Fractal Pullback Market StructureFractal Pullback Market Structure
Author: The_Forex_Steward
License: Mozilla Public License 2.0
The Fractal Pullback Market Structure indicator is a sophisticated price action tool designed to visualize internal structure shifts and break-of-structure (BoS) events with high accuracy. It leverages fractal pullback logic to identify market swing points and confirm whether a directional change has occurred.
This indicator detects swing highs and lows based on fractal behavior, drawing zigzag lines to connect these key pivot points. It classifies and labels each structural point as either a Higher High (HH), Higher Low (HL), Lower High (LH), or Lower Low (LL). Internal shifts are marked using triangle symbols on the chart, distinguishing bullish from bearish developments.
Break of Structure events are confirmed when price closes beyond the most recent swing high or low, and a horizontal line is drawn at the breakout level. This helps traders validate when a structural trend change is underway.
Users can configure the lookback period that defines the sensitivity of the pullback detection, as well as a timeframe multiplier to align the logic with higher timeframes such as 4H or Daily. There are visual customization settings for the zigzag lines and BoS markers, including color, width, and style (solid, dotted, or dashed).
Alerts are available for each key structural label—HH, HL, LH, LL—as well as for BoS events. These alerts are filtered through a selectable alert mode that separates signals by timeframe category: Low Timeframe (LTF), Medium Timeframe (MTF), and High Timeframe (HTF). Each mode allows the user to receive alerts only when relevant to their strategy.
This indicator excels in trend confirmation and reversal detection. Traders can use it to identify developing structure, validate internal shifts, and anticipate breakout continuation or rejection. It is particularly useful for Smart Money Concept (SMC) traders, swing traders, and those looking to refine entries and exits based on price structure rather than lagging indicators.
Visual clarity, adaptable timeframe logic, and precise structural event detection make this tool a valuable addition to any price action trader’s toolkit.
Sentiment
Economy RadarEconomy Radar — Key US Macro Indicators Visualized
A handy tool for traders and investors to monitor major US economic data in one chart.
Includes:
Inflation: CPI, PCE, yearly %, expectations
Monetary policy: Fed funds rate, M2 money supply
Labor market: Unemployment, jobless claims, consumer sentiment
Economy & markets: GDP, 10Y yield, US Dollar Index (DXY)
Options:
Toggle indicators on/off
Customizable colors
Tooltips explain each metric (in Russian & English)
Perfect for spotting economic cycles and supporting trading decisions.
Add to your chart and get a clear macro picture instantly!
Open Interest Screener
Open Interest Screener
Traders often wonder: how do you enter a trend before it takes off — not at the very peak? Most classic technical indicators lag behind price. So what could you add to your system to catch a move earlier?
🔍 Enter the Open Interest Screener!
I've personally relied on this metric for years while trading crypto. It helps detect abnormal spikes in open interest — sudden increases in the number of outstanding derivative contracts — which often signal that something big is about to happen. These moments can mark the very start of a major trend.
🧠 How to use it:
Go long if price is rising and there's a spike in open interest on the way up.
Go short if price is falling and open interest rises during the decline.
Exit positions when open interest sharply drops — this may indicate the move is losing momentum.
⚙️ Settings & Customization:
Bars to look back — defines how far back the script looks to detect % changes in open interest.
OI % Change Threshold — adjust this to control sensitivity; higher = fewer, stronger signals.
Exchange source toggles — choose between BitMEX (USD/USDT) and Kraken data feeds.
Show Spike Zones — enable or disable visual highlights for detected spikes.
📌 Tips:
Configure the indicator for your preferred cryptocurrency pair and timeframe.
Visually validate that the OI spikes look meaningful and are not cluttering the chart.
Optimal settings vary by asset — take time to test and tune them for each coin.
With this tool, you're no longer guessing where the trend might begin — you're tracking the intent of market participants as it unfolds. Use it as part of a broader system and stay ahead of the herd.
USDT + USDC Dominance USDT + USDC Dominance: This refers to the combined market capitalization of Tether (USDT) and USD Coin (USDC) as a percentage of the total cryptocurrency market capitalization. It measures the proportion of the crypto market held by these stablecoins, which are pegged to the US dollar. High dominance indicates a "risk-off" sentiment, where investors hold stablecoins for safety during market uncertainty. A drop in dominance suggests capital is flowing into riskier assets like altcoins, often signaling a bullish market or the start of an "alt season.
LEOLA LENS SignalProLeola Lens SignalPro is a closed-source, invite-only overlay that provides automated Buy/Sell labels on the chart. It is built for traders who want to visually capture high-probability turning points using adaptive market logic.
The system operates in two intelligent modes, suitable for different risk profiles and market conditions:
🔁 Two Core Modes:
Scalper Mode
Reacts to short-term price momentum shifts. Ideal for fast-paced trading in crypto, intraday stocks, or volatile sessions.
Safeguard Mode
Prioritizes confirmation. Waits for cleaner structural breaks or volume-backed exhaustion before generating signals — designed for those seeking higher signal quality and fewer false positives.
📊 How It Works (Conceptual Overview):
The script analyzes:
Live price structure
Volatility bands
Dynamic support/resistance reactions
A custom trigger engine monitors:
Breakout conditions
Liquidity imbalances
Exhaustion wicks and trap patterns
Labels are only generated after strict checks.
A yellow caution label appears when there’s a likely trend reversal, alerting traders to proceed with extra caution.
🟡 Additional Visual Layers:
🟡 Yellow Line → Marks a key psychological decision zone. Often precedes major breakouts or trend changes.
🩷 Pink Lines → Show reactive support and resistance levels derived from recent liquidity sweeps. These lines help anticipate pullbacks, reversal rejections, or false breakouts.
🧩 How to Use It:
Toggle between Scalper and Safeguard modes depending on your strategy
Works across all markets — crypto, stocks, forex, and commodities
Watch for:
Buy labels near exhaustion candles or support retests
Sell labels after extended upside moves or trap wicks
Yellow caution tag = high reversal risk zone
Pink/Yellow lines = visual context for decision-making
⚠️ Important Notes:
This script does not use common indicators like RSI, MACD, or Bollinger Bands
Not derived from public scripts — it’s built from original models combining structure and momentum imbalance
For best results, use on a clean chart with no overlapping indicators.
LEOLA LENS FOOTPRINTLeola Lens Footprint is a closed-source, invite-only overlay tool built to track and visualize historical support and resistance levels where price has previously shown clear reactions.
Unlike predictive models or indicator-based tools, Footprint focuses solely on market memory — highlighting zones where actual buying/selling interest occurred in the past and continues to influence price behavior in the present.
🔍 What It Does:
Plots validated zones based on historical reactions — not assumptions
Displays support/resistance layers that have caused rejections, consolidations, or breakouts
Works in all markets (crypto, stocks, forex, commodities) and all timeframes
Color Markers:
🟣 Purple zones → Historical price memory zones with frequent rejections
🟤 Brown zones → Most recent rejection clusters (fresh supply/demand levels)
🟡 Yellow lines → Significant levels that often act as decision points
📊 Best For:
Traders who trade reactions at proven levels, not speculative predictions
Scalpers and swing traders looking for clean retest and rejection entries
Traders who want a consistent visual of historical support/resistance behavior
⚠️ Technical Notes:
This tool uses original logic and does not rely on indicators like RSI, MACD, MA, or volume
No future projection — levels are drawn only after confirmed reactions
Built to work in both trend and range markets
LEOLA LENS PROLeola Lens Pro is a closed-source, invite-only overlay designed to give traders deeper insight into liquidity shifts, trap zones, and expansion/reversion mechanics across all markets.
Built on the foundation of Leola Lens Standard, this version introduces:
✅ More precise, price-reactive zones
✅ Adaptive expansion and reversion levels
✅ Real-time visibility into liquidity sweeps and institutional trap zones
🔍 What It Displays:
Dynamic structure zones that adapt as price evolves
Expansion lines suggesting potential breakout or exhaustion targets
Zone clusters that highlight where breakouts may trap late entries
Additional color-coded markers:
🟡 Yellow Line → Key psychological decision zone
🩷 Pink Lines → Potential support/pullback or resistance-reversal zones
📊 Best Suited For:
Traders identifying value area breaks, imbalances, or liquidity voids
Scalpers seeking early signs of trap formations
Swing traders looking to catch mean reversion setups after expansions
⚠️ Technical Notes:
Leola Lens Pro is built with original code, not based on public Pine libraries or commonly reused indicator logic
Does not include RSI, MACD, Moving Averages, or volume indicators
Best visual performance on 15-minute charts, but adaptable to any timeframe
SIG PRINT + COMBO SIG PRINT + COMBO — Multi-Timeframe Trend & EMA Crossover Tool
This script combines EMA crossover logic with DMI-based trend analysis across multiple timeframes. It helps visualize directional trends (Bullish, Bearish, or No Clear Trend) on 5-minute, 15-minute, 30-minute, and 1-hour charts, displayed in a color-coded table overlay.
Key Components:
• EMA Strategy: Uses configurable short- and long-term EMAs to define crossover-based entry conditions.
• DMI Trend Detection: Implements ADX, +DI, and -DI to assess trend direction and strength.
• Multi-Timeframe Display: Shows trend signals for 5m, 15m, 30m, 1h, and current chart timeframe.
Built for users interested in aligning strategy entries with trend context across multiple timeframes.
⸻
@zaytradellc
USDT + USDC DominanceUSDT and USDC Dominance: This refers to the combined market capitalization of Tether (USDT) and USD Coin (USDC) as a percentage of the total cryptocurrency market capitalization. It measures the proportion of the crypto market held by these stablecoins, which are pegged to the US dollar. High dominance indicates a "risk-off" sentiment, where investors hold stablecoins for safety during market uncertainty. A drop in dominance suggests capital is flowing into riskier assets like altcoins, often signaling a bullish market or the start of an "alt season."
RISK ROTATION MATRIX ║ BullVision [3.0]🔍 Overview
The Risk Rotation Matrix is a comprehensive market regime detection system that analyzes global market conditions across four critical domains: Liquidity, Macroeconomic, Crypto/Commodities, and Risk/Volatility. Through proprietary algorithms and advanced statistical analysis, it transforms 20+ diverse market metrics into a unified framework for identifying regime transitions and risk rotations.
This institutional-grade system aims to solve a fundamental challenge: how to synthesize complex, multi-domain market data into clear, actionable trading intelligence. By combining proprietary liquidity calculations with sophisticated cross-asset analysis.
The Four-Domain Architecture
1. 💧 LIQUIDITY DOMAIN
Our liquidity analysis combines standard metrics with proprietary calculations:
Proprietary Components:
Custom Global Liquidity Index (GLI): Unique formula aggregating central bank assets, credit spreads, and FX dynamics through our weighted algorithm
Federal Reserve Balance Proxy: Advanced calculation incorporating reverse repos, TGA fluctuations, and QE/QT impacts
China Liquidity Proxy: First-of-its-kind metric combining PBOC operations with FX-adjusted aggregates
Global M2 Composite: Custom multi-currency M2 aggregation with proprietary FX normalization
2. 📈 MACRO DOMAIN
Sophisticated integration of global economic indicators:
S&P 500: Momentum and trend analysis with custom z-score normalization
China Blue Chips: Asian market sentiment with correlation filtering
MBA Purchase Index: Real estate market health indicator
Emerging Markets (EEMS): Risk appetite measurement
Global ETF (URTH): Worldwide equity exposure tracking
Each metric undergoes proprietary transformation to ensure comparability and regime-specific sensitivity.
3. 🪙 CRYPTO/COMMODITIES DOMAIN
Unique cross-asset analysis combining:
Total Crypto Market Cap: Liquidity flow indicator with custom smoothing
Bitcoin SOPR: On-chain profitability analysis with adaptive periods
MVRV Z-Score: Advanced implementation with multiple MA options
BTC/Silver Ratio: Novel commodity-crypto relationship metric
Our algorithms detect when crypto markets lead or lag traditional assets, providing crucial timing signals.
4. ⚡ RISK/VOLATILITY DOMAIN
Advanced volatility regime detection through:
MOVE Index: Bond volatility with inverse correlation analysis
VVIX/VIX Ratio: Volatility-of-volatility for regime extremes
SKEW Index: Tail risk measurement with custom normalization
Credit Stress Composite: Proprietary combination of credit spreads
USDT Dominance: Crypto flight-to-safety indicator
All risk metrics are inverted and normalized to align with the unified scoring system.
🧠 Advanced Integration Methodology
Multi-Stage Processing Pipeline
Data Collection: Real-time aggregation from 20+ sources
Normalization: Custom z-score variants accounting for regime-specific volatility
Domain Scoring: Proprietary weighting within each domain
Cross-Domain Synthesis: Advanced correlation matrix between domains
Regime Detection: State-transition model identifying four market phases
Signal Generation: Composite score with adaptive smoothing
🔁 Composite Smoothing & Signal Generation
The user can apply smoothing (ALMA, EMA, etc.) to highlight trends and reduce noise. Smoothing length, type, and parameters are fully customizable for different trading styles.
🎯 Color Feedback & Market Regimes
Visual dynamics (color gradients, labels, trails, and quadrant placement) offer an at-a-glance interpretation of the market’s evolving risk environment—without forecasting or forward-looking assumptions.
🎯 The Quadrant Visualization System
Our innovative visual framework transforms complex calculations into intuitive intelligence:
Dynamic Ehlers Loop: Shows current position and momentum
Trailing History: Visual path of regime transitions
Real-Time Animation: Immediate feedback on condition changes
Multi-Layer Information: Depth through color, size, and positioning
🚀 Practical Applications
Primary Use Cases
Multi-Asset Portfolio Management: Optimize allocation across asset classes based on regime
Risk Budgeting: Adjust exposure dynamically with regime changes
Tactical Trading: Time entries/exits using regime transitions
Hedging Strategies: Implement protection before risk-off phases
Specific Trading Scenarios
Domain Divergence: When liquidity improves but risk metrics deteriorate
Early Rotation Detection: Crypto/commodity signals often lead broader markets
Volatility Regime Trades: Position for mean reversion or trend following
Cross-Asset Arbitrage: Exploit temporary dislocations between domains
⚙️ How It Works
The Composite Score Engine
The system's intelligence emerges from how it combines domains:
Each domain produces a normalized score (-2 to +2 range)
Proprietary algorithms weight domains based on market conditions
Composite score indicates overall market regime
Smoothing options (ALMA, EMA, etc.) optimize for different timeframes
Regime Classification
🟢 Risk-On (Green): Positive composite + positive momentum
🟠 Weakening (Orange): Positive composite + negative momentum
🔵 Recovery (Blue): Negative composite + positive momentum
🔴 Risk-Off (Red): Negative composite + negative momentum
Signal Interpretation Framework
The indicator provides three levels of analysis:
Composite Score: Overall market regime (-2 to +2)
Domain Scores: Identify which factors drive regime
Individual Metrics: Granular analysis of specific components
🎨 Features & Functionality
Core Components
Risk Rotation Quadrant: Primary visual interface with Ehlers loop
Data Matrix Dashboard: Real-time display of all 20+ metrics
Domain Aggregation: Separate scores for each domain
Composite Calculation: Unified score with multiple smoothing options
Customization Options
Selective Metrics: Enable/disable individual components
Period Adjustment: Optimize lookback for each metric
Smoothing Selection: 10 different MA types including ALMA
Visual Configuration: Quadrant scale, colors, trails, effects
Advanced Settings
Pre-smoothing: Reduce noise before final calculation
Adaptive Periods: Automatic adjustment during volatility
Correlation Filters: Remove redundant signals
Regime Memory: Hysteresis to prevent whipsaws
📋 Implementation Guide
Setup Process
Add to chart (optimized for daily, works on all timeframes)
Review default settings for your market focus
Adjust domain weights based on trading style
Configure visual preferences
Optimization by Trading Style
Position Trading: Longer periods (60-150), heavy smoothing
Swing Trading: Medium periods (20-60), balanced smoothing
Active Trading: Shorter periods (10-40), minimal smoothing
Best Practices
Monitor domain divergences for early signals
Use extreme readings (-1.5/+1.5) for high-conviction trades
Combine with price action for confirmation
Adjust parameters during major events (FOMC, earnings)
💎 What Makes This Unique
Beyond Traditional Indicators
Multi-Domain Integration: Only system combining liquidity, macro, crypto, and volatility
Proprietary Calculations: Custom formulas for GLI, Fed, China, and M2 proxies
Adaptive Architecture: Dynamically adjusts to market regimes
Institutional Depth: 20+ integrated metrics vs typical 3-5
Technical Innovation
Statistical Normalization: Custom z-score variants for cross-asset comparison
Correlation Management: Prevents double-counting related signals
Regime Persistence: Algorithms to identify sustainable vs temporary shifts
Visual Intelligence: Information-dense display without overwhelming
🔢 Performance Characteristics
Strengths
Early regime detection (typically 1-3 weeks ahead)
Robust across different market environments
Clear visual feedback reduces interpretation errors
Comprehensive coverage prevents blind spots
Optimal Conditions
Most effective with 100+ bars of history
Best on daily timeframe (4H minimum recommended)
Requires liquid markets for accurate signals
Performance improves with more enabled components
⚠️ Risk Considerations & Limitations
Important Disclaimers
Probabilistic system, not predictive
Requires understanding of macro relationships
Signals should complement other analysis
Past regime behavior doesn't guarantee future patterns
Known Limitations
Black swan events may cause temporary distortions
Central bank interventions can override signals
Requires active management during regime transitions
Not suitable for pure technical traders
💎 Conclusion
The Risk Rotation Matrix represents a new paradigm in market regime analysis. By combining proprietary liquidity calculations with comprehensive multi-domain monitoring, it provides institutional-grade intelligence previously available only to large funds. The system's strength lies not just in its individual components, but in how it synthesizes diverse market information into clear, actionable trading signals.
⚠️ Access & Intellectual Property Notice
This invite-only indicator contains proprietary algorithms, custom calculations, and years of quantitative research. The mathematical formulations for our liquidity proxies, cross-domain correlation matrices, and regime detection algorithms represent significant intellectual property. Access is restricted to protect these innovations and maintain their effectiveness for serious traders who understand the value of comprehensive market regime analysis.
Trend Reversal Strength Indicator 2Trend reversal strength indicator that monitors bullish or bearish sentiment for scalpers.
Momentum Commitment Delta (MCD)Momentum Commitment Delta (M C D)
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What it is
M C D fuses five micro-structure clues into one 0-to-1 score that says, “how hard are traders actually leaning on this move?”
1. Body-Delta Momentum – average net candle body direction.
2. Volume Commitment – up-volume ÷ down-volume over the same window.
3. Wick Compression – shrinking upper/lower wicks = clean conviction.
4. Candle Sequencing – rewards orderly, staircase-style body growth.
5. Pin Ratio – where the close pins inside each candle’s range.
The five factors are multiplied, then auto-normalized so extremes always land near 0 / 1 on any symbol or timeframe.
I recommend tweaking the settings to fit your edge, the pre-loaded settings may not be suitable for most traders. The MCD works on all timeframes as well :)
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How to read basic signals
• Fresh cross above 0.70 → often the birth of a real breakout.
• Cluster of > 0.70 bars → “commitment lock,” pull-backs usually shallow.
• Price makes new high while M C D doesn’t → beware...
• Cross back below 0.30 after a run → momentum is out of fuel.
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Because M C D is multiplicative, it’s hard to hit the extremes—so when the bars light lime green, the print is usually telling the truth.
I personally use the MCD to identify the peak of a high-conviction range, NOT a breakout. If a bar prints over 0.70 (green) and then a range forms off of the bar which exceeded 0.70, the breakout has a high chance to be explosive, regardless of what MCD reads at the breakout inflection point.
Play around with it, im sure there are plenty of other patterns.
Disclaimer: The Momentum Commitment Delta (MCD) indicator is provided strictly for educational and informational purposes. It does not constitute financial or investment advice, nor is it a recommendation to buy or sell any security. Trading involves substantial risk, and you should always perform your own due diligence and consult a qualified financial professional before making any trading decisions. Past performance is not indicative of future results.
Monday Swing Box# Monday Swing Box Indicator - Trading Applications
This "Monday Swing Box" indicator can be very useful in trading for several strategic reasons:
## 1. **"Monday Effect" Analysis**
* **Concept**: Mondays often have particular characteristics in the markets (opening gaps, weekend catch-up, different volumes)
* **Utility**: Allows visualization and quantification of these Monday-specific movements
* **Application**: Helps identify recurring patterns in your strategy
## 2. **Relative Volatility Measurement with ATR**
* **The ATR percentage tells you**:
* **< 50%**: Low volatility Monday (possible consolidation)
* **50-100%**: Normal volatility
* **> 100%**: Very volatile Monday (important event, potential breakout)
* **Advantage**: Contextualizes the movement relative to historical volatility
## 3. **Practical Trading Applications**
### **For Day Trading**:
* **Entry**: A Monday with >150% ATR may signal a strong movement to follow
* **Stop Loss**: Adjust stop sizes according to Monday's volatility
* **Targets**: Calibrate targets according to the movement's magnitude
### **For Swing Trading**:
* **Support/Resistance**: Monday's high/low often become key levels
* **Breakout**: Breaking above/below Monday's box may signal continuation
* **Retracement**: Return to Monday's box = support/resistance zone
### **For Risk Management**:
* **Sizing**: Adapt position sizes according to measured volatility
* **Timing**: Avoid trading abnormally volatile Mondays if you prefer stability
## 4. **Specific Possible Strategies**
### **"Monday Breakout"**:
* Wait for a break above/below Monday's box
* Enter in the direction of the breakout
* Stop at the other end of the box
### **"Monday Reversal"**:
* If Monday shows >200% ATR, look for a reversal
* The box becomes a resistance/support zone
### **"Monday Range"**:
* Trade bounces off the box limits
* Particularly effective if ATR % is normal (50-100%)
## 5. **Visualization Advantages**
* **Historical**: See past patterns across multiple Mondays
* **Comparison**: Compare current volatility to previous Mondays
* **Anticipation**: Prepare your strategy according to the type of Monday observed
## 6. **Limitations to Consider**
* Monday patterns can vary according to markets and periods
* Don't trade solely on this indicator, but use it as a complement
* Consider macroeconomic context and news
This indicator is therefore particularly useful for traders who want to exploit Monday's specificities and have an objective measure of this day's relative volatility compared to normal market conditions.
Advanced Risk Appetite Index ProThe Advanced Risk Appetite Index (RAI) represents a sophisticated institutional-grade measurement system for quantifying market risk sentiment through proprietary multi-factor fundamental analysis. This indicator synthesizes behavioral finance theory, market microstructure research, and macroeconomic indicators to provide real-time assessment of market participants' risk tolerance and investment appetite.
## Theoretical Foundation
### Academic Framework
The Risk Appetite Index is grounded in established financial theory, particularly the behavioral finance paradigm introduced by Kahneman and Tversky (1979) in their seminal work on prospect theory¹. The indicator incorporates insights from market microstructure theory (O'Hara, 1995)² and extends the risk-on/risk-off framework developed by Kumar and Lee (2006)³ through advanced statistical modeling techniques.
The theoretical foundation draws from multiple academic disciplines:
**Behavioral Finance**: The indicator recognizes that market participants exhibit systematic biases in risk perception, as documented by Shefrin and Statman (1985)⁴. These cognitive biases create measurable patterns in asset pricing and cross-asset relationships.
**Market Microstructure**: Following the work of Hasbrouck (1991)⁵, the model incorporates liquidity dynamics and market structure effects that influence risk sentiment transmission.
**Macroeconomic Theory**: The indicator integrates insights from monetary economics (Taylor, 1993)⁶ and international finance (Dornbusch, 1976)⁷ to capture policy impact on market sentiment.
### Methodological Approach
The Advanced Risk Appetite Index employs a proprietary multi-factor modeling approach that combines elements of:
1. **Advanced Factor Analysis**: Following established methodologies from Fama and French (1993)⁸, the system identifies fundamental factors that explain risk appetite variations.
2. **Regime-Adaptive Modeling**: Incorporating insights from Hamilton (1989)⁹ on regime-switching models to adapt to changing market conditions.
3. **Robust Statistical Framework**: Implementation of robust estimation methods (Huber, 1981)¹⁰ to ensure signal reliability and minimize noise impact.
## Technical Architecture
### Proprietary Multi-Factor Framework
The indicator processes information from multiple fundamental market dimensions through a sophisticated weighting and normalization system. The specific factor selection and weighting methodology represents proprietary intellectual property developed through extensive empirical research and optimization.
**Statistical Processing**: All inputs undergo robust statistical transformation using advanced normalization techniques based on Rousseeuw and Croux (1993)²⁰ to ensure consistent signal generation across different market environments.
**Dynamic Adaptation**: The system incorporates dynamic weighting adjustments based on market regime detection, drawing from the dynamic factor model literature (Stock and Watson, 2002)²¹.
**Quality Assurance**: Multi-layered quality assessment ensures signal reliability through proprietary filtering mechanisms that evaluate:
- Factor consensus requirements
- Signal persistence validation
- Data quality thresholds
- Regime-dependent adjustments
## Implementation and Usage
### Professional Visualization
The indicator provides institutional-grade visualization through:
**Multi-Theme Color Schemes**: Eight professional color themes optimized for different trading environments, following data visualization best practices (Tufte, 2001)²².
**Dynamic Background System**: Real-time visual feedback system that provides immediate market risk appetite assessment.
**Signal Quality Indicators**: Professional-grade visual representations of signal strength and reliability metrics.
### Analytics Dashboard
The comprehensive dashboard provides key institutional metrics including:
- Strategy position status and signal tracking
- Risk level assessment and market sentiment indicators
- Uncertainty measurements and volatility forecasting
- Trading signal quality and regime identification
- Performance analytics and model diagnostics
### Professional Alert System
Comprehensive alert framework covering:
- Entry and exit signal notifications
- Threshold breach warnings
- Market regime change alerts
- Signal quality degradation warnings
## Trading Applications
### Signal Generation Framework
The indicator generates professionally validated signals through proprietary algorithms:
**Long Entry Signals**: Generated when risk appetite conditions satisfy multiple proprietary criteria, indicating favorable risk asset exposure conditions.
**Position Management Signals**: Generated when risk appetite deteriorates below critical thresholds, suggesting defensive positioning requirements.
### Risk Management Integration
The indicator seamlessly integrates with institutional risk management frameworks through:
- Real-time regime identification and classification
- Advanced volatility forecasting capabilities
- Crisis detection and early warning systems
- Comprehensive uncertainty quantification
### Multi-Timeframe Applications
While optimized for daily analysis, the indicator supports various analytical timeframes for:
- Strategic asset allocation decisions
- Tactical portfolio rebalancing
- Risk management applications
## Empirical Validation
### Performance Characteristics
The indicator has undergone extensive empirical validation across multiple market environments, demonstrating:
- Consistent performance across different market regimes
- Robust signal generation during crisis periods
- Effective risk-adjusted return enhancement capabilities
### Statistical Validation
All model components and signal generation rules have been validated using:
- Comprehensive out-of-sample testing protocols
- Monte Carlo simulation analysis
- Cross-regime performance evaluation
- Statistical significance testing
## Model Specifications
### Market Applications and Target Instruments
**Primary Target Market**: The Advanced Risk Appetite Index is specifically optimized for S&P 500 Index (SPX) analysis, where it demonstrates peak performance characteristics. The model's proprietary factor weighting and signal generation algorithms have been calibrated primarily against SPX historical data, ensuring optimal sensitivity to US large-cap equity market dynamics.
**Secondary Market Applications**: While designed for SPX, the indicator demonstrates robust performance across other major equity indices, including:
- NASDAQ-100 (NDX) and related instruments
- Dow Jones Industrial Average (DJIA)
- Russell 2000 (RUT) for small-cap exposure
- International indices with sufficient liquidity and data availability
**Cross-Market Validation**: The model's fundamental approach to risk appetite measurement provides meaningful signals across different equity markets, though performance characteristics may vary based on market structure, liquidity, and regional economic factors.
### Data Requirements
The indicator requires access to institutional-grade market data across multiple asset classes and economic indicators. Specific data requirements and processing methodologies are proprietary.
### Computational Framework
The system utilizes advanced computational techniques including:
- Robust statistical estimation methods
- Dynamic factor modeling approaches
- Regime-switching algorithms
- Real-time signal processing capabilities
## Limitations and Risk Disclosure
### Model Limitations
**Data Dependency**: The indicator requires comprehensive market data and may experience performance variations during periods of limited data availability.
**Regime Sensitivity**: Performance characteristics may vary across different market regimes and structural breaks.
### Risk Warnings
**Past Performance Disclaimer**: Historical results do not guarantee future performance. All trading involves substantial risk of loss.
**Model Risk**: Quantitative models are subject to model risk and may fail to predict future market movements accurately.
**Market Risk**: The indicator does not eliminate market risk and must be used within comprehensive risk management frameworks.
## Professional Applications
### Target Users
The Advanced Risk Appetite Index is designed for:
- Institutional portfolio managers and investment professionals
- Risk management teams and quantitative analysts
- Professional traders and hedge fund managers
- Academic researchers and financial consultants
### Integration Capabilities
The indicator supports integration with:
- Portfolio optimization and management systems
- Risk management and monitoring platforms
- Automated trading and execution systems
- Research and analytics databases
## References
1. Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-291.
2. O'Hara, M. (1995). Market Microstructure Theory. Cambridge, MA: Blackwell Publishers.
3. Kumar, A., & Lee, C. M. (2006). Retail Investor Sentiment and Return Comovements. Journal of Finance, 61(5), 2451-2486.
4. 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.
5. Hasbrouck, J. (1991). Measuring the Information Content of Stock Trades. Journal of Finance, 46(1), 179-207.
6. Taylor, J. B. (1993). Discretion versus Policy Rules in Practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195-214.
7. Dornbusch, R. (1976). Expectations and Exchange Rate Dynamics. Journal of Political Economy, 84(6), 1161-1176.
8. Fama, E. F., & French, K. R. (1993). Common Risk Factors in the Returns on Stocks and Bonds. Journal of Financial Economics, 33(1), 3-56.
9. Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384.
10. Huber, P. J. (1981). Robust Statistics. New York: John Wiley & Sons.
11. Breeden, D. T. (1979). An Intertemporal Asset Pricing Model with Stochastic Consumption and Investment Opportunities. Journal of Financial Economics, 7(3), 265-296.
12. Mishkin, F. S. (1990). What Does the Term Structure Tell Us About Future Inflation? Journal of Monetary Economics, 25(1), 77-95.
13. Estrella, A., & Hardouvelis, G. A. (1991). The Term Structure as a Predictor of Real Economic Activity. Journal of Finance, 46(2), 555-576.
14. Collin-Dufresne, P., Goldstein, R. S., & Martin, J. S. (2001). The Determinants of Credit Spread Changes. Journal of Finance, 56(6), 2177-2207.
15. Carr, P., & Wu, L. (2009). Variance Risk Premiums. Review of Financial Studies, 22(3), 1311-1341.
16. Engel, C. (1996). The Forward Discount Anomaly and the Risk Premium: A Survey of Recent Evidence. Journal of Empirical Finance, 3(2), 123-192.
17. Ranaldo, A., & Söderlind, P. (2010). Safe Haven Currencies. Review of Finance, 14(3), 385-407.
18. Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
19. Pástor, L., & Stambaugh, R. F. (2003). Liquidity Risk and Expected Stock Returns. Journal of Political Economy, 111(3), 642-685.
20. Rousseeuw, P. J., & Croux, C. (1993). Alternatives to the Median Absolute Deviation. Journal of the American Statistical Association, 88(424), 1273-1283.
21. Stock, J. H., & Watson, M. W. (2002). Dynamic Factor Models. Oxford Handbook of Econometrics, 1, 35-59.
22. Tufte, E. R. (2001). The Visual Display of Quantitative Information (2nd ed.). Cheshire, CT: Graphics Press.
RSI(14) Custom by ChadRSI 14 : this indicator works in low time frame like 1h and 4h, for entry long position and short position. when the line touch 70 mean the price is overbought, when the line touch 50 it"s neutral, and when the line touch 30 mean price is oversold.
Ultimate Poker Bluff Strategy🎲 Ultimate Poker Bluff Strategy (Intraday Trading)
This strategy integrates multiple sophisticated concepts into a dynamic intraday trading system designed to identify and capitalize on short-term market inefficiencies (fake pumps and fakeouts).
The fake pump indicator can be found here:
📌 Core Concepts & Logic
This TradingView (Pine Script) strategy combines:
Poker principles:
Pot Odds: Ensures a positive risk-reward ratio (at least 2:1).
Bluff Detection: Identifies fake pumps or unnatural price movements using arbitrage detection methods relative to a benchmark (e.g., DXY).
Blackjack "Forbidden Strategy" principles:
Dynamically adjusts the position size based on the profitability of recent trades, scaling up slightly after wins and scaling down after losses.
Devil’s Game (Risk Management):
Implements strict capital protection rules by capping the maximum allowed position size, safeguarding your capital against rare and extreme market events.
⚙️ Detailed Explanation of Parameters
🎛 Strategy Inputs
Basis Risk % per Trade (baseRiskPercent): The baseline percentage of capital risked per trade (default is 1%).
TP ATR Multiplier (atrTPMultiplier = 3.0): Defines the profit target as a multiple of the ATR (Average True Range).
SL ATR Multiplier (atrSLMultiplier = 0.5): Defines the stop-loss level as a multiple of ATR. A tight SL ensures high Reward/Risk.
ATR Length (atrLength = 10): Period for ATR calculation to measure volatility.
Max Position per Trade ($) (maxAbsolutePosition): Maximum allowed position size in USD to protect from catastrophic losses (default is $100,000).
Fake Pump Scale (k) (k = 0.25): Sensitivity setting for detecting unusual price discrepancies (fake pumps).
Benchmark Asset (benchmarkTicker = "DXY"): The asset used as a reference benchmark for arbitrage detection.
📈 Indicators & Calculations
Volatility Measurement (ATR)
Uses the ATR indicator to set dynamic take-profit and stop-loss levels:
Take Profit = current price + (ATR × 3)
Stop Loss = current price − (ATR × 0.5)
Fake Pump Detection (Arbitrage Indicator)
Measures deviations from expected asset price based on a constant relation with a benchmark (e.g., DXY).
Generates EMAs (arb_ema_fast and arb_ema_slow) to detect abnormal short-term movements.
Defines upper and lower thresholds (arb_threshold) to identify potential fake pumps or unsustainable price spikes.
Gamma Stability Check
Ensures stable market conditions by confirming that the difference between fast and slow EMAs (arb_ema_fast and arb_ema_slow) remains small. Trades are entered only during stable conditions to avoid high volatility periods.
🔄 Dynamic Blackjack Position Sizing
Adjusts position sizing dynamically based on previous trade results:
Profitable last trade → Increase risk slightly (up to a cap of 3%).
Losing last trade → Reduce risk to 75% of base risk, enhancing capital protection.
🚨 Entry & Exit Logic
Long Entry Conditions:
Fast EMA crosses above Slow EMA (bullish crossover).
Market is stable (gamma_stable condition true).
Previous candle indicated a downward fake pump (isFakePumpDown ).
Short Entry Conditions:
Fast EMA crosses below Slow EMA (bearish crossover).
Market is stable (gamma_stable condition true).
Previous candle indicated an upward fake pump (isFakePumpUp ).
Risk-Reward Validation: Only enters trades when the risk-reward ratio is at least 2:1.
🛡️ Capital Protection (Devil’s Game Principle)
Ensures no single trade exceeds the absolute maximum allowable position size, providing protection against rare, catastrophic events.
🖥️ Visual Plots for Analysis
Triangles: Visual indications of detected fake pumps:
🔻 Red down arrow: Potential fake upward spike.
🔺 Green up arrow: Potential fake downward spike.
🎯 Strategy Goals & Benefits
Identifies high-probability intraday trades using a rigorous probabilistic framework inspired by professional gambling strategies.
Limits exposure effectively, scaling position size strategically to capitalize on profitable sequences and minimize the impact of losing streaks.
Ensures long-term capital growth with disciplined risk and reward management.
This is just an experiment on how to identify fake moves in the market which works especially in lower timeframe. This is not financial advice.
[Enhanced] L1 Banker Move🧠 L1 Banker Move
This is a multi-layered momentum signal tool designed to reveal institutional activity before major price moves. It combines deep liquidity detection, price pressure dynamics, and short-term investor alignment to deliver actionable signals with clarity and precision.
Key Features:
🔴 Institutional Signal
Detects potential Level 1 banker moves based on deep price compression and long-term sweep logic (Lowest Low 90 + smoothed momentum spikes).
🔵 Institutional Build Phase
Shows stealth accumulation/distribution zones using low volatility buildup and compression-based ratios over the past 30 bars.
🟢 Short-Term Investor Signal
Confirms price shifts with VWAP cross, SMA structure, and fast/slow EMA delta acceleration. Useful for timing precision entries after institutional setups.
💜 Combined Strength Histogram
A composite momentum bar that blends all three layers to visually rank the power of each setup.
🎯 Smart Highlighting & Alerts
Background turns red when an institutional signal appears without retail confirmation—flagging early entry traps or front-running zones. Includes alert conditions to notify you of optimal entry moments.
Customization:
Adjust the EMA delta sensitivity
Choose your preferred institutional timeframe (default: Daily)
[Enhanced] L1 Banker MoveThis is a multi-layered momentum signal tool designed to reveal institutional activity before major price moves. It combines deep liquidity detection, price pressure dynamics, and short-term investor alignment to deliver actionable signals with clarity and precision.
Key Features:
🔴 Institutional Signal
Detects potential Level 1 banker moves based on deep price compression and long-term sweep logic (Lowest Low 90 + smoothed momentum spikes).
🔵 Institutional Build Phase
Shows stealth accumulation/distribution zones using low volatility buildup and compression-based ratios over the past 30 bars.
🟢 Short-Term Investor Signal
Confirms price shifts with VWAP cross, SMA structure, and fast/slow EMA delta acceleration. Useful for timing precision entries after institutional setups.
💜 Combined Strength Histogram
A composite momentum bar that blends all three layers to visually rank the power of each setup.
🎯 Smart Highlighting & Alerts
Background turns red when an institutional signal appears without retail confirmation—flagging early entry traps or front-running zones. Includes alert conditions to notify you of optimal entry moments.
Customization:
Adjust the EMA delta sensitivity
Choose your preferred institutional timeframe (default: Daily)
Intradayscanner – Institutional Interest (vs. RSP)This indicator measures volatility-adjusted Relative Residual Strength (RRS) of any symbol versus RSP (the Invesco S&P 500® Equal Weight ETF) to surface potential institutional interest overlooked by cap-weighted benchmarks.
Equal-weighted benchmark: Uses RSP instead of SPY, so each S&P 500 component carries equal influence—highlighting broad institutional flows beyond the largest names.
ATR normalization: Computes a “Divergence Index” by dividing RSP’s price move by its ATR(14), then adjusts the symbol’s move by that index and rescales by its own ATR(14). This isolates true outperformance.
Residual focus: RRS represents the portion of a symbol’s move unexplained by broad-market action, making it easier to spot when institutions rotate into specific stocks.
Visualization: Plots RRS as green/red histogram bars and overlays a 14-period EMA for trend smoothing.
Inverted USDT.DSignal Logic at a Glance
Exits happen automatically if price crosses EMA200 in the opposite direction, or whenever any SAR cross occurs (strict stop on your “risky” trades).
The indicator’s core logic uses a 200-period EMA crossover on USDT.D (and optionally VIX) to define the primary trend—price crossing above the EMA closes shorts and opens longs, while crossing below does the opposite—and then layers on “risky” entries whenever the Parabolic SAR flips within that trend (SAR dot appearing below price in an uptrend for add-on longs, above price in a downtrend for add-on shorts). All positions—main and risky—are closed automatically if price crosses the EMA against your trade or any SAR cross occurs. An invert toggle flips every entry/exit rule, letting you trade the opposite signals, and identical logic runs in parallel on VIX to offer complementary or hedged signals.
Step-by-Step Usage Example
1. Set your timeframe (e.g., Daily or 4H).
2. Watch for the Main Long label (green arrow up).
3. When it appears, the strategy will close any short and open a new long.
4. Optionally, use a Sar Long label as a signal to add to your position.
5. Stay in the trade while price remains above EMA200.
6. Exit on either a Main Short or when SAR flips against you.
Tips for Real-World Trading
• Turn on alerts for each label type so you never miss a signal.
• Use the built-in Strategy Tester to optimize your SAR parameters and position sizing.
• Combine with a fixed stop-loss or take-profit discipline off-chart.
• Experiment with the Invert Signal toggle in different market regimes.
