Smart Fixed Volume Profile [MarkitTick]💡 This comprehensive analysis suite integrates Auction Market Theory, structural gap analysis, and statistical liquidity strain modeling into a single, cohesive toolkit. Designed for traders who require a granular view of institutional order flow, this indicator overlays a Fixed Range Volume Profile with intelligent price gap classification and a volatility-adjusted exhaustion detector. By combining these three distinct analytical dimensions, it allows users to identify value consensus, structural breakouts, and potential market turns driven by liquidity shortages.
✨ Originality and Utility
While standard Volume Profiles display where trading occurred, this script advances the concept by contextually analyzing *how* price arrived at those levels. It solves the problem of isolated analysis by fusing three disparate methodologies:
Contextual Integration: It does not merely show support and resistance; it qualifies moves using "Smart Gaps" (classifying gaps based on market structure) and "Liquidity Strain" (identifying unsustainable price velocity).
Institutional Footprint: The inclusion of an "Unusual Volume" highlighter within the profile bars helps traders spot hidden institutional accumulation or distribution blocks that standard profiles miss.
Hybrid Logic: By combining a fixed-time profile (anchored to specific dates) with dynamic, developing gap analysis, it provides both a static roadmap of the past and a dynamic interpretation of current price action.
🔬 Methodology and Concepts
• Fixed Volume Profile Engine
The core of the indicator constructs a volume distribution histogram over a user-defined time window. It utilizes a custom aggregation engine that:
Fetches higher-timeframe volume and price data to ensure accuracy.
Segments the price range into specific "bins" or rows.
Allocates volume to these bins based on price action within the bar, separating Buying Volume (Up bars) from Selling Volume (Down bars).
Calculates the Point of Control (POC) —the price level with the highest traded volume—and the Value Area , which contains 70% (customizable) of the total volume centered around the POC.
• Smart Gap Logic
The script systematically identifies price gaps and classifies them based on their location relative to market pivots (Highs/Lows):
Breakaway Gaps: Occur when price gaps beyond a significant structural pivot (Lookback High/Low), signaling a potential trend initiation.
Runaway Gaps: Occur within an existing trend without breaking structure, indicating trend continuation.
Exhaustion Gaps: Identified when a gap occurs late in a mature trend (measured by bar count since the last pivot) accompanied by a volume spike, suggesting the trend is overextended.
• Liquidity Strain Detector
This module utilizes a statistical approach to measure market stress. It calculates "Illiquidity" by analyzing the ratio of True Range to Volume (Price Impact).
It applies a Logarithmic transformation to normalize the data.
It calculates a Z-Score (Standard Deviation from the mean) of this impact.
If the Z-Score exceeds a threshold (e.g., 2.0 Sigma) while the trend opposes the price move, it triggers an exhaustion signal, indicating that price is moving too easily on too little volume (thin liquidity).
🎨 Visual Guide
• Volume Profile Elements
Histogram Bars: Horizontal bars representing volume at price. Cyan indicates bullish volume; Red indicates bearish volume.
Unusual Volume Highlight: Bars with volume exceeding the average by a set factor (default 2x) are highlighted with brighter, distinct overlays to denote institutional interest.
POC Line: A solid Yellow line marking the price level with the highest volume.
VAH / VAL Lines: Dashed Blue lines marking the Value Area High and Value Area Low.
Background Box: A grey shaded area encapsulating the entire time and price range of the profile.
• Smart Gap Boxes
Blue Box (Breakaway): Marks the start of a new structural move.
Orange Box (Runaway): Marks continuation gaps in the middle of a trend.
Red Box (Exhaustion): Marks potential trend termination points.
Dotted Lines: Extend from the center of gap boxes to serve as future support/resistance levels. These boxes are automatically deleted if price "fills" or violates the gap level.
Note: This tool incorporates core components from [ Smart Gap Concepts ], optimized for this specific strategy.
• Liquidity Signals
Green Label (SE): "Seller Exhaustion" – Appears below bars in a downtrend when selling pressure is statistically overextended.
Red Label (BE): "Buyer Exhaustion" – Appears above bars in an uptrend when buying pressure is statistically overextended.
Note: This tool incorporates core components from [ Liquidity Strain Detector ], optimized for this specific strategy.
📖 How to Use
• Interactive Range Selection: This indicator features a flexible, interactive input system. Upon adding the script to your chart, execution is paused until the analysis range is defined. You will be prompted to click on the chart twice: first to establish the Start Date and second to establish the End Date. Once these anchor points are confirmed, the indicator will automatically load the data and generate the profile for the selected specific period.
● Strategies for Optimal Anchoring
the optimal starting and ending points for high-probability setups:
Swing Highs and Lows (Trend Analysis):
Anchor the Start Date at a major structural swing high or low and the End Date at the current price using the Extend to Present feature. This identifies the "Fair Value" for the entire price move .
Consolidation/Range Anchoring:
Set the Start Date at the first bar of a sideways range and the End Date at the breakout candle. This reveals the high-node volume clusters that will act as future support or resistance.
Session-Based Anchoring (Intraday):
Align the Start Date with the session open (e.g., London or New York open) to track institutional flow for that specific day .
Event-Driven Anchoring:
Place the Start Date on a significant news event or a Breakaway Gap identified by the script's Gap Engine. This helps determine if the new volume supports the direction of the gap.
Correction Cycles:
During a pullback, anchor the Start Date at the start of the correction to find the Value Area Low (VAL), which often serves as a tactical entry point for a trend continuation.
• Identifying Value:
Use the Value Area to gauge market consensus. Acceptance of price within the VA indicates balance. A breakout above VAH or below VAL suggests the market is searching for new value. The POC often acts as a magnet for price correction.
• Trading Breakouts:
Watch for Breakaway Gaps (Blue) that align with a move out of the Volume Profile's Value Area. This confluence increases the probability of a sustained trend.
• Spotting Reversals:
Combine Exhaustion Gaps (Red) with Liquidity Strain Signals (SE/BE) . If price gaps up into a low-volume node on the profile and prints a "Buyer Exhaustion" signal, it suggests the move is unsupported by liquidity and liable to reverse.
• Support and Resistance:
The extended dotted lines from the Smart Gap boxes act as dynamic support/resistance. A retest of a "Runaway Gap" is often a viable entry point for trend continuation.
⚙️ Inputs and Settings
• Global Profile:
Start/End Date: Define the exact window for the volume profile calculation.
Extend to Present: If checked, the profile updates with live data beyond the end date.
• Profile Settings:
Number of Rows: Determines the vertical resolution (granularity) of the histogram.
Value Area %: Default is 70%, representing one standard deviation of volume distribution.
Placement: Position the profile on the Left or Right of the defined range.
• Liquidity & Gaps:
Unusual Threshold: Multiplier of average volume to highlight institutional bars (default 2.0x).
Structure Lookback: Adjusts the sensitivity of pivot detection for gap classification.
Stress Threshold (Sigma): The Z-Score limit for triggering Liquidity Strain signals (default 2.0).
🔍 Deconstruction of the Underlying Scientific and Academic Framework
• Auction Market Theory (AMT):
The script is grounded in AMT, which posits that the market's primary function is to facilitate trade. The Volume Profile visualizes this by displaying a bell curve of price distribution. The Value Area (typically 70%) corresponds to the First Standard Deviation in a normal Gaussian distribution, representing the area of "Fair Value" where buyers and sellers agree.
• Market Microstructure & Kyle’s Lambda:
The Liquidity Strain module draws conceptually from Kyle’s Lambda, a metric in market microstructure that measures market depth and price impact (Illiquidity). By calculating the ratio of price change (True Range) to Volume, the script approximates the "cost" of moving the market.
• Statistical Z-Score Normalization:
To make the liquidity data actionable, the script applies Z-Score normalization: Z = (X - μ) / σ . This converts raw illiquidity values into standard deviations from the mean. A Z-Score above +2.0 signifies a statistically significant anomaly—an outlier event where price moved excessively relative to the volume traded, often preceding a mean-reversion event.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
ค้นหาในสคริปต์สำหรับ "accumulation"
CandelaCharts - SMT 📝 Overview
The CandelaCharts – SMT indicator is a professional-grade Smart Money Technique (SMT) divergence detector designed to compare price action between correlated markets (intermarket analysis).
It identifies moments where the main chart makes a swing high or low while one or more comparison symbols fail to confirm the move—revealing potential institutional imbalance, distribution, or accumulation .
By automatically detecting pivot-based divergences and drawing clean, contextual lines and labels directly on price, SMT helps traders spot high-probability reversal or continuation zones driven by relative strength and weakness across markets.
📦 Features
Automatic SMT divergence detection – Identifies divergences between the main chart and up to two comparison symbols.
Pivot-based logic – Uses swing highs and swing lows to ensure structurally meaningful SMT signals.
Dual-symbol comparison – Compare the main market against one or two correlated instruments simultaneously.
Bullish & bearish SMT filtering – Show only bullish, bearish, or both divergence types.
Clear visual mapping – Divergence lines are drawn directly between pivots for intuitive price-context reading.
Smart labels – Compact labels display symbol(s), volume, and directional markers.
Detailed tooltips – Hover tooltips include divergence type, symbols involved, prices, volume, timestamps, and pivot settings.
Highly customizable visuals – Control colors, line width, and label styling.
⚙️ Settings
Lookback – Pivot lookback length used to detect swing highs and lows. Higher values produce fewer but more significant SMT signals.
Bias – Control which SMTs are displayed: Both, Bearish or Bullish
Swing High Color – Line and label color for SMT at swing highs.
Swing Low Color – Line and label color for SMT at swing lows.
Line Width – Thickness of SMT divergence lines.
Symbol 1 – Enable and select the first comparison instrument (e.g., NQ vs ES).
Symbol 2 – Enable and select the second comparison instrument (optional).
⚡️ Showcase
Bullish and Bearish SMTs
Bearish SMTs
Bullish SMTs
🚨 Alerts
This indicator does not include built-in alert conditions.
⚠️ Disclaimer
This indicator is provided for educational and informational purposes only and does not constitute financial or investment advice. Trading and investing involve substantial risk, and losses can exceed expectations. Past performance is not indicative of future results. You are solely responsible for your trading decisions. CandelaCharts assumes no liability for any outcomes resulting from the use of this indicator.
BarCoreLibrary "BarCore"
BarCore is a foundational library for technical analysis, providing essential functions for evaluating the structural properties of candlesticks and inter-bar relationships.
It prioritizes ratio-based metrics (0.0 to 1.0) over absolute prices, making it asset-agnostic and ideal for robust pattern recognition, momentum analysis, and volume-weighted pressure evaluation.
Key modules:
- Structure & Range: High-precision bar and body metrics with relative positioning.
- Wick Dynamics: Absolute and relative wick analysis for identifying price rejection.
- Inter-bar Logic: Containment, coverage, and quantitative price overlap (Ratio-based).
- Gap Intelligence: Real body and price gaps with customizable significance thresholds.
- Flow & Pressure: Volume-weighted buying/selling pressure and Money Flow metrics.
isBuyingBar()
Checks if the bar is a bullish (up) bar, where close is greater than open.
Returns: bool True if the bar closed higher than it opened.
isSellingBar()
Checks if the bar is a bearish (down) bar, where close is less than open.
Returns: bool True if the bar closed lower than it opened.
barMidpoint()
Calculates the absolute midpoint of the bar's total range (High + Low) / 2.
Returns: float The midpoint price of the bar.
barRange()
Calculates the absolute size of the bar's total range (High to Low).
Returns: float The absolute difference between high and low.
barRangeMidpoint()
Calculates half of the bar's total range size.
Returns: float Half the bar's range size.
realBodyHigh()
Returns the higher price between the open and close.
Returns: float The top of the real body.
realBodyLow()
Returns the lower price between the open and close.
Returns: float The bottom of the real body.
realBodyMidpoint()
Calculates the absolute midpoint of the bar's real body.
Returns: float The midpoint price of the real body.
realBodyRange()
Calculates the absolute size of the bar's real body.
Returns: float The absolute difference between open and close.
realBodyRangeMidpoint()
Calculates half of the bar's real body size.
Returns: float Half the real body size.
upperWickRange()
Calculates the absolute size of the upper wick.
Returns: float The range from high to the real body high.
lowerWickRange()
Calculates the absolute size of the lower wick.
Returns: float The range from the real body low to low.
openRatio()
Returns the location of the open price relative to the bar's total range (0.0 at low to 1.0 at high).
Returns: float The ratio of the distance from low to open, divided by the total range.
closeRatio()
Returns the location of the close price relative to the bar's total range (0.0 at low to 1.0 at high).
Returns: float The ratio of the distance from low to close, divided by the total range.
realBodyRatio()
Calculates the ratio of the real body size to the total bar range.
Returns: float The real body size divided by the bar range. Returns 0 if barRange is 0.
upperWickRatio()
Calculates the ratio of the upper wick size to the total bar range.
Returns: float The upper wick size divided by the bar range. Returns 0 if barRange is 0.
lowerWickRatio()
Calculates the ratio of the lower wick size to the total bar range.
Returns: float The lower wick size divided by the bar range. Returns 0 if barRange is 0.
upperWickToBodyRatio()
Calculates the ratio of the upper wick size to the real body size.
Returns: float The upper wick size divided by the real body size. Returns 0 if realBodyRange is 0.
lowerWickToBodyRatio()
Calculates the ratio of the lower wick size to the real body size.
Returns: float The lower wick size divided by the real body size. Returns 0 if realBodyRange is 0.
totalWickRatio()
Calculates the ratio of the total wick range (Upper Wick + Lower Wick) to the total bar range.
Returns: float The total wick range expressed as a ratio of the bar's total range. Returns 0 if barRange is 0.
isBodyExpansion()
Checks if the current bar's real body range is larger than the previous bar's real body range (body expansion).
Returns: bool True if realBodyRange() > realBodyRange() .
isBodyContraction()
Checks if the current bar's real body range is smaller than the previous bar's real body range (body contraction).
Returns: bool True if realBodyRange() < realBodyRange() .
isWithinPrevBar(inclusive)
Checks if the current bar's range is entirely within the previous bar's range.
Parameters:
inclusive (bool) : If true, allows equality (<=, >=). Default is false.
Returns: bool True if High < High AND Low > Low .
isCoveringPrevBar(inclusive)
Checks if the current bar's range fully covers the entire previous bar's range.
Parameters:
inclusive (bool) : If true, allows equality (<=, >=). Default is false.
Returns: bool True if High > High AND Low < Low .
isWithinPrevBody(inclusive)
Checks if the current bar's real body is entirely inside the previous bar's real body.
Parameters:
inclusive (bool) : If true, allows equality (<=, >=). Default is false.
Returns: bool True if the current body is contained inside the previous body.
isCoveringPrevBody(inclusive)
Checks if the current bar's real body fully covers the previous bar's real body.
Parameters:
inclusive (bool) : If true, allows equality (<=, >=). Default is false.
Returns: bool True if the current body fully covers the previous body.
isOpenWithinPrevBody(inclusive)
Checks if the current bar's open price falls within the real body range of the previous bar.
Parameters:
inclusive (bool) : If true, includes the boundary prices. Default is false.
Returns: bool True if the open price is between the previous bar's real body high and real body low.
isCloseWithinPrevBody(inclusive)
Checks if the current bar's close price falls within the real body range of the previous bar.
Parameters:
inclusive (bool) : If true, includes the boundary prices. Default is false.
Returns: bool True if the close price is between the previous bar's real body high and real body low.
isPrevOpenWithinBody(inclusive)
Checks if the previous bar's open price falls within the current bar's real body range.
Parameters:
inclusive (bool) : If true, includes the boundary prices. Default is false.
Returns: bool True if open is between the current bar's real body high and real body low.
isPrevCloseWithinBody(inclusive)
Checks if the previous bar's closing price falls within the current bar's real body range.
Parameters:
inclusive (bool) : If true, includes the boundary prices. Default is false.
Returns: bool True if close is between the current bar's real body high and real body low.
isOverlappingPrevBar()
Checks if there is any price overlap between the current bar's range and the previous bar's range.
Returns: bool True if the current bar's range has any intersection with the previous bar's range.
bodyOverlapRatio()
Calculates the percentage of the current real body that overlaps with the previous real body.
Returns: float The overlap ratio (0.0 to 1.0). 1.0 means the current body is entirely within the previous body's price range.
isCompletePriceGapUp()
Checks for a complete price gap up where the current bar's low is strictly above the previous bar's high, meaning there is zero price overlap between the two bars.
Returns: bool True if the current low is greater than the previous high.
isCompletePriceGapDown()
Checks for a complete price gap down where the current bar's high is strictly below the previous bar's low, meaning there is zero price overlap between the two bars.
Returns: bool True if the current high is less than the previous low.
isRealBodyGapUp()
Checks for a gap between the current and previous real bodies.
Returns: bool True if the current body is completely above the previous body.
isRealBodyGapDown()
Checks for a gap between the current and previous real bodies.
Returns: bool True if the current body is completely below the previous body.
gapRatio()
Calculates the percentage difference between the current open and the previous close, expressed as a decimal ratio.
Returns: float The gap ratio (positive for gap up, negative for gap down). Returns 0 if the previous close is 0.
gapPercentage()
Calculates the percentage difference between the current open and the previous close.
Returns: float The gap percentage (positive for gap up, negative for gap down). Returns 0 if previous close is 0.
isGapUp()
Checks for a basic gap up, where the current bar's open is strictly higher than the previous bar's close. This is the minimum condition for a gap up.
Returns: bool True if the current open is greater than the previous close (i.e., gapRatio is positive).
isGapDown()
Checks for a basic gap down, where the current bar's open is strictly lower than the previous bar's close. This is the minimum condition for a gap down.
Returns: bool True if the current open is less than the previous close (i.e., gapRatio is negative).
isSignificantGapUp(minRatio)
Checks if the current bar opened significantly higher than the previous close, as defined by a minimum percentage ratio.
Parameters:
minRatio (float) : The minimum required gap percentage ratio. Default is 0.03 (3%).
Returns: bool True if the gap ratio (open vs. previous close) is greater than or equal to the minimum ratio.
isSignificantGapDown(minRatio)
Checks if the current bar opened significantly lower than the previous close, as defined by a minimum percentage ratio.
Parameters:
minRatio (float) : The minimum required gap percentage ratio. Default is 0.03 (3%).
Returns: bool True if the absolute value of the gap ratio (open vs. previous close) is greater than or equal to the minimum ratio.
trueRangeComponentHigh()
Calculates the absolute distance from the current bar's High to the previous bar's Close, representing one of the components of the True Range.
Returns: float The absolute difference: |High - Close |.
trueRangeComponentLow()
Calculates the absolute distance from the current bar's Low to the previous bar's Close, representing one of the components of the True Range.
Returns: float The absolute difference: |Low - Close |.
isUpperWickDominant(minRatio)
Checks if the upper wick is significantly long relative to the total range.
Parameters:
minRatio (float) : Minimum ratio of the wick to the total bar range. Default is 0.7 (70%).
Returns: bool True if the upper wick dominates the bar's range.
isUpperWickNegligible(maxRatio)
Checks if the upper wick is very small relative to the total range.
Parameters:
maxRatio (float) : Maximum ratio of the wick to the total bar range. Default is 0.05 (5%).
Returns: bool True if the upper wick is negligible.
isLowerWickDominant(minRatio)
Checks if the lower wick is significantly long relative to the total range.
Parameters:
minRatio (float) : Minimum ratio of the wick to the total bar range. Default is 0.7 (70%).
Returns: bool True if the lower wick dominates the bar's range.
isLowerWickNegligible(maxRatio)
Checks if the lower wick is very small relative to the total range.
Parameters:
maxRatio (float) : Maximum ratio of the wick to the total bar range. Default is 0.05 (5%).
Returns: bool True if the lower wick is negligible.
isSymmetric(maxTolerance)
Checks if the upper and lower wicks are roughly equal in length.
Parameters:
maxTolerance (float) : Maximum allowable percentage difference between the two wicks. Default is 0.15 (15%).
Returns: bool True if wicks are symmetric within the tolerance level.
isMarubozuBody(minRatio)
Candle with a very large body relative to the total range (minimal wicks).
Parameters:
minRatio (float) : Minimum body size ratio. Default is 0.9 (90%).
Returns: bool True if the bar has minimal wicks (Marubozu body).
isLargeBody(minRatio)
Candle with a large body relative to the total range.
Parameters:
minRatio (float) : Minimum body size ratio. Default is 0.6 (60%).
Returns: bool True if the bar has a large body.
isSmallBody(maxRatio)
Candle with a small body relative to the total range.
Parameters:
maxRatio (float) : Maximum body size ratio. Default is 0.4 (40%).
Returns: bool True if the bar has small body.
isDojiBody(maxRatio)
Candle with a very small body relative to the total range (indecision).
Parameters:
maxRatio (float) : Maximum body size ratio. Default is 0.1 (10%).
Returns: bool True if the bar has a very small body.
isLowerWickExtended(minRatio)
Checks if the lower wick is significantly extended relative to the real body size.
Parameters:
minRatio (float) : Minimum required ratio of the lower wick length to the real body size. Default is 2.0 (Lower wick must be at least twice the body's size).
Returns: bool True if the lower wick's length is at least `minRatio` times the size of the real body.
isUpperWickExtended(minRatio)
Checks if the upper wick is significantly extended relative to the real body size.
Parameters:
minRatio (float) : Minimum required ratio of the upper wick length to the real body size. Default is 2.0 (Upper wick must be at least twice the body's size).
Returns: bool True if the upper wick's length is at least `minRatio` times the size of the real body.
isStrongBuyingBar(minCloseRatio, maxOpenRatio)
Checks for a bar with strong bullish momentum (open near low, close near high), indicating high conviction.
Parameters:
minCloseRatio (float) : Minimum required ratio for the close location (relative to range, e.g., 0.7 means close must be in the top 30%). Default is 0.7 (70%).
maxOpenRatio (float) : Maximum allowed ratio for the open location (relative to range, e.g., 0.3 means open must be in the bottom 30%). Default is 0.3 (30%).
Returns: bool True if the bar is bullish, opened in the low extreme, and closed in the high extreme.
isStrongSellingBar(maxCloseRatio, minOpenRatio)
Checks for a bar with strong bearish momentum (open near high, close near low), indicating high conviction.
Parameters:
maxCloseRatio (float) : Maximum allowed ratio for the close location (relative to range, e.g., 0.3 means close must be in the bottom 30%). Default is 0.3 (30%).
minOpenRatio (float) : Minimum required ratio for the open location (relative to range, e.g., 0.7 means open must be in the top 30%). Default is 0.7 (70%).
Returns: bool True if the bar is bearish, opened in the high extreme, and closed in the low extreme.
isWeakBuyingBar(maxCloseRatio, maxBodyRatio)
Identifies a bar that is technically bullish but shows significant weakness, characterized by a failure to close near the high and a small body size.
Parameters:
maxCloseRatio (float) : Maximum allowed ratio for the close location relative to the range (e.g., 0.6 means the close must be in the bottom 60% of the bar's range). Default is 0.6 (60%).
maxBodyRatio (float) : Maximum allowed ratio for the real body size relative to the bar's range (e.g., 0.4 means the body is small). Default is 0.4 (40%).
Returns: bool True if the bar is bullish, but its close is weak and its body is small.
isWeakSellingBar(minCloseRatio, maxBodyRatio)
Identifies a bar that is technically bearish but shows significant weakness, characterized by a failure to close near the low and a small body size.
Parameters:
minCloseRatio (float) : Minimum required ratio for the close location relative to the range (e.g., 0.4 means the close must be in the top 60% of the bar's range). Default is 0.4 (40%).
maxBodyRatio (float) : Maximum allowed ratio for the real body size relative to the bar's range (e.g., 0.4 means the body is small). Default is 0.4 (40%).
Returns: bool True if the bar is bearish, but its close is weak and its body is small.
balanceOfPower()
Measures the net pressure of buyers vs. sellers within the bar, normalized to the bar's range.
Returns: float A value between -1.0 (strong selling) and +1.0 (strong buying), representing the strength and direction of the close relative to the open.
buyingPressure()
Measures the net buying volume pressure based on the close location and volume.
Returns: float A numerical value representing the volume weighted buying pressure.
sellingPressure()
Measures the net selling volume pressure based on the close location and volume.
Returns: float A numerical value representing the volume weighted selling pressure.
moneyFlowMultiplier()
Calculates the Money Flow Multiplier (MFM), which is the price component of Money Flow and CMF.
Returns: float A normalized value from -1.0 (strong selling) to +1.0 (strong buying), representing the net directional pressure.
moneyFlowVolume()
Calculates the Money Flow Volume (MFV), which is the Money Flow Multiplier weighted by the bar's volume.
Returns: float A numerical value representing the volume-weighted money flow. Positive = buying dominance; negative = selling dominance.
isAccumulationBar()
Checks for basic accumulation on the current bar, requiring both positive Money Flow Volume and a buying bar (closing higher than opening).
Returns: bool True if the bar exhibits buying dominance through its internal range location and is a buying bar.
isDistributionBar()
Checks for basic distribution on the current bar, requiring both negative Money Flow Volume and a selling bar (closing lower than opening).
Returns: bool True if the bar exhibits selling dominance through its internal range location and is a selling bar.
Wave Dynamics - Neural Adaptive Engine🌊 WAVE DYNAMICS - NEURAL ADAPTIVE ENGINE
The Official Reference Manual & Trading Protocol
═════════════════════════════════════════════════════════════
📖 PREFACE: THE END OF STATIC ANALYSIS
The financial markets are not linear; they are fractal. They do not move in straight lines; they breathe. They expand in trending volatility and contract in chopping noise.
The fundamental failure of traditional technical analysis is Static Sensitivity .
• A 14-period RSI works beautifully in a range but fails in a trend.
• A 12,26 MACD captures trends but destroys capital in chop.
Wave Dynamics solves this by treating the market as a living organism. At its core is a Neural Adaptive Engine that calculates the Hurst Exponent (Fractal Dimension) in real-time. It measures the "roughness" of price action and automatically adjusts the lookback periods of every subsystem—Waves, Ribbons, and Oscillators—to match the current market regime.
This manual is your guide to navigating this adaptive framework.
PART 1: THEOLOGY & MARKET PHYSICS
To use this tool, you must understand the three pillars of its logic:
1. The Hurst Exponent (Chaos Theory)
The engine continuously calculates H (Hurst) on a rolling window.
• Persistent Regime (H > 0.5): "What is happening now is likely to continue." The market is trending. The Engine Tightens sensitivity to catch fast pullbacks.
• Anti-Persistent Regime (H < 0.5): "What is happening now is likely to reverse." The market is chopping/ranging. The Engine Widens sensitivity to filter out noise and stop runs.
2. The Elliott Wave Cycle (Crowd Psychology)
Price moves in 5-wave motive sequences followed by corrections.
• Waves 1 & 3: Institutional Accumulation/Mark-up.
• Waves 2 & 4: Profit Taking (The Pullback). These are the only safe entry points.
• Wave 5: Retail FOMO (The Trap). Identified by Momentum Divergence .
3. Smart Money Concepts (Liquidity)
Price moves from liquidity to liquidity.
• Order Blocks: Where institutions initiated the move.
• Breakers: Where institutions trapped traders (Support flips to Resistance).
• Fair Value Gaps: Where price moved too fast, leaving inefficiency.
PART 2: VISUAL INTELLIGENCE (COLOR THEORY)
The chart communicates instantly through a strict color-coded language.
🎨 THE RIBBON (Adaptive Equilibrium)
The background "Cloud" is an Adaptive EMA ribbon.
• Neon Green (#00FF88): Bullish Trend. Only look for Longs. Price is above the equilibrium mean.
• Neon Red (#FF3366): Bearish Trend. Only look for Shorts. Price is below the equilibrium mean.
• Grey/Narrow: Compression. The market is deciding. Do not trade inside a grey ribbon.
🎨 INSTITUTIONAL ZONES
• Green/Red Boxes (Order Blocks): Standard Support/Resistance. Valid entry zones, but lower probability.
• Vivid Purple Boxes (#9C27B0) - THE BREAKER: CRITICAL. This appears when a Green Order Block is smashed through by price. It turns Purple to signify it has flipped from Support to Resistance (or vice versa). A retest of a Purple Zone is the highest probability setup in the system.
• Dotted Outlines (FVG): Magnets. Do not place stops inside these; price will likely travel through them.
🎨 WAVE ANATOMY
• Cyan Lines: Valid Impulse Waves (1, 3, 5).
• Orange Lines/Dots: EXHAUSTION. If a wave line turns Orange, Angular Momentum is decaying. The trend is dying.
• Diamonds (◆): DIVERGENCE. Price made a Higher High, but the internal oscillator (MPI) made a Lower Low. Immediate reversal warning.
🎨 SIGNALS
• Triangles: Confirmed Entries. (Green = Long, Red = Short).
• Labels (e.g., A+): The Grade of the trade based on Confluence.
• A+: Perfect Confluence (Trend + Structure + Zone + Momentum).
• C: Counter-trend or Weak.
PART 3: THE DASHBOARD ECOSYSTEM
Three panels provide Total Situational Awareness. You must read them in order: Top Right → Bottom Left → Bottom Right.
1. MISSION CONTROL (Top Right)
This panel tells you the "Weather Report."
• Neural Status:
• 🧠 TREND: Safe to trade breakout and trend-following strategies.
• 🧠 CHOP: Danger. Use mean-reversion or stay out.
• 🧠 RND (Random): No clear edge.
• Phase: Displays the Bias (Bull/Bear) and Strength. "WEAK BEARISH" usually signals a bottom is forming.
• Score Bar: A live visual meter of the Confluence Score (0-100%).
2. THE ASSISTANT (Bottom Left)
This panel acts as your co-pilot, translating data into English.
• Situation:
• "💎 BULL GEM": You are in a range, at the bottom, showing exhaustion. Buy immediately.
• "🔥 COMPRESSION": Volatility squeeze. A violent move is imminent.
• Action: Tells you exactly what to do (e.g., "Wait for confluence," "Trail Stop," "Let it develop").
• Pro Metrics (Simulated):
• Win Rate: The percentage of signals on the current visible chart that hit Target 1.
• Profit Factor: Gross Win / Gross Loss. If this is < 1.0, stop trading this asset immediately.
• Buckets: Shows the win rate of A-Grade signals vs. C-Grade signals.
3. WAVE INTELLIGENCE (Bottom Right)
This panel provides structural context.
• Channel Gauge (0-100%):
• 0-20%: Oversold / Channel Bottom.
• 80-100%: Overbought / Channel Top.
• 50%: Equilibrium.
• W3/W1 Ratio: The "Health Check" of the trend.
• < 1.0: Weak. Wave 3 is shorter than Wave 1. The trend is struggling.
• > 1.618: Extended. The move is parabolic. Expect a snap-back.
• Trend Health (0-100): Composite score of sub-wave physics. If Health < 30, the trend is effectively dead.
PART 4: PARAMETER OPTIMIZATION (THE INPUTS)
Every input allows you to tune the engine. Here is the deep dive:
🧠 NEURAL ADAPTIVE ENGINE
• Enable Neural Adaptive Engine: Master switch for the Hurst calculation.
• Hurst Period (100):
• Adjustment: Increase to 200 for Crypto/Alts (too much noise). Decrease to 50 for
Forex/Indices (need speed).
• How to tell: If the dashboard says "TREND" but the chart is sideways, INCREASE this value.
• Min/Max Lookback: Defines the constraints. Only adjust if you are an advanced user creating a custom scalping setup (e.g., Min 3 / Max 10).
🌊 WAVE & STRUCTURE
• Base Swing Detection (8): The "Anchor."
• Scalpers (1m-5m): Set to 5-8.
• Swing Traders (1H-4H): Set to 15-20.
• Min Wave Size (ATR): Prevents the script from labeling tiny wicks as waves. Increase this during high-volatility news events.
🔗 MTF STRUCTURE MAPPING
• Require Macro Align: Strict Mode. If enabled, the script checks the Higher Timeframe (e.g., 4H). If 4H is Bearish, it BLOCKS all Long signals on the 5m chart. Use this to prevent counter-trend losses.
🏦 SMART MONEY CONCEPTS
• Enable Breakers: ALWAYS ON. This turns failed Order Blocks into Breaker Zones (Purple).
• Institutional Mode: ULTRA STRICT. If enabled, signals will ONLY fire if price is physically touching an Order Block, FVG, or Breaker. This creates very few, very high-quality signals.
🎯 SIGNAL ENGINE
• Signal Mode:
• Strict: Grades A+ and A only.
• Balanced: Grades B and above.
• Aggressive: Includes counter-trend scalps (Grade C).
• Min Confluence Score (5-35): The raw points needed to trigger. 5 is standard. 10 is conservative.
PART 5: TRADE EXECUTION PLAYBOOKS
PLAYBOOK A: THE "BREAKER RETEST" (Highest Probability)
1. Context: Ribbon is Green.
2. Event: Price creates a Red Order Block, then smashes upward through it.
3. Change: The Red Block turns Purple (Bullish Breaker).
4. Trigger: Price pulls back down to touch the top of the Purple Box.
5. Signal: Green Triangle appears.
6. Action: Max Size Entry. Stop Loss below the Purple Box. Target Wave 3 Projection.
PLAYBOOK B: THE "WAVE 4 DIP" (Trend Following)
1. Context: Wave count shows "3". Ribbon is Green.
2. Event: Price pulls back towards the Ribbon.
3. Wave Panel: Wave count flips to "4".
4. Trigger: Price touches Ribbon, prints Green Triangle.
5. Action: Standard Size Entry. Stop Loss at Swing Low. Target New High (Wave 5).
PLAYBOOK C: THE "HIDDEN GEM" (Range Reversal)
1. Context: Ribbon is Grey (Consolidation). Neural Status is CHOP.
2. Wave Panel: Channel Gauge is < 10% (Extreme Bottom).
3. Visuals: Orange Exhaustion Dot + Divergence Diamond (◆).
4. Assistant: Reads "💎 BULL GEM".
5. Action: Half Size Entry. This is a counter-trend trade. Target the middle of the range (50% Channel).
PLAYBOOK D: THE "BULL TRAP" (When to Fold)
1. Context: Wave Count is "5".
2. Wave Panel: Trend Health < 30. W3/W1 Ratio > 1.618 (Extended).
3. Visuals: Orange Line appears on price high.
4. Signal: Green Triangle appears (Grade C).
5. Action: NO TRADE. The system is warning you that even though a signal fired, the structural physics indicate exhaustion.
PART 6: GRADING & SCORING MATRIX
Every signal is graded on a 35-point scale. Know what you are buying.
• Trend Alignment (5 pts): Ribbon & HTF agreement.
• Structure (5 pts): BOS (Break of Structure) & Higher Highs.
• Physics (5 pts): MPI (Volume Flow) & Angular Velocity.
• Institutional Location (10 pts):
• Inside Order Block: +3 pts
• Inside Breaker: +4 pts
• Wave 2/4 Pullback: +3 pts
• Penalty: Wave 5 Extension (-3 pts).
Grade Scale:
• A+ (Score ≥ 70%): "All In" Setup.
• A (Score 55-69%): Strong Setup.
• B (Score 40-54%): Standard Setup.
• C (Score < 40%): Dangerous.
PART 7: RISK DISCLOSURE & LIMITATIONS
1. The Reality of Adaptation (Redrawing):
The Neural Engine is dynamic. As new data arrives, the calculation of "Chaos" changes. This means historical channel lines or wave labels may shift to fit the matured trend. HOWEVER: Entry Signals (Triangles) NEVER repaint once the bar is closed.
2. Simulation vs. Reality:
The Dashboard metrics (Win Rate, Profit Factor) are Simulations run on the historical data visible on your chart. They do not account for spread, slippage, or liquidity. They are a tool to gauge the current market personality, not a promise of future returns.
3. No Financial Advice:
Wave Dynamics is a tool for structural analysis. It helps you see the market, but it cannot trade for you. You are responsible for your own risk management.
CLOSING THOUGHTS
Wave Dynamics is not just an indicator; it is a lens. It allows you to see the market not as a random walk of candles, but as a structured, breathing entity.
Trust the Neural Status. Respect the Breakers. Fear the Exhaustion.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Smart Money Flow Cloud [BOSWaves]Smart Money Flow Cloud - Volume-Weighted Trend Detection with Adaptive Volatility Bands
Overview
Smart Money Flow Cloud is a volume flow-aware trend detection system that identifies directional market regimes through money flow analysis, constructing adaptive volatility bands that expand and contract based on institutional pressure intensity.
Instead of relying on traditional moving average crossovers or fixed-width channels, trend direction, band width, and signal generation are determined through volume-weighted money flow calculation, nonlinear flow strength modulation, and volatility-adaptive band construction.
This creates dynamic trend boundaries that reflect actual institutional buying and selling pressure rather than price momentum alone - tightening during periods of weak flow conviction, expanding during strong directional moves, and incorporating flow strength statistics to reveal whether regimes formed under accumulation or distribution conditions.
Price is therefore evaluated relative to adaptive bands anchored at a flow-informed baseline rather than conventional trend-following indicators.
Conceptual Framework
Smart Money Flow Cloud is founded on the principle that sustainable trends emerge where volume-weighted money flow confirms directional price movement rather than where price alone creates patterns.
Traditional trend indicators identify regime changes through price crossovers or slope analysis, which often ignore the underlying volume dynamics that validate or contradict those movements.This framework replaces price-centric logic with flow-driven regime detection informed by actual buying and selling volume.
Three core principles guide the design:
Trend direction should correspond to volume-weighted flow dominance, not price movement alone.
Band width must adapt dynamically to current flow strength and volatility conditions.
Flow intensity context reveals whether regimes formed under conviction or uncertainty.
This shifts trend analysis from static moving averages into adaptive, flow-anchored regime boundaries.
Theoretical Foundation
The indicator combines adaptive baseline smoothing, close location value (CLV) methodology, volume-weighted flow tracking, and nonlinear strength amplification.
A smoothed trend baseline (EMA or ALMA) establishes the core directional reference, while close location value measures where price settled within each bar's range. Volume weighting applies directional magnitude to flow calculation, which accumulates into a normalized money flow ratio. Flow strength undergoes nonlinear power transformation to amplify strong conviction periods and dampen weak flow environments. Average True Range (ATR) provides volatility-responsive band sizing, with final width determined by the interaction between base volatility and flow-modulated multipliers.
Four internal systems operate in tandem:
Adaptive Baseline Engine : Computes smoothed trend reference using either EMA or ALMA methodology with configurable secondary smoothing.
Money Flow Calculation System : Measures volume-weighted directional pressure through CLV analysis and ratio normalization.
Nonlinear Flow Strength Modulation : Applies power transformation to flow intensity, creating dynamic sensitivity scaling.
Volatility-Adaptive Band Construction : Scales band width using ATR measurement combined with flow-strength multipliers that range from minimum (calm) to maximum (strong flow) expansion.
This design allows bands to reflect actual institutional behavior rather than reacting mechanically to price volatility alone.
How It Works
Smart Money Flow Cloud evaluates price through a sequence of flow-aware processes:
Close Location Value (CLV) Calculation : Each bar's closing position within its high-low range is measured, creating a directional bias indicator ranging from -1 (closed at low) to +1 (closed at high).
Volume-Weighted Flow Tracking : CLV is multiplied by bar volume, then accumulated and normalized over a configurable flow window to produce a money flow ratio between -1 and +1.
Flow Smoothing and Strength Extraction : The raw money flow ratio undergoes optional smoothing, then nonlinear power transformation to amplify strong flow periods and compress weak flow environments.
Adaptive Baseline Construction : Price (both open and close) is smoothed using either EMA or ALMA methodology with optional secondary smoothing to create a stable trend reference.
Dynamic Band Sizing : ATR measurement is multiplied by a flow-strength-modulated factor that interpolates between minimum (tight) and maximum (wide) multipliers based on current flow conviction.
Regime Detection and Visualization : Price crossing above the upper band triggers bullish regime, crossing below the lower band triggers bearish regime. The baseline cloud visualizes open-close relationship within the current trend.
Retest Signal Generation : Price touching the baseline from within an established regime generates retest signals with configurable cooldown periods to prevent noise.
Together, these elements form a continuously updating trend framework anchored in volume flow reality.
Interpretation
Smart Money Flow Cloud should be interpreted as flow-confirmed trend boundaries:
Bullish Regime (Blue) : Activated when price crosses above the upper adaptive band, indicating volume-confirmed buying pressure exceeding volatility-adjusted resistance.
Bearish Regime (Red) : Established when price crosses below the lower adaptive band, identifying volume-confirmed selling pressure breaking volatility-adjusted support.
Baseline Cloud : The gap between smoothed open and smoothed close within the baseline visualizes intrabar directional bias - wider clouds indicate stronger intrabar momentum.
Adaptive Band Width : Reflects combined volatility and flow strength - wider bands during high-conviction institutional activity, tighter bands during consolidation or weak flow periods.
Buy/Sell Labels : Appear at regime switches when price crosses from one band to the other, marking potential trend inception points.
Retest Signals (✦) : Diamond markers indicate price touching the baseline within an established regime, often occurring during healthy pullbacks in trending markets.
Trend Strength Gauge : Visual meter displays current regime strength as a percentage, calculated from price position within the active band relative to baseline.
Background Gradient : Optional coloring intensity reflects flow strength magnitude, darkening during high-conviction periods.
Flow strength, band width adaptation, and baseline relationship outweigh isolated price fluctuations.
Signal Logic & Visual Cues
Smart Money Flow Cloud presents three primary interaction signals:
Regime Switch - Buy : Blue "Buy" label appears when price crosses above the upper band after previously being in a bearish regime, suggesting volume-confirmed bullish transition.
Regime Switch - Sell : Red "Sell" label displays when price crosses below the lower band after previously being in a bullish regime, indicating volume-confirmed bearish transition.
Trend Retest : Diamond (✦) markers appear when price touches the baseline within an established regime, with configurable cooldown periods to filter noise.
Alert generation covers regime switches and retest events for systematic monitoring.
Strategy Integration
Smart Money Flow Cloud fits within volume-informed and institutional flow trading approaches:
Flow-Confirmed Entry : Use regime switches as primary trend inception signals where volume validates directional breakouts.
Retest-Based Refinement : Enter on baseline retest signals within established regimes for improved risk-reward positioning during pullbacks.
Band Width Context : Expect wider price swings when bands expand (high flow strength), tighter ranges when bands contract (weak flow).
Baseline Cloud Confirmation : Favor trades where baseline cloud width confirms intrabar momentum alignment with regime direction.
Strength Gauge Filtering : Use trend strength percentage to gauge continuation probability - higher readings suggest stronger institutional conviction.
Multi-Timeframe Regime Alignment : Apply higher-timeframe regime context to filter lower-timeframe entries, taking only setups aligned with dominant flow direction.
Technical Implementation Details
Core Engine : Configurable EMA or ALMA baseline with secondary smoothing
Flow Model : Close Location Value (CLV) with volume weighting and ratio normalization
Strength Transformation : Configurable power function for nonlinear flow amplification
Band Construction : ATR-scaled width with flow-strength-interpolated multipliers
Visualization : Dual-line baseline cloud with gradient fills, regime-colored bands, and embedded strength gauge
Signal Logic : Band crossover detection with baseline retest identification and cooldown management
Performance Profile : Optimized for real-time execution with minimal computational overhead
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Micro-structure regime detection for scalping and intraday reversals
15 - 60 min : Intraday trend identification with flow-validated swings
4H - Daily : Swing and position-level regime analysis with institutional flow context
Suggested Baseline Configuration:
Trend Length : 34
Trend Engine : EMA
Trend Smoothing : 3
Flow Window : 24
Flow Smoothing : 5
Flow Boost : 1.2
ATR Length : 14
Band Tightness (Calm) : 0.9
Band Expansion (Strong Flow) : 2.2
Reset Cooldown : 12
These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volume profile, volatility characteristics, and preferred signal frequency, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Bands too wide/frequent whipsaws : Reduce "Band Expansion (Strong Flow)" to limit maximum band width, or increase "Band Tightness (Calm)" to widen minimum bands and reduce noise sensitivity.
Trend baseline too choppy : Increase "Trend Length" for smoother baseline, or increase "Trend Smoothing" for additional filtering.
Flow readings unstable : Increase "Flow Smoothing" to reduce bar-to-bar noise in money flow calculation.
Missing legitimate regime changes : Decrease "Trend Length" for faster baseline response, or reduce "Band Tightness (Calm)" for earlier breakout detection.
Too many retest signals : Increase "Reset Cooldown" to space out retest markers, or disable retest signals entirely if not using pullback entries.
Flow strength not responding : Increase "Flow Boost" (power factor) to amplify strong flow differentiation, or decrease "Flow Window" to emphasize recent volume activity.
Prefer different smoothing characteristics : Switch "Trend Engine" to ALMA and adjust "ALMA Offset" (higher = more recent weighting) and "ALMA Sigma" (higher = smoother) for alternative baseline behavior.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Markets with consistent volume participation and institutional flow
Instruments where volume accurately reflects true liquidity and conviction
Trending environments where flow confirms directional price movement
Mean-reversion strategies using retest signals within established regimes
Reduced Effectiveness:
Extremely low volume environments where flow calculations become unreliable
News-driven or gapped markets with discontinuous volume patterns
Highly manipulated or thinly traded instruments with erratic volume distribution
Ranging markets where price oscillates within bands without conviction
Integration Guidelines
Confluence : Combine with BOSWaves structure, order flow analysis, or traditional volume profile
Flow Validation : Trust regime switches accompanied by strong flow readings and wide band expansion
Context Awareness : Consider whether current market regime matches historical flow patterns
Retest Discipline : Use baseline retest signals as confirmation within trends, not standalone entries
Breach Management : Exit regime-aligned positions when price crosses opposing band with volume confirmation
Disclaimer
Smart Money Flow Cloud is a professional-grade volume flow and trend analysis tool. Results depend on market conditions, volume reliability, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, market context, and comprehensive risk management.
Linear Regression Market State IndexStandard Deviation Market Structure Indicator
A Comprehensive Multi-Timeframe Market Analysis Tool
🎯 Overview
The Standard Deviation Market Structure (SDMS) indicator is a sophisticated technical analysis tool that integrates multiple proven methodologies to identify market structure, trend direction, and potential reversal zones. By combining price action, statistical analysis, and momentum indicators across multiple timeframes, SDMS provides traders with a comprehensive view of market dynamics.
✨ Key Features
Multi-Timeframe Integration
Primary analysis on current timeframe
1-hour statistical confirmation for support/resistance levels
Order block extension across 500 future bars
Comprehensive Technical Suite
RSI with Deviation Analysis
Dynamic Order Block Detection
Gaussian Filter Channels
Linear Regression with Statistical Bands
Standard deviation to detect price outliers
Directional Movement Index (DMI/ADX)
Bollinger Band % Analysis
Support/Resistance Line System
Visual Clarity
Color-coded signals and zones
Automatic level management
Clean, intuitive display
📊 Core Components Explained
1. Order Block System
What Are Order Blocks?
Order blocks are price zones where institutional activity has occurred, creating future support or resistance levels. SDMS automatically detects these critical zones.
Detection Logic:
Bullish Order Blocks: Form when price breaks above recent highs following bearish candles
Bearish Order Blocks: Form when price breaks below recent lows following bullish candles
Visual Identification:
Green boxes with "BuOB" labels (support zones)
Red boxes with "BeOB" labels (resistance zones)
Each block shows its boundary price for easy reference
Dynamic Management:
Automatically extends 300 bars into the future
Self-cleaning: removes blocks when price breaches their boundaries
Real-time adjustment to changing market structure
2. Statistical Support/Resistance System
How It Works:
SDMS creates support and resistance lines based on statistical extremes confirmed on the 1-hour timeframe.
Trigger Conditions:
Support Lines (Green): Trigger when 1H Bollinger Band % crosses above 0 and bearish momentum subsides.
Resistance Lines (Red): Trigger when 1H Bollinger Band % crosses below 1 and bullish momentum subsides
The Science Behind BB%:
BB% = (Price - Lower Band) / (Upper Band - Lower Band)
BB% <= 0: Price at statistical oversold extreme; also indicated by white candles.
BB% > 1: Price at statistical overbought extreme; also indicated by white candles.
Line Management:
Maximum of 15 active lines
Oldest lines automatically removed
Lines extend across chart for ongoing reference
3. Trend Analysis Suite
Hull Moving Average (HMA):
55-period smoothed trend indicator
Color-coded: Green = bullish, Red = bearish
Visual band shows trend acceleration/deceleration
Gaussian Channel:
Advanced filtering of market noise
Dynamic channel based on true range volatility
Helps identify mean reversion opportunities
Form a yellow band when price is overbought or oversold zones.
Linear Regression System:
Statistical price modeling
Multiple standard deviation bands (up to 3SD)
Regression-based candlestick visualization
Candles turn white when in overbought zones. Yellow candles indicate extremely overbought zones. Blue candles indicate a bullish trend with high volume.
Bearish candles are bluish-purple when volume is high and red when the volume is within normal ranges or low.
4. Momentum & Oscillator Integration
RSI with Deviation Tracking:
21-period RSI with 30-period smoothing
Tracks deviation from moving average based off linear regression
Identifies momentum divergences
Directional Movement Index:
Multi-period DMI/ADX analysis
Used to detect overbought and oversold zones within the indicator calculations.
Combines with RSI for enhanced signals
Momentum confirmation for all entries/exits
🎯 Trading Signals & Alerts
Buy Signals (Yellow "Buy" Labels)
Multi-Condition Confirmation Required:
RSI Oversold Reversal: RSI crosses above 30
Trend Alignment: HMA showing bullish structure
Momentum Confirmation: DMI alignment
Statistical Support: Price at or near support zones
Risk Management: Multiple confirming indicators
Strong Buy Conditions:
Confluence of order block support + BB% support line
Multiple timeframe alignment
Volume confirmation at key levels
Sell Signals (Red/Yellow "Sell" Labels)
Multi-Condition Confirmation Required:
RSI Overbought Reversal: RSI crosses below 70
Trend Exhaustion: HMA showing bearish structure
Momentum Divergence: DMI bearish alignment
Statistical Resistance: Price at or near resistance zones
Timeframe Confirmation: 1H BB% bearish signals
Strong Sell Conditions:
Confluence of order block resistance + BB% resistance line
Multiple timeframe distribution
Volume surge at resistance
Additional Alerts
RSI Divergence Signals: Triangles showing momentum shifts
Extreme Price Alerts: Circles at statistical extremes
Structure Breaks: Visual cues for order block violations
🎨 Visual System Guide
Color Coding System
Green: Bullish conditions, support zones, rising trends
Red: Bearish conditions, resistance zones, falling trends
Blue: Statistical channels, neutral zones
Yellow: Alert conditions, extreme signals
White: Transition zones, neutral signals
Zone Identification
Buying Pressure Zones: Green/blue tinted areas below price or white candles with white dots within the moving average center line
Selling Pressure Zones: Red tinted areas above price with white dots within the moving average center line
Standard Deviation Zones: Gradient colors showing statistical extremes
⚙️ Customization Options
Adjustable Parameters
RSI Settings: Period, oversold/overbought levels, sensitivity
Order Block Detection: Lookback period, ATR multiplier, extension
Statistical Settings: Gaussian filter poles, regression periods
Support/Resistance: Maximum lines, BB% settings
Visual Preferences: Colors, band displays, alert styles
Input Groups
RSI Trading Strategy
Order Block Configuration
Gaussian Channel Settings
Linear Regression Parameters
DMI/ADX Configuration
Bollinger Band % Settings
📈 Practical Trading Applications
For Swing Traders
Identify Key Levels: Use order blocks + BB% lines for entry/exit planning
Trend Confirmation: HMA + Gaussian channel for trend direction
Risk Management: Standard deviation bands for stop placement
Timing Entries: RSI/DMI alignment for optimal entry timing
For Day Traders
Intraday Levels: Order blocks provide immediate S/R for day trading
Momentum Signals: Real-time RSI/DMI signals for quick moves
Statistical Edges: Gaussian channel for mean reversion plays
Breakout Confirmation: Order block breaks with volume
For Position Traders
Higher Timeframe Structure: 1H BB% lines for major levels
Trend Persistence: HMA for long-term trend identification
Accumulation/Distribution Zones: Order blocks show institutional activity
Multi-Timeframe Alignment: Confirmation across timeframes
🔍 How to Use SDMS Effectively
Step 1: Market Structure Assessment
Identify active order blocks (green/red boxes)
Note BB% support/resistance lines (horizontal lines)
Assess HMA and moving average trend direction (color)
Check Gaussian channel position (preferably outside 2SD)
Step 2: Signal Confirmation
Wait for multiple indicator alignment
look for doji candles.
Confirm with green (bullish) or red (bearish) candles
Confirm with volume if available
Check for confluence of levels
Assess risk/reward based on nearby levels
Step 3: Trade Management
Enter at confirmed support/resistance
Place stops beyond opposite levels
Take profits at next statistical level
Monitor for structure changes
Step 4: Risk Management
Use standard deviation bands for volatility assessment
Never risk more than 1-2% per trade
Adjust position size based on confluence strength
Have predefined exit rules
💡 Advanced Strategies
Strategy 1: Confluence Trading
Setup: Order block + BB% line at same level
Entry: Price tests confluence zone with RSI signal
Stop: Beyond the confluence zone
Target: Next statistical level
Strategy 2: Breakout Trading
Setup: Price approaching order block boundary
Entry: Break with volume + RSI/DMI confirmation
Stop: Re-entry into order block
Target: Next BB% line extension
Strategy 3: Mean Reversion
Setup: Price at Gaussian channel extremes
Entry: RSI reversal signal at channel boundary
Stop: Beyond channel extreme
Target: Channel midline or opposite boundary
⚠️ Important Considerations
Best Market Conditions
Trending Markets: Excellent performance in clear trends
Breakout Scenarios: Strong identification of break levels
Range Markets: Works well with defined ranges
Limitations
Choppy Markets: May give false signals in consolidation
News Events: Fundamental shocks can override technical levels
Timeframe Specific: Optimal on 15-minute to daily charts
Risk Management Rules
Always use stops
Never rely on single signals
Consider market context
Adjust for volatility changes
Keep position sizes consistent
🔧 Technical Specifications
Maximum Lines: 500
Maximum Bars Back: 1000
Maximum Boxes: 500
Calculation Efficiency: Optimized for real-time use
🏆 Why SDMS Stands Out
Unique Advantages
Integrated Approach: Combines multiple methodologies into one tool
Self-Adjusting: Automatically adapts to market changes
Multi-Timeframe: Provides both immediate and higher timeframe context
Visual Clarity: Clean, intuitive display of complex data
Professional Grade: Institutional-level analysis accessible to all traders
Educational Value: Learn how different indicators interact
Understand market structure development
See institutional order flow patterns
Develop disciplined trading habits
📚 Learning Resources
Recommended Study Approach
Start Simple: Focus on order blocks and BB% lines first
Add Complexity: Gradually incorporate other indicators
Paper Trade: Practice without risk
Keep Journal: Document setups and outcomes
Review Regularly: Analyze both wins and losses
Common Pitfalls to Avoid
Overtrading: Wait for high-quality setups
Ignoring Context: Consider overall market conditions
Chasing Signals: Enter at planned levels, not after moves
Risk Mismanagement: Always know your risk before entering
Confirmation Bias: Be objective about signals
🤝 Community & Support
Getting the Most from SDMS
Start with Defaults: Use default settings initially
Adjust Gradually: Make small changes as you understand the tool
Combine with Fundamentals: Use for timing within fundamental context
Stay Disciplined: Follow your trading plan consistently
Continuous Improvement
SDMS is designed for continuous learning. As you use the indicator, you'll develop insights into:
Market microstructure
Institutional trading patterns
Statistical edge identification
Risk management optimization
Risk management is more important than signal accuracy
Patience is required for high-quality setups
Success Factors
Discipline: Following your plan consistently
Patience: Waiting for proper setups
Risk Management: Protecting your capital
Continuous Learning: Improving your skills over time
🌟 Final Thoughts
The Standard Deviation Market Structure indicator represents a sophisticated approach to technical analysis, combining the best elements of price action, statistical analysis, and momentum indicators. While powerful, remember that no indicator guarantees success. SDMS is a tool – your skill, discipline, and risk management determine your trading results.
Use SDMS as part of a comprehensive trading plan, combine it with proper risk management, and continue developing your trading skills. The markets are always teaching – stay humble, stay disciplined, and trade well.
Disclaimer: This indicator is for educational purposes only. Past performance does not guarantee future results. Trading involves risk of loss. Always consult with a qualified financial professional before making investment decisions.
ATH Dip Levels - Buy on Dips
This indicator is a "Buy the Dip" guide designed for assets in long-term uptrends, such as Nasdaq (QQQ) or S&P 500 (SPY). It uses a mathematical discipline to identify accumulation zones based on the rolling 220-bar All-Time High (ATH).
Key Features:
Dynamic Levels: Automatically calculates entry points at 3%, 5%, 10%, 15%, 25%, 35%, and 50% retracements from the recent ATH.
Smart Filter: Each level is triggered only once per ATH cycle. It prevents over-trading in sideways markets; levels only reset when a brand-new high is formed.
Clean Visuals: Features precise "BUY" labels at exact price points and a handy status dashboard in the top-right corner.
Unified Alerts: Simplify your workflow by setting a single alert for all 7 dip levels.
PLOW/PLHW (Potential weekly highs/lows)AP Capital – PLOW / PLHW (Potential Weekly Low / High)
This indicator highlights Potential Weekly Lows (PLOW) and Potential Weekly Highs (PLHW) in real time, using current-week price action, session context, and confirmed candle closes.
It is designed for intraday and swing traders who want early-week and late-week structure levels without repainting or hindsight bias.
🔹 How It Works
Potential Weekly Low (PLOW)
Detected during early week sessions
Triggers when price prints the current week’s lowest low
Confirmed only on candle close
Typically aligns with liquidity grabs, stop runs, or accumulation
Potential Weekly High (PLHW)
Detected during late week sessions
Triggers when price prints the current week’s highest high
Confirmed only on candle close
Often marks distribution or exhaustion zones
📊 Visual Elements
Clean weekly high & low levels
Optional weekly midpoint
Session-aware confirmation
Non-repainting labels
Minimalist layout (no clutter)
⚙️ Key Features
Works on any intraday timeframe
Fully non-repainting
Session-based logic (early vs late week)
Optional weekly range info panel
Suitable for Gold, FX, Indices, Crypto
🧠 Best Use Cases
Fade moves into weekly extremes
Combine with:
Previous Day High / Low
Liquidity sweeps
Market structure shifts
Identify high-probability reversals
Avoid chasing price late in the week
⚠️ Important Notes
This is NOT predictive — levels are confirmed from live price action
Best used as context, not a standalone entry system
Designed to complement price action & liquidity-based trading
📌 Disclaimer
This indicator is for educational purposes only.
Not financial advice. Always manage risk.
Kalman Absorption/Distribution Tracker 3-State EKFQuant-Grade Institutional Flow: 3-State EKF Absorption Tracker
SUMMARY
An advanced, open-source implementation of a 3-State Extended Kalman Filter (EKF) designed to track institutional Order Flow. By analyzing 1-second intrabar microstructure data, this script estimates the true Position, Velocity, and Volatility of the Cumulative Volume Delta (CVD), revealing hidden Absorption and Distribution events in real-time.
INTRODUCTION: THE SIGNAL AMIDST THE NOISE
In the world of technical analysis, noise is the enemy. Traditional indicators rely on Moving Averages (SMA, EMA) to smooth out price and volume data. The problem is the "Lag vs. Noise" paradox: to get a smooth signal, you must accept lag; to get a fast signal, you must accept noise.
This indicator solves that paradox by introducing aerospace-grade mathematics to the TradingView community: The 3-State Extended Kalman Filter (EKF).
Unlike moving averages that blindly average past data, a Kalman Filter is a probabilistic state-space model. It constantly predicts where the order flow "should" be, compares it to the actual measurement, and updates its internal model based on the calculated uncertainty of the market.
This script is not just another volume oscillator. It is a full microstructure analysis engine that digests intrabar data (down to 1-second resolution) to track the true intent of "Smart Money" while filtering out the noise of retail chop.
THE INNOVATION: WHY 3 STATES?
Most Kalman Filters found in public libraries are "1-State" (tracking price only) or occasionally "2-State" (tracking price and velocity). This script introduces a highly advanced 3-State EKF.
The filter tracks three distinct variables simultaneously in a feedback loop:
State 1: Position (The True CVD)
This is the noise-filtered estimate of the Cumulative Volume Delta. It represents the actual inventory accumulation of aggressive buyers versus sellers, stripped of random noise.
State 2: Velocity (The Momentum)
This tracks the rate of change of the order flow. Is buying accelerating? Is selling pressure fading even as price drops? This provides a leading signal before the cumulative value even turns.
State 3: Volatility (The Adaptive Regime)
This is the game-changer. The filter estimates the current volatility of the order flow (Log-Volatility). In high-volatility environments (like news events), the filter automatically widens its uncertainty bands (Covariance) and reacts faster. In low-volatility environments (chop), it tightens up and ignores minor fluctuations.
THE LOGIC: DETECTING ABSORPTION AND DISTRIBUTION
The core philosophy of this indicator is based on Wyckoff Logic: Effort vs. Result.
-- Effort: Represented by the CVD (Buying/Selling pressure).
-- Result: Represented by Price Movement.
When these two diverge, we have an actionable signal. The script uses the EKF Velocity state to detect these moments:
Absorption (Bullish)
This occurs when the EKF detects high negative Velocity (aggressive selling), but Price refuses to drop. The "Smart Money" is absorbing the sell orders via limit buys. The indicator highlights this as a Blue Event in the dashboard.
Distribution (Bearish)
This occurs when the EKF detects high positive Velocity (aggressive buying), but Price refuses to rise. Limit sellers are capping the market. The indicator highlights this as an Orange Event.
TECHNICAL DEEP DIVE: UNDER THE HOOD
For the developers and quants, here is how the Pine Script is architected using the "type" and "method" features of Pine Script v5.
1. Data Ingestion (Microstructure)
The script uses "request.security_lower_tf" to pull intrabar data regardless of your chart timeframe. This allows the script to see "inside" the bar. A 5-minute candle might look green, but the microstructure might reveal that 80% of the volume was selling absorption at the wick. This script sees that.
2. Tick Classification
Standard CVD assumes that if Price Close is greater than Price Open, all volume is buying. This is often flawed. This script offers three modes of tick handling, including a "High-Low Distribution" method that statistically apportions volume based on where the tick closed relative to its high and low.
3. The EKF Mathematics
The script implements the standard Extended Kalman Filter equations manually. It calculates the Jacobian matrix to handle the non-linear relationship between volatility and price. The "Process Noise Matrix" (Q) is dynamically scaled by the Volatility State. This means the mathematics of the indicator literally "breathe" with the market conditions—expanding during expansion and contracting during consolidation.
THE DASHBOARD & VISUALS:
The indicator features a professional-grade HUD (Heads Up Display) located on the chart table.
-- EKF State Vector: Displays the real-time Position, Velocity, and Volatility values derived from the matrix.
-- Ease of Movement (Wyckoff): Calculates how much price moves per 1,000 contracts of CVD. For example, if Price moves +5 points per 1k Buy CVD, but only -2 points per 1k Sell CVD, the "Path of Least Resistance" is clearly UP.
-- Session State: Tracks cumulative confirmed Bullish vs. Bearish events for Today, Yesterday, and the Day Before (3-Day Profile).
-- Bias Summary: An algorithmic conclusion telling you if the day is "Confirmed Bullish," "Accumulating," or "Neutral."
HOW TO TRADE THIS INDICATOR
Strategy A: The Reversal (Absorption Play)
Look for price making a Lower Low.
Look for the EKF Velocity (Histogram) to be Deep Red (High Selling Pressure).
Watch the Dashboard "Absorption" count increase.
SIGNAL: When EKF Velocity crosses back toward zero and turns grey/green, the absorption is complete. This indicates sellers are exhausted and limit buyers have control.
Strategy B: The Trend Continuation (Ease of Movement)
Check the Dashboard "Ease of Movement" section.
If "Price per +1K CVD" is significantly higher than "Price per -1K CVD", buyers are efficient.
Wait for a pullback where EKF Velocity hits the "Neutral Zone" (Gray).
SIGNAL: Enter Long when Velocity ticks positive again, aligning with the dominant Ease of Movement stats.
CONFIGURATION GUIDE:
Because this is a quant-grade tool, the settings allow for fine-tuning the physics of the filter.
-- Velocity Decay: Controls how fast momentum resets to zero. Set high (0.98) for trending markets, or lower (0.85) for mean-reverting chop.
-- Volatility Persistence: Controls how "sticky" volatility regimes are.
-- Process Noise: Increase this if the filter feels too laggy; decrease it if the filter feels too jittery (noisy).
-- Measurement Noise: Increase this to trust the Mathematical Model more than the Price Data (smoother output).
WHY OPEN SOURCE?
Complex statistical filtering is often sold behind closed doors in expensive "Black Box" algorithms. By releasing this 3-State EKF open source, the goal is to raise the standard of development on TradingView.
I encourage the community to inspect the code, specifically the "ekf_update_3state" function, to understand how matrix operations can be simulated in Pine Script to create adaptive, self-correcting indicators. And also update me for improvements.
DISCLAIMER:
This tool analyzes microstructure volume data. It requires a subscription plan that supports Intrabar inspection (Premium/Pro recommended for best results). Past performance of the Kalman Filter logic does not guarantee future results. Volume analysis is subjective and should be used as part of a comprehensive strategy.
SUGGESTED SETTINGS
-- Timeframe: Works best on 1m, 3m, or 5m charts (Intrabar data is fetched from 1S).
-- Asset Class: Highly effective on Futures (ES, NQ, BTC) and high-volume Forex/Crypto pairs where volume data is reliable.
-- Background: Dark mode recommended for Dashboard visibility.
WHAT IS A KALMAN FILTER?
Imagine driving a car into a tunnel where your GPS signal is lost.
Prediction: Your car knows its last speed (Velocity) and position. It predicts where you are every second inside the tunnel.
Update: When you exit the tunnel, the GPS connects again. The system compares where it thought you were versus where the satellite says you are.
Correction: It corrects your position and updates its estimate of your speed.
Now apply this to trading:
-- The Tunnel: Market Noise, wicks, and Fake-outs.
-- The Car: The True Market Trend.
-- This Indicator: The navigation system that tells you where the market actually is, ignoring the noise of the tunnel.
Enjoy the indicator and trade safe!
Dr. Jay Desai
(Investment Management & Derivatives Area, Gujarat University)
HV and IMP candle finderHV and IMP candle finder
Highest volume candle (HV) and Important candle (IMP) are usually a traces of institutional activity. We can take help of these candles to form a bias for the next trading day.
This script does the following:
1. Finds the IMP candle for a given day range with the trend of a given day, ie it finds highest volume candle between the high and low of the day and marks as IMP on the chart
2. It finds the highest volume candle for a given day and marks it.
Use case:
Spot institutional activity, accumulation, and key intraday pivot candles.
View can be made by seeing this HH and LL in these volume candles. Also by considering the closing and opening for the price the next trading session.
Notes
Best to be used on 5 min TF for after market analysis. It does get the candles in live market but it might change with time.
Works really best when delivery volume is also analysed along with it.
Made with Love.
Regards,
Jitendra Varma
Zig Zag ++ SG (Premium)🔥 Zig Zag ++ SG
Professional Market Structure & Cycle Analyzer
Zig Zag ++ SG is an advanced, research-grade market structure indicator built on top of a refined ZigZag engine, designed for traders and investors who want to understand price cycles, not chase candles.
This is not a buy-sell arrow tool.
It is a decision-support system used to analyze trend strength, exhaustion, pullback depth, and cycle behavior across any market and timeframe.
🧠 What Makes Zig Zag ++ SG Different?
Most ZigZag indicators only draw lines.
Zig Zag ++ SG answers the real questions:
Is the trend getting stronger or weaker?
Are higher highs still meaningful?
How deep are pullbacks in percentage terms?
Which stocks recover fast vs stay weak?
Is this accumulation, distribution, or reversal?
It does this by combining:
Market Structure (HH / HL / LH / LL)
Consecutive structure counting
Gain & fall percentage per swing
Clean visual logic (no repaint confusion)
📌 Core Features
✅ 1. Automatic Market Structure Detection
Labels every major swing as:
HH – Higher High
HL – Higher Low
LH – Lower High
LL – Lower Low
This instantly shows whether the market is:
Trending
Consolidating
Distributing
Reversing
✅ 2. Consecutive Structure Count (ON by default)
Each structure type is counted sequentially:
HH (1), HH (2), HH (3)…
HL (1), HL (2)…
This reveals:
Trend maturity
Exhaustion zones
Early breakdown warnings
Example:
HH (4) = trend may be overextended
HL (3) = healthy trend continuation
✅ 3. Gain & Fall % on Every Swing (ON by default)
Every HH, HL, LH, LL shows:
Exact % move from the previous pivot
This allows you to:
Compare pullback depth across stocks
Identify leaders (shallow HLs)
Spot weak stocks (deep HLs / LHs)
Study cycle symmetry
Example label:
HL (2)
-6.4%
✅ 4. Clean, Readable Visual Design
🟩 Green labels → White text
🟥 Red labels → High-contrast white text
Optional background trend shading (OFF by default)
Works perfectly in dark & light mode
Designed for long chart study sessions, not flashy screenshots.
✅ 5. Safe Repaint Logic (Transparent by Design)
Uses ZigZag logic intentionally
No fake “non-repainting” claims
Ideal for analysis, research & planning
What you see is structurally correct
This indicator is for thinking traders, not signal chasers.
⚙️ Best Settings (Recommended)
🔹 Intraday Trading
Timeframe: 5m / 15m
Depth: 8–10
Deviation: 3–5
Backstep: 2
🔹 Swing Trading (Most Popular)
Timeframe: Daily
Depth: 12–15
Deviation: 5
Backstep: 2
🔹 Long-Term / Investing
Timeframe: Weekly
Depth: 15–20
Deviation: 5–8
Backstep: 3
💡 Tip:
Lower depth = more swings
Higher depth = cleaner, major cycles
📈 How to Use Zig Zag ++ SG (Practically)
🔹 Trend Strength
HH (3+) + HL (2–3)
→ Strong, healthy trend
🔹 Exhaustion Warning
HH (4+)
→ Risk of distribution or slowdown
🔹 Pullback Quality
HL −3% to −7%
→ Strong stock
HL −12% to −20%
→ Weak hands / fragile trend
🔹 Reversal Confirmation
LH followed by LL (2+)
→ Trend change likely
🧪 Who Is This Indicator For?
✅ Swing traders
✅ Positional traders
✅ Long-term investors
✅ Market structure students
✅ Stock researchers
✅ Anyone tired of noisy indicators
❌ Not for:
People wanting instant buy/sell arrows
Scalpers chasing 1-minute signals
“Magic indicator” seekers
💎 Why This Is Worth Purchasing
Built with Pine Script v6 best practices
Solves real market questions
Helps avoid:
Buying late
Selling early
Holding weak stocks too long
Encourages process-driven trading
One-time learning tool you’ll use for years
Most traders lose money not because of entries —
but because they misread structure and cycles.
Zig Zag ++ SG fixes that.
Weis Wave Renko Panel 2 (Effort / Strength / Climax)Weis Wave Renko • Institutional HUD + Panel 2
Wyckoff / Auction Market Framework
This project consists of TWO COMPLEMENTARY INDICATORS, designed to be used together as a complete visual framework for reading Effort vs Result, Auction Direction, and Session Control, based on Wyckoff methodology and Auction Market Theory.
These tools are not trade signal generators.
They are context and decision-support instruments, built for discretionary traders who want to understand who is active, where effort is occurring, and when the auction is reaching maturity or exhaustion.
🔹 1) WEIS WAVE RENKO — INSTITUTIONAL HUD (Overlay)
📍 Location: Plotted directly on the price chart
🎯 Purpose: Fast, high-level institutional context and trade permission
The HUD answers:
“What is the current state of the auction, and is trading permitted?”
What the HUD shows:
🧠 Market Participation
Measures how much participation is present in the market:
Low Participation
Weak Participation
Active Participation
Dominant Participation
This reflects whether professional activity is present or absent, not direction alone.
📐 Auction Direction
Defines how the auction is currently resolving:
Auction Up
Auction Down
Balanced Auction
This is derived from price progression and effort alignment.
🔥 Effort (Effort vs Result)
Displays the relative strength of the current effort, normalized over recent waves:
Visual effort bar
Strength percentage (0–100)
Effort classification:
Low Effort
Increasing Effort
Strong Effort
Effort Exhaustion
This is the core Wyckoff concept: effort must produce result.
🌐 Session Control
Shows which trading session is controlling the auction:
Asia – Accumulation Phase
London – Development Phase
US RTH – Decision Phase
The dominant session is visually emphasized, while others are intentionally de-emphasized.
🔎 Market State & Trade Permission
Clearly separates structure from permission:
Structure (Neutral, Developing, Trending, Climactic Extension)
Permission
Trade Permitted
No Trade Zone
When Effort Exhaustion is detected, the HUD explicitly signals No Trade Zone.
🔹 2) WEIS WAVE RENKO — PANEL 2 (Lower Pane)
📍 Location: Dedicated lower pane below the price chart
🎯 Purpose: Detailed, continuous visualization of effort, strength, and climax
Panel 2 answers:
“How is effort evolving, and is the auction maturing or exhausting?”
What Panel 2 shows:
📊 Effort Wave (Weis-like)
Histogram of accumulated effort per directional wave
Green: Auction Up effort
Red: Auction Down effort
This reveals where real participation is building.
📈 Strength Line (0–100)
Normalized strength of the current effort wave
Same calculation used by the HUD
Enables precise comparison of effort over time
⚠️ Climax / Effort Exhaustion Marker
Triggered when effort is both strong and mature
Highlights Climactic Extension / Exhaustion
Serves as a warning, not an entry signal
🔗 HOW TO USE BOTH TOGETHER (IMPORTANT)
These indicators are designed to be used simultaneously:
Panel 2 reveals
→ how effort is building, peaking, or exhausting
HUD translates that information into
→ market state and trade permission
Typical workflow:
Panel 2 identifies rising effort or climax
HUD confirms:
Participation quality
Auction direction
Session control
Whether trading is permitted or restricted
⚠️ IMPORTANT NOTES
These tools do not generate buy or sell signals
They are contextual and structural
Best used with:
Wyckoff schematics
Auction-based execution
Market profile / volume profile
Discretionary trade management
🎯 SUMMARY
Institutional, non-lagging framework
Effort vs Result at the core
Clear separation between:
Context
Structure
Permission
Designed for professional discretionary traders
Weis Wave Renko Institutional HUD (Wyckoff/Auction) v6Weis Wave Renko • Institutional HUD + Panel 2
Wyckoff / Auction Market Framework
This project consists of TWO COMPLEMENTARY INDICATORS, designed to be used together as a complete visual framework for reading Effort vs Result, Auction Direction, and Session Control, based on Wyckoff methodology and Auction Market Theory.
These tools are not trade signal generators.
They are context and decision-support instruments, built for discretionary traders who want to understand who is active, where effort is occurring, and when the auction is reaching maturity or exhaustion.
🔹 1) WEIS WAVE RENKO — INSTITUTIONAL HUD (Overlay)
📍 Location: Plotted directly on the price chart
🎯 Purpose: Fast, high-level institutional context and trade permission
The HUD answers:
“What is the current state of the auction, and is trading permitted?”
What the HUD shows:
🧠 Market Participation
Measures how much participation is present in the market:
Low Participation
Weak Participation
Active Participation
Dominant Participation
This reflects whether professional activity is present or absent, not direction alone.
📐 Auction Direction
Defines how the auction is currently resolving:
Auction Up
Auction Down
Balanced Auction
This is derived from price progression and effort alignment.
🔥 Effort (Effort vs Result)
Displays the relative strength of the current effort, normalized over recent waves:
Visual effort bar
Strength percentage (0–100)
Effort classification:
Low Effort
Increasing Effort
Strong Effort
Effort Exhaustion
This is the core Wyckoff concept: effort must produce result.
🌐 Session Control
Shows which trading session is controlling the auction:
Asia – Accumulation Phase
London – Development Phase
US RTH – Decision Phase
The dominant session is visually emphasized, while others are intentionally de-emphasized.
🔎 Market State & Trade Permission
Clearly separates structure from permission:
Structure (Neutral, Developing, Trending, Climactic Extension)
Permission
Trade Permitted
No Trade Zone
When Effort Exhaustion is detected, the HUD explicitly signals No Trade Zone.
🔹 2) WEIS WAVE RENKO — PANEL 2 (Lower Pane)
📍 Location: Dedicated lower pane below the price chart
🎯 Purpose: Detailed, continuous visualization of effort, strength, and climax
Panel 2 answers:
“How is effort evolving, and is the auction maturing or exhausting?”
What Panel 2 shows:
📊 Effort Wave (Weis-like)
Histogram of accumulated effort per directional wave
Green: Auction Up effort
Red: Auction Down effort
This reveals where real participation is building.
📈 Strength Line (0–100)
Normalized strength of the current effort wave
Same calculation used by the HUD
Enables precise comparison of effort over time
⚠️ Climax / Effort Exhaustion Marker
Triggered when effort is both strong and mature
Highlights Climactic Extension / Exhaustion
Serves as a warning, not an entry signal
🔗 HOW TO USE BOTH TOGETHER (IMPORTANT)
These indicators are designed to be used simultaneously:
Panel 2 reveals
→ how effort is building, peaking, or exhausting
HUD translates that information into
→ market state and trade permission
Typical workflow:
Panel 2 identifies rising effort or climax
HUD confirms:
Participation quality
Auction direction
Session control
Whether trading is permitted or restricted
⚠️ IMPORTANT NOTES
These tools do not generate buy or sell signals
They are contextual and structural
Best used with:
Wyckoff schematics
Auction-based execution
Market profile / volume profile
Discretionary trade management
🎯 SUMMARY
Institutional, non-lagging framework
Effort vs Result at the core
Clear separation between:
Context
Structure
Permission
Designed for professional discretionary traders
Premium Money Flow Oscillator [NeuraAlgo]Premium Money Flow Oscillator (PMFO) — NeuraAlgo
The Premium Money Flow Oscillator (PMFO) is an advanced volume-weighted momentum engine designed to reveal true capital flow, not just price movement.
It combines multi-layer smoothing, zero-lag correction, and dynamic normalization to deliver a clean, responsive, and noise-resistant money flow signal suitable for both scalping and swing trading.
Unlike traditional oscillators, PMFO focuses on pressure behind price — showing when smart money accumulation or distribution is actively occurring.
🔹 Core Features
Volume-Weighted Money Flow
Measures real buying and selling pressure using price displacement × volume.
Filters out weak price moves with low participation.
Multi-Layer Smoothing Engine
EMA + SMA hybrid base smoothing
Gaussian noise reduction
Zero-Lag correction
Deep & Super smoothing layers
→ Result: ultra-smooth yet fast reaction to momentum shifts.
Dynamic Normalization
Automatically adapts to volatility.
Keeps signals consistent across all markets and timeframes.
🔹 Smart Zones & Visual Intelligence
Dynamic Overbought / Oversold Zones
Zones strengthen visually as momentum increases.
Strong zones highlight extreme institutional pressure.
Adaptive Gradient Coloring
Color intensity reflects money flow strength.
Instantly see dominance without reading numbers.
Background Pulse
Subtle market bias feedback (bullish / bearish pressure).
🔹 Multi-Timeframe Confirmation
Optional Higher Timeframe Money Flow Confirmation
Align lower-timeframe entries with higher-timeframe capital direction.
Ideal for trend validation and false-signal reduction.
🔹 Professional Dashboard
Live Money Flow Value
Market Flow State
Strength Percentage
MTF Trend Bias
Institutional-style status readout designed for quick decision making.
🔹 Best Use Cases
✔ Trend confirmation
✔ Momentum continuation entries
✔ Reversal exhaustion detection
✔ Divergence analysis
✔ Smart money flow tracking
⚠️ Notes
PMFO works best when combined with price structure, support/resistance, or trend context.
Extreme readings indicate pressure, not immediate reversal — always wait for confirmation.
Designed for traders who want clarity, not clutter.
Built for precision, not lag.
MA RespectRatio RespectRatio
A Structural Moving Average Quality Indicator
What is RespectRatio
RespectRatio is a statistical indicator designed to evaluate *how reliably a stock respects a specific moving average over time.
Instead of asking “Did price touch the MA?”, it answers a more meaningful question:
Does this moving average actually function as support for this stock consistently and structurally?
The indicator focuses on *historical behavior, not short-term signals, and is intended to support buy / hold / reduce decisions rather than precise trade timing.
Why RespectRatio Exists
Many stocks frequently touch moving averages, but only some of them:
Rebound cleanly
Hold above the average
Do so repeatedly over long periods
RespectRatio was built to separate real support from visual noise.
Core Concept
RespectRatio treats every interaction between price and the moving average as a measurable event.
Each event ends in one of two outcomes:
• Bounce — price respects the moving average
• Break — price fails and breaks below it
Over time, these outcomes form a probability profile of how the stock behaves around that average.
How an Event Starts
An event begins when price meaningfully interacts with the moving average, either by:
• Entering a volatility-adjusted proximity zone around the MA, or
• Crossing below the MA (including gap-downs)
The proximity zone is adaptive and defined as:
k = ATR% × kMultiplier
This keeps the definition of “close enough” consistent across assets and volatility regimes.
Event Outcomes
Bounce (Respect)
An event is classified as a Bounce when price:
• Moves back above the moving average
• Clears a minimal buffer above it
• *Maintains that position for a defined number of sessions.
This confirms that the moving average acted as real support not a temporary pause.
Break (Failure)
An event becomes a Break when price:
• Remains below the moving average for too long, or
• Falls significantly below it and fails to reclaim it within a short window
A Break signals structural weakness at that average.
Noise Control
To avoid statistical distortion:
• Only one outcome per event is recorded
• A cooldown period prevents immediate re-counting of the same struggle
• Each event is counted once, regardless of intraday noise
This ensures clean, independent data points.
The Final Metric
The indicator produces a single core metric:
RespectRatio = Bounces / (Bounces + Breaks)
Calculated over a rolling historical window.
How to Interpret RespectRatio
• High RespectRatio
The moving average has historically acted as reliable support
→ suitable for accumulation or holding strategies
• Low RespectRatio
The moving average is frequently violated
→ caution when relying on it as support
RespectRatio does not predict future price, but measures structural trustworthiness.
What RespectRatio Is Not
• Not a buy/sell signal generator
• Not a trend-following indicator
• Not a momentum oscillator
It is a contextual filter* that improves decision quality.
Typical Use Cases
• Evaluating whether a stock deserves to be bought near a long-term MA
• Comparing multiple stocks using the same moving average
• Filtering candidates before applying other strategies
• Long-term portfolio decision support
One-Sentence Summary
RespectRatio quantifies how often the market actually respects a moving average — turning a visual assumption into measurable probability.*
RVOL Highlighter (Bullish Volume Spikes)Description:
A simple yet powerful indicator that highlights candles with unusually high buying volume.
What it does:
Identifies candles where relative volume (RVOL) exceeds your chosen threshold AND the candle is bullish (green). These high-volume bullish candles often signal strong institutional buying interest or momentum breakouts.
How it works:
Calculates RVOL by comparing current volume to the simple moving average of volume over your selected period
Only highlights candles that meet BOTH conditions: RVOL above threshold + bullish close
Highlighted candles appear in bright magenta for easy visibility on dark mode charts
Settings:
RVOL Period: Lookback period for average volume calculation (default: 10)
RVOL Threshold: Minimum relative volume multiplier to trigger highlight (default: 2.5x)
Highlight Color: Customizable (default: magenta #FF00FF)
Use cases:
Spot potential breakout entries with volume confirmation
Identify accumulation zones
Filter for high-conviction bullish moves
Works on any timeframe and any asset. The actual RVOL value is available in the data window when hovering over candles.
USDT: Market cap changeUSDT: Market Cap Change
This indicator tracks the market capitalization changes of major stablecoins (USDT, USDC, and DAI) to help identify capital flows in the cryptocurrency market.
Features:
Monitor daily and custom period market cap changes for selected stablecoins
Configurable stablecoin selection (USDT, USDC, DAI)
Adjustable lookback period for measuring market cap changes
Multiple moving average types (SMA, EMA, HMA, WMA, RMA) for trend analysis
Visual representation with columns for daily changes and area fill for custom period changes
How to Use:
The indicator displays two main metrics: daily market cap change (shown as columns) and custom period change (shown as a line with area fill). Positive values indicate capital inflow into stablecoins, which may suggest accumulation or risk-off sentiment. Negative values indicate capital outflow, potentially signaling deployment into other crypto assets.
The moving average overlay helps identify trends in stablecoin market cap changes over time.
Settings:
Select which stablecoins to track
Adjust the lookback period (default: 60 days)
Toggle and configure the moving average overlay
Customize MA type and length
Data Source:
Uses Glassnode market capitalization data for USDT, USDC, and DAI on a daily timeframe.
Tradix COR Report Index📊 Tradix COT Report Index
The Tradix COT Report Index is an advanced market sentiment and positioning tool built on official Commitment of Traders (COT) Report data, designed to reveal how major market participants are truly positioned, beyond what price alone can show.
Instead of focusing on short-term price movements, the COT Report Index analyzes real futures positioning reported to the CFTC and categorizes it into three key groups:
Commercials – hedgers and so-called smart money
Non-Commercials – institutions, funds, and large speculators
Retail / Non-Reportables – small traders and crowd positioning
Raw positioning data (Long − Short) is transformed into a normalized 0–100 index, allowing traders to instantly identify extreme market sentiment, structural imbalances, and potential turning points — without manually interpreting complex COT tables.
🧠 How the Tradix COT Index Works
The index evaluates current net positions within a historical range (typically the last 52 weeks). This contextual approach makes it easy to see:
when Commercials are at extreme long or short levels
when speculative positioning becomes overcrowded
when the market reaches structural imbalance, increasing the probability of a mean-reversion or trend shift
By standardizing positioning data, the Tradix COT Index allows cross-market comparison, making it equally useful for indices, commodities, currencies, and futures-based CFDs.
🎯 How Traders Use It
The Tradix COT Report Index is not an entry signal tool.
Instead, it acts as a high-timeframe confirmation and market context indicator, commonly used for:
identifying long-term market bias
spotting divergences between price and positioning
confirming trend exhaustion or accumulation phases
filtering trades to align with institutional positioning
When combined with technical analysis, seasonality, and risk management, the COT Index provides a statistical edge rooted in real positioning data, not opinions or lagging indicators.
⚠️ Important Notes
COT data is updated weekly, not in real time
Best used on higher timeframes (Daily, Weekly)
Designed to enhance decision-making, not to replace trading systems
5 Layer Script P5 ICT Identifier Package (Sessions + Narrative)This script is a session-based market narrative framework designed to help traders understand where price is likely seeking liquidity and alignment, rather than focusing on isolated entries.
This script mainly identifies and labels the Asia, London, and New York trading sessions, providing structure for how price behavior evolves throughout the day. It is intended to be used as a context and timing tool.
How it works
-Automatically maps Asia, London, and New York sessions
-Highlights session ranges and transitions
-Helps visualize accumulation, expansion, and distribution phases
-No repainting once a session is completed
How to use it
-Use Asia to observe range formation and liquidity build-up
-Use London for expansion, manipulation, or early continuation
-Use New York for confirmation, continuation, or reversal (IMPORTANT)
-Align session behavior with:
Higher-timeframe bias
Midpoint equilibrium levels
Fair Value Gaps
Signal or Potential Reversal confirmations
Best practices
-Avoid treating sessions as directional signals
-Focus on session objectives, not candle patterns
-Most effective on futures, indices, and liquid FX pairs
-Works best when combined with higher-timeframe structure
This package is intentionally narrative-driven and non-mechanical, allowing traders to frame intraday price action within a repeatable session logic rather than reactive decision-making.
ADDITIONAL: If youve made it this far i will tell you a cheat code to this specific script. Once you alligned your standard time for the sessions you will notice that if you set the sessions to close properly i recommend asking Chatgpt or any other AI tool, you will notice that the sessions end a few hours earlier for NY. You should see a label pop up for the NY just like the Asia and London session. That signal will tell you the next potential move only if you utilize the ICT killzones cheatsheet, easy to find on google images and I will attach it here if possible. its definetly mixed up but thats just market structure, only one you should pay attention to take a trade is the end of the NY session if adjusted properly. over 90% success rate following this strategy. I will add the link for the full cheat sheet below
www.scribd.com
Pulse Volume Commitment [JOAT]
Pulse Volume Commitment - Three-Dimensional Momentum Analysis
Introduction and Purpose
Pulse Volume Commitment is an open-source oscillator indicator that analyzes price action through three distinct dimensions: Quantity (candle count), Quality (body structure), and Commitment (volume-weighted quality). The core problem this indicator solves is that simple bullish/bearish candle counts miss important context. A market can have more green candles but still be weak if those candles have small bodies and low volume.
This indicator addresses that by requiring all three dimensions to align before generating strong signals, filtering out weak moves that lack conviction.
Why These Three Dimensions Work Together
Each dimension measures a different aspect of market conviction:
1. Quantity - Counts bullish vs bearish candles over the lookback period. Tells you WHO is winning the candle count battle.
2. Quality - Scores candles by body size relative to total range. Full-bodied candles (small wicks) indicate stronger conviction than doji-like candles. Tells you HOW decisively price is moving.
3. Commitment - Weights quality scores by volume. High-quality candles on high volume indicate institutional participation. Tells you WHETHER smart money is involved.
When all three align (e.g., more bullish candles + bullish quality + bullish commitment), the signal is significantly more reliable.
How the Calculations Work
Quantity Analysis:
int greenCount = 0
int redCount = 0
for i = 0 to lookbackPeriod - 1
if close > open
greenCount += 1
if close < open
redCount += 1
bool quantityBull = greenCount > redCount
Quality Analysis (body-to-range scoring):
for i = 0 to lookbackPeriod - 1
float candleBody = close - open // Signed (positive = bull)
float candleRange = high - low
float bodyQuality = candleRange > 0 ? (candleBody / candleRange * 100) * candleRange : 0.0
sumBodyQuality += bodyQuality
bool qualityBull = sumBodyQuality > 0
Signal Types
FULL BULL - All three dimensions bullish (Quantity + Quality + Commitment)
FULL BEAR - All three dimensions bearish
LEAN BULL/BEAR - 2 of 3 dimensions agree
MIXED - No clear consensus
STRONG BUY/SELL - Full confluence + ADX confirms trending market
ADX Integration
The indicator includes ADX (Average Directional Index) to filter signals:
- ADX >= 20 = TRENDING market (signals more reliable)
- ADX < 20 = RANGING market (signals may whipsaw)
Strong signals only trigger when full confluence occurs in a trending environment.
Dashboard Information
Quantity - BULL/BEAR/FLAT with green/red candle ratio
Quality - Directional bias based on body quality scoring
Commit - Volume-weighted commitment reading
ADX - Trend strength (TRENDING/RANGING)
Signal - Confluence status (FULL BULL/FULL BEAR/LEAN/MIXED)
Action - STRONG BUY/STRONG SELL/WAIT
How to Use This Indicator
For High-Conviction Entries:
1. Wait for FULL BULL or FULL BEAR confluence
2. Confirm ADX shows TRENDING
3. Enter when Action shows STRONG BUY or STRONG SELL
For Filtering Weak Setups:
1. Avoid entries when signal shows MIXED
2. Be cautious when ADX shows RANGING
3. Require at least 2 of 3 dimensions to agree
For Divergence Analysis:
1. Watch for Quantity bullish but Commitment bearish (distribution)
2. Watch for Quantity bearish but Commitment bullish (accumulation)
Input Parameters
Lookback Period (9) - Bars to analyze for all three dimensions
ADX Smoothing (14) - Period for ADX calculation
ADX DI Length (14) - Period for directional indicators
Timeframe Recommendations
15m-1H: Good for intraday momentum analysis
4H-Daily: Best for swing trading confluence
Lookback period may need adjustment for different timeframes
Limitations
Lookback period affects signal responsiveness vs reliability tradeoff
Volume data quality varies by exchange
ADX filter may cause missed entries in early trends
Works best on liquid instruments with consistent volume
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Confluence signals do not guarantee profitable trades. Always use proper risk management.
- Made with passion by officialjackofalltrades
BTC - Cycle Integrity Index (CII) BTC - Cycle Integrity Index (CII) | RM
Are we following a calendar or a capital flow? Is the Halving still the heartbeat of Bitcoin, or has the institutional "Engine" taken over?
The most polarized debate in the digital asset space today centers on a single question: Is the 4-year Halving Cycle dead? While some market participants wait for a pre-ordained calendar countdown, the reality of 2026 suggests that visual guesswork is no longer sufficient. As institutional gravity takes hold, we cannot rely on the simple "Clock" of the past. Instead, we must audit the Integrity of the present.
The Cycle Integrity Index (CII) was engineered to move beyond simple price action and provide a clinical answer to the market's biggest mystery: "Is this trend supported by structural substance, or is it merely speculative foam?" By aggregating eight diverse Pillars into a single 0-100% score, this model uses Gaussian Distributions and Sigmoid Normalization to distinguish between professional accumulation and retail-driven chaos. We aren't guessing where we are in a cycle; we are measuring the internal health of the asset's engine in real-time.
Why these 8 Pillars?
The CII does not rely on a single indicator because the "New Era" of Bitcoin is multi-dimensional. To capture the full picture, I selected eight specific pillars that cover the three layers of market truth:
• The Capital Layer: Global Liquidity (M2) and ETF Flows (Wall Street Absorption).
• The Network Layer: Mining Difficulty and Security Backbone expansion.
• The Sentiment Layer: Long-Term Holder conviction, Valuation Heat (MVRV), and Corporate Adoption (MSTR). While alternatives like the Pi Cycle or RSI exist, they are often "one-dimensional." The CII is a synthesis—a modular engine where every part validates the others.
How the Calculation Works
The CII is a sophisticated model for Bitcoin. It aggregates 8 diverse pillars into a single 0-100% score in the following way:
• Mathematical Normalization: We don't just use raw prices. We use Gaussian Distributions to find "Institutional DNA" in drawdowns and Sigmoid (S-Curve) functions to score volatility and valuation.
• Dynamic Weighting: The index is modular. If a data source (like a specific on-chain metric) is toggled off, the engine automatically redistributes the weight among the active sensors so the final integrity score is always balanced to 100%.
• Multi-Source Integration: The script pulls from Global Liquidity (M2), ETF flows, Corporate Treasury premiums (MSTR), and Network Difficulty to create a truly "Full-Stack" view of the asset.
The 8 Pillars of Integrity
Pillar 1: Drawdown DNA The "Identity Crisis" Filter
• Concept: Audits the depth of corrections to distinguish between "Institutional Floors" and "Retail Panics."
• Logic: Historically, retail crashes reached -80%, while institutions view -20% to -25% as primary value entries.
• Implementation: Uses a Gaussian (Normal) Distribution centered at -25%. Scores of 10/10 are awarded for holding institutional targets; scores decay as drawdowns accelerate toward legacy "crash" levels.
Basis: DNA Drawdown
Pillar 2: Volatility Regime The "Smoothness" Audit
• Concept: Measures the "vibration" of the trend. High-integrity moves are characterized by "smooth" price action.
• Logic: Erratic volatility signals speculative bubbles; consistent "volatility clusters" indicate professional trend-following.
• Implementation: Calculates a Z-Score of the 14-day ATR against a 100-day benchmark. This is passed through a Sigmoid function to penalize "chaotic" price shocks while rewarding stability.
Basis: RVPM
Pillar 3: Liquidity Sync (Global M2) The Macro Heartbeat
• Concept: Audits whether price growth is fueled by monetary expansion or internal speculative leverage.
• Logic: True cycle integrity requires a positive correlation between Central Bank balance sheets and price action.
• Implementation: Aggregates a custom Global Liquidity Proxy (Fed, RRP, TGA, PBoC, ECB, BoJ). It measures the Pearson Correlation between BTC and M2 with a standardized 80-day transmission lag.
Basis: Liquisync
Pillar 4: ETF Absorption (Wall Street Entry) The "Cost Basis" Defense
• Concept: Tracks the aggregate institutional cost-basis since the January 2024 Spot ETF launch.
• Logic: Integrity is high when the "Wall Street Floor" is defended; it fails when the aggregate position is underwater.
• Implementation: A Cumulative VWAP engine tracking the "Big 3" (IBIT, FBTC, BITB). Scoring decays based on the percentage distance the price drifts below this institutional average entry.
Basis: Institutional Cost Corridor
Note: Turning this to OFF will significantly expand the timeframe of the indicator on the chart (otherwise it will just start in 2024)
Pillar 5: LTH Dormancy (Conviction) The HODL Floor Audit
• Concept: Monitors the conviction of Long-Term Holders (LTH) to identify supply-side constraints.
• Logic: Sustainable cycles require stable or increasing 1Y+ dormant supply; rapid "thawing" signals distribution.
• Implementation: Uses Min-Max Normalization on the Active 1Y Supply over a 252-day window. A score of 10/10 indicates peak annual holding conviction.
Basis: RHODL Proxy & VDD Multiple
Pillar 6: Valuation Intensity The MVRV Heat Map
• Concept: Measures market "overheat" by comparing Market Value to Realized Value.
• Logic: High integrity trends rise steadily; vertical spikes in MVRV indicate "speculative foam" and bubble risk.
• Implementation: Performs a Relative Rank Analysis of the MVRV Ratio over a 730-day window, passed through a high-steepness Sigmoid curve to identify extreme valuation anomalies.
Pillar 7: Miner Stress The Security Backbone
• Concept: Tracks Mining Difficulty to ensure network infrastructure is expanding alongside price.
• Logic: Difficulty expansion signals health; drops in difficulty (Miner Stress) signal capitulation and sell-side pressure.
• Implementation: Monitors the 30-day Rate of Change (ROC) of Global Mining Difficulty. Maintains a 10/10 score during expansion; decays rapidly during network contraction.
Pillar 8: Corporate Adoption The MSTR NAV Proxy
• Concept: Audits the MicroStrategy (MSTR) premium as a barometer for institutional demand.
• Logic: A high premium indicates a willingness to pay a "convenience fee" for BTC exposure; a collapsing premium signals waning appetite.
• Implementation: Calculates the Adjusted Enterprise Value (Market Cap + Debt - Cash) relative to the Net Asset Value (NAV) of its BTC holdings.
Note1: Debt and share parameters are user-adjustable to maintain accuracy as corporate balance sheets evolve.
Note2: I just included this because I was curious about the mNAV calculation I saw in other scripts, where the printed value often does not match exactly the propagated value from the MSTR page itself. Hence, for my live calculation, we calculate the Adjusted Enterprise Value to find the "Market NAV" (mNAV). Unlike simpler scripts that only look at Market Cap vs. Bitcoin holdings, our engine accounts for the Capital Structure . We explicitly factor in the corporate debt (approx. $8.24B long-term + $7.95B convertible notes) and subtract the cash reserves (approx. $2.18B) to find the true cost Wall Street is paying for the underlying Bitcoin. Since this will ran "old" very quickly, I recommend to update in the code by yourself from time to time, or just de-select this parameter.
Interpretation Guide
• Score 100% (The Perfect Storm): This represents a state of "Maximum Integrity." All 8 pillars are in perfect institutional alignment—liquidity is surging, conviction is at yearly highs, and price action is perfectly smooth. This is the hallmark of a healthy, structural parabolic run.
• 75% - 100% (High Integrity): Robust trend. Price is supported by structural demand and macro tailwinds.
• 35% - 75% (Equilibrium): Transition zone. The market is digesting gains or waiting for a new liquidity pulse.
• 0% - 35% (Fragile): Speculative foam. Structural support has failed.
• Score 0% (The Ghost Trend): Absolute structural failure. All pillars (liquidity, miners, LTH, ETFs) have broken down. Note: Due to the robust nature of the Bitcoin network, the index naturally floors around 20-30% during deep bear markets, as specific pillars (like Miner Security) rarely drop to zero.
To provide a complete experience, I have included the Cycle Triad —a visualization layer consisting of the Halving, Ideal Peak, and Ideal Low. It is important to understand the role of this feature:
• Benchmark Only (Not Calculated): The Triad is based purely on historical evidence from previous Bitcoin epochs. While the Halving is fixed anyway, the "Ideal Peak" or "Ideal Low" are not calculated or computed by the 8 pillars. These are user-adjustable temporal anchors drawn on the chart to provide a static map of the "Legacy 4-Year Cycle."
• The Temporal Audit: The power of the CII lies in comparing the Engine (the 8 Pillars) against the Clock (the Triad) . By overlaying historical time-windows on top of our integrity math, we can see if the "New Era" is currently ahead of, behind, or perfectly in sync with the past.
• The "Peak Divergence" Logic: Based on the specific models selected for this ECU—specifically Volatility Decay and Valuation Heat —traders will notice that a cycle peak often coincides with a low integrity score (Red Zone) . While the index measures structural health, a low score is a byproduct of a market that has become "too hot to handle."
• Regime Detection: Although the primary goal is to audit the "New Era," the CII is highly effective at detecting overheated regimes. When the score drops toward the 25–35% range, the structural floor is giving way to speculative foam—making it a dual-purpose tool for both cycle analysis and risk management.
Dashboard Calibration & Settings
Cycle Triad Calibration
• Ideal Peak/Trough Window: Defines the historical "Average Days" from a Halving to the cycle top and bottom. This sets the vertical anchors for the Halving, Peak, and Low labels.
• Show Cycle Triad: A master toggle to enable or disable the temporal lines and labels on your dashboard.
The CII Master ECU is fully modular. You can toggle individual pillars ON/OFF to focus on specific market dimensions, and calibrate the sensitivity of each sensor to match your strategic bias.
• P1: Drawdown DNA Lookback (Weeks): Defines the window for the "Rolling High." Inst. Target (%): The specific percentage drawdown you define as "Institutional Support" (e.g., -25%).
• P2: Volatility Regime Benchmark (Days): The historical window used to define "Normal" vs. "Abnormal" volatility.
• P3: Liquidity Sync Corr. Window (Bars): The lookback for the Pearson Correlation calculation. Transmission Lag (Bars): The delay (standard 80 days) for Central Bank M2 to hit price.
• P4: ETF Absorption FBTC Ticker: The data source for the ETF volume audit (Default: CBOE:FBTC).
• P5: LTH Dormancy LTH Source: The ticker for 1Y+ Active Supply (Default: GLASSNODE:BTC_ACTIVE1Y). Norm. Window: The lookback (252 days) used to rank current conviction.
• P6: Valuation Intensity MVRV Source: The ticker for the MVRV Ratio (Default: INTOTHEBLOCK:BTC_MVRV). Relative Window: The lookback (730 days) to calculate the valuation rank.
• P7: Miner Stress Mining Diff: The data source for Global Mining Difficulty (Default: QUANDL:BCHAIN/DIFF).
• P8: Corporate Adoption Shares (M) & BTC (K): The balance sheet parameters for MicroStrategy (MSTR). Update these as the company executes new purchases to maintain mNAV accuracy.
Operational Usage This index is best used on the Daily (D) (recommended - description for inputs optimized for this time-window) or Weekly (W) timeframes. While the code is optimized to fetch daily data regardless of your chart setting, the structural "Integrity" of a cycle is a macro phenomenon and should be viewed with a medium-to-long-term lens.
The Verdict: Is the 4-Year Cycle Still Alive?
Based on the data provided by the CII Master ECU, the answer remains a nuanced "Work in Progress." The evidence presents a fascinating conflict between legacy patterns and the new institutional regime:
• The Case for the Cycle: Historically, a local "Peak" in price corresponds with a "Local Low" in our integrity indicator (Red Zone). We observed this exact phenomenon in October 2025. When viewed through the lens of the "Ideal Peak" anchor, this alignment suggests that the 4-year temporal rhythm is still exerts a massive influence on market behavior.
• The Case for the New Era: While the timing of the October 2025 peak followed the legacy script, the intensity did not. Previous cycle tops produced far more aggressive and persistent "Red Zone" clusters. The relative brevity of the integrity breakdown suggests that the "Institutional Era" provides a much higher floor than the retail-driven bubbles of 2017 and 2021.
• The Institutional Floor: Our data shows that while "Tops" still resemble the 4-year cycle, the "Lows" now reflect a regime of constant institutional absorption. This suggests that the brutal 80% drawdowns of the past may be replaced by the "Institutional DNA" of Pillar 1.
Final Outlook: As we move through 2026, the ultimate test lies in the Q3/Q4 window. While classical theory demands a "Cycle Low" during this period, the CII will be our primary auditor. We cannot definitively say the cycle is dead, but we can say it has evolved. We will not know if the 4-year low will manifest until the model either flags a total structural breakdown or confirms that the institutional "Floor" has permanently shifted the rhythm of the asset.
Tags: Bitcoin, Institutional, Macro, On-chain, Liquidity, MSTR, ETF, Cycle
Note to Moderators: This script is a "Master Index" that aggregates several quantitative models I have previously published on this platform (including DNA Drawdown, RVPM, and Liquisync). I am the original author of the logic and source code referenced in the "Basis" sections of the description.
OBV Apex: Donchian-Bollinger Dual Resonance (DBDR)以下是为您定制的 **OBV Apex: DBDR (Donchian-Bollinger Dual Resonance)** 指标双语简介。
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## 指标简介 / Indicator Overview
**OBV Apex: Donchian-Bollinger Dual Resonance (DBDR)** 是一款专为捕捉高概率趋势反转和波动率爆发而设计的尖端量价指标。它打破了传统指标单一维度的局限，将基于绝对价格区间的**唐奇安通道逻辑**与基于统计学概率分布的**布林带动能逻辑**深度融合，旨在为交易者提供“跨维度共振”的决策依据。
**OBV Apex: Donchian-Bollinger Dual Resonance (DBDR)** is a cutting-edge volume-price indicator designed to capture high-probability trend reversals and volatility breakouts. It breaks the limitations of single-dimensional indicators by integrating **Donchian Channel logic** (based on absolute price ranges) with **Bollinger Band momentum logic** (based on statistical probability distribution), providing traders with a "cross-dimensional resonance" framework for decision-making.
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## 核心功能与视觉识别 / Key Features & Visual Identification
### **1. 智能变色主线 / Intelligent Multi-Color Main Line**
指标 OBV 主线根据当前动能状态实时切换颜色。
* **白色 (极端区)**：当 OBV 触碰或刺破唐奇安通道轨道时变为白色，提示动能进入超买或超卖的极端区域。
* **绿色/红色 (趋势区)**：代表 OBV 突破了中轨缓冲区，确认了当前的上涨或下跌趋势。
* **黄色 (噪音区)**：OBV 处于缓冲区内部，提示市场处于震荡或无方向阶段。
The main OBV line switches colors in real-time based on momentum states.
* **White (Extreme)**: Turns white when OBV touches or pierces Donchian boundaries, signaling extreme overbought/oversold momentum.
* **Green/Red (Trend)**: Indicates OBV has broken out of the mid-rail buffer, confirming an uptrend or downtrend.
* **Yellow (Noise)**: OBV stays within the buffer zone, suggesting a sideways or directionless market.
### **2. 波动率挤压背景 / Volatility Squeeze Background**
当唐奇安通道大幅收窄，代表市场进入蓄力阶段。此时离散区域（Dispersion Area）会变为**深紫色**，这是即将发生大级别变盘的重要视觉信号。
When the Donchian Channel narrows significantly, it represents a market accumulation phase. The Dispersion Area turns **Deep Purple**, providing a crucial visual signal for an impending major volatility breakout.
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## 详细用法说明 / Detailed Usage Instructions
### **1. 逻辑共振星号 (⭐) 的实战意义 / Strategic Meaning of the Resonance Star (⭐)**
这是本指标最具价值的核心信号。
* **基础信号 (R/H)**：当唐奇安系统检测到结构性背离时产生。
* **共振信号 (⭐)**：仅当后台隐藏的布林带算法也同时检测到逻辑背离时，信号后才会附带 ⭐。
* **用法**：普通 R 信号仅代表价格结构的衰竭，而 **R⭐** 则代表空间结构与波动率动能的**双重衰竭**。在实战中，带有星号的信号具有极高的反转成功率，是摸顶抄底的核心参考。
This is the most valuable core signal of the indicator.
* **Basic Signals (R/H)**: Generated when the Donchian system detects structural divergence.
* **Resonance Signal (⭐)**: A star is appended only when the hidden Bollinger Band algorithm also detects logical divergence simultaneously.
* **Usage**: A standard R signal represents structural exhaustion, while **R⭐** signifies **dual exhaustion** of both space structure and volatility momentum. In practice, signals with stars offer significantly higher reversal success rates.
### **2. 顶点爆发策略 (突破交易) / The Apex Explosion Strategy (Breakout)**
* **观察**：寻找背景出现持续**深紫色**填充的区域（挤压期）。
* **入场**：当 OBV 主线由黄转绿（多头突破）或由黄转红（空头突破）并脱离紫色区域时，是爆发性行情的起始点。
* **Observation**: Look for areas with continuous **Deep Purple** background filling (Squeeze phase).
* **Entry**: When the OBV line shifts from yellow to green (Bullish breakout) or red (Bearish breakout) and exits the purple zone, it marks the start of an explosive trend.
### **3. 双重共振反转策略 (反转交易) / Double Resonance Reversal Strategy**
* **确认条件**：OBV 主线变为**白色**进入极端区，随后出现带有 **⭐** 的背离标签。
* **辅助确认**：观察 KDJ 标签。如果共振星号出现后，KDJ 产生顺势的大写 **B (Buy)** 或 **S (Sell)** 标签，则反转的确定性进一步增强。
* **Confirmation**: The OBV line turns **White** (Extreme zone), followed by a divergence label with a **⭐**.
* **Secondary Confirmation**: Monitor KDJ labels. If an uppercase **B (Buy)** or **S (Sell)** appears after the resonance star, the certainty of the reversal is further enhanced.
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## 下一步建议 / Next Step
您现在可以根据此简介进行实盘复盘。如果您需要我将**警报逻辑 (Alerts)** 进一步细化，例如针对“带星号的背离”设置专门的推送提醒，请随时告诉我。
You can now use this overview for backtesting. If you need me to further refine the **Alert logic**, such as setting specific push notifications for "Divergence with Star," please let me know.
Log Trend Channel Enhanced**Log Trend Channel Enhanced (LTC+)**
A logarithmic regression channel with 11 deviation bands and comprehensive statistical metrics.
**Features:**
- Logarithmic regression trendline from customizable start date
- 11 parallel bands at ±0.5σ, ±1σ, ±1.5σ, ±2σ, ±2.5σ standard deviations
- Color-coded zones (green = undervalued, red = overvalued)
**Metrics displayed:**
- R² (goodness of fit)
- Pearson correlation
- Implied CAGR (annualized return from trendline)
- Distance from trend (%)
- Current σ position
- Channel position (%)
- Historical percentile rank
**Usage:**
Ideal for long-term trend analysis on assets with exponential growth patterns. Use on log-scale charts for best visualization. Green zones near -2σ historically indicate accumulation opportunities; red zones near +2σ suggest distribution phases.
**Settings:**
- Adjustable start date (default: 1 year ago)
- Customizable colors and line widths
- Optional deviation labels
- Configurable future projection
