Smart Trader, Episode 04, by Ata Sabanci, Candles and Z ScoresSmart Trader, Episode 04
Candles and Z-Scores: A Statistical Approach to Market Analysis
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
OVERVIEW
This indicator applies Z-Score statistical analysis to measure how unusual current market conditions are compared to historical norms. It simultaneously analyzes five key metrics: Price, Total Volume, Buy Volume, Sell Volume, and Delta (Buy minus Sell) . The system detects 60 academically-researched market scenarios and provides visual feedback through Z-Lines (support/resistance levels), Event Markers, Trend Channels, and a comprehensive Dashboard.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
CORE CONCEPT: WHY Z-SCORE?
A Z-Score measures how many standard deviations a value is from its mean. In financial markets, extreme Z-Scores indicate statistically rare events that often precede significant price movements.
Mathematical Formula:
Z = (Current Value - Mean) / Standard Deviation
Interpretation:
• Z ≥ +2.0: Extremely high (occurs approximately 2.5% of the time)
• Z ≥ +1.0: Above average
• Z ≈ 0: Normal (near the mean)
• Z ≤ -1.0: Below average
• Z ≤ -2.0: Extremely low (occurs approximately 2.5% of the time)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
ACADEMIC FOUNDATION
This indicator is inspired by / grounded in market microstructure literature (abbreviated citations in-script) from market microstructure literature:
• Price-Volume Relationship - Karpoff (1987), Journal of Financial and Quantitative Analysis, Cambridge
Volume is positively correlated with price change magnitude
• Order Flow Imbalance - Cont, Kukanov, Stoikov (2014), Journal of Financial Econometrics
Order imbalance drives price more reliably than raw volume
• Informed Trading (PIN Model) - Easley, Kiefer, O'Hara, Paperman (1996), Journal of Finance
Buy/Sell imbalance reveals informed trader activity
• Mixture of Distributions - Tauchen & Pitts (1983), Clark (1973)
Volume clusters with volatility regimes
• Volume Predictability - Gervais, Kaniel, Mingelgrin (2001)
Volume shocks predict future returns
• Liquidity & Order Imbalance - Chordia, Roll, Subrahmanyam (2002)
Order imbalance affects short-term returns
• Volume-Return Dynamics - Llorente, Michaely, Saar, Wang (2002)
Speculation vs. risk-sharing patterns
• Reversal vs. Continuation - Campbell, Grossman, Wang (MIT)
High volume predicts lower autocorrelation
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
VOLUME ENGINE
The indicator offers two methods for decomposing total volume into Buy and Sell components:
Method 1: Geometry (Approximation)
Uses candle structure to estimate buying and selling pressure:
Buy Volume = Total Volume × (Close - Low) / (High - Low)
Sell Volume = Total Volume × (High - Close) / (High - Low)
• Works on all instruments without additional data requirements
• Fast calculation
• Less precise than intrabar method
Method 2: Intrabar (Precise)
Uses Lower Timeframe (LTF) tick/second data to aggregate actual up-ticks versus down-ticks:
• More accurate volume decomposition
• Requires LTF data availability
• Configurable LTF: 1T (tick), 1S, 15S, 1M
Delta Calculation:
Delta = Buy Volume - Sell Volume
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Z-SCORE SYSTEM
The system calculates Z-Scores for five metrics simultaneously, using a configurable lookback period (default: 20 bars):
• Zp (Price Z-Score): Measures price deviation from its mean
• Zv (Volume Z-Score): Measures total volume deviation
• Zbuy (Buy Volume Z-Score): Measures buying pressure deviation
• Zsell (Sell Volume Z-Score): Measures selling pressure deviation
• ZΔ (Delta Z-Score): Measures order flow imbalance deviation
Threshold Constants:
• ZH (Z High) = 2.0: Extreme threshold
• ZM (Z Medium) = 1.0: Moderate threshold
• Z0 (Z Zero) = 0.5: Near-zero threshold
Group System:
The analysis window is divided into groups (default: 5 groups × 20 bars = 100 bar total window). Group numbers (1, 2, 3...) are displayed above candles when enabled, helping identify the relative age of detected levels.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Z-LINES (SUPPORT/RESISTANCE LEVELS)
When any metric reaches an extreme Z-Score, the system marks that price level as a significant support or resistance zone.
Detection Logic:
• Upper Z-Line: Drawn from the HIGH when Z ≥ upper threshold (default +2.0)
• Lower Z-Line: Drawn from the LOW when Z ≤ lower threshold (default -2.0)
Multi-Metric Detection:
Z-Lines can be triggered by any of the five metrics (Price, Volume, Buy, Sell, Delta). When multiple metrics trigger at similar price levels, they are clustered together into a single combined label showing all contributing metrics.
Persistence:
Z-Lines persist for the entire analysis window (Period × Groups bars) and are NOT removed when price touches them. This allows traders to see historical support/resistance levels that may still be relevant.
Anti-Overlap System:
Labels are automatically repositioned to prevent overlap. The "Label Min Gap (%)" setting controls minimum vertical separation between ALL labels (both upper and lower), ensuring readability even when multiple levels cluster together.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
EVENT DETECTION ENGINE (60 SCENARIOS)
The system analyzes 60 distinct market scenarios based on Z-Score combinations. Each scenario is derived from academic research and assigned a confidence score based on signal strength and alignment.
Notation:
• Zp = Price Z-Score
• Zv = Total Volume Z-Score
• Zbuy = Buy Volume Z-Score
• Zsell = Sell Volume Z-Score
• ZΔ = Delta Z-Score
• dirP = Price direction (+1 if Zp > 0.5, -1 if Zp < -0.5, else 0)
• = Previous bar value
• ZH = 2.0 (High threshold)
• ZM = 1.0 (Medium threshold)
• Z0 = 0.5 (Zero threshold)
─────────────────────────────────────────────────────────────
CATEGORY A: PRICE-VOLUME (Events 1-10)
Based on: Karpoff (1987), Tauchen-Pitts (1983), Clark (1973)
─────────────────────────────────────────────────────────────
Event 1: Breakout Confirmed
|Zp| ≥ ZH AND Zv ≥ ZH AND sign(ZΔ) = dirP AND dirP ≠ 0
Direction: Bullish/Bearish (follows price direction)
Event 2: Trend Strength Confirmed
|Zp| ≥ ZH AND Zv ≥ ZH
Direction: Follows price direction
Event 3: Fragile Move
|Zp| ≥ ZH AND Zv ≤ -ZM
Direction: Warning (price move without volume support)
Event 4: Weak Rally
Zp ≥ ZH AND Zv ≤ -ZH
Direction: Warning (price up without volume)
Event 5: Weak Selloff
Zp ≤ -ZH AND Zv ≤ -ZH
Direction: Warning (price down without volume)
Event 6: Momentum Build
ZM ≤ |Zp| < ZH AND Zv ≥ ZH
Direction: Follows price direction
Event 7: Churn
|Zp| ≤ Z0 AND Zv ≥ ZH
Direction: Neutral (high volume, low price movement)
Event 8: Quiet Compression
|Zp| ≤ Z0 AND Zv ≤ -ZH
Direction: Neutral (low volume, low price movement)
Event 9: High Volume Regime
Zv ≥ ZH
Direction: Neutral
Event 10: Low Volume Regime
Zv ≤ -ZH
Direction: Neutral
─────────────────────────────────────────────────────────────
CATEGORY B: ORDER-FLOW / DELTA (Events 11-16)
Based on: Cont, Kukanov, Stoikov (2014), Easley, Kiefer, O'Hara, Paperman (1996)
─────────────────────────────────────────────────────────────
Event 11: Imbalance Drives Price
|ZΔ| ≥ ZH AND sign(ZΔ) = dirP AND dirP ≠ 0
Direction: Follows price direction (dirP), with delta alignment required
Event 12: Divergence Top
Zp ≥ ZH AND ZΔ ≤ -ZH
Direction: Warning (distribution at top)
Event 13: Divergence Bottom
Zp ≤ -ZH AND ZΔ ≥ ZH
Direction: Warning (accumulation at bottom)
Event 14: Absorption Positive
|Zp| ≤ Z0 AND Zv ≥ ZH AND ZΔ ≥ ZH
Direction: Bullish (buy absorption, support forming)
Event 15: Absorption Negative
|Zp| ≤ Z0 AND Zv ≥ ZH AND ZΔ ≤ -ZH
Direction: Bearish (sell absorption, resistance forming)
Event 16: Depth Wall
Zv ≥ ZH AND |ZΔ| ≥ ZH AND |Zp| ≤ Z0
Direction: Neutral (market depth absorbing)
─────────────────────────────────────────────────────────────
CATEGORY C: BUY VS SELL (Events 17-23)
Based on: Easley, Kiefer, O'Hara, Paperman (1996), Chordia, Roll, Subrahmanyam (2002)
─────────────────────────────────────────────────────────────
Event 17: Aggressive Buy Dominance
Zbuy ≥ ZH AND ZΔ ≥ ZH AND Zsell ≤ -ZM
Direction: Bullish
Event 18: Aggressive Sell Dominance
Zsell ≥ ZH AND ZΔ ≤ -ZH AND Zbuy ≤ -ZM
Direction: Bearish
Event 19: Two-Sided Battle
Zbuy ≥ ZH AND Zsell ≥ ZH AND |ZΔ| ≤ Z0
Direction: Neutral (buyers and sellers equally strong)
Event 20: Battle with Buy Edge
Zbuy ≥ ZH AND Zsell ≥ ZH AND ZM ≤ ZΔ < ZH
Direction: Bullish
Event 21: Battle with Sell Edge
Zbuy ≥ ZH AND Zsell ≥ ZH AND -ZH < ZΔ ≤ -ZM
Direction: Bearish
Event 22: Hidden Accumulation
Zbuy ≥ ZH AND |Zp| ≤ Z0 AND Zv ≥ ZH
Direction: Bullish (buy shock without price movement)
Event 23: Hidden Distribution
Zsell ≥ ZH AND |Zp| ≤ Z0 AND Zv ≥ ZH
Direction: Bearish (sell shock without price movement)
─────────────────────────────────────────────────────────────
CATEGORY D: PREDICTABILITY (Events 24-26)
Based on: Gervais, Kaniel, Mingelgrin (2001), Karpoff (1987)
─────────────────────────────────────────────────────────────
Event 24: Volume Shock Positive Drift
Zv ≥ ZH AND |Zp| ≤ ZM
Direction: Follows price direction
Event 25: Volume Shock Negative Drift
Zv ≤ -ZH AND |Zp| ≤ ZM
Direction: Opposite to price direction
Event 26: Abnormal Volume Info Arrival
Zv ≥ ZH
Direction: Neutral
─────────────────────────────────────────────────────────────
CATEGORY E: REVERSAL VS CONTINUATION (Events 27-30)
Based on: Campbell, Grossman, Wang (MIT), Llorente, Michaely, Saar, Wang (2002)
─────────────────────────────────────────────────────────────
Event 27: High Vol Reversal Risk
Zv ≥ ZH
Direction: Warning (high volume implies lower positive autocorrelation)
Event 28: Low Vol Continuation Risk
Zv ≤ -ZH
Direction: Follows price direction (trend likely continues)
Event 29: Speculation Continuation
Zv ≥ ZH AND |ZΔ| ≥ ZM AND sign(ZΔ) = dirP AND dirP ≠ 0
Direction: Follows price direction
Event 30: Risk Sharing Reversal
Zv ≥ ZH AND |ZΔ| ≤ Z0
Direction: Warning (potential reversal)
─────────────────────────────────────────────────────────────
CATEGORY F: IMBALANCE LAG (Events 31-33)
Based on: Chordia, Roll, Subrahmanyam (2002)
─────────────────────────────────────────────────────────────
Event 31: Persistent Imbalance Push
|ZΔ| ≥ ZM AND |ZΔ | ≥ ZM AND sign(ZΔ) = sign(ZΔ )
Direction: Follows delta direction (persistent pressure)
Event 32: Imbalance Pressure Decay
(ZΔ ≥ ZM AND ZΔ ≤ -ZM) OR (ZΔ ≤ -ZM AND ZΔ ≥ ZM)
Direction: Warning (imbalance sign flip)
Event 33: Intraday Imbalance Predicts
|ZΔ| ≥ ZM
Direction: Follows delta direction
─────────────────────────────────────────────────────────────
CATEGORY G: SUPPORT/RESISTANCE (Events 34-36)
Based on: Peskir (Manchester)
─────────────────────────────────────────────────────────────
Event 34: SR Barrier Event
|Zp| ≤ Z0 AND Zv ≥ ZH
Direction: Neutral (price stalls with high volume)
Event 35: Volume Backed SR Level
|Zp| ≤ Z0 AND Zv ≥ ZH AND |ZΔ| ≥ ZM
Direction: Follows delta direction
Event 36: Volume Poor SR Level
|Zp| ≤ Z0 AND Zv ≤ -ZM
Direction: Warning (weak S/R without volume)
─────────────────────────────────────────────────────────────
CATEGORY H: EXTENDED ANALYSIS (Events 37-50)
Based on: Extended market microstructure analysis
─────────────────────────────────────────────────────────────
Event 37: Climax Buy
Zbuy ≥ ZH AND Zp ≥ ZH AND Zv ≥ ZH
Direction: Warning (extreme buying exhaustion, potential top)
Event 38: Climax Sell
Zsell ≥ ZH AND Zp ≤ -ZH AND Zv ≥ ZH
Direction: Warning (extreme selling exhaustion, potential bottom)
Event 39: Stealth Accumulation
Zbuy ≥ ZM AND |Zp| ≤ Z0 AND Zv ≤ Z0
Direction: Bullish (quiet buying)
Event 40: Stealth Distribution
Zsell ≥ ZM AND |Zp| ≤ Z0 AND Zv ≤ Z0
Direction: Bearish (quiet selling)
Event 41: Volume Divergence Bull
Zp ≤ -ZM AND Zv ≤ -ZM
Direction: Bullish (price down but volume declining)
Event 42: Volume Divergence Bear
Zp ≥ ZM AND Zv ≤ -ZM
Direction: Bearish (price up but volume declining)
Event 43: Delta Price Alignment
|Zp| ≥ ZM AND |ZΔ| ≥ ZM AND sign(Zp) = sign(ZΔ)
Direction: Follows price direction (strong trend confirmation)
Event 44: Extreme Compression
|Zp| ≤ Z0 AND Zv ≤ -ZH
Direction: Neutral (very low volatility)
Event 45: Volatility Expansion
|Zp| ≥ ZH AND Zv ≥ ZH
Direction: Follows price direction (breakout from compression)
Event 46: Buy Exhaustion
Zbuy ≥ ZH AND Zp ≤ Z0
Direction: Warning (high buy but price fails)
Event 47: Sell Exhaustion
Zsell ≥ ZH AND Zp ≥ -Z0
Direction: Warning (high sell but price holds)
Event 48: Trend Acceleration
|Zp| ≥ ZM AND |Zp| > |Zp | AND Zv ≥ ZM
Direction: Follows price direction (increasing momentum)
Event 49: Trend Deceleration
|Zp| ≥ ZM AND |Zp| < |Zp | AND sign(Zp) = sign(Zp )
Direction: Warning (decreasing momentum)
Event 50: Multi Divergence
(Zp ≥ ZM AND ZΔ ≤ -ZM) OR (Zp ≤ -ZM AND ZΔ ≥ ZM) + |Zp| ≥ ZM AND Zv ≤ -ZM
Direction: Warning (multiple divergence signals)
─────────────────────────────────────────────────────────────
CATEGORY I: TREND-INTEGRATED (Events 51-60)
Based on: Combined price-volume-delta trend analysis
─────────────────────────────────────────────────────────────
Event 51: Trend Breakout Confirmed
|Zp| ≥ ZH AND Zv ≥ ZH AND |ZΔ| ≥ ZM AND sign(ZΔ) = dirP AND dirP ≠ 0
Direction: Follows price direction
Event 52: Trend Support Test
Zp ≥ ZM AND Z0 ≤ Zp < ZM AND ZΔ ≥ Z0
Direction: Bullish (pullback in uptrend)
Event 53: Trend Resistance Test
Zp ≤ -ZM AND -ZM < Zp ≤ -Z0 AND ZΔ ≤ -Z0
Direction: Bearish (rally in downtrend)
Event 54: Trend Reversal Signal
sign(Zp) ≠ sign(Zp ) AND |Zp| ≥ ZM AND |Zp | ≥ ZM
Direction: Follows new price direction (momentum flip)
Event 55: Channel Absorption
|Zp| ≤ Z0 AND Zv ≥ ZH
Direction: Neutral (range-bound with volume)
Event 56: Trend Continuation Volume
|Zp| ≥ ZM AND Zv ≥ ZM AND sign(ZΔ) = dirP AND dirP ≠ 0
Direction: Follows price direction (healthy trend with volume)
Event 57: Trend Exhaustion
|Zp| ≥ ZM AND Zv ≤ -ZM AND |Zp| < |Zp |
Direction: Warning (trend losing steam)
Event 58: Range Breakout Pending
|Zp| ≤ Z0 AND Zv ≤ -ZH AND |ZΔ| ≥ ZM
Direction: Follows delta direction (compression with imbalance)
Event 59: Trend Quality High
|Zp| ≥ ZM AND sign(ZΔ) = dirP AND Zv ≥ Z0 AND dirP ≠ 0
Direction: Follows price direction (strong aligned signals)
Event 60: Trend Quality Low
|Zp| ≥ ZM AND sign(ZΔ) ≠ dirP AND dirP ≠ 0
Direction: Warning (conflicting signals)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
TREND CHANNEL SYSTEM
The trend channel system is adapted from Smart Trader Episode 03 to provide consistent visual context for price action analysis.
How It Works:
• Divides the chart into blocks based on Z-Score groups
• Calculates OHLC (Open, High, Low, Close) for each block
• Detects Higher Highs/Higher Lows (uptrend) or Lower Highs/Lower Lows (downtrend) patterns
• Draws channel lines connecting block extremes
• Classifies by angle: steep angles indicate trends, flat angles indicate ranges
Channel Classifications:
• UPTREND: Higher highs and higher lows detected
• DOWNTREND: Lower highs and lower lows detected
• RANGE: Channel angle below threshold (default 10 degrees)
Label Information:
• Trend direction (UPTREND/DOWNTREND/RANGE)
• Channel boundary prices
• Distance from current price (absolute and percentage)
• Channel angle in degrees
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DASHBOARD
The dashboard provides a comprehensive real-time view of all Z-Score metrics and detected events.
Dashboard Sections:
1. Header Row
Displays indicator name and current calculation mode (CLOSED or LIVE).
2. Metric Rows (Price, Total Volume, Buy Volume, Sell Volume, Delta)
Each row displays:
• Value: Current metric value
• Z: Calculated Z-Score
• Visual: Graphical Z-bar showing position relative to mean
• Status: Interpretation (Extreme High, Above Avg, Normal, Below Avg, Extreme Low)
• Upper: Oldest active upper Z-Line in window (Label Mirror)
• Lower: Oldest active lower Z-Line in window (Label Mirror)
3. Event Detection Section
• Count of triggered events out of 60 total scenarios
• Market Bias: Bull/Bear/Neutral percentage with visual bar
• Strongest Event: Highest confidence event currently triggered
• #2 Event: Second highest confidence event
4. Footer
Shows engine type (Geometry/Intrabar), Z-Score period, calculation basis, and number of valid bars.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
ALERT SYSTEM
The indicator uses native alertcondition() functions, keeping the settings menu clean while providing comprehensive alert options in TradingView's alert dialog.
Available Alert Categories:
• Master Alerts: Any event, Any bullish, Any bearish, Any warning
• Single Event Alerts: Individual alerts for key events (Breakout, Climax, Divergence, etc.)
• Category Alerts: Alerts by event category (Price-Volume, Order-Flow, etc.)
• Confluence Alerts: 2+, 3+, 4+, or 5+ aligned events
• Bias Shift Alerts: 10%, 20%, or 30% shifts in market bias
• High Confidence Alerts: Events with 60%+, 70%+, 80%+, or 90%+ confidence
• Divergence Alerts: Price vs Volume or Price vs Delta divergences
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DATA ACCURACY AND LIMITATIONS
This indicator is 100% VOLUME-BASED and requires Lower Timeframe (LTF) intrabar data for accurate calculations when using the Intrabar method.
Data Accuracy Levels:
• 1T (Tick): Most accurate, real volume distribution per tick
• 1S (1 Second): Reasonably accurate approximation
• 15S (15 Seconds): Good approximation, longer historical data available
• 1M (1 Minute): Rough approximation, maximum historical data range
Backtest and Replay Limitations:
• Replay mode results may differ from live trading due to data availability
• For longer backtest periods, use higher LTF settings (15S or 1M)
• Not all symbols/exchanges support tick-level data
• Crypto and Forex typically have better LTF data availability than stocks
A Note on Data Access:
Higher TradingView plans provide access to more historical intrabar data, which directly impacts the accuracy of volume-based calculations. More precise volume data leads to more reliable calculations.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
LANGUAGE SUPPORT (TRI-LINGUAL UI)
This indicator includes a built-in language switch with three interface languages :
• English (EN)
• Türkçe (TR)
• 한국어 (KO)
The selected language updates key interface text such as the Dashboard headers/rows , tooltips , and the Event Engine outputs (event names, category names, and direction labels). Turkish diacritics and Korean Hangul are supported for clean, native readability.
Why only three languages?
Each additional language requires duplicating strings throughout the code, which increases script size/memory usage and compilation time. To keep the indicator optimized and responsive, language options are intentionally limited to three.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ DISCLAIMER
FOR EDUCATIONAL AND RESEARCH PURPOSES ONLY
This indicator is designed as an educational and research tool based on academic market microstructure literature. It is NOT financial advice and should NOT be used as the sole basis for trading decisions.
Important Notices:
• Past performance does not guarantee future results
• All trading involves risk of substantial loss
• The indicator's signals are statistical probabilities, not certainties
• Always conduct your own research and consult qualified financial advisors
• The creator assumes no responsibility for trading losses
Research Sources:
This indicator is built upon peer-reviewed academic research from:
• Journal of Financial and Quantitative Analysis (Cambridge University Press)
• Journal of Finance
• Journal of Financial Econometrics
• MIT Working Papers
• arXiv Financial Mathematics
Bestsignals
Smart Trader, Episode 03, by Ata Sabanci, Candles and TradelinesA volume-based multi-block analysis system designed for educational purposes. This indicator helps traders understand their current market situation through aggregated block analysis, volumetric calculations, trend detection, and an AI-style narrative engine.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DESIGN PHILOSOPHY: CLEAN CHART, RICH DASHBOARD
Traditional indicators often clutter charts with dozens of support/resistance lines, making it difficult to see price action clearly. This indicator takes a different approach:
The Chart:
Displays only the most meaningful, nearest levels (1 up, 1 down) that have not been consumed by price. This keeps your chart clean and focused on what matters right now.
The Dashboard:
Contains all detailed metrics, calculations, and analysis. Instead of drawing 20 lines on your chart, you get comprehensive data in an organized table format.
Why this approach?
• A clean chart allows you to see price action without visual noise
• Fewer but more meaningful levels help focus attention on immediate reference points
• The dashboard provides depth without sacrificing chart clarity
• Beginners can learn chart reading with an uncluttered view while accessing detailed analysis when needed
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1. BLOCK SEGMENTATION
What it does:
Divides the analysis window into fixed-size blocks. Each block contains multiple bars that are analyzed as a single unit.
Why:
Individual bars contain noise. A single red candle in an uptrend might cause unnecessary concern, but when you view 5-10 bars as one block, the overall direction becomes clear. Block segmentation filters out bar-to-bar noise and reveals the underlying structure.
Benefit:
• Clearer view of market structure at a higher aggregation level
• Enables comparison between time periods (Block 1 vs Block 2 vs Block 3)
• Creates the foundation for composite candles and trend detection
• Reduces emotional reaction to single-bar movements
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
2. COMPOSITE CANDLES (FRACTAL CONCEPT)
What it does:
Each block generates a "ghost candle" representing aggregated OHLC:
• Open: First bar's open in the block
• High: Highest high across all bars in the block
• Low: Lowest low across all bars in the block
• Close: Last bar's close in the block
Why:
This is essentially a FRACTAL view of the market. The same candlestick patterns that appear on a daily chart also appear on hourly charts, and on 5-minute charts. By aggregating bars into composite candles, you create a synthetic higher timeframe view without changing your actual timeframe.
Benefit:
• See higher timeframe patterns while staying on your preferred timeframe
• Identify block-level candlestick patterns (Doji, Hammer, Marubozu, Engulfing, etc.)
• Compare composite candle relationships: Does Block 1 engulf Block 2? Is Block 1 an inside bar relative to Block 2?
• Recognize patterns that individual bars obscure due to noise
Fractal Nature:
A hammer pattern means the same thing whether it appears on a 1-minute chart or a weekly chart: price tested lower levels and was rejected. Composite candles let you see these patterns at your chosen aggregation level, providing a multi-scale view of market behavior.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
3. VOLUME ENGINE
What it does:
This indicator is 100% VOLUME-BASED. It separates total volume into buying volume and selling volume using two methods:
Method 1 - Geometric (Approximation):
• Buy Volume = Total Volume × ((Close - Low) / Range)
• Sell Volume = Total Volume × ((High - Close) / Range)
Method 2 - Intrabar LTF (Precise):
Uses actual tick-level or lower timeframe data to determine real buy/sell distribution.
Why:
Raw volume tells you HOW MUCH was traded, but not WHO was aggressive. A large volume bar could mean heavy buying, heavy selling, or both. By separating buy and sell volume, you can identify which side is driving the market.
Benefit:
• Identify whether buyers or sellers are more aggressive
• Detect when volume contradicts price direction (divergence)
• Measure accumulation (buying into weakness) vs distribution (selling into strength)
• Quantify the delta (buy minus sell) to see net pressure
Why Delta Matters:
If price is rising but delta is negative, sellers are actually more aggressive despite the price increase. This divergence often precedes reversals because the price movement lacks volume confirmation.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
4. PIN ANALYSIS (WICK MEASUREMENT)
What it does:
Calculates average upper pin (wick) and lower pin sizes for each block, then tracks how these change across consecutive blocks.
Why:
Upper pins represent price levels that were tested but rejected by sellers. Lower pins represent price levels that were tested but rejected by buyers. The size and direction of pins reveal rejection strength at specific price zones.
Benefit:
• Large upper pins = strong selling pressure at higher levels
• Large lower pins = strong buying support at lower levels
• Increasing upper pins across blocks = intensifying selling pressure
• Decreasing lower pins across blocks = weakening buying support
Why Track Pin Changes:
Pin behavior often changes before price direction changes. If lower pins are shrinking while price is still rising, the buying support that was defending dips is weakening. This is observable data, not prediction.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
5. TREND CHANNEL DETECTION
What it does:
Identifies trend direction using block-level price structure:
• UPTREND: Block highs are higher than previous block highs, AND block lows are higher than previous block lows (HH/HL pattern)
• DOWNTREND: Block highs are lower than previous block highs, AND block lows are lower than previous block lows (LH/LL pattern)
• RANGE: No consistent directional pattern
Once detected, the system draws upper and lower channel boundaries by connecting extreme points within each trend segment.
Why:
HH/HL and LH/LL are the classical definitions of trend. By applying this logic to composite candles (blocks) rather than individual bars, the trend detection becomes more stable and less prone to whipsaws from single-bar noise.
Benefit:
• Clear visual boundaries showing the current trend channel
• Upper channel line = dynamic resistance based on actual price structure
• Lower channel line = dynamic support based on actual price structure
• Channel angle indicates trend strength (steeper = stronger)
• Channel width indicates volatility
Why Lock Trend States:
Once a block's trend classification is determined, it locks and does not change on subsequent recalculations. Without locking, the same block could flip between UP and DOWN repeatedly, creating inconsistent analysis. Locking ensures stability.
Why Project Lines Forward:
Channel lines can be projected into the future to show where support/resistance would be if the current trend continues at the same angle. This is not a prediction; it is a visual reference showing the trend's trajectory.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
6. CORE LEVELS: POC, MAX BUY, MAX SELL
What it does:
Identifies key price levels within each block based on volume data:
POC (Point of Control):
The price level where the highest total volume occurred within the block.
MAX BUY Level:
The bar with the highest buying volume. The HIGH of this bar marks the level.
MAX SELL Level:
The bar with the highest selling volume. The LOW of this bar marks the level.
MIN BUY/SELL Levels:
Optional levels showing where minimum buy/sell volume occurred.
Why:
High volume at a specific price means many participants entered positions there. These participants have a vested interest in that price level. If price returns to that area, those same participants may act to defend their positions.
Benefit:
• POC acts as a volume-based magnet; price tends to revisit high-volume areas
• MAX BUY level shows where buyers committed most aggressively
• MAX SELL level shows where sellers committed most aggressively
• These levels are based on actual transaction data, not arbitrary calculations
Why Consumed Levels Disappear:
When price crosses through a level, that level has been "tested." Keeping consumed levels on the chart creates visual clutter and suggests they are still relevant when they may no longer be. Removing them keeps focus on levels that have not yet been tested.
Why Show Only Nearest Levels:
If you have 20 blocks, you could have 60+ potential levels (POC, MAX BUY, MAX SELL for each). Displaying all of them makes the chart unreadable. Showing only the nearest untested level above and below current price keeps the chart clean while providing immediate reference points.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
7. QUALITY SCORE AND TREND INTELLIGENCE
What it does:
Calculates a quality score (0-100) for the current trend based on multiple factors:
• Angle steepness (stronger trends have steeper angles)
• Delta consistency (does volume support the trend direction?)
• Volume momentum (is participation increasing or decreasing?)
• Body expansion (are candle bodies growing or shrinking?)
• Pin alignment (do pins support the trend direction?)
• Contradiction count (how many factors disagree?)
Why:
Not all trends are equal. A trend with consistent volume support, expanding bodies, and aligned pins is healthier than a trend with contradicting signals. The quality score quantifies this.
Benefit:
• HIGH quality (80+): Multiple factors confirm the trend
• MEDIUM quality (60-79): Some factors confirm, some neutral
• LOW quality (below 60): Multiple contradictions exist
• Strength rating based on channel angle: VERY STRONG, STRONG, MODERATE, WEAK
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
8. NARRATIVE ENGINE
What it does:
Generates a text-based market analysis by synthesizing all calculated data into readable sentences.
How it works:
1. Analyzes current candle: pattern type (Doji, Hammer, Marubozu, etc.), body/wick ratios, range vs ATR
2. Analyzes composite candle: Block 1 pattern and relationship to Block 2 (Engulfing, Inside, Outside)
3. Evaluates trend context: direction, duration, quality, transitions
4. Examines volume data: delta, dominance, momentum direction
5. Checks proximity to key levels: channel boundaries, POC, core levels
6. Identifies divergences: when price and volume directions contradict
7. Produces a coherent narrative describing the current situation
Why:
Numbers and charts require interpretation. The narrative engine translates calculated data into plain language, helping traders understand what the data means in context. This is especially valuable for beginners learning to read charts.
Benefit:
• Synthesizes multiple data points into a coherent story
• Explicitly flags divergences and contradictions
• Describes the current situation without making predictions
• Educational: shows how different factors relate to each other
What the Narrative Does NOT Do:
The narrative describes what IS, not what WILL BE. It does not predict future price movement. It reports the current candle pattern, the current trend state, the current volume situation, and the current proximity to levels.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
9. SMART DASHBOARD
What it does:
Displays all metrics in an organized table with multiple sections.
Sections:
• Volume Engine: Calculation method, data availability, current candle buy/sell/delta
• Trend Volumetrics: Aggregated buy/sell/delta across the current trend, trend type
• Pressure and Momentum: Average pins, pin change percentages, body expansion status
• Trend Channel Boundaries: Upper/lower levels with exact prices, distances, percentages
• Trend Intelligence: Quality score, confidence level, strength rating, volume momentum
Why:
All the detailed calculations need to live somewhere without cluttering the chart. The dashboard provides comprehensive data in a structured format.
Benefit:
• All metrics in one place
• Organized by category for easy reference
• Hover over any label to see a tooltip explaining that metric
• No need to draw dozens of lines on the chart
TIP: Hover over dashboard headers and labels to see tooltips explaining each metric.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
10. LANGUAGE SUPPORT
The indicator supports three languages:
• English
• Türkçe (Turkish)
• हिन्दी (Hindi)
Why only three languages?
Each additional language requires duplicate strings throughout the code, increasing memory usage and compilation time. To keep the script optimized and responsive, language options are limited to these three.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
11. DATA ACCURACY AND LIMITATIONS
This indicator is 100% VOLUME-BASED and requires Lower Timeframe (LTF) intrabar data for accurate calculations.
DATA ACCURACY LEVELS:
• 1T (Tick): Most accurate, real volume distribution per tick
• 1S (1 Second): Reasonably accurate approximation
• 15S (15 Seconds): Good approximation, longer historical data available
• 1M (1 Minute): Rough approximation, maximum historical data range
BACKTEST AND REPLAY LIMITATIONS:
• Replay mode results may differ from live trading due to data availability
• For longer backtest periods, use higher LTF settings (15S or 1M)
• Not all symbols/exchanges support tick-level data
• Crypto and Forex typically have better LTF data availability than stocks
A NOTE ON DATA ACCESS:
Higher TradingView plans provide access to more historical intrabar data, which directly impacts the accuracy of volume-based calculations. More precise volume data leads to more reliable calculations.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
12. SETTINGS OVERVIEW
Main Settings:
• Window Bars: Total bars to analyze
• Group Count: Number of blocks to create
• Calculation Basis: Current bar (live updates) or Closed bar (stable, no repaint)
Block Analytics:
• Show Composite Candle: Toggle ghost candles on/off
• Composite Candle Transparency: Adjust visibility
• Dim Original Candles: Fade original candles when composites are shown
Volume Engine:
• Calculation Method: Geometric (approx) or Intrabar (precise)
• Lower Timeframe: Select LTF for intrabar calculations
Multi-Segment Trend:
• Enable Trend Detection: Toggle trend channels on/off
• Range Angle Threshold: Angle below which trend is classified as RANGE
• Line colors, width, and style
• Project to Future: Extend trend lines forward
Core Calculation:
• Enable Core Calculation: Toggle POC and core levels
• Show POC Nearest Up/Down: Display nearest untested POC levels
• Include MAX/MIN Buy/Sell Levels: Toggle extremes display
• Nearest Only: Show only the closest level above and below price
Market Narrative:
• Enable Market Narrative: Toggle narrative text
• Language selection
• Show Educational Disclaimer: Toggle disclaimer in dashboard
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
EDUCATIONAL PURPOSE
This indicator is designed to help traders:
1. Understand their current market situation at a glance
2. Learn chart reading through block analysis and composite candles
3. See how volume relates to price movement
4. Recognize when technical factors align or contradict
5. Focus on meaningful levels without chart clutter
Whether you are a beginner learning to read charts or an experienced trader seeking a cleaner analytical view, this tool provides structured data to support your analysis.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
IMPORTANT DISCLAIMER
This indicator is for EDUCATIONAL PURPOSES ONLY and does not constitute investment advice. Always conduct your own research and consult with a qualified financial advisor before making investment decisions.
This disclaimer is also displayed within the indicator itself. If you prefer a cleaner chart, you can disable it in Settings under Market Narrative by unchecking Show Educational Disclaimer.
Smart Money Concepts - Absorption Smart Money Concepts - Absorption (SMC-ABS)
Absorption event detector using split-volume VWMA ribbons, entropy filtering, and elasticity validation
Overview
This indicator highlights potential absorption/defense events: moments where price touches a volume-weighted band and then rejects, while additional filters confirm that market conditions are not random/noisy.
What it plots
• Energy ribbons (bands): two split-volume VWMA ribbon sets - Buy-weighted (cyan) and Sell-weighted (magma).
• ABS markers: printed when touch + rejection + validation conditions are met (see Logic section).
• Dashboard (HUD): real-time metrics such as price/volume z-scores, delta, entropy state, and resonance momentum states.
Core logic
1) Volume engine
The script builds Buy Volume and Sell Volume series using one of two modes:
• Geometry (candle-range split): estimates buy/sell participation from the close position within the candle range.
• Intrabar (precise): uses lower-timeframe up/down volume to derive buy/sell flows when data is available.
2) Split-VWMA resonance score
For multiple periods (5, 10, 20, 30, 40, 50), the script computes:
• A standard SMA of price.
• A Buy-weighted VWMA of price (weighted by Buy Volume).
• A Sell-weighted VWMA of price (weighted by Sell Volume).
Resonance is derived from the normalized divergence between the SMA and the split VWMAs, aggregated across the available periods.
3) Validation filters
Signals can be filtered by the following components (each toggleable):
• Volume-weighted entropy: a fractal-efficiency style disorder metric (TR-sum vs range) adjusted by relative volume; high entropy blocks signals.
• Momentum alignment (resonance velocity) : direction filter requiring positive velocity for buy events and negative velocity for sell events.
• Elasticity (recoil vs penetration): rejection quality check based on the bounce-back strength relative to the penetration depth into the fast band.
Absorption event conditions (ABS markers)
ABS markers are generated using the fastest ribbon band (length 5) for the touch/rejection logic:
• Buy absorption: low touches/penetrates the Buy band and the candle closes back above it, with filters passing.
• Sell absorption: high touches/penetrates the Sell band and the candle closes back below it, with filters passing.
Note: acceleration/deceleration is displayed in the HUD as a state; the primary directional filter is the resonance velocity.
Settings
• Volume Model: choose Geometry or Intrabar.
• Intrabar LTF: lower timeframe used by the Intrabar model (only applies when Intrabar is selected).
• Global Lookback: lookback window used for z-score statistics and related calculations.
• Quantum Filters: toggles and thresholds for entropy, momentum alignment, and elasticity validation.
• Dashboard Settings :/ Energy Ribbons / Absorption Events: controls for visuals and filtering behavior.
Usage notes and limitations
• Signals are most reliable after candle close. On the forming candle, conditions can change until the bar closes.
• Results depend on the availability and quality of volume data for the selected symbol and exchange.
• The Geometry mode is an estimate based on candle structure; it is not tick-accurate order flow.
• Terms such as “quantum” and “physics” are metaphorical labels for statistical filters and validation heuristics.
Disclaimer
This tool is provided for analytical and educational use only. It does not constitute investment advice. Trading involves risk.
Important note about Intrabar data and TradingView plan limits
This indicator is volume-dependent. When using the Intrabar model, the best results typically come from very low intrabar timeframes such as 1 tick or 1 second (if your symbol and data feed support it). Please check your TradingView subscription plan and data entitlements - access to 1-second/1-tick lower timeframes is commonly restricted to higher-tier plans (often referred to as Premium/Ultra tiers). If intrabar data is not available, the script falls back to relative buy/sell volume estimation (Geometry mode), and results may be less precise.
Dynamic Support and Resistance with Trend LinesDynamic Support and Resistance with Trend Lines (DSRTL)
1. Introduction & Methodology
The DSRTL indicator is designed to provide a multidimensional analysis of market structure. Unlike traditional tools that rely solely on price pivots, this script combines Static Volume-based Zones with Dynamic Trend Lines to evaluate the price's position relative to critical market components.
The S/R Identification Technique
Instead of standard pivot points, DSRTL utilizes Volume Analysis to highlight areas of significant trader participation:
- Strategy A:
Matrix Climax: Identifies candles within the lookback period that are near price extremes (Highs/Lows) and coincide with significant buying or selling volume.
- Strategy B:
Volume Extremes: Detects candles with the absolute highest buy/sell volumes within the selected lookback window, creating extreme volume-based S/R zones.
- Result:
This creates Support/Resistance (S/R) zones that are validated by actual market activity, not just price geometry.
Dynamic Trend Lines
To complement the static zones, the indicator employs two adaptive channel methods:
- Pivot Span: Connects recent significant pivots for a fast, reactive trend corridor.
- 5-Point Channel: Segments the lookback period into 5 parts to perform a linear regression analysis, creating a stable and statistically significant channel.
2. Volume Calculation Methodology
Accurate S/R detection requires distinguishing Buy Volume from Sell Volume. DSRTL offers two calculation modes:
- Geometry (Source File): Estimates buy/sell volume based on the Close price's position relative to the High/Low of the candle.
Note: This is an approximation that works on all plan types as it does not require intrabar data.
- Intrabar (Precise): Analyzes historical lower-timeframe data (e.g., 15S) to calculate intrabar-based volume deltas with higher precision compared to the geometric method.
Note: This offers superior accuracy. It requires access to historical intrabar data (depending on your plan limits). For the best analytical results, use this mode if available.
3. The Smart Matrix Engine (3D Analysis)
The core of DSRTL is its dashboard, powered by the "Smart Matrix Engine." This engine evaluates the current price in a multi-layer market structure context (Static Volume Zones + Dynamic Channels + Volume Metrics).:
A. S-State (Static): Where is the price relative to the Volume S/R zones?
B. D-State (Dynamic): Where is the price relative to the Trend Channels?
How to read the Matrix Map:
The dashboard displays a 5x5 grid representing 25 possible market scenarios.
- Rows (S1-S5): Represent the Static State (S1=Breakout, S3=Mid-Range, S5=Breakdown).
- Columns (D1-D5): Represent the Dynamic State (D1=Overextended Up, D3=Neutral, D5=Overextended Down).
- Active Cell: Marked with a dot, indicating the specific intersection of price action and market structure.
4. Matrix Interpretations (The 25 Scenarios)
Below is the detailed logic for every possible state displayed on the dashboard, explaining the Title, Bias, and actionable Signal.
Section I: S1 - Static Breakout (Price > Static Resistance)
The price has cleared the static volume resistance zone.
- S1 / D1: HYPER EXTENSION
Bias: Extreme Bullish
Signal: Caution: Exhaustion Risk. Trail stops tight.
- S1 / D2: RESISTANCE CLASH
Bias: Bullish
Signal: Breakout confirmed but facing immediate dynamic resistance.
- S1 / D3: CHANNEL BREAKOUT
Bias: Strong Bullish
Signal: Ideal Trend Continuation. Look to buy dips.
- S1 / D4: SMART PULLBACK
Bias: Bullish (Pullback)
Signal: A pullback occurring after a breakout. Strong buy opportunity.
- S1 / D5: CONFLICT (DIV)
Bias: Conflict/Reversal
Signal: Major Divergence. Static breakout is failing against dynamic structure. High Risk.
Section II: S2 - Inside Static Resistance
The price is currently testing the overhead resistance zone.
- S2 / D1: WEAK SPIKE
Bias: Neutral/Bullish
Signal: Testing resistance, but short-term overextended.
- S2 / D2: IRON FORTRESS (R)
Bias: Rejection Risk
Signal: Double Resistance (Static + Dynamic). High probability of rejection.
- S2 / D3: TESTING RES
Bias: Neutral
Signal: Consolidating at resistance. Wait for a clear break or rejection.
- S2 / D4: COMPRESSION (UP)
Bias: Conflict (Squeeze)
Signal: Squeezed between Static Resistance and Dynamic Support. Volatility imminent.
- S2 / D5: RES vs DOWN-TREND
Bias: Bearish
Signal: Strong downtrend meeting static resistance. Potential Short entry.
Section III: S3 - Mid-Range
The price is floating between significant Static Support and Resistance.
- S3 / D1: OVERBOUGHT RANGE
Bias: Rejection Risk (OB)
Signal: Overextended within the range. Potential fade (short).
- S3 / D2: RANGE HIGH LIMIT
Bias: Neutral/Bearish
Signal: At the top of the dynamic channel. Look for rejection signs.
- S3 / D3: NEUTRAL / CHOPPY
Bias: Neutral
Signal: Dead Center. Low probability environment. Avoid trading.
- S3 / D4: RANGE DIP BUY
Bias: Neutral/Bullish
Signal: At the bottom of the dynamic channel. Look for bounce signs.
- S3 / D5: WEAK RANGE (OS)
Bias: Bounce Risk (OS)
Signal: Oversold within the range. Potential fade (long).
Section IV: S4 - Inside Static Support
The price is currently testing the floor support zone.
- S4 / D1: SUP vs UP-TREND
Bias: Bullish
Signal: Strong uptrend meeting static support. Potential Long entry.
- S4 / D2: COMPRESSION (DN)
Bias: Conflict (Squeeze)
Signal: Squeezed between Static Support and Dynamic Resistance. Volatility imminent.
- S4 / D3: TESTING SUPPORT
Bias: Neutral
Signal: Consolidating at support. Wait for a bounce or breakdown.
- S4 / D4: IRON FLOOR (S)
Bias: Bounce Risk
Signal: Double Support (Static + Dynamic). High probability of a bounce.
- S4 / D5: WEAK DIP
Bias: Neutral/Bearish
Signal: Testing support, but short-term oversold.
Section V: S5 - Static Breakdown (Price < Static Support)
The price has dropped below the static volume support zone.
- S5 / D1: CONFLICT (DIV)
Bias: Conflict/Reversal
Signal: Major Divergence. Static breakdown is failing. High Risk.
- S5 / D2: BEAR PULLBACK
Bias: Bearish (Pullback)
Signal: A pullback occurring after a breakdown. Strong selling opportunity.
- S5 / D3: CHANNEL BREAKDOWN
Bias: Strong Bearish
Signal: Ideal Trend Continuation (Down). Sell rallies.
- S5 / D4: SUPPORT CLASH
Bias: Bearish
Signal: Breakdown confirmed but facing immediate dynamic support.
- S5 / D5: HYPER DROP (VOID)
Bias: Extreme Bearish
Signal: Caution: Climax risk. Trail stops for shorts.
DISCLAIMER & EDUCATIONAL PURPOSE
This indicator is strictly an educational tool designed to visualize complex market structure concepts. Its primary purpose is to help traders "bridge the gap" between academic theory and real-time market behavior by providing a visual representation of support, resistance, and volume dynamics.
Please Note:
1. Not a Trading Strategy: This script is an analytical assistant, not a standalone "Black Box" trading system. It does not generate buy or sell signals that should be followed blindly.
2. No Financial Advice: The data provided by this tool is for informational purposes only. It is not a recommendation to buy or sell any asset.
3. Risk Warning: Trading involves significant risk. Always use your own judgment, perform your own technical analysis, and use proper risk management. Do not use this tool as the sole basis for your trading decisions.
4. Data Precision & Platform Limits: The "Intrabar (Precise)" calculation mode relies on high-resolution historical data to provide exact results. Access to this specific data depth depends entirely on your platform's subscription capabilities. If your plan does not support this level of historical intrabar data, the Precise mode may have limited coverage. In that case, you should switch to "Geometry" mode for a fully populated view.
Multi Timeframe Bollinger Bands Spectrum [Ata]Multi-Timeframe Bollinger Bands Spectrum
Technical Overview
This script integrates multi-timeframe volatility analysis with volume-derived order flow estimation. By combining Bollinger Bands (statistical deviation) with internal candle volume logic, the indicator qualifies price movements to differentiate between sustained trends, reversals, and exhaustion events.
The system is designed to provide a structural context for price action, visualizing market regimes through a dual-zone spectrum and filtering signals based on the interaction between price location and specific volume thresholds.
Core Logic & Calculation
1. Volume Decomposition Algorithm
Instead of using total volume, the script estimates Buying Pressure vs. Selling Pressure based on the close position relative to the candle's High/Low range:
- Buying Volume (vb): Increases as the close approaches the High.
- Selling Volume (vs): Increases as the close approaches the Low.
This logic allows the detection of directional flow even within standard volume bars.
2. Statistical Spectrum
The indicator renders deviations from the Basis (SMA) as two distinct zones:
- Bullish Zone (Blue): Price positioning between the Basis and Upper Band.
- Bearish Zone (Red): Price positioning between the Basis and Lower Band.
This structure is applied across multiple timeframes (overlay) to visualize the macro trend context without noise.
3. Non-Repainting Execution
To ensure historical accuracy and reliability for backtesting, all higher-timeframe data is requested using "lookahead_off". Signals are confirmed only upon the closure of the respective timeframe's candle.
Signal Definitions
Signals are generated only when specific Volatility and Volume conditions intersect:
Reversal Setups (Reaction to Liquidity)
- WALL: Triggered when price rejects the Upper Band accompanied by Extreme Selling Volume (vs > Limit). This suggests active limit sell orders absorbing the rally.
- FLOOR: Triggered when price rejects the Lower Band accompanied by Extreme Buying Volume (vb > Limit). This suggests active limit buy orders absorbing the drop.
- ABSORP: Identifies absorption near the lower bands where selling pressure is met with passive buying (indicated by lower wicks and relative buy volume).
Momentum Setups (Trend Continuation)
- POWER: Validates a breakout above the Upper Band only if supported by Dominant Buying Volume and a strong candle body.
- PANIC: Validates a breakdown below the Lower Band only if supported by Dominant Selling Volume.
- TRAP: Marks failed breakouts where price exits the bands but volume analysis contradicts the move (e.g., low directional volume).
Exhaustion Setups (Statistical Extremes)
- CLIMAX/CRASH: Identifies anomalies where price deviates significantly from the mean (Extreme Deviation) or when volume reaches unsustainable levels relative to the average, often preceding a mean reversion.
Input Parameters
- Bollinger Logic: Configuration for Length and Standard Deviation Multiplier.
- Volume Thresholds: Adjustable factors for Minimum Volume (Trend) and Extreme Volume (Reversal/Climax).
- Timeframe Layers: Toggle visibility for up to 5 higher timeframes.
- Theme: Adjusts label contrast for Dark/Light backgrounds.
Disclaimer
This indicator is strictly for analytical purposes. It provides a visualization of past market data based on statistical and volumetric formulas. Users should apply their own risk management protocols.
Smart Money Volume Matrix [Ata]Smart Money Volume Matrix
The Smart Money Volume Matrix (SMV Matrix) is an advanced volume-spread analysis (VSA) dashboard and charting tool designed to identify significant market anomalies by analyzing the relationship between price extremes and volume flow.
Unlike traditional indicators that rely solely on moving averages or oscillators, this tool performs a "Snapshot Analysis" of a defined lookback period (default: 100 bars) to rank price action based on Order Flow Dominance. It isolates the Top 10 Highest and Lowest Close prices and scrutinizes the volume behind them to categorize market sentiment into four distinct phases: Distribution, No Demand, Absorption, and Exhaustion.
Core Logic & Methodology
The script operates on a Zero-Lag Snapshot Engine. It does not print historical signals bar-by-bar; instead, it evaluates the current market structure relative to the recent history (Lookback Period).
1. Ranking Engine: The script scans the lookback period to find the Top 10 Highest Closes and Top 10 Lowest Closes.
2. Volume Classification: For each ranked bar, it calculates the "Intrabar Buy/Sell Volume" (or approximates it using candle geometry if Intrabar data is unavailable).
3. Dominance Detection: It compares Buying Volume vs. Selling Volume to determine who is in control at critical price levels.
Signal Classifications (VSA Logic)
The indicator generates labels on the chart and updates the dashboard table based on the following logic:
1. At Price Tops (Resistance Areas):
- Distribution (Supply): High Price + High Total Volume + Sellers Dominant.
Interpretation: Indicates heavy institutional selling into rising prices. Often precedes a reversal.
- Buy Climax: High Price + High Total Volume + Buyers Dominant.
Interpretation: Extreme buying frenzy. While bullish, it often marks a "trap" or temporary top due to exhaustion.
- No Demand: High Price + Low Volume.
Interpretation: Prices drifted higher but lack institutional participation. A sign of weakness.
2. At Price Bottoms (Support Areas):
- Absorption: Low Price + High Total Volume + Buyers Dominant.
Interpretation: Institutional money is absorbing selling pressure (passive buying). A strong sign of accumulation.
- Panic Sell: Low Price + High Total Volume + Sellers Dominant.
Interpretation: Extreme fear. High volume at lows typically indicates capitulation and potential hands-changing.
- Exhaustion: Low Price + Low Volume.
Interpretation: Selling pressure has dried up. The market may float upward due to lack of sellers.
Key Features
- Dashboard Matrix Table:
Displays the exact Close Price, Buy/Sell Volume, and Market State (Group) for the Top 10 ranking bars.
Smart Footer: Automatically detects the active "Resistance Zone" (derived from G1 Distribution levels) and "Support Zone" (derived from G3 Absorption levels) and reports the current price status relative to these zones (e.g., "Testing Resistance", "Breakout", "At Support").
- Smart Zones (Auto S/R):
Automatically draws Support and Resistance boxes extending into the future based on the most significant volume clusters found in the rankings. Includes logic to detect "Flips" (e.g., when Support breaks, it is labeled as a flip to Resistance).
- Average Trend Channels:
Calculates a Linear Regression trend line based specifically on the coordinates of the Top 10 Highs and Top 10 Lows, providing a "Best Fit" channel for the current market structure.
- Visual Clarity:
Labels utilize a "Smart Stacking" algorithm to prevent overlap on the chart. Guide lines connect labels to their respective candles for precise identification.
Settings & Configuration
- Matrix Settings: Lookback Period (default 100 bars) and Top Rank Count.
- Volume Engine: Choose between "Intrabar (Precise)" for accurate order flow or "Geometry (Approx)" for standard volume estimation.
- Visuals: Toggle Table, Labels, Lines, Zones, and Trend Lines. Adjust transparency and font sizes.
IMPORTANT NOTE ON SNAPSHOT LOGIC
This indicator is designed as a Real-Time Dashboard. It continuously updates the "Top 10" list as new candles form. Therefore, a label that appears on a candle may disappear if that candle falls out of the Top 10 ranking or leaves the lookback window. This is intended behavior to ensure the chart always reflects the current most critical levels, rather than a historical record of past signals. It is best used for live market analysis rather than historical back testing.
Disclaimer: This tool is for educational and analytical purposes only. Volume analysis is subjective and should be used in conjunction with other methods of technical analysis.
Trend Line Methods (TLM)Trend Line Methods (TLM)
Overview
Trend Line Methods (TLM) is a visual study designed to help traders explore trend structure using two complementary, auto-drawn trend channels. The script focuses on how price interacts with rising or falling boundaries over time. It does not generate trade signals or manage risk; its purpose is to support discretionary chart analysis.
Method 1 – Pivot Span Trendline
The Pivot Span Trendline method builds a dynamic channel from major swing points detected by pivot highs and pivot lows.
• The script tracks a configurable number of recent pivot highs and lows.
• From the oldest and most recent stored pivot highs, it draws an upper trend line.
• From the oldest and most recent stored pivot lows, it draws a lower trend line.
• An optional filled area can be drawn between the two lines to highlight the active trend span.
As new pivots form, the lines are recalculated so that the channel evolves with market structure. This method is useful for visualising how price respects a trend corridor defined directly by swing points.
Method 2 – 5-Point Straight Channel
The 5-Point Straight Channel method approximates a straight trend channel using five key points extracted from a fixed lookback window.
Within the selected window:
• The window is divided into five segments of similar length.
• In each segment, the highest high is used as a representative high point.
• In each segment, the lowest low is used as a representative low point.
• A straight regression-style line is fitted through the five high points to form the upper boundary.
• A second straight line is fitted through the five low points to form the lower boundary.
The result is a pair of straight lines that describe the overall directional channel of price over the chosen window. Compared to Method 1, this approach is less focused on the very latest swings and more on the broader slope of the market.
Inputs & Menus
Pivot Span Trendline group (Method 1)
• Enable Pivot Span Trendline – Turns Method 1 on or off.
• High trend line color / Low trend line color – Colors of the upper and lower trend lines.
• Fill color between trend lines – Base color used to shade the area between the two lines. Transparency is controlled internally.
• Trend line thickness – Line width for both high and low trend lines.
• Trend line style – Line style (solid, dashed, or dotted).
• Pivot Left / Pivot Right – Number of bars to the left and right used to confirm pivot highs and lows. Larger values produce fewer but more significant swing points.
• Pivot Count – How many historical pivot points are kept for constructing the trend lines.
• Lookback Length – Number of bars used to keep pivots in range and to extend the trend lines across the chart.
5-Point Straight Channel group (Method 2)
• Enable 5-Point Straight Channel – Turns Method 2 on or off.
• High channel line color / Low channel line color – Colors of the upper and lower channel lines.
• Channel line thickness – Line width for both channel lines.
• Channel line style – Line style (solid, dashed, or dotted).
• Channel Length (bars) – Lookback window used to divide price into five segments and build the straight high/low channel.
Using Both Methods Together
Both methods are designed to visualise the same underlying idea: price tends to move inside rising or falling channels. Method 1 emphasises the most recent swing structure via pivot points, while Method 2 summarises the broader channel over a fixed window.
When the Pivot Span Trendline corridor and the 5-Point Straight Channel boundaries align or intersect, they can highlight zones where multiple ways of drawing trend lines point to similar support or resistance areas. Traders can use these confluence zones as a visual reference when planning their own entries, exits, or risk levels, according to their personal trading plan.
Notes
• This script is meant as an educational and analytical tool for studying trend lines and channels.
• It does not generate trading signals and does not replace independent analysis or risk management.
• The behaviour of both methods is timeframe- and symbol-agnostic; they will adapt to whichever chart you apply them to.
Smart Money Dynamics Blocks - Pearson MatrixSmart Money Dynamics Blocks — Pearson Matrix
A structural fusion of Prime Number Theory, Pearson Correlation, and Cumulative Delta Geometry.
1. Mathematical Foundation
This indicator is built on the intersection of Prime Number Theory and the Pearson correlation coefficient, creating a structural framework that quantifies how price and time evolve together.
Prime numbers — unique, indivisible, and irregular — are used here as nonlinear time intervals. Each prime length (2, 3, 5, 7, 11…97) represents a regression horizon where correlation is measured between price and time. The result is a multi-scale correlation lattice — a geometric matrix that captures hidden directional strength and temporal bias beyond traditional moving averages.
2. The Pearson Matrix Logic
For every prime interval p, the indicator calculates the linear correlation:
r_p = corr(price, bar_index, p)
Each r_p reflects how closely price and time move together across a prime-defined window. All r_p values are then averaged to create avgR, a single adaptive coefficient summarizing overall structural coherence.
- When avgR > 0.8 → strong positive correlation (labeled R+).
- When avgR < -0.8 → strong negative correlation (labeled R−).
This approach gives a mathematically grounded definition of trend — one that isn’t based on pattern recognition, but on measurable correlation strength.
3. Sequential Prime Slope and Median Pivot
Using the ordered sequence of 25 prime intervals, the model computes sequential slopes between adjacent primes. These slopes represent the rate of change of structure between two prime scales. A robust median aggregator smooths the slopes, producing a clean, stable directional vector.
The system anchors this slope to the 41-bar pivot — the median of the first 25 primes — serving as the geometric midpoint of the prime lattice. The resulting yellow line on the chart is not an ordinary regression line; it’s a dynamic prime-slope function, adapting continuously with correlation feedback.
4. Regression-Style Parallel Bands
Around this prime-slope line, the indicator constructs parallel bands using standard deviation envelopes — conceptually similar to a regression channel but recalculated through the prime–Pearson matrix.
These bands adjust dynamically to:
- Volatility, via standard deviation of residuals.
- Correlation strength, via avgR sign weighting.
Together, they visualize statistical deviation geometry, making it easier to observe symmetry, expansion, and contraction phases of price structure.
5. Volume and Cumulative Delta Peaks
Below the geometric layer, the indicator incorporates a custom lower-timeframe volume feed — by default using 15-second data (custom_tf_input_volume = “15S”). This allows precise delta computation between up-volume and down-volume even on higher timeframe charts.
From this feed, the indicator accumulates delta over a configurable period (default: 100 bars). When cumulative delta reaches a local maximum or minimum, peak and trough markers appear, showing the precise bar where buying or selling pressure statistically peaked.
This combination of geometry and order flow reveals the intersection of market structure and energy — where liquidity pressure expresses itself through mathematical form.
6. Chart Interpretation
The primary chart view represents the live execution of the indicator. It displays the relationship between structural correlation and volume behavior in real time.
Orange “R+” and blue “R−” labels indicate regions of strong positive or negative Pearson correlation across the prime matrix. The yellow median prime-slope line serves as the structural backbone of the indicator, while green and red parallel bands act as dynamic regression boundaries derived from the underlying correlation strength. Peaks and troughs in cumulative delta — displayed as numerical annotations — mark statistically significant shifts in buying and selling pressure.
The secondary visualization (Prime Regression Concept) expands on this by illustrating how regression behavior evolves across prime intervals. Each colored regression fan corresponds to a prime number window (2, 3, 5, 7, …, 97), demonstrating how multiple regression lines would appear if drawn independently. The indicator integrates these into one unified geometric model — eliminating the need to plot tens of regression lines manually. It’s a conceptual tool to help visualize the internal logic: the synthesis of many small-scale regressions into a single coherent structure.
7. Interpretive Insight
This model is not a prediction tool; it’s an instrument of mathematical observation. By translating price dynamics into a prime-structured correlation space, it reveals how coherence unfolds through time — not as a forecast, but as a measurable evolution of structure.
It unifies three analytical domains:
- Prime distribution — defines a nonlinear temporal architecture.
- Pearson correlation — quantifies statistical cohesion.
- Cumulative delta — expresses behavioral imbalance in order flow.
The synthesis creates a geometric analysis of liquidity and time — where structure meets energy, and where the invisible rhythm of market flow becomes measurable.
8. Contribution & Feedback
Share your observations in the comments:
- The time gap and alternation between R+ and R− clusters.
- How different timeframes change delta sensitivity or reveal compression/expansion.
- Prime intervals/clusters that tend to sit near turning points or liquidity shifts.
- How avgR behaves across assets or regimes (trending, ranging, high-vol).
- Notable interactions with the parallel bands (touches, breaks, mean-revert).
Your field notes help others read the model more effectively and compare contexts.
Summary
- Primes define the structure.
- Pearson quantifies coherence.
- Slope median stabilizes geometry.
- Regression bands visualize deviation.
- Cumulative delta locates imbalance.
Together, they construct a framework where mathematics meets market behavior.
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.
ATAI Volume Pressure Analyzer V 1.0 — Pure Up/DownATAI Volume Pressure Analyzer V 1.0 — Pure Up/Down
Overview
Volume is a foundational tool for understanding the supply–demand balance. Classic charts show only total volume and don’t tell us what portion came from buying (Up) versus selling (Down). The ATAI Volume Pressure Analyzer fills that gap. Built on Pine Script v6, it scans a lower timeframe to estimate Up/Down volume for each host‑timeframe candle, and presents “volume pressure” in a compact HUD table that’s comparable across symbols and timeframes.
1) Architecture & Global Settings
Global Period (P, bars)
A single global input P defines the computation window. All measures—host‑TF volume moving averages and the half‑window segment sums—use this length. Default: 55.
Timeframe Handling
The core of the indicator is estimating Up/Down volume using lower‑timeframe data. You can set a custom lower timeframe, or rely on auto‑selection:
◉ Second charts → 1S
◉ Intraday → 1 minute
◉ Daily → 5 minutes
◉ Otherwise → 60 minutes
Lower TFs give more precise estimates but shorter history; higher TFs approximate buy/sell splits but provide longer history. As a rule of thumb, scan thin symbols at 5–15m, and liquid symbols at 1m.
2) Up/Down Volume & Derived Series
The script uses TradingView’s library function tvta.requestUpAndDownVolume(lowerTf) to obtain three values:
◉ Up volume (buyers)
◉ Down volume (sellers)
◉ Delta (Up − Down)
From these we define:
◉ TF_buy = |Up volume|
◉ TF_sell = |Down volume|
◉ TF_tot = TF_buy + TF_sell
◉ TF_delta = TF_buy − TF_sell
A positive TF_delta indicates buyer dominance; a negative value indicates selling pressure. To smooth noise, simple moving averages of TF_buy and TF_sell are computed over P and used as baselines.
3) Key Performance Indicators (KPIs)
Half‑window segmentation
To track momentum shifts, the P‑bar window is split in half:
◉ C→B: the older half
◉ B→A: the newer half (toward the current bar)
For each half, the script sums buy, sell, and delta. Comparing the two halves reveals strengthening/weakening pressure. Example: if AtoB_delta < CtoB_delta, recent buying pressure has faded.
[ 4) HUD (Table) Display /i]
Colors & Appearance
Two main color inputs define the theme: a primary color and a negative color (used when Δ is negative). The panel background uses a translucent version of the primary color; borders use the solid primary color. Text defaults to the primary color and flips to the negative color when a block’s Δ is negative.
Layout
The HUD is a 4×5 table updated on the last bar of each candle:
◉ Row 1 (Meta): indicator name, P length, lower TF, host TF
◉ Row 2 (Host TF): current ↑Buy, ↓Sell, ΔDelta; plus Σ total and SMA(↑/↓)
◉ Row 3 (Segments): C→B and B→A blocks with ↑/↓/Δ
◉ Rows 4–5: reserved for advanced modules (Wings, α/β, OB/OS, Top
5) Advanced Modules
5.1 Wings
“Wings” visualize volume‑driven movement over C→B (left wing) and B→A (right wing) with top/bottom lines and a filled band. Slopes are ATR‑per‑bar normalized for cross‑symbol/TF comparability and converted to angles (degrees). Coloring mirrors HUD sign logic with a near‑zero threshold (default ~3°):
◉ Both lines rising → blue (bullish)
◉ Both falling → red (bearish)
◉ Mixed/near‑zero → gray
Left wing reflects the origin of the recent move; right wing reflects the current state.
5.2 α / β at Point B
We compute the oriented angle between the two wings at the midpoint B:
β is the bottom‑arc angle; α = 360° − β is the top‑arc angle.
◉ Large α (>180°) or small β (<180°) flags meaningful imbalance.
◉ Intuition: large α suggests potential selling pressure; small β implies fragile support. HUD cells highlight these conditions.
5.3 OB/OS Spike
OverBought/OverSold (OB/OS) labels appear when directional volume spikes align with a 7‑oscillator vote (RSI, Stoch, %R, CCI, MFI, DeMarker, StochRSI).
◉ OB label (red): unusually high sell volume + enough OB votes
◉ OS label (teal): unusually high buy volume + enough OS votes
Minimum votes and sync window are user‑configurable; dotted connectors can link labels to the candle wick.
5.4 Top3 Volume Peaks
Within the P window the script ranks the top three BUY peaks (B1–B3) and top three SELL peaks (S1–S3).
◉ B1 and S1 are drawn as horizontal resistance (at B1 High) and support (at S1 Low) zones with adjustable thickness (ticks/percent/ATR).
◉ The HUD dedicates six cells to show ↑/↓/Δ for each rank, and prints the exact High (B1) and Low (S1) inline in their cells.
6) Reading the HUD — A Quick Checklist
◉ Meta: Confirm P and both timeframes (host & lower).
◉ Host TF block: Compare current ↑/↓/Δ against their SMAs.
◉ Segments: Contrast C→B vs B→A deltas to gauge momentum change.
◉ Wings: Right‑wing color/angle = now; left wing = recent origin.
◉ α / β: Look for α > 180° or β < 180° as imbalance cues.
◉ OB/OS: Note labels, color (red/teal), and the vote count.
◉Top3: Keep B1 (resistance) and S1 (support) on your radar.
Use these together to sketch scenarios and invalidation levels; never rely on a single signal in isolation.
[ 7) Example Highlights (What the table conveys) /i]
◉ Row 1 shows the indicator name, the analysis length P (default 55), and both TFs used for computation and display.
◉ B1 / S1 blocks summarize each side’s peak within the window, with Δ indicating buyer/seller dominance at that peak and inline price (B1 High / S1 Low) for actionable levels.
◉ Angle cells for each wing report the top/bottom line angles vs. the horizontal, reflecting the directional posture.
◉ Ranks B2/B3 and S2/S3 extend context beyond the top peak on each side.
◉ α / β cells quantify the orientation gap at B; changes reflect shifting buyer/seller influence on trend strength.
Together these visuals often reveal whether the “wings” resemble a strong, upward‑tilted arm supported by buyer volume—but always corroborate with your broader toolkit
8) Practical Tips & Tuning
◉ Choose P by market structure. For daily charts, 34–89 bars often works well.
◉ Lower TF choice: Thin symbols → 5–15m; liquid symbols → 1m.
◉ Near‑zero angle: In noisy markets, consider 5–7° instead of 3°.
◉ OB/OS votes: Daily charts often work with 3–4 votes; lower TFs may prefer 4–5.
◉ Zone thickness: Tie B1/S1 zone thickness to ATR so it scales with volatility.
◉ Colors: Feel free to theme the primary/negative colors; keep Δ<0 mapped to the negative color for readability.
Combine with price action: Use this indicator alongside structure, trendlines, and other tools for stronger decisions.
Technical Notes
Pine Script v6.
◉ Up/Down split via TradingView/ta library call requestUpAndDownVolume(lowerTf).
◉ HUD‑first design; drawings for Wings/αβ/OBOS/Top3 align with the same sign/threshold logic used in the table.
Disclaimer: This indicator is provided solely for educational and analytical purposes. It does not constitute financial advice, nor is it a recommendation to buy or sell any security. Always conduct your own research and use multiple tools before making trading decisions.
Volume Based Analysis V 1.00
Volume Based Analysis V1.00 – Multi-Scenario Buyer/Seller Power & Volume Pressure Indicator
Description:
1. Overview
The Volume Based Analysis V1.00 indicator is a comprehensive tool for analyzing market dynamics using Buyer Power, Seller Power, and Volume Pressure scenarios. It detects 12 configurable scenarios combining volume-based calculations with price action to highlight potential bullish or bearish conditions.
When used in conjunction with other technical tools such as Ichimoku, Bollinger Bands, and trendline analysis, traders can gain a deeper and more reliable understanding of the market context surrounding each signal.
2. Key Features
12 Configurable Scenarios covering Buyer/Seller Power convergence, divergence, and dominance
Advanced Volume Pressure Analysis detecting when both buy/sell volumes exceed averages
Global Lookback System ensuring consistency across all calculations
Dominance Peak Module for identifying strongest buyer/seller dominance at structural pivots
Real-time Signal Statistics Table showing bullish/bearish counts and volume metrics
Fully customizable inputs (SMA lengths, multipliers, timeframes)
Visual chart markers (S01 to S12) for clear on-chart identification
3. Usage Guide
Enable/Disable Scenarios: Choose which signals to display based on your trading strategy
Fine-tune Parameters: Adjust SMA lengths, multipliers, and lookback periods to fit your market and timeframe
Timeframe Control: Use custom lower timeframes for refined up/down volume calculations
Combine with Other Indicators:
Ichimoku: Confirm volume-based bullish signals with cloud breakouts or trend confirmation
Bollinger Bands: Validate divergence/convergence signals with overbought/oversold zones
Trendlines: Spot high-probability signals at breakout or retest points
Signal Tables & Peaks: Read buy/sell volume dominance at a glance, and activate the Dominance Peak Module to highlight key turning points.
4. Example Scenarios & Suggested Images
Image #1 – S01 Bullish Convergence Above Zero
S01 activated, Buyer Power > 0, both buyer power slope & price slope positive, above-average buy volume. Show S01 ↑ marker below bar.
Image #2 – Combined with Ichimoku
Display a bullish scenario where price breaks above Ichimoku cloud while S01 or S09 bullish signal is active. Highlight both the volume-based marker and Ichimoku cloud breakout.
Image #3 – Combined with Bollinger Bands & Trendlines
Show a bearish S10 signal at the upper Bollinger Band near a descending trendline resistance. Highlight the confluence of the volume pressure signal with the band touch and trendline rejection.
Image #4 – Dominance Peak Module
Pivot low with green ▲ Bull Peak and pivot high with red ▼ Bear Peak, showing strong dominance counts.
Image #5 – Statistics Table in Action
Bottom-left table showing buy/sell volume, averages, and bullish/bearish counts during an active market phase.
5. Feedback & Collaboration
Your feedback and suggestions are welcome — they help improve and refine this system. If you discover interesting use cases or have ideas for new features, please share them in the script’s comments section on TradingView.
6. Disclaimer
This script is for educational purposes only. It is not financial advice. Past performance does not guarantee future results. Always do your own analysis before making trading decisions.
Tip: Use this tool alongside trend confirmation indicators for the most robust signal interpretation.
Price Statistical Strategy-Z Score V 1.01
Price Statistical Strategy – Z Score V 1.01
Overview
A technical breakdown of the logic and components of the “Price Statistical Strategy – Z Score V 1.01”.
This script implements a smoothed Z-Score crossover mechanism applied to the closing price to detect potential statistical deviations from local price mean. The strategy operates solely on price data (close) and includes signal spacing control and momentum-based candle filters. No volume-based or trend-detection components are included.
Core Methodology
The strategy is built on the statistical concept of Z-Score, which quantifies how far a value (closing price) is from its recent average, normalized by standard deviation. Two moving averages of the raw Z-Score are calculated: a short-term and a long-term smoothed version. The crossover between them generates long entries and exits.
Signal Conditions
Entry Condition:
A long position is opened when the short-term smoothed Z-Score crosses above the long-term smoothed Z-Score, and additional entry conditions are met.
Exit Condition:
The position is closed when the short-term Z-Score crosses below the long-term Z-Score, provided the exit conditions allow.
Signal Gapping:
A minimum number of bars (Bars gap between identical signals) must pass between repeated entry or exit signals to reduce noise.
Momentum Filter:
Entries are prevented during sequences of three or more consecutively bullish candles, and exits are prevented during three or more consecutively bearish candles.
Z-Score Function
The Z-Score is calculated as:
Z = (Close - SMA(Close, N)) / STDEV(Close, N)
Where N is the base period selected by the user.
Input Parameters
Enable Smoothed Z-Score Strategy
Enables or disables the Z-Score strategy logic. When disabled, no trades are executed.
Z-Score Base Period
Defines the number of bars used to calculate the simple moving average and standard deviation for the Z-Score. This value affects how responsive the raw Z-Score is to price changes.
Short-Term Smoothing
Sets the smoothing window for the short-term Z-Score. Higher values produce smoother short-term signals, reducing sensitivity to short-term volatility.
Long-Term Smoothing
Sets the smoothing window for the long-term Z-Score, which acts as the reference line in the crossover logic.
Bars gap between identical signals
Minimum number of bars that must pass before another signal of the same type (entry or exit) is allowed. This helps reduce redundant or overly frequent signals.
Trade Visualization Table
A table positioned at the bottom-right displays live PnL for open trades:
Entry Price
Unrealized PnL %
Text colors adapt based on whether unrealized profit is positive, negative, or neutral.
Technical Notes
This strategy uses only close prices — no trend indicators or volume components are applied.
All calculations are based on simple moving averages and standard deviation over user-defined windows.
Designed as a minimal, isolated Z-Score engine without confirmation filters or multi-factor triggers.
