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Volumespreadanalysis

Vortex Volume Spectrum [JOAT]Vortex Volume Spectrum Overview Vortex Volume Spectrum is a dynamic, proportional volume profile indicator built from scratch in Pine Script v6. It analyses how traded volume distributes across price levels within any configurable lookback window, identifies the Point of Control (POC) — the price level with the highest volume concentration — and draws the Value Area (the 70% of total volume nearest the POC) as a live-updating profile rendered directly on the chart using the box drawing API. Unlike fixed-range volume profiles offered by some platforms, this engine recalculates on every bar and is fully parametric. Why Build a Volume Profile in Pine? Volume profile is one of the most powerful market microstructure tools available, revealing where the majority of market participants transacted. Most TradingView users rely on the built-in session profile which cannot be customised, scripted, or combined with other logic. Vortex Volume Spectrum gives Pine authors and traders a fully transparent, open-source volume distribution engine they can understand, modify, and build upon — with the visual quality of a professional charting suite. Distribution Engine The profile is built with a configurable number of price bins (default 30) spanning the high-to-low range of the lookback window. For each bin, the engine calculates the proportional contribution of each historical bar's volume using an overlap method: Each bar contributes volume proportionally to the fraction of its high-to-low range that overlaps with each bin. A bar spanning multiple bins splits its volume across all overlapping bins by the fraction of overlap — preventing the unrealistic "winner takes all" binning used by simpler implementations. This overlap-proportional distribution produces a smooth, accurate volume histogram that closely mirrors the actual traded price distribution. POC Detection After computing the full distribution array, the engine scans for the bin with the highest accumulated volume. This bin's midpoint is the Point of Control — the price level where the most volume traded during the lookback window. The POC is highlighted as the brightest horizontal line in the profile. Value Area (70%) Calculation Starting from the POC bin, the Value Area algorithm expands outward — one bin up and one bin down in alternating steps — absorbing bins into the Value Area until their cumulative volume equals or exceeds 70% of total profile volume. The result is a price range (Value Area High and Value Area Low) that contains the bulk of institutional activity. This range is where the majority of price acceptance occurred and serves as a reference for mean-reversion and breakout trading contexts. Live Rendering at barstate.islast The entire profile is rebuilt from scratch on each bar's final tick using the delete-before-create pattern: all existing profile boxes are deleted before redrawing. This ensures that the profile is always current without leaving ghost boxes on the chart. Each bin is drawn as a horizontal box scaled to its volume proportion relative to the maximum bin, using a gradient colour from muted (low volume) to bright teal (near-POC), with the POC bin rendered in gold. Profile Elements - Volume bins: Horizontal boxes scaled by proportional volume, coloured by intensity - POC line: Gold horizontal line at the maximum-volume price level - Value Area High / Low lines: Teal dashed lines marking the 70% value area boundary - Volume Delta overlay: For each bar, buy volume (close > open) and sell volume (close < open) are tracked separately and displayed as a delta bar, showing the directional pressure within the profile window Inputs Reference - Profile Length (100) — number of bars included in the lookback window - Number of Bins (30) — vertical resolution of the price distribution - Profile Width (40 bars) — horizontal width of the rendered boxes - Show POC Line — toggles the gold POC highlight - Show Value Area — toggles the 70% Value Area High/Low lines - Show Volume Delta — toggles the delta bar visualisation - Profile Offset (0) — shifts the profile left or right from the current bar - Theme: Dark / Light / Auto How to Use 1. Add to any chart. The profile automatically spans the last N bars (configurable lookback). 2. The POC (gold line) is the most significant reference level — price tends to be attracted back to the POC when trading away from it. 3. The Value Area High and Low act as potential support/resistance zones. Breakouts above VAH with volume expansion are bullish continuation signals; breakouts below VAL signal bearish continuation. 4. If price is trading within the Value Area, expect range behaviour with mean reversion toward the POC. 5. Volume Delta bars help identify whether the current session's participation is predominantly buying or selling within the profiled window. Non-Repainting Design The profile always renders at barstate.islast using only confirmed historical bar data. No forward-looking data is accessed. The POC and Value Area lines represent historical distribution within the defined lookback and do not shift on historical bars. Limitations - Volume profiles are most meaningful on instruments with genuine, transparent volume (equities, futures, crypto on-chain exchanges). Forex tick volume is a proxy and may produce less reliable distribution shapes. - Increasing the number of bins significantly increases the number of box objects drawn, approaching TradingView's per-indicator box limit on very long lookbacks. - The profile always represents the most recent N bars — it does not anchor to specific sessions or swing levels. Session-anchored profiles require different logic. - Very low-volume bins at the extremes are accurate but may appear invisible at small chart scales. Disclaimer This indicator is provided for educational and informational purposes only. Volume profile is a descriptive market microstructure tool and does not predict future price movement. Always use proper risk management in conjunction with your own analysis. Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
Strata Volume Contour [JOAT]Strata Volume Contour Introduction Strata Volume Contour (SVC) is an open-source dynamic volume profile engine that divides a configurable lookback window into 25 equidistant price bins and accumulates the total traded volume within each bin. The result is a real-time horizontal histogram drawn to the right of the current bar, showing exactly where the market has spent the most volume over the selected period. The Point of Control (POC) — the highest-volume bin — is highlighted as the dominant fair-value level. The Value Area — the range of bins containing 70% of total volume — is shaded to mark the institutional accumulation zone. The problem SVC solves is the inability of time-based charts to show volume distribution across price levels. Standard volume bars show how much was traded each period, but not at which prices. Volume profile reveals the price levels that attracted the most participation — these are the levels where institutional orders were concentrated, making them the most meaningful support and resistance references available. SVC brings this institutional-grade analysis directly to the chart without requiring specialized volume profile software. Core Concepts 1. Price Range Binning The indicator determines the highest high and lowest low across the full lookback window, then divides this range into 25 equal-width bins. Each bin represents a price zone: float rangeHi = ta.highest(high, math.min(bar_index + 1, lookback)) float rangeLo = ta.lowest( low, math.min(bar_index + 1, lookback)) float binStep = (rangeHi - rangeLo) / BINS A zero-range guard (binStep > 0) prevents division errors on flat or illiquid instruments. With 25 bins, the histogram provides enough granularity to identify structural features while remaining visually clean. 2. Volume Accumulation (Performance-Gated) Volume accumulation runs exclusively on the last bar of the chart (barstate.islast). This is a critical design decision: running the O(bins x lookback) double-loop on every bar within the lookback window would create an O(bars x bins x lookback) computational cost that exceeds TradingView's execution limits on longer charts. By gating to the last bar, the full recalculation costs O(bins x lookback) exactly once per chart update: if barstate.islast if binStep > 0.0 for i = 0 to BINS - 1 float binLevel = rangeLo + binStep * i float binVol = 0.0 for k = 0 to lookback - 1 if math.abs(close - binLevel) <= binStep binVol += nz(volume , 0.0) array.set(volBins, i, binVol) Each bar within the lookback is assigned to the nearest bin based on its closing price. 3. Point of Control (POC) The POC is the bin with the highest accumulated volume. It represents the price level where the most trading activity occurred over the lookback period. Markets tend to use the POC as a magnet — price is attracted to it during consolidation and uses it as a reference when transitioning between ranges. The POC is rendered with a distinct highlight color (default orange) to make it immediately identifiable. 4. Value Area Calculation (70% Rule) The Value Area is determined by a symmetric expansion algorithm. Starting from the POC, the algorithm expands outward one bin at a time, always adding the bin (above or below) that contributes the most volume, until the accumulated volume within the expanding range reaches 70% of total volume: while vaVol < vaTarget and (vaLow > 0 or vaHigh < BINS - 1) float addUp = vaHigh < BINS - 1 ? array.get(volBins, vaHigh + 1) : 0.0 float addDn = vaLow > 0 ? array.get(volBins, vaLow - 1) : 0.0 if addUp >= addDn and vaHigh < BINS - 1 vaHigh += 1 vaVol += addUp else if vaLow > 0 vaLow -= 1 vaVol += addDn The Value Area High (VAH) and Value Area Low (VAL) define the institutional accumulation zone. Price outside the value area represents a premium (above) or discount (below) relative to the lookback period's fair value. 5. Horizontal Histogram Visualization Each bin is drawn as a horizontal box extending rightward from the current bar. The box width is proportional to the bin's volume relative to the POC volume — the POC spans the maximum width (50 bars right), and all other bins scale proportionally. Volume amounts are labeled on each bar. Features 25-Bin Volume Profile Histogram: Full horizontal volume distribution rendered to the right of price with proportional bar widths and volume labels Point of Control (POC): Highest-volume bin highlighted in a distinct color (default orange) with automatic detection each bar update Value Area (VAH / VAL): The 70%-volume range shaded in a distinct color, with Value Area High and Low explicitly tracked and displayed in the dashboard Gradient Bin Coloring: Each non-POC, non-VA bin is colored on a gradient from low volume (nearly transparent) to high volume (full opacity), creating a visual density map Static Level Plots: All 25 bin levels are plotted as horizontal lines over the lookback window, providing a persistent price level grid even without the boxes visible Price vs POC Context: The dashboard reports whether price is currently Above POC, Below POC, or At POC 8-Row Dashboard (Top Right): POC price, VA High, VA Low, price vs POC relationship, total volume, lookback period, and version Watermark: JackOfAllTrades signature at chart center-bottom Input Parameters Profile Settings: Lookback Period: Number of bars to include in the volume accumulation (default: 200, range: 50-500) Visual Settings: Show Volume Bins: Toggle the horizontal histogram boxes Bin Color: Base color for the bin gradient (default: blue) Bin Width: Border width of histogram boxes (default: 1, range: 0-5) Highlight POC: Toggle POC highlighting POC Color: Color for the highest-volume bin (default: orange) Show Value Area: Toggle the 70%-volume range shading VA High Color: Color for the Value Area High reference VA Low Color: Color for the Value Area Low reference Theme: Auto, Dark, or Light How to Use This Indicator Step 1: Identify the Point of Control The POC is the most important level on the profile. It is the price the market spent the most time trading at — the ultimate fair-value anchor. Price below the POC is at a discount; above is at a premium. Trading setups at the POC during retest often exhibit tight risk/reward. Step 2: Use Value Area Boundaries for Support and Resistance The Value Area High and Low are the primary structural boundaries. Price often oscillates within the value area and struggles when attempting to leave it. A close outside the value area with high volume often signals the beginning of a new directional move. Step 3: Adjust Lookback to Your Trading Style Shorter lookbacks (50-100 bars) produce a profile of recent price structure, relevant for intraday traders. Longer lookbacks (300-500 bars) produce a macro structural view, relevant for swing traders. The POC and value area boundaries shift as the lookback changes. Step 4: Watch Price Return to the POC After price moves away from the POC, it frequently returns to it during low-volume periods. When price is far from the POC and trending, the POC can serve as a magnet target for reversion. When price is oscillating around the POC, it reflects a balanced, two-sided auction. Indicator Limitations The profile recalculates only on barstate.islast — it reflects the state at the last confirmed bar. During real-time market hours, the profile is not updating tick-by-tick; it updates each time a bar closes The volume accumulation assigns each bar to a bin based on closing price, not the intrabar high-low range. This is a simplification — a professional volume profile distributes volume across all prices touched during the bar. The close-based method is computationally feasible within Pine Script's constraints The 25-bin resolution is fixed. Very large price ranges (e.g., a lookback spanning a major crash) may produce bins too wide to be structurally meaningful. Users should adjust the lookback to keep the range within a reasonable structural period Instruments with no volume data (some indices, spot forex) will show all zero bins and the profile will not render meaningfully The histogram boxes are drawn to the right of the current bar. On instruments with extended right-side padding disabled, the boxes may be partially hidden off-chart Originality Statement SVC is original in its approach to making volume profile accessible within Pine Script's performance constraints. This indicator is published because: The barstate.islast performance gate is the key design innovation — it collapses what would otherwise be an O(bars x bins x lookback) computation into a single O(bins x lookback) pass, making a 25-bin volume profile with 500-bar lookback feasible within TradingView's execution limits The 70% Value Area algorithm uses a symmetric expansion approach (always adding the larger of the next bin up or down) that correctly implements the standard Volume Profile Value Area methodology The gradient bin coloring uses color.from_gradient() against the POC volume as the maximum reference, making the visual density map adaptive to the actual volume distribution rather than a fixed scale The Price vs POC contextual label in the dashboard provides an immediately actionable market context read without requiring the user to visually judge their position relative to the histogram 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. Volume profile levels are based on historical volume distribution and represent areas of past interest, not guarantees of future price behavior. The Point of Control and Value Area boundaries can and do shift significantly as the lookback window evolves. Always use proper risk management. The author is not responsible for any trading losses resulting from the use of this indicator. -Made with passion by jackofalltrades
Indicador Pine Script®
por officialjackofalltrades
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
Indicador Pine Script®
por 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
Indicador Pine Script®
por officialjackofalltrades
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Confluence Signal Engine [JOAT]Confluence Signal Engine Introduction Most traders encounter a common trap: stacking multiple indicators that all claim to measure something different, yet each one is ultimately derived from the same price data. The result is not confirmation — it is correlated noise presented as agreement. The Confluence Signal Engine was built to address this directly. This indicator assigns a composite score to the current market condition by evaluating six deliberately chosen dimensions of market behavior. Each dimension is designed to measure a fundamentally different property of price action. When multiple dimensions agree, that agreement carries more weight than any single indicator firing alone. The result is a single, normalised score between -1 and +1, accompanied by a visual confidence meter and a score breakdown table so you can see exactly what is driving the signal. This is an overlay indicator — it plots directly on the price chart. --- Core Concepts The Six Scoring Dimensions Each dimension returns one of three values: +1 (bullish contribution), -1 (bearish contribution), or 0 (neutral / insufficient data). These are summed and divided by 6.0 to produce the composite score. D1 — EMA Alignment (Trend Direction) Compares a fast EMA to a slow EMA. If the fast EMA is above the slow EMA, the trend dimension scores +1. If below, it scores -1. This is the structural backbone — a baseline read on which side of the trend the price currently sits. D2 — Price Z-Score (Statistical Deviation) Calculates how many standard deviations the current close is from a baseline EMA. A Z-score below the negative threshold suggests the price has deviated far enough below the mean to be considered statistically stretched — a potential reversion candidate, scored +1. A Z-score above the positive threshold scores -1. This dimension does not measure trend; it measures relative price position against recent statistical norms. D3 — Volume Pressure (Demand Validation) Uses a Volume RSI (RSI applied to volume over 8 bars, divided by 50) as a proxy for whether volume activity is elevated. When volume pressure exceeds the threshold, the candle's direction (close vs. open) determines the score: a bullish candle in high-volume conditions scores +1; a bearish candle scores -1. When volume is not elevated, this dimension returns 0, contributing nothing. This prevents volume noise on low-activity bars from polluting the signal. D4 — RSI Momentum (Momentum Quality) Evaluates both the current RSI value and its slope. A rising RSI above 50 scores +1 — confirming that momentum is positive and strengthening. A falling RSI below 50 scores -1. This differs from a simple RSI threshold because the slope requirement means momentum must be actively moving in the scored direction, not merely sitting above or below a level. D5 — Structural Position (Range Placement) Compares the current close to the midpoint of the highest high and lowest low over a configurable lookback period. Closing above the midpoint scores +1; closing below scores -1. This is a simple but useful structural context: is price holding in the upper or lower half of its recent range? D6 — Volatility Context (Environment Quality) Divides a fast ATR by a slow ATR to produce a volatility ratio. A low ratio (calm, contracting volatility) scores +1 — historically a more favorable environment for trend continuation. A high ratio (expanding, elevated volatility) scores -1, flagging that the current environment may be erratic. A ratio between the two thresholds is neutral. This dimension does not predict price direction; it assesses whether current conditions are conducive to acting on the other signals. --- Composite Score and Confidence compositeScore = (D1 + D2 + D3 + D4 + D5 + D6) / 6.0 confidence = math.abs(compositeScore) * 100 The composite score ranges from -1.0 (all six dimensions bearish) to +1.0 (all six dimensions bullish). The confidence value is simply the absolute magnitude — a score of ±1.0 represents 100% agreement across all dimensions, while a score near 0 represents disagreement or neutrality. Signal thresholds: Score > buy threshold (default 0.3) → bullish signal Score < sell threshold (default -0.3) → bearish signal Score > high-confidence threshold (default ±0.6) → high-confidence signal Signals are gated by barstate.isconfirmed — they only fire on fully closed bars, preventing intra-bar repainting. State tracking also prevents the same directional signal from repeating consecutively without a change in direction first. --- Visual Components 24-Cell Gradient Confidence Meter A horizontal bar of 24 cells is displayed at the bottom of the chart. The left side is the bearish extreme, the center is neutral, and the right side is the bullish extreme. The current composite score position is highlighted within the meter, giving a continuous visual read of where the market sits in the conviction range — not just whether a signal has fired, but how strongly. Score Breakdown Table A table showing three columns for each dimension: dimension name, dimension number, and its current score (+1, -1, or 0). This allows you to see exactly which dimensions are contributing to the composite and which are neutral or conflicting. Gradient Bar Coloring Price bars are colored using a gradient that interpolates from a neutral color toward the signal color, weighted by the absolute value of the composite score. A high-confidence bull signal produces a strong green bar; a low-confidence or mixed signal produces a muted or neutral color. This keeps bar coloring proportional to actual conviction rather than using a binary flip. --- Features Six-dimension composite scoring system covering trend, statistics, volume, momentum, structure, and volatility Composite score normalised to with confidence percentage Non-repainting: all signals confirmed on bar close via barstate.isconfirmed State-tracked signals prevent repeated same-direction firing 24-cell gradient confidence meter with continuous position display Score breakdown table showing each dimension's individual contribution Gradient bar coloring proportional to conviction level Configurable thresholds for all six dimensions and signal levels --- Input Parameters EMA Fast / Slow (default 21 / 55) — D1 trend alignment Z-Score Baseline EMA (default 50) — the mean used for Z-score calculation Z-Score Window (default 50) — standard deviation lookback Z-Score Threshold (default 1.5) — how many standard deviations trigger the score Volume RSI Length (default 8) — RSI period applied to volume Volume Threshold (default 1.2) — Volume RSI / 50 must exceed this to activate D3 RSI Length (default 14) — standard RSI period for D4 Structure Lookback (default 20) — bars used to define the high/low range for D5 ATR Fast / Slow (default 14 / 50) — periods for the volatility ratio in D6 Volatility Thresholds (default 0.8 / 1.5) — low and high boundaries for the ATR ratio Buy Threshold (default 0.3) — minimum composite score to generate a long signal Sell Threshold (default -0.3) — maximum composite score to generate a short signal High-Confidence Threshold (default ±0.6) — score level at which a signal is classified as high-confidence --- How to Use Apply to any chart. The overlay paints directly on price bars. Watch the confidence meter for the current composite score position. A score pressed toward either extreme with multiple dimensions aligned is a higher-quality read than one sitting near center. Use the score breakdown table to understand why the composite score is what it is. If only 2 of 6 dimensions are contributing, the signal is weaker regardless of whether it crossed the threshold. High-confidence signals (score beyond ±0.6 by default) indicate that four or more of the six dimensions are in agreement. These can be treated as stronger setups than threshold-level signals. Combine the composite score read with your own price action, support/resistance, or higher-timeframe context before entering a trade. This indicator is a confluence tool, not a standalone entry system. If several dimensions are conflicting (score near 0), the market is not in a clear state — no action is the appropriate response. --- Limitations No indicator can predict future price. The composite score reflects current market conditions based on recent historical data — not what will happen next. Z-score and structural position dimensions are mean-reverting in nature, while EMA alignment and RSI momentum are trend-following. In strongly trending markets, D2 and D5 may produce persistent bearish readings even during a healthy uptrend, suppressing the composite score. This is by design — the indicator is more suited to environments where confluence across all dimensions is achievable. Volume RSI (D3) is only reliable on instruments and timeframes with consistent, meaningful volume data. On synthetic instruments, indices, or very low-timeframe charts, volume data may be unreliable and D3's contribution should be weighted accordingly. The volatility context dimension (D6) measures the environment , not direction. A low-volatility score of +1 does not mean the market is about to move up — only that conditions are historically more favorable for clean signals. Signal state tracking prevents consecutive same-direction signals, which reduces noise but also means the indicator will not re-fire during a prolonged trending move. This is a deliberate design choice but should be understood before use. Default thresholds were chosen for general applicability. Different asset classes, timeframes, and volatility regimes may benefit from threshold adjustment. Past signal quality on any given instrument does not guarantee future performance. --- Originality Statement The core innovation of this indicator is the deliberate selection of six dimensions that measure fundamentally different market properties rather than multiple views of the same property. Standard multi-indicator approaches tend to combine RSI, MACD, and Stochastic — all of which are momentum oscillators derived from price, generating correlated signals that appear independent but are not. This indicator separates the problem into distinct domains: trend direction (EMA alignment), statistical deviation from the mean (Z-score), demand-side pressure (Volume RSI), momentum quality and direction (RSI slope + level), structural placement within recent range (midpoint comparison), and environmental favorability (ATR ratio). Because these dimensions are largely uncorrelated with each other, genuine multi-dimension agreement represents a qualitatively different kind of confluence than stacking three oscillators. The 24-cell gradient meter goes further — it provides a continuous conviction read rather than a binary signal, treating market condition as a spectrum. --- Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any security. All trading involves risk, including the possible loss of principal. Past indicator performance does not guarantee future results. Always conduct your own research and consult a qualified financial professional before making any trading decisions. -Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
Volatility Squeeze Oscillator [JOAT]Volatility Squeeze Oscillator Introduction Volatility does not move randomly. It compresses, coils, and then releases — and the magnitude of the release is frequently proportional to the depth and duration of the compression. This relationship between volatility contraction and subsequent expansion is one of the most durable patterns in market behavior across all asset classes and timeframes. The Volatility Squeeze Oscillator is built to quantify this relationship with precision, using a multi-layered analysis framework that goes well beyond standard squeeze detection. At its core, the indicator uses an ATR compression ratio engine to measure the difference between a short-term and long-term ATR. When the short-term ATR is smaller than the long-term ATR, volatility is contracting — the market is coiling. When the short-term ATR expands beyond the long-term reference, the coil is releasing. This compression differential is normalized against the high-low range, making the oscillator comparable across different instruments and volatility regimes. Three additional analytical layers are stacked on top of the compression engine. A cumulative delta proxy estimates buying versus selling pressure within each bar using range-based calculations — no Level 2 or order flow data required. A volume RSI module measures whether the current volume is elevated relative to its own history, providing a confluence filter that separates high-conviction from low-conviction squeeze releases. And a statistical deviation band system built on a 200-bar lookback marks the historically significant boundaries of the squeeze oscillator's own distribution, so traders can identify not just whether a squeeze is forming, but how extreme it is relative to its own history. Core Concepts 1. ATR Compression Ratio Engine The compression ratio is derived from two ATR calculations at different smoothing periods. Both use EMA smoothing rather than RMA (Wilder's method) to produce a more responsive and visually cleaner oscillator. The short-term ATR reflects current volatility conditions. The long-term ATR (calculated at double the base period) establishes the reference level representing the recent historical norm. The difference between these two — long minus short — is the squeeze value: positive when the market is contracting (short ATR below long-term baseline), negative when expanding. trueRange = ta.tr(true) atrShort = ta.ema(trueRange, len) atrLong = ta.ema(atrShort, len * 2) sqzRaw = atrLong - atrShort hlRange = ta.highest(high, len) - ta.lowest(low, len) sqzVal = hlRange > 0 ? sqzRaw / hlRange : 0 Normalizing by the HL range makes the oscillator dimensionless — a squeeze value of 0.3 carries the same meaning whether you are analyzing a $1 stock or a $50,000 Bitcoin contract. The signal line is an EMA of the squeeze value, used to detect the inflection point where the squeeze begins to build (sqzVal crossing above sqzSig) or release (sqzVal crossing below sqzSig). 2. Hyper-Squeeze Detection A hyper-squeeze occurs when the squeeze value is not merely positive (compressing) but is actively rising for N consecutive bars — indicating an accelerating contraction rather than a stable one. Accelerating compression is particularly significant because it suggests market participants are increasingly reducing their activity, creating a coiled spring effect where the eventual release may be more forceful. hyperSqz = sqzVal > 0 and ta.rising(sqzVal, hyperLen) When a hyper-squeeze is active, a violet tint is overlaid on the oscillator background in addition to the regular delta-driven background color. The dashboard updates the hyper squeeze row to ACTIVE status. This dual visual layer makes extended compression phases immediately distinguishable from ordinary positive squeeze readings. 3. Cumulative Delta Proxy Order flow analysis — understanding whether buyers or sellers are dominant within a given period — typically requires tick-level data or exchange-provided volume breakdown. This indicator constructs a proxy for cumulative delta using bar-level range analysis, making the information accessible without any data feed requirements. barRange = high - low bullPress = barRange > 0 ? (close - low) / barRange : 0.5 bearPress = barRange > 0 ? (high - close) / barRange : 0.5 deltaBar = bullPress - bearPress deltaSma = ta.sma(deltaBar, deltaLen) deltaPos = deltaSma > 0 A close near the high of the bar implies buyers dominated (bull pressure near 1.0). A close near the low implies sellers dominated (bear pressure near 1.0). The difference, smoothed over a configurable window, produces a normalized delta reading. When delta is positive during a squeeze, the compressed volatility is accumulating with a bullish lean. When negative, with a bearish lean. This directional information is used both in the histogram coloring (alpha derived from delta conviction) and in dashboard output. 4. Volume RSI Confluence Volume RSI applies the standard RSI momentum formula to the volume series rather than price. This produces a normalized reading of whether current volume is elevated or depressed relative to its recent distribution. A high volume RSI (default threshold: 65) during a squeeze release indicates that the expansion is occurring on above-average participation — a meaningful distinction from low-volume releases that can quickly reverse. volRsi = ta.rsi(volume, 14) highVol = volRsi > volThresh The volume RSI value and status are displayed in the dashboard. Alert conditions include a "high-volume release" alert specifically when both a squeeze release signal and elevated volume RSI occur simultaneously, providing a higher-conviction composite signal. 5. Statistical Deviation Bands Rather than using fixed threshold lines at arbitrary values, the oscillator's own distribution is analyzed statistically using a 200-bar lookback. The mean and one and two standard deviation levels of the squeeze value over this window establish dynamically updating bands. These bands are filled with a gradient and rendered at adaptive transparency based on the current Z-score — as the oscillator approaches the 2σ band, the fill becomes more opaque, visually emphasizing extreme readings. sqzMean = ta.sma(sqzVal, statLen) sqzStd = ta.stdev(sqzVal, statLen) band1Up = sqzMean + sqzStd band2Up = sqzMean + 2 * sqzStd band1Dn = sqzMean - sqzStd band2Dn = sqzMean - 2 * sqzStd zScore = sqzStd > 0 ? (sqzVal - sqzMean) / sqzStd : 0 A squeeze reading above the 2σ upper band is historically anomalous compression — significantly above what has been typical over the prior 200 bars. Such readings often precede the most explosive release moves. 6. Histogram Coloring and Background Rendering The histogram bar colors encode two simultaneous dimensions. The base color is red when the squeeze is building (sqzVal above sqzSig) and teal when releasing (sqzVal below sqzSig). The alpha channel of each bar is modulated by the absolute value of the delta conviction — high delta conviction produces more saturated colors, while low-conviction delta (price closing near the bar midpoint) produces more transparent bars. The background color is a 93% alpha gradient driven entirely by delta: teal for bullish delta, red for bearish delta, with the hyper-squeeze violet tint layered on top when active. Features ATR Compression Ratio Engine: Measures the difference between short-term and long-term EMA-smoothed ATR, normalized by HL range for cross-instrument comparability. Signal Line: EMA of the squeeze value provides the crossover reference for detecting compression buildup and release initiation. Hyper-Squeeze Detection: Identifies accelerating compression phases where the squeeze is rising for N consecutive bars simultaneously. Cumulative Delta Proxy: Bar-range-based buying and selling pressure estimate, smoothed and normalized, requiring no Level 2 data. Volume RSI Confluence: RSI applied to volume series identifies above-average participation, separating high-conviction releases from low-volume ones. Statistical Deviation Bands: 200-bar mean and sigma levels with gradient fill and adaptive transparency based on Z-score position. Delta-Driven Alpha Histogram: Histogram color and opacity encode both squeeze direction and delta conviction simultaneously. Layered Background Coloring: Delta-based background with hyper-squeeze overlay provides immediate pane-level context without requiring close inspection. Signal Markers: Circle markers at oscillator bottom on squeeze cross and release cross events. Seven-Row Dashboard: Real-time status covering state, hyper squeeze, volume RSI, delta bias, Z-score, and squeeze value. Four Alert Conditions: Squeeze building, release detected, hyper squeeze active, and high-volume release composite signal. Input Parameters ATR Settings: Base Length: Period for short-term ATR EMA and HL range lookback (default: 20) Hyper-Squeeze Settings: Hyper Squeeze Consecutive Bars: Number of consecutive rising bars required for hyper-squeeze (default: 3) Delta Settings: Delta Smoothing Window: SMA period for the delta bar average (default: 10) Volume RSI Settings: Volume RSI Period: RSI lookback applied to volume series (default: 14) Volume RSI Threshold: Level above which volume is considered elevated (default: 65) Statistical Bands Settings: Statistical Lookback: Bar count for mean and standard deviation computation (default: 200) Show Bands: Toggle deviation band fills (default: true) Display Settings: Show Background: Toggle delta and hyper-squeeze background coloring (default: true) Show Signal Markers: Toggle circle markers at squeeze and release crosses (default: true) Show Dashboard: Toggle the seven-row information table (default: true) How to Use This Indicator Step 1: Monitor the Squeeze State The primary read from this oscillator is the current state displayed in the dashboard: SQUEEZING, RELAXING, or EXPANDING. Squeezing means the compression ratio is positive and rising — the market is actively coiling. Relaxing means the compression is positive but flattening or declining — the coil is beginning to unwind. Expanding means the oscillator has gone negative — volatility is actively expanding beyond the historical baseline. The transition from SQUEEZING to RELAXING is the early warning signal; the transition to EXPANDING is confirmation that the release has begun. Step 2: Watch for Hyper-Squeeze Conditions When the dashboard shows HYPER SQUEEZE: ACTIVE and the chart shows the violet tint overlay, the compression is accelerating — each bar the market is coiling tighter. These conditions historically precede more forceful releases. In hyper-squeeze conditions, position sizing on the anticipated breakout can be considered carefully, as the magnitude of the release may be larger than during ordinary squeeze exits. Step 3: Check Delta Bias for Directional Lean Before committing to a directional bias, check the delta row in the dashboard. Positive delta (bullish) during a squeeze indicates that even during compression, buyers have been closing bars near the upper portion of their range — a bullish accumulation signature. Negative delta (bearish) suggests the opposite. Delta bias does not guarantee direction, but it provides a useful lean when combined with the squeeze release signal. Step 4: Require Volume RSI Confluence on Release Not all squeeze releases produce sustained moves. Low-volume releases frequently reverse within a few bars. The "High-Volume Release" alert fires only when both a release cross and elevated volume RSI (above threshold) occur simultaneously. Waiting for this composite signal before acting on a release — rather than responding to the release cross alone — filters out a meaningful number of false expansion signals in low-participation environments. Indicator Limitations The ATR compression ratio measures relative volatility contraction but cannot determine the direction of the eventual breakout. This indicator identifies when a release is likely, not which way price will move. Directional analysis must come from structure, trend, or other contextual tools. The delta proxy is a bar-level approximation of order flow. It does not access actual tick data, order book data, or trade-level information. In markets with high-frequency activity, the close-to-high/low ratio can systematically misrepresent actual buying and selling pressure. The statistical deviation bands require 200 bars to be fully seeded. On instruments or timeframes with limited history, or immediately after loading a new chart, the bands may produce unreliable readings until sufficient data is available. Volume RSI confluence is not applicable to instruments where volume data is unreliable, unavailable, or represents synthetic aggregation (some forex pairs, certain CFDs). In these cases, the volume RSI row should be treated as informational only. The hyper-squeeze condition measures consecutive rising bars in the squeeze value. This makes it sensitive to the base period setting — shorter periods produce more variable squeeze values, leading to more frequent interruptions of the consecutive count. This indicator operates entirely on the chart's native timeframe. It does not incorporate multi-timeframe squeeze data — a squeeze on a 15-minute chart may be occurring within the context of a much larger timeframe expansion that this indicator would not reflect. Originality Statement The Volatility Squeeze Oscillator is a purpose-built analytical instrument that combines techniques not previously assembled in this specific architecture. The ATR compression ratio engine — using EMA-smoothed ATR at the base period versus double the base period, normalized by the HL range — is an original squeeze quantification method. It differs from the widely used Lazybear TTM Squeeze (which measures Bollinger Band width versus Keltner Channel width) by operating entirely within the ATR framework with range normalization. The hyper-squeeze detection via ta.rising() on the already-positive squeeze value identifies accelerating compression as a distinct state separate from ordinary compression, a categorization not found in standard squeeze implementations. The cumulative delta proxy using bar-range ratios (close minus low divided by range for bull pressure; high minus close divided by range for bear pressure), smoothed and normalized, provides order-flow-inspired information without any data dependency beyond OHLC — an original application of range analysis. The integration of volume RSI as a confluence gate within the squeeze oscillator framework — not as a separate indicator but as an internal filter with dedicated dashboard output and composite alert conditions — is an original design choice. The statistical deviation band system applied to the squeeze oscillator's own values (using a 200-bar SMA and StDev of the squeeze value itself) to create adaptive significance thresholds is an original meta-statistical layer not found in comparable oscillators. Disclaimer The Volatility Squeeze Oscillator is provided for educational and informational purposes only. It is a technical analysis tool and does not constitute financial advice. Identifying squeeze conditions does not predict the direction or magnitude of subsequent price moves with any certainty. All trading involves risk of loss. Users are solely responsible for their own trading decisions. Please consider your individual risk tolerance and consult a licensed financial professional before engaging in any trading activity. -Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
Liquidity Zone Harvester [JOAT]Liquidity Zone Harvester Introduction Institutional order flow leaves footprints in market structure. When a large buyer or seller places a significant order, the execution of that order creates an imbalance between supply and demand at a specific price level — and markets frequently return to these levels to test whether the original interest remains. These price areas are commonly referred to as order blocks or liquidity zones, and they form one of the core concepts in institutional and Smart Money trading methodology. The Liquidity Zone Harvester is an automated order block detection and management system that identifies these zones using statistically validated momentum signals rather than arbitrary manual placement. Instead of drawing boxes wherever a trader's eye thinks supply or demand may exist, this indicator uses Z-score cumulative impulse detection to identify when directional momentum has reached statistically significant levels — and only then marks the most recent opposing-close candle as the source order block. Volume quality gates ensure that only high-participation impulses create zones, filtering out low-conviction moves that are less likely to represent genuine institutional activity. What sets this indicator apart from standard order block tools is what happens after zone creation. Every active zone is tracked through a dual-mechanism aging system. The Bayesian exponential decay model progressively reduces zone visual intensity over time with a configurable half-life, providing a continuous probability signal about zone freshness. Simultaneously, a Kaplan-Meier survival analysis engine — borrowed from medical statistics — estimates the probability that a given zone will survive future price tests, based on the historical survival rates of all previously observed zones in the training window. Each zone displays both its current age and its estimated survival probability directly on the chart, turning static boxes into dynamically updated probability estimates. Core Concepts 1. Z-Score Cumulative Impulse Detection Zone creation is triggered only when directional momentum reaches a statistically defined threshold. The system accumulates a running streak of directional closes — when consecutive bars close higher than their open, the bull accumulator grows; when consecutive bars close lower, the bear accumulator grows. The streak resets when direction reverses. This cumulative streak is then normalized against its own rolling mean and standard deviation, producing a Z-score that measures how unusual the current momentum streak is relative to recent history. cumBull := close > open ? nz(cumBull ) + (close - open) : 0 cumBear := close < open ? nz(cumBear ) + (open - close) : 0 zBull = (cumBull - ta.sma(cumBull, zLen)) / ta.stdev(cumBull, zLen) zBear = (cumBear - ta.sma(cumBear, zLen)) / ta.stdev(cumBear, zLen) bullEvent = ta.crossover(zBull, zThresh) and barstate.isconfirmed and volOK bearEvent = ta.crossover(zBear, zThresh) and barstate.isconfirmed and volOK When a bullEvent fires (bull Z-score crosses the threshold with volume confirmation), the system looks backward to find the most recent down-close candle — the last bar where sellers were dominant before the impulse began. This becomes the demand zone. Similarly, a bearEvent marks the most recent up-close candle as the supply zone. 2. Volume Quality Gate Not all Z-score impulses are created equal. An impulse that occurs on abnormally low volume represents weak conviction — possibly a thin-market price drift rather than genuine institutional momentum. The volume gate applies RSI to the volume series to normalize it against its own history. Only when volume RSI exceeds the configurable threshold is the volOK condition true, enabling zone creation. volRsi = ta.rsi(volume, 14) volOK = volRsi > volThresh This filter meaningfully reduces the number of zones created during low-participation conditions such as pre-market sessions, lunch hours, or holiday-period trading — precisely the times when order block levels are least likely to represent significant institutional interest. 3. Order Block Zone Construction When a signal event is confirmed, the most recent opposing candle is identified using ta.valuewhen(). For a bullEvent, the system finds the most recent bar where close was less than open (a down candle) — its high and low define the demand zone boundaries. For a bearEvent, it finds the most recent up candle — its high and low define the supply zone boundaries. A box object is created spanning from that historical bar to the current bar, with height defined by the candle's actual high-low range. lastDnHigh = ta.valuewhen(close < open, high, 0) lastDnLow = ta.valuewhen(close < open, low, 0) lastDnBar = ta.valuewhen(close < open, bar_index, 0) if bullEvent newBox = box.new(lastDnBar, lastDnHigh, bar_index, lastDnLow, ...) bullBoxes.push(newBox) 4. Overlap Prevention (f_no_overlap) To avoid cluttering the chart with redundant zones that occupy the same price territory, an overlap check function evaluates whether a proposed new zone overlaps with any existing zone of the same type. The function iterates over all existing bull or bear boxes and compares the new zone's top and bottom against each existing box's top and bottom. A guard condition (nBull > 0) prevents the iteration from running on an empty array, which would cause an index -1 crash. f_no_overlap(newTop, newBot, boxes) => noOverlap = true if boxes.size() > 0 for i = 0 to boxes.size() - 1 b = boxes.get(i) if newTop >= box.get_bottom(b) and newBot <= box.get_top(b) noOverlap := false noOverlap 5. Bayesian Exponential Decay Each zone's visual transparency is driven by an exponential decay function that represents the diminishing probability of zone relevance over time. The half-life parameter (default: 75 bars) defines how quickly a zone fades. At age 0, the zone is fully opaque. At age 75 bars, the zone is at 50% opacity. At age 150 bars, 25% opacity. This continuous decay — rather than a binary active/expired switch — provides an analog probability signal directly encoded in the zone's visual intensity. decayFactor = math.exp(-0.693 * age / halfLife) zoneAlpha = math.round(decayFactor * 200) box.set_bgcolor(b, color.new(zoneColor, 255 - zoneAlpha)) 6. Kaplan-Meier Survival Analysis The Kaplan-Meier estimator is a nonparametric statistical method originally developed to measure survival probabilities in clinical trial data. In this indicator, "survival" is defined as a liquidity zone remaining unmitigated (not breached by a closing price on two separate occasions). Each time a zone is mitigated, it is recorded as a "death event" at its current age. Zones that expire by age limit without mitigation are recorded as "censored events" — incomplete observations. The KM formula multiplies survival probabilities across all observed events up to a given age. // For each completed event (death at age t_i with n_i at-risk zones): S_t := S_t * (1.0 - d_i / n_i) // Product over all event times <= query age For each active zone, the indicator queries the KM estimate at the zone's current age and displays the result as a percentage label. A zone at age 40 showing "Age 40 | 72%" means that historically, 72% of zones survived to at least 40 bars without being mitigated — giving traders a quantitative assessment of how likely the zone is to hold on the next test. Features Z-Score Cumulative Impulse: Statistical momentum threshold using normalized cumulative directional streaks to gate zone creation. Volume Quality Gate: Volume RSI filter ensures only high-participation impulses create zones. Precise Order Block Identification: Most recent opposing candle (last down-close for bull event, last up-close for bear event) defines zone boundaries. Overlap Prevention: f_no_overlap function checks all existing zones before creating a new one, preventing chart clutter from redundant levels. Bayesian Exponential Decay: Zone opacity decays over time with configurable half-life, encoding freshness as a visual probability signal. Kaplan-Meier Survival Analysis: Medical-statistics survival estimator applied to zone longevity, displayed as a percentage probability label on each active zone. Dynamic Zone Extension: Box right edge extends to the current bar on every update, keeping zones visually connected to the present. Mitigation Tracking: Zones that are closed through twice are flagged as mitigated and removed, with the event recorded for KM analysis. Seven-Row Dashboard: Active demand count, active supply count, bull Z, bear Z, volume RSI, KM training size, and signal status. Two Alert Conditions: Zone created alert and zone rejection (price tests and bounces back) alert. Input Parameters Z-Score Settings: Z Lookback: Rolling window for Z-score normalization (default: 50) Z Threshold: Sigma level required to trigger an impulse event (default: 2.0) Volume Gate Settings: Volume RSI Period: RSI lookback for volume normalization (default: 14) Volume RSI Threshold: Minimum volume RSI for zone creation eligibility (default: 55) Zone Management Settings: Max Zone Age: Maximum bars a zone remains active before forced removal (default: 300) Mitigation Count: Number of closes through a zone required for mitigation (default: 2) Max Active Zones Per Side: Maximum simultaneous demand or supply zones displayed (default: 5) Decay Settings: Decay Half-Life: Number of bars at which zone opacity reaches 50% of initial value (default: 75) KM Settings: KM Training Window: Bar lookback for Kaplan-Meier training data collection (default: 500) Show Survival Labels: Toggle KM probability labels on active zones (default: true) Display Settings: Show Demand Zones: Toggle demand (bull) zone boxes (default: true) Show Supply Zones: Toggle supply (bear) zone boxes (default: true) Show Dashboard: Toggle the seven-row information table (default: true) How to Use This Indicator Step 1: Understand Zone Creation Conditions Zones are not created on every bar — they are created only when a statistically significant directional impulse (Z-score above threshold) occurs on above-average volume. This selectivity is intentional. In any given trading session, you will likely see only a few zone creation events, each backed by a genuine momentum surge that suggests institutional participation. When you see a new zone appear, note the Z-score values in the dashboard and the volume RSI reading — higher values on both indicate a stronger impulse and more confident zone placement. Step 2: Prioritize Fresh, High-Survival Zones Not all zones on the chart are equally relevant. A fresh zone (low age, full opacity) at a KM survival rate of 80% is a far stronger candidate for price reaction than an old zone (high age, near-transparent) at 30% survival probability. Use both the visual opacity and the KM label together: as a zone ages and fades, reduce your expectation that it will provide meaningful support or resistance. When price approaches a zone that is both visually fresh and shows high KM survival probability, the statistical expectation of reaction is at its highest. Step 3: Watch for Zone Rejection Alerts The zone rejection alert fires when price tests a zone (enters the box boundary) and then closes back away from it without mitigating it. This is the core trade setup: price returning to the institutional order block level, briefly penetrating it, and then reversing. The rejection alert provides a timely notification for potential entries in the direction of the original impulse that created the zone, with the zone's near boundary serving as the natural stop-loss reference. Step 4: Monitor KM Training Size for Statistical Validity The dashboard displays the KM training sample size — the number of completed zone events (both mitigated and aged-out) available for the survival analysis. With fewer than 10 training events, the KM estimate has high variance and should be treated as rough guidance. With 30 or more training events, the estimate becomes statistically stable. On instruments or timeframes where the indicator has run for extended periods, the KM estimates become increasingly reliable as the training dataset grows. Indicator Limitations The Z-score cumulative impulse and volume gate require sufficient chart history for the rolling normalization periods to be seeded. In the first Z-lookback bars of a new chart, zone creation signals may be less reliable as the mean and standard deviation are not yet fully established. Kaplan-Meier survival estimates are only as reliable as the training dataset. On instruments or timeframes that have not accumulated many completed zone events, the survival probabilities should be treated as rough estimates rather than statistically precise values. The mitigation definition (two closes through the zone) is a configurable approximation. In real order block theory, mitigation can be defined in several ways; this indicator's specific definition may not match every trader's conceptual framework. Zones are based on the most recent opposing candle at the time of the impulse event. In fast markets where multiple large candles cluster closely together, the marked candle may not represent the most significant institutional order location. This indicator requires volume data. On instruments where volume is unavailable or unreliable (some synthetic indices, certain forex pairs), the volume gate will not function as intended and should be disabled or its threshold lowered significantly. The exponential decay model assumes a constant half-life across all market conditions. In reality, zone relevance can be regime-dependent — a zone formed during a trending market may remain relevant longer than one formed during a range, or vice versa. Maximum active zones per side is a hard limit. If the limit is reached, new valid zone creation events will be rejected until an existing zone is mitigated or aged out. Originality Statement The Liquidity Zone Harvester is a genuinely original indicator that applies statistical and mathematical frameworks from outside the trading domain to a problem common in technical analysis. The Z-score cumulative impulse detection — using consecutive close-open accumulation normalized against rolling sma/stdev — as the primary trigger for order block marking is an original signal architecture. Most order block indicators use visual pattern matching (e.g., a large candle followed by a gap) rather than statistical significance thresholds. Applying the Kaplan-Meier survival estimator — a nonparametric method from biostatistics — to estimate the probability that a liquidity zone will survive future price tests is a novel application of medical statistics to market analysis. This provides a mathematically grounded probability estimate that no standard order block indicator offers. The Bayesian exponential decay applied to zone visual transparency — using a configurable half-life to continuously encode zone freshness as opacity — is an original visual design that treats zone relevance as a continuously diminishing probability rather than a binary active/inactive state. The overlap prevention function that iterates over all existing zone arrays before creating a new zone — with the index-crash guard for empty arrays — is a specific engineering solution to a concrete problem in box-based indicator design. The volume RSI quality gate, applied specifically to filter Z-score impulse events rather than as a standalone signal, is an original confluence filter design that specifically addresses the problem of thin-market false signals in order block detection. Disclaimer The Liquidity Zone Harvester is provided for educational and informational purposes only. It is a technical analysis tool and does not constitute financial advice. Liquidity zones and order blocks are analytical constructs; they do not guarantee price reactions. Past zone behavior as encoded in Kaplan-Meier estimates does not predict future zone performance. All trading involves risk of loss. Users are solely responsible for their own trading decisions. Please consider your individual risk tolerance and consult a licensed financial professional before engaging in any trading activity. -Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
Adaptive Pressure Trail [JOAT]Adaptive Pressure Trail Introduction Adaptive Pressure Trail is an open-source overlay indicator that combines an HMA-based adaptive ratchet trail with a custom volume-weighted Money Flow Index to classify bars into bull pressure, bear pressure, and neutral states. The system uses a three-layer visual architecture — an outer volatility cloud, an inner ratchet band fill, and a core gradient pressure fill between the HMA baseline and candle mid-body — to create a clear, spatially organized picture of momentum and direction on any chart. Volatility squeeze detection identifies compression phases before potential breakouts, and high-confidence signals fire when a squeeze releases simultaneously with pressure alignment. The core problem this indicator solves is that most trail-based systems are either too reactive (flipping constantly on noise) or too slow (missing meaningful moves). The HMA ratchet addresses this: the upper band only falls and the lower band only rises after a direction flip, preventing whipsaw while remaining responsive when momentum is genuine. Layering a volume-weighted MFI filter on top means a directional trail alone is not sufficient — volume-backed money flow must confirm the move before the indicator reports active pressure. Core Concepts 1. HMA Adaptive Ratchet Trail The trail baseline is computed using a Hull Moving Average, which provides low lag while remaining smooth. ATR-scaled upper and lower bands are applied around the HMA. The ratchet rule prevents band noise: the upper band can only move downward (or reset when price closes above it), and the lower band can only move upward (or reset when price closes below it). Direction flips when price closes through the active band. This creates a one-directional drift that is far more stable than a raw crossover trail: The trail direction variable persists with var and updates each bar. Direction == 1 means the lower band is the active trail (bullish), direction == -1 means the upper band is the active trail (bearish). 2. Custom Volume-Weighted MFI Rather than using a standard price-only momentum oscillator, the pressure engine uses a custom volume-weighted Money Flow Index. Positive flow is volume multiplied by HLC3 on bars where HLC3 increased; negative flow is volume multiplied by HLC3 on bars where HLC3 decreased. These are summed over the MFI length and converted to a 0-100 scale using the RSI formula. The result is smoothed with an HMA for responsiveness. This produces a momentum measure that is inherently volume-weighted — large-volume moves carry more influence than low-volume drift. The MFI is further smoothed to distinguish sustained pressure from transient spikes. 3. Pressure Regime Classification Bull pressure is active when the trail direction is bullish AND the smoothed MFI is above the bull threshold. Bear pressure is active when the trail direction is bearish AND MFI is below the bear threshold. Neutral is everything else. This dual-condition structure means you need both directional commitment from the ratchet trail AND volume-backed momentum to enter a pressure state. Either condition alone is insufficient. A rolling 50-bar history tracks what percentage of recent bars were in an active pressure state, producing a Pressure Strength percentage that indicates whether the current regime has been sustained or is a brief spike. 4. Squeeze Detection Band width — the distance between the upper and lower ratchet bands — is compared to its own SMA. When band width drops below 72% of its recent average, the market is compressing. A squeeze start fires a golden diamond marker at the trail level. A squeeze release fires a larger circle marker. The high-confidence signal fires when a squeeze release coincides with an active pressure state, identifying the highest-probability setups where compressed volatility breaks out in a confirmed directional context. 5. Three-Layer Visual Architecture The chart renders three nested visual layers: Outer Cloud: The ATR envelope (cloudMult * ATR from HMA center) filled with a very transparent directional color — gives spatial context to where price is within the volatility range Inner Band Fill: The ratchet upper and lower bands filled with medium transparency — shows the active directional channel Core Pressure Fill: A gradient fill between the HMA baseline and the candle mid-body — transparent at the HMA, saturated at the body, colored by pressure state The trail line itself uses three stacked plots at widths 10, 5, and 2 to create a neon glow shadow effect. Bar coloring uses color.from_gradient driven by MFI intensity, producing increasingly saturated candles as momentum builds. Features HMA Ratchet Trail with Triple-Layer Glow: Direction-persistent adaptive trail rendered as a neon glow (widths 10/5/2) using the bullish lime or bearish fuchsia color Outer ATR Volatility Cloud: Wide ATR envelope filled directionally, providing spatial context at a glance Inner Ratchet Band Fill: Gradient-filled active channel between upper and lower ratchet bands Core Pressure Gradient: Background-to-body gradient between HMA and mid-body, colored by current pressure state HMA Skeleton Reference: Subtle neutral line showing the raw HMA baseline beneath all fills Volatility Squeeze Markers: Golden diamonds during compression, circle flash on breakout High-Confidence Signal: Starred HC LONG / HC SHORT labels when squeeze releases into confirmed pressure alignment — the highest-quality setup the system produces Volume Impulse Labels: When a strong directional candle exceeds the volume threshold, a label shows the volume ratio (e.g., 2.1x vol) at the bar MFI Cross Markers: Small triangles on the trail when MFI crosses the 50 level, marking momentum regime shifts TP Signals: Labeled plotshapes when MFI reaches overbought/oversold extremes in the trail direction Pressure Strength Percentage: Rolling 50-bar % of time spent in active pressure — distinguishes sustained trends from brief spikes Gradient Bar Coloring: color.from_gradient driven by MFI intensity — bars saturate as momentum builds and fade as it weakens 11-Row Dashboard: Pressure state, trail direction, MFI reading, pressure score, pressure strength %, volatility state, band width, trend bars, trail price, ATR Input Parameters Adaptive Trail: Trail HMA Length: Period for the HMA baseline (default 21) Trail ATR Multiplier: Width of inner ratchet bands (default 1.8) Trail ATR Length: ATR lookback for band calculation (default 14) Outer Cloud ATR Width: Outer envelope width multiplier (default 3.2) Squeeze Reference Bars: SMA period for band-width baseline (default 20) Pressure Filter: MFI Length: Volume-weighted money flow lookback (default 14) MFI Smoothing: HMA smoothing on raw MFI (default 7) MFI Bull/Bear Thresholds: Activation levels for pressure states (default 62/38) Signals: TP Overbought/Oversold Levels: MFI levels that trigger TP signals (default 78/22) Impulse Volume Multiplier: Volume multiple above SMA required for impulse label (default 1.3) Visuals: Toggles for entry signals, TP signals, glow, cloud, pressure fill, squeeze markers, and dashboard Bull Color (default lime #a3e635), Bear Color (default fuchsia #e879f9), Neutral Color (default slate #94a3b8) How to Use This Indicator Primary Setup — Trend Following with Pressure Confirmation: Look for the trail to flip direction (circle marker on trail). Wait for MFI to cross the bull or bear threshold, confirming the pressure state activates. Enter in the trail direction once the pressure fill color saturates. Trail your stop at the active trail line. Exit on a TP signal or when the pressure state deactivates. High-Confidence Setup: Wait for squeeze markers (golden diamonds) to appear, indicating compression. When the squeeze releases (larger circle flash) and the pressure state is simultaneously active, the HC LONG or HC SHORT label fires. These are the setups where compressed volatility breaks out with momentum behind it. Filtering with Pressure Strength: The dashboard Pressure Strength percentage tells you how sustained the current move has been. Values above 60% indicate a mature trend. Values below 30% indicate the pressure state is new or unstable. Adjust position sizing accordingly. Reading Impulse Candles: Volume impulse labels (e.g., "2.1x vol") mark bars where a strong directional move was accompanied by significantly elevated volume. These often mark the start or acceleration of a pressure phase and can serve as reference points for support/resistance. APT dashboard showing bull pressure active, MFI at 71.2, P-Score 7.1/10, P-Strength at 64%, band width expanding after a squeeze release, and the trail at current price with ATR reference Indicator Limitations The ratchet trail requires a confirmed close through the active band to flip direction. On higher-timeframe charts with large candle bodies this can mean the flip is confirmed well after the actual turning point The volume-weighted MFI requires volume data. On instruments with unreliable volume reporting (some forex pairs, synthetic indices) the pressure filter may be less meaningful than on equities or futures Squeeze detection uses a 72% band-width threshold. In persistently low-volatility instruments this threshold may trigger too frequently; adjusting the Squeeze Reference Bars parameter can help High-confidence signals require both a squeeze release and active pressure simultaneously. On trending markets with no compression phase, HC signals will be rare MFI thresholds at 62/38 are defaults designed for balanced use; highly trending instruments may require raising the bull threshold and lowering the bear threshold to reduce false pressure activations Originality Statement This indicator is original in its combination of a ratchet-constrained HMA trail with a custom volume-weighted MFI, the three-layer nested visual system, and the squeeze-breakout confluence signal. While HMA trails and MFI oscillators exist independently, this publication is justified because: The ratchet logic applied to HMA (rather than ATR midline or EMA) reduces lag while preventing the constant flipping common in standard trail indicators The custom volume-weighted MFI differs from the standard MFI by using HLC3 as the price component with RSI-formula normalization, producing a smoother measure with better noise rejection The three-layer nested fill architecture (outer cloud, inner band, core pressure gradient) provides a spatially organized visual system where the distance between layers communicates volatility context Squeeze detection integrated with pressure confirmation for HC signals is a novel combination that identifies setups at the intersection of volatility compression and momentum alignment The Pressure Strength rolling percentage provides a trend maturity measure not present in standard trail indicators Disclaimer This indicator is provided for educational and informational purposes only and does not constitute financial advice or a recommendation to buy or sell any financial instrument. Past performance of any pattern or signal does not guarantee future results. All trading involves substantial risk. Always use proper risk management and conduct your own independent analysis. — Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
Vantage Protocol [JOAT]Vantage Protocol Introduction Vantage Protocol is an advanced open-source execution strategy that integrates regime classification, adaptive momentum filtering, volume confirmation, session timing, and ATR-based risk management into a unified NNFX-aligned trading engine. Rather than relying on a single entry signal, the strategy requires alignment across five independent subsystems — regime state, momentum direction, cumulative volume delta, volume presence, and session timing — before entering a trade. This multi-gate architecture is designed to filter out low-probability setups and only execute when multiple independent factors converge. This strategy exists because most retail strategies fail for a predictable reason: they use one or two conditions for entry and ignore the broader market context. A moving average crossover in a choppy market produces losses. A momentum signal during a low-volume session lacks follow-through. An entry outside the active institutional window misses the liquidity needed for clean execution. Vantage Protocol addresses each of these failure modes with a dedicated subsystem, and only enters when all subsystems agree. Important Note on Strategy Results Backtesting results shown with this strategy are historical simulations and do not guarantee future performance. Markets change, and strategies that performed well historically may not perform well in the future. The default settings use realistic parameters: 2% of equity per trade, $100,000 initial capital, no pyramiding, and zero margin. Users should add commission and slippage appropriate for their broker and instrument in the strategy Properties dialog before evaluating results. The strategy is published with these defaults to provide a transparent starting point — users are expected to adjust parameters for their specific trading conditions. Strategy Architecture The strategy follows an NNFX (No Nonsense Forex) inspired architecture where each subsystem acts as an independent gate. A trade is only entered when all gates are open simultaneously. Gate 1: Regime Engine The regime engine determines whether the market is trending or ranging. It combines three independent measures: H-Infinity Filter: An adaptive filter from control theory that tracks price under worst-case noise assumptions. The filter's slope determines directional bias — positive slope = bullish, negative slope = bearish R-Squared Efficiency Gate: Measures how well price fits a linear regression. When R-squared exceeds an auto-calibrating threshold (rolling mean plus k standard deviations), the efficiency gate opens, indicating a trending market. A hysteresis band prevents flickering Chop Score: Measures path efficiency — the ratio of net movement to total path length. High chop scores indicate choppy, non-directional markets where trend-following strategies fail The regime is classified as trending (bullish or bearish) only when R-squared confirms efficiency AND chop score confirms directional movement. If either condition fails, the regime is classified as ranging and no entries are allowed. bool regimeTrend = effOK and not isChoppy int regimeBias = regimeTrend ? (hinfSlope >= 0 ? 1 : -1) : 0 Gate 2: Momentum Core The momentum subsystem uses a Laguerre RSI processed through JMA adaptive smoothing. The Laguerre filter provides a smoother, less laggy momentum reading than standard RSI, and the JMA smoothing further reduces noise while preserving responsiveness to genuine momentum shifts. Momentum must confirm the regime direction: For long entries: JMA-smoothed Laguerre RSI must be above the bull threshold (default: 62) For short entries: JMA-smoothed Laguerre RSI must be below the bear threshold (default: 38) This prevents entries when momentum is neutral or contradicts the regime bias. Gate 3: Volume Filter (CVD) Cumulative Volume Delta tracks net buying versus selling pressure. The strategy requires the CVD slope (smoothed with an EMA) to confirm the trade direction: For long entries: CVD slope must be positive (net buying pressure increasing) For short entries: CVD slope must be negative (net selling pressure increasing) Additionally, the current bar's volume must exceed a minimum ratio relative to the 50-bar average (default: 0.7x). This filters out entries during thin-liquidity periods where price moves lack conviction and slippage risk is elevated. Gate 4: Session Filter An optional session window filter restricts entries to a configurable time window (default: 0200-1200 New York time). This aligns trading with the London and New York sessions where institutional liquidity is deepest. Entries outside this window are blocked because low-liquidity sessions produce unreliable price action and wider spreads. Gate 5: Cooldown After any exit (whether by stop loss, take profit, or regime exit), a configurable cooldown period (default: 5 bars) must pass before a new entry is allowed. This prevents revenge trading and allows the market to establish a new setup after a position closes. Entry and Exit Logic Entry Conditions: All five gates must be open simultaneously, and the strategy must be flat (no existing position): bool longSetup = regimeBias == 1 and momBull and cvdBull and volOK and sessOK and cooldownOK bool shortSetup = regimeBias == -1 and momBear and cvdBear and volOK and sessOK and cooldownOK Stop Loss and Take Profit: SL and TP levels are calculated using ZEMA-smoothed ATR multiplied by configurable factors: Stop Loss: Entry price minus (ZEMA-ATR x SL Multiplier) for longs, plus for shorts (default SL multiplier: 1.8) Take Profit: Entry price plus (ZEMA-ATR x TP Multiplier) for longs, minus for shorts (default TP multiplier: 2.8) The default risk-reward ratio is approximately 1:1.56 (1.8 SL to 2.8 TP). ZEMA smoothing on the ATR removes noise from the volatility measure, producing more stable SL/TP levels than raw ATR. Regime Exit: If the regime flips to ranging or the opposite direction while a position is open, the strategy closes the position immediately with a "Regime Exit" comment. Additionally, if momentum deteriorates significantly (Laguerre RSI crossing back toward neutral), the position is closed. This prevents holding positions through regime changes where the original thesis is no longer valid. Band Structure Visualization The strategy plots a JMA baseline with regime-colored glow, and SL/TP bands around it: SL bands (inner) shown in muted scarlet with fill zones TP bands (outer) shown in muted jade with cross-style plotting The baseline color shifts based on regime: green for bullish trend, red for bearish trend, purple for ranging Bar coloring reflects the current position state: green when long, red when short, purple when ranging (no position allowed), and grey when flat in a trending regime. Default Strategy Properties These are the default values used in the strategy's Properties dialog: Initial Capital: $100,000 Order Size: 2% of equity per trade Pyramiding: 0 (no adding to positions) Margin: Long 0%, Short 0% (cash account simulation) Commission: Not set by default — users should configure this for their broker (typical values: 0.01-0.1% for crypto, $1-5 per contract for futures, 1-3 pips for forex) Slippage: Not set by default — users should configure this for their instrument (typical values: 1-3 ticks for liquid instruments, more for illiquid ones) Users are strongly encouraged to set realistic commission and slippage values before evaluating backtesting results. Results without commission and slippage will overstate performance. Input Parameters Regime Engine: R-Squared Length (default: 30), R-Squared Threshold k (default: 0.8), Chop Length (default: 20), Chop Threshold (default: 0.55) H-Infinity Order (default: 3), Noise (default: 0.5), Disturbance (default: 1.0) Momentum Core: Laguerre Alpha (default: 0.07), JMA Smooth Period (default: 8), Bull Threshold (default: 62), Bear Threshold (default: 38) Volume Filter: CVD Smoothing (default: 14), Min Volume Ratio (default: 0.7) Band Structure: JMA Period (default: 21), ATR Length (default: 14), SL Multiplier (default: 1.8), TP Multiplier (default: 2.8) Session Filter: Session Filter toggle (default: on), Active Window (default: 0200-1200), Timezone (default: America/New_York) Risk Management: Risk % (default: 1.5), Re-entry Cooldown (default: 5 bars) How to Use This Strategy Step 1: Configure for Your Instrument Open the strategy Properties dialog and set commission and slippage values appropriate for your broker and instrument. Adjust the session window if you trade instruments with different liquidity patterns than the default London/NY window. Step 2: Evaluate on Sufficient Data Run the strategy on a dataset that produces at least 100 trades for statistical significance. Short datasets with few trades produce unreliable performance metrics. Use the strategy tester's detailed trade list to review individual trades. Step 3: Monitor the Dashboard The 9-row dashboard shows the state of every subsystem in real-time: regime classification, momentum reading, CVD direction, volume ratio, session status, current position, ATR value, and cooldown status. This transparency lets you understand exactly why the strategy is or is not entering trades. Step 4: Understand the Regime Exit The strategy will close positions when the regime changes, even if the SL/TP has not been hit. This is by design — holding a trend-following position through a regime change to ranging is a common source of losses. Regime exits may result in small wins or small losses, but they prevent the larger losses that come from ignoring changing conditions. Step 5: Adjust Parameters Thoughtfully If the strategy produces too few trades, consider lowering the momentum thresholds (bull from 62 to 58, bear from 38 to 42) or reducing the minimum volume ratio. If it produces too many losing trades, consider increasing the R-squared threshold k or the chop threshold. Each parameter change affects the trade-off between signal frequency and signal quality. Strategy Limitations and Compromises Trade Frequency: The five-gate architecture is deliberately selective. On many instruments and timeframes, the strategy may only produce a handful of trades per month. This is by design — fewer, higher-quality trades — but it means the strategy is not suitable for traders who need frequent activity Regime Detection Lag: The regime engine uses lookback-based measures (R-squared, chop score) and persistence requirements. Regime changes are identified with a delay, which means the strategy may miss the first portion of a new trend or hold slightly into a regime change CVD Approximation: The volume delta calculation (close > open = buying) is an approximation. True order flow requires Level 2 data not available in Pine Script. On instruments with unreliable volume data (forex with tick volume), the CVD gate may be less effective Fixed SL/TP: Stop loss and take profit are set at entry and do not trail. In strong trends, the strategy may exit at the TP while the trend continues. A trailing stop modification could capture more of extended moves but would also increase the risk of giving back profits during pullbacks Session Dependency: The default session filter is optimized for forex and futures with distinct London/NY sessions. Crypto and other 24/7 markets may benefit from disabling the session filter or adjusting the window No Pyramiding: The strategy does not add to winning positions. This limits profit potential in strong trends but also limits risk exposure Backtesting vs Live: Backtesting assumes fills at the close of the signal bar. In live trading, slippage, requotes, and execution delays may produce different results. Always paper trade before committing real capital Originality Statement This strategy is original in its multi-gate architecture that synthesizes five independent subsystems into a unified execution engine. While individual components (regime detection, Laguerre RSI, CVD, session filtering, ATR-based risk management) are established concepts, this strategy is justified because: The five-gate entry architecture (regime + momentum + CVD + volume + session) provides a systematic approach to filtering low-probability setups that is not available in single-indicator strategies The H-Infinity filter for regime detection applies control theory to market classification, providing a theoretically grounded alternative to simple moving average crossover regime detection The triple-measure regime engine (R-squared + chop + H-Infinity slope) provides more robust regime classification than any single measure The regime exit mechanism actively manages positions based on changing market conditions rather than relying solely on fixed SL/TP levels The NNFX-inspired architecture with clearly separated subsystems (baseline, confirmation, volume, exit, session) provides a modular framework that traders can understand, evaluate, and modify The cooldown mechanism prevents revenge trading after exits, addressing a common behavioral trading error All subsystem states are displayed transparently in the dashboard, allowing traders to understand exactly why trades are or are not being taken Disclaimer This strategy 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. Backtesting results are historical simulations based on past data. Past performance does not guarantee future results. The strategy's historical performance was generated under specific market conditions that may not repeat. Markets are dynamic, and strategies that worked historically may fail in the future. The default strategy properties do not include commission or slippage. Users must configure these values for their specific broker and instrument to obtain realistic performance estimates. Results without commission and slippage will overstate actual trading performance. Always use proper risk management, including position sizing appropriate for your account and risk tolerance. Never risk more than you can afford to lose. Consider paper trading this strategy extensively before using real capital. The author is not responsible for any losses incurred from using this strategy. -Made with passion by officialjackofalltrades
Estrategia Pine Script®
por officialjackofalltrades
Liquidity Tessera [JOAT]Liquidity Tessera Introduction Liquidity Tessera is an advanced open-source volume intelligence pane that fuses Cumulative Volume Delta (CVD), Weis Wave volume clustering, multi-design intensity bars, volume absorption and climax detection, CVD momentum ribbon, liquidity exhaustion tracking, session-partitioned delta accumulation, and a comprehensive 16-row dashboard into a unified volume analysis system. This indicator transforms raw volume data into actionable intelligence about who controls the market — buyers or sellers — and whether that control is strengthening or weakening. Standard volume indicators show you how much trading occurred. Liquidity Tessera shows you the character of that trading: whether volume is flowing in or out (CVD), whether volume waves are expanding or contracting (Weis Wave), whether institutions are absorbing supply or distributing into demand (absorption detection), and whether a move is reaching climactic exhaustion (climax and exhaustion signals). The indicator operates in its own pane below the price chart, providing a complete volume intelligence layer without cluttering price action. Core Concepts 1. Cumulative Volume Delta (CVD) CVD approximates the net buying and selling pressure by assigning each bar's volume as positive (buying) when the close is above the open, and negative (selling) when the close is below the open: float barDelta = close > open ? volume : close < open ? -volume : 0.0 var float cvdRaw = 0.0 cvdRaw := nz(cvdRaw ) + barDelta The cumulative sum of these deltas creates a running total of net order flow. Rising CVD indicates net buying pressure is accumulating; falling CVD indicates net selling pressure. The indicator offers optional normalization using a z-score approach (CVD relative to its rolling mean and standard deviation), which makes CVD comparable across different instruments and timeframes. CVD divergences from price are particularly significant: when price makes a new high but CVD does not confirm (it stays below its recent high), it suggests the rally lacks genuine buying conviction and may be vulnerable to reversal. 2. Weis Wave Volume Clustering The Weis Wave method groups volume into directional waves. Rather than looking at volume bar-by-bar, it accumulates volume during each directional swing. A wave reversal is triggered when price moves against the current wave direction by more than a configurable ATR-based threshold: float waveThreshold = ta.atr(waveAtrLen) * waveAtrMul // When price reverses by more than the threshold, the wave completes // and accumulated volume is plotted as a single wave column This reveals the Wyckoff-style volume pattern: are up-waves attracting more volume than down-waves (accumulation), or are down-waves attracting more volume (distribution)? The indicator tracks wave history and detects divergences between price swings and their corresponding wave volumes. 3. Volume Absorption Detection Institutional absorption occurs when large players absorb selling pressure (or buying pressure) without allowing price to move significantly. The indicator detects this by identifying bars where volume is extremely high relative to average (above the configurable threshold, default 2x) but the price range is unusually small (below 50% of average range): High volume + small range = someone is absorbing the opposite side's orders This often occurs at the end of trends when institutions are building positions against the prevailing direction Absorption bars are highlighted with a distinct amethyst color and labeled "ABS" on the chart. 4. Volume Climax Detection A volume climax occurs when extreme volume (above the configurable threshold, default 3x average) coincides with a reversal candle pattern — specifically, a bar with a large wick-to-body ratio (wick > 2x body). This combination suggests that a massive influx of orders met strong opposition, creating a potential turning point. Climax bars are highlighted in fuchsia and labeled "CLIMAX." 5. Liquidity Exhaustion Tracking The indicator tracks consecutive Weis Waves where volume declines from wave to wave. When two or more consecutive waves in the same direction show declining volume, it signals exhaustion — the trend is running out of fuel. This is a classic Wyckoff concept: a trend sustained by decreasing volume is unsustainable. 6. Delta Intensity Bar Coloring Rather than simple up/down coloring, the indicator offers gradient-based bar coloring where the intensity of the color reflects the strength of the bar's delta relative to average volume: float deltaStr = math.min(math.abs(barDelta) / volMA, 2.0) / 2.0 // Weak delta = faint color, strong delta = vivid color baseCol := color.from_gradient(deltaStr, 0, 1, color.new(TESS_INFLOW, 65), color.new(TESS_INFLOW, 0)) This means a green bar with faint color had weak buying conviction, while a vivid green bar had strong buying conviction — information not available from standard volume bars. 7. CVD Momentum Ribbon A fast and slow EMA of the raw CVD create a momentum ribbon. When the fast CVD EMA is above the slow, delta momentum is bullish (buying pressure is accelerating). Crossovers between the two indicate shifts in delta momentum direction. Features Four Bar Design Modes: Solid (standard filled bars), Hollow (outline only), Intensity (transparency scales with volume relative to average), and Glass (semi-transparent with a stepline cap) — each providing a different visual emphasis Weis Wave Histogram: Background columns showing completed wave volumes, colored by wave direction. Up-wave volumes plot above zero, down-wave volumes below CVD Overlay: The cumulative delta line scaled to fit the volume pane, with gradient coloring from bearish (red) to bullish (teal) based on CVD value Session Volume Accumulation: Separate tracking of pre-market, regular, and post-market session volumes and deltas, with session background coloring Delta Pressure Score: A 0-100 percentage measuring net buying pressure over the last 20 bars. Above 60 = buy pressure dominant, below 40 = sell pressure dominant Wave Volume Comparison: Real-time comparison of the current wave's volume against the previous wave, classified as Expanding, Steady, or Contracting Liquidity State Classification: Categorizes the current bar as Absorption, Climax, Exhaustion, Spike, Dry-Up, or Normal based on the composite of all detection systems Volume Spike Detection: Identifies bars where volume exceeds 2.5x average with a background highlight Session Delta Bias: Tracks whether the current session's cumulative delta is net accumulating or distributing 16-Row Dashboard: Displays bar delta, CVD state, volume ratio, wave direction, session volumes, last wave volume, liquidity state, delta pressure, CVD momentum, wave volume comparison, session delta bias, delta strength, active wave volume, exhaustion counts, and bar style Input Parameters Cumulative Delta: CVD Smoothing: EMA period for CVD smoothing (default: 14) Normalize CVD: Toggle z-score normalization for cross-asset comparability (default: on) CVD Ribbon Fast/Slow: EMA periods for the momentum ribbon (default: 8/21) Wave Volume: Wave ATR Multiplier: Threshold for wave reversal detection (default: 1.5) Wave ATR Length: ATR period for wave threshold (default: 14) Signals: Absorption Vol Threshold: Volume multiple for absorption detection (default: 2.0) Climax Vol Threshold: Volume multiple for climax detection (default: 3.0) Toggles for wave divergence, absorption, climax, and exhaustion signals Visuals: Bar Style: Solid, Hollow, Intensity, or Glass (default: Intensity) Toggles for delta intensity coloring, wave histogram, CVD overlay, CVD ribbon, session background, and dashboard How to Use This Indicator Step 1: Read the Liquidity State Check the dashboard's Liquidity State. "Absorption" at support suggests institutions are buying. "Climax" after an extended move suggests a potential turning point. "Exhaustion" means the trend is losing volume fuel. "Normal" means standard conditions apply. Step 2: Monitor CVD Direction Rising CVD confirms uptrends; falling CVD confirms downtrends. CVD diverging from price is a warning sign. If price is making new highs but CVD is flat or declining, the rally may lack genuine buying support. Step 3: Compare Wave Volumes In a healthy uptrend, up-wave volumes should be larger than down-wave volumes. If down-wave volumes start exceeding up-wave volumes while price is still rising, distribution may be occurring. The Wave Volume Comparison metric in the dashboard tracks this automatically. Step 4: Use Delta Pressure for Bias The Delta Pressure score (0-100) provides a quick read on who controls the last 20 bars. Above 60 = buyers dominate. Below 40 = sellers dominate. Between 40-60 = balanced/contested. Step 5: Watch for Signal Clusters The most significant moments occur when multiple signals cluster: an absorption bar followed by a wave divergence during an exhaustion phase, for example, creates a high-conviction reversal setup. Single signals in isolation are less reliable. Indicator Limitations The CVD approximation (close > open = buying, close < open = selling) is a simplification. True order flow data requires Level 2/DOM data not available in Pine Script. This approximation works reasonably well on liquid instruments but is inherently imprecise Volume data quality varies significantly across instruments and data providers. Forex "volume" is typically tick count, not actual traded volume. Crypto volume may include wash trading. The indicator's effectiveness depends on the quality of the underlying volume data Weis Wave reversal detection depends on the ATR threshold parameter. Too small a threshold produces too many waves (noise); too large produces too few (missing genuine reversals). The optimal setting varies by instrument and timeframe Absorption and climax detection use fixed ratio thresholds. What constitutes "extreme" volume varies across instruments and market conditions. The thresholds may need adjustment Session volume tracking uses TradingView's built-in session detection, which may not align perfectly with all exchanges or instruments The indicator operates in a separate pane and cannot overlay directly on price. Cross-referencing signals with price action requires visual comparison between panes Originality Statement This indicator is original in its comprehensive fusion of multiple volume analysis methodologies into a unified intelligence pane. While individual components (CVD, Weis Wave, volume absorption) exist separately, this indicator is justified because: The integration of CVD, Weis Wave clustering, absorption detection, climax detection, and exhaustion tracking into a single system provides layered volume intelligence not available in any single existing indicator The delta intensity bar coloring system uses gradient transparency based on delta strength, providing conviction information within the volume bars themselves The liquidity state classification system synthesizes all detection subsystems into a single categorical assessment of current market conditions Session-partitioned delta tracking reveals whether accumulation or distribution is occurring within specific market sessions The CVD momentum ribbon provides a trend-following overlay on the delta data, identifying shifts in buying/selling momentum Four distinct bar design modes (Solid, Hollow, Intensity, Glass) offer visual flexibility for different analysis preferences Wave volume comparison with expanding/contracting classification automates Wyckoff-style wave analysis 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. Volume analysis provides context about market participation but does not predict future price direction. Absorption, climax, and exhaustion signals are probabilistic patterns that can and do fail. CVD approximations are not equivalent to true order flow data. Always use proper risk management and conduct your own analysis. The author is not responsible for any losses incurred from using this indicator. -Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
Delta Absorption Scanner[MarkitTick]💡 This advanced analytical tool is engineered to bridge the gap between price action and order flow dynamics by identifying critical moments where market participants encounter significant liquidity barriers. In the modern trading landscape, volume alone is often insufficient to determine market direction. The Delta Absorption Scanner provides a sophisticated lens through which traders can observe the interaction between aggressive market orders and passive limit orders, specifically highlighting "Absorption" events. These events occur when high-volume "Effort" fails to produce a proportional price "Result," signaling a potential exhaustion of the current trend or a hidden accumulation/distribution phase. By synthesizing volume delta, candle spread, and multi-timeframe context into a unified interface, this script empowers traders to make decisions based on the structural integrity of the market rather than superficial price movements. ✨ Originality and Utility The primary utility of this script lies in its multi-layered approach to market analysis, moving beyond simple oscillators or trend-following moving averages. Unlike standard volume indicators that merely report total activity, this scanner differentiates between buying and selling pressure by calculating candle-based delta, allowing for a more granular view of market intent. The script introduces a unique "Scanner" architecture that monitors four distinct high-timeframe (HTF) perspectives simultaneously. This provides an institutional-grade view of the trend without the need to constantly switch chart intervals. It incorporates a proprietary "Absorption" detection logic that correlates delta percentage with the physical spread of the candle. This identifies "hidden" strength or weakness that is often invisible to the naked eye. The inclusion of Fair Value Gap (FVG) and Swing High/Low detection within the dashboard creates a comprehensive "Confluence Engine," ensuring that short-term delta signals are validated by higher-level market structures. By utilizing non-repainting multi-timeframe logic (security calls with index offsets), the indicator maintains the highest standards of data integrity, making it suitable for both discretionary trading and systemic strategy development. 🔬 Methodology and Concepts The core logic begins with the calculation of "Candle Delta," which determines the dominant force within a single bar based on its polarity. If a candle closes above its open, the entire volume is attributed to positive delta; if it closes below, it is negative. The indicator then calculates the "Spread," defined as the absolute distance between the high and low of the bar. This metric is critical for the "Effort vs. Result" analysis. Absorption is mathematically flagged when a candle exceeds the user-defined "Minimum Delta %" threshold but fails to generate significant directional movement, or when the spread is disproportionately small compared to the volume injected. The Support (S3) and Resistance (R3) levels are derived from the most recent significant high-volume or high-delta bars, creating dynamic zones that reflect where institutional liquidity was last engaged. Multi-Timeframe Integration: The script utilizes the request.security() function with a bar offset. This ensures that the data displayed from higher timeframes is "confirmed" and prevents the visual bias known as repainting. Trend determination on the dashboard is calculated using a proprietary relationship between the current price and the 14-period smoothed high/low averages, providing a stable "Trend Bias" for each monitored timeframe. ● Main Feature Components • Volume Delta labels The script places dynamic labels above or below candles that exhibit significant delta. These labels display the Delta percentage, helping traders identify where "Climax" volume is occurring. • Spread Analysis (S) Next to the Delta % is a value representing the "Spread." This allows for an immediate visual comparison: High Delta with Low Spread suggests passive absorption (reversal), while High Delta with High Spread suggests aggressive momentum (continuation). • Multi-Timeframe (HTF) Dashboard A sophisticated table displayed on the chart that aggregates data from up to four higher timeframes. This dashboard is the "brain" of the scanner, providing a bird's-eye view of the market's broader health. 🎨 Visual Guide Positive Delta Labels: Displayed as green labels with white text. These signify bars where buying volume was dominant. Negative Delta Labels: Displayed as red labels with white text. These signify bars where selling volume was dominant. Neutral/Spread Labels: Displayed in a dark neutral color to represent bars where the spread is being analyzed without a significant delta bias. Dashboard - Trend Column: Displays "UP" in green for bullish regimes and "DN" in red for bearish regimes for each of the four HTF settings. Dashboard - S3/R3 Column: Displays the price of the nearest significant support or resistance level identified by the script. Dashboard - Distance % Column: A dynamic calculation showing how far the current price is from the S3/R3 levels. Green indicates distance from support, while red indicates distance from resistance. Dashboard - FVG Column: Displays "+FVG" in green if a bullish Fair Value Gap exists on that timeframe, or "-FVG" in red if a bearish gap is present. Dashboard - Swing Column: Identifies if the current price is near a local "Top" or "Bottom" based on pivot logic. 📖 How to Use Step 1: Identify "Effort" on the Chart. Look for a large Delta % label (e.g., >20%) appearing at a local high or low. Step 2: Analyze the "Result." If the Delta is high (Green/Positive) but the candle spread (S) is small and price fails to move higher, this is a classic Bearish Absorption signal. Limit sellers are "absorbing" the market buyers. Step 3: Consult the Dashboard. Check if the HTF trends are in alignment. For a short trade based on Bearish Absorption, you ideally want to see "DN" trends on higher timeframes and the presence of a "-FVG." Step 4: Proximity to S/R. Use the "Dist %" column to ensure you are not selling directly into a higher-timeframe support (S3) or buying directly into resistance (R3). Step 5: Confluence. The highest probability trades occur when a Delta climax appears at a dashboard-confirmed Swing Top/Bottom in the direction of the HTF trend. ⚙️ Inputs and Settings Positive/Negative Delta Color: Customizes the aesthetic of the bull/bear labels to match your chart theme. Max Labels on Chart: Controls the lookback period for visual labels to maintain chart performance and reduce clutter. Minimum Delta % to Show: A sensitivity filter. Higher values (e.g., 50%) will only show the most extreme volume events, while lower values (e.g., 10%) provide more frequent signals. Show Spread (S): Toggles the visibility of the candle spread value within the labels. HTF 1-4 Settings: Allows the user to define which timeframes the dashboard should track (e.g., 1H, 4H, Daily, Weekly). Dashboard Position: Permits the user to move the table to different corners of the chart for better visibility. 🔍 Deconstruction of the Underlying Scientific and Academic Framework • The Law of Effort vs. Result Based on the principles established by Richard Wyckoff, this indicator quantifies "Effort" as Volume Delta and "Result" as Price Spread. In a balanced market, increased effort should lead to an equivalent result. When these two diverge (Anomalies), it suggests a change in market character. • Auction Market Theory (AMT) The indicator utilizes AMT principles by identifying areas of "High Volume Nodes" (represented by S3/R3) where the market has found value or met significant opposition. The "Distance %" feature measures the market's deviation from these nodes, which often acts as a mean-reversion catalyst. • Order Flow Imbalance While traditional indicators use price as a lagging derivative, the Delta Absorption Scanner attempts to lead price by observing the imbalance between aggressive market participants. By isolating the delta within each bar, the script identifies where one side of the "Auction" is becoming exhausted. • Statistical Significance of Spread The inclusion of spread analysis is rooted in statistical volatility measurements. A narrow spread during high volume indicates a high density of limit orders (Liquidity), which is a precursor to price reversals or significant breakouts once the liquidity is exhausted. • Multi-Timeframe Structuralism The scanner's architecture is based on the theory that lower-timeframe "noise" is resolved by higher-timeframe "structure." By mapping FVGs and Swings across four dimensions, the script applies a fractal analysis to the current bar's delta events. ⚠️ Disclaimer All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Indicador Pine Script®
por MarkitTick
Ferrum Pressure Gauge [JOAT]Ferrum Pressure Gauge Introduction The Ferrum Pressure Gauge is an open-source composite momentum-volume oscillator that fuses three independent pressure measurements — volume-weighted momentum, price velocity with acceleration, and RSI-derived trend pressure — into a single index displayed in a separate pane. The index is paired with a signal (resonance) line, and the space between them is filled with an 8-layer gradient that visually communicates momentum intensity at a glance. Dynamic non-repainting zones adapt to recent range, divergence detection identifies price-vs-index fractures, and a precursor engine spots early reversal conditions before the main index confirms them. Most momentum oscillators measure a single dimension — either price momentum or volume momentum, but rarely both in a unified way. FPG addresses this by weighting price changes by volume activity through a logarithmic volume impact function, then combining that with velocity, acceleration, and RSI into a composite reading. The result is an oscillator that responds to both the speed and the conviction behind price moves. Core Engine: Fusion Reactor The composite index is built from three sub-components: 1. Volume-Weighted Momentum (Net Flow) Price changes are scaled by a logarithmic volume impact function that amplifies moves occurring on above-average volume while dampening moves on thin volume: float vRatio = ta.sma(volume, 3) / ta.sma(volume, volPeriod) float vwMom = pChange * math.log(1 + vRatio * volSens) The logarithmic scaling prevents extreme volume spikes from producing absurdly large momentum readings while still giving meaningful weight to elevated volume. Fast and slow EMAs of this volume-weighted momentum produce a dual-speed flow, and their difference (smoothed) becomes the Net Flow component. 2. Price Velocity and Acceleration Velocity measures the average price change per bar over the fast period. Acceleration is the change in velocity — it detects whether momentum is building or fading. These are combined with the volume ratio and scaled to produce the Flow Strength component. 3. RSI Trend Pressure RSI is centered around zero (RSI - 50) and smoothed, providing a bounded measure of trend pressure that complements the unbounded volume-weighted components. The three components are averaged and passed through a final WMA smoothing pass to produce the Pressure Index. A separate EMA of the index produces the Resonance (signal) line. 8-Layer Gradient Fill The space between the Pressure Index and the Resonance Line is divided into 8 equal segments, each filled with progressively increasing transparency. This creates a smooth gradient that is dense and vivid when momentum is strong (large gap between index and signal) and thin and faded when momentum is weak. The gradient direction and color shift based on whether the index is positive or negative and whether it is in the upper or lower crucible zone. Dynamic Crucible Boundaries (Non-Repainting Zones) Rather than using fixed overbought/oversold levels, FPG calculates dynamic zones based on the recent range of the index: float rHi = ta.highest(idx, zoneLen) float rLo = ta.lowest(idx, zoneLen) float volF = (rHi - rLo) / 2 float upperZ = math.min(60, 30 + volF * 0.3) float lowerZ = math.max(-60, -30 - volF * 0.3) The offset on highest/lowest ensures these zones never repaint. They widen during volatile periods and tighten during calm ones, adapting the overbought/oversold thresholds to current market conditions rather than using arbitrary fixed levels. Volume Climax (Surge Detection) The indicator percentile-ranks current volume against a configurable lookback (default 100 bars). When volume exceeds the 90th percentile, a surge is detected. The edge-triggered SURGE label fires only on the first bar of the spike, marking potential climax events where institutional-scale volume enters the market. Exhaustion Index (Fatigue Meter) When the Pressure Index dwells in an extreme zone (above upper or below lower boundary), a fatigue counter increments each bar. The fatigue percentage rises linearly toward 100% over a configurable horizon (default 20 bars). Fatigue is classified as NONE, MILD, BUILDING, or CRITICAL. Critical fatigue warns that momentum has been stretched for an extended period and reversal probability is elevated. Fracture Detection (Divergence) The indicator detects classic divergences between price and the Pressure Index: Bullish Fracture: Price is falling (making lower lows) while the Pressure Index is rising — hidden buying pressure beneath falling prices. Bearish Fracture: Price is rising (making higher highs) while the Pressure Index is falling — hidden selling pressure beneath rising prices. Fracture signals are confirmed-bar only and placed outside the crucible boundaries to avoid overlapping with the main index plot. Precursor Engine (Early Reversal Detection) The precursor engine identifies conditions where the fast and slow flow lines cross while the main index is on the opposite side of zero: IGNITION (Bullish Precursor): Fast flow crosses above slow flow while the Pressure Index is still negative — early bullish momentum building before the index turns positive. QUENCH (Bearish Precursor): Fast flow crosses below slow flow while the Pressure Index is still positive — early bearish momentum building before the index turns negative. These signals often lead the main index crossover by several bars, providing an early warning system. Command Panel (Dashboard) A 9-row monospace dashboard displays: PRESSURE: Current Pressure Index value with color reflecting zone position RESONANCE: Current signal line value FLOW: Net flow delta (fast minus slow) — the raw momentum differential FLUX: Volume ratio (short/long SMA) — values above 1.2 indicate elevated activity CRUCIBLE: Current dynamic upper and lower zone boundaries SURGE: Whether volume is currently in a climax state (ACTIVE / QUIET) FATIGUE: Exhaustion classification with percentage (NONE / MILD / BUILDING / CRITICAL) DELTA: Histogram value (index minus signal) — positive = bullish momentum, negative = bearish Input Parameters Fusion Reactor: Ignition Cycle: Fast EMA period (default 8) Sustain Cycle: Slow EMA period (default 21) Flux Epoch: Volume SMA lookback (default 14) Flux Amplifier: Volume impact scaling (default 1.5) Forge Smoothing / Temper Pass: Composite and final smoothing Resonance Layer: Resonance Period: Signal line EMA (default 12) Crucible Boundaries: Toggle dynamic zones Boundary Lookback: Zone calculation window (default 50) Volume Climax: Enable Surge Detection / Surge Percentile / Surge Lookback Exhaustion Index: Enable Fatigue Meter / Fatigue Horizon: Bars in extreme zone before max fatigue Fracture Detection: Show Fractures / Fracture Lookback: Divergence detection parameters Precursor Engine: Show Precursors: Toggle early reversal signals How to Use This Indicator Use the Pressure Index crossing above/below the Resonance Line as a momentum confirmation signal — similar to MACD crossovers but volume-weighted. Watch for IGNITION/QUENCH precursor signals — they often lead the main crossover by several bars and can provide earlier entries. FRACTURE (divergence) signals are among the most reliable warnings of trend exhaustion. A bullish fracture during a downtrend suggests hidden accumulation. Monitor the Fatigue meter when the index is in an extreme zone. CRITICAL fatigue combined with a fracture signal is a high-probability reversal setup. SURGE markers highlight institutional-scale volume events. A surge occurring at a crucible boundary often marks a climax reversal point. The 8-layer gradient provides instant visual feedback — dense, vivid fills indicate strong momentum conviction; thin, faded fills indicate weakening momentum. Limitations Like all momentum oscillators, FPG is lagging — it confirms momentum after it has begun, not before. Divergence (fracture) signals can persist for extended periods before price reverses. They indicate weakening momentum, not guaranteed reversals. Precursor signals are early by design and therefore have a higher false-positive rate than confirmed crossover signals. Volume-weighted calculations are less reliable on instruments with inconsistent or unreported volume data. The Fatigue meter is a heuristic based on time-in-zone, not a statistical probability. Extended trends can maintain extreme readings longer than expected. Dynamic zones adapt to recent range but may lag during sudden regime changes. Originality Statement This indicator is original in its composite fusion approach. While MACD, RSI, and volume analysis are established concepts individually, FPG is justified because: The logarithmic volume-weighted momentum calculation provides a unique fusion of price change and volume conviction that differs from standard MACD or OBV approaches. Three independent sub-components (volume-weighted flow, velocity/acceleration, RSI pressure) are composited into a single index, providing multi-dimensional momentum measurement. The 8-layer gradient fill between index and signal line creates a visual momentum density map not found in standard oscillators. Dynamic non-repainting crucible boundaries adapt overbought/oversold levels to current conditions rather than using fixed thresholds. The Exhaustion Index tracks time-in-extreme-zone as a fatigue metric, adding a temporal dimension to momentum analysis. The Precursor Engine identifies early flow crossovers while the main index is on the opposite side, providing leading signals ahead of the main crossover. Volume Climax detection via percentile ranking integrates institutional-scale volume event identification directly into the oscillator. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Momentum oscillators describe the current state of price momentum but do not predict future price direction. Overbought conditions can persist in strong trends, and oversold conditions can deepen in bear markets. Always use proper risk management and conduct your own analysis before making trading decisions. The author is not responsible for any losses incurred from using this tool. -Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
Delta Pressure Index [JOAT]Delta Pressure Index Introduction The Delta Pressure Index is an advanced open-source volume analysis indicator that deconstructs order flow into actionable pressure metrics, combining volume delta estimation, absorption zone detection, smart money divergence analysis, and institutional order block identification. This indicator transforms raw volume data into a comprehensive pressure measurement system that reveals the true balance of power between buyers and sellers. Unlike basic volume indicators that simply display volume bars, this system analyzes the internal structure of volume to identify buying and selling pressure, detect institutional absorption patterns, recognize smart money positioning through divergences, and map order blocks where large players have established positions. The indicator is designed for traders who understand that volume precedes price and that institutional footprints can be detected through systematic pressure analysis. Why This Indicator Exists This indicator addresses a critical gap in retail volume analysis: the ability to measure directional pressure and institutional activity in real-time. While exchange-provided volume data shows total activity, it doesn't reveal who is winning the battle between buyers and sellers. The Delta Pressure Index solves this by: Volume Delta Estimation: Separates buying volume from selling volume using candle structure and wick analysis Pressure Index Calculation: Normalizes delta to a -100 to +100 scale showing relative pressure strength Absorption Zone Detection: Identifies when high volume produces minimal price movement, indicating institutional accumulation or distribution Smart Money Divergence: Compares volume-weighted price to actual price to detect hidden institutional positioning Order Block Mapping: Marks zones where institutional orders have been placed based on volume and price action patterns Multi-Timeframe Pressure: Analyzes pressure alignment across multiple timeframes for conviction measurement Cumulative Delta Tracking: Monitors net buying/selling pressure over time to identify accumulation and distribution phases Each component provides unique intelligence about market microstructure. Delta estimation shows directional bias, pressure index quantifies strength, absorption detection reveals institutional activity, divergences expose hidden positioning, order blocks mark support/resistance zones, and cumulative delta tracks longer-term institutional flow. Core Components Explained 1. Enhanced Volume Delta Estimation The indicator uses advanced candle structure analysis to estimate buying and selling volume: barRange = high - low bodySize = math.abs(close - open) wickUp = high - math.max(open, close) wickDown = math.min(open, close) - low buyVolume = close > open ? volume * ((close - open + wickUp * 0.5) / barRange) : close < open ? volume * ((wickUp + bodySize * 0.3) / barRange) : volume * 0.5 sellVolume = volume - buyVolume delta = buyVolume - sellVolume This calculation considers: - Bullish candles (close > open): Majority of volume is buying, with upper wick getting 50% weight - Bearish candles (close < open): Majority of volume is selling, with upper wick and 30% of body getting buying weight - Doji candles (close = open): Volume split 50/50 between buying and selling The wick weighting acknowledges that wicks represent rejected prices where one side overwhelmed the other, providing additional directional information beyond just the candle body. 2. Pressure Index Normalization Raw delta values are normalized to create a pressure index ranging from -100 (extreme selling) to +100 (extreme buying): pressureIndex = ta.sma(delta, deltaLength) / ta.sma(volume, deltaLength) * 100 This normalization divides smoothed delta by smoothed volume, creating a percentage that shows the proportion of volume favoring buyers vs sellers. The smoothing (default 14 periods) reduces noise while maintaining responsiveness to genuine pressure shifts. The pressure index is further enhanced with volume-weighted calculations: vwPressure = ta.vwma(pressureIndex, deltaLength) Volume-weighted pressure gives more importance to high-volume bars, ensuring that pressure readings reflect periods of genuine institutional participation rather than low-volume noise. 3. Pressure Zone Classification The indicator classifies pressure into seven distinct zones: Extreme Buy (>70): Overwhelming buying pressure, potential exhaustion or continuation Strong Buy (50-70): Significant buying dominance, healthy uptrend conditions Moderate Buy (30-50): Mild buying bias, early trend development Weak Buy (20-30): Slight buying edge, transitional conditions Neutral (-20 to +20): Balanced conditions, no clear directional pressure Weak Sell (-30 to -20): Slight selling edge, transitional conditions Moderate Sell (-50 to -30): Mild selling bias, early downtrend development Strong Sell (-70 to -50): Significant selling dominance, healthy downtrend conditions Extreme Sell (<-70): Overwhelming selling pressure, potential exhaustion or continuation These zones help traders quickly assess current pressure conditions and identify extreme readings that often precede reversals or accelerations. 4. Absorption Detection System Absorption occurs when high volume produces minimal price movement, indicating that one side is absorbing the other's orders: avgVolume = ta.sma(volume, 20) avgRange = ta.sma(barRange, 20) volumeRatio = volume / avgVolume rangeRatio = barRange / avgRange absorption = volumeRatio > absorptionThreshold and rangeRatio < 0.5 The system identifies absorption when: - Volume exceeds average by the threshold multiplier (default 2.5x) - Price range is less than 50% of average range Absorption is classified as: - Buy Absorption: High volume + small range + positive delta = Institutional accumulation - Sell Absorption: High volume + small range + negative delta = Institutional distribution - Extreme Absorption: Absorption score exceeds 1.5x threshold = Major institutional activity Absorption zones often mark significant support/resistance levels where institutions have established large positions. 5. Smart Money Divergence Analysis The indicator compares volume-weighted average price (VWAP) to simple moving average to detect smart money positioning: vwPrice = ta.vwma(close, 20) actualPrice = ta.sma(close, 20) smartMoneyDivergence = ((vwPrice - actualPrice) / actualPrice) * 100 When VWAP is significantly above SMA (>2%), it indicates that higher-volume bars occurred at higher prices, suggesting smart money accumulation. When VWAP is significantly below SMA (<-2%), it indicates higher-volume bars occurred at lower prices, suggesting smart money distribution. Smart money signals are generated when: - Bullish: Divergence >2%, price below VWAP, positive pressure = Accumulation opportunity - Bearish: Divergence <-2%, price above VWAP, negative pressure = Distribution warning 6. Order Block Detection Order blocks are identified using institutional footprint patterns: bullishOB = close < open and close > open and volume > avgVolume * 1.2 bearishOB = close > open and close < open and volume > avgVolume * 1.2 Bullish order blocks occur when: - Previous candle was bearish (close < open) - Current candle is bullish (close > open) - Volume exceeds average by 20% This pattern suggests institutions placed buy orders in the previous bearish candle, which then fueled the bullish reversal. The zone between the previous candle's low and high becomes a potential support area. Bearish order blocks follow the inverse logic, marking potential resistance zones where institutional sell orders were placed. 7. Cumulative Delta Tracking The indicator maintains a running total of delta to track longer-term institutional positioning: var float cumulativeDelta = 0 cumulativeDelta += delta Rising cumulative delta indicates sustained buying pressure (accumulation phase). Falling cumulative delta indicates sustained selling pressure (distribution phase). The rate of change in cumulative delta shows acceleration or deceleration of institutional flow. The indicator also tracks session cumulative delta that resets on trend changes, providing shorter-term context for intraday pressure analysis. 8. Delta Momentum and Acceleration The indicator calculates momentum and acceleration metrics: deltaMomentum = ta.roc(pressureIndex, 5) deltaAcceleration = ta.roc(deltaMomentum, 3) Delta momentum shows the rate of change in pressure, identifying when pressure is building or fading. Delta acceleration (second derivative) identifies inflection points where momentum is changing direction, often preceding major pressure shifts. Positive acceleration with positive momentum suggests strengthening buying pressure. Negative acceleration with positive momentum warns that buying pressure is weakening, even if still positive. 9. Multi-Timeframe Pressure Analysis The indicator requests pressure data from four higher timeframes (default: 5m, 15m, 60m, 240m): htf1_pressure = request.security(syminfo.tickerid, htf1, pressureIndex, lookahead=barmerge.lookahead_off) MTF confluence score is calculated by averaging the sign of pressure across all timeframes: mtfConfluence = (math.sign(htf1_pressure) + math.sign(htf2_pressure) + math.sign(htf3_pressure) + math.sign(htf4_pressure)) / 4 * 100 Confluence scores near +100 indicate all timeframes show buying pressure. Scores near -100 indicate all timeframes show selling pressure. Scores near 0 indicate mixed or transitional conditions across timeframes. Visual Elements Pressure Index Columns: Main histogram showing pressure index with gradient coloring from extreme sell (pink) to extreme buy (cyan) Volume-Weighted Pressure Line: Yellow line overlay showing VWMA of pressure for trend identification Pressure EMA Line: Cyan line showing smoothed pressure trend Delta Momentum Histogram: Purple histogram showing rate of change in pressure Reference Lines: Horizontal lines at 0, ±30, ±50, ±70 marking pressure zone boundaries Divergence Labels: Text labels marking regular and hidden divergences between price and pressure Smart Money Labels: Green labels marking accumulation/distribution signals Absorption Markers: Cyan/red labels marking buy/sell absorption zones Order Block Boxes: Orange boxes marking institutional order block zones on price chart Extreme Pressure Labels: Small labels marking extreme buy/sell pressure conditions Pressure Heatmap: Subtle background gradient showing pressure intensity Comprehensive Dashboard: Real-time metrics table showing pressure, delta %, cumulative delta, zone, absorption, smart money, divergence, momentum, MTF confluence, and all key metrics The dashboard displays 12+ key metrics with color-coded values and status indicators, providing complete pressure analysis at a glance. Input Parameters Core Settings: Delta Length: Period for delta smoothing (5-100, default 14) Smoothing Period: Additional smoothing for pressure index (1-20, default 3) Volume MA Length: Period for volume average (5-100, default 20) Absorption Threshold: Volume multiplier for absorption detection (1.0-5.0, default 2.5) Multi-Timeframe: Enable Multi-Timeframe Analysis: Toggle MTF pressure analysis (default enabled) HTF 1/2/3/4: Four higher timeframe selections (default 5m, 15m, 60m, 240m) Display Options: Show Cumulative Delta: Toggle cumulative delta tracking (default enabled) Show Absorption Zones: Toggle absorption detection markers (default enabled) Show Divergences: Toggle divergence detection (default enabled) Show Smart Money Signals: Toggle smart money analysis (default enabled) Show Volume Profile: Toggle volume profile POC (default enabled) Show Dashboard: Toggle metrics table (default enabled) Show Pressure Heatmap: Toggle background gradient (default enabled) Show Order Blocks: Toggle order block boxes (default enabled) Colors: All colors are fully customizable including buy pressure (neon cyan), sell pressure (neon pink), buy absorption (neon cyan), sell absorption (neon red), smart money (neon green), divergence (neon purple), and order blocks (sunset orange). How to Use This Indicator Step 1: Assess Current Pressure Check the dashboard "Pressure" value and "Zone" classification. Extreme readings (>70 or <-70) often precede reversals or strong continuations. Strong readings (50-70 or -50 to -70) indicate healthy trend conditions. Step 2: Monitor Delta Percentage Review "Delta %" showing the proportion of volume favoring buyers vs sellers. Values above 50% indicate buying dominance, below -50% indicate selling dominance. This provides confirmation of pressure index readings. Step 3: Track Cumulative Delta Observe "Cum Delta" to identify longer-term institutional positioning. Rising cumulative delta during pullbacks suggests accumulation. Falling cumulative delta during rallies warns of distribution. Step 4: Identify Absorption Zones Watch for absorption labels and check dashboard "Absorption" status. Buy absorption near support levels suggests institutional accumulation. Sell absorption near resistance suggests institutional distribution. These zones often become significant support/resistance. Step 5: Detect Smart Money Divergence Monitor smart money labels and dashboard status. Accumulation signals during downtrends suggest smart money is buying weakness. Distribution signals during uptrends warn that smart money is selling strength. Step 6: Analyze Divergences Look for divergence labels where price makes new highs/lows but pressure doesn't confirm. Regular divergences signal potential reversals. Hidden divergences suggest trend continuation after pullbacks. Step 7: Map Order Blocks Identify order block boxes on the price chart. These zones mark where institutions placed large orders. Price often respects these levels on retests, providing high-probability entry zones. Step 8: Confirm with MTF Confluence Check "MTF Confluence" in dashboard. High positive confluence (>75) confirms buying pressure across timeframes. High negative confluence (<-75) confirms selling pressure. Low confluence suggests mixed conditions. Best Practices Use on liquid instruments with reliable volume data for most accurate pressure readings Extreme pressure readings (>70 or <-70) are most reliable when accompanied by volume surges Absorption zones near key price levels offer highest-probability reversal setups Smart money divergence signals work best when confirmed by order block formation Cumulative delta diverging from price often precedes major reversals Order blocks are most reliable when formed on high volume (>1.5x average) MTF confluence above 75% or below -75% provides strong directional conviction Delta momentum acceleration signals often precede pressure regime changes Pressure heatmap intensity helps visualize pressure strength at a glance Regular divergences are most reliable at extreme pressure levels Hidden divergences work best in established trends as continuation signals Combine pressure analysis with price action for optimal entry timing Indicator Limitations Volume delta estimation is approximate - true delta requires exchange order flow data The indicator works best on instruments with consistent, reliable volume reporting Low-volume instruments or off-market hours can produce unreliable pressure readings Absorption detection requires sufficient volume history for accurate average calculations Smart money divergence assumes VWAP represents institutional positioning, which is a simplification Order block detection uses pattern recognition that may not capture all institutional activity MTF analysis requires data availability on all selected timeframes Cumulative delta can drift significantly over long periods without reset mechanisms The indicator shows pressure dynamics but cannot predict how long pressure will persist Extreme pressure can remain extreme longer than expected during strong trends Divergences can persist for extended periods before price responds Technical Implementation Built with Pine Script v6 using: Advanced volume delta estimation using candle structure and wick analysis Normalized pressure index calculation with volume-weighted enhancement Seven-zone pressure classification system Absorption detection using volume ratio and range ratio analysis Smart money divergence calculation comparing VWAP to SMA Order block detection using institutional footprint patterns Cumulative delta tracking with session reset capability Delta momentum and acceleration calculations using rate-of-change Multi-timeframe security requests with proper lookahead settings Fractal-based divergence detection system Dynamic color gradients based on pressure intensity Comprehensive dashboard with 12+ metrics and color-coded indicators Persistent label system to prevent chart clutter Order block box management with automatic cleanup The code is fully open-source with detailed comments explaining each pressure calculation and detection algorithm. Originality Statement This indicator is original in its comprehensive pressure analysis approach. While volume delta concepts are established, this indicator is justified because: It combines volume delta estimation with absorption detection, smart money analysis, and order block mapping in a unified system The enhanced delta calculation uses wick weighting to capture rejected price information Seven-zone pressure classification provides granular pressure assessment beyond simple buy/sell Absorption detection identifies institutional activity through volume-range relationship analysis Smart money divergence reveals hidden positioning through VWAP-SMA comparison Order block detection maps institutional zones using volume-confirmed reversal patterns Multi-timeframe confluence scoring validates pressure across temporal dimensions Delta momentum and acceleration tracking provides early warning of pressure shifts The comprehensive dashboard synthesizes 12+ distinct metrics into unified pressure intelligence Integration of cumulative delta, absorption, divergence, and order blocks creates layered confirmation Each component contributes unique intelligence: delta shows directional bias, pressure index quantifies strength, absorption reveals institutional activity, divergences expose hidden positioning, order blocks mark key zones, MTF confluence validates conviction, and momentum tracks acceleration. The indicator's value lies in combining these complementary perspectives into a cohesive pressure analysis 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 pressure analysis is a tool for understanding order flow dynamics, not a crystal ball for predicting future price movement. Extreme pressure readings do not guarantee reversals. Absorption zones do not guarantee support/resistance. Past pressure patterns do not guarantee future pressure 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. Pressure readings, divergences, absorption zones, and order blocks 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
Indicador Pine Script®
por officialjackofalltrades
Adaptive Trend Ribbon [JOAT]Adaptive Trend Ribbon Introduction The Adaptive Trend Ribbon is an advanced open-source trend-following indicator that combines multi-layer moving average analysis with real-time volatility adaptation, momentum weighting, and volume confirmation. This indicator transforms traditional ribbon systems into an institutional-grade tool by dynamically adjusting to market conditions, providing traders with a comprehensive view of trend strength, direction, and potential reversals across all timeframes. Unlike static ribbon indicators that use fixed parameters, this system continuously adapts to volatility percentiles, momentum shifts, and volume surges, creating a responsive framework that works equally well in ranging, trending, and explosive market conditions. The indicator is designed for traders who understand that market regimes change and that adaptive systems outperform static ones in real-world trading. Why This Indicator Exists This indicator addresses critical limitations in traditional moving average systems by introducing adaptive intelligence that responds to market microstructure. The core innovation lies in combining multiple adaptation mechanisms: Volatility Adaptation: Ribbon parameters adjust based on ATR percentile ranking, expanding during high volatility and contracting during consolidation Momentum Adaptation: RSI-based momentum weighting modifies ribbon sensitivity to capture acceleration and deceleration phases Volume Adaptation: Volume ratio analysis confirms trend validity and filters false signals during low-participation moves Multi-Timeframe Alignment: Higher timeframe trend confirmation across three customizable periods validates directional conviction Ribbon Compression Detection: Identifies coiling patterns that precede explosive breakouts with statistical precision Twist Reversal System: Detects ribbon layer crossovers that signal potential trend exhaustion or reversal Each adaptation layer provides unique intelligence. Volatility adaptation ensures the ribbon remains relevant across different market regimes, momentum adaptation captures trend acceleration, volume adaptation confirms institutional participation, MTF alignment validates conviction, compression detection anticipates breakouts, and twist detection warns of reversals. Core Components Explained 1. Adaptive Multiplier System The indicator calculates three distinct adaptation factors that combine into a unified multiplier: Volatility Multiplier: Based on ATR percentile ranking over 100 bars, this factor increases ribbon responsiveness during high volatility periods and decreases it during low volatility. The calculation uses percentile ranking rather than raw ATR to normalize across different instruments and timeframes. Momentum Multiplier: Derived from RSI deviation from the 50 midpoint, this factor amplifies ribbon sensitivity during strong momentum phases and dampens it during consolidation. The normalization ensures the multiplier remains bounded and predictable. Volume Multiplier: Calculated as the ratio of current volume to 20-period average volume, capped at 2x to prevent extreme distortions. This factor confirms that price movements are supported by genuine participation rather than thin-market noise. The combined adaptive multiplier averages these three factors, creating a balanced response to multiple market dimensions simultaneously. This multi-factor approach prevents over-optimization to any single market characteristic. 2. Multi-Layer Ribbon Construction The ribbon consists of 3 to 20 customizable moving average layers (default 12) spanning from a fast length (default 5) to a slow length (default 55). The indicator supports five moving average types: EMA (Exponential Moving Average): Responsive to recent price action, ideal for trending markets SMA (Simple Moving Average): Equal weighting, provides stable trend identification WMA (Weighted Moving Average): Linear weighting favoring recent data VWMA (Volume-Weighted Moving Average): Incorporates volume into price averaging HMA (Hull Moving Average): Reduced lag through weighted calculations and square root periods Each ribbon layer is calculated with evenly distributed periods between fast and slow lengths. The spacing ensures smooth gradient transitions and prevents clustering that can create false signals. The ribbon can optionally use Heikin Ashi candles as the source, providing additional smoothing for noisy instruments. 3. Trend Detection and Classification The indicator employs multiple trend detection mechanisms: Ribbon Trend: Determined by comparing the fastest MA to the slowest MA. When fast > slow, the ribbon trend is bullish; when fast < slow, it's bearish. Price Trend: Determined by comparing current price to the middle ribbon layer. This provides confirmation that price is aligned with the ribbon structure. Aligned Trend: Occurs when both ribbon trend and price trend agree, indicating high-probability directional moves. Trend strength is measured using percentile ranking of ribbon width over 50 bars. Higher percentile rankings indicate stronger trends with greater separation between ribbon layers, while lower rankings suggest consolidation or trend exhaustion. 4. Ribbon Metrics and Analysis The indicator calculates comprehensive ribbon metrics: Ribbon Width: Absolute distance between fastest and slowest MAs, providing a raw measure of trend strength. Ribbon Width Percent: Width expressed as a percentage of current price, normalizing across different price levels and instruments. Ribbon Strength: Percentile ranking of width percent over 50 bars, showing relative strength compared to recent history. Compression Detection: Identifies when ribbon width falls below its 20-period average, signaling potential energy buildup before breakouts. Expansion Rate: Measures the rate of change in ribbon width, identifying acceleration or deceleration in trend development. These metrics work together to provide a complete picture of trend dynamics, from initiation through maturation to exhaustion. 5. Twist Detection System The twist detection system identifies potential reversals by counting crossovers between adjacent ribbon layers. When multiple layers cross simultaneously (threshold: 50% of total layers), it signals a "twist" - a condition where the ribbon is reorganizing its structure, often preceding significant directional changes. The system tracks twist count cumulatively, allowing traders to identify instruments or timeframes experiencing frequent regime changes versus those in stable trends. High twist counts suggest choppy, range-bound conditions, while low twist counts indicate clean trending environments. 6. Trend Acceleration Detection Trend acceleration is measured using rate-of-change calculations on the middle ribbon layer: Trend Momentum: 5-period rate of change of the mid-ribbon MA Trend Acceleration: 3-period rate of change of trend momentum (second derivative) When acceleration exceeds one standard deviation of its 20-period history, the indicator flags accelerating conditions. This early warning system helps traders identify when trends are gaining steam versus when they're losing momentum, even if price continues in the same direction. 7. Multi-Timeframe Alignment The indicator requests ribbon trend data from three higher timeframes (default: 15m, 60m, 240m) and calculates an alignment score. The score ranges from -1 (all timeframes bearish) to +1 (all timeframes bullish), with values near zero indicating mixed or transitional conditions. MTF alignment above 0.75 or below -0.75 indicates strong multi-timeframe conviction, suggesting high-probability directional moves. This feature is particularly valuable for swing traders who need confirmation that their trade direction aligns with higher timeframe structure. Visual Elements Ribbon Lines: Up to 20 gradient-colored MA lines with transparency increasing from fast to slow, creating a visual "ribbon" effect Cloud Fill: Filled area between fastest and slowest MAs, colored based on trend direction and strength Signal Labels: Text-based labels for crossovers, twists, compression breakouts, and extreme conditions Background Heatmap: Optional gradient background showing ribbon strength intensity Compression Zones: Subtle background highlighting during ribbon compression periods MTF Alignment Background: Very subtle background when multi-timeframe alignment is strong Comprehensive Dashboard: Real-time metrics table showing trend, strength, width, compression status, acceleration, twist count, volatility, momentum, volume ratio, expansion rate, adaptive factor, and MTF alignment The dashboard displays 12 key metrics with color-coded values and status indicators, providing at-a-glance assessment of all ribbon dimensions simultaneously. Input Parameters Core Settings: Ribbon Count: Number of MA layers (3-20, default 12) Fast Length: Shortest MA period (2-50, default 5) Slow Length: Longest MA period (10-200, default 55) MA Type: EMA, SMA, WMA, VWMA, or HMA (default EMA) Adaptation Settings: Adapt to Volatility: Enable/disable ATR-based adaptation (default enabled) Adapt to Momentum: Enable/disable RSI-based adaptation (default enabled) Adapt to Volume: Enable/disable volume ratio adaptation (default enabled) Use Heikin Ashi: Calculate ribbon using HA candles instead of regular OHLC (default disabled) Display Options: Show Cloud: Toggle ribbon cloud fill (default enabled) Show Ribbon Lines: Toggle individual MA lines (default enabled) Show Signals: Toggle entry/exit signal labels (default enabled) Show Twists: Toggle twist reversal markers (default enabled) Show Compression: Toggle compression breakout signals (default enabled) Show Dashboard: Toggle metrics table (default enabled) Show Heatmap: Toggle strength-based background gradient (default enabled) Multi-Timeframe: Enable MTF: Toggle multi-timeframe analysis (default enabled) HTF 1/2/3: Three higher timeframe selections (default 15m, 60m, 240m) Colors: All colors are fully customizable including bull ribbon (neon cyan), bear ribbon (neon pink), twist (gold), compression (neon purple), and acceleration (neon green). How to Use This Indicator Step 1: Assess Ribbon Direction and Alignment Check the dashboard "Trend" field and observe ribbon color. Bullish ribbon (cyan) indicates uptrend, bearish ribbon (pink) indicates downtrend. Verify that price is aligned with ribbon direction - price above ribbon in uptrends, below in downtrends. Step 2: Evaluate Trend Strength Monitor the "Strength" metric in the dashboard. Values above 70 indicate strong trends with high conviction, 40-70 suggests moderate trends, below 40 indicates weak or developing trends. Strong trends typically offer better risk/reward for trend-following entries. Step 3: Watch for Compression Breakouts When the dashboard shows "Compression: YES" and "Width" is contracting, prepare for potential breakout. Compression breakout signals appear when ribbon expands after coiling, often marking the start of new trend legs. These setups offer excellent risk/reward as stops can be placed tight to the compression zone. Step 4: Identify Twist Reversals Twist signals (gold labels) indicate ribbon layers are crossing, suggesting potential trend exhaustion or reversal. High twist counts in the dashboard suggest choppy conditions where trend-following strategies may underperform. Use twists as warnings to tighten stops or reduce position size. Step 5: Confirm with Multi-Timeframe Alignment Check MTF alignment in the dashboard. "ALIGNED" status with high percentage (>75%) confirms that higher timeframes support your trade direction. "MIXED" status suggests caution as higher timeframes may be in conflict with current timeframe trend. Step 6: Monitor Acceleration Signals Acceleration labels (neon green) indicate trend momentum is increasing. These often appear early in new trend legs and can signal optimal entry timing. Lack of acceleration in mature trends may warn of impending exhaustion. Step 7: Use Volume Confirmation Check "Volume Ratio" in dashboard. Ratios above 1.5x confirm strong participation, while ratios below 0.8x suggest weak participation. Volume-confirmed signals (labeled "STRONG BUY/SELL") offer higher probability than signals on low volume. Best Practices Use on liquid instruments with consistent volume patterns for most reliable adaptation Combine with price action analysis - ribbon shows trend, price action shows entry timing In ranging markets, reduce ribbon count and increase fast/slow length spread to filter noise In trending markets, increase ribbon count for finer gradient visualization Pay attention to compression zones near key support/resistance levels for high-probability breakout setups Use MTF alignment as a filter - only take trades when alignment exceeds 75% in your direction Twist signals are most reliable when they occur at extreme ribbon strength levels (>70 or <30) Monitor adaptive factor in dashboard - values above 1.3 indicate high adaptation, below 0.9 indicate low adaptation Heikin Ashi mode reduces noise but adds lag - use for very choppy instruments only Acceleration signals work best in early trend phases, less reliable in mature trends Volume ratio below 0.5 suggests thin liquidity - avoid new positions during these periods Ribbon width expansion rate above 5% indicates strong trend acceleration Indicator Limitations Moving average-based systems inherently lag price action - ribbon confirms trends but doesn't predict them Adaptation mechanisms require sufficient historical data - may be less reliable on newly listed instruments MTF analysis requires data availability on all selected timeframes - some instruments may not support all timeframes Compression detection can produce false signals in extremely low volatility environments Twist detection sensitivity depends on ribbon count - too few layers may miss twists, too many may over-signal Volume adaptation assumes volume data is accurate and representative - some instruments have unreliable volume Heikin Ashi mode adds significant lag and should be used cautiously Adaptive multiplier can become extreme during unusual market conditions - monitor dashboard values The indicator shows what is happening, not why - fundamental catalysts can override technical ribbon signals Ribbon crossovers can whipsaw in ranging markets - use compression detection to filter range-bound periods Technical Implementation Built with Pine Script v6 using: Custom MA calculation function supporting five MA types with dynamic length parameters Multi-factor adaptive multiplier combining volatility, momentum, and volume dimensions Percentile-based strength calculations for normalized cross-instrument comparison Compression detection using rolling average width comparison Twist detection via adjacent layer crossover counting Multi-timeframe security requests with proper lookahead settings to prevent future data leakage Trend acceleration using rate-of-change and second derivative calculations Dynamic color gradients based on strength percentile ranking Comprehensive dashboard with 12 real-time metrics and color-coded status indicators Persistent label system to prevent label proliferation and maintain chart clarity The code is fully open-source and extensively commented for educational purposes and customization. Originality Statement This indicator is original in its comprehensive adaptive approach to ribbon analysis. While moving average ribbons are an established concept, this indicator is justified because: It introduces multi-factor adaptation (volatility + momentum + volume) not found in standard ribbon indicators The compression detection system provides statistical breakout anticipation beyond simple width measurement Twist detection quantifies ribbon reorganization to identify reversal conditions systematically Multi-timeframe alignment scoring provides conviction measurement across temporal dimensions Trend acceleration tracking using second derivatives offers early momentum shift detection The adaptive multiplier system creates a self-adjusting framework that works across all market regimes Integration of five MA types with Heikin Ashi option provides unprecedented flexibility The comprehensive dashboard synthesizes 12 distinct metrics into a unified intelligence panel Persistent label system prevents chart clutter while maintaining signal visibility Volume confirmation layer filters false signals during low-participation moves Each component contributes unique intelligence: adaptation ensures relevance across regimes, compression detects energy buildup, twists warn of reversals, MTF alignment validates conviction, acceleration identifies momentum shifts, and the dashboard synthesizes everything into actionable intelligence. The indicator's value lies in combining these complementary perspectives into a cohesive, adaptive trend-following 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. Moving average-based systems are lagging indicators that confirm trends rather than predict them. Strong ribbon signals do not guarantee profitable trades. Past ribbon performance does not guarantee future ribbon performance. 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. Ribbon alignment, compression breakouts, and twist signals 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
Indicador Pine Script®
por officialjackofalltrades
CVD IQ [TradingIQ]Hello Traders! 🔹 CVD IQ CVD IQ is a delta-driven analytical tool designed to reveal how aggressive buying and selling activity translates into price movement. Instead of relying purely on price, this indicator reconstructs order flow dynamics using lower timeframe data , allowing you to see: Where did the pressure come from… and how efficiently did it move price? It focuses on answering a deeper question: Was the move driven by real participation, or was it inefficient, absorbed, or divergent? aggressive buy vs sell activity (CVD) price vs delta divergences efficiency of price movement relative to flow cost of moving price (delta per tick) absorption and imbalance conditions multi-scale flow analysis (bar, day, swing) classic divergence detection (RSI style) 🔹 What the indicator shows 🔸 Cumulative Volume Delta (CVD) CVD is built using lower timeframe data to approximate aggressive buying and selling. This allows you to track: whether buyers or sellers are in control how much pressure is building over time when participation is increasing or fading 🔸 IMMEDIATE Divergence detection (Classic & Cost Models) The indicator detects when price and delta are out of sync . Classic divergence highlights: price making new highs while delta weakens price making new lows while delta strengthens potential exhaustion or reversal conditions Cost-based divergence goes further by evaluating: how much delta was required to move price whether moves are becoming more or less efficient hidden weakness in “expensive” price movement This shifts your perspective from: “price is moving” to: “how much effort did it take to move price?” 🔸 CVD Cost Per Tick (Efficiency Analysis) One of the most important features. The indicator measures: Delta per tick = how much aggressive volume was required to move price This allows you to identify: efficient moves (low cost → strong response) inefficient moves (high cost → weak response) potential exhaustion when cost rises sharply Each swing is classified into categories like: Very High Cost High Cost Normal Cost Low Cost Very Low Cost High cost often signals absorption or resistance from opposing liquidity . 🔸 Swing-based flow analysis The indicator breaks market structure into swings and evaluates: delta across each swing cost of movement between pivots relative efficiency vs previous swings This helps you understand: whether trends are strengthening or weakening if continuation is becoming harder when liquidity is likely opposing the move 🔸 Delta-Implied Close (Expected Price) The script estimates where price should have closed based on delta. This gives insight into: whether price overperformed or underperformed relative to flow hidden absorption when price fails to match delta inefficiencies between participation and result Important Note This model is adaptive and continuously updates based on changing market conditions. It is not a predictive engine, but rather a framework for interpreting how order flow is currently interacting with price. 🔸 Delta Analysis Table (Bar / Day / Swing) A live table provides a structured breakdown of flow and price response across three contexts: current bar current day current swing It includes: aggressive buy & sell volume buy/sell percentages net delta imbalance ratios price movement in ticks close position within range delta cost per tick cost classification absorption detection This allows you to quickly answer: Who is in control, and is price responding properly? 🔹 Table Overview Metric Name of the metric shown in each row. Bar Value calculated for the current bar only. Day Value accumulated from the start of the current day. Swing Value accumulated from the start of the current swing. 🔹 Flow Aggressive Buys Total buy-side market order volume. Higher values indicate stronger buying pressure. Aggressive Sells Total sell-side market order volume. Higher values indicate stronger selling pressure. Buy % Percentage of total aggressive volume coming from buyers. Higher values indicate buy-side dominance. Sell % Percentage of total aggressive volume coming from sellers. Higher values indicate sell-side dominance. Net Delta Aggressive buys minus aggressive sells. Positive values favor buyers, negative values favor sellers. Imbalance Ratio Relative dominance between buyers and sellers, expressed as a multiple. Higher values indicate stronger directional control. 🔹 Price Response Total Aggression Combined aggressive buy and sell volume. Represents total market participation. Bar Tick Move Price movement measured in ticks. Shows how far price moved over the period. Close Position Where price closed within its range. Higher values mean the close is nearer the high, lower values nearer the low. 🔹 Efficiency & Cost Delta Cost / Tick How much delta was required to move price by one tick. Higher values indicate less efficient movement and potential absorption. Cost Classification of how expensive the move is relative to recent conditions. High cost suggests resistance or absorption, low cost suggests efficient movement. Ticks per 1k Delta Number of ticks price moved per 1000 delta. Higher values indicate more efficient price movement. Price Move per 1k Delta Actual price movement per 1000 delta. Higher values indicate stronger price response to order flow. 🔹 Delta-Based Expectations Delta-Implied Close The price level where the bar would be expected to close based on the underlying delta. Move Ratio Actual price movement relative to the delta-implied move. 1.0 = expected response 1.0 = stronger than expected <1.0 = weaker than expected 🔹 How to read it Each component provides a different layer: CVD → who is active Divergence → when price and flow disagree Cost → how efficient the move is Table → structured confirmation across contexts Together, this shifts your thinking from: “price moved up” to: “buyers were aggressive - but did price actually respond?” 🔹 Example interpretations strong delta + efficient move → clean continuation strong delta + weak move → absorption rising cost over time → trend weakening divergence signals → potential reversal or trap low cost + expansion → strong directional move 🔹 Why this indicator is useful It gives you: participation behind price context for whether moves are efficient early detection of exhaustion or absorption a way to quantify “effort vs result” multi-timeframe flow insight (bar, day, swing) 🔹 Best use cases confirming trend strength identifying weak breakouts spotting absorption at key levels analyzing liquidity interaction enhancing price action or liquidity-based models 🔹 Important note This script uses lower timeframe data to approximate aggressive volume. This means: accuracy depends on data availability different symbols may behave differently lower timeframe selection impacts results 🔹 Inputs you can customize lower timeframe for CVD calculation divergence models (Classic / Cost / Both) divergence sensitivity (small, medium, large swings) cost structure length and thresholds visual styling and colors delta analysis table size Closing Notes CVD IQ is built to show the relationship between participation and outcome . As always, thank you TradingView!
Indicador Pine Script®
por Trading-IQ
29
Meridian Zones [JOAT]Meridian Zones Introduction Meridian Zones is an advanced open-source session analysis engine built for traders who structure their trading around the Asia, London, and New York sessions. Unlike typical session indicators that clutter the chart with dozens of lines and levels, Meridian Zones takes a deliberately clean approach: session boxes, killzone backgrounds, session-colored candles, and precise liquidity sweep labels live on the chart, while all analytical depth lives in a fully-populated 15-row dashboard. The result is a chart that remains readable at any zoom level while giving you institutional-grade session intelligence at a glance. The indicator tracks session ranges, calculates session VWAP, monitors volume distribution across sessions, detects liquidity sweeps with wick filtering and cooldown logic, flags volume spikes, grades institutional candles, and reports previous day high/low positioning — all without drawing a single horizontal line on the chart. Why This Indicator Exists Session-based trading is a cornerstone of institutional methodology. The Asia session establishes a range, London often breaks that range with directional intent, and New York either continues or reverses the London move. Understanding which session is dominant, where sweeps occur, and how volume distributes across sessions gives traders a significant edge. Most session indicators fall into two traps: either they are too simple (just drawing boxes) or too cluttered (drawing session highs, lows, midpoints, opens, VWAP lines, and previous session levels all on the chart simultaneously). Meridian Zones avoids both by: Drawing only the essential visual elements on the chart — session range boxes, killzone background shading, and labeled signals Moving all analytical data into a comprehensive dashboard where it can be read without visual noise Adding features that most session indicators lack entirely: session VWAP calculation, volume-weighted session dominance, institutional candle detection within sessions, and precise liquidity sweep identification with ATR-based wick filtering Core Session Engine Sessions are defined by UTC hour ranges (all configurable): Asia: 00:00 - 08:00 UTC (default) London: 08:00 - 16:00 UTC (default) New York: 13:00 - 21:00 UTC (default) The indicator detects session opens and closes, tracks high/low/volume/VWAP within each session, and draws range boxes when sessions close. A timeframe filter ensures the indicator only displays on charts where session analysis is meaningful (up to 4H by default). Session overlap (London + NY) is automatically detected and reported in the dashboard, as overlap periods often produce the highest-volume, most directional moves of the day. Session Tracking and Analytics For each session, the indicator calculates and tracks: Session Range: High and low of the session, displayed as a colored box Session VWAP: Volume-weighted average price calculated from session open, updated every bar. This is the true institutional fair value for the session — not a simple midpoint Session Momentum: The ratio of bullish candles to total candles within the session, giving a quick read on directional bias Session Volume: Total volume accumulated during the session, used for dominance and volume leader calculations Session Open/Close Prices: Used to determine session bias (bullish if close > open, bearish if close < open) Liquidity Sweep Detection One of the most valuable features is the precise liquidity sweep detector. A sweep occurs when price wicks beyond a session high or low and closes back inside — this is institutional stop hunting. The sweep detector uses two filters to avoid false signals: ATR Wick Filter: The wick beyond the session level must exceed a configurable ATR multiple (default 0.4x ATR). This eliminates tiny wicks that barely touch the level. Cooldown Timer: After a sweep is detected, no new sweep can fire for a configurable number of bars (default 8). This prevents multiple labels from stacking on the same sweep event. Sweep labels are color-coded: bullish sweeps (wicking below and closing above) in teal, bearish sweeps (wicking above and closing below) in rose. Volume Spike Detection When volume exceeds the session's average volume by a configurable multiplier (default 2.0x), a volume spike flag appears. Volume spikes during sessions often coincide with institutional order execution and can confirm the validity of a sweep or directional move. Institutional Candle Labels Candles with a body-to-range ratio exceeding the threshold (default 75%) are flagged as institutional candles. These are large-bodied, low-wick candles that indicate strong directional conviction — the kind of candles that institutions create when executing large orders. Session-Colored Candles When enabled, candles are tinted by the active session: gold for Asia, blue for London, rose for New York. This provides an instant visual reference for which session produced each candle, making it easy to see session transitions and overlap periods on the chart. 15-Row Dashboard The dashboard is the analytical heart of the indicator. Every cell is populated — no empty rows. It displays: Row 1: Active Session — Which session is currently active, or "OFF" between sessions Row 2: Overlap Status — Whether London and NY are overlapping Row 3-5: Session Ranges — Asia, London, and NY ranges in price with pip/point size Row 6-8: Session Bias — Bullish/Bearish for each session based on open vs close Row 9: Dominance — Which session has the largest range (the "dominant" session) Row 10: Volume Leader — Which session has the highest total volume Row 11: VWAP Position — Whether current price is above or below the active session's VWAP Row 12: Range/ATR — Current session range as a multiple of ATR (shows how extended the session is) Row 13: PDH/PDL — Previous Day High and Low with current price position relative to them Row 14: Candle Quality — Current candle's body ratio and institutional grade Row 15: Sweep Radar — Most recent sweep direction and how many bars ago it occurred Input Parameters Session Definitions (UTC): Asia Start/End Hour (default 0/8) London Start/End Hour (default 8/16) NY Start/End Hour (default 13/21) Features: Show Session Boxes, Killzone Background, Session-Colored Candles, Session Open Markers Show Liquidity Sweeps, Volume Spike Markers, Institutional Candle Labels, Dashboard Sessions to Keep (default 3) — how many past session boxes remain on chart Sweep Min Wick ATR multiplier (default 0.4), Sweep Cooldown bars (default 8) Volume Spike Multiplier (default 2.0), Institutional Candle Body % (default 75%) Timeframe Filter: Show Up To (default 4H) — prevents the indicator from displaying on higher timeframes where session analysis is not meaningful How to Use This Indicator Step 1: Identify the Dominant Session Check the dashboard for which session has the largest range and highest volume. The dominant session sets the directional tone for the day. Step 2: Watch for Asia Range Breaks London often breaks the Asia range. When London's first move sweeps the Asia high or low, the sweep label confirms the liquidity grab. The direction of the break often sets the trend for the day. Step 3: Monitor Overlap Period The London-NY overlap (typically 13:00-16:00 UTC) produces the highest volume and most decisive moves. Volume spikes during overlap are particularly significant. Step 4: Use VWAP Position for Bias If price is above the session VWAP, institutional flow is net bullish for that session. Below VWAP, net bearish. The dashboard shows this in real-time. Step 5: Confirm with Institutional Candles When a sweep occurs and is followed by an institutional candle (large body, high volume), the move has strong institutional backing. Step 6: Reference PDH/PDL Previous Day High and Low are key institutional levels. The dashboard shows whether price is above PDH (bullish), below PDL (bearish), or between them (range-bound). Limitations Session analysis is most relevant on intraday timeframes (1m to 4H). The timeframe filter prevents display on higher timeframes, but users should understand that session dynamics are inherently intraday concepts. UTC-based session times may need adjustment for instruments that trade in different time zones or have non-standard trading hours. Volume data quality varies by instrument. Forex volume on TradingView is tick volume, which approximates but does not equal true institutional volume. Session VWAP resets at each session open. It is not a continuous daily VWAP. Sweep detection relies on wick analysis, which can produce false signals in extremely volatile or illiquid conditions. The indicator shows session dynamics, not price predictions. A bullish session bias does not guarantee price will continue higher. Originality Statement This indicator is original in its clean-chart, dashboard-heavy approach to session analysis. While session boxes and killzone backgrounds exist in other indicators, this indicator is justified because: It deliberately separates visual elements (chart) from analytical data (dashboard), solving the clutter problem that plagues most session indicators Session VWAP calculation per session provides institutional fair value that simple midpoint calculations cannot match The liquidity sweep detector uses dual filtering (ATR wick threshold + cooldown timer) for precision that basic "price crossed level" detection lacks Volume-weighted session dominance and volume leader tracking provide insights into which session is driving the market — information not available in standard session indicators Institutional candle grading within sessions identifies the specific candles where large orders were executed The 15-row dashboard presents all session analytics simultaneously with zero empty cells, creating a true session command center The combination of session boxes, sweep detection, volume spikes, institutional candle grading, and comprehensive analytics in a single clean-chart indicator is not available in existing public scripts 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. Session analysis reveals historical patterns in how different trading sessions behave. Past session patterns do not guarantee future session behavior. Market conditions, news events, and institutional positioning can cause sessions to behave atypically at any time. Always use proper risk management. Never risk more than you can afford to lose. The author is not responsible for any losses incurred from using this indicator. -Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
Vortex Liquidation Reaper [JOAT]Vortex Liquidation Reaper Introduction The Vortex Liquidation Reaper is an advanced open-source liquidity detection system that identifies institutional liquidity sweeps, equal highs/lows, volume imbalances, and cascade events. This indicator reveals where retail stop losses cluster and how institutions hunt that liquidity to fill their orders, providing traders with a systematic approach to understanding market manipulation and liquidity engineering. Unlike basic support/resistance indicators, the Vortex Liquidation Reaper provides institutional-grade liquidity analysis through pivot detection, equal level identification, volume profiling, sweep tracking, and cascade detection. The indicator is designed for traders who understand that institutions move markets by systematically hunting liquidity pools where retail traders place their stops. Why This Indicator Exists This indicator addresses the critical need for liquidity analysis in modern trading. By combining liquidity level detection with volume profiling and sweep tracking, it reveals: Buy Side Liquidity (BSL): Pivot highs where long stop losses cluster above current price Sell Side Liquidity (SSL): Pivot lows where short stop losses cluster below current price Equal Highs/Lows: Multiple pivots at similar levels indicating concentrated liquidity Liquidity Sweeps: When price moves through liquidity levels to trigger stops Volume Confirmation: Volume surge detection confirms institutional participation Cascade Events: Multiple sweeps with high volume indicating forced liquidations Liquidity Voids: Gaps between liquidity levels where price may move quickly Core Components Explained 1. Liquidity Level Detection Liquidity levels are identified at pivot highs and lows using swing analysis: Pivot Detection: Uses left and right bars (default 10) to identify swing points Buy Side Liquidity: Pivot highs represent areas where long traders place stops above Sell Side Liquidity: Pivot lows represent areas where short traders place stops below Volume Tracking: Each liquidity level stores the volume at the pivot formation The indicator maintains arrays of active liquidity levels, tracking up to the maximum specified (default 5 BSL and 5 SSL levels). 2. Equal Level Detection Equal highs and lows are identified by comparing new pivots with existing liquidity levels: Threshold Calculation: Two levels are considered equal if within threshold percentage (default 0.3%) Equal Highs (EQH): Multiple pivot highs at similar prices indicate strong resistance and concentrated liquidity Equal Lows (EQL): Multiple pivot lows at similar prices indicate strong support and concentrated liquidity Visual Distinction: Equal levels are displayed in gold color to highlight their importance Equal levels are particularly significant because they represent areas where multiple waves of traders have placed stops, creating dense liquidity pools that institutions target. 3. Volume Profiling The indicator analyzes volume at each liquidity level and compares it to average volume: Average Volume: Calculated over lookback period (default 45 bars) Volume Surge: Detected when current volume exceeds average by multiplier (default 2.25x) Volume Percentage: Shows how much above/below average the pivot volume was Volume Labels: Display actual volume and percentage on liquidity level labels High volume at pivot formation suggests institutional interest. Volume surges during sweeps confirm institutional participation in the liquidity hunt. 4. Liquidity Sweep Detection Sweeps occur when price moves through a liquidity level, triggering stops: Wick Mitigation: Sweep confirmed when wick touches the level Close Mitigation: Sweep confirmed when close passes through the level Sweep Tracking: Swept levels are marked with dotted lines and "SWEPT" labels Reversal Potential: Sweeps often precede reversals as institutions fill orders The indicator tracks which levels have been swept and can optionally hide mitigated levels to keep charts clean. 5. Cascade Detection Cascades occur when multiple liquidity sweeps happen in quick succession with high volume: Cascade Counter: Tracks how many times a level has been swept Volume Confirmation: Requires volume surge for cascade classification Cascade Threshold: Two or more sweeps with volume surges trigger cascade status Visual Indication: Cascade zones displayed in magenta with "CASCADE" labels Cascades indicate forced liquidations where stop losses trigger more stop losses, creating chain reactions that institutions exploit. 6. Liquidity Void Detection The indicator identifies gaps between liquidity levels where price may move quickly: Void Calculation: Measures distance between nearest BSL and SSL Void Threshold: Gaps exceeding 2% of price are classified as liquidity voids Visual Display: Voids shown as magenta boxes with percentage labels Trading Implication: Price often moves quickly through voids due to lack of liquidity Liquidity voids represent areas where few stops exist, allowing price to move rapidly with minimal resistance. 7. Liquidity Strength Levels The indicator identifies the strongest liquidity concentrations: Highest BSL: The highest buy side liquidity level represents strongest overhead resistance Lowest SSL: The lowest sell side liquidity level represents strongest support Strength Lines: Dashed lines extend from these levels showing key liquidity zones Labels: "STRONG BSL" and "STRONG SSL" labels mark these critical levels Strong liquidity levels are prime targets for institutional liquidity hunts. 8. Volume Imbalance Detection The indicator tracks extreme volume spikes that indicate institutional activity: Imbalance Calculation: Current volume compared to average volume Spike Threshold: Imbalances exceeding 100% (2x average) are flagged Visual Labels: "VOL SPIKE" labels show percentage above average Institutional Footprint: Extreme volume often accompanies institutional order flow Volume imbalances at liquidity levels confirm institutional participation in the sweep. Visual Elements Liquidity Level Boxes: Colored boxes extending from pivot time showing BSL (green), SSL (red), EQH/EQL (gold), and cascades (magenta) Liquidity Lines: Horizontal lines at each level with thickness indicating importance (equal levels = thicker) Projection Lines: Dashed extensions showing where liquidity levels project into the future Volume Labels: Display volume amount and percentage above/below average Sweep Indicators: Small "SWEEP" labels mark when levels are taken out Cascade Labels: "CASCADE" text on levels that have been swept multiple times Void Boxes: Magenta boxes showing liquidity voids with percentage labels Strength Lines: Dashed lines marking strongest BSL and SSL levels Information Dashboard: Displays active BSL/SSL count, equal highs/lows, cascades, volume status, swept counts, and trading bias How to Use This Indicator Step 1: Identify Active Liquidity Levels Check the dashboard for active BSL and SSL counts. More levels indicate more potential targets for institutional sweeps. Step 2: Look for Equal Highs/Lows Equal levels (gold color) represent concentrated liquidity. These are prime targets for institutional liquidity hunts. Step 3: Monitor Volume at Levels High volume at pivot formation suggests institutional interest. Volume surges during sweeps confirm institutional participation. Step 4: Watch for Liquidity Sweeps When price sweeps a level (especially equal levels), watch for reversal. Institutions often reverse price after filling orders. Step 5: Identify Cascade Events Cascades (multiple sweeps with volume) indicate forced liquidations. These often mark exhaustion points and reversals. Step 6: Check for Liquidity Voids Large gaps between BSL and SSL indicate voids where price may move quickly. Avoid entering in voids. Step 7: Use Trading Bias Dashboard shows bias based on liquidity balance. More active BSL = long bias, more active SSL = short bias. Best Practices Wait for liquidity sweeps before entering - don't front-run the sweep Equal highs/lows are highest probability sweep targets Volume confirmation is critical - sweeps without volume may fail Cascades often mark exhaustion - look for reversals after cascades Avoid trading in liquidity voids - wait for price to reach liquidity Use higher timeframe liquidity levels for stronger significance Combine with order blocks and FVGs for highest probability setups Be patient - institutions may sweep multiple levels before reversing Input Parameters Liquidity Detection: Pivot Length: Swing detection period (default: 10) Equal Level Threshold: Percentage for equal level detection (default: 0.3%) Max Buy Side Levels: Maximum BSL to display (default: 5) Max Sell Side Levels: Maximum SSL to display (default: 5) Volume Profiling: Volume Surge Multiplier: Threshold for volume surges (default: 2.25x) Volume Lookback: Period for average volume (default: 45) Show Volume Profile: Toggle volume display (default: enabled) Mitigation Rules: Mitigation Method: Wick or Close (default: Wick) Show Mitigated Levels: Toggle swept level display (default: disabled) Cascade Detection: Enable cascade tracking (default: enabled) Visual Configuration: Buy/Sell Liquidity Colors: Customizable BSL and SSL colors Equal Level Color: Color for EQH/EQL (default: gold) Cascade Color: Color for cascade zones (default: magenta) Box Width: Width of liquidity boxes (default: -5.0) Extension Length: How far to extend levels (default: 20) Show Projections: Toggle projection lines (default: enabled) Show Sweep Signals: Toggle sweep labels (default: enabled) Originality Statement This indicator is original in its comprehensive liquidity analysis approach. While liquidity concepts are established trading principles, this indicator is justified because: It combines liquidity detection with equal level identification and volume profiling The cascade detection system identifies forced liquidation events Liquidity void detection reveals areas where price may move quickly Volume imbalance tracking confirms institutional participation Liquidity strength levels identify the most significant zones The comprehensive dashboard presents all liquidity metrics simultaneously Integration of multiple liquidity concepts creates a complete liquidity analysis system Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Liquidity analysis does not guarantee profitable trades. Liquidity sweeps do not guarantee reversals. Always use proper risk management and never risk more than you can afford to lose. -Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
Nexus Structure Detector [JOAT]Nexus Structure Detector Introduction The Nexus Structure Detector is an advanced open-source Smart Money Concepts (SMC) indicator that identifies institutional order flow through Order Blocks, Fair Value Gaps, Liquidity Levels, and Market Structure analysis. This indicator combines multiple SMC methodologies into a unified system that reveals where institutions are positioning their orders and how they manipulate price to fill those orders. Unlike basic support/resistance indicators, the Nexus Structure Detector provides institutional-grade structure analysis through order block detection, FVG identification, liquidity sweep tracking, and premium/discount zone mapping. The indicator is designed for traders who understand that institutions move markets through systematic order placement and liquidity manipulation. Why This Indicator Exists This indicator addresses the need for systematic SMC analysis on TradingView. By combining order blocks, fair value gaps, liquidity levels, and market structure into one tool, it reveals: Order Blocks: The last candle before a strong move where institutions placed orders Fair Value Gaps: Imbalances in price where institutions will likely return to fill orders Liquidity Levels: Pivot highs/lows where retail stops cluster and institutions hunt liquidity Market Structure: Break of Structure (BOS) and Change of Character (CHOCH) detection Premium/Discount Zones: Price positioning relative to range equilibrium Mitigation Tracking: Monitors when order blocks and FVGs are filled Core Components Explained 1. Order Block Detection Order blocks are identified by finding the candle with the most extreme price before a strong directional move. The indicator uses pivot detection to identify swing points, then traces back to find the order block candle: Bullish Order Block: Forms when price breaks above a pivot low - the candle with the lowest low before the breakout becomes the bullish OB Bearish Order Block: Forms when price breaks below a pivot high - the candle with the highest high before the breakdown becomes the bearish OB Order blocks are drawn as boxes extending into the future. When price returns to an order block, institutions are likely to defend that zone. Mitigation occurs when price closes through the order block (wick or close mitigation options available). 2. Fair Value Gap (FVG) Detection FVGs are three-candle patterns where there's a gap between candle 1's high/low and candle 3's low/high: Bullish FVG: Current low > high from 2 bars ago (gap up) Bearish FVG: Current high < low from 2 bars ago (gap down) FVGs represent imbalances where price moved too quickly, leaving unfilled orders. Institutions often return to these zones to fill orders. The indicator tracks FVG mitigation using touch, wick, close, or average methods. 3. Liquidity Level Tracking Liquidity levels are identified at pivot highs (Buy Side Liquidity - BSL) and pivot lows (Sell Side Liquidity - SSL). These represent areas where retail traders place stop losses: Buy Side Liquidity (BSL): Above pivot highs where long stop losses cluster Sell Side Liquidity (SSL): Below pivot lows where short stop losses cluster Institutions often push price through these levels to trigger stops and fill their orders. The indicator tracks when liquidity is swept (price moves through the level) and displays swept levels with dotted lines. 4. Market Structure Analysis The indicator tracks market structure by monitoring higher highs/lows and lower highs/lows: Bullish Structure: Price making higher highs and higher lows Bearish Structure: Price making lower highs and lower lows Break of Structure (BOS): When structure continues in the same direction Change of Character (CHOCH): When structure shifts direction Market structure helps identify the current trend and potential reversal points. The indicator combines structure with order blocks and liquidity to identify high-probability setups. 5. Premium/Discount Zones The indicator calculates the range between the highest high and lowest low over a lookback period (default 50 bars), then divides it into zones: Premium Zone: Above 50% of the range (75-100%) - ideal for shorts Equilibrium: At 50% of the range - neutral zone Discount Zone: Below 50% of the range (0-25%) - ideal for longs Institutions typically buy in discount zones and sell in premium zones. The indicator displays these zones with dotted lines and tracks current price position. Visual Elements Order Block Boxes: Solid boxes showing bullish (green) and bearish (red) order blocks with volume labels Fair Value Gap Boxes: Dashed boxes showing bullish (cyan) and bearish (orange) FVGs Liquidity Lines: Horizontal lines at pivot highs (BSL - green) and pivot lows (SSL - red) Premium/Discount Lines: Dotted lines showing range extremes, 75%, equilibrium, and 25% levels Mitigation Indicators: Faded boxes and dotted lines show mitigated zones Information Dashboard: Displays market structure, active OBs/FVGs, liquidity levels, price position, and trading bias How to Use This Indicator Step 1: Identify Market Structure Check the dashboard for current market structure (Bullish/Bearish/Neutral). Trade in the direction of structure for highest probability. Step 2: Locate Order Blocks Look for unmitigated order blocks in the direction of structure. Bullish OBs in discount zones and bearish OBs in premium zones offer best setups. Step 3: Monitor Fair Value Gaps FVGs often get filled before price continues. Use FVGs as entry zones when they align with order blocks and structure. Step 4: Watch for Liquidity Sweeps When price sweeps liquidity (BSL or SSL), it often reverses. Look for liquidity sweeps near order blocks for high-probability reversals. Step 5: Check Price Position Use premium/discount zones to determine if price is at an extreme. Buy in discount, sell in premium, avoid equilibrium. Step 6: Combine Elements for Confluence Best setups occur when multiple elements align: structure + order block + FVG + liquidity sweep + premium/discount zone. Best Practices Trade with market structure, not against it Wait for price to return to order blocks before entering Use liquidity sweeps as confirmation, not standalone signals Combine order blocks with FVGs for highest probability entries Avoid trading in equilibrium zones - wait for premium or discount Monitor mitigation - once an OB or FVG is mitigated, it's no longer valid Use higher timeframe structure to confirm lower timeframe setups Be patient - wait for all elements to align before entering Input Parameters Structure Detection: Swing Length: Pivot detection period (default: 10) Max Order Blocks: Maximum OBs to display (default: 3) Max Fair Value Gaps: Maximum FVGs to display (default: 3) Max Liquidity Levels: Maximum liquidity lines (default: 3) Mitigation Rules: OB Mitigation: Wick or Close (default: Close) FVG Mitigation: Touch, Wick, Close, or Average (default: Close) Show Mitigated Zones: Toggle mitigated zone display (default: disabled) Premium/Discount Zones: Show PD Zones: Toggle zone display (default: enabled) Lookback Period: Range calculation period (default: 50) Visual Configuration: Bullish/Bearish OB Colors: Customizable order block colors Bullish/Bearish FVG Colors: Customizable FVG colors Buy/Sell Liquidity Colors: Customizable liquidity line colors Show Labels: Toggle zone labels (default: enabled) Show Volume: Toggle volume display on OBs (default: enabled) Show Dashboard: Toggle information table (default: enabled) Originality Statement This indicator is original in its comprehensive SMC integration. While individual concepts (order blocks, FVGs, liquidity) are established SMC principles, this indicator is justified because: It combines four distinct SMC methodologies into a unified detection system The automatic order block detection uses swing analysis to identify the exact candle FVG tracking with multiple mitigation methods provides flexibility Liquidity sweep detection with volume confirmation adds institutional context Premium/discount zone integration provides price positioning context Market structure tracking with BOS/CHOCH detection guides directional bias The comprehensive dashboard presents all SMC elements simultaneously Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Smart Money Concepts are analytical tools, not guarantees of future price movement. Order blocks, FVGs, and liquidity levels do not guarantee profitable trades. Always use proper risk management and never risk more than you can afford to lose. -Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
7
Quantum Flux Oscillator [JOAT]Quantum Flux Oscillator Introduction The Quantum Flux Oscillator is an advanced open-source momentum detection system that synthesizes six distinct analytical methodologies into a unified institutional-grade oscillator. This indicator combines Volume Flux Indicator (VFI), Laguerre RSI, Fisher Transform, True Strength Index (TSI), Money Flow Index (MFI), and On-Balance Volume (OBV) with Accumulation/Distribution analysis to create a comprehensive momentum engine that reveals institutional positioning and market regime shifts. Unlike traditional single-dimension oscillators, the Quantum Flux Oscillator provides multi-layered momentum intelligence through weighted composite calculations, regime classification, velocity tracking, and divergence detection. The indicator is designed for traders who understand that momentum precedes price and that institutional footprints can be detected through systematic multi-indicator confluence. Why This Indicator Exists This indicator addresses a critical gap in momentum analysis: the ability to detect institutional momentum shifts before they become obvious to retail traders. By combining multiple momentum methodologies with volume-weighted analysis, this indicator reveals: Volume Flux Intelligence: Detects unusual volume-price relationships that signal institutional activity Laguerre RSI: Zero-centered adaptive RSI that responds faster to price changes while filtering noise Fisher Transform: Converts momentum into a Gaussian normal distribution for clearer extreme identification True Strength Index: Double-smoothed momentum that separates genuine trends from noise Money Flow Analysis: Tracks buying and selling pressure through volume-weighted price movements Volume Confirmation: Integrates OBV and A/D Line to confirm momentum with volume flow Regime Classification: Categorizes market conditions as Extreme Bull, Bullish, Neutral, Bearish, or Extreme Bear Multi-Timeframe Alignment: Confirms momentum across higher timeframes for conviction measurement Each component provides a different perspective on momentum. VFI shows volume-driven momentum, Laguerre RSI shows adaptive momentum, Fisher Transform shows statistical extremes, TSI shows smoothed directional momentum, MFI shows money flow momentum, and OBV/A/D show cumulative volume momentum. Together, they create a comprehensive view of institutional momentum positioning. Core Components Explained 1. Volume Flux Indicator (VFI) VFI measures the relationship between price movement and volume to identify institutional accumulation or distribution. The calculation uses logarithmic price changes and volume cutoffs to filter significant moves: The indicator classifies volume-price relationships by comparing actual volume against average volume with a cutoff threshold. When price moves significantly with volume above the cutoff, it signals institutional participation. VFI is scaled and smoothed to create a momentum baseline that responds to volume-confirmed price movements. 2. Laguerre RSI (Zero-Centered) Laguerre RSI applies a four-stage Laguerre filter to price data, creating an adaptive RSI that responds faster to recent price changes while maintaining smoothness. The zero-centered output ranges from -50 to +50, making it easier to identify bullish and bearish momentum: The Laguerre filter uses a gamma parameter (default 0.4) to control responsiveness. Lower gamma values create faster response, while higher values create smoother output. The zero-centered format allows direct comparison with other momentum components. 3. Fisher Transform The Fisher Transform converts the composite momentum into a Gaussian normal distribution, making extreme values more identifiable. This transformation compresses the middle range and expands the tails, creating clearer overbought and oversold signals: The Fisher Transform output oscillates around zero with extreme values typically beyond +2 and -2. These extremes often precede reversals as momentum reaches unsustainable levels. 4. True Strength Index (TSI) TSI applies double exponential smoothing to price momentum, creating a smooth oscillator that filters out short-term noise while preserving trend direction. The calculation uses two EMA periods (default 25 and 13) to separate signal from noise: TSI values above zero indicate bullish momentum, while values below zero indicate bearish momentum. The double smoothing reduces whipsaws while maintaining responsiveness to genuine momentum shifts. 5. Money Flow Index (MFI) MFI is a volume-weighted RSI that measures buying and selling pressure. It calculates the ratio of positive money flow (volume on up days) to negative money flow (volume on down days): MFI values above 80 indicate overbought conditions with high volume, while values below 20 indicate oversold conditions with high volume. The indicator normalizes MFI to a zero-centered scale for integration with other components. 6. On-Balance Volume (OBV) and Accumulation/Distribution (A/D) OBV and A/D track cumulative volume flow to confirm momentum direction. OBV adds volume on up days and subtracts on down days, while A/D weights volume by the close's position within the day's range: Both indicators are normalized to a 0-100 scale and then zero-centered for composite integration. Rising OBV/A/D with rising momentum confirms institutional accumulation, while falling OBV/A/D with rising price warns of distribution. Quantum Flux Core Calculation The Quantum Flux Core combines all components using weighted averaging: Quantum Flux = (VFI × 0.20) + (Laguerre RSI × 0.20) + (Fisher × 0.15) + (TSI × 0.15) + (MFI × 0.10) + (OBV × 0.10) + (A/D × 0.05) + (CMF × 0.05) This weighted approach emphasizes volume-driven components (VFI, Laguerre) while incorporating smoothed momentum (Fisher, TSI) and volume confirmation (MFI, OBV, A/D, CMF). The result is smoothed with an EMA to create the final Quantum Flux line. Regime Classification System The indicator classifies market conditions into five regimes based on Quantum Flux levels: Extreme Bull (QF > 35): Institutional buying pressure at extreme levels, potential exhaustion Bullish (QF > 25): Strong bullish momentum with institutional participation Neutral (-25 < QF < 25): Balanced conditions, no clear institutional bias Bearish (QF < -25): Strong bearish momentum with institutional selling Extreme Bear (QF < -35): Institutional selling pressure at extreme levels, potential capitulation Regime shifts often precede significant price moves as institutional positioning changes. The indicator tracks regime changes and generates signals when momentum confirms directional bias. Multi-Timeframe Alignment The indicator requests Quantum Flux data from three customizable higher timeframes (default: 5m, 15m, 60m) and calculates alignment: Strong Aligned (3/3): All timeframes show bullish/bearish momentum - high conviction Aligned (2/3): Majority timeframes confirm - moderate conviction Weak (1/3): Only one timeframe confirms - low conviction No Alignment (0/3): No timeframe confirmation - conflicting signals Strong alignment across multiple timeframes indicates institutional participation at scale, as large orders are often split across timeframes to minimize market impact. Velocity and Acceleration Tracking The indicator calculates momentum velocity (rate of change) and acceleration (change in velocity): Velocity: Current Quantum Flux minus previous bar's value Acceleration: Current velocity minus previous velocity (second derivative) Accelerating momentum often precedes breakouts as institutional orders hit the market. Decelerating momentum warns of potential reversals or consolidation. Visual Elements Quantum Flux Line: Main oscillator with regime-based color coding (cyan = extreme bull, aqua = bullish, yellow = neutral, red = bearish, magenta = extreme bear) Threshold Lines: Horizontal lines at +35 (extreme overbought), +25 (overbought), 0 (zero line), -25 (oversold), -35 (extreme oversold) Velocity Histogram: Shows momentum velocity with color-coded bars (green = rising, red = falling) Acceleration Columns: Displays momentum acceleration to identify momentum shifts early Regime Strength Bars: Visual regime indicator showing current market condition strength Gradient Glow Effect: Multiple layered fills create a glowing effect that emphasizes momentum intensity Information Dashboard: Comprehensive table displaying all metrics in real-time with color-coded cells The dashboard displays 10 key metrics: Regime, Flux Value, HTF Confirmation, MFI, CMF, Velocity, Divergence, Volume, and Signal status. Signal Generation The indicator generates two types of signals: Primary Reversal Signals: Bullish Reversal: Quantum Flux in extreme oversold (< -35), rising momentum, positive velocity acceleration, and HTF confirmation Bearish Reversal: Quantum Flux in extreme overbought (> 35), falling momentum, negative velocity acceleration, and HTF confirmation Momentum Crossover Signals: Bullish Momentum: Quantum Flux crosses above -25 (oversold threshold) with positive velocity and volume confirmation Bearish Momentum: Quantum Flux crosses below +25 (overbought threshold) with negative velocity and volume confirmation Signals include anti-overlap logic to prevent signal clustering and ensure clean chart presentation. Divergence Detection The indicator detects both regular and hidden divergences between price and Quantum Flux: Regular Bullish Divergence: Price makes lower low, Quantum Flux makes higher low (potential reversal up) Regular Bearish Divergence: Price makes higher high, Quantum Flux makes lower high (potential reversal down) Hidden Bullish Divergence: Price makes higher low, Quantum Flux makes lower low (trend continuation up) Hidden Bearish Divergence: Price makes lower high, Quantum Flux makes higher high (trend continuation down) Divergences are drawn with clean lines (solid for regular, dashed for hidden) without text clutter. How to Use This Indicator Step 1: Monitor Regime Classification Watch for regime shifts between Extreme Bear, Bearish, Neutral, Bullish, and Extreme Bull. Regime changes often precede significant price moves. Step 2: Check Multi-Timeframe Alignment Strong alignment (3/3) across timeframes confirms institutional conviction. Weak or no alignment suggests retail-driven moves that may lack follow-through. Step 3: Analyze Velocity and Acceleration Accelerating momentum (positive acceleration) often precedes breakouts. Decelerating momentum (negative acceleration) warns of potential reversals. Step 4: Look for Divergences Regular divergences at extreme levels (QF > 35 or < -35) often signal reversals. Hidden divergences confirm trend continuation. Step 5: Confirm with Volume Metrics Check MFI, CMF, OBV, and A/D for confirmation. Rising volume metrics with rising Quantum Flux confirms institutional accumulation. Step 6: Wait for Signal Confirmation Primary reversal signals at extreme levels with HTF confirmation provide highest probability setups. Momentum crossover signals work best in trending markets. Best Practices Use on liquid instruments (major forex pairs, large-cap stocks, major crypto) for most reliable signals Combine with price action analysis - momentum shows intent, price shows result Pay attention to extreme levels (QF > 35 or < -35) as these often precede reversals MTF alignment is most reliable in trending markets, less reliable in choppy conditions Extreme momentum can persist longer than expected during strong trends - use stops Look for momentum divergences at key support/resistance levels for highest probability setups Monitor velocity and acceleration for early warning signs of momentum shifts Use the dashboard to quickly assess overall market condition and signal status Indicator Limitations Momentum analysis works best on liquid instruments with consistent volume patterns Low-volume instruments or off-market hours can produce unreliable readings MTF alignment requires sufficient data on all timeframes - may not work on newly listed instruments Momentum precedes price but doesn't guarantee direction - high momentum can occur on both breakouts and fakeouts Extreme momentum levels can persist longer than expected during major news events or market dislocations The indicator shows what is happening, not why - fundamental catalysts can override technical momentum patterns Divergences are more reliable at extreme levels than in neutral zones Multiple components mean the indicator can be slower to respond than single-component oscillators Input Parameters Core Engine: Primary Length: Period for momentum calculations (default: 14) Smoothing Period: EMA smoothing for final output (default: 7) Sensitivity Factor: Multiplier for Fisher Transform input (default: 1.5) Volume Flux Engine: VFI Coefficient: Cutoff multiplier for significant moves (default: 0.2) Volume Cutoff: Maximum volume multiplier (default: 2.5) Scale Multiplier: VFI output scaling (default: 4.0) Laguerre Transform: Gamma: Responsiveness parameter (default: 0.4, lower = faster) Threshold Zones: Extreme Overbought: Upper extreme threshold (default: 35) Overbought: Upper threshold (default: 25) Oversold: Lower threshold (default: -25) Extreme Oversold: Lower extreme threshold (default: -35) Money Flow & Volume: MFI Length: Period for Money Flow Index (default: 14) OBV Smoothing: Smoothing period for OBV (default: 14) A/D Smoothing: Smoothing period for A/D Line (default: 14) Multi-Timeframe Analysis: Enable Higher Timeframe: Toggle MTF calculations (default: enabled) HTF Timeframe 1/2/3: Customizable timeframes (default: 5m, 15m, 60m) Visual Configuration: Color Theme: Choose from Gradient Glow, Professional Dark, Neon Spectrum, or Institutional Grey Bullish/Bearish Spectrum: Customizable colors for momentum direction Glow Layers: Number of gradient layers for glow effect (default: 20) Show Divergence: Toggle divergence detection (default: enabled) Show Volume Profile: Toggle volume profile histogram (default: enabled) Technical Implementation Built with Pine Script v6 using: Custom VFI calculations with logarithmic price changes and volume cutoffs Four-stage Laguerre filter for adaptive RSI Fisher Transform for Gaussian distribution conversion Double-smoothed TSI for noise filtering Volume-weighted MFI calculations Normalized OBV and A/D Line integration Multi-timeframe security requests with proper lookahead settings Velocity and acceleration calculations for momentum derivatives Real-time regime classification system Dynamic dashboard with 10 metrics and color-coded cells Gradient glow effect with multiple layered fills Divergence detection with pivot analysis 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 (VFI, Laguerre RSI, Fisher Transform, TSI, MFI, OBV, A/D) are established concepts, this indicator is justified because: It synthesizes six distinct momentum methodologies into a unified weighted composite system The regime classification provides institutional momentum measurement not available in standard oscillators Multi-timeframe alignment detection measures institutional conviction across timeframes Velocity and acceleration calculations provide early warning of momentum shifts The gradient glow visualization creates intuitive momentum intensity display Integration of volume-weighted components (VFI, MFI) with smoothed momentum (Fisher, TSI) and cumulative volume (OBV, A/D) creates layered confirmation The comprehensive dashboard presents 10 metrics simultaneously for holistic momentum analysis Each component contributes unique information: VFI shows volume-driven momentum, Laguerre RSI shows adaptive momentum, Fisher Transform shows statistical extremes, TSI shows smoothed momentum, MFI shows money flow, OBV shows cumulative volume, and A/D shows distribution. The indicator's value lies in presenting these complementary perspectives simultaneously with a unified regime 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. Momentum analysis is a tool for understanding market dynamics, not a crystal ball for predicting future price movement. High momentum does not guarantee profitable trades. Past momentum patterns do not guarantee future momentum 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. Extreme momentum levels, regime classifications, and signal generation 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
Indicador Pine Script®
por officialjackofalltrades
Echelon Regime Gauge [JOAT]Echelon Regime Gauge Introduction The Echelon Regime Gauge is an open-source market regime detection and session awareness indicator built in Pine Script v6. It classifies the current market state into one of six regimes — Trend Up, Trend Down, Range, Volatile, Squeeze, or Mixed — using a combination of SMA alignment, VWAP slope analysis, and Bollinger Band volatility metrics. On top of regime detection, the indicator provides session identification (Asian, London, New York, Kill Zones, Power Hour), volatility state tracking (Expansion, Contraction, Squeeze), R-squared trend quality measurement, historical volatility percentile, Wyckoff effort/result analysis, and an institutional activity score that colors candles by multi-factor heatmap logic. The core question this indicator answers is: "What kind of market am I in right now?" Knowing whether the market is trending, ranging, squeezing, or volatile changes everything about how you should trade — from entry type to stop placement to position sizing. This indicator provides that context in real-time with a confidence percentage and a comprehensive HUD dashboard. Why This Indicator Exists Most traders apply the same strategy regardless of market conditions. A breakout strategy in a ranging market produces whipsaws. A mean-reversion strategy in a trending market produces losses. This indicator solves the context problem by providing a clear, quantified regime classification: Regime Detection: Six distinct market states, each requiring different trading approaches. The classification uses three independent inputs — SMA alignment, VWAP slope direction, and Bollinger Band percentile — to produce a robust, multi-factor regime reading. Regime Confidence: A 0-100 score indicating how clearly the market fits the detected regime. High confidence means the classification is strong and reliable. Low confidence suggests transitional or ambiguous conditions. Session Awareness: Identifies the current trading session (Asian, London, New York) and highlights Kill Zones (London 2-5am, NY 7-10am) and Power Hour (3-4pm) — the periods when institutional activity is highest and moves are most significant. Volatility State: Tracks whether volatility is in Expansion, Contraction, Squeeze, or Normal state. Squeeze conditions (Bollinger width in the bottom 10th percentile) often precede explosive moves. Trend Quality (R-Squared): Measures how linear and clean the current trend is on a 0-1 scale. R-squared above 0.6 indicates a clean, tradeable trend. Below 0.4 indicates choppy, random price action. Institutional Activity Score: A multi-factor score (0-100) computed from body ratio, volume ratio, R-squared, Bollinger Band position, and VWAP distance. This score drives the candle heatmap coloring. How Regime Detection Works The regime engine combines three independent analytical dimensions: Dimension 1 — SMA Alignment: The indicator calculates three Simple Moving Averages (default 20, 50, 200). When all three are aligned in order (20 > 50 > 200), the market is in bull alignment. When reversed (20 < 50 < 200), bear alignment. Any other configuration is diverged/mixed. Dimension 2 — VWAP Slope: The VWAP (Volume Weighted Average Price) slope is calculated over a configurable lookback and normalized by ATR to make it comparable across instruments. A normalized slope above the threshold indicates upward momentum. Below the negative threshold indicates downward momentum. Within the threshold band indicates flat/ranging conditions. Dimension 3 — Volatility Percentile: Bollinger Band width percentile rank over 120 bars determines volatility state. Below the 10th percentile is a squeeze. Above the configurable expansion percentile (default 75th) is expansion. ATR percentile rank provides a secondary volatility measure. These three dimensions combine into the regime classification: Squeeze: BB width in bottom 10th percentile — volatility compression, potential breakout imminent Trend Up: Bull SMA alignment AND positive VWAP slope — clear directional momentum upward Trend Down: Bear SMA alignment AND negative VWAP slope — clear directional momentum downward Volatile: ATR in expansion percentile WITHOUT SMA alignment — high volatility but no clear trend direction Range: Flat VWAP slope WITHOUT SMA alignment — sideways, mean-reverting conditions Mixed: Conditions do not clearly fit any category — transitional state Regime Confidence Calculation Each regime has its own confidence formula based on how strongly the inputs support the classification: Trend Up/Down: SMA alignment (40pts) + slope direction (30pts) + slope magnitude (up to 30pts) Range: Flat slope (40pts) + no alignment (30pts) + low ATR percentile (up to 30pts) Squeeze: Low BB percentile (70%) + low ATR percentile (30%) Volatile: High ATR percentile (70%) + high BB percentile (30%) Mixed: Fixed at 25 — low confidence by definition The confidence is displayed as both a number and a visual bar (||||......) in the HUD, making it easy to assess at a glance. Session and Time-of-Day Analysis The indicator identifies seven session states with configurable timezone (default America/New_York): Asia (7pm-3am): Low volatility, range-building session. Quality: Low. London (3am-9:30am): Increasing volatility, often sets the day's direction. Quality: Medium. London Kill Zone (2-5am): Peak London institutional activity. Quality: High. New York (9:30am-4pm): Highest volume session for US instruments. Quality: Medium. NY Kill Zone (7-10am): Peak NY institutional activity, overlap with London. Quality: High. Lunch (10am-12pm): Low conviction, choppy price action. Quality: Low. Power Hour (3-4pm): End-of-day positioning, often produces strong moves. Quality: High. Kill Zones are highlighted with a subtle gold background tint. Lunch hours receive a dark tint as a visual warning of low-quality conditions. Institutional Signal System The indicator detects and labels six types of institutional events using a priority-based system with cooldowns to prevent label stacking: P1 — BULL/BEAR CONFLUENCE (highest priority): Full alignment of SMA, VWAP slope, R-squared trend quality, regime confidence > 70, and price vs VWAP. This is the strongest possible directional signal — all factors agree. P2 — MAJOR GOLDEN/DEATH CROSS: Mid SMA (50) crosses the Slow SMA (200). These are rare, high-impact structural events that signal major trend shifts. P2b — GOLDEN X / DEATH X: Fast SMA (20) crosses Mid SMA (50). More frequent than major crosses but still significant structural events. P3 — REGIME CHANGE: The regime classification changes from one state to another. Labels show the new regime name. P4 — SQZ BREAK: Squeeze releases into expansion with price above (bull) or below (bear) the fast SMA. These are high-energy breakout events. P5 — VWAP RECLAIM/REJECT: Price crosses above VWAP with positive slope (reclaim) or below with negative slope (rejection). VWAP is the institutional benchmark — reclaiming or losing it is significant. P6 — DISP (Displacement, lowest priority): Large-body candles (body > 70% of range, body > 2x average) indicating aggressive institutional order flow. Each signal checks a cooldown counter before firing. Higher-priority signals suppress lower-priority ones within the cooldown window, ensuring the chart shows only the most important signal at any given time. Candle Heatmap Coloring When enabled, candles are colored based on the current regime and trend quality rather than simple bull/bear direction: Bull Aligned + Clean Trend: Bright aurora lime (bullish candles) / aurora green (bearish candles) Bull Aligned: Aurora green / aurora teal Bear Aligned + Clean Trend: Aurora pink / aurora purple Bear Aligned: Aurora purple / aurora pink Squeeze: Aurora gold / warm orange Neutral: Ice blue / arctic blue This coloring scheme makes it immediately obvious what regime the market is in without looking at the HUD — the entire chart changes character with the regime. Advanced Metrics R-Squared Trend Quality: Calculated as the square of the correlation between close price and bar_index over a configurable period. Values above 0.7 indicate a clean, linear trend. Values below 0.4 indicate choppy, non-directional price action. This metric helps distinguish between trending markets that are tradeable and trending markets that are too choppy to trade reliably. Historical Volatility: Annualized standard deviation of log returns, displayed as a percentage with percentile ranking over 252 bars. This provides a longer-term volatility context beyond the Bollinger-based squeeze detection. Wyckoff Effort/Result: Volume divided by range — when this ratio is high (high volume, small range), institutional absorption is occurring. The indicator detects these events and displays them in the HUD. Regime Duration: Counts how many bars the current regime has persisted. Long-duration regimes are more established. Short-duration regimes may be transitional. Institutional Score: A 0-100 composite from body ratio, volume ratio, R-squared, BB position extremes, and VWAP distance. Higher scores indicate more institutional-quality price action. HUD Dashboard The HUD displays 12 metrics with color-coded values: Regime State with regime-specific color Confidence score with visual bar (||||......) VWAP Slope direction (Rising/Falling/Flat) Volatility state with squeeze duration counter Current Session name Session Quality rating (High/Medium/Low) SMA Alignment (Bull Aligned/Bear Aligned/Diverged) R-Squared trend quality (Clean/Moderate/Choppy) Historical Volatility with percentile classification Regime Duration in bars Institutional Activity Score Input Parameters Regime Detection: Fast/Mid/Slow SMA: Moving average periods (default: 20/50/200) VWAP Slope Lookback: Period for slope calculation (default: 20) Slope Threshold: Normalized slope threshold for trend detection (default: 0.12) Volatility: ATR Length: Period for ATR calculation (default: 14) Bollinger Length/Multiplier: BB parameters (default: 20/2.0) Squeeze Lookback: Percentile rank period (default: 120) Expansion Percentile: ATR percentile threshold for expansion (default: 75) Sessions: Show Session Zones: Toggle session background highlighting Timezone: Configurable timezone (default: America/New_York) Highlight Kill Zones: Toggle kill zone emphasis Visual: Regime Background: Toggle regime-adaptive background tinting SMA Trend Ribbon: Toggle ribbon fill between fast and mid SMA Candle Heatmap Coloring: Toggle institutional activity-based candle colors Show Prior Day H/L: Toggle PDH/PDL reference lines HUD Panel: Toggle with configurable position How to Use This Indicator Step 1: Check the Regime Before entering any trade, check what regime the market is in. Trend Up/Down = directional strategies. Range = mean-reversion. Squeeze = wait for breakout. Volatile = reduce size or stand aside. Step 2: Verify Confidence A regime reading with 80+ confidence is reliable. Below 50 suggests the market is in transition — be cautious. Step 3: Check the Session Kill Zones and Power Hour produce the most reliable moves. Lunch hour and Asian session moves are less reliable for most instruments. Step 4: Watch for Signals BULL/BEAR CONFLUENCE is the highest-conviction signal — all factors agree. SQZ BREAK signals high-energy breakouts. VWAP RECLAIM/REJECT provides key level context. Step 5: Use Trend Quality for Filtering R-squared above 0.6 means the trend is clean and tradeable. Below 0.4 means the trend is choppy — consider waiting for cleaner conditions. Best Practices The regime classification is most reliable on timeframes of 5 minutes and above Session features are most relevant for instruments with clear session structures (equities, futures, major forex) Squeeze conditions can persist for extended periods. Do not assume a squeeze will break immediately. Regime transitions (Mixed state) are the most dangerous periods. Consider reducing exposure during transitions. The institutional score is a heuristic — use it as one input among many, not as a standalone signal SMA crosses are lagging by nature. They confirm trend changes rather than predict them. Combine this indicator with structure or momentum tools for entry timing — this indicator provides context, not entries. Limitations Regime detection uses lagging indicators (SMAs, BB percentile). Regime changes are confirmed after they occur, not predicted in advance. The six-regime classification is a simplification. Real markets exist on a continuum, not in discrete states. Session times are hardcoded for EST timezone sessions. Instruments traded primarily in other timezones may need different session definitions. R-squared measures linearity, not direction. A perfectly linear downtrend has the same R-squared as a perfectly linear uptrend. The institutional activity score is estimated from available data (body ratio, volume, BB position). True institutional activity detection requires order flow data not available in Pine Script. VWAP resets daily on most instruments. Intraday VWAP slope is most meaningful for day trading timeframes. Kill Zone highlighting assumes EST-based session times. Adjust the timezone input for your local market. Technical Implementation Built with Pine Script v6 using: Three-dimensional regime classification (SMA alignment + VWAP slope + BB volatility) Regime confidence scoring with per-regime formulas Session detection using time() with configurable timezone R-squared trend quality via ta.correlation() Annualized historical volatility with percentile ranking Wyckoff effort/result absorption detection Multi-factor institutional activity scoring Priority-based signal system with 6 tiers and cooldown anti-overlap Volatility-adaptive gradient background coloring Aurora-themed SMA ribbon with alignment-responsive colors 10 alert conditions covering regime changes, SMA crosses, absorption, and clean trend detection Originality Statement This indicator is original in its comprehensive regime detection and session awareness integration. While SMA alignment and Bollinger squeeze are established concepts, this indicator is justified because: The three-dimensional regime classification (SMA + VWAP slope + BB volatility) produces a more robust state detection than any single method Regime confidence scoring quantifies how clearly the market fits the detected state, providing actionable uncertainty information Session awareness with quality ratings integrates time-of-day context directly into the regime framework R-squared trend quality measurement distinguishes between clean tradeable trends and choppy non-directional trends The priority-based signal system with 6 tiers ensures only the most important events are displayed Candle heatmap coloring driven by regime and trend quality provides immediate visual context The Aurora Borealis theme with volatility-adaptive background creates a dynamic visual environment that changes character with market conditions Squeeze duration tracking and regime duration counting provide temporal context for current conditions Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Regime detection classifies current market conditions based on historical data — it does not predict future regime changes. Markets can transition between regimes without warning. Squeeze conditions do not guarantee breakouts. Session quality ratings are generalizations that may not apply to all instruments or market conditions. Past regime patterns do not guarantee future behavior. Always use proper risk management and never risk more than you can afford to lose. The author is not responsible for any losses incurred from using this indicator. -Made by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
IQ Candles [TradingIQ]Hello Traders! 🔹IQ Candles IQ Candles is a brand new chart type - a pressure-based visualization tool designed to break down what’s happening inside each candle. Gone are the days of traditional candlesticks - it's time for an upgrade! Instead of treating candles as simple open-high-low-close structures, this chart type reconstructs how buying and selling pressure actually developed within the bar using lower timeframe data. It focuses on answering a more refined question: Where did the pressure come from… and how did it translate into price? buy vs sell pressure inside each candle true dominance within the bar imbalances driven by aggressive participation absorption of pressure by opposing liquidity hidden strength or weakness behind candle structure 🔹What the chart type shows 🔸Pressure candles (internal structure) Each candle is reconstructed to reflect the internal distribution of buying and selling pressure. This allows you to instantly see: where buying pressure accumulated where selling pressure dominated how evenly or unevenly the candle was built Instead of a single body, you see the composition of the move. The example above shows a candlestick that is majority green and about 20% red. This indicates that aggressive buys dominated the candle/price area, and contributed made the highest contribution to the structure of the candle. The example above shows a candlestick that is majority red and about 10% green. This indicates that aggressive sells dominated the candle/price area, and contributed made the highest contribution to the structure of the candle. The example above shows a candlestick that is 50% green and 50% red. This indicates equal contribution. 🔸Smoothed Contribution When smoothing is enabled, the chart type applies a moving average to buying and selling pressure. This reduces noise and highlights the underlying trend of participation over time. Instead of focusing on every short-term fluctuation, you get a clearer view of: sustained buying pressure sustained selling pressure gradual shifts in control between buyers and sellers This is especially useful for: filtering out erratic lower timeframe noise identifying persistent dominance understanding whether pressure is building or fading over multiple bars In fast or choppy conditions, raw pressure can fluctuate rapidly. 🔸Absorption detection The chart type detects when strong pressure fails to move price effectively. This is one of the most important concepts in order flow. It highlights: buying absorbed at highs selling absorbed at lows hidden liquidity opposing aggressive traders potential exhaustion or reversal conditions This helps answer: “Was that pressure actually effective?” The image above shows an example of the chart type when buyers are absorbed. The image above shows an example of the chart type when sellers are absorbed. 🔸Imbalance detection When one side heavily outweighs the other, the chart type highlights imbalance conditions. This helps identify: aggressive one-sided participation momentum-driven moves bars where one side clearly overpowered the other Imbalances are not just about direction - they show conviction. The image above shows the chart type detecting a buy-side imbalance candle. The image above shows the chart type detecting a sell-side imbalance candle. 🔸Buy vs Sell pressure histogram A histogram displays total buying and selling pressure per bar. This gives you a quick read on: which side is in control how dominant that control is whether pressure is increasing or fading 🔸Delta mode (pressure expansion) Delta mode emphasizes the difference between dominant and opposing pressure. This is useful for: highlighting extreme dominance isolating one-sided control visualizing pressure expansion during strong moves The image above shows how to read positive delta candles for the chart type. The image above shows how to read negative delta candles for the chart type. 🔸Candle Radar (live table) A live table summarizes current bar activity, including: buy pressure sell pressure buy/sell percentages delta ratio dominant side imbalance status absorption status This provides a quick overview without needing to interpret the chart visually. 🔹How to read it Each component gives a different layer of information: Histogram → total pressure (who is active) Candle structure → how pressure translated into price Imbalance → when one side dominates Absorption → when dominance fails Together, this shifts your perspective from: “price moved up” to: “buying pressure dominated — but did it actually succeed?” Example interpretations: strong buy pressure + strong close → clean continuation strong buy pressure + weak close → possible absorption balanced pressure → indecision / consolidation extreme imbalance → momentum or potential exhaustion absorption signals → potential reversal or liquidity interaction 🔹Why this chart type is useful It gives you: internal candle structure clear separation of buying and selling pressure context for whether pressure is effective imbalance detection for momentum absorption detection for reversals a deeper understanding of how price actually forms 🔹Best use cases analyzing strength behind moves confirming continuation vs weakness spotting absorption at key levels understanding liquidity interactions enhancing price action or liquidity-based models 🔹Important note Pressure can: drive moves fail to move price or be absorbed by opposing liquidity Context always matters. 🔹Important consideration This script uses lower timeframe data to approximate internal pressure. This means: accuracy depends on available data different symbols may behave differently lower timeframe selection impacts results 🔹Inputs you can customize The script includes flexible controls such as: lower timeframe selection smoothing of pressure imbalance threshold absorption sensitivity delta mode behavior extended move filtering visual styling and colors Closing Notes And that’s about it! This script is built to reveal what candles are actually doing beneath the surface -turning price into something you can interpret, not just observe. It may receive updates based on feedback - stay tuned! Thank you TradingView as always!
Indicador Pine Script®
por Trading-IQ
80
Oscillator Confluence Tracker [JOAT]Oscillator Confluence Tracker Introduction The Oscillator Confluence Tracker is an advanced open-source multi-oscillator divergence detection indicator that combines RSI divergence analysis, MACD momentum tracking, Stochastic extreme identification, volume divergence detection, and pattern recognition into a unified smart money divergence system. This indicator helps traders identify when price and momentum are moving in opposite directions - a powerful signal that the current trend is losing strength and a reversal may be imminent. Unlike basic oscillator indicators that simply show overbought/oversold levels, this system detects divergences across multiple oscillators simultaneously and quantifies confluence. Regular divergences signal potential reversals, hidden divergences signal trend continuation, and multi-oscillator confluence provides the highest probability setups. The indicator is designed for traders who understand that divergences reveal institutional positioning changes before they're visible in price action. Why This Indicator Exists This indicator addresses a critical challenge in divergence trading: single oscillator divergences produce many false signals. By combining multiple oscillators and requiring confluence, this indicator reveals: RSI Divergence Detection: Identifies when price makes new highs/lows but RSI doesn't - signals momentum exhaustion MACD Momentum Analysis: Tracks MACD line and histogram for momentum shifts and crossovers Stochastic Extreme Zones: Identifies overbought (>80) and oversold (<20) conditions for context Hidden Divergence Patterns: Detects hidden divergences that signal trend continuation rather than reversal Volume Divergence: Identifies when price makes new highs/lows on decreasing volume - warns of weak moves Multi-Oscillator Confluence: Quantifies how many oscillators show divergence simultaneously Momentum Divergence: Detects when price momentum and oscillator momentum conflict Each component provides a different lens on momentum. RSI shows relative strength, MACD shows trend momentum, Stochastic shows extremes, volume shows participation, and confluence shows conviction. Together, they create a comprehensive view of smart money divergence. Core Components Explained 1. Regular Bearish Divergence (Price HH, RSI LH) Regular bearish divergence occurs when price makes a higher high but RSI makes a lower high - signals uptrend exhaustion: // Detect pivot highs in both price and RSI pricePivotHigh = ta.pivothigh(high, 5, 5) rsiPivotHigh = ta.pivothigh(rsi, 5, 5) // Compare current pivot to previous pivot if pricePivotHigh > lastPriceHigh and rsiPivotHigh < lastRsiHigh: // Bearish divergence detected drawDivergenceLines() createDivergenceLabel("BEAR DIV") The indicator identifies bearish divergence by: Tracking swing highs in both price and RSI using pivot detection Comparing current swing high to previous swing high Confirming price made higher high while RSI made lower high Drawing solid line on price chart and dashed line on RSI Creating "BEAR DIV" label at the divergence point Bearish divergence is most powerful when: RSI is in overbought zone (>70) - "BEAR DIV EXTREME" label Multiple oscillators show divergence simultaneously Volume is decreasing on the higher high Occurs at resistance or Fibonacci level 2. Regular Bullish Divergence (Price LL, RSI HL) Regular bullish divergence occurs when price makes a lower low but RSI makes a higher low - signals downtrend exhaustion: // Detect pivot lows in both price and RSI pricePivotLow = ta.pivotlow(low, 5, 5) rsiPivotLow = ta.pivotlow(rsi, 5, 5) // Compare current pivot to previous pivot if pricePivotLow < lastPriceLow and rsiPivotLow > lastRsiLow: // Bullish divergence detected drawDivergenceLines() createDivergenceLabel("BULL DIV") The indicator identifies bullish divergence by: Tracking swing lows in both price and RSI Comparing current swing low to previous swing low Confirming price made lower low while RSI made higher low Drawing solid line on price chart and dashed line on RSI Creating "BULL DIV" label at the divergence point Bullish divergence is most powerful when: RSI is in oversold zone (<30) - "BULL DIV EXTREME" label Multiple oscillators show divergence simultaneously Volume is decreasing on the lower low Occurs at support or Fibonacci level 3. Hidden Bullish Divergence (Price HL, MACD LL) Hidden bullish divergence occurs when price makes a higher low but MACD makes a lower low - signals uptrend continuation: // Price makes higher low (bullish structure) if pricePivotLow > lastPriceLow and macdPivotLow < lastMacdLow: // Hidden bullish divergence - trend continuation signal drawHiddenDivergence("H-BULL") Hidden divergences are different from regular divergences: Signal trend continuation, not reversal Occur during pullbacks in established trends Show that momentum is building despite price correction Drawn with dotted lines to distinguish from regular divergence Labeled "H-BULL" or "H-BEAR" for clarity Hidden divergences are powerful for: Entering pullbacks in strong trends Adding to winning positions Confirming trend strength Identifying optimal re-entry points 4. Volume Divergence Detection Volume divergence occurs when price makes new highs/lows but volume decreases - warns of weak moves: // Track volume at pivot highs volPivotHigh = ta.pivothigh(volume, 5, 5) // Price makes higher high, volume makes lower high if pricePivotHigh > lastPriceHigh and volPivotHigh < lastVolHigh: label.new(bar_index, high, "VOL DIV", color=COLOR_VOL_DIV) Volume divergence reveals: Decreasing participation in the move Lack of institutional conviction Potential exhaustion or trap Warning that trend may not continue Volume divergence combined with RSI/MACD divergence creates extremely high-probability reversal setups. 5. Momentum Divergence Analysis Momentum divergence occurs when price momentum and oscillator momentum move in opposite directions: rsiMomentum = ta.change(rsi, 5) macdMomentum = ta.change(macdLine, 5) priceMomentum = ta.change(close, 5) // Price momentum positive but RSI momentum negative momentumDivergence = (priceMomentum > 0 and rsiMomentum < 0) or (priceMomentum < 0 and rsiMomentum > 0) Momentum divergence shows: Acceleration/deceleration conflicts Early warning of trend changes Momentum exhaustion before price exhaustion Institutional positioning shifts The dashboard displays momentum divergence status (Active/Aligned) with color coding. 6. Multi-Oscillator Confluence Scoring The indicator quantifies confluence by counting how many oscillators show divergence simultaneously: confluenceScore = 0 if rsi_divergence: confluenceScore += 1 if macd_divergence: confluenceScore += 1 if stochastic_extreme: confluenceScore += 1 if volume_divergence: confluenceScore += 1 if momentum_divergence: confluenceScore += 1 // Classify confluence confluenceLevel = confluenceScore >= 4 ? "EXTREME BULL/BEAR" : confluenceScore >= 3 ? "STRONG BULL/BEAR" : confluenceScore >= 2 ? "MODERATE" : "NONE" Confluence scoring reveals: Setup quality (higher score = higher probability) How many independent signals confirm the divergence Whether to take the trade (3+ recommended) Position sizing guidance (higher score = larger size) The dashboard displays confluence score and classification with color intensity. 7. Enhanced Candlestick Coloring The indicator colors candles based on trend strength and momentum: // Determine trend trendStrength = ta.ema(close, 20) isBullTrend = close > trendStrength isBearTrend = close < trendStrength // Momentum strength momentumStrong = abs(rsiMomentum) > 5 or abs(macdMomentum) > abs(macdHist) * 0.5 // Color candles if isBullTrend: candleColor = momentumStrong ? COLOR_BULL_STRONG : COLOR_BULL_WEAK else if isBearTrend: candleColor = momentumStrong ? COLOR_BEAR_STRONG : COLOR_BEAR_WEAK Candlestick coloring shows: Bright green: Strong bullish momentum Light green: Weak bullish momentum Bright red: Strong bearish momentum Light red: Weak bearish momentum This provides instant visual feedback on trend and momentum strength. Visual Elements Divergence Lines: Solid lines on price, dashed lines on oscillator connecting pivot points Divergence Labels: "BULL DIV", "BEAR DIV", "H-BULL", "H-BEAR" at divergence points Extreme Labels: "BULL DIV EXTREME" or "BEAR DIV EXTREME" in overbought/oversold zones Volume Labels: "VOL DIV" markers when volume diverges Divergence Zones: Semi-transparent boxes highlighting divergence areas Enhanced Candles: Color-coded by trend and momentum strength Volume Spike Boxes: Gold boxes around high-volume candles Extreme Zone Backgrounds: Red tint when RSI >70 and Stochastic >80, green tint when RSI <30 and Stochastic <20 Dashboard: Real-time oscillator states and confluence metrics The dashboard displays 9 key metrics: 1. RSI State (value and Overbought/Oversold/Neutral) 2. MACD Flow (Bullish/Bearish and Strong/Weak) 3. Stochastic (value and Extreme/Normal) 4. Momentum Div (Active/Aligned) 5. Volume Profile (ratio and Spike/Elevated/Low) 6. Trend Strength (Bullish/Bearish and Strong/Weak) 7. Confluence (Extreme/Strong/Moderate/None) 8. Signal Quality (Elite Setup/Strong Setup/Moderate/Weak) Input Parameters Oscillator Settings: RSI Period: Length for RSI calculation (default: 14) MACD Fast: Fast EMA for MACD (default: 12) MACD Slow: Slow EMA for MACD (default: 26) MACD Signal: Signal line period (default: 9) Stochastic Period: Length for Stochastic calculation (default: 14) Divergence Detection: Pivot Detection: Lookback for swing detection (default: 5) Regular Divergence: Enable/disable regular divergence detection Hidden Divergence: Enable/disable hidden divergence detection Multi-Oscillator Confluence: Require multiple oscillators Extreme Zones Only: Only detect divergences in overbought/oversold Volume Analysis: Volume Analysis Period: Length for volume average (default: 20) Volume Divergence: Enable/disable volume divergence detection Volume Spike Threshold: Multiplier for spike detection (default: 1.5x) How to Use This Indicator Step 1: Monitor RSI State Check dashboard for RSI level. Divergences in extreme zones (>70 or <30) are most powerful. Wait for extremes for best setups. Step 2: Watch for Divergence Labels When "BULL DIV" or "BEAR DIV" labels appear, divergence is detected. "EXTREME" suffix means it's in overbought/oversold - highest probability. Step 3: Check Confluence Score Dashboard shows confluence level. "EXTREME" or "STRONG" = multiple oscillators confirming. Only trade 3+ confluence setups. Step 4: Confirm with Volume Look for "VOL DIV" labels. Volume divergence + oscillator divergence = very high probability. Volume confirms the divergence. Step 5: Assess Signal Quality [/b> Dashboard shows "ELITE SETUP" when momentum divergence + extreme RSI/Stochastic + high confluence. "STRONG SETUP" for good setups. Only trade Elite and Strong. Step 6: Use Hidden Divergence for Continuation "H-BULL" or "H-BEAR" labels signal trend continuation. Enter pullbacks in strong trends when hidden divergence appears. Step 7: Monitor Trend Strength Best Practices Divergences in extreme zones (RSI >70 or <30) are most reliable Multi-oscillator confluence (3+) significantly increases win rate Volume divergence adds powerful confirmation Hidden divergences are for trend continuation, not reversal Regular divergences are for reversal, not continuation Momentum divergence provides early warning before price divergence Extreme zone backgrounds (red/green tint) show best divergence areas Enhanced candle colors show when momentum is weakening Confluence score guides position sizing (higher = larger) Signal quality in dashboard filters low-probability setups Indicator Limitations Divergences can persist for extended periods before reversing Not all divergences result in reversals - some fail Strong trends can produce multiple divergences before reversing Hidden divergences require established trend context Volume divergence less reliable on low-volume instruments Pivot detection requires sufficient volatility Multiple divergences in short period may signal consolidation The indicator shows momentum conflicts, not guaranteed reversals Extreme zones can remain extreme longer than expected Technical Implementation Built with Pine Script v6 using: RSI divergence detection with pivot comparison MACD momentum analysis with histogram tracking Stochastic extreme zone identification Volume divergence detection with pivot tracking Momentum divergence calculations (rate-of-change) Multi-oscillator confluence scoring system Enhanced candlestick coloring based on trend and momentum Volume spike detection with box visualization Extreme zone background gradients Real-time dashboard with 9 divergence metrics 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 divergence integration approach. While individual components (RSI, MACD, Stochastic, volume) are established concepts, this indicator is justified because: It synthesizes multiple oscillator divergence detection into unified confluence scoring The multi-oscillator confluence system quantifies setup quality across independent signals Hidden divergence detection distinguishes continuation from reversal patterns Volume divergence integration adds participation confirmation layer Momentum divergence analysis provides early warning system Enhanced candlestick coloring shows trend and momentum strength visually Signal quality classification (Elite/Strong/Moderate/Weak) filters setups Extreme zone backgrounds highlight optimal divergence areas Real-time dashboard presents 9 metrics simultaneously for holistic divergence analysis Each component contributes unique information: RSI shows relative strength, MACD shows momentum, Stochastic shows extremes, volume shows participation, momentum shows acceleration, confluence shows conviction, and quality shows probability. The indicator's value lies in presenting these complementary perspectives simultaneously with unified classification and actionable trade signals. 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. Divergence analysis is a tool for identifying potential reversals and continuations, not a crystal ball for predicting future price movement. Divergences do not guarantee reversals. Confluence does not guarantee success. Past divergence patterns do not guarantee future divergence patterns. Market conditions change, and strategies that worked historically may not work in the future. The divergences displayed are analytical constructs based on current market data, not predictions of future price movement. High confluence scores 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
Indicador Pine Script®
por officialjackofalltrades
Sessions + Prev + PDH/PDL + Killzones SuiteDescription This indicator is designed to provide time-based and price-based market context by combining session ranges with commonly referenced prior levels into a single, unified framework. The purpose of the script is contextual analysis, not signal generation. What the script does The script tracks and plots the following elements directly on the price chart: • High and Low ranges for multiple trading sessions (Asia, London, New York morning, and New York afternoon) • High and Low levels from the previous occurrence of each session • Prior Day High (PDH) and Prior Day Low (PDL) • Optional session “killzone” boxes that visually mark active session time windows All calculations are performed using time-based session boundaries and price extrema (high/low) within those windows. Why these components are combined Sessions, previous session levels, and prior day levels are frequently analyzed together by discretionary traders because they represent: • Where liquidity formed earlier in the day or previous day • Where price previously paused, expanded, or reversed • Natural reference points for intraday structure and range analysis Instead of plotting these elements using multiple separate scripts, this indicator integrates them into one consistent framework so that all levels are calculated using the same timezone, session logic, and display rules. This avoids mismatched session times, duplicate levels, or conflicting calculations that can occur when multiple scripts are used simultaneously. How the script works (high-level) • Each session is defined using user-selectable session times and timezone • During a session, the script tracks the highest and lowest traded price • When a session ends, its final high and low are stored as the “previous session” levels • PDH and PDL are calculated using the completed trading day • Lines and labels are anchored to the bars where levels are formed, rather than extending indefinitely • Optional display filters allow users to show only the current trading day to reduce chart clutter No forward-looking logic, prediction, alerts, or trade execution logic is included. How to use it This script is intended to be used as a visual reference tool to help traders: • Identify session boundaries and intraday ranges • Observe how price reacts near prior session highs and lows • Assess where price is trading relative to PDH and PDL • Maintain consistent session timing across different timezones The script does not provide trade entries, exits, alerts, or performance claims. Important notes • This indicator does not generate buy or sell signals • It does not predict future price movement • It is not a trading strategy • All decisions remain the responsibility of the user Disclaimer This script is provided for educational and informational purposes only. It does not constitute financial advice. Trading involves risk, and users should apply appropriate risk management and personal judgment when using any technical tool.
Indicador Pine Script®
por TradeswithB