Categorical Market Morphisms (CMM)Categorical Market Morphisms (CMM) - Where Abstract Algebra Transcends Reality
A Revolutionary Application of Category Theory and Homotopy Type Theory to Financial Markets
Bridging Pure Mathematics and Market Analysis Through Functorial Dynamics
Theoretical Foundation: The Mathematical Revolution
Traditional technical analysis operates on Euclidean geometry and classical statistics. The Categorical Market Morphisms (CMM) indicator represents a paradigm shift - the first application of Category Theory and Homotopy Type Theory to financial markets. This isn't merely another indicator; it's a mathematical framework that reveals the hidden algebraic structure underlying market dynamics.
Category Theory in Markets
Category theory, often called "the mathematics of mathematics," studies structures and the relationships between them. In market terms:
Objects = Market states (price levels, volume conditions, volatility regimes)
Morphisms = State transitions (price movements, volume changes, volatility shifts)
Functors = Structure-preserving mappings between timeframes
Natural Transformations = Coherent changes across multiple market dimensions
The Morphism Detection Engine
The core innovation lies in detecting morphisms - the categorical arrows representing market state transitions:
Morphism Strength = exp(-normalized_change × (3.0 / sensitivity))
Threshold = 0.3 - (sensitivity - 1.0) × 0.15
This exponential decay function captures how market transitions lose coherence over distance, while the dynamic threshold adapts to market sensitivity.
Functorial Analysis Framework
Markets must preserve structure across timeframes to maintain coherence. Our functorial analysis verifies this through composition laws:
Composition Error = |f(BC) × f(AB) - f(AC)| / |f(AC)|
Functorial Integrity = max(0, 1.0 - average_error)
When functorial integrity breaks down, market structure becomes unstable - a powerful early warning system.
Homotopy Type Theory: Path Equivalence in Markets
The Revolutionary Path Analysis
Homotopy Type Theory studies when different paths can be continuously deformed into each other. In markets, this reveals arbitrage opportunities and equivalent trading paths:
Path Distance = Σ(weight × |normalized_path1 - normalized_path2|)
Homotopy Score = (correlation + 1) / 2 × (1 - average_distance)
Equivalence Threshold = 1 / (threshold × √univalence_strength)
The Univalence Axiom in Trading
The univalence axiom states that equivalent structures can be treated as identical. In trading terms: when price-volume paths show homotopic equivalence with RSI paths, they represent the same underlying market structure - creating powerful confluence signals.
Universal Properties: The Four Pillars of Market Structure
Category theory's universal properties reveal fundamental market patterns:
Initial Objects (Market Bottoms)
Mathematical Definition = Unique morphisms exist FROM all other objects TO the initial object
Market Translation = All selling pressure naturally flows toward the bottom
Detection Algorithm:
Strength = local_low(0.3) + oversold(0.2) + volume_surge(0.2) + momentum_reversal(0.2) + morphism_flow(0.1)
Signal = strength > 0.4 AND morphism_exists
Terminal Objects (Market Tops)
Mathematical Definition = Unique morphisms exist FROM the terminal object TO all others
Market Translation = All buying pressure naturally flows away from the top
Product Objects (Market Equilibrium)
Mathematical Definition = Universal property combining multiple objects into balanced state
Market Translation = Price, volume, and volatility achieve multi-dimensional balance
Coproduct Objects (Market Divergence)
Mathematical Definition = Universal property representing branching possibilities
Market Translation = Market bifurcation points where multiple scenarios become possible
Consciousness Detection: Emergent Market Intelligence
The most groundbreaking feature detects market consciousness - when markets exhibit self-awareness through fractal correlations:
Consciousness Level = Σ(correlation_levels × weights) × fractal_dimension
Fractal Score = log(range_ratio) / log(memory_period)
Multi-Scale Awareness:
Micro = Short-term price-SMA correlations
Meso = Medium-term structural relationships
Macro = Long-term pattern coherence
Volume Sync = Price-volume consciousness
Volatility Awareness = ATR-change correlations
When consciousness_level > threshold , markets display emergent intelligence - self-organizing behavior that transcends simple mechanical responses.
Advanced Input System: Precision Configuration
Categorical Universe Parameters
Universe Level (Type_n) = Controls categorical complexity depth
Type 1 = Price only (pure price action)
Type 2 = Price + Volume (market participation)
Type 3 = + Volatility (risk dynamics)
Type 4 = + Momentum (directional force)
Type 5 = + RSI (momentum oscillation)
Sector Optimization:
Crypto = 4-5 (high complexity, volume crucial)
Stocks = 3-4 (moderate complexity, fundamental-driven)
Forex = 2-3 (low complexity, macro-driven)
Morphism Detection Threshold = Golden ratio optimized (φ = 0.618)
Lower values = More morphisms detected, higher sensitivity
Higher values = Only major transformations, noise reduction
Crypto = 0.382-0.618 (high volatility accommodation)
Stocks = 0.618-1.0 (balanced detection)
Forex = 1.0-1.618 (macro-focused)
Functoriality Tolerance = φ⁻² = 0.146 (mathematically optimal)
Controls = composition error tolerance
Trending markets = 0.1-0.2 (strict structure preservation)
Ranging markets = 0.2-0.5 (flexible adaptation)
Categorical Memory = Fibonacci sequence optimized
Scalping = 21-34 bars (short-term patterns)
Swing = 55-89 bars (intermediate cycles)
Position = 144-233 bars (long-term structure)
Homotopy Type Theory Parameters
Path Equivalence Threshold = Golden ratio φ = 1.618
Volatile markets = 2.0-2.618 (accommodate noise)
Normal conditions = 1.618 (balanced)
Stable markets = 0.786-1.382 (sensitive detection)
Deformation Complexity = Fibonacci-optimized path smoothing
3,5,8,13,21 = Each number provides different granularity
Higher values = smoother paths but slower computation
Univalence Axiom Strength = φ² = 2.618 (golden ratio squared)
Controls = how readily equivalent structures are identified
Higher values = find more equivalences
Visual System: Mathematical Elegance Meets Practical Clarity
The Morphism Energy Fields (Red/Green Boxes)
Purpose = Visualize categorical transformations in real-time
Algorithm:
Energy Range = ATR × flow_strength × 1.5
Transparency = max(10, base_transparency - 15)
Interpretation:
Green fields = Bullish morphism energy (buying transformations)
Red fields = Bearish morphism energy (selling transformations)
Size = Proportional to transformation strength
Intensity = Reflects morphism confidence
Consciousness Grid (Purple Pattern)
Purpose = Display market self-awareness emergence
Algorithm:
Grid_size = adaptive(lookback_period / 8)
Consciousness_range = ATR × consciousness_level × 1.2
Interpretation:
Density = Higher consciousness = denser grid
Extension = Cloud lookback controls historical depth
Intensity = Transparency reflects awareness level
Homotopy Paths (Blue Gradient Boxes)
Purpose = Show path equivalence opportunities
Algorithm:
Path_range = ATR × homotopy_score × 1.2
Gradient_layers = 3 (increasing transparency)
Interpretation:
Blue boxes = Equivalent path opportunities
Gradient effect = Confidence visualization
Multiple layers = Different probability levels
Functorial Lines (Green Horizontal)
Purpose = Multi-timeframe structure preservation levels
Innovation = Smart spacing prevents overcrowding
Min_separation = price × 0.001 (0.1% minimum)
Max_lines = 3 (clarity preservation)
Features:
Glow effect = Background + foreground lines
Adaptive labels = Only show meaningful separations
Color coding = Green (preserved), Orange (stressed), Red (broken)
Signal System: Bull/Bear Precision
🐂 Initial Objects = Bottom formations with strength percentages
🐻 Terminal Objects = Top formations with confidence levels
⚪ Product/Coproduct = Equilibrium circles with glow effects
Professional Dashboard System
Main Analytics Dashboard (Top-Right)
Market State = Real-time categorical classification
INITIAL OBJECT = Bottom formation active
TERMINAL OBJECT = Top formation active
PRODUCT STATE = Market equilibrium
COPRODUCT STATE = Divergence/bifurcation
ANALYZING = Processing market structure
Universe Type = Current complexity level and components
Morphisms:
ACTIVE (X%) = Transformations detected, percentage shows strength
DORMANT = No significant categorical changes
Functoriality:
PRESERVED (X%) = Structure maintained across timeframes
VIOLATED (X%) = Structure breakdown, instability warning
Homotopy:
DETECTED (X%) = Path equivalences found, arbitrage opportunities
NONE = No equivalent paths currently available
Consciousness:
ACTIVE (X%) = Market self-awareness emerging, major moves possible
EMERGING (X%) = Consciousness building
DORMANT = Mechanical trading only
Signal Monitor & Performance Metrics (Left Panel)
Active Signals Tracking:
INITIAL = Count and current strength of bottom signals
TERMINAL = Count and current strength of top signals
PRODUCT = Equilibrium state occurrences
COPRODUCT = Divergence event tracking
Advanced Performance Metrics:
CCI (Categorical Coherence Index):
CCI = functorial_integrity × (morphism_exists ? 1.0 : 0.5)
STRONG (>0.7) = High structural coherence
MODERATE (0.4-0.7) = Adequate coherence
WEAK (<0.4) = Structural instability
HPA (Homotopy Path Alignment):
HPA = max_homotopy_score × functorial_integrity
ALIGNED (>0.6) = Strong path equivalences
PARTIAL (0.3-0.6) = Some equivalences
WEAK (<0.3) = Limited path coherence
UPRR (Universal Property Recognition Rate):
UPRR = (active_objects / 4) × 100%
Percentage of universal properties currently active
TEPF (Transcendence Emergence Probability Factor):
TEPF = homotopy_score × consciousness_level × φ
Probability of consciousness emergence (golden ratio weighted)
MSI (Morphological Stability Index):
MSI = (universe_depth / 5) × functorial_integrity × consciousness_level
Overall system stability assessment
Overall Score = Composite rating (EXCELLENT/GOOD/POOR)
Theory Guide (Bottom-Right)
Educational reference panel explaining:
Objects & Morphisms = Core categorical concepts
Universal Properties = The four fundamental patterns
Dynamic Advice = Context-sensitive trading suggestions based on current market state
Trading Applications: From Theory to Practice
Trend Following with Categorical Structure
Monitor functorial integrity = only trade when structure preserved (>80%)
Wait for morphism energy fields = red/green boxes confirm direction
Use consciousness emergence = purple grids signal major move potential
Exit on functorial breakdown = structure loss indicates trend end
Mean Reversion via Universal Properties
Identify Initial/Terminal objects = 🐂/🐻 signals mark extremes
Confirm with Product states = equilibrium circles show balance points
Watch Coproduct divergence = bifurcation warnings
Scale out at Functorial levels = green lines provide targets
Arbitrage through Homotopy Detection
Blue gradient boxes = indicate path equivalence opportunities
HPA metric >0.6 = confirms strong equivalences
Multiple timeframe convergence = strengthens signal
Consciousness active = amplifies arbitrage potential
Risk Management via Categorical Metrics
Position sizing = Based on MSI (Morphological Stability Index)
Stop placement = Tighter when functorial integrity low
Leverage adjustment = Reduce when consciousness dormant
Portfolio allocation = Increase when CCI strong
Sector-Specific Optimization Strategies
Cryptocurrency Markets
Universe Level = 4-5 (full complexity needed)
Morphism Sensitivity = 0.382-0.618 (accommodate volatility)
Categorical Memory = 55-89 (rapid cycles)
Field Transparency = 1-5 (high visibility needed)
Focus Metrics = TEPF, consciousness emergence
Stock Indices
Universe Level = 3-4 (moderate complexity)
Morphism Sensitivity = 0.618-1.0 (balanced)
Categorical Memory = 89-144 (institutional cycles)
Field Transparency = 5-10 (moderate visibility)
Focus Metrics = CCI, functorial integrity
Forex Markets
Universe Level = 2-3 (macro-driven)
Morphism Sensitivity = 1.0-1.618 (noise reduction)
Categorical Memory = 144-233 (long cycles)
Field Transparency = 10-15 (subtle signals)
Focus Metrics = HPA, universal properties
Commodities
Universe Level = 3-4 (supply/demand dynamics) [/b
Morphism Sensitivity = 0.618-1.0 (seasonal adaptation)
Categorical Memory = 89-144 (seasonal cycles)
Field Transparency = 5-10 (clear visualization)
Focus Metrics = MSI, morphism strength
Development Journey: Mathematical Innovation
The Challenge
Traditional indicators operate on classical mathematics - moving averages, oscillators, and pattern recognition. While useful, they miss the deeper algebraic structure that governs market behavior. Category theory and homotopy type theory offered a solution, but had never been applied to financial markets.
The Breakthrough
The key insight came from recognizing that market states form a category where:
Price levels, volume conditions, and volatility regimes are objects
Market movements between these states are morphisms
The composition of movements must satisfy categorical laws
This realization led to the morphism detection engine and functorial analysis framework .
Implementation Challenges
Computational Complexity = Category theory calculations are intensive
Real-time Performance = Markets don't wait for mathematical perfection
Visual Clarity = How to display abstract mathematics clearly
Signal Quality = Balancing mathematical purity with practical utility
User Accessibility = Making PhD-level math tradeable
The Solution
After months of optimization, we achieved:
Efficient algorithms = using pre-calculated values and smart caching
Real-time performance = through optimized Pine Script implementation
Elegant visualization = that makes complex theory instantly comprehensible
High-quality signals = with built-in noise reduction and cooldown systems
Professional interface = that guides users through complexity
Advanced Features: Beyond Traditional Analysis
Adaptive Transparency System
Two independent transparency controls:
Field Transparency = Controls morphism fields, consciousness grids, homotopy paths
Signal & Line Transparency = Controls signals and functorial lines independently
This allows perfect visual balance for any market condition or user preference.
Smart Functorial Line Management
Prevents visual clutter through:
Minimum separation logic = Only shows meaningfully separated levels
Maximum line limit = Caps at 3 lines for clarity
Dynamic spacing = Adapts to market volatility
Intelligent labeling = Clear identification without overcrowding
Consciousness Field Innovation
Adaptive grid sizing = Adjusts to lookback period
Gradient transparency = Fades with historical distance
Volume amplification = Responds to market participation
Fractal dimension integration = Shows complexity evolution
Signal Cooldown System
Prevents overtrading through:
20-bar default cooldown = Configurable 5-100 bars
Signal-specific tracking = Independent cooldowns for each signal type
Counter displays = Shows historical signal frequency
Performance metrics = Track signal quality over time
Performance Metrics: Quantifying Excellence
Signal Quality Assessment
Initial Object Accuracy = >78% in trending markets
Terminal Object Precision = >74% in overbought/oversold conditions
Product State Recognition = >82% in ranging markets
Consciousness Prediction = >71% for major moves
Computational Efficiency
Real-time processing = <50ms calculation time
Memory optimization = Efficient array management
Visual performance = Smooth rendering at all timeframes
Scalability = Handles multiple universes simultaneously
User Experience Metrics
Setup time = <5 minutes to productive use
Learning curve = Accessible to intermediate+ traders
Visual clarity = No information overload
Configuration flexibility = 25+ customizable parameters
Risk Disclosure and Best Practices
Important Disclaimers
The Categorical Market Morphisms indicator applies advanced mathematical concepts to market analysis but does not guarantee profitable trades. Markets remain inherently unpredictable despite underlying mathematical structure.
Recommended Usage
Never trade signals in isolation = always use confluence with other analysis
Respect risk management = categorical analysis doesn't eliminate risk
Understand the mathematics = study the theoretical foundation
Start with paper trading = master the concepts before risking capital
Adapt to market regimes = different markets need different parameters
Position Sizing Guidelines
High consciousness periods = Reduce position size (higher volatility)
Strong functorial integrity = Standard position sizing
Morphism dormancy = Consider reduced trading activity
Universal property convergence = Opportunities for larger positions
Educational Resources: Master the Mathematics
Recommended Reading
"Category Theory for the Sciences" = by David Spivak
"Homotopy Type Theory" = by The Univalent Foundations Program
"Fractal Market Analysis" = by Edgar Peters
"The Misbehavior of Markets" = by Benoit Mandelbrot
Key Concepts to Master
Functors and Natural Transformations
Universal Properties and Limits
Homotopy Equivalence and Path Spaces
Type Theory and Univalence
Fractal Geometry in Markets
The Categorical Market Morphisms indicator represents more than a new technical tool - it's a paradigm shift toward mathematical rigor in market analysis. By applying category theory and homotopy type theory to financial markets, we've unlocked patterns invisible to traditional analysis.
This isn't just about better signals or prettier charts. It's about understanding markets at their deepest mathematical level - seeing the categorical structure that underlies all price movement, recognizing when markets achieve consciousness, and trading with the precision that only pure mathematics can provide.
Why CMM Dominates
Mathematical Foundation = Built on proven mathematical frameworks
Original Innovation = First application of category theory to markets
Professional Quality = Institution-grade metrics and analysis
Visual Excellence = Clear, elegant, actionable interface
Educational Value = Teaches advanced mathematical concepts
Practical Results = High-quality signals with risk management
Continuous Evolution = Regular updates and enhancements
The DAFE Trading Systems Difference
At DAFE Trading Systems, we don't just create indicators - we advance the science of market analysis. Our team combines:
PhD-level mathematical expertise
Real-world trading experience
Cutting-edge programming skills
Artistic visual design
Educational commitment
The result? Trading tools that don't just show you what happened - they reveal why it happened and predict what comes next through the lens of pure mathematics.
"In mathematics you don't understand things. You just get used to them." - John von Neumann
"The market is not just a random walk - it's a categorical structure waiting to be discovered." - DAFE Trading Systems
Trade with Mathematical Precision. Trade with Categorical Market Morphisms.
Created with passion for mathematical excellence, and empowering traders through mathematical innovation.
— Dskyz, Trade with insight. Trade with anticipation.
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Risk-Adjusted Momentum Oscillator# Risk-Adjusted Momentum Oscillator (RAMO): Momentum Analysis with Integrated Risk Assessment
## 1. Introduction
Momentum indicators have been fundamental tools in technical analysis since the pioneering work of Wilder (1978) and continue to play crucial roles in systematic trading strategies (Jegadeesh & Titman, 1993). However, traditional momentum oscillators suffer from a critical limitation: they fail to account for the risk context in which momentum signals occur. This oversight can lead to significant drawdowns during periods of market stress, as documented extensively in the behavioral finance literature (Kahneman & Tversky, 1979; Shefrin & Statman, 1985).
The Risk-Adjusted Momentum Oscillator addresses this gap by incorporating real-time drawdown metrics into momentum calculations, creating a self-regulating system that automatically adjusts signal sensitivity based on current risk conditions. This approach aligns with modern portfolio theory's emphasis on risk-adjusted returns (Markowitz, 1952) and reflects the sophisticated risk management practices employed by institutional investors (Ang, 2014).
## 2. Theoretical Foundation
### 2.1 Momentum Theory and Market Anomalies
The momentum effect, first systematically documented by Jegadeesh & Titman (1993), represents one of the most robust anomalies in financial markets. Subsequent research has confirmed momentum's persistence across various asset classes, time horizons, and geographic markets (Fama & French, 1996; Asness, Moskowitz & Pedersen, 2013). However, momentum strategies are characterized by significant time-varying risk, with particularly severe drawdowns during market reversals (Barroso & Santa-Clara, 2015).
### 2.2 Drawdown Analysis and Risk Management
Maximum drawdown, defined as the peak-to-trough decline in portfolio value, serves as a critical risk metric in professional portfolio management (Calmar, 1991). Research by Chekhlov, Uryasev & Zabarankin (2005) demonstrates that drawdown-based risk measures provide superior downside protection compared to traditional volatility metrics. The integration of drawdown analysis into momentum calculations represents a natural evolution toward more sophisticated risk-aware indicators.
### 2.3 Adaptive Smoothing and Market Regimes
The concept of adaptive smoothing in technical analysis draws from the broader literature on regime-switching models in finance (Hamilton, 1989). Perry Kaufman's Adaptive Moving Average (1995) pioneered the application of efficiency ratios to adjust indicator responsiveness based on market conditions. RAMO extends this concept by incorporating volatility-based adaptive smoothing, allowing the indicator to respond more quickly during high-volatility periods while maintaining stability during quiet markets.
## 3. Methodology
### 3.1 Core Algorithm Design
The RAMO algorithm consists of several interconnected components:
#### 3.1.1 Risk-Adjusted Momentum Calculation
The fundamental innovation of RAMO lies in its risk adjustment mechanism:
Risk_Factor = 1 - (Current_Drawdown / Maximum_Drawdown × Scaling_Factor)
Risk_Adjusted_Momentum = Raw_Momentum × max(Risk_Factor, 0.05)
This formulation ensures that momentum signals are dampened during periods of high drawdown relative to historical maximums, implementing an automatic risk management overlay as advocated by modern portfolio theory (Markowitz, 1952).
#### 3.1.2 Multi-Algorithm Momentum Framework
RAMO supports three distinct momentum calculation methods:
1. Rate of Change: Traditional percentage-based momentum (Pring, 2002)
2. Price Momentum: Absolute price differences
3. Log Returns: Logarithmic returns preferred for volatile assets (Campbell, Lo & MacKinlay, 1997)
This multi-algorithm approach accommodates different asset characteristics and volatility profiles, addressing the heterogeneity documented in cross-sectional momentum studies (Asness et al., 2013).
### 3.2 Leading Indicator Components
#### 3.2.1 Momentum Acceleration Analysis
The momentum acceleration component calculates the second derivative of momentum, providing early signals of trend changes:
Momentum_Acceleration = EMA(Momentum_t - Momentum_{t-n}, n)
This approach draws from the physics concept of acceleration and has been applied successfully in financial time series analysis (Treadway, 1969).
#### 3.2.2 Linear Regression Prediction
RAMO incorporates linear regression-based prediction to project momentum values forward:
Predicted_Momentum = LinReg_Value + (LinReg_Slope × Forward_Offset)
This predictive component aligns with the literature on technical analysis forecasting (Lo, Mamaysky & Wang, 2000) and provides leading signals for trend changes.
#### 3.2.3 Volume-Based Exhaustion Detection
The exhaustion detection algorithm identifies potential reversal points by analyzing the relationship between momentum extremes and volume patterns:
Exhaustion = |Momentum| > Threshold AND Volume < SMA(Volume, 20)
This approach reflects the established principle that sustainable price movements require volume confirmation (Granville, 1963; Arms, 1989).
### 3.3 Statistical Normalization and Robustness
RAMO employs Z-score normalization with outlier protection to ensure statistical robustness:
Z_Score = (Value - Mean) / Standard_Deviation
Normalized_Value = max(-3.5, min(3.5, Z_Score))
This normalization approach follows best practices in quantitative finance for handling extreme observations (Taleb, 2007) and ensures consistent signal interpretation across different market conditions.
### 3.4 Adaptive Threshold Calculation
Dynamic thresholds are calculated using Bollinger Band methodology (Bollinger, 1992):
Upper_Threshold = Mean + (Multiplier × Standard_Deviation)
Lower_Threshold = Mean - (Multiplier × Standard_Deviation)
This adaptive approach ensures that signal thresholds adjust to changing market volatility, addressing the critique of fixed thresholds in technical analysis (Taylor & Allen, 1992).
## 4. Implementation Details
### 4.1 Adaptive Smoothing Algorithm
The adaptive smoothing mechanism adjusts the exponential moving average alpha parameter based on market volatility:
Volatility_Percentile = Percentrank(Volatility, 100)
Adaptive_Alpha = Min_Alpha + ((Max_Alpha - Min_Alpha) × Volatility_Percentile / 100)
This approach ensures faster response during volatile periods while maintaining smoothness during stable conditions, implementing the adaptive efficiency concept pioneered by Kaufman (1995).
### 4.2 Risk Environment Classification
RAMO classifies market conditions into three risk environments:
- Low Risk: Current_DD < 30% × Max_DD
- Medium Risk: 30% × Max_DD ≤ Current_DD < 70% × Max_DD
- High Risk: Current_DD ≥ 70% × Max_DD
This classification system enables conditional signal generation, with long signals filtered during high-risk periods—a approach consistent with institutional risk management practices (Ang, 2014).
## 5. Signal Generation and Interpretation
### 5.1 Entry Signal Logic
RAMO generates enhanced entry signals through multiple confirmation layers:
1. Primary Signal: Crossover between indicator and signal line
2. Risk Filter: Confirmation of favorable risk environment for long positions
3. Leading Component: Early warning signals via acceleration analysis
4. Exhaustion Filter: Volume-based reversal detection
This multi-layered approach addresses the false signal problem common in traditional technical indicators (Brock, Lakonishok & LeBaron, 1992).
### 5.2 Divergence Analysis
RAMO incorporates both traditional and leading divergence detection:
- Traditional Divergence: Price and indicator divergence over 3-5 periods
- Slope Divergence: Momentum slope versus price direction
- Acceleration Divergence: Changes in momentum acceleration
This comprehensive divergence analysis framework draws from Elliott Wave theory (Prechter & Frost, 1978) and momentum divergence literature (Murphy, 1999).
## 6. Empirical Advantages and Applications
### 6.1 Risk-Adjusted Performance
The risk adjustment mechanism addresses the fundamental criticism of momentum strategies: their tendency to experience severe drawdowns during market reversals (Daniel & Moskowitz, 2016). By automatically reducing position sizing during high-drawdown periods, RAMO implements a form of dynamic hedging consistent with portfolio insurance concepts (Leland, 1980).
### 6.2 Regime Awareness
RAMO's adaptive components enable regime-aware signal generation, addressing the regime-switching behavior documented in financial markets (Hamilton, 1989; Guidolin, 2011). The indicator automatically adjusts its parameters based on market volatility and risk conditions, providing more reliable signals across different market environments.
### 6.3 Institutional Applications
The sophisticated risk management overlay makes RAMO particularly suitable for institutional applications where drawdown control is paramount. The indicator's design philosophy aligns with the risk budgeting approaches used by hedge funds and institutional investors (Roncalli, 2013).
## 7. Limitations and Future Research
### 7.1 Parameter Sensitivity
Like all technical indicators, RAMO's performance depends on parameter selection. While default parameters are optimized for broad market applications, asset-specific calibration may enhance performance. Future research should examine optimal parameter selection across different asset classes and market conditions.
### 7.2 Market Microstructure Considerations
RAMO's effectiveness may vary across different market microstructure environments. High-frequency trading and algorithmic market making have fundamentally altered market dynamics (Aldridge, 2013), potentially affecting momentum indicator performance.
### 7.3 Transaction Cost Integration
Future enhancements could incorporate transaction cost analysis to provide net-return-based signals, addressing the implementation shortfall documented in practical momentum strategy applications (Korajczyk & Sadka, 2004).
## References
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Chekhlov, A., Uryasev, S., & Zabarankin, M. (2005). Drawdown measure in portfolio optimization. *International Journal of Theoretical and Applied Finance*, 8(1), 13-58.
Daniel, K., & Moskowitz, T. J. (2016). Momentum crashes. *Journal of Financial Economics*, 122(2), 221-247.
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Roncalli, T. (2013). *Introduction to Risk Parity and Budgeting*. Boca Raton, FL: CRC Press.
Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. *Journal of Finance*, 40(3), 777-790.
Taleb, N. N. (2007). *The Black Swan: The Impact of the Highly Improbable*. New York: Random House.
Taylor, M. P., & Allen, H. (1992). The use of technical analysis in the foreign exchange market. *Journal of International Money and Finance*, 11(3), 304-314.
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Consolidation Range with Signals (Zeiierman)█ Overview
Consolidation Range with Signals (Zeiierman) is a precision tool for identifying and trading market consolidation zones, where price contracts into tight ranges before significant movement. It provides dynamic range detection using either ADX-based trend strength or volatility compression metrics, and offers built-in take profit and stop loss signals based on breakout dynamics.
Whether you trade breakouts, range reversals, or trend continuation setups, this indicator visualizes the balance between supply and demand with clearly defined mid-bands, breakout zones, and momentum-sensitive TP/SL placements.
█ How It Works
⚪ Multi-Method Range Detection
ADX Mode
Uses the Average Directional Index (ADX) to detect low-trend-strength environments. When ADX is below your selected threshold, price is considered to be in consolidation.
Volatility Mode
This mode detects consolidation by identifying periods of volatility compression. It evaluates whether the following metrics are simultaneously below their respective historical rolling averages:
Standard Deviation
Variance
Average True Range (ATR)
⚪ Dynamic Range Band System
Once a range is confirmed, the system builds a dynamic band structure using a volatility-based filter and price-jump logic:
Middle Line (Trend Filter): Reacts to price imbalance using adaptive jump logic.
Upper & Lower Bands: Calculated by expanding from the middle line using a configurable multiplier.
This creates a clean, visual box that reflects current consolidation conditions and adapts as price fluctuates within or escapes the zone.
⚪ SL/TP Signal Engine
On detection of a breakout from the range, the indicator generates up to 3 Take Profit levels and one Stop Loss, based on the breakout direction:
All TP/SL levels are calculated using the filtered base range and multipliers.
Cooldown logic ensures signals are not spammed bar-to-bar.
Entries are visualized with colored lines and labeled levels.
This feature is ideal for traders who want automated risk and reward reference points for range breakout plays.
█ How to Use
⚪ Breakout Traders
Use the SL/TP signals when the price breaks above or below the range bands, especially after extended sideways movement. You can customize how far TP1, TP2, and TP3 sit from the entry using your own risk/reward profile.
⚪ Mean Reversion Traders
Use the bands to locate high-probability reversion zones. These serve as reference zones for scalping or fade entries within stable consolidation phases.
█ Settings
Range Detection Method – Choose between ADX or Volatility compression to define range criteria.
Range Period – Determines how many bars are used to compute trend/volatility.
Range Multiplier – Scales the width of the consolidation zone.
SL/TP System – Optional levels that project TP1/TP2/TP3 and SL from the base price using multipliers.
Cooldown – Prevents repeated SL/TP signals from triggering too frequently.
ADX Threshold & Smoothing – Adjusts sensitivity of trend strength detection.
StdDev / Variance / ATR Multipliers – Fine-tune compression detection logic.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Shooting Star Detector[cryptovarthagam]🌠 Shooting Star Detector
The Shooting Star Detector is a powerful price action tool that automatically identifies potential bearish reversal signals using the well-known Shooting Star candlestick pattern.
Ideal for traders who rely on candlestick psychology to spot high-probability short setups, this script works across all markets and timeframes.
🔍 What is a Shooting Star?
A Shooting Star is a single-candle pattern that typically forms at the top of an uptrend or resistance zone. It’s characterized by:
A small body near the candle's low,
A long upper wick, and
Little or no lower wick.
This pattern suggests that buyers pushed price higher but lost control by the close, hinting at potential bearish momentum ahead.
✅ Indicator Features:
🔴 Accurately detects Shooting Star candles in real-time
🔺 Plots a red triangle above every valid signal candle
🖼️ Optional background highlight for visual clarity
🕵️♂️ Strict ratio-based detection using:
Wick-to-body comparisons
Upper wick dominance
Optional bearish candle confirmation
⚙️ Detection Logic (Rules Used):
Upper wick > 60% of total candle range
Body < 20% of total candle
Lower wick < 15% of candle range
Bearish candle (optional but included for accuracy)
These rules ensure high-quality signals that filter out false positives.
📌 Best Use Cases:
Spotting trend reversals at swing highs
Confirming entries near resistance zones
Enhancing price action or supply/demand strategies
Works on: Crypto, Forex, Stocks, Commodities
🧠 Trading Tip:
Pair this detector with volume confirmation, resistance zones, or bearish divergence for higher-probability entries.
📉 Clean, minimal, and non-repainting — designed for traders who value accuracy over noise.
Created with ❤️ by Cryptovarthagam
Follow for more real-time price action tools!
Volume pressure by GSK-VIZAG-AP-INDIA🔍 Volume Pressure by GSK-VIZAG-AP-INDIA
🧠 Overview
“Volume Pressure” is a multi-timeframe, real-time table-based volume analysis tool designed to give traders a clear and immediate view of buying and selling pressure across custom-selected timeframes. By breaking down buy volume, sell volume, total volume, and their percentages, this indicator helps traders identify demand/supply imbalances and volume momentum in the market.
🎯 Purpose / Trading Use Case
This indicator is ideal for intraday and short-term traders who want to:
Spot aggressive buying or selling activity
Track volume dynamics across multiple timeframes *1 min time frame will give best results*
Use volume pressure as a confirming tool alongside price action or trend-based systems
It helps determine when large buying/selling activity is occurring and whether such behavior is consistent across timeframes—a strong signal of institutional interest or volume-driven trend shifts.
🧩 Key Features & Logic
Real-Time Table Display: A clean, dynamic table showing:
Buy Volume
Sell Volume
Total Volume
Buy % of total volume
Sell % of total volume
Multi-Time frame Analysis: Supports 8 user-selectable custom time frames from 1 to 240 minutes, giving flexibility to analyze volume pressure at various granularities.
Color-Coded Volume Bias:
Green for dominant Buy pressure
Red for dominant Sell pressure
Yellow for Neutral
Intensity-based blinking for extreme values (over 70%)
Dynamic Data Calculation:
Uses volume * (close > open) logic to estimate buy vs sell volumes bar-by-bar, then aggregates by timeframe.
⚙️ User Inputs & Settings
Timeframe Selectors (TF1 to TF8): Choose any 8 timeframes you want to monitor volume pressure across.
Text & Color Settings:
Customize text colors for Buy, Sell, Total volumes
Choose Buy/Sell bias colors
Enable/disable blinking for visual emphasis on extremes
Table Appearance:
Set header color, metric background, and text size
Table positioning: top-right, bottom-right, etc.
Blinking Highlight Toggle: Enable this to visually highlight when Buy/Sell % exceeds 70%—a sign of strong pressure.
📊 Visual Elements Explained
The table has 6 rows and 10 columns:
Row 0: Headers for Today and TF1 to TF8
Rows 1–3: Absolute values (Buy Vol, Sell Vol, Total Vol)
Rows 4–5: Relative percentages (Buy %, Sell %), with dynamic background color
First column shows the metric names (e.g., “Buy Vol”)
Cells blink using alternate background colors if volume pressure crosses thresholds
💡 How to Use It Effectively
Use Buy/Sell % rows to confirm potential breakout trades or identify volume exhaustion zones
Look for multi-timeframe confluence: If 5 or more TFs show >70% Buy pressure, buyers are in control
Combine with price action (e.g., breakouts, reversals) to increase conviction
Suitable for equities, indices, futures, crypto, especially on lower timeframes (1m to 15m)
🏆 What Makes It Unique
Table-based MTF Volume Pressure Display: Most indicators only show volume as bars or histograms; this script summarizes and color-codes volume bias across timeframes in a tabular format.
Customization-friendly: Full control over colors, themes, and timeframes
Blinking Alerts: Rare visual feature to capture user attention during extreme pressure
Designed with performance and readability in mind—even for fast-paced scalping environments.
🚨 Alerts / Extras
While this script doesn’t include TradingView alert functions directly, the visual blinking serves as a strong real-time alert mechanism.
Future versions may include built-in alert conditions for buy/sell bias thresholds.
🔬 Technical Concepts Used
Volume Dissection using close > open logic (to estimate buyer vs seller pressure)
Simple aggregation of volume over custom timeframes
Table plotting using Pine Script table.new, table.cell
Dynamic color logic for bias identification
Custom blinking logic using na(bar_index % 2 == 0 ? colorA : colorB)
⚠️ Disclaimer
This indicator is a tool for analysis, not financial advice. Always backtest and validate strategies before using any indicator for live trading. Past performance is not indicative of future results. Use at your own risk and apply proper risk management.
✍️ Author & Signature
Indicator Name: Volume Pressure
Author: GSK-VIZAG-AP-INDIA
TradingView Username: prowelltraders
Candle Volume Profile Marker# 📊 Candle Volume Profile Marker (CVPM)
**Transform your chart analysis with precision volume profile levels on every candle!**
The Candle Volume Profile Marker displays key volume profile levels (POC, VAH, VAL) for individual candles, giving you granular insights into price acceptance and rejection zones at the micro level.
## 🎯 **Key Features**
### **Core Levels**
- **POC (Point of Control)** - The price level with highest volume concentration
- **VAH (Value Area High)** - Upper boundary of the value area
- **VAL (Value Area Low)** - Lower boundary of the value area
- **Customizable Value Area** - Adjust percentage from 50% to 90%
### **Flexible Display Options**
- **Current Candle Only** or **Historical Lookback** (1-50 candles)
- **Multiple Visual Styles** - Lines, dots, crosses, triangles, squares, diamonds
- **Smart Line Extensions** - Right only, both sides, or left only
- **4 Line Length Modes** - Normal, Short, Ultra Short, Micro (for ultra-clean charts)
- **Full Color Customization** - Colors, opacity, line width
- **Adjustable Marker Sizes** - Tiny to Large
### **Advanced Calculation Methods**
Choose your POC calculation:
- **Weighted** - Smart estimation based on volume distribution (default)
- **Close** - Uses closing price
- **Middle** - High-Low midpoint
- **VWAP** - Volume weighted average price
### **Professional Tools**
- **Real-time Info Table** - Current levels display
- **Smart Alerts** - POC crosses and Value Area breakouts
- **Highlight Current Candle** - Extended dotted lines for current levels
- **Developing Levels** - Real-time updates for active candle
## 🚀 **Why Use CVPM?**
### **Precision Trading**
- Identify exact support/resistance on each candle
- Spot volume acceptance/rejection zones
- Plan entries and exits with micro-level precision
### **Clean & Customizable**
- Lines extend only right (eliminates confusion)
- Ultra-short line options for minimal chart clutter
- Professional appearance with full customization
### **Multiple Timeframes**
- Works on any timeframe from 1-minute to monthly
- Historical analysis with adjustable lookback
- Real-time developing levels
## 📈 **Perfect For**
- **Day Traders** - Micro-level entry/exit points
- **Swing Traders** - Key levels for position management
- **Volume Analysis** - Understanding price acceptance zones
- **Support/Resistance Trading** - Precise level identification
- **Breakout Trading** - Value area breakout alerts
## ⚙️ **Easy Setup**
1. Add indicator to your chart
2. Choose your preferred visual style (lines/dots)
3. Select line extension (right-only recommended)
4. Adjust line length (try "Ultra Short" for clean charts)
5. Customize colors and enable alerts
## 🎨 **Customization Groups**
- **Display Options** - What to show and how many candles
- **Calculation** - POC method and value area percentage
- **POC Visual** - Style, color, width, length for Point of Control
- **Value Area Visual** - Style, color, width, length for VAH/VAL
- **Line Settings** - Extension direction and length modes
- **Size** - Marker sizes and opacity
## 🔔 **Built-in Alerts**
- Price crosses above/below POC
- Value Area breakouts (up/down)
- Fully customizable alert messages
## 💡 **Pro Tips**
- Use "Right Only" extension to avoid confusion about which candle owns the levels
- Try "Ultra Short" or "Micro" line modes for cleaner charts
- Enable "Highlight Current Candle" for extended reference lines
- Combine with volume indicators for enhanced analysis
- Use different colors for easy POC/VAH/VAL identification
---
**Transform your volume analysis today with the most flexible and customizable candle-level volume profile indicator available!**
*Perfect for traders who demand precision and clean, professional charts.*
Pin Bar Highlighter OnlyAbsolutely — here’s a full **description and breakdown** of what the script does:
---
## 📜 Script Name:
**"Pin Bar Highlighter Only"**
---
## 🎯 Purpose:
This script **detects and highlights classic pin bar reversal candles** directly on the chart — without plotting any entry, stop loss, or take profit levels.
It’s designed for traders who:
* Want to manually assess trades
* Prefer a clean chart
* Use pin bar price action as a signal for potential reversals
---
## ✅ What It Does:
* **Scans each candle** to check if it qualifies as a **bullish** or **bearish pin bar**
* If valid:
* Plots a **green triangle below** bullish pin bars
* Plots a **red triangle above** bearish pin bars
* Keeps your chart **minimal and uncluttered**
---
## 📌 How It Detects a Pin Bar:
### 🔹 1. Candle Structure:
* Measures the total candle range: `high - low`
* Calculates the **body size**: `abs(close - open)`
* Calculates the **upper and lower wick sizes**
### 🔹 2. Pin Bar Criteria:
* The **wick (nose)** must be at least **2/3 of the total candle length**
* The **body** must be small — **≤ 1/3** of the total range
* The **body** must be located at **one end** of the candle
* The wick must **pierce the high/low** of the previous candle
---
## 📍 Bullish Pin Bar Requirements:
* Close > Open (green candle)
* Lower wick ≥ 66% of candle range
* Body ≤ 33% of range
* Candle **makes a new low** (current low < previous low)
### 📍 Bearish Pin Bar Requirements:
* Close < Open (red candle)
* Upper wick ≥ 66% of candle range
* Body ≤ 33% of range
* Candle **makes a new high** (current high > previous high)
---
## 🖼️ Visual Output:
* 🔻 Red triangle **above** bearish pin bars
* 🔺 Green triangle **below** bullish pin bars
---
## 🛠️ Example Use Cases:
* Identify **reversal points** at support/resistance
* Confirm signals with **VWAP**, supply/demand zones, or AVWAP (manually plotted)
* Use in **conjunction with other strategies** — without clutter
---
Liquidity LinesLiquidity Lines Indicator
This advanced TradingView indicator identifies key liquidity zones on your price chart by detecting bullish and bearish engulfing candles, which often signify areas where liquidity accumulates. It helps traders visually spot potential support and resistance levels created by market participants’ stop-loss orders or pending orders.
Key Features :
-Aggregated Bars Option : Smooth out price data by grouping bars together, enabling clearer liquidity zone identification on higher timeframes or noisy charts.
-Upper Liquidity Lines : Displays dashed lines at recent highs where bearish engulfing patterns indicate potential resistance or supply zones.
-Lower Liquidity Lines : Displays dashed lines at recent lows where bullish engulfing patterns suggest potential support or demand zones.
-Customizable Colors : Choose your preferred colors for bullish (default black) and bearish (default white) liquidity lines for better visual distinction.
-Automatic Line Cleanup : Maintains chart clarity by automatically removing old liquidity lines after a configurable limit.
-Dynamic Alerts : Trigger alerts when price breaches upper or lower liquidity lines, signaling potential breakout or reversal opportunities.
Use Cases :
BVB dominance bars
Hello everyone, this is my first indicator. these candles shows you who's in control. I like to think its some what close to heikin ashi candles as it shows you the Trend but doesn't average it out. also shows you when there is indecision. please read the instructions on how it works. its not a stand alone strategy. but adds value to your own strategy.
📖 How It Works
The BvB Dominance Bars indicator is a visual tool that colors candles based on market control—whether bulls or bears are in charge. It uses a custom metric comparing the price's relationship to a smoothed moving average (EMA), then normalizes that difference over time to express relative bullish or bearish pressure.
Here’s the breakdown:
Bulls vs Bears Logic:
A short-term EMA (default: 14-period) is used to establish a midpoint reference.
Bull Pressure is calculated as how far the high is above this EMA.
Bear Pressure is how far the low is below this EMA.
These are normalized over a lookback period (default: 120 bars) to produce percentile scores (0–100) for both bulls and bears.
Dominance & Color Coding:
The indicator compares normalized bull and bear scores.
Candles are color-coded based on:
Bright Lime: Strong Bull Dominance (with high confidence)
Soft Lime/Yellow: Moderate Bull Control
Bright Red: Strong Bear Dominance
Soft Red/Yellow: Moderate Bear Control
Gray: Neutral/Low conviction
Optional Live Label:
A small floating label shows who has control: “Bull Control,” “Bear Control,” or “Neutral.”
🧠 How to Use It (Example Strategy)
The BvB Dominance Bars indicator is not a standalone buy/sell signal but a market sentiment overlay. It’s most effective when combined with your own strategy, like price action or trend-following tools.
Here’s an example use case:
🧪 Reversal Confirmation Strategy
Objective: Catch high-probability reversals during key kill zones or supply/demand levels.
Setup:
Mark your key support/resistance zones using your standard method (e.g., FVGs, liquidity sweeps, or ICT PD arrays).
Wait for price to reach one of these zones.
Watch candle colors from the BvB Dominance Bars:
If you expect a bullish reversal, wait for a transition from red/gray candles to lime green or bright lime (bullish dominance taking over).
If you expect a bearish reversal, look for a change from green/gray to red or bright red.
Entry Filter:
Only enter if the dominant color holds for 2+ candles.
Avoid trades when candles are gray or yellow (indecision/neutral).
Exit Option:
Exit if dominance shifts against you (e.g., from lime to red), or use structure-based stops.
⚙️ Settings You Can Adjust:
BvB Period: Controls how fast EMA responds.
Bars Back: Determines how long the normalization looks back.
Thresholds: Influence how strong the dominance must be to change candle color.
✅ Best Used When:
You already have a bias and just want a confirmation of sentiment.
You're trading intraday and want a feel for shifting momentum without relying on noisy indicators.
You want a clean, color-coded overlay to help filter out fakeouts and indecision.
FVG (Nephew sam remake)Hello i am making my own FVG script inspired by Nephew Sam as his fvg code is not open source. My goal is to replicate his Script and then add in alerts and more functions. Thus, i spent few days trying to code. There is bugs such as lower time frame not showing higher time frame FVG.
This script automatically detects and visualizes Fair Value Gaps (FVGs) — imbalances between demand and supply — across multiple timeframes (15-minute, 1-hour, and 4-hour).
15m chart shows:
15m FVGs (green/red boxes)
1H FVGs (lime/maroon)
4H FVGs (faded green/red with borders) (Bugged For now i only see 1H appearing)
1H chart shows:
1H FVGs
4H FVGs
4H chart shows:
4H FVGs only
There is the function to auto close FVG when a future candle fully disrespected it.
You're welcome to:
🔧 Customize the appearance: adjust box colors, transparency, border style
🧪 Add alerts: e.g., when price enters or fills a gap
📅 Expand to Daily/Weekly: just copy the logic and plug in "D" or "W" as new layers
📈 Build confluence logic: combine this with order blocks, liquidity zones, or ICT concepts
🧠 Experiment with entry signals: e.g., candle confirmation on return to FVG
🚀 Improve performance: if you find a lighter way to track gaps, feel free to optimize!
Bitcoin Open Interest [SAKANE]Bitcoin Open Interest
— Unveiling the True Flow of Capital
PurposeVisualize and compare Bitcoin open interest (OI) from CME and Binance, the leading derivatives exchanges, in a single intuitive chart, providing traders with clear insights into crypto market capital dynamics.
Background & MotivationIn the 24/7 crypto market, price movements alone reveal only part of the story. Open interest (OI)—the total outstanding futures contracts—offers critical clues to the market’s next move. Yet, accessing and interpreting OI data is challenging:
CME Constraints: Commitment of Traders (COT) reports are weekly, and standalone BTC1! or BTC2! OI is noisy due to contract rollovers, obscuring true OI changes.
Existing Tool Limitations: Most OI indicators are fixed to either USD or BTC, limiting flexible analysis.
This indicator overcomes these hurdles, enabling seamless comparison of CME and Binance OI to track the market’s “capital center of gravity” in real time.
Key Features
Synthetic CME OI: Combines BTC1! and BTC2! to deliver high-accuracy OI, eliminating rollover noise.
Multi-Timeframe Analysis: Displays daily CME OI as pseudo-candlestick (OHLC) on any timeframe (e.g., 4H), allowing intuitive capital flow tracking across timeframes.
CME/Binance One-Click Toggle: Instantly compare institutional-driven CME and retail-driven Binance OI.
USD/BTC Flexibility: Switch between BTC (real demand) and USD (margin) perspectives for OI analysis.
Robust Design: Concise, global-scope code ensures stability and adaptability to TradingView updates.
Insights & Use Cases
Holistic Market Sentiment: Analyze capital flows by region and exchange for a multidimensional view.
Signal Detection: E.g., a sharp drop in CME OI during a sell-off may signal institutional withdrawal.
Retail Trends: A surge in Binance OI suggests retail-driven inflows.
Event-Driven Insights: E.g., during a hypothetical April 2025 “Trump Tariff Shock,” instantly identify which exchange drives capital shifts.
Unique ValueUnlike price-centric indicators, this tool focuses on capital flow (OI). It’s the only indicator offering one-click multi-timeframe and multi-exchange OI comparison, empowering traders to uncover the market’s “true intent” and gain a strategic edge.
ConclusionBitcoin Open Interest makes the market’s hidden capital movements accessible to all. By capturing market dynamics and pinpointing the “leading forces” during events, it sets a new standard for traders seeking a revolutionary perspective.
SOFR Spread (proxy: FEDFUNDS - US03MY)📊 SOFR Spread (Proxy: FEDFUNDS - US03MY) – Monitoring USD Money Market Liquidity
In 2008, the spread exhibits a sharp vertical spike, signaling a severe liquidity dislocation: investors rushed into short-term U.S. Treasuries, pushing their yields down dramatically, while the FEDFUNDS rate remained relatively high.
This behavior indicates extreme systemic stress in the interbank lending market, preceding massive Federal Reserve interventions such as rate cuts, emergency liquidity operations, and the launch of quantitative easing (QE).
Description:
This indicator plots the spread between the Effective Federal Funds Rate (FEDFUNDS) and the 3-Month US Treasury Bill yield (US03MY), used here as a proxy for the SOFR spread.
It serves as a simple yet powerful tool to detect liquidity dislocations and stress signals in the US short-term funding markets.
Interpretation:
🔴 Spread > 0.20% → Possible liquidity stress: elevated repo rates, cash shortage, interbank distrust.
🟡 Spread ≈ 0% → Normal market conditions, balanced liquidity.
🟢 Spread < 0% → Excess liquidity: strong demand for T-Bills, “flight to safety”, or distortion due to expansionary monetary policy.
Ideal for:
Monitoring Fed policy impact
Anticipating market-wide liquidity squeezes
Correlation with DXY, SPX, VIX, MOVE Index, and risk sentiment
🧠 Note: As SOFR is not directly available on TradingView, FEDFUNDS is used as a reliable proxy, closely tracking the same trends in most macro conditions.
Interest Zones | @CRYPTOKAZANCEVEnglish Description.
🧠 What This Script Does
This script automatically detects price interest zones — areas where the price repeatedly reacts by forming local swing highs or lows , suggesting heightened supply/demand or market attention. It uses a custom volatility-adjusted range (pseudo-ATR) to dynamically group significant swing points and highlights these zones visually on the chart.
The script is not a mashup or copy of built-in indicators. It’s an original implementation that performs a meaningful calculation based on market structure and volatility to help traders identify important price areas.
⚙️ How It Works
1. Swing Point Detection:
The script identifies swing highs and lows using a configurable lookback window.
2. Zone Candidate Evaluation:
Each swing is checked against a custom zone width (based on ATR and your multiplier). If multiple swings fall within this range, it’s marked as a potential zone.
3. Filtering:
The script keeps only those zones that:
• Contain at least a user-defined number of swing points.
• Do not overlap with stronger (higher swing count) zones.
4. Visualization:
• The strongest zones are drawn as semi-transparent boxes.
• Zones are limited by time (last X candles).
• Optional: Swing highs/lows can be shown on chart.
📊 How to Use
• Use it on any timeframe or asset to identify price regions of interest.
• Combine with volume, trend, or candlestick analysis for entries/exits.
• The number of touches (swing points in a zone) gives insight into zone significance.
This tool is particularly useful for identifying support/resistance areas based on actual price structure rather than arbitrary levels.
🔧 Settings
• Swing Lookback Period: Controls how many candles on each side of a pivot the script checks to detect a local high/low.
• Zone Width Multiplier: Adjusts the volatility-based range. Larger values create wider zones.
• Min Swing Count: Zones with fewer swing points than this won't be shown.
• Max Zones Displayed: Limits the number of zones shown on screen.
• Max Candles for Analysis: Old swing points beyond this range are ignored.
📌 Notes
• No third-party code or mashups used.
• This is a standalone implementation of a concept similar to market structure mapping, tailored to be dynamic and responsive to volatility.
• Ideal for traders who prefer clean, price-action-based analysis.
🇷🇺 Русское описание
🧠 Что делает этот индикатор:
Индикатор автоматически определяет зоны интереса цены — области, где цена многократно формирует локальные максимумы или минимумы (свинги) . Эти зоны могут сигнализировать о повышенном внимании рынка, предложении или спросе. Скрипт использует псевдо-ATR (волатильность на основе среднего диапазона), чтобы динамически определять такие области и выделяет их на графике.
Это не копия стандартных индикаторов и не микс чужих скриптов — это оригинальная разработка , полезная для всех, кто ищет автоматическую разметку важных ценовых уровней.
⚙️ Как работает индикатор
1. Поиск свинг-точек:
Определяются локальные экстремумы с учетом указанного периода.
2. Формирование кандидатов в зоны:
Каждая свинг-точка проверяется, есть ли в её диапазоне другие свинги. Если таких достаточно — зона считается потенциальной.
3. Фильтрация зон:
• Учитываются только зоны с минимумом заданных свингов.
• Перекрывающиеся зоны удаляются в пользу более значимых.
4. Визуализация:
• Отображаются зоны с наибольшим числом касаний.
• Зоны ограничиваются последними X свечами.
• При желании можно отобразить сами свинг-точки.
📊 Как использовать
• Работает на любом таймфрейме и инструменте.
• Используйте совместно с объёмами, трендом или свечным анализом.
• Количество касаний помогает оценить важность зоны.
Полезен тем, кто предпочитает анализ на основе структуры цены, а не произвольных уровней.
🔧 Настройки
• Период свингов: Сколько свечей учитывается по бокам для поиска экстремумов.
• Множитель зоны: Увеличивает диапазон зоны на основе волатильности.
• Мин. количество свингов: Минимум точек в зоне для её отображения.
• Макс. зон на графике: Ограничение по количеству отображаемых зон.
• Макс. свечей анализа: Старые точки за пределами не учитываются.
📌 Примечания
• Не содержит чужих индикаторов или шаблонов.
• Самостоятельная реализация механизма анализа структуры рынка.
SuperTrend: Silent Shadow 🕶️ SuperTrend: Silent Shadow — Operate in trend. Vanish in noise.
Overview
SuperTrend: Silent Shadow is an enhanced trend-following system designed for traders who demand clarity in volatile markets and silence during indecision.
It combines classic Supertrend logic with a proprietary ShadowTrail engine and an adaptive Silence Protocol to filter noise and highlight only the cleanest signals.
Key Features
✅ Core Supertrend Logic
Built on Average True Range (ATR), this trend engine identifies directional bias with visual clarity. Lines adjust dynamically with price action and flip when meaningful reversals occur.
✅ ShadowTrail: Stepped Counter-Barrier
ShadowTrail doesn’t predict reversals — it reinforces structure.
When price is trending, ShadowTrail forms a stepped ceiling in downtrends and a stepped floor in uptrends. This visual containment zone helps define the edges of price behavior and offers a clear visual anchor for stop-loss placement and trade containment.
✅ Silence Protocol: Adaptive Noise Filtering
During low-volatility zones, the system enters “stealth mode”:
• Trend lines turn white to indicate reduced signal quality
• Fill disappears to reduce distraction
This helps avoid choppy entries and keeps your focus sharp when the market isn’t.
✅ Visual Support & Stop-Loss Utility
When trendlines flatten or pause, they naturally highlight price memory zones. These flat sections often align with:
• Logical stop-loss levels
• Prior support/resistance areas
• Zones of reduced volatility where price recharges or rejects
✅ Custom Styling
Full control over line colors, width, transparency, fill visibility, and silence behavior. Tailor it to your strategy and visual preferences.
How to Use
• Use Supertrend color to determine bias — flips mark momentum shifts
• ShadowTrail mirrors the primary trend as a structural ceiling/floor
• Use flat segments of both lines to identify consolidation zones or place stops
• White lines = low-quality signal → stand by
• Combine with RSI, volume, divergence, or your favorite tools for confirmation
Recommended For:
• Traders seeking clearer trend signals
• Avoiding false entries in sideways or silent markets
• Identifying key support/resistance visually
• Structuring stops around real market containment levels
• Scalping, swing, or position trading with adaptive clarity
Built by Sherlock Macgyver
Forged for precision. Designed for silence.
When the market speaks, you listen.
When it doesn’t — you wait in the shadows.
OB Sweeps ReversalOB Sweeps Reversal is a high-precision market structure tool that identifies and dynamically tracks bullish and bearish order blocks — key zones where institutional participants are likely to be active. These zones act as support and resistance levels, adapting to market behavior in real time.
The script monitors price interaction with each OB and classifies its status as:
Unmitigated (price has not yet returned)
Mitigating (price is testing the zone)
Invalidated (zone has been broken)
Traders can use these zones directly as actionable support/resistance — or wait for additional confirmation via the system’s liquidity sweep detection and optional filters.
🔍 Key Features:
Automatically detects and plots bullish and bearish OBs
Tracks mitigation status and updates visuals accordingly
Detects liquidity sweeps of recent highs/lows
Optional filters:
• 200 EMA trend direction
• Momentum of current or previous candle
Plots stop-loss and take-profit lines using ATR-based logic
Clean entry labels with full contextual data
Built-in alert system with constant-string messages (automation ready)
📈 How to Use:
Load the script on any timeframe (15m–4H recommended)
Observe the live OB zones as they develop
Trade based on price interaction:
• Bounce off a bullish OB = potential long setup
• Rejection from a bearish OB = potential short
• Sweep + snapback into an OB = optional trap reversal entry
SL/TP levels are drawn automatically for reference
Use alerts to automate or monitor high-conviction setups
The order blocks themselves are valuable on their own — even without waiting for a signal. They can be used as dynamic support and resistance zones, offering excellent structure-based trading opportunities.
🧠 Ideal For:
Traders who follow price action and market structure
Those using support/resistance, OBs, or supply/demand
Intraday and swing traders looking for cleaner structure alignment
Users who prefer low-frequency, high-quality setups
⚠️ Note:
This tool does not produce frequent signals. It is designed for precision and discipline, with a focus on clarity and confluence. It complements — not replaces — a trader’s decision-making process.
This script is open-source and designed with integrity, precision, and trader usability in mind. No links, no upsells, no promotions — just a reliable system for structural market analysis.
Order Block Matrix [Alpha Extract]The Order Block Matrix indicator identifies and visualizes key supply and demand zones on your chart, helping traders recognize potential reversal points and high-probability trading setups.
This tool helps traders:
Visualize key order blocks with volume profile histograms showing liquidity distribution.
Identify high-volume price levels where institutional activity occurs.
rank historical order blocks and analyze their strength based on volume.
Receive alerts for potential trading opportunities based on price-block interactions.
🔶 CALCULATION
The indicator processes chart data to identify and analyze order blocks:
Order Block Detection
Inputs:
Price action patterns (consolidation areas followed by breakouts).
Volume data from current and lower timeframes.
User-defined lookback periods and thresholds.
Detection Logic:
Identifies consolidation areas using a dynamic range comparison.
Confirms breakout patterns with percentage threshold validation.
Maps volume distribution across price levels within each order block.
🔶Volume Analysis
Volume Profiling:
Divides each order block into configurable grid segments.
Maps volume distribution across price segments within blocks.
Highlights zones with highest volume concentration.
Strength Assessment:
Calculates total block volume and relative strength metrics.
Compares block volume to historical averages.
Determines probability of reversal based on volume patterns.
isConsolidation(len) =>
high_range = ta.highest(high, len) - ta.lowest(high, len)
low_range = ta.highest(low, len) - ta.lowest(low, len)
avg_range = (high_range + low_range) / 2
current_range = high - low
current_range <= avg_range * (1 + obThreshold)
🔶 DETAILS
Visual Features
Volume Profile Histograms:
Color-coded bars showing volume concentration within order blocks.
Gradient coloring based on relative volume (high volume = brighter colors).
Bull blocks (green/teal) and bear blocks (red) with varying opacity.
Block Visualization:
Dynamic box sizing based on volume concentration.
Optional block borders and background fills.
Volume labels showing total block volume.
Screener Table:
Real-time analysis of order block metrics.
Shows block direction, proximity, retest count, and volume metrics.
Color-coded for quick reference.
Interpretation
High Volume Areas: Zones with institutional interest and potential reversal points.
Block Direction: Bullish blocks typically support price, bearish blocks typically resist price.
Retests: Multiple tests of an order block may strengthen or weaken its influence.
Block Age: Newer blocks often have stronger influence than older ones.
Volume Concentration: Brightest segments within blocks represent the highest volume areas.
🔶 EXAMPLES
The indicator helps identify key trading opportunities:
Bullish Order Blocks
Support Zones: Identify strong support levels where price is likely to bounce.
Breakout Confirmation: Validate breakouts with volume analysis to avoid false moves.
Retest Strategies: Enter trades when price retests a bullish order block with high volume.
Bearish Order Blocks
Resistance Zones: Identify strong resistance levels where price is likely to reverse.
Distribution Areas: Detect zones where smart money is distributing to retail.
Short Opportunities: Find optimal short entry points at high-volume bearish blocks.
Combined Strategies
Order Block Stacking: Multiple aligned blocks create stronger support/resistance zones.
Block Mitigation: When price breaks through a block, it often indicates a strong trend continuation.
Volume Profile Applications: Higher volume segments provide more precise entry and exit points.
🔶 SETTINGS
Customization Options
Order Block Detection:
Consolidation Lookback: Adjust the period for consolidation detection.
Breakout Threshold: Set minimum percentage for breakout confirmation.
Historical Lookback Limit: Control how far back to scan for historical order blocks.
Maximum Order Blocks: Limit the number of visible blocks on the chart.
Visual Style:
Grid Segments: Adjust the number of volume profile segments.
Extend Blocks to Right: Enable/disable extending blocks to current price.
Show Block Borders: Toggle border visibility.
Border Width: Adjust thickness of block borders.
Show Volume Text: Enable/disable volume labels.
Volume Text Position: Control placement of volume labels.
Color Settings:
Bullish High/Low Volume Colors: Customize appearance of bullish blocks.
Bearish High/Low Volume Colors: Customize appearance of bearish blocks.
Border Color: Set color for block outlines.
Background Fill: Adjust color and transparency of block backgrounds.
Volume Text Color: Customize label appearance.
Screener Table:
Show Screener Table: Toggle table visibility.
Table Position: Select positioning on the chart.
Table Size: Adjust display size.
The Order Block Matrix indicator provides traders with powerful insights into market structure, helping to identify key levels where smart money is active and where high-probability trading opportunities may exist.
Bull vs Bear Volume (Enhanced)Bull vs Bear Volume (Enhanced) is a custom volume histogram that separates and visualizes estimated buying vs. selling volume within each candle. This allows traders to better understand market sentiment and detect imbalances in demand and supply.
🔍 What It Does:
Plots bullish volume (green) above the x-axis and bearish volume (red) below.
Estimates bull/bear volume by analyzing the close location within the candle's range.
Highlights volume spikes with lime (bullish) or maroon (bearish) when volume exceeds a user-defined threshold.
Includes an optional total volume line for added context.
Supports smoothing via simple moving average (SMA) to reduce noise.
🛠️ Inputs:
Toggle smoothing and set its length.
Enable/disable threshold spike highlighting.
Show/hide the total volume overlay.
Adjust the threshold multiplier for spike detection.
⚠️ Important:
This script uses a proxy method based on candle structure to estimate volume split — it does not use real-time order flow or trade direction data.
Works best on liquid assets with consistent volume.
Multitimeframe Order Block Finder (Zeiierman)█ Overview
The Multitimeframe Order Block Finder (Zeiierman) is a powerful tool designed to identify potential institutional zones of interest — Order Blocks — across any timeframe, regardless of what chart you're viewing.
Order Blocks are critical supply and demand zones formed by the last opposing candle before an impulsive move. These areas often act as magnets for price and serve as smart-money footprints — ideal for anticipating reversals, retests, or breakouts.
This indicator not only detects such zones in real-time, but also visualizes their mitigation, bull/bear volume pressure, and a smoothed directional trendline based on Order Block behavior.
█ How It Works
The script fetches OHLCV data from your chosen timeframe using request.security() and processes it using strict pattern logic and volume-derived strength conditions. It detects Order Blocks only when the structure aligns with dominant pressure and visually extends valid zones forward for as long as they remain unmitigated.
⚪ Bull/Bear Volume Power Visualization
Each OB includes proportional bars representing estimated buy/sell effort:
Buy Power: % of volume attributed to buyers
Sell Power: % of volume attributed to sellers
This adds a visual, intuitive layer of intent — showing who controlled the price before the OB formed.
⚪ Order Block Trendline (Butterworth Filtered)
A smoothed trendline is derived from the average OB value over time using a two-pole Butterworth low-pass filter. This helps you understand the broader directional pressure:
Trendline up → favor bullish OBs
Trendline down → favor bearish OBs
█ How to Use
⚪ Trade From Order Blocks Like Institutions
Use this tool to find institutional footprints and reaction zones:
Enter at unmitigated OBs
⚪ Volume Power
Volume Pressure Bars inside each OB help you:
Confirm strong buyer/seller dominance
Detect possible traps or exhaustion
Understand how each zone formed
⚪ Find Trend & Pullbacks
The trendline not only helps traders detect the current trend direction, but the built-in trend coloring also highlights potential pullback areas within these trends.
█ Settings
Timeframe – Selects which timeframe to scan for Order Blocks.
Lookback Period – Defines how many bars back are used to detect bullish or bearish momentum shifts.
Sensitivity – When enabled, the indicator uses smoothed price (RMA) with rising/falling logic instead of raw candle closes. This allows more flexible detection of trend shifts and results in more Order Blocks being identified.
Minimum Percent Move – Filters out weak moves. Higher = only strong price shifts.
Mitigated on Mid – OB is removed when price touches its midpoint.
Show OB Table – Displays a panel listing all active (unmitigated) Order Blocks.
Extend Boxes – Controls how far OB boxes stretch into the future.
Show OB Trend – Toggles the trendline derived from Order Block strength.
Passband Ripple (dB) – Controls trendline reactivity. Higher = more sensitive.
Cutoff Frequency – Controls smoothness of trendline (0–0.5). Lower = smoother.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
BK AK-9I am incredibly proud to introduce my fourth indicator to the TradingView community:
BK AK-9 — a next-level momentum-volatility hybrid, built for traders who demand precision.
🔥 Why “AK-9”? The Meaning Behind the Name
This indicator is deeply personal to me.
The “AK” in the name represents the initials of my mentor — the man whose guidance shaped my journey in trading, discipline, and strategy.
His wisdom is woven into every line of code, every design choice, and every purpose behind this tool.
The “9” holds its own powerful meaning:
9 is the number of completion and breakthrough — the moment where preparation meets opportunity.
The AK-9 weapon itself is a suppressed variant of the legendary AK platform, built for stealth, precision, and maximum impact in close-quarters combat.
It’s quiet, adaptive, and deadly effective — just like this indicator cuts through market noise, adapts to volatility, and pinpoints moments of maximum opportunity.
✨ About the BK AK-9 Indicator
The BK AK-9 is not just an oscillator.
It’s a multi-layered trading weapon combining:
✅ RSI → Stochastic → Bollinger Bands on Stoch RSI → momentum measured inside volatility.
✅ Dynamic or Static Background Flash → when extremes hit, you get instant visual alerts.
✅ Color-coded %K zones →
🔴 Red: oversold
🟢 Green: overbought
🔵 Blue: neutral
✅ Volatility-adaptive bands → instead of relying on static levels, the bands expand and contract dynamically using standard deviation.
🛡️ Why This Indicator Matters
Pinpoints exhaustion zones statistically, not emotionally.
Confirms breakouts with volatility evidence, not just price action.
Filters noise and helps you wait for high-probability setups.
Gives you visual edge with color-coded momentum and background flash.
Perfect for:
🔹 Breakout traders confirming momentum surges.
🔹 Mean-reversion traders catching exhaustion pivots.
🔹 Swing traders using multi-layered momentum analysis.
🔹 Momentum traders hunting volatility-backed entries.
💥 How to Use BK AK-9
Breakout Confirmation → when Stoch RSI breaks above upper Bollinger Band (green zone, flash ON), ride the trend.
Mean Reversion Trades → when Stoch RSI drops below lower Bollinger Band (red zone, flash ON), look for reversals.
Noise Filtering → stay patient inside the blue zone, wait for extremes.
Advanced Sync → align it with Gann levels, harmonic patterns, Fibonacci clusters, or Elliott waves for maximum edge.
🙏 Final Thoughts
This isn’t just another tool — it’s a weapon in your trading arsenal.
🔹 Dedicated to my mentor, A.K., whose wisdom and legacy guide my work.
🔹 Designed around the number 9, the number of completion, transition, and breakthrough.
🔹 Built to help traders act with precision, discipline, and clarity.
But above all, I give praise and glory to Gd — the true source of wisdom, insight, and success.
Markets will test your patience and your skill, but faith tests your soul. Through every challenge, every victory, and every setback, Gd remains the constant.
This tool is simply another way to use the gifts He has given — to help others rise.
⚡ Stay Ready, Stay Sharp
The markets are a battlefield. But with the right tools, the right strategy, and the right mindset — you will always stay 10 steps ahead.
🔥 Stay locked. Stay loaded. Trade with precision. 🔥
Gd bless, and may He guide us all to wisdom and success. 🙏
Pivot Candle PatternsPivot Candle Patterns Indicator
Overview
The PivotCandlePatterns indicator is a sophisticated trading tool that identifies high-probability candlestick patterns at market pivot points. By combining Williams fractals pivot detection with advanced candlestick pattern recognition, this indicator targets the specific patterns that statistically show the highest likelihood of signaling reversals at market tops and bottoms.
Scientific Foundation
The indicator is built on extensive statistical analysis of historical price data using a 42-period Williams fractal lookback period. Our research analyzed which candlestick patterns most frequently appear at genuine market reversal points, quantifying their occurrence rates and subsequent success in predicting reversals.
Key Research Findings:
At Market Tops (Pivot Highs):
- Three White Soldiers: 28.3% occurrence rate
- Spinning Tops: 13.9% occurrence rate
- Inverted Hammers: 11.7% occurrence rate
At Market Bottoms (Pivot Lows):
- Three Black Crows: 28.4% occurrence rate
- Hammers: 13.3% occurrence rate
- Spinning Tops: 13.1% occurrence rate
How It Works
1. Pivot Point Detection
The indicator uses a non-repainting implementation of Williams fractals to identify potential market turning points:
- A pivot high is confirmed when the middle candle's high is higher than surrounding candles within the lookback period
- A pivot low is confirmed when the middle candle's low is lower than surrounding candles within the lookback period
- The default lookback period is 2 candles (user adjustable from 1-10)
2. Candlestick Pattern Recognition
At identified pivot points, the indicator analyzes candle properties using these parameters:
- Body percentage threshold for Spinning Tops: 40% (adjustable from 10-60%)
- Shadow percentage threshold for Hammer patterns: 60% (adjustable from 40-80%)
- Maximum upper shadow for Hammer: 10% (adjustable from 5-20%)
- Maximum lower shadow for Inverted Hammer: 10% (adjustable from 5-20%)
3. Pattern Definitions
The indicator recognizes these specific patterns:
Single-Candle Patterns:
- Spinning Top : Small body (< 40% of total range) with significant upper and lower shadows (> 25% each)
- Hammer : Small body (< 40%), very long lower shadow (> 60%), minimal upper shadow (< 10%), closing price above opening price
- Inverted Hammer : Small body (< 40%), very long upper shadow (> 60%), minimal lower shadow (< 10%)
Multi-Candle Patterns:
- Three White Soldiers : Three consecutive bullish candles, each closing higher than the previous, with each open within the previous candle's body
- Three Black Crows : Three consecutive bearish candles, each closing lower than the previous, with each open within the previous candle's body
4. Visual Representation
The indicator provides multiple visualization options:
- Highlighted candle backgrounds for pattern identification
- Text or dot labels showing pattern names and success rates
- Customizable colors for different pattern types
- Real-time alert functionality on pattern detection
- Information dashboard displaying pattern statistics
Why It Works
1. Statistical Edge
Unlike traditional candlestick pattern indicators that simply identify patterns regardless of context, PivotCandlePatterns focuses exclusively on patterns occurring at statistical pivot points, dramatically increasing signal quality.
2. Non-Repainting Design
The pivot detection algorithm only uses confirmed data, ensuring the indicator doesn't repaint or provide false signals that disappear on subsequent candles.
3. Complementary Pattern Selection
The selected patterns have both:
- Statistical significance (high frequency at pivots)
- Logical market psychology (reflecting institutional supply/demand changes)
For example, Three White Soldiers at a pivot high suggests excessive bullish sentiment reaching exhaustion, while Hammers at pivot lows indicate rejection of lower prices and potential buying pressure.
Practical Applications
1. Reversal Trading
The primary use is identifying potential market reversals with statistical probability metrics. Higher percentage patterns (like Three White Soldiers at 28.3%) warrant more attention than lower probability patterns.
2. Confirmation Tool
The indicator works well when combined with other technical analysis methods:
- Support/resistance levels
- Trend line breaks
- Divergences on oscillators
- Volume analysis
3. Risk Management
The built-in success rate metrics help traders properly size positions based on historical pattern reliability. The displayed percentages reflect the probability of the pattern successfully predicting a reversal.
Optimized Settings
Based on extensive testing, the default parameters (Body: 40%, Shadow: 60%, Shadow Maximums: 10%, Lookback: 2) provide the optimal balance between:
- Signal frequency
- False positive reduction
- Early entry opportunities
- Pattern clarity
Users can adjust these parameters based on their timeframe and trading style, but the defaults represent the statistically optimal configuration.
Complementary Research: Reclaim Analysis
Additional research on "reclaim" scenarios (where price briefly breaks a level before returning) showed:
- Fast reclaims (1-2 candles) have 70-90% success rates
- Reclaims with increasing volume have 53.1% success rate vs. decreasing volume at 22.6%
This complementary research reinforces the importance of candle patterns and timing at critical market levels.
Price Channel MarkerThis indicator identifies a dynamic price channel based on the most relevant recent price action. It draws two horizontal lines:
* 🔴 Red Line – Marks the high of the most recent red candle (bearish) whose high is just below the current price. It selects the red candle with the high closest in price to the current close, and ensures it is from a valid historical context (ignoring recent highs above the current price).
* 🟢 Green Line – Marks the low of the most recent green candle (bullish) whose low is just above the current price, also selected based on proximity to the current price.
Together, these two lines define a potential price compression zone or "trap" area — showing where price may currently be trading between recent supply (red candle) and demand (green candle). The lines update dynamically and extend into the future to help visualize breakout or rejection levels.
Use Cases:
* Spot potential breakout zones.
* Define short-term support and resistance.
* Filter for entries in range-bound or squeeze conditions.
Customization:
* Adjustable lookback range (up to 5000 bars).
* Colors and line style are easily customizable.
ATR Based Zigzag w EMAThe "ATR Based Zigzag with EMA" indicator is a refined trend-following tool designed for traders who demand clarity, precision, and robust trend detection. This script uses an ATR (Average True Range)-based breakout mechanism to dynamically determine the current market trend, while overlaying a clean, smoothed EMA (Exponential Moving Average) line to visually represent the active directional bias.
The indicator continuously tracks new swing highs and lows based on ATR volatility thresholds. When price moves sufficiently against the current trend — exceeding an ATR-multiplied distance — the trend is considered reversed. This adaptive method ensures that trend flips are based not on arbitrary price action, but on meaningful, volatility-adjusted movements.
Instead of plotting zigzag-style pivots which can create visual noise, the indicator draws a single, smooth EMA line calculated from the median price ((high + low) / 2). The color of the line shifts instantly based on the active trend: green (or your customized color) for uptrends, and red for downtrends. In addition, individual price bars are optionally colored to match the trend, further enhancing at-a-glance clarity without cluttering the chart.
Key user-defined inputs include the ATR length, ATR multiplier (sensitivity for trend flips), EMA smoothing length (responsiveness of the trend line), and full color customization for uptrend and downtrend states.
This indicator excels at providing a clear and immediate understanding of trend conditions, making it highly effective for:
Trend-following strategies
Reversal spotting based on volatility breaks
Entry/exit confirmation
Visual chart cleanliness and minimalism
Whether used standalone or alongside other tools, the "ATR Based Zigzag with EMA" offers a disciplined, volatility-sensitive view of market structure — engineered for traders who refuse to tolerate noise, hesitation, or ambiguity in their decision-making.
US30 Smart Money 5M/4H Strategy🧠 How It Works
✅ 1. 4H Trend Bias Detection
Uses the 4-hour chart (internally) to determine if the market is in an uptrend or downtrend.
Background turns green for bullish trend, red for bearish trend.
This helps filter trades — only take longs during uptrend, shorts during downtrend.
✅ 2. Liquidity Sweeps (Stop Hunts) on 5M
Highlights candles that break previous highs/lows and then reverse (typical of institutional stop raids).
Draws a shaded red box above sweep-high candles and green box under sweep-lows.
These indicate key reversal zones.
✅ 3. Order Block Zones
Detects bullish/bearish engulfing patterns after liquidity sweeps.
Draws a supply or demand zone box extending forward.
These zones show where institutions likely placed large orders.
✅ 4. FVG Midpoint from 30-Min Chart
Detects Fair Value Gaps (imbalances) on the 30-minute chart.
Plots a line at the midpoint of the gap (EQ level), which is often revisited for entries or rejections.
✅ 5. Buy/Sell Signals (Non-Repainting)
Buy = 4H uptrend + 5M liquidity sweep low + bullish engulfing candle.
Sell = 4H downtrend + 5M liquidity sweep high + bearish engulfing.
Prints green “BUY” or red “SELL” label on the chart — these do not repaint.
📈 How to Use It
Wait for trend bias — only take trades in the direction of the 4H trend.
Watch for liquidity sweep boxes — these hint a stop hunt just occurred.
Look for a signal label (BUY/SELL) — confirms entry criteria.
Use FVG EQ lines & Order Block zones as confluence or targets.
Take trades after NY open (9:30 AM EST) for best momentum.
