Engulfing Failure & Overlap Zones [HASIB]🧭 Overview
Engulfing Failure & Overlap Zones is a smart price action–based indicator that detects failed engulfing patterns and overlapping zones where potential liquidity traps or reversal setups often occur.
It’s designed to visually highlight both bullish and bearish failed engulfing areas with clean labels and zone markings, making it ideal for traders who follow Smart Money Concepts (SMC) or price action–driven trading.
⚙️ Core Concept
Engulfing patterns are powerful reversal signals — but not all of them succeed.
This indicator identifies:
When a Buy Engulfing setup fails and overlaps with a Sell Engulfing zone, and
When a Sell Engulfing setup fails and overlaps with a Buy Engulfing zone.
These overlapping areas often represent liquidity grab zones, reversal points, or Smart Money manipulation levels.
🎯 Key Features
✅ Detects both Buy and Sell Engulfing Failures
✅ Highlights Overlapping (OL) zones with colored rectangles
✅ Marks Buy EG OL / Sell EG OL labels automatically
✅ Fully customizable visuals — colors, padding, and zone styles
✅ Optimized for both scalping and swing trading
✅ Works on any timeframe and any instrument
⚡ How It Helps
Identify liquidity traps before reversals happen
Visually see Smart Money overlap zones between opposing engulfing structures
Strengthen your entry timing and confirmation zones
Combine with your own SMC or ICT-based trading setups for higher accuracy
📊 Recommended Use
Use on higher timeframes (e.g., M15, H1, H4) to confirm major liquidity zones.
Use on lower timeframes (e.g., M1–M5) for precision entries inside the detected zones.
Combine with tools like Order Blocks, Break of Structure (BOS), or Fair Value Gaps (FVG).
🧠 Pro Tip
When a failed engulfing overlaps with an opposite engulfing zone, it often signals market maker intent to reverse price direction after liquidity has been taken. Watch these zones closely for strong reaction candles.
In den Scripts nach "liquidity" suchen
REQH/L [TakingProphets]OVERVIEW
This indicator identifies and maintains liquidity reference levels derived from swing highs and swing lows, then flags Relative Equal Highs (REQH) and Relative Equal Lows (REQL) when two active levels are within a user-defined distance.
It is intended for educational study of liquidity behavior and market structure. It does not predict price, provide signals, or recommend trades.
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PURPOSE AND SCOPE
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• Provide a consistent, rule-based way to mark possible equal-high/equal-low liquidity pools.
• Help users journal, review, and study how price interacts with those pools.
• Keep charts clear by automatically managing lines/labels and optionally fading traded-through levels.
This is an indicator, not a strategy. No entries, exits, or performance claims are made.
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CONCEPTS AND DEFINITIONS
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• Swing High / Swing Low: local extrema used to seed candidate liquidity levels.
• Buyside Liquidity (BSL): swing highs (potential buy-side stops).
• Sellside Liquidity (SSL): swing lows (potential sell-side stops).
• Relative Equal Highs (REQH): two unswept highs within a small price distance.
• Relative Equal Lows (REQL): two unswept lows within a small price distance.
• Traded-Through: a level is considered taken once price trades past it (high > level for BSL, low < level for SSL).
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HOW IT WORKS (ALGORITHMIC FLOW)
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Swing Detection
• Uses built-in pivot functions with a fixed swingStrength = 1.
• On a confirmed pivot high, a BSL level is created; on a pivot low, an SSL level is created.
• Each level stores: price, bar index, line handle, label handle, and status flags.
REQH / REQL Identification
• A constant REQ_THRESHOLD = 2.0 is used to test proximity between active levels of the same side.
• For BSL (highs): when two highs are within threshold, the higher level is kept and flagged REQH; the other is removed.
• For SSL (lows): when two lows are within threshold, the lower level is kept and flagged REQL; the other is removed.
• When a level is flagged, its line is revealed in side color and its label updates to “REQH” or “REQL”.
Traded-Through Handling
• If price trades through an active level (high > BSL price, or low < SSL price), two behaviors are possible:
– If Keep Traded-Through Levels = OFF: the level is deleted.
– If ON: the level is marked traded, its color is faded (opacity ≈ 75), and the line’s extension is frozen at the trade-through bar.
Line/Label Maintenance
• Lines are created initially invisible (fully transparent). Flagging reveals the line in color.
• Labels can be shown/hidden; placement can be Left (at level start, with left offset) or Right (at current bar, with right offset).
• All active lines extend to the right as bars progress.
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KEY INPUTS
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• Buyside Level Color (default #089981)
• Sellside Level Color (default #E91E63)
• Line Style (Solid / Dashed / Dotted) and Width
• Show Labels (on/off), Label Placement (Left/Right)
• Keep Traded-Through Levels (on/off), Traded Opacity (~75)
• REQ Threshold (fixed in code at 2.0 by default; represents the max distance between two levels to be considered “relative equal”)
Note: In this version, swingStrength is fixed to 1 inside the script. If you want a user control here, I can expose it as an input.
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PRACTICAL USAGE
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• Identify potential equal-high/equal-low zones using objective proximity logic.
• Observe if those zones attract price or are traded through during your session study.
• Journal how often flagged REQH/REQL zones remain intact versus get swept.
• Combine with your own analysis and risk framework; this script is informational only.
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VISUAL BEHAVIOR AND STYLE
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• Flagged levels are plotted in side color (buyside/sellside).
• Right-placement keeps labels aligned near the most recent bar for clarity; Left-placement anchors labels near the origin index.
• When keep-traded-levels is enabled, faded color indicates the level has been traded through, while preserving the historical reference.
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LIMITATIONS AND TECHNICAL NOTES
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• Timeframe and symbol volatility will influence the usefulness of a fixed REQ threshold. For very high-priced or low-priced instruments, consider adjusting the threshold in code to suit your market’s tick/point value.
• Using swingStrength = 1 introduces more sensitivity; users who prefer fewer, stronger pivots may wish to expose this as an input and increase it.
• No look-ahead is used; pivots are confirmed using standard pivot confirmation.
• Arrays and line/label objects are bounded by max_lines_count = 500; extremely long sessions or dense markets may require reducing visual retention.
• The script does not compute performance, signals, or recommendations.
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ORIGINALITY AND VALUE
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• Implements a simple, explicit REQ proximity engine that only reveals and labels lines after they qualify as REQH/REQL, keeping charts clean.
• Provides deterministic deletion or fading behavior once levels are traded through, preserving historical context when desired.
• Uses a clear line/label management model with consistent right-extension and optional label offsets to avoid overlap.
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TERMS AND DISCLAIMER
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This indicator is provided solely for educational and informational purposes.
It does not constitute financial advice, trading signals, or a recommendation to buy or sell any instrument.
Past behavior of price structures does not guarantee future results.
Users are fully responsible for their own decisions and outcomes.
This description is self-contained and does not solicit purchases or external contact.
💸 Monetary Momentum Oscillator (MMO)Monetary Momentum Oscillator (MMO)
The Monetary Momentum Oscillator (MMO) measures the rate of change in the money supply (like M2, Fed Balance Sheet, or similar macro series) and applies a momentum-based RSI calculation to visualize liquidity acceleration and deceleration.
💡 Purpose:
MMO is designed for macro-level analysis — it identifies when monetary expansion is overheating (potential inflation or risk-on conditions) and when contraction is cooling off (liquidity tightening or deflationary stress).
📊 How It Works:
Calculates the percentage change of the selected data source over a chosen lookback period.
Applies an RSI transformation to visualize momentum extremes.
Overlays signal smoothing and highlights overheat/cooldown zones.
🔍 Interpretation:
Above 70 → Liquidity acceleration / overheating (potential inflationary impulse).
Below 30 → Liquidity deceleration / contraction (risk-off, tightening).
Crossovers → Momentum shifts that often precede macro trend reversals in risk assets.
⚙️ Best Used On:
Macroeconomic series such as M2SL, M2V, WALCL, or custom liquidity indexes.
Long-term charts (weekly or monthly) for detecting major monetary regime transitions.
🧩 Core Idea:
Liquidity is the real market engine — this oscillator quantifies its pulse.
Fractals & SweepThe Fractals & Sweep indicator is designed to identify key market structure points (fractals) and detect potential liquidity sweeps around those areas. It visually highlights both Bill Williams fractals and regular fractals, and alerts the user when the market sweeps liquidity above or below the most recent fractal levels.
Fractal Recognition:
Detects both bullish (low) and bearish (high) fractals on the price chart.
Users can choose between:
Bill Williams fractal logic (default), or
Regular fractal logic (when the “Filter Bill Williams Fractals” option is enabled).
Fractals are plotted directly on the chart as red downward triangles for highs and green upward triangles for lows.
Fractal Tracking:
The indicator stores the most recent high and low fractal levels to serve as reference points for potential sweep detection.
Sweep Detection:
A bearish sweep is triggered when the price wicks above the last fractal high but closes below it — suggesting a liquidity grab above resistance.
A bullish sweep is triggered when the price wicks below the last fractal low but closes above it — suggesting a liquidity grab below support.
When a sweep occurs, the indicator draws a horizontal line from the previous fractal point to the current bar.
Alert System:
Custom alerts notify the trader when a bearish sweep or bullish sweep occurs, allowing for timely reactions to potential reversals or liquidity traps.
Trend Pivots Profile [BigBeluga]🔵 OVERVIEW
The Trend Pivots Profile is a dynamic volume profile tool that builds profiles around pivot points to reveal where liquidity accumulates during trend shifts. When the market is in an uptrend , the indicator generates profiles at low pivots . In a downtrend , it builds them at high pivots . Each profile is constructed using lower timeframe volume data for higher resolution, making it highly precise even in limited space. A colored trendline helps traders instantly recognize the prevailing trend and anticipate which type of profile (bullish or bearish) will form.
🔵 CONCEPTS
Pivot-Driven Profiles : Profiles are only created when a new pivot forms, aligning liquidity analysis with market structure shifts.
Trend-Contextual : Profiles form at low pivots in uptrends and at high pivots in downtrends.
Lower Timeframe Data : Volume and close values are pulled from smaller timeframes to provide detailed, high-resolution profiles inside larger pivot windows.
Adaptive Bin Sizing : Bin size is automatically calculated relative to ATR, ensuring consistent precision across different markets and volatility conditions.
Point of Control (PoC) : The highest-volume level within each profile is marked with a PoC line that extends until the next pivot forms.
Trendline Visualization : A wide, semi-transparent line follows the rolling average of highs and lows, colored blue in uptrends and orange in downtrends.
🔵 FEATURES
Pivot Length Control : Adjust how far back the script looks to detect pivots (e.g., length 5 → profiles cover 10 bars after pivot).
Pivot Profile toggle :
On → draw the filled pivot profile + PoC + pivot label.
Off → hide profiles; show only PoC level (clean S/R mode).
Trend Length Filter : Smooths trendline detection to ensure reliable up/down bias.
Precise Volume Distribution : Volume is aggregated into bins, creating a smooth volume curve around the pivot range.
PoC Extension : Automatically extends the most active price level until a new pivot is confirmed.
Profile Visualization : Profiles appear as filled shapes anchored at the pivot candle, colored based on trend.
Trendline Overlay : Thick, semi-transparent trendline provides visual guidance on directional bias.
Automatic Cleanup : Old profiles are deleted once they exceed the chart’s capacity (default 25 stored profiles).
🔵 HOW TO USE
Spotting Trend Liquidity : In an uptrend, monitor profiles at low pivots to see where buyers concentrated. In downtrends, use high-pivot profiles to spot sell-side pressure.
Watch the PoC : The PoC line highlights the strongest traded level of the pivot structure—expect reactions when price retests it.
Anticipate Trend Continuation/Reversal : Use the trendline (blue = bullish, orange = bearish) together with pivot profiles to forecast directional momentum.
Combine with HTF Context : Overlay with higher timeframe structure (order blocks, liquidity zones, or FVGs) for confluence.
Fine-Tune with Inputs : Adjust Pivot Length for sensitivity and Trend Length for smoother or faster trend shifts.
🔵 CONCLUSION
The Trend Pivots Profile blends pivot-based structure with precise volume profiling. By dynamically plotting profiles on pivots aligned with the prevailing trend, highlighting PoCs, and overlaying a directional trendline, it equips traders with a clear view of liquidity clusters and directional momentum—ideal for anticipating reactions, pullbacks, or breakouts.
Project Pegasus RevenantDescription
Project Pegasus Revenant is a reversal and liquidity-trap detection system combining a configurable fractal reversal engine with the SweepTrigger liquidity finder. It highlights potential structural turning points and stop-hunt scenarios directly on the chart.
What’s unique
Fractal Reversal Engine: Adjustable strictness (1 = loose, 5 = strict) to fit different market conditions.
Signal Filtering: Minimum bar spacing to avoid clustering of false or repeated signals.
SweepTrigger Add-on: Detects liquidity sweeps with wick-based rejection logic, auto-doji detection, and range-strength confirmation.
Dual Signal Output: Circle markers for pure fractal reversals, triangles for sweep-based liquidity traps.
Adaptive Filters: Customizable thresholds for body size, candle range, and sweep strength.
How it works (technical)
Fractals: A reversal fractal is confirmed when the high/low at position n is surrounded by lower/higher highs/lows across a configurable frontier.
Signal confirmation: Once price trades back through the fractal level within a limited number of bars, a potential reversal is triggered.
Bar filter: Signals require a minimum distance in bars to prevent noise.
SweepTrigger logic:
Wick comparison (upper vs lower) determines rejection direction.
Doji and low-body candles are auto-filtered.
Range check ensures the current candle exceeds a configurable multiple of the average range.
Visuals:
Green/Red circles = fractal reversals.
Cyan/Purple triangles = liquidity sweep triggers.
How to use
Watch fractal signals to anticipate structural reversal points.
Combine SweepTrigger signals with liquidity highs/lows for identifying stop hunts and fakeouts.
Use as standalone reversal tool or as confirmation within a broader system (e.g., order blocks, volume profile, or market structure).
Key settings
Reversal Mode: 1–5 (controls strictness of fractals).
SweepTrigger: On/off toggle, lookback window, body-size filter, range strength multiplier.
Visuals: Shapes, sizes, and color-coded signals for clear separation between fractal and sweep triggers.
Notes & limitations
Works on all timeframes.
Signals are reactive (based on confirmed bars), not predictive — no lookahead logic.
Too strict settings may reduce signal frequency; too loose may increase noise.
Disclaimer
For educational and informational purposes only. Not financial advice.
Volume Based Sampling [BackQuant]Volume Based Sampling
What this does
This indicator converts the usual time-based stream of candles into an event-based stream of “synthetic” bars that are created only when enough trading activity has occurred . You choose the activity definition:
Volume bars : create a new synthetic bar whenever the cumulative number of shares/contracts traded reaches a threshold.
Dollar bars : create a new synthetic bar whenever the cumulative traded dollar value (price × volume) reaches a threshold.
The script then keeps an internal ledger of these synthetic opens, highs, lows, closes, and volumes, and can display them as candles, plot a moving average calculated over the synthetic closes, mark each time a new sample is formed, and optionally overlay the native time-bars for comparison.
Why event-based sampling matters
Markets do not release information on a clock: activity clusters during news, opens/closes, and liquidity shocks. Event-based bars normalize for that heteroskedastic arrival of information: during active periods you get more bars (finer resolution); during quiet periods you get fewer bars (coarser resolution). Research shows this can reduce microstructure pathologies and produce series that are closer to i.i.d. and more suitable for statistical modeling and ML. In particular:
Volume and dollar bars are a common event-time alternative to time bars in quantitative research and are discussed extensively in Advances in Financial Machine Learning (AFML). These bars aim to homogenize information flow by sampling on traded size or value rather than elapsed seconds.
The Volume Clock perspective models market activity in “volume time,” showing that many intraday phenomena (volatility, liquidity shocks) are better explained when time is measured by traded volume instead of seconds.
Related market microstructure work on flow toxicity and liquidity highlights that the risk dealers face is tied to information intensity of order flow, again arguing for activity-based clocks.
How the indicator works (plain English)
Choose your bucket type
Volume : accumulate volume until it meets a threshold.
Dollar Bars : accumulate close × volume until it meets a dollar threshold.
Pick the threshold rule
Dynamic threshold : by default, the script computes a rolling statistic (mean or median) of recent activity to set the next bucket size. This adapts bar size to changing conditions (e.g., busier sessions produce more frequent synthetic bars).
Fixed threshold : optionally override with a constant target (e.g., exactly 100,000 contracts per synthetic bar, or $5,000,000 per dollar bar).
Build the synthetic bar
While a bucket fills, the script tracks:
o_s: first price of the bucket (synthetic open)
h_s: running maximum price (synthetic high)
l_s: running minimum price (synthetic low)
c_s: last price seen (synthetic close)
v_s: cumulative native volume inside the bucket
d_samples: number of native bars consumed to complete the bucket (a proxy for “how fast” the threshold filled)
Emit a new sample
Once the bucket meets/exceeds the threshold, a new synthetic bar is finalized and stored. If overflow occurs (e.g., a single native bar pushes you past the threshold by a lot), the code will emit multiple synthetic samples to account for the extra activity.
Maintain a rolling history efficiently
A ring buffer can overwrite the oldest samples when you hit your Max Stored Samples cap, keeping memory usage stable.
Compute synthetic-space statistics
The script computes an SMA over the last N synthetic closes and basic descriptors like average bars per synthetic sample, mean and standard deviation of synthetic returns, and more. These are all in event time , not clock time.
Inputs and options you will actually use
Data Settings
Sampling Method : Volume or Dollar Bars.
Rolling Lookback : window used to estimate the dynamic threshold from recent activity.
Filter : Mean or Median for the dynamic threshold. Median is more robust to spikes.
Use Fixed? / Fixed Threshold : override dynamic sizing with a constant target.
Max Stored Samples : cap on synthetic history to keep performance snappy.
Use Ring Buffer : turn on to recycle storage when at capacity.
Indicator Settings
SMA over last N samples : moving average in synthetic space . Because its index is sample count, not minutes, it adapts naturally: more updates in busy regimes, fewer in quiet regimes.
Visuals
Show Synthetic Bars : plot the synthetic OHLC candles.
Candle Color Mode :
Green/Red: directional close vs open
Volume Intensity: opacity scales with synthetic size
Neutral: single color
Adaptive: graded by how large the bucket was relative to threshold
Mark new samples : drop a small marker whenever a new synthetic bar prints.
Comparison & Research
Show Time Bars : overlay the native time-based candles to visually compare how the two sampling schemes differ.
How to read it, step by step
Turn on “Synthetic Bars” and optionally overlay “Time Bars.” You will see that during high-activity bursts, synthetic bars print much faster than time bars.
Watch the synthetic SMA . Crosses in synthetic space can be more meaningful because each update represents a roughly comparable amount of traded information.
Use the “Avg Bars per Sample” in the info table as a regime signal. Falling average bars per sample means activity is clustering, often coincident with higher realized volatility.
Try Dollar Bars when price varies a lot but share count does not; they normalize by dollar risk taken in each sample. Volume Bars are ideal when share count is a better proxy for information flow in your instrument.
Quant finance background and citations
Event time vs. clock time : Easley, López de Prado, and O’Hara advocate measuring intraday phenomena on a volume clock to better align sampling with information arrival. This framing helps explain volatility bursts and liquidity droughts and motivates volume-based bars.
Flow toxicity and dealer risk : The same authors show how adverse selection risk changes with the intensity and informativeness of order flow, further supporting activity-based clocks for modeling and risk management.
AFML framework : In Advances in Financial Machine Learning , event-driven bars such as volume, dollar, and imbalance bars are presented as superior sampling units for many ML tasks, yielding more stationary features and fewer microstructure distortions than fixed time bars. ( Alpaca )
Practical use cases
1) Regime-aware moving averages
The synthetic SMA in event time is not fooled by quiet periods: if nothing of consequence trades, it barely updates. This can make trend filters less sensitive to calendar drift and more sensitive to true participation.
2) Breakout logic on “equal-information” samples
The script exposes simple alerts such as breakout above/below the synthetic SMA . Because each bar approximates a constant amount of activity, breakouts are conditioned on comparable informational mass, not arbitrary time buckets.
3) Volatility-adaptive backtests
If you use synthetic bars as your base data stream, most signal rules become self-paced : entry and exit opportunities accelerate in fast markets and slow down in quiet regimes, which often improves the realism of slippage and fill modeling in research pipelines (pair this indicator with strategy code downstream).
4) Regime diagnostics
Avg Bars per Sample trending down: activity is dense; expect larger realized ranges.
Return StdDev (synthetic) rising: noise or trend acceleration in event time; re-tune risk.
Interpreting the info panel
Method : your sampling choice and current threshold.
Total Samples : how many synthetic bars have been formed.
Current Vol/Dollar : how much of the next bucket is already filled.
Bars in Bucket : native bars consumed so far in the current bucket.
Avg Bars/Sample : lower means higher trading intensity.
Avg Return / Return StdDev : return stats computed over synthetic closes .
Research directions you can build from here
Imbalance and run bars
Extend beyond pure volume or dollar thresholds to imbalance bars that trigger on directional order flow imbalance (e.g., buy volume minus sell volume), as discussed in the AFML ecosystem. These often further homogenize distributional properties used in ML. alpaca.markets
Volume-time indicators
Re-compute classical indicators (RSI, MACD, Bollinger) on the synthetic stream. The premise is that signals are updated by traded information , not seconds, which may stabilize indicator behavior in heteroskedastic regimes.
Liquidity and toxicity overlays
Combine synthetic bars with proxies of flow toxicity to anticipate spread widening or volatility clustering. For instance, tag synthetic bars that surpass multiples of the threshold and test whether subsequent realized volatility is elevated.
Dollar-risk parity sampling for portfolios
Use dollar bars to align samples across assets by notional risk, enabling cleaner cross-asset features and comparability in multi-asset models (e.g., correlation studies, regime clustering). AFML discusses the benefits of event-driven sampling for cross-sectional ML feature engineering.
Microstructure feature set
Compute duration in native bars per synthetic sample , range per sample , and volume multiple of threshold as inputs to state classifiers or regime HMMs . These features are inherently activity-aware and often predictive of short-horizon volatility and trend persistence per the event-time literature. ( Alpaca )
Tips for clean usage
Start with dynamic thresholds using Median over a sensible lookback to avoid outlier distortion, then move to Fixed thresholds when you know your instrument’s typical activity scale.
Compare time bars vs synthetic bars side by side to develop intuition for how your market “breathes” in activity time.
Keep Max Stored Samples reasonable for performance; the ring buffer avoids memory creep while preserving a rolling window of research-grade data.
Advanced Institucional Trading IndicatorThe Advanced Institutional Trading Indicator is a comprehensive technical analysis tool that combines four institutional trading concepts to identify where large market participants hunt liquidity, establish positions, and create supply/demand imbalances. The indicator integrates pivot-based reversal signals, liquidity sweep detection, volumetric order blocks, and equal highs/lows identification into a unified framework for analyzing institutional footprints in the market.
What It Detects
Pivot-Based Reversal Signals: Swing highs/lows marking potential trend reversals
Liquidity Sweeps: False breakouts indicating institutional stop-hunting
Volumetric Order Blocks: Supply/demand zones with buying vs selling pressure ratios
Equal Highs/Lows (EQH/EQL): Liquidity pools where stops cluster
In Practice
Traders can watch for equal highs/lows near order blocks, wait for sweeps of these levels as confirmation of liquidity capture, then look for reversal signals to time entries with the expectation that institutions have now positioned themselves and the true directional move can begin.
Logic used
Pivots: Standard functions with configurable periods, signals when swing type alternates
Sweeps: Detects brief violations of swing levels with cooldown filter
Order Blocks: Three-candle volume split into buying/selling pressure, filtered by ATR
Equal Levels: Compares consecutive pivots within ATR-based threshold
Visual representation
Reversal Signals: Green "Buy-point"/red "Sell-point" labels.
Sweeps: Dashed lines with "Sweep" text and swing markers.
Order Blocks: Colored boxes with volumetric bars and percentages.
Equal Levels: Golden lines with $ symbols.
Customization options
Pivot Length, Cooldown Period, Swing Length, Zone Count (1/3/5/10), ATR Multiplier, Threshold, customizable colors and styles.
Recommendations for use: Lower timeframes use smaller parameters (5-15 pivot, 20-35 swing). Higher timeframes use larger (20-50 pivot, 50-100 swing). Adjust for volatility.
Originality and value
While this indicator utilizes established concepts from institutional trading methodology (particularly Smart Money Concepts and ICT principles), its value proposition includes:
- Integration: Combines four complementary analysis tools into a single cohesive framework rather than requiring multiple separate indicators
- Volumetric Enhancement: Adds quantitative volume analysis to order blocks, showing not just where institutions positioned but how much buying vs selling pressure existed
- Automated Zone Management: Intelligently combines overlapping order blocks to reduce visual noise while preserving essential information
- Intelligent Filtering: Uses ATR-based thresholds for equal highs/lows and maximum order block size, adapting to market volatility
- Coordinated Signaling: All components reference similar swing detection logic, creating alignment between different institutional footprint indicators
Disclaimer
This indicator is a technical analysis tool and does not constitute financial advice.
/////Descripcion en español/////
El Advanced Institutional Trading Indicator combina cuatro conceptos institucionales—reversiones por pivotes, barridos de liquidez, bloques volumétricos y niveles iguales—para identificar dónde grandes participantes cazan liquidez y establecen posiciones.
Qué detecta
1. Reversiones por Pivotes: Máximos/mínimos marcando cambios de tendencia
2. Barridos de Liquidez: Falsas roturas indicando caza de stops institucional
3. Bloques Volumétricos: Zonas oferta/demanda con ratios presión compradora/vendedora
4. Niveles Iguales (EQH/EQL): Pools de liquidez donde se agrupan stops
Cómo usarlo
Observar niveles iguales cerca de bloques, esperar barridos como confirmación de captura de liquidez, entrar con señales de reversión cuando instituciones se han posicionado.
Lógica utilizada
- Pivotes: Funciones estándar configurables, señaliza cuando alternan
- Barridos: Detecta violaciones breves con filtro de enfriamiento
- Bloques: Volumen de tres velas dividido en presión compradora/vendedora, filtrado por ATR
- Niveles Iguales: Compara pivotes consecutivos dentro de umbral ATR
Representación visual
Señales: Etiquetas "Buy/Sell-point" verdes/rojas. Barridos: Líneas punteadas con "Sweep" y marcadores swing. Bloques: Cajas con barras volumétricas y porcentajes. Niveles: Líneas doradas con símbolo $.
Configuraciones clave
Pivot Length, Cooldown Period, Swing Length, Zone Count (1/3/5/10), ATR Multiplier, Threshold, colores y estilos personalizables.
Consejos: Marcos menores usan parámetros pequeños (5-15 pivot, 20-35 swing). Marcos mayores usan grandes (20-50 pivot, 50-100 swing). Ajustar según volatilidad.
Originalidad
Integra cuatro herramientas en un marco. Añade análisis volumétrico a bloques. Combina automáticamente zonas superpuestas. Usa filtrado adaptativo basado en ATR. Alinea componentes con lógica unificada basada en Smart Money/ICT.
Descargo
Herramienta de análisis técnico, no asesoramiento financiero.
One Trade Setup for LifeIndicators are refered from @TFlab and @ChartPrime and @UAlgo
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## Indicator Overview 🚀
**One Trade Setup for Life** is a sophisticated TradingView Pine Script indicator blending Smart Money Concepts (SMC), advanced Price Action, and Liquidity Analysis. It provides signals for structural market moves, trade setups, and custom alerts. This tool is designed for **precision execution**, giving traders a comprehensive edge in diverse market conditions.
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## Key Logic Sections & Explanation
### Smart Money Concept Logic 💸
- **Pivot Lines**: Plots SMC levels based on swing high/low pivots, customizable for wick/body detection and colored to represent bullish or bearish market structure.
- **Market Structure Detection**: Tracks changes such as BOS (Break of Structure) and CHoCH (Change of Character), using real-time breakout logic to highlight structural shifts, confirm reversal setups, and trigger accompanying alerts.
- **Engulfing & Confirmation**: Identifies engulfing candles, confirms market structure changes, and plots colored lines—with shape plots at exact highs/lows for visual clarity.
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### Pure Price Action 📈
- **Swing Detection**: Adjustable bars for detecting swing points, making the indicator sensitive to trend reversals and continuations based on candle closes or wicks.
- **BOS/CHoCH Lines**: Plots dashed, solid, or dotted lines (user-selected) to visualize structural changes in price, adding color-coded markers for transparency.
- **Sentiment Table**: Displays an emoji-based sentiment table at the chart bottom, updating live to quickly gauge overall price action and market mood (bull, bear, neutral emoji).
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### Supertrend Logic 🟩🟥
- **ATR-Based Trend Filter**: Implements Supertrend bands using customizable ATR length, multiplier, and increment. Options include normalization for flexibility in ranging versus trending markets.
- **Multi-Factor Signals**: Detects buy/sell crossovers and plots median/stdev areas for additional confirmation. Users can visually track Supertrend support/resistance as trade triggers.
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### RSI & Activity Analysis 📊
- **RSI Calculation**: Provides customizable RSI length, overbought/oversold thresholds. Candle coloring flips as RSI hits extreme levels, giving immediate visual signals for exhaustion or reversals.
- **Trading Volume Proxy**: Advanced logic computes percentile rankings and plots quintile bands, triggering signal arrows when activity surges above or below key thresholds.
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### Liquidity Sweep & Fair Value Gap Logic 💧
- **Sweep Zones**: Detects price sweeps at key resistance/support lines generated from pivots, marking with labels and enabling sweep alerts.
- **FVG & Mitigation**: Integrates Fair Value Gap (FVG) detection. The indicator can filter FVG zones by aggressiveness, classify supply/demand FVGs, and highlight where price is likely to react for entry or exit.
***
### Support, Resistance, and Swing Levels 🟦🟥
- **Multi-Period SR Lines**: Draws dynamic lines for support/resistance from high/low pivots, adjustable for length and quantity, and visually distinct using color, label, and style options.
- **Main Swing Alerts**: Tracks swing direction, assigns colors, and fires alerts only when direction changes, ensuring traders catch priority momentum shifts.
***
### Detailed Alerts System 🚨
- **Custom Alert Inputs**: Users can toggle alerts for CHoCH, BOS, liquidity structure, high-volume, FVG events, sweep zones, false breakouts, and trigger candles—ensuring critical signals are never missed.
- **On-Chart Graphics**: Circles, arrows, and emoji labels clearly mark confirmation, swings, and reversal points directly on the chart, streamlining decision-making.
***
## Example Markdown Table: Alert Features
| Alert Type | Logic/Trigger | Emoji | Visual Output |
|------------------------|--------------------------------------|-------|---------------------------|
| CHoCH (Change of Char.)| Counter-trend BOS detection | 🔄 | Colored line & arrow |
| BOS (Break of Struct.) | Trend BOS, confirming market shift | 💥 | Line/circle at high/low |
| Liquidity Sweep | Price breaks support/resistance | 💧 | Label "Sweep" + alert |
| FVG Alert | FVG zone formation by aggression | ⚡ | Box highlight + alert |
| Supertrend Trigger | Median/std crossovers | 🟩🟥 | Colored area, Buy/Sell |
***
## Customization, Emoji & Styling 🎨
- **All key inputs are grouped and tooltipped for easy setup.**
- **Charts use emojis for sentiment** and direction, visible on tables and labels.
- **Colors are user-selected** for all markers (pivot, BOS, CHoCH, FVG, SR, swing).
- **Visuals (circles/arrows)** highlight entry, exit, and alert points for instant interpretation—making the script unique and easy to use.
***
## Publication & Use 🌐
This script is covered under the Mozilla Public License 2.0. When publishing, provide the following metadata:
- **Title**: One Trade Setup for Life
- **Description**: A fusion tool combining SMC, price action, advanced liquidity analytics, and market structure detection—with a robust alert system and richly visual trading interface.
**Enjoy clear signals, custom alerts, and visually appealing chart markers—all in one package!** 🏆
ICT First FVG - 9:30am & Custom (v4)ICT First FVG - 9:30am & Custom Time Ranges (v4)
📖 DESCRIPTION
This comprehensive Pine Script indicator identifies and displays Fair Value Gaps (FVGs), Volume Imbalances (VIs), and Liquidity Voids (LVs) based on Inner Circle Trading (ICT) concepts. The indicator offers dual functionality: traditional 9:30am New York session FVG detection and customizable time range analysis for maximum flexibility.
🚀 KEY FEATURES
Dual Detection System
9:30am NY Open FVG: Classic ICT first presentation detection after market open
Custom Time Range FVG: User-configurable time periods for specialized analysis
Independent Operations: Both systems work simultaneously without interference
Separate Controls: Each system has its own settings and previous days configuration
Advanced Gap Detection
Fair Value Gaps (FVG): Three-candle patterns showing price inefficiencies
Volume Imbalances (VI): Single candle volume-related gaps
Liquidity Voids (LV): Areas where price moved too fast, creating liquidity gaps
Consequent Encroachment (CE): Midpoint lines of detected inefficiencies
Precision Sizing System
Multi-Asset Support: Automatic point/pip calculation for Forex, Futures, and Indices
Forex Handling: Specialized pip calculation for major pairs and JPY crosses
Size Filtering: Minimum gap size filter to eliminate noise
Real-Time Display: Shows exact gap sizes in labels (e.g., "15.3 pips" or "12.7 pts")
Professional Visualization
Dual Display Modes: Choose between solid blocks or line representations
Color Coding: Different colors for current vs. previous day imbalances
Smart Labels: Configurable date, time, type, and size information
Extension Options: Extend gaps to session end or current bar
M1 Data Integration
High Accuracy: Uses 1-minute data regardless of chart timeframe
Better Detection: More precise gap identification on higher timeframes
Flexible Usage: Works on any timeframe ≤15 minutes
⚙️ CONFIGURATION GUIDE
General Settings
Visualization Type: Choose "Blocks" for filled areas or "Lines" for boundaries
Previous Days: Number of historical days to display (0 = today only)
Extend Imbalances: Project gaps to session end or current bar
Use M1 Data: Recommended ON for better accuracy
FVG Size Filter
Minimum FVG Size: Filter out gaps smaller than specified points
Enable Filter: Toggle size filtering on/off
🎯 RECOMMENDED MINIMUM SIZES:
USD/JPY: 0.01 points (1 pip)
Gold (XAUUSD): 1.6 points
NQ (Nasdaq-100): 0.2 points
Nasdaq CFD: 2.0 points
Other instruments: Experiment and discover optimal values
Custom FVG System
Enable Custom FVG: Activate secondary time range detection
Custom Time Range: Use session format (e.g., "1430-1600" for 2:30-4:00 PM)
Custom Previous Days: Independent historical period for custom ranges
Custom Label Color: Distinct color for custom time range gaps
Delete Default FVG 9:30: Use when running multiple instances with different timeframes
Imbalance Types
Fair Value Gaps: Main three-candle inefficiency patterns
Include Open/Close Gap: Additional gap calculation method
Volume Imbalances: Single-candle volume-based gaps
Liquidity Voids: Fast price movement gaps
C.E. (Consequent Encroachment): Midpoint reference lines
Label Customization
Show Labels: Toggle date/time information display
Include Time: Add timestamp to labels
Include Type: Display gap type (FVG, VI, LV)
Include Size: Show calculated gap size in points/pips
Position: Configure label placement (left/center/right, top/center/bottom)
Size & Color: Customize label appearance
Visual Styling
Colors: Separate colors for FVG, VI, LV types
Previous Day Colors: Distinct styling for historical gaps
Border Styles: Solid, dashed, or dotted borders
Line Widths: Configurable border thickness
📊 TECHNICAL SPECIFICATIONS
Supported Markets
Forex: All major and minor pairs with proper pip calculation
Futures: ES, NQ, YM, RTY, GC, SI, CL, etc.
Indices: SPX, NDX, DJI, and CFD versions
Stocks: Individual equities (adjust size filter accordingly)
Time Frame Compatibility
Recommended: 1m, 3m, 5m, 15m charts
Maximum: 15-minute timeframe
Optimal: 1m or 5m for best precision
Session Handling
Timezone: America/New_York (Eastern Time)
Default 9:30am: Standard NY market open detection
Custom Sessions: Any time range using HHMM-HHMM format
Weekend Filtering: Automatic exclusion of non-trading days
🔧 USAGE INSTRUCTIONS
Basic Setup
Add indicator to chart (≤15m timeframe recommended)
Enable "Use M1 Data" for accuracy
Set "Minimum FVG Size" based on instrument (see recommendations above)
Configure "Previous Days Imbalances" (5 is good default)
Custom Time Range Setup
Enable "Enable Custom FVG"
Set "Custom Time Range" (e.g., "1430-1600" for 2:30-4:00 PM ET)
Adjust "Custom Previous Days" as needed
Choose distinct "Custom Label Color" for easy identification
Multiple Instance Usage
Add indicator multiple times for different time ranges
Enable "Delete Default FVG 9:30" on additional instances
Use different custom time ranges for each instance
Assign unique colors to distinguish between instances
Label Optimization
Enable size display to see gap magnitude
Position labels to avoid chart clutter
Use appropriate label size for your screen resolution
Consider disabling time display on crowded charts
🎯 PRACTICAL APPLICATIONS
ICT Trading Concepts
First Presentation: Initial FVG after 9:30am NY open
Return to Gap: Price revisiting inefficiency areas
Mitigation Levels: Using FVG boundaries as support/resistance
Liquidity Hunting: Understanding where price seeks efficiency
Multi-Session Analysis
London Close: Set custom range for 1600-1601 London close gaps
Asian Session: Configure overnight inefficiencies
Power Hour: Analyze 1500-1600 ET gaps
Lunch Hour: Study 1200-1300 ET price behavior
Risk Management
Size-Based Filtering: Focus on significant gaps only
Historical Context: Compare current gaps to previous days
Confluence Trading: Combine with other ICT concepts
Session-Specific: Target gaps from specific market sessions
⚠️ IMPORTANT NOTES
Performance Considerations
Maximum Objects: Indicator creates multiple visual elements
Historical Limit: Adjust "Previous Days" to balance history vs. performance
Chart Refresh: Allow time for initial loading on historical data
Data Quality
Broker Dependency: Gap detection accuracy depends on data feed quality
Weekend Gaps: Sunday gaps may appear due to data provider differences
Fast Markets: Extremely volatile periods may create false gaps
Best Practices
Timeframe Consistency: Use same timeframe for analysis and execution
Size Calibration: Adjust minimum sizes based on instrument volatility
Session Awareness: Understand which sessions produce most relevant gaps
Confirmation: Use additional ICT concepts to confirm gap validity
ICT Entry Models (Riz)The ICT Entry Models Indicator is a complete framework built to help traders visualize and apply multiple Institutional concepts on a single chart. Instead of relying on one entry technique, this tool combines 14+ ICT entry models and evaluates them under a unified structure. Each model is detected independently but filtered through a multi-factor confluence engine that considers liquidity, higher-timeframe structure, premium/discount zones, and session context. This ensures only high-probability setups are highlighted.
What This Indicator Does
⦁ Detects and plots ICT-based entry models such as: Fair Value Gaps, Order Blocks, Breakers, Liquidity Grabs, Stop Hunts, Asian Range Breakouts, Silver Bullet setups, Power of Three, Judas Swing, Unicorn model, Market Maker models, Previous Day High/Low breaks, and others.
⦁ Automatically validates entries using higher timeframe confirmation and confluence filters.
⦁ Provides risk management tools with structural stop-loss, ATR-based SL, TP1/TP2 targets, and R:R calculations.
⦁ Displays visual trade labels showing direction, strength, and expected risk/reward.
⦁ Includes a performance dashboard that tracks win rates, session stats, and risk outcomes.
How It Works
Each entry model is activated through custom detection logic. The script checks for key conditions like displacement, imbalance, BOS/CHoCH, liquidity sweeps, and premium/discount zones. When multiple models align, the indicator assigns a signal strength rating.
⦁ Weak setups: Highlighted but marked lower confidence.
⦁ Strong setups: Require confluence of liquidity, structure, and time-based filters (e.g., killzones).
⦁ The indicator then calculates a safe stop-loss placement (always on the correct side of price) and take-profit levels based on Goldbach ratios and volatility expansion.
Inputs
⦁ Model Toggles: Enable/disable individual entry models (e.g., FVG only, OB only, or full confluence).
⦁ Confluence Filters: Higher-timeframe structure, premium/discount zones, volatility thresholds.
⦁ Risk Management Settings: ATR multiplier, fixed SL/TP options, R:R target adjustments.
⦁ Dashboard & Visuals: Choose which stats, labels, and levels appear on chart.
How to Use
1. Apply the indicator to any forex, crypto, or index chart.
2. Select your timeframe. For scalping, use 1–5m with HTF confirmation. For day/swing trades, use 15m–1H with HTF overlays.
3. Toggle your preferred entry models (e.g., FVG + Liquidity Sweep) or enable all for confluence.
4. Watch for strong confluence signals: entry marker + calculated SL/TP + dashboard confirmation.
5. Use the signals as decision support not as automated buy/sell triggers.
Notes & Tips
Best used in liquid markets (Majors, Gold, Indices, BTC/ETH).
HTF confirmation greatly improves accuracy e.g., align 1m entries with 15m structure.
Combining time-based models (Silver Bullet, Killzones) with structural models improves precision.
Disclaimer
This tool is for educational and research purposes only. It is not financial advice, nor does it guarantee profitability. All trading involves risk, and users should test thoroughly before applying live.
Manipulation Ribbon [FxScripts]Manipulation Ribbon
Designed to detect areas of price manipulation by Market Makers vs areas where it is trading in a natural, price-driven state. By identifying zones of control and imbalance, the ribbon provides a clear visualization of where price is being held or artificially displaced, offering key insights into potential future direction.
Indicator Function
Unlike traditional oscillators, the Manipulation Ribbon plots a continuous line or ribbon, with no defined y-axis. The ribbon dynamically adapts to market conditions, allowing the user to spot potential manipulation and price containment vs natural price movement.
Calculation Methodology
The Manipulation Ribbon is derived exclusively from price action. The underlying algorithm evaluates where price is, where it should be and where it’s being held.
The resulting ribbon reflects these dynamics in real time, providing a visual framework for interpreting price behavior at a granular level.
Operational Use: Divergences
The primary use of the Manipulation Ribbon is to locate divergences between price and the ribbon.
There are two distinct types of divergence to look for:
Price Containment: Where the ribbon moves but price doesn’t. This can help identify zones where price is being held, often preceding sharp movements once control is released.
Price Manipulation: Where price moves but the ribbon doesn’t. This can help identify liquidity sweeps, often preceding swift reversals once the liquidity has been taken.
Analytical Scenarios
High Liquidity Sweep: Price forms a higher high while the ribbon forms a lower high. Indicates a liquidity sweep may be occurring at the highs and a potential bearish reversal may be imminent.
Low Liquidity Sweep: Price forms a lower low while the ribbon forms a higher low. Indicates a liquidity sweep may be occurring at the lows and a potential bullish reversal may be imminent.
Top Edge Hold: Upwards movement of the ribbon without price followthrough. Indicates price may be being held at the highs, suggesting Market Makers are artificially holding price down in order to create a top edge and potential bearish reversal.
Bottom Edge Hold: Downwards movement of the ribbon without price followthrough. Indicates price may be being held at the lows, suggesting Market Makers are artificially holding price up in order to create a bottom edge and potential bearish reversal.
Settings
Guides: Option to have dynamic guides applied to your chart. Customizable style, color and width.
Guide Lookback: Due to the ribbon having a non-standard y-axis scale, it’s not possible to plot standard interval guides. Due to technical limitations this value is not calculable automatically either. The upper and lower bounds of the guides are therefore calculated using a user-inputted lookback function. In order to ensure the guides use the correct y-axis on the chart, simply input the average number of bars in your current viewport using the ruler, the guides will automatically update to match this.
Line 1 / Band 1: Option to turn on/off Line 1 and Band 1 alongside updating color and linewidth. Line 1 and Band 1 use the current chart symbol as their source.
Line 2 / Band 2: Option to add a second line and/or band to the chart. Use this to compare any correlated instrument e.g. BTCUSDT and ETHUSDT (as visualized in the chart above) or other pairs such as XAUUSD/XAUEUR or ES/NQ. Due to differences in y-axis scaling it's advised to add this as an additional indicator on a new pane (as per chart above).
Inverse Line 2 / Band 2: Option to show/hide the inverse of Line 2 and Band 2. This is useful for comparing inversely correlated symbols e.g. EURUSD and USDCHF.
Performance and Optimization
Backtesting Results: The Manipulation Ribbon has undergone extensive backtesting across various instruments, timeframes and market conditions, demonstrating strong performance in identifying where price is out of sync with its natural state. User backtesting is strongly encouraged as it allows traders to gain familiarity with the ribbon using their preferred instruments and timeframes.
Optimization for Diverse Markets: The Manipulation Ribbon can be used on crypto, forex, indices, commodities and stocks. The Manipulation Ribbon's algorithmic foundation ensures consistent performance across a variety of instruments. The lack of complex settings makes it easy for the trader to set up and go.
Educational Resources and Support
Users of the Manipulation Ribbon benefit from comprehensive educational resources and full access to FxScripts Support. This ensures traders can maximize the potential of the Manipulation Ribbon and other tools in the Sigma Indicator Suite by learning best practices and gaining insights from an experienced team of traders.
RT-Signal LiteRT-Signal Lite — Learning & Price-Action Companion (EN)
Protected script – source code is not visible. Educational tool for learning structured entries, filters and risk management.
What it is
RT-Signal Lite is a learning-first price-action indicator that helps you turn chart context into repeatable entries. It combines a score engine (trend, momentum, volume, divergences) with optional pattern/structure filters, a clear signal panel, and a visual TP/SL ladder in R-multiples.
How it helps you learn
• Practice exact entry logic (Cross/Pullback/Breakout with optional Retest).
• See why a setup is allowed or blocked (FVG/HTF proximity, ADX/DI, Volume Z, Liquidity sweep etc.).
• Train risk thinking with R-based TP ladder, BE/Trailing, “SL-Fishing” concept and a compact monthly performance table (educational only).
• Multi-TF RSI panel + simple market labels keep the big picture in view.
• Works great in Replay mode for bar-by-bar drills.
Quick start
Pick a supported timeframe (3/5/15/30/45/60/240/D by default; or add your own in Settings → Timeframe-Gate).
Choose an Entry Mode : CrossOnly / Pullback / Breakout (with ATR buffer) / Retest / Any.
Keep default risk presets (ATR or Structure SL, TP1 in R, step in R, optional BE/Trailing).
Read the Signal Box : direction, Entry/SL/SL-Fishing, TP1…TPn, status, VIX/VDAX state, score & confidence.
Use Trend Box for MTF RSI and a quick checklist (Breakout, Volume OK, Divergence, VIX allowed).
Train in Replay → journal your decisions.
Main features (Lite)
• Entry engine : SMA cross, EMA pullback bounce, prior HH/LL breakout with ATR buffer, optional strict Retest window; candlestick assists (Hammer/Shooting Star, Engulfing, Morning/Evening Star, Doji, Inside Bar, 3 Soldiers/Crows).
• Filters : ADX/DI thresholds (TF-aware), Volume (level & Z-score), RSI divergences (pivot-anchored), ATR/Close regime, FOMO-bar guard, Liquidity sweep window, Opposite Order-Block distance, FVG zone gating, HTF zone proximity, optional VIX/VDAX gate (auto picks VDAX for DAX).
• Structure : Support/Resistance lines, classical FVG (lifetime & mitigation), robust Order-Blocks with separate states and mitigation logic.
• Scanners : Triangle breakout (Lite).
• Risk & exits : Structure/ATR SL, SL-Fishing buffer, TP ladder in R (TP1…TPn), optional BE & Trailing after TP1, cooldown, max bars in trade.
• UI : Signal Box, Trend Box, local trade boxes/lines (entry/sl/tp), watermark, monthly performance table (one outcome per trade: highest TP or SL-Fishing; counted by exit/entry month – for learning only).
• Alerts : Alerts are available in PRO only.
• Privacy : Compiled & protected; source code is not visible.
Key inputs (short list)
Entry mode • Breakout ATR buffer • Retest window/strict • Pullback bounce •
Risk: min R:R, Structure/ATR SL, ATR multiplier, TP ladder, BE/Trail, Cooldown •
Filters: ADX/DI, Volume/Z, ATR regime, RSI limits, FVG/HTF gates, Liquidity sweep, Opp. OB distance •
Scanners: Triangle (Lite) • RSI-MTF toggles • Visuals (Signal/Trend boxes, SR, OB/FVG).
Markets & timeframes
Indices (US/DE), commodities, crypto, forex, stocks.
Works on the whitelisted/custom TFs (e.g., 3/5/15/30/45/60/240/D). Heikin-Ashi and some feeds may change results; volume-based filters need reliable volume.
Best practice (learning workflow)
• Start with 5m/15m/1h on liquid symbols.
• Train in Replay: define entry, see blockers, adjust rules, collect screenshots.
• Move to live observation (paper/sim) only after you can explain every entry/avoidance.
• Use strict risk: position sizing to SL, no over-optimization, no promises.
FAQ — “No signal?” (common blockers)
TF not allowed • Cooldown active • ADX/DI below threshold • VIX/VDAX gate off •
Retest not hit yet • FVG/HTF gate blocking • FOMO bar filtered • Min R:R to next level not met • Opposite OB too close • Liquidity sweep window not satisfied.
PRO upgrade
Adds alerts and extra scanners (Range/Channel/Double-Top/Bottom), more visualization and flexibility. Links are provided inside the script under Settings → Info .
Disclaimer
For educational purposes only. No financial advice. No performance guarantee. Always validate signals in context (structure, liquidity, volatility, news). You are fully responsible for your decisions and risk.
PAT [PieTrader]This Pine Script (//@version=6) is an advanced Price Action Toolkit (PAT) – PieTrader, enhanced by the PieTrader community to combine core Smart Money Concepts into one visual framework. It integrates market structure, liquidity sweeps, order blocks, and dynamic trendlines, with customizable settings for flexibility.
Market Structure (Zigzag): The script tracks trend shifts using a configurable zigzag length. Swing highs and lows are recorded, and optional zigzag lines visualise price movement. Structure shifts are highlighted with Change of Character (CHoCH) or Break of Structure (BoS) labels, providing clear signals of directional intent.
Order Blocks: On detecting structure breaks, bullish and bearish order blocks are marked with ATR-based zones. These are drawn as shaded boxes, with user control over how many remain visible. Invalid or broken blocks are automatically removed to keep the chart clean.
Liquidity Sweeps: Pivot highs and lows over a chosen lookback define liquidity levels. These are shown as horizontal lines that switch to dashed style once swept by price. Markers (“x”) identify sweep points, helping traders spot liquidity grabs. To optimise performance, older levels are deleted beyond a fixed storage limit.
Trendlines: Using pivot detection, the system identifies bullish and bearish trendlines. Valid lines with upward or downward slopes are extended in real time, updating dynamically with price. Bullish lines are teal; bearish lines are red.
Additional Features: A watermark option displays “PieTrader” on the chart, and colour themes are fully customizable.
In summary, the PieTrader community’s enhancements make this toolkit a comprehensive visual aid for analysing market structure, liquidity, and trend alignment within a streamlined charting solution.
ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action
1. Introduction
1.1 Overview
ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active.
The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured:
import TradingView/ta/10 as tvta
// Determine lower timeframe string based on user choice and chart resolution
string lower_tf_breakout = use_custom_tf_input ? custom_tf_input :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
// Request up/down volume (both positive)
= tvta.requestUpAndDownVolume(lower_tf_breakout)
Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity.
Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate.
Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history.
Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”)
2. Price‑Structure Backbone
Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations.
2.1 What it draws
• Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded.
• Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly.
• Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels.
• Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick.
2.2 Key settings
• length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels.
• pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings.
• point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded.
• label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price.
• Styling inputs for trend lines, horizontal lines and labels (color, width and line style).
Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots.
These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle.
The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable.
3. Breakout Module
3.1 Concept
This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled.
3.2 Inputs
• lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly.
• vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout.
• rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution.
• ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases).
• use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe.
• Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width.
3.3 Detection logic
1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume.
2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window.
3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive.
4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history.
5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1).
6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector.
Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move.
Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold.
4. Market Phase Module (Volume Only)
4.1 Concept
Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table.
4.2 Inputs
• phase_period_len: Number of bars over which to compute sums and ratios for phase detection.
• phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume.
• strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation).
• Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles.
• show_phase_module: Toggles the entire phase detection subsystem.
• show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected.
4.3 Detection logic
The module computes three families of statistics over the volume window defined by phase_period_len:
1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends.
2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction.
3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues.
The algorithm then combines these signals:
• For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case.
• For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category.
If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” .
4.4 Outputs
• Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral).
• On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences.
Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began.
Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window.
5. OB/OS Spike Module
5.1 What overbought/oversold means here
In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate.
5.2 Inputs
• minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print.
• syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals.
• Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike.
• Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable.
• Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width.
5.3 Detection logic
1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos.
2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS.
3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold).
4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought.
5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line.
Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels.
Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow.
6. Buyer/Seller Trap Module
6.1 Concept
A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps.
6.2 Inputs
• trap_lookback_len: Window length used to rank extremes and detect sweeps.
• trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep.
• trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.)
• trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed.
• Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps.
• Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart.
6.3 Scoring logic
The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped):
1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick.
2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick.
3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand.
4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa.
5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average.
The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars.
Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label.
Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range.
7. Sharp Move Module
7.1 Concept
Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation.
7.2 Inputs
• sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels.
• sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window.
• sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax.
• sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks.
• sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range).
• sharpScoreRisk: Minimum number of conditions that must be true to print a risk label.
• sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation.
• sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution).
• Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves.
• Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn.
7.3 Conditions (six per side)
For each side, the indicator computes six boolean conditions and sums them to form a score:
1. Dominance (instant and cumulative):
– Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume.
– Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks).
2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish).
3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window.
4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range).
5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile.
6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed.
Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores.
7.4 Scoring and labels
• Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar.
• Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1).
• Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled.
Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move.
Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window.
8. Market‑Maker / Spread‑Capture Module
8.1 Concept
Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets.
8.2 Inputs
• scalpLookback: Window length used to compute volume averages.
• scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple.
• scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement.
• scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%.
• Label settings: ATR length, multiplier, size, colors, connector style and width.
• Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels.
8.3 Signal
When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled.
Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window.
9. Money Flow Module
9.1 Concept
To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow.
9.2 Inputs
• mf_period_len_mf: Number of bars used for summing buy and sell dollars.
• Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width.
• Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed.
9.3 Calculations
• Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $.
• Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum().
• Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate.
• Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences.
Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context.
In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period.
10. Info Table
10.1 Purpose
When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active.
10.2 Symbols
• ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money.
• MA — Moving average. In the table it shows the average value of a series over the lookback period.
• Σ (Sigma) — Cumulative sum over the chosen lookback period.
• Δ (Delta) — Difference between buy and sell values.
• B / S — Buyer and seller share of total volume, expressed as percentages.
• Ref. Price — Reference price for breakout calculations, based on the latest pivot.
• Status — Indicates whether a breakout condition is currently active (True) or has failed.
10.3 Row definitions
1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period.
2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity.
3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period.
4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume.
5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period.
6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume.
7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more.
8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed.
9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral.
10. Money Flow – The final rows display dollar amounts and status:
– ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period.
– ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum.
– Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively.
– Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral.
– Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral.
The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out).
11. Conclusion & Final Remarks
This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart.
A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window.
Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
ICT SIlver Bullet Trading Windows UK times🎯 Purpose of the Indicator
It’s designed to highlight key ICT “macro” and “micro” windows of opportunity, i.e., time ranges where liquidity grabs and algorithmic setups are most likely to occur. The ICT Silver Bullet concept is built on the idea that institutions execute in recurring intraday windows, and these often produce high-probability setups.
🕰️ Windows
London Macro Window
10:00 – 11:00 UK time
This aligns with a major liquidity window after the London equities open settles and London + EU traders reposition.
You’re looking for setups like liquidity sweeps, MSS (market structure shift), and FVG entries here.
New York Macro Window
15:00 – 16:00 UK time (10:00 – 11:00 NY time)
This is right after the NY equities open, a key ICT window for volatility and liquidity grabs.
Power Hour
Usually 20:00 – 21:00 UK time (3pm–4pm NY time), the last trading hour of NY equities.
ICT often refers to this as another manipulation window where setups can form before the daily close.
🔍 What the Indicator Does
Draws session boxes or shading: so you can visually see the London/NY/Power Hour windows directly on your chart.
Macro vs. Micro time frames:
Macro windows → The ones you set (London & NY) are the major daily algo execution windows.
Micro windows → Within those boxes, ICT expects smaller intraday setups (like a Silver Bullet entry from a sweep + FVG).
Guides your trade selection: it tells you when not to hunt trades everywhere, but instead to wait for price action confirmation inside those boxes.
🧩 How This Fits ICT Silver Bullet Trading
The ICT Silver Bullet strategy says:
Wait for one of the macro windows (London or NY).
Look for liquidity sweep → market structure shift → FVG.
Enter with defined risk inside that hour.
This indicator essentially does step 1 for you: it makes those high-probability windows visually obvious, so you don’t waste time trading random hours where algos aren’t active.
