: 14) RSI Overbought/Oversold: Thresholds for RSI classification (default: 70/30) Display Options: Show Info Table: Toggle information dashboard (default: enabled) Show Volume Histogram: Toggle RVOL histogram (default: enabled) Show VWAP Deviation: Toggle VWAP calculations (default: enabled) Table Position: Choose dashboard location (Top Right/Top Left/Bottom Right/Bottom Left) Colors: All colors are customizable including bullish, bearish, neutral, extreme volume, and high volume colors. How to Use This Indicator Step 1: Monitor RVOL for Unusual Activity Watch for RVOL spikes above 1.5 (high) or 3.0 (extreme). These indicate institutional activity. Extreme RVOL often marks climax moves or major reversals. Step 2: Check Buyer/Seller Strength Identify who controls the market. Buyer ratio > 70% suggests bullish control, seller ratio > 70% suggests bearish control. Look for divergences where price moves one direction but strength moves another. Step 3: Confirm with MTF Alignment Strong alignment across multiple timeframes confirms institutional conviction. Weak or no alignment suggests retail-driven moves that may lack follow-through. Step 4: Analyze Flow Metrics Check MFI, OBV, and A/D for confirmation. Rising OBV with rising price confirms uptrend. Falling A/D with rising price warns of distribution. Step 5: Assess Liquidity Conditions Strong Buying or Strong Selling conditions with high RVOL often precede significant moves. Thin liquidity conditions increase risk of slippage and false moves. Step 6: Look for Volume Acceleration Accelerating volume momentum often precedes breakouts. Decelerating volume momentum often precedes consolidation or reversal. Best Practices Use on liquid instruments (major forex pairs, large-cap stocks, major crypto) for most reliable signals Combine with price action analysis - volume shows intent, price shows result Pay attention to RVOL spikes at key support/resistance levels Look for volume divergences: price making new highs/lows without volume confirmation often fails MTF alignment is most reliable on trending markets, less reliable in choppy conditions Extreme RVOL can signal exhaustion - be cautious of chasing moves with RVOL > 5.0 Use VWAP deviation for mean reversion opportunities when price extends far from VWAP Monitor A/D and OBV for early warning signs of trend changes Indicator Limitations Volume analysis works best on liquid instruments with consistent volume patterns Low-volume instruments or off-market hours can produce unreliable RVOL readings MTF alignment requires sufficient data on all timeframes - may not work on newly listed instruments Volume precedes price but doesn't guarantee direction - high volume can occur on both breakouts and fakeouts Buyer/seller strength calculations assume close > open = buying and close < open = selling, which is a simplification RVOL thresholds may need adjustment for different instruments and market conditions The indicator shows what is happening, not why - fundamental catalysts can override technical volume patterns Extreme RVOL can persist longer than expected during major news events or market dislocations Technical Implementation Built with Pine Script v6 using: Custom RVOL calculations with dynamic thresholds Volume-weighted buyer/seller strength analysis Multi-timeframe security requests with proper lookahead settings Comprehensive flow metrics (MFI, OBV, A/D, VWAP) Volume momentum and acceleration calculations Real-time liquidity classification system Dynamic table with 15 metrics and color-coded cells Thick histogram and line plots for enhanced visibility The code is fully open-source and can be modified to suit individual trading styles and preferences. Originality Statement This indicator is original in its comprehensive integration approach. While individual components (RVOL, MFI, OBV, A/D, buyer/seller strength) are established concepts, this indicator is justified because: It synthesizes six distinct volume analysis methodologies into a unified system The multi-timeframe alignment detection provides institutional conviction measurement not available in standard volume indicators Buyer/seller strength calculations combine volume, ATR, and RSI for multi-dimensional pressure analysis The liquidity classification system categorizes market conditions in real-time Volume speed and acceleration metrics provide early warning of momentum shifts The comprehensive dashboard presents 15 metrics simultaneously for holistic volume analysis Integration of flow metrics (MFI, OBV, A/D, VWAP) with RVOL and strength analysis creates layered confirmation Each component contributes unique information: RVOL shows intensity, buyer/seller strength shows direction, MTF alignment shows conviction, flow metrics show positioning, liquidity classification shows conditions, and volume acceleration shows momentum. The indicator's value lies in presenting these complementary perspectives simultaneously with a unified classification system. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors. Volume analysis is a tool for understanding market dynamics, not a crystal ball for predicting future price movement. High volume does not guarantee profitable trades. Past volume patterns do not guarantee future volume patterns. Market conditions change, and strategies that worked historically may not work in the future. The metrics displayed are mathematical calculations based on current market data, not predictions of future price movement. High RVOL, strong buyer/seller ratios, and MTF alignment do not guarantee profitable trades. Users must conduct their own analysis and risk assessment before making trading decisions. Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions. The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool. -Made with passion by officialjackofalltrades

Pine Script® Indikator

von officialjackofalltrades

Accumulation Zone Profiles [UAlgo]Accumulation Zone Profiles is an overlay indicator that detects low volatility accumulation phases and automatically builds a fixed range volume profile for each confirmed zone. The script uses a statistical volatility model based on log returns, identifies periods where volatility compresses into an unusually quiet regime, then verifies that price action remains sufficiently sideways before confirming the zone. When a zone is confirmed, the indicator draws two complementary views: A highlighted accumulation range on the chart A fixed range volume profile drawn to the right of the zone, including Point of Control and Value Area levels The intent is to turn consolidation into a structured map. Instead of treating ranges as vague rectangles, the script assigns a volume distribution to the range so you can see where the market accepted price, where it rejected price, and which levels are most likely to matter during expansion. 🔹 Features 1) Statistical Accumulation Detection Using Log Volatility The detection engine starts from log returns r = ln(C / C ) and builds an EWMA based volatility estimate. Volatility is converted into log space and evaluated with a rolling distribution model. A z score determines whether the current volatility is unusually low relative to its own history. Zones begin when the z score falls below a configurable entry threshold and they end after volatility recovers above an exit threshold for a configurable number of confirmation bars. 2) Sideways Quality Filter With Trend Score Not every low volatility period is true accumulation. The script measures drift using a trend score defined as: absolute sum of returns divided by sum of absolute returns Lower values indicate more rotation and less directional drift. A maximum trend score filter ensures zones remain meaningfully sideways before a profile is created. 3) Non Repainting Option Using Confirmed Bars When enabled, the system only updates on confirmed bars. This reduces repainting behavior and makes zone start and zone end decisions more stable for live trading workflows. 4) Fixed Range Volume Profile Per Zone For each confirmed accumulation zone, the script builds a histogram of volume across a user selected number of price rows. Each bar’s volume is distributed into bins according to how much of that candle range overlaps each bin. This produces a true fixed range profile for the zone. The profile is drawn to the right of the zone so it does not cover price action. 5) Point of Control and Value Area Levels The highest volume row is treated as the Point of Control. Value Area High and Value Area Low are computed by expanding outward from POC until a target percent of total volume is captured. This creates a practical acceptance framework inside the zone. Optional plotting allows: Highlighting the POC row Drawing VAH and VAL lines Drawing zone boundary guides Showing an information label that summarizes zone statistics 6) Tick Alignment For Clean Levels If enabled, the zone range, bin step size, and derived levels are aligned to the instrument tick size. This produces cleaner price levels and reduces floating point noise in labels and lines. 7) Object Budget Management Volume profiles use many boxes. The script computes an effective rows value based on the number of profiles you choose to keep, then limits total box usage so you are less likely to hit platform object limits. Older profiles are deleted automatically when new ones are created. 8) Alerts Two alerts are available: Accumulation Zone Started Accumulation Zone Confirmed and Profile Created This supports automation such as watchlist monitoring and breakout preparation. 🔹 Calculations 1) Log Return and EWMA Variance The script defines log return as ln(C / C ) and uses an EWMA of squared returns as a variance proxy. Alpha for EWMA: f_alpha(int len) => 2.0 / (len + 1.0) Log return: lr = math.log(close / close ) lr := na(close ) or close == 0.0 ? 0.0 : lr EWMA variance and volatility: alphaFast = f_alpha(fastLen) var float ewmaVarR = na ewmaVarR := na(ewmaVarR ) ? lr * lr : alphaFast * (lr * lr) + (1.0 - alphaFast) * ewmaVarR vol = math.sqrt(math.max(ewmaVarR, 0.0)) 2) Log Volatility Distribution and z Score Volatility is transformed into log space to stabilize distribution behavior. The script maintains EWMA estimates of mean and second moment, then computes standard deviation and z score. eps = 1e-10 logVol = math.log(vol + eps) alphaDist = f_alpha(distLen) var float m1 = na var float m2 = na m1 := na(m1 ) ? logVol : alphaDist * logVol + (1.0 - alphaDist) * m1 m2 := na(m2 ) ? logVol * logVol : alphaDist * (logVol * logVol) + (1.0 - alphaDist) * m2 sigma = math.sqrt(math.max(m2 - m1 * m1, eps)) z = (logVol - m1) / sigma Interpretation: Negative z means volatility is below its typical level More negative z means stronger compression 3) Zone Start and Zone End Conditions Entry and exit logic uses the z score relative to thresholds: Start when z is less than or equal to minus Enter Threshold End when z is greater than or equal to minus Exit Threshold for Exit Confirm Bars lowNow = not na(z) and z <= -enterZ highNow = not na(z) and z >= -exitZ Exit confirmation counter: zb.exitCount := highNow ? zb.exitCount + 1 : 0 bool exitByConfirm = zb.exitCount >= exitBars A maximum zone duration also forces closure: bool exitByMax = zb.barCount() >= maxZoneBars If exit is triggered via confirmation bars, the script removes those last bars from the zone before profiling to avoid contaminating the accumulation range with the volatility recovery phase. 4) Sideways Drift Score Filter During zone building, returns are accumulated: sumR is the signed drift sumAbsR is total movement magnitude Trend score: method driftScore(ZoneBuilder this) => math.abs(this.sumR) / math.max(this.sumAbsR, 1e-10) A zone is accepted only if: Bar count is at least Min Zone Bars Drift score is less than or equal to Max Trend Score 5) Profile Range and Row Step Once accepted, the profile range is built from the min low and max high of the zone. The range is optionally aligned to tick. Step size equals range divided by rows, with optional tick alignment: float stepRaw = (hi - lo) / rows float step = stepRaw if alignTick step := math.max(syminfo.mintick, f_roundToTick(stepRaw)) 6) Volume Histogram Construction For each bar in the zone, volume is assigned into bins. If the candle range is very small, volume goes to a single nearest bin. Otherwise, volume is distributed proportionally by overlap between candle range and each bin range. Core proportional distribution logic: float overlap = math.max(0.0, math.min(bh, binHi) - math.max(bl, binLo)) if overlap > 0 float frac = overlap / br array.set(binVol, b, array.get(binVol, b) + bv * frac) This produces binVol, a per row volume distribution. 7) POC Calculation POC is the index of the maximum bin volume. POC price is the center of that row. if v > maxV maxV := v pocIdx := b float poc = lo + (pocIdx + 0.5) * step 8) Value Area Computation Value Area is derived by expanding outward from POC until the cumulative volume reaches Value Area percent of total volume. Target volume: float target = totV * (valueAreaPct / 100.0) Expand left and right by choosing the side with higher next volume until the target is met. This creates a contiguous value area band. VAL and VAH mapping to prices: float valP = lo + left * step float vahP = lo + (right + 1) * step 9) Rendering Logic Zone highlight is drawn directly over the accumulation period using a box with configurable fill and border transparency. The volume profile is drawn as a stack of boxes to the right of the zone. Each row width is proportional to row volume relative to max row volume. Transparency is mapped so high volume rows appear more prominent. POC row can be highlighted using a dedicated color and transparency configuration. VAH and VAL can be drawn as horizontal lines across the profile region, and optional boundary lines can mark the start and end of the detected zone. 10) Profile Retention and Cleanup Profiles are stored in an array. When the number of stored profiles exceeds Keep Last Profiles, the oldest profile is deleted and all of its objects are removed. This keeps the chart responsive and prevents reaching the platform maximum object counts.

Pine Script® Indikator

Rolling Liquidity Clusters Channel [LuxAlgo]The Rolling Liquidity Clusters Channel indicator identifies dynamic support and resistance zones by calculating levels that maximize candle wick touches while strictly avoiding intersections with candle bodies within a rolling window. This tool provides a unique perspective on liquidity clusters, highlighting price levels where historical rejection is most concentrated without being invalidated by price "closing" through them. 🔶 USAGE The indicator plots a channel consisting of an Upper Level, a Lower Level, and a Mid Level. The space between these levels is filled with a vertical gradient to visually represent the strength of the liquidity zone. Upper Level (Red): Represents a resistance zone where the most upper wicks are concentrated without any candle body in the lookback window crossing above it. Lower Level (Green): Represents a support zone where the most lower wicks are concentrated without any candle body in the lookback window crossing below it. Mid Level (Orange): Represents the equilibrium or average of the current liquidity channel. Traders can use these levels to identify potential reversal points or areas of price consolidation. A breakout from the channel might indicate a shift in market structure as price moves beyond the most inclusive "non-broken" wick levels. 🔶 DETAILS The script employs a specific constraint logic to ensure the levels represent true "untouched" liquidity: 🔹 Body-Crossing Constraint Before identifying the wick touches, the script calculates the highest candle body high and lowest candle body low within the user-defined window. The resulting levels are guaranteed to stay outside of this "body zone," ensuring that the plotted levels represent prices that the market reached but failed to sustain via a close. 🔹 Maximizing Touches To find the most significant level, the algorithm searches for the most inclusive price point. For the upper level, it identifies the lowest "high" that remains above all candle bodies. For the lower level, it identifies the highest "low" that remains below all candle bodies. This mathematical approach effectively finds the level where the most price action "clusters" via wicks. 🔹 Vertical Gradient Fills The visual style uses a vertical gradient fill. The upper half fades from 90% transparency at the Upper Level (Red) to 100% transparency at the Mid Level. The lower half follows a similar logic, fading from the Lower Level (Green) toward the center. This creates a "glow" effect, emphasizing the outer boundaries where liquidity is highest. 🔶 SETTINGS Window Size: The number of bars used for the rolling calculation. A larger window creates more stable, long-term levels, while a smaller window adapts quickly to recent price action. Upper Level: Customize the color of the upper resistance level and its associated gradient fill. Lower Level: Customize the color of the lower support level and its associated gradient fill. Mid Level: Customize the color of the central equilibrium line.

Pine Script® Indikator

Security Liquidity Liquidity could be powerful indicator to gauze the interest in a particular security. It is calculated by multiplying vwap with average volume over a period of time, e.g 20 days. This script displays the current liquidity over the current session bar as a label & gets updated in real time. Below are the settings one can choose. 1. Average Period - the look back period to calculate liquidity. Defaults to 20. 2. Source - Source of the price like hlc3 etc. 3. Label Size - How big or small you want this to be displayed. 4. Notation - The liquidity in millions or crores (for India) 5. Trend - if the current session liquidity is greater than 5 sessions ago then label color will turn green. 6. Alert - One can set alerts for any security based on liquidity. e.g if liquidity of a stock is more than 200 million then trigger an alert

Pine Script® Indikator

von tgunasekhar

Volume Energy Reservoirs [LuxAlgo]The Volume Energy Reservoirs indicator is a physics-inspired momentum tool based on a "capacitance" model that treats the market as a system storing potential energy during stability and releasing it as kinetic flow during high-volume trends. 🔶 USAGE The indicator helps traders identify periods of market compression (Squeezes) and subsequent expansion. It provides a dual-view approach with an oscillator tracking energy flow and on-chart visuals highlighting price consolidation ranges and trend climaxes. Energy Accumulation (The Box): When the yellow Energy Reservoir fills in the oscillator, a filled Squeeze Box appears on the chart. This represents the "charging" phase where the market is storing potential energy within a tight range. Range Extension (The Lines): Once the energy building phase completes, the filled box stops, and two horizontal dashed Squeeze Extension Lines project from the box's high and low. These lines define the critical support and resistance levels established during the squeeze. The Breakout: A breakout is confirmed when a candle closes above or below the extension lines. At this moment, the lines stop drawing, signaling that the stored energy has been released into kinetic momentum. Trend Monitoring: Follow the Conviction Gradient on the background (default 75% transparency) and the vibrant Kinetic Aura in the oscillator to gauge the strength of the move. Exhaustion (The Exit): Look for Exhaustion Bubbles on the chart. A Red bubble at a bullish peak or a Green bubble at a bearish trough indicates the trend's "fuel" is spent. Larger bubbles represent higher-volume climaxes. 🔶 DETAILS The script utilizes a unique "Energy Reservoir" logic to quantify market state by using relative displacement math rather than absolute price values, making it adaptive across different asset classes. 🔹 Squeeze Mechanism The system transitions through three distinct visual states: Active Squeeze: A filled yellow box that dynamically expands its high and low boundaries as long as the "Energy Reservoir" is charging (Reservoir > 5). Post-Squeeze Extension: Once the reservoir level drops, the box is locked. Two horizontal dashed lines extend to the right from the box's maximum high and minimum low. Breakout Termination: The extension lines persist until the market price closes outside of the defined range, providing a clear visual of the "Range to Beat." 🔹 Exhaustion & Conviction Exhaustion Bubbles: These signals are specifically coded to ignore consolidation zones, only appearing during active trends when momentum begins to fade at an extreme. Size is determined by relative volume. Conviction Gradient: A thermal background heatmap (Teal for Bullish, Red for Bearish) that tracks trend conviction directly on the price chart. The default transparency is set to 75 to ensure a balance between visibility and chart clarity. Kinetic Aura: A vertical gradient glow in the oscillator that scales with the asset's recent volatility and volume-weighted flow. 🔶 SETTINGS 🔹 Main Settings Energy Horizon: The lookback period used to calculate the price midpoint and range stability for energy accumulation. Energy Sensitivity: Adjusts how quickly energy is released during volume spikes. Higher values require more significant volume to discharge the reservoir. 🔹 Visual Settings Highlight Squeeze Range: Toggles the drawing of the filled box and the subsequent extension lines on the chart. Show Exhaustion Bubbles: Toggles the volume-weighted bubbles that appear during momentum extremes. Show Conviction Gradient on Chart: Toggles the thermal background gradient on the main price chart. Background Transparency: Adjusts the maximum opacity of the on-chart conviction gradient (Default: 75).

Pine Script® Indikator

Chaikin Money Flow with Shaded Backgound This script is a modernized version of Chaikin Money Flow with time‑horizon presets, Histogram Mode, and Regime Background Shading. Preset Modes Daily – Standard (20): Classic CMF(20), ideal for swing trading. **Weekly – Short (5): Time‑scaled equivalent of CMF(20) for weekly charts. Monthly – Smooth (10): Long‑cycle accumulation/distribution smoothing. Manual: Full control over CMF length. These presets are designed to maintain **consistent time‑horizon behavior** across different chart timeframes. Line: Traditional CMF line. Histogram: Momentum‑style histogram. Hybrid: Line + histogram. CMF‑SMA Mode: Histogram shows CMF minus its SMA. CMF Change Mode: Histogram shows bar‑to‑bar CMF acceleration. Note: When using Histogram Mode, switch the Histogram Type input between CMF‑SMA and CMF Change depending on the style you want. Green: CMF > 0 (Accumulation) Red: CMF < 0 (Distribution) This provides a clean, structural read of market pressure without cluttering the chart.

Pine Script® Indikator

von followmytradingjournal

Hidden Markov Model Market Regimes [LuxAlgo]The Hidden Markov Model Market Regimes tool provides a probabilistic framework for identifying the current state of the market by applying a Hidden Markov Model (HMM) to price action and volatility data. 🔶 USAGE The indicator identifies four distinct market regimes. Each regime is represented by a unique color, and the oscillator values (0-100%) represent the probability of the market being in that specific state. 🔹 Regime Breakdown & Trading Implications Low Volatility Trend (Gray): Characterized by steady, consistent returns with minimal price swings. Ideal for trend-following strategies and "buy-and-hold" positions. High Volatility Chop (Orange): Large price swings without a clear directional trend. Suggests a "risk-off" environment or mean-reversion strategies. Crash Regime (Red): Extreme negative returns coupled with a spike in volatility. Indicates high panic; traders may look for hedging opportunities. Accumulation (Blue): Low volatility with neutral-to-rounding price action. Often occurs at the end of a bear cycle, signaling a potential "bottom-fishing" zone. 🔹 Visual Cues The indicator features background highlighting that changes based on the "Dominant State" (the state with the highest current probability). When a specific probability line crosses above the 50% "Neutral" line, the model is gaining conviction. Crosses above 80% indicate "High Confidence" in that regime. Users should watch for "probability flips," where one regime's dominance is rapidly overtaken by another, signaling a structural shift in the market. 🔶 DETAILS The script implements a specialized version of the Forward Algorithm to estimate the likelihood of hidden states. 🔹 Heuristic vs. Trained ML It is important to note that this indicator is accurately described as a "Heuristic" or "Static" HMM rather than a traditional Machine Learning model. Unlike modern ML models that require extensive training on historical datasets (using algorithms like Baum-Welch or Expectation-Maximization), this model uses fixed mathematical parameters and predefined heuristic-based emission profiles. This approach ensures deterministic behavior—the model will always react to the same price patterns in the same way—and eliminates the "black box" nature of traditional ML while still providing the probabilistic benefits of a Markov chain. 🔹 Mathematical Logic Log Returns: The model utilizes log returns ( TSX:LN (Close_{t} / Close_{t-1})$) rather than simple percentage changes to ensure time-additivity and a more symmetric distribution of data. Emission Likelihoods: The model uses Gaussian-style probability density functions to compare normalized returns and volatility against "ideal" profiles for each state. For example, the Crash Regime likelihood increases when returns are significantly below the mean and volatility is significantly above the mean. Transition Matrix (Markov Property): This defines the "memory" of the system. The matrix is weighted toward "persistence" (diagonal values), meaning the market is statistically more likely to stay in its current regime than to jump to a different one every bar. 🔶 SETTINGS 🔹 HMM Settings Lookback Period: The window used to calculate the mean and standard deviation for normalizing returns and volatility. Learning Rate: Controls how quickly the model updates its internal probabilities. Range: 0.01 (very slow/stable) to 1.0 (instant/reactive). 🔹 Dashboard Enable Dashboard: Toggles the visibility of the on-screen information table. Position: Determines where the dashboard is anchored (Top Right, Bottom Right, or Bottom Left). Size: Adjusts the scale of the dashboard text and cells.

Pine Script® Indikator

Accumulation/Distribution Line (Volume Surge Markers) - TP This indicator plots a classic Accumulation/Distribution (A/D) Line, built manually from the candle’s close position and volume, then adds circle markers when volume spikes versus the previous bar. What the A/D Line means (in plain English) Think of each candle as a “battle” between buyers and sellers: If the candle closes near the high, that bar is treated as buying pressure (accumulation). If the candle closes near the low, that bar is treated as selling pressure (distribution). If it closes near the middle, it’s more neutral. The script converts that “close location” into a score from -1 to +1, multiplies it by volume, then cumulates it over time. So the A/D line rises when “buying-style” bars dominate, and falls when “selling-style” bars dominate. Volume Surge Circles A circle prints when the current bar’s volume is at least 50% higher than the previous bar (default). This helps you spot moments where participation suddenly increases and can confirm (or warn) about moves. Best way to use it This tool is most useful when you overlay it on the price chart (like in the screenshot), so you can quickly compare: price trend vs A/D trend (divergences), and where volume surges occur relative to breakouts, pullbacks, or reversals. Tip: Watch for cases where price keeps rising but the A/D line goes flat or down — that can hint the move is losing real accumulation.

Pine Script® Indikator

Aktualisiert

Multi-Metric Valuation Indicator Multi-Metric Valuation Indicator - Accumulation/Distribution Signal This indicator combines six proven technical metrics into a single composite valuation score to help identify optimal accumulation and distribution zones for any asset. Built with the Mayer Multiple as its foundation, it provides a comprehensive view of whether an asset is overvalued or undervalued. Core Components: Mayer Multiple - Compares current price to 200-day moving average (traditional Bitcoin valuation metric) RSI (Relative Strength Index) - Identifies overbought/oversold momentum conditions Bollinger Band Position - Measures price location within volatility bands 50-Day MA Deviation - Tracks short-term trend strength Rate of Change (ROC) - Captures momentum shifts Volume Analysis - Confirms price moves with relative volume strength How It Works: Each metric is scored from -1 (extremely undervalued) to +1 (extremely overvalued) using granular thresholds. These scores are averaged into a composite valuation score that oscillates around zero: < -0.4: Strong Accumulation Zone (dark green background) -0.4 to -0.2: Accumulation Zone (light green background) -0.2 to +0.2: Neutral Zone (gray background) +0.2 to +0.4: Distribution Zone (light red background) > +0.4: Strong Distribution Zone (dark red background) Key Features: Real-time scoring table displays all component values and their individual scores Color-coded composite line (green = undervalued, red = overvalued) Background shading for instant visual signal recognition Built-in alerts for strong accumulation/distribution crossovers Fully customizable inputs for all parameters Clean, efficient code using ternary operators and one-line declarations Best Use Cases: Long-term position accumulation strategies Identifying macro market tops and bottoms Dollar-cost averaging entry/exit planning Multi-timeframe confirmation (works on daily, weekly, monthly charts) Risk management and position sizing decisions Interpretation: When the composite score drops below -0.4, multiple metrics simultaneously indicate undervaluation - a historically favorable accumulation opportunity. Conversely, scores above +0.4 suggest distribution may be prudent as multiple indicators flash overbought signals. The indicator is most powerful when combined with fundamental analysis and proper risk management. It's designed to keep emotions in check during extreme market conditions.

Pine Script® Indikator

von MonkeyPhone

Accumulation & Distribution Days Histogram WHAT IT TRACKS: • Distribution Days (Selling Pressure): Price closes down >0.2% on higher volume than previous day • Accumulation Days (Buying Pressure): Price closes up >0.2% on higher volume than previous day HOW IT WORKS: The histogram displays a rolling count of distribution and accumulation days within your chosen lookback period (default: 20 bars). Green bars show accumulation days above the zero line, while red bars show distribution days below the zero line. A white line plots the net difference (accumulation minus distribution) to show the overall balance. SETTINGS: • Lookback Period: Number of bars to count (default: 20) • Price Threshold: Minimum % move required (default: 0.2%) • Colors: Fully customizable histogram colors USAGE: Use this to gauge the balance between buying and selling pressure. When accumulation exceeds distribution, it suggests bullish pressure. When distribution exceeds accumulation, it suggests bearish pressure. The indicator can also serve as a market health filter: • 0-3 Distribution Days: Bullish market condition - healthy for long positions • 4-5 Distribution Days: Cautious - monitor for potential trend change • 6+ Distribution Days: Bearish signal - institutional selling intensifying Other potential uses to explore: • Divergence analysis: Price making new highs while distribution days cluster • Sector rotation: Compare distribution/accumulation across different sectors • Entry timing: Wait for accumulation to exceed distribution before entering • Risk management: Reduce position size as distribution days increase Experiment with different lookback periods and thresholds to match your trading timeframe and style. If you discover effective ways to use this indicator, please share in the comments below - your insights could help others, enjoy.

Pine Script® Indikator

Chaikin Oscillator Z-Score With Divergences [MAXmks]Hello Traders, This is my take on the Chaikin Oscillator — statistically normalized into a Z-Score with built-in divergence detection. The problem with raw Chaikin The standard ChO is unbounded and extremely sensitive to volume spikes. A single anomalous bar can flatten the entire oscillator, making it hard to compare signals across time or between instruments. The fix Z-Score normalization with asinh (inverse hyperbolic sine) transformation. While standard Z-Scores assume a normal distribution, market data often features "fat tails" (extreme outliers). This transformation compresses those spikes effectively, ensuring the indicator remains responsive without getting stuck during high-volatility events. The result: a more comparable scale across instruments. What's inside: Adaptive normalization + EMA-based variance for smooth Z calculation Regular and hidden divergence detection with segment validation (fewer false signals) Gradient coloring that intensifies toward extremes Dashboard with current Z value Pre-built alerts for OB/OS entries/exits and all divergence types Note: This is a volume-based indicator. No volume = no signal. If you see "No Volume Data" in the dashboard, switch to a data source that provides volume. Works on any timeframe. Feedback welcome. For analysis purposes, not financial advice.

Pine Script® Indikator

Aktualisiert

Die ausgewählten Marktdaten werden von ICE Data Services bereitgestellt.Die ausgewählten Referenzdaten werden von FactSet. Copyright © 2026 FactSet Research Systems Inc.Copyright © 2026, American Bankers Association bereitgestellt. Die CUSIP-Datenbank wird von FactSet Research Systems Inc. bereitgestellt. Alle Rechte vorbehalten.Die SEC-Einreichungen und sonstigen Dokumente werden von Quartr bereitgestellt.© 2026 TradingView, Inc.

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