AURA AI - Multi-Layer Signal System# AURA AI - Multi-Layer Signal System
## Originality and Value Proposition
This indicator implements a proprietary multi-layer signal filtering system designed specifically for educational trading analysis. The core value lies in three advanced algorithmic features developed to address common issues in market analysis:
1. **Adaptive Signal Spacing Algorithm**: Dynamically adjusts signal frequency based on real-time volatility calculations using custom ATR multipliers (0.7x to 1.8x)
2. **Hierarchical Signal Filtering**: Three-tier priority system with conflict prevention, cooldown periods, and cross-validation
3. **Progressive Educational Framework**: Contextual learning system with market concept explanations
## Technical Implementation
The system processes market data through multiple validation layers:
- **Primary Signals**: Multi-condition convergence requiring simultaneous confirmation from trend detection, directional strength analysis, momentum indicators, volume validation, and positioning filters
- **Trend Signals**: Direction-following analysis with moving average crossover confirmation and momentum validation
- **Reversal Signals**: Counter-trend opportunity detection with strict distance requirements and timeout filtering
## Algorithm Components and Processing
- **Adaptive Trend Detection**: Custom trailing stop methodology with configurable sensitivity parameters
- **Directional Strength Analysis**: Smoothed momentum indicators with threshold validation
- **Volume-Weighted Confirmation**: Market participation analysis using comparative volume metrics
- **Multi-Timeframe Validation**: Higher timeframe directional bias with hysteresis algorithms for stable detection
- **Custom Filtering Engine**: Proprietary noise reduction and signal prioritization algorithms
## Educational Framework Design
The indicator includes a comprehensive learning system addressing the gap between technical analysis tools and trader education:
- **Progressive Complexity**: Simplified interface for beginners transitioning to professional-grade controls
- **Contextual Explanations**: Real-time tooltips explaining market conditions and signal rationale
- **Risk Management Integration**: Built-in safeguards teaching proper trading practices
- **Signal Classification**: Clear categorization helping users understand different opportunity types
## Justification for Closed-Source Protection
This indicator warrants protection due to:
1. **Proprietary Filtering Algorithms**: Custom-developed signal prioritization and conflict resolution logic
2. **Adaptive Volatility System**: Original methodology for dynamic parameter adjustment
3. **Educational Integration**: Comprehensive learning framework with contextual market education
4. **Risk-Aware Design**: Built-in overtrading prevention and educational safeguards
The combination of these elements creates a unified analytical and educational system that goes beyond standard indicator combinations.
## Configuration and Usage
**Educational Mode**: Simplified interface focusing on high-probability setups with learning tooltips
**Professional Mode**: Full parameter control for experienced traders with advanced filtering options
Key settings include signal type selection, volatility adaptation parameters, multi-timeframe analysis, and day-of-week filtering for backtesting optimization.
## Market Application and Limitations
This system is designed for educational analysis across multiple markets and timeframes. The adaptive algorithms adjust to different volatility environments, though users should understand that no analytical tool can predict future market movements.
The indicator serves as an educational tool to help traders understand market dynamics while providing structured signal analysis. Proper risk management, position sizing, and market knowledge remain essential for successful trading.
## Important Disclosures
- This indicator provides educational analysis tools, not trading advice
- Past signal performance does not guarantee future results
- No claims are made regarding win rates or profitability
- Users must implement proper risk management practices
- Market conditions can change, affecting any analytical system's relevance
In den Scripts nach "algo" suchen
Crypto Volatility Panel ProCrypto Volatility Panel Pro
This advanced indicator creates a comprehensive volatility monitoring dashboard that displays real-time volatility metrics for up to 30 cryptocurrency pairs simultaneously. The tool combines sophisticated volatility assessment techniques with leverage-adjusted analysis and heat map visualization to provide enhanced market insights in an organized table format.
Proprietary Methodology
This indicator utilizes a proprietary dual-metric volatility assessment system developed specifically for cryptocurrency market analysis. The methodology combines advanced technical analysis components including price volatility measurements, range position analysis, and leverage scaling algorithms optimized through extensive market testing.
The unique approach enables more accurate volatility assessments across diverse cryptocurrency price ranges and market conditions compared to standard volatility indicators. Specific calculation methods and optimization parameters remain proprietary to maintain competitive advantages.
Core Functionality and Innovation
Unlike standard volatility indicators that focus on single instruments, this tool provides simultaneous multi-asset monitoring with proprietary volatility calculations specifically optimized for cryptocurrency markets. The innovation lies in combining multiple volatility assessment techniques with enhanced leverage scaling algorithms, heat map ranking system, and comprehensive multi-asset dashboard presentation.
The indicator processes data from up to 30 different cryptocurrency pairs, each with independent leverage settings ranging from 0.1x to 10,000x. Users can apply universal leverage across all pairs for consistent analysis scenarios, or customize individual leverage ratios for specific trading strategies.
Visual Organization and Heat Map System
The table displays three primary columns with an advanced heat map ranking system:
Symbol Column: Shows cryptocurrency pair names with dynamic visual indicators (🔥, ⚡, ✅, 💤) representing volatility intensity levels. Each symbol includes its current leverage setting in parentheses for reference. Invalid or unavailable symbols display error indicators (❌) with appropriate error messaging.
Change Percentage Column: Displays leverage-adjusted volatility measurements with both color-coded text and heat map background ranking. Text colors indicate volatility levels (Red for extreme, Yellow for high, Green for moderate, Gray for low), while background heat map colors rank performance relative to all monitored pairs.
Lookback Percentage Column: Shows leverage-adjusted position analysis within recent price ranges with heat map background ranking, indicating market positioning relative to recent highs and lows across all monitored instruments.
Advanced Heat Map Ranking
The proprietary heat map system ranks all enabled pairs in real-time based on their volatility metrics, providing instant visual identification of the most and least volatile instruments:
Hottest (Top 10%): Deep red background indicating highest volatility
Warm (10-20%): Orange-red background for elevated volatility
Medium (20-40%): Yellow background for moderate-high volatility
Cool (40-60%): Green background for moderate volatility
Cold (60-80%): Blue background for low volatility
Sleepy (Bottom 20%): Dark background for minimal volatility
Heat map opacity is fully customizable, and the system can be disabled for users preferring traditional static backgrounds.
Configuration Options
Expanded Pair Selection: Monitor up to 30 cryptocurrency pairs across major exchanges including Bitstamp and Binance. Default selections include established cryptocurrencies (BTC, ETH, SOL) and emerging assets (INJ, NEAR, FTM), with full customization available.
Table Positioning: Nine position options including top/middle/bottom combinations with left/center/right alignment, allowing optimal placement on any chart layout without interfering with price action or other indicators.
Visual Customization: Comprehensive control over table dimensions, frame width, font size, background colors, frame colors, header styling, text colors, and heat map color schemes to match user preferences and chart themes.
Leverage Management: Individual leverage settings for each of the 30 pairs, with optional universal leverage mode that applies consistent multipliers across all enabled pairs. Supports extreme leverage ranges up to 10,000x for advanced risk modelling.
Error Handling: Robust symbol validation with clear error indicators for invalid, unavailable, or misconfigured trading pairs, ensuring reliable operation across different market conditions.
Practical Trading Applications
Multi-Asset Volatility Screening: Identify the most and least volatile cryptocurrency markets in real-time using the heat map ranking system, enabling quick allocation of attention to instruments with the highest potential for profitable moves.
Leverage Risk Assessment: Visualize how different leverage ratios amplify volatility metrics across multiple markets simultaneously, supporting informed position sizing decisions before entering leveraged trades.
Market Timing and Rotation: Use the combination of volatility measurements and heat map rankings to identify optimal entry/exit timing across cryptocurrency markets, facilitating effective portfolio rotation strategies.
Portfolio Diversification: Compare volatility levels and rankings across 30 cryptocurrencies to construct portfolios with desired risk characteristics, balancing high-volatility growth opportunities with stable store-of-value positions.
Risk Management Dashboard: Monitor real-time volatility changes and relative rankings to adjust position sizes, implement protective measures, or reallocate capital when market conditions change significantly.
Technical Implementation
Built using Pine Script v5 with optimized security request handling to minimize performance impact while accessing 30 external data sources simultaneously. The indicator uses efficient array-based data collection, real-time ranking algorithms, and conditional table updates to maintain smooth chart operation.
The heat map system employs dynamic ranking calculations that process all enabled pairs in real-time, sorting values and applying percentile-based color mapping for instant visual feedback. Error handling includes invalid symbol detection and graceful fallback display for unavailable data feeds.
Usage Instructions
Configure Pair Selection: Enable desired cryptocurrency pairs from the 30 available options, organized across three input groups for easy navigation. Set individual leverage values or activate universal leverage mode for consistent multipliers.
Customize Heat Map: Adjust heat map colors and opacity to match your visual preferences and chart theme. The system can be disabled for users preferring static backgrounds.
Position and Style Table: Select optimal table position from nine available options and customize appearance including colors, sizing, and text elements to integrate seamlessly with your trading setup.
Interpret Rankings: Monitor both absolute values and heat map rankings to identify relative performance.
Hottest colors indicate pairs experiencing the highest volatility relative to the monitored universe.
Apply Leverage Context: Use leverage-adjusted values to understand how volatility would affect leveraged positions, remembering these are mathematical projections designed for risk assessment rather than trading signals.
Advanced Features
Dynamic Symbol Processing: The indicator automatically handles symbol validation, displaying clear error messages for invalid or unavailable trading pairs while maintaining operation for valid symbols.
Real-Time Ranking: Heat map colors update dynamically as market conditions change, providing instant visual feedback on shifting volatility patterns across the cryptocurrency universe.
Scalable Monitoring: Users can monitor anywhere from a few key pairs to the full 30-pair universe, with the ranking system automatically adjusting to the number of enabled instruments.
Cross-Exchange Support: Incorporates data from multiple cryptocurrency exchanges to provide comprehensive market coverage and reduce single-source dependency risks.
Limitations and Important Considerations
Proprietary Algorithm: The specific calculation methods are proprietary and not disclosed. Users should evaluate the indicator's output through their own analysis and testing before incorporating it into trading decisions.
Complex Volatility Model: While the proprietary methodology is sophisticated, it represents one approach to volatility assessment and may not capture all forms of market volatility such as gap movements, flash crashes, or news-driven events.
Performance Considerations: Processing data from up to 30 external securities may impact chart loading speed or cause timeouts during periods of high TradingView server load. Users experiencing performance issues should consider reducing the number of enabled pairs.
Leverage Calculations: Leverage adjustments are mathematical projections that assume linear scaling, which may not reflect actual leveraged trading mechanics including margin requirements, funding costs, liquidation risks, and exchange-specific policies.
Market Data Dependencies: Cryptocurrency prices and volatility can vary significantly between exchanges. The indicator's data sources may not represent the specific exchange or trading pair you use, and some feeds may experience gaps or delays during maintenance periods.
Ranking Relativity: Heat map rankings are relative to the enabled pair universe. Rankings will change based on which pairs are monitored and their current market conditions, making absolute interpretations less meaningful than relative comparisons.
Educational Value
This indicator helps traders develop understanding of relative volatility patterns across cryptocurrency markets and the mathematical impact of leverage on risk metrics. The heat map system provides intuitive visualization of market dynamics, helping users identify which assets are experiencing unusual activity relative to their peers.
The tool serves as an educational platform for understanding advanced volatility measurement techniques, relative ranking systems, and multi-asset risk assessment concepts that are crucial for professional cryptocurrency trading and portfolio management.
Performance and Compatibility
The indicator is optimized for cryptocurrency markets but can be adapted to other volatile asset classes by modifying the symbol inputs. Security request limits may occasionally affect data availability, particularly when multiple indicators requesting external data are used simultaneously on the same chart.
The heat map rendering system is designed for efficiency, updating color mappings only when ranking changes occur rather than on every price tick, ensuring smooth chart performance even when monitoring the full 30-pair universe.
Risk Disclaimer: This indicator is designed for educational and analytical purposes only. Volatility calculations are estimates based on historical price data and proprietary mathematical models that are not disclosed. Results do not constitute trading advice or predictions of future price movements. Users should conduct independent analysis to evaluate the indicator's effectiveness before making trading decisions.
Leveraged trading involves substantial risk of loss and may not be suitable for all investors. Always conduct thorough research and consider consulting with qualified financial professionals before making leveraged trading decisions. Cryptocurrency markets are highly volatile and can result in significant losses. Past volatility patterns do not guarantee future market behavior.
This indicator is compatible with all TradingView chart types and timeframes. It is specifically designed for cryptocurrency markets using proprietary algorithms optimized for digital asset volatility characteristics.
Hidden Markov Model [Extension] | FractalystWhat's the indicator's purpose and functionality?
The Hidden Markov Model is specifically designed to integrate with the Quantify Trading Model framework, serving as a probabilistic market regime identification system for institutional trading analysis.
Hidden Markov Models are particularly well-suited for market regime detection because they can model the unobservable (hidden) state of the market, capture probabilistic transitions between different states, and account for observable market data that each state generates.
The indicator uses Hidden Markov Model mathematics to automatically detect distinct market regimes such as low-volatility bull markets, high-volatility bear markets, or range-bound consolidation periods.
This approach provides real-time regime probabilities without requiring optimization periods that can lead to overfitting, enabling systematic trading based on genuine probabilistic market structure.
How does this extension work with the Quantify Trading Model?
The Hidden Markov Model | Fractalyst serves as a probabilistic state estimation engine for systematic market analysis.
Instead of relying on traditional technical indicators, this system automatically identifies market regimes using forward algorithm implementation with three-state probability calculation (bullish/neutral/bearish), Viterbi decoding process for determining most likely regime sequence without repainting, online parameter learning with adaptive emission probabilities based on market observations, and multi-feature analysis combining normalized returns, volatility comprehensive regime assessment.
The indicator outputs regime probabilities and confidence levels that can be used for systematic trading decisions, portfolio allocation, or risk management protocols.
Why doesn't this use optimization periods like other indicators?
The Hidden Markov Model | Fractalyst deliberately avoids optimization periods to prevent overfitting bias that destroys out-of-sample performance.
The system uses a fixed mathematical framework based on Hidden Markov Model theory rather than optimized parameters, probabilistic state estimation using forward algorithm calculations that work across all market conditions, online learning methodology with adaptive parameter updates based on real-time market observations, and regime persistence modeling using fixed transition probabilities with 70% diagonal bias for realistic regime behavior.
This approach ensures the regime detection signals remain robust across different market cycles without the performance degradation typical of over-optimized traditional indicators.
Can this extension be used independently for discretionary trading?
No, the Hidden Markov Model | Fractalyst is specifically engineered for systematic implementation within institutional trading frameworks.
The indicator is designed to provide regime filtering for systematic trading algorithms and risk management systems, enable automated backtesting through mathematical regime identification without subjective interpretation, and support institutional-level analysis when combined with systematic entry/exit models.
Using this indicator independently would miss the primary value proposition of systematic regime-based strategy optimization that institutional frameworks provide.
How do I integrate this with the Quantify Trading Model?
Integration enables institutional-grade systematic trading through advanced machine learning and statistical validation:
- Add both HMM Extension and Quantify Trading Model to your chart
- Select HMM Extension as the bias source using input.source()
- Quantify automatically uses the extension's bias signals for entry/exit analysis
- The built-in machine learning algorithms score optimal entry and exit levels based on trend intensity, and market structure patterns identified by the extension
The extension handles all bias detection complexity while Quantify focuses on optimal trade timing, position sizing, and risk management along with PineConnector automation
What markets and assets does the indicator Extension work best on?
The Hidden Markov Model | Fractalyst performs optimally on markets with sufficient price movement since the system relies on statistical analysis of returns, volatility, and momentum patterns for regime identification.
Recommended asset classes include major forex pairs (EURUSD, GBPUSD, USDJPY) with high liquidity and clear regime transitions, stock index futures (ES, NQ, YM) providing consistent regime behavior patterns, individual equities (large-cap stocks with sufficient volatility for regime detection), cryptocurrency markets (BTC, ETH with pronounced regime characteristics), and commodity futures (GC, CL showing distinct market cycles and regime transitions).
These markets provide sufficient statistical variation in returns and volatility patterns, ensuring the HMM system's mathematical framework can effectively distinguish between bullish, neutral, and bearish regime states.
Any timeframe from 15-minute to daily charts provides sufficient data points for regime calculation, with higher timeframes (4H, Daily) typically showing more stable regime identification with fewer false transitions, while lower timeframes (30m, 1H) provide more responsive regime detection but may show increased noise.
Acceptable Timeframes and Portfolio Integration:
- Any timeframe that can be evaluated within Quantify Trading Model's backtesting engine is acceptable for live trading implementation.
Legal Disclaimers and Risk Acknowledgments
Trading Risk Disclosure
The HMM Extension is provided for informational, educational, and systematic bias detection purposes only and should not be construed as financial, investment, or trading advice. The extension provides institutional analysis but does not guarantee profitable outcomes, accurate bias predictions, or positive investment returns.
Trading systems utilizing bias detection algorithms carry substantial risks including but not limited to total capital loss, incorrect bias identification, market regime changes, and adverse conditions that may invalidate analysis. The extension's performance depends on accurate data, TradingView infrastructure stability, and proper integration with Quantify Trading Model, any of which may experience data errors, technical failures, or service interruptions that could affect bias detection accuracy.
System Dependency Acknowledgment
The extension requires continuous operation of multiple interconnected systems: TradingView charts and real-time data feeds, accurate reporting from exchanges, Quantify Trading Model integration, and stable platform connectivity. Any interruption or malfunction in these systems may result in incorrect bias signals, missed transitions, or unexpected analytical behavior.
Users acknowledge that neither Fractalyst nor the creator has control over third-party data providers, exchange reporting accuracy, or TradingView platform stability, and cannot guarantee data accuracy, service availability, or analytical performance. Market microstructure changes, reporting delays, exchange outages, and technical factors may significantly affect bias detection accuracy compared to theoretical or backtested performance.
Intellectual Property Protection
The HMM Extension, including all proprietary algorithms, classification methodologies, three-state bias detection systems, and integration protocols, constitutes the exclusive intellectual property of Fractalyst. Unauthorized reproduction, reverse engineering, modification, or commercial exploitation of these proprietary technologies is strictly prohibited and may result in legal action.
Liability Limitation
By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from reliance on the extension's bias detection signals. Fractalyst shall not be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension.
Past performance of bias detection accuracy, classification effectiveness, or integration with Quantify Trading Model does not guarantee future results. Trading outcomes depend on numerous factors including market regime changes, pattern evolution, institutional behavior shifts, and proper system configuration, all of which are beyond the control of Fractalyst.
User Responsibility Statement
Users are solely responsible for understanding the risks associated with algorithmic bias detection, properly configuring system parameters, maintaining appropriate risk management protocols, and regularly monitoring extension performance. Users should thoroughly validate the extension's bias signals through comprehensive backtesting before live implementation and should never base trading decisions solely on automated bias detection.
This extension is designed to provide systematic institutional flow analysis but does not replace the need for proper market understanding, risk management discipline, and comprehensive trading methodology. Users should maintain active oversight of bias detection accuracy and be prepared to implement manual overrides when market conditions invalidate analysis assumptions.
Terms of Service Acceptance
Continued use of the HMM Extension constitutes acceptance of these terms, acknowledgment of associated risks, and agreement to respect all intellectual property protections. Users assume full responsibility for compliance with applicable laws and regulations governing automated trading system usage in their jurisdiction.
[blackcat] L1 Net Volume DifferenceOVERVIEW
The L1 Net Volume Difference indicator serves as an advanced analytical tool designed to provide traders with deep insights into market sentiment by examining the differential between buying and selling volumes over precise timeframes. By leveraging these volume dynamics, it helps identify trends and potential reversal points more accurately, thereby supporting well-informed decision-making processes. The key focus lies in dissecting intraday changes that reflect short-term market behavior, offering critical input for both swing and day traders alike. 📊
Key benefits encompass:
• Precise calculation of net volume differences grounded in real-time data.
• Interactive visualization elements enhancing interpretability effortlessly.
• Real-time generation of buy/sell signals driven by dynamic volume shifts.
TECHNICAL ANALYSIS COMPONENTS
📉 Volume Accumulation Mechanisms:
Monitors cumulative buy/sell volumes derived from comparative closing prices.
Periodically resets accumulation counters aligning with predefined intervals (e.g., 5-minute bars).
Facilitates identification of directional biases reflecting underlying market forces accurately.
🕵️♂️ Sentiment Detection Algorithms:
Employs proprietary logic distinguishing between bullish/bearish sentiments dynamically.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy.
Supports adaptive thresholds adjusting sensitivities based on changing market conditions flexibly.
🎯 Dynamic Signal Generation:
Detects transitions indicating dominance shifts between buyers/sellers promptly.
Triggers timely alerts enabling swift reactions to evolving market dynamics effectively.
Integrates conditional logic reinforcing signal validity minimizing erroneous activations.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Utilizes moving averages along with standardized deviation formulas generating precise net volume measurements.
Implements Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent alignment with established statistical principles preserving fidelity.
🖱️ User Interface Elements:
Dedicated plots displaying real-time net volume markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively.
Background shading highlighting proximity to key threshold activations enhancing visibility.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals.
Validate entry decisions considering concurrent market sentiment factors.
Assess alignment between net volume readings and broader trend directions ensuring coherence.
🚫 Exit Mechanisms:
Trigger exits upon hitting predetermined thresholds derived from historical analyses.
Monitor continuous breaches signifying potential trend reversals promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Reset Interval: Governs responsiveness versus stability balancing sensitivity/stability.
Price Source: Dictates primary data series driving volume calculations selecting relevant inputs accurately.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts.
Evaluate adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity.
Sustain balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines.
Mandatorily apply trailing stop-loss orders conforming to script outputs reinforcing discipline.
Allocate positions proportionately relative to available capital reserves managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically.
Prepare contingency plans mitigating margin call possibilities preparing proactive responses effectively.
Continuously assess automated system reliability amidst fluctuating conditions ensuring seamless functionality.
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics:
Assess win percentages consistently across diverse trading instruments gauging reliability.
Calculate average profit ratios per successful execution measuring profitability efficiency accurately.
Measure peak drawdown durations alongside associated magnitudes evaluating downside risks comprehensively.
Analyze signal generation frequencies revealing hidden patterns potentially skewing outcomes uncovering systematic biases.
📈 Historical Data Analysis Tools:
Maintain comprehensive records capturing every triggered event meticulously documenting results.
Compare realized profits/losses against backtested simulations benchmarking actual vs expected performances accurately.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily.
Document evolving performance metrics tracking progress dynamically addressing identified shortcomings proactively.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities.
Overfitted models yielding suboptimal results post-extensive tuning demanding recalibrations.
Inaccuracies stemming from incomplete/inaccurate data feeds necessitating verification procedures.
💡 Effective Resolution Pathways:
Exclude low-liquidity assets prone to erratic movements enhancing signal integrity.
Introduce buffer intervals safeguarding major news/event impacts mitigating distortions effectively.
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations reliably.
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
THANKS
Heartfelt acknowledgment extends to all developers contributing invaluable insights about volume-based trading methodologies! ✨
Forex Pips Tracker PinescriptlabsThis algorithm is exclusively designed for the Forex market 🌐 and serves as a tool to measure volatility, helping to determine on average how many pips positions move per hour. With this information, a trader can place take profit and stop loss orders with greater certainty, since they know the average pip movement range during each hour of the day.
What does it do and how does it work?
• Volatility measurement in pips 📊:
The algorithm calculates the size of the movement (or range) of each candle expressed in pips. To do this, it takes the difference between the highest and lowest price of each candle and converts it into pips.
👉
• Time zone adjustment ⏰:
It allows you to configure the time zone so that the data aligns with your desired schedule. This is especially useful for comparing movements at different times based on the trader's location.
• Analysis by time intervals 🕒:
The algorithm’s logic organizes the information for each hour of the day. It stores data for the current day, the previous day, weekly, and historically (200 candles). This allows you to see how volatility varies across different periods, providing a dynamic view of market behavior.
👉
• Directionality of movement 🔄:
In addition to averaging the pip range, the algorithm determines the predominant direction of each candle (bullish or bearish). This translates into visual indicators (like arrows) that help identify whether, on average, the movement during that hour tends to go up or down.
• Table visualization 📈:
Finally, the information is presented in an integrated table on the chart. Each row corresponds to an hour of the day and shows the average number of pips and the direction (bullish, bearish, or neutral) for each analyzed period. This table makes it easy to quickly and practically interpret the volatility data.
By combining these features, the algorithm becomes an essential tool for traders looking to better understand market dynamics and optimize their trading strategies! 💼✨
Español:
Este algoritmo está diseñado exclusivamente para el mercado Forex 🌐 y sirve como una herramienta para medir la volatilidad, ayudando a determinar en promedio cuántos pips se mueven las posiciones por hora. Con esta información, un trader puede colocar el take profit y el stop loss con mayor certeza, ya que conoce el rango promedio de movimiento en pips durante cada hora del día.
¿Qué hace y cómo funciona?
• Medición de volatilidad en pips 📊:
El algoritmo calcula el tamaño del movimiento (o rango) de cada vela expresado en pips. Para ello, toma la diferencia entre el precio máximo y el mínimo de cada vela y la convierte a pips.
👉
• Ajuste de zona horaria ⏰:
Permite configurar la zona horaria para que los datos se ajusten al horario deseado. Esto es especialmente útil para comparar movimientos durante distintas horas en función de la localización del trader.
• Análisis por intervalos de tiempo 🕒:
La lógica del algoritmo organiza la información por cada hora del día. Guarda datos para el día actual, el día anterior, a nivel semanal e histórico (200 velas). Esto permite ver cómo varía la volatilidad en diferentes periodos, proporcionando una visión dinámica del comportamiento del mercado.
👉
• Direccionalidad del movimiento 🔄:
Además de promediar el rango en pips, el algoritmo determina la dirección predominante de cada vela (alcista o bajista). Esto se traduce en indicadores visuales (como flechas) que permiten identificar si, en promedio, el movimiento en esa hora tiende a subir o bajar.
• Visualización en tabla 📈:
Finalmente, la información se presenta en una tabla integrada en el gráfico. Cada fila corresponde a una hora del día y muestra el promedio de pips y la dirección (alcista, bajista o neutral) para cada uno de los periodos analizados. Esta tabla facilita la interpretación rápida y práctica de los datos de volatilidad.
Al combinar estas funciones, el algoritmo se convierte en una herramienta esencial para traders que buscan entender mejor la dinámica del mercado y optimizar sus estrategias de trading! 💼✨
ZenAlgo - Advanced Open InterestZenAlgo - Advanced Open Interest combines open interest, price changes, and volume dynamics into a single, powerful TradingView indicator. By integrating these key market metrics and enhancing them with proprietary algorithms, it provides traders with actionable insights that streamline decision-making and enhance market analysis.
Features
Open Interest Change (%): Tracks changes in open interest, a key indicator of market participation and sentiment.
Price Change (%): Monitors price momentum, providing clarity on trend directions.
Volume Analysis: Aggregates upward and downward volume for detailed sentiment analysis.
Delta Calculation: Highlights the net difference between upward and downward volume, offering instant insights into buying or selling dominance.
Proprietary Trend Detection: Suggests "Long Enter," "Short Enter," "Long Close," or "Short Close" signals based on a synergy of open interest, price, and volume.
Market Sentiment Insights: Indicates whether new long or short positions dominate.
Customizable Display: Features themes, sizes, and positions for a tailored interface.
Added Value: Why Is This Indicator Original/Why Shall You Pay for This Indicator?
Integrated Synergy: Combining open interest, price, and volume into a single indicator reduces complexity and offers enhanced clarity. Instead of toggling between multiple charts, users receive actionable insights from a unified view.
Proprietary Rules-Based Algorithm: The algorithm synthesizes data from sub-indicators, creating trends and signals not available in free tools. For instance, the "Long Enter" or "Short Close" signals are generated by evaluating relationships between metrics, offering a predictive edge.
Enhanced Trend Confirmation: By correlating open interest changes with price movements and volume imbalances, the indicator provides a more robust confirmation of market trends compared to individual metrics.
Time-Saving and Simplicity: Freely available sub-indicators require manual setup, interpretation, and customization. ZenAlgo - Advanced Open Interest offers pre-configured analysis, reducing the learning curve and decision time.
Unique Customization: With themes, positions, and table sizes, users can adapt the interface to their preferences, enhancing usability.
How It Works
1. Open Interest and Price Change
Retrieves historical open interest and price data for the selected timeframe.
Calculates percentage changes between bars to indicate market participation (open interest) and directional momentum (price).
Combines these metrics to assess whether price movements are supported by increasing or decreasing participation.
2. Volume Aggregation
Splits the selected timeframe into smaller sub-timeframes to analyze granular volume data.
Aggregates upward (price closes above open) and downward (price closes below open) volumes, calculating their totals and percentage contributions to overall volume.
3. Delta Calculation
Computes Delta as the difference between upward and downward volume.
Highlights buyer or seller dominance using color-coded visuals for quick interpretation.
4. Trend Analysis
Uses a proprietary algorithm to classify market states:
"Long Enter": Rising price, increasing open interest, and dominant upward volume.
"Short Enter": Falling price, increasing open interest, and dominant downward volume.
Neutral States: Generated when no strong alignment is found among metrics.
5. Market Sentiment
Correlates open interest and price to indicate if new long or short positions dominate.
Outputs simplified insights like "More longs opened" or "Shorts closing."
6. Customizable Table
Displays real-time updates with user-controlled themes, sizes, and positions for a tailored experience.
Usage Examples
Detecting Bullish Trends: Identify "Long Enter" signals when open interest and price rise, supported by strong upward volume.
Spotting Bearish Reversals: Use "Short Enter" signals when price declines, open interest rises, and downward volume dominates.
Analyzing Volume Shifts: Leverage Delta to uncover significant shifts in buying or selling pressure.
Validating Trends: Use the combination of open interest and volume trends to confirm price movements.
Exiting Profitable Trades: Look for "Long Close" or "Short Close" signals to time exits during profit-taking phases.
Avoiding Choppy Markets: Use "Neutral" signals to stay out of indecisive markets and avoid unnecessary risks.
Identifying Sentiment Swings: Follow "Positions" insights to detect a transition in market dominance from longs to shorts or vice versa.
High-Volume Trend Confirmation: Confirm strong trends during high trading volumes.
Short-Term Scalping: Use sub-timeframes to spot rapid entry and exit points.
Event-Based Trading: Correlate indicator signals with major market events for timely trades.
Settings
ZenAlgo Theme: Toggle a branded theme for better visual integration.
Table Size: Adjust display size (Tiny, Small, Normal, Large) based on preference.
Table Position: Choose between four positions (e.g., Bottom Right, Top Left).
Table Mode: Switch between Dark and Light themes for optimal readability.
Important Notes
This indicator is a technical analysis tool and does not guarantee trading success. Use it with other indicators and fundamental analysis for a comprehensive strategy.
Always validate signals in conjunction with other market factors to ensure informed trading decisions.
Scenarios of Potential Underperformance:
Low-Volume Markets: Signals may lack reliability due to insufficient data granularity.
Extreme Volatility: Rapid price movements can distort short-term insights.
Exchange Variations: Data discrepancies between exchanges may affect calculations.
Choppy Markets: During indecisive phases, the indicator may generate more neutral signals.
Dual Zigzag [Trendoscope®]🎲 Dual Zigzag indicator is built on recursive zigzag algorithm. It is very similar to other zigzag indicators published by us and other authors. However, the key point here is, the indicator draws zigzag on both price and any other plot based indicator on separate layouts.
Before we get into the indicator, here are some brief descriptions of the underlying concepts and key terminologies
🎯 Zigzag
Zigzag indicator breaks down price or any input series into a series of Pivot Highs and Pivot Lows alternating between each other. Zigzags though shows pivot high and lows, should not be used for buying at low and selling at high. The main application of zigzag indicator is for the visualisation of market structure and this can be used as basic building block for any pattern recognition algorithms.
🎯 Recursive Zigzag Algorithm
Recursive zigzag algorithm builds zigzag on multiple levels and each level of zigzag is based on the previous level pivots. The level zero zigzag is built on price. However, for level 1, instead of price level 0 zigzag pivots are used. Similarly for level 2, level 1 zigzag pivots are used as base.
🎲 Components Dual Zigzag Indicator
Here are the components of Dual zigzag indicator
Built in Oscillator - Indicator has built in oscillator options for plotting RSI (Relative Strength Index), MFI (Money Flow Index), cci (Commodity Channel Index) , CMO (Chande Momentum Oscillator), COG (Center of Gravity), and ROC (Rate of Change). Apart from the given built in oscillators, users can also use a custom external output as base. The oscillators are not printed on the price pane. But, printed on a separate indicator overlay.
Zigzag On Oscillator - Recursive zigzag is calculated and printed on the oscillator series. Each pivot high and pivot low also prints a label having the retracement ratios, and price levels at those points. Zigzag on the oscillator is also printed on the indicator overlay pane.
Zigzag on Price - Recursive zigzag calculated based on price and printed on the price pane. This is made possible by using force_overlay option present in the drawing objects. At each zigzag pivot levels, the label having price retracement ratios, and oscillator values are printed.
It is called dual zigzag because, the indicator calculates the zigzag on both price and oscillator series of values and prints them separately on different panes on the chart.
🎲 Indicator Settings
Settings include
Theme display settings to get the right colour combination to match the background.
Zigzag settings to be used for zigzag calculation and display
Oscillator settings to chose the oscillator to be used as base for 2nd zigzag
🎲 Applications
Useful in spotting divergences with both indicator and price having their own zigzag to highlight pivots
Spotting patterns in indicators/oscillators and correlate them with the patterns on price
🎲 Using External Input
If users want to use an external indicator such as OBV instead of the built in oscillators, then can do so by using the custom option.
Here is how this can be done.
Step1. Add both Dual Zigzag and the intended indicator (in this case OBV) on the chart. Notice that both OBV and Dual zigzag appear on different panes.
Step2. Edit the indicator settings of Dual zigzag and set custom indicator by selecting "custom" as oscillator name and then by setting the custom external indicator name and input.
Step 3. You would notice that the zigzag in Dual Zigzag indictor pane is already showing the zigzag pivots based on the OBV indicator and the price pivots display obv values at the pivot points. We can leave this as is.
Step 4. As an additional step, you can also merge the OBV pane and the Dual zigzag indicator pane into one by going into OBV settings and moving the indicator to above pane. Merge the scales so that there is no two scales on the same pane and the entire scale appear on the right.
At the end, you should see two panes - one with price and other with OBV and both having their zigzag plotted.
TradingIQ - Reversal IQIntroducing "Reversal IQ" by TradingIQ
Reversal IQ is an exclusive trading algorithm developed by TradingIQ, designed to trade trend reversals in the market. By integrating artificial intelligence and IQ Technology, Reversal IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Reversal IQ
Reversal IQ integrates IQ Technology (AI) with the timeless concept of reversal trading. Markets follow trends that inevitably reverse at some point. Rather than relying on rigid settings or manual judgment to capture these reversals, Reversal IQ dynamically designs, creates, and executes reversal-based trading strategies.
Reversal IQ is designed to work straight out of the box. In fact, its simplicity requires just one user setting, making it incredibly straightforward to manage.
AI Aggressiveness is the only setting that controls how Reversal IQ works.
Traders don’t have to spend hours adjusting settings and trying to find what works best - Reversal IQ handles this on its own.
Key Features of Reversal IQ
Self-Learning Reversal Detection
Employs AI and IQ Technology to identify trend reversals in real-time.
AI-Generated Trading Signals
Provides reversal trading signals derived from self-learning algorithms.
Comprehensive Trading System
Offers clear entry and exit labels.
AI-Determined Profit Target and Stop Loss
Position exit levels are clearly defined and calculated by the AI once the trade is entered.
Performance Tracking
Records and presents trading performance data, easily accessible for user analysis.
Configurable AI Aggressiveness
Allows users to adjust the AI's aggressiveness to match their trading style and risk tolerance.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
IQ Channel
The IQ Channel represents what Reversal IQ considers a tradable long opportunity or a tradable short opportunity. The channel is dynamic and adjusts from chart to chart.
IQMA – Proprietary Moving Average
Introduces the IQ Moving Average (IQMA), designed to classify overarching market trends.
IQCandles – Trend Classification Tool
Complements IQMA with candlestick colors designed for trend identification and analysis.
How It Works
Reversal IQ operates on a straightforward heuristic: go long during an extended downside move and go short during an extended upside move.
What defines an "extended move" is determined by IQ Technology, TradingIQ's exclusive AI algorithm. For Reversal IQ, the algorithm assesses the extent to which historical high and low prices are breached. By learning from these price level violations, Reversal IQ adapts to trade future, similar violations in a recurring manner. It calculates a price area, distant from the current price, where a reversal is anticipated.
In simple terms, price peaks (tops) and troughs (bottoms) are stored for Reversal IQ to learn from. The degree to which these levels are violated by subsequent price movements is also recorded. Reversal IQ continuously evaluates this stored data, adapting to market volatility and raw price fluctuations to better capture price reversals.
What classifies as a price top or price bottom?
For Reversal IQ, price tops are considered the highest price attained before a significant downside reversal. Price bottoms are considered the lowest price attained before a significant upside reversal. The highest price achieved is continuously calculated before a significant counter trend price move renders the high price as a swing high. The lowest price achieved is continuously calculated before a significant counter trend price move renders the low price as a swing low.
The image above illustrates the IQ channel and explains the corresponding prices and levels
The blue lower line represents the Long Reversal Level, with the price highlighted in blue showing the Long Reversal Price.
The red upper line represents the Short Reversal Level, with the price highlighted in red showing the Short Reversal Price.
Limit orders are placed at both of these levels. As soon as either level is touched, a trade is immediately executed.
The image above shows a long position being entered after the Long Reversal Level was reached. The profit target and stop loss are calculated by Reversal IQ
The blue line indicates where the profit target is placed (acting as a limit order).
The red line shows where the stop loss is placed (acting as a stop loss order).
Green arrows indicate that the strategy entered a long position at the highlighted price level.
You can also hover over the trade labels to get more information about the trade—such as the entry price, profit target, and stop loss.
The image above demonstrates the profit target being hit for the trade. All profitable trades are marked by a blue arrow and blue line. Hover over the blue arrow to obtain more details about the trade exit.
The image above depicts a short position being entered after the Short Reversal Level was touched. The profit target and stop loss are calculated by the AI
The blue line indicates where the profit target is placed (acting as a limit order).
The red line shows where the stop loss is placed (acting as a stop loss order).
The image above shows the profit target being hit for the short trade. Profitable trades are indicated by a blue arrow and blue line. Hover over the blue arrow to access more information about the trade exit.
Long Entry: Green Arrow
Short Entry: Red Arrow
Profitable Trades: Blue Arrow
Losing Trades: Red Arrow
IQMA
The IQMA implements a dynamic moving average that adapts to market conditions by adjusting its smoothing factor based on its own slope. This makes it more responsive in volatile conditions (steeper slopes) and smoother in less volatile conditions.
The IQMA is not used by Reversal IQ as a trade condition; however, the IQMA can be used by traders to characterize the overarching trend and elect to trade only long positions during bullish conditions and only short positions during bearish conditions.
The IQMA is an adaptive smoothing function that applies a combination of multiple moving averages to reduce lag and noise in the data. The adaptiveness is achieved by dynamically adjusting the Volatility Factor (VF) based on the slope (derivative) of the price trend, making it more responsive to strong trends and smoother in consolidating markets.
This process effectively makes the moving average a self-adjusting filter, the IQMA attempts to track both trending and ranging market conditions by dynamically changing its sensitivity in response to price movements.
When IQMA is blue, an overarching uptrend is in place. When IQMA is red, an overarching downtrend is in place.
IQ Candles
IQ Candles are price candles color-coordinated with IQMA. IQ Candles help visualize the overarching trend and are not used by Reversal IQ to determine trade entries and trade exits.
AI Aggressiveness
Reversal IQ has only one setting that controls its functionality.
AI Aggressiveness controls the aggressiveness of the AI. This setting has three options: Sniper, Aggressive, and Very Aggressive.
Sniper Mode
In Sniper Mode, Reversal IQ will prioritize trading large deviations from established reversal levels and extracting the largest countertrend move possible from them.
Aggressive Mode
In Aggressive Mode, Reversal IQ still prioritizes quality but allows for strong, quantity-based signals. More trades will be executed in this mode with tighter stops and profit targets. Aggressive mode forces Reversal IQ to learn from narrower raw-dollar violations of historical levels.
Very Aggressive Mode
In Very Aggressive Mode, Reversal IQ still prioritizes the strongest quantity-based signals. Stop and target distances aren't inherently affected, but entries will be aggressive while prioritizing performance. Very Aggressive mode forces Reversal IQ to learn from narrower raw-dollar violations of historical levels and also forces it to embrace volatility more aggressively.
AI Direction
The AI Direction setting controls the trade direction Reversal IQ is allowed to take.
“Both” allows for both long and short trades.
“Long” allows for only long trades.
“Short” allows for only short trades.
Verifying Reversal IQ’s Effectiveness
Reversal IQ automatically tracks its performance and displays the profit factor for the long strategy and the short strategy it uses. This information can be found in a table located in the top-right corner of your chart.
The image above shows the long strategy profit factor and the short strategy profit factor for Reversal IQ.
A profit factor greater than 1 indicates a strategy profitably traded historical price data.
A profit factor less than 1 indicates a strategy unprofitably traded historical price data.
A profit factor equal to 1 indicates a strategy did not lose or gain money when trading historical price data.
Using Reversal IQ
While Reversal IQ is a full-fledged trading system with entries and exits, it was designed for the manual trader to take its trading signals and analysis indications to greater heights - offering numerous applications beyond its built-in trading system.
The hallmark feature of Reversal IQ is its sniper-like reversal signals. While exits are dynamically calculated as well, Reversal IQ simply has a knack for "sniping" price reversals.
When performing live analysis, you can use the IQ Channel to evaluate price reversal areas, whether price has extended too far in one direction, and whether price is likely to reverse soon.
Of course, in times of exuberance or panic, price may push through the reversal levels. While infrequent, it can happen to any indicator.
The deeper price moves into the bullish reversal area (blue) the better chance that price has extended too far and will reverse to the upside soon. The deeper price moves into the bearish reversal area (red) the better chance that price has extended too far and will reverse to the downside soon.
Of course, you can set alerts for all Reversal IQ entry and exit signals, effectively following along its systematic conquest of price movement.
TradingIQ - Impulse IQIntroducing "Impulse IQ" by TradingIQ
Impulse IQ is an exclusive trading algorithm developed by TradingIQ, designed to trade breakouts and established trends. By integrating artificial intelligence and IQ Technology, Impulse IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Impulse IQ
Impulse IQ combines IQ Technology (AI) with the classic principles of trend and breakout trading. Recognizing that markets inherently follow trends that need to persist for significant price movements to unfold, Impulse IQ eliminates the need for rigid settings or manual intervention.
Instead, it dynamically develops, adapts, and executes trend-based trading strategies, enabling a more responsive approach to capturing meaningful market opportunities.
Impulse IQ is designed to work straight out of the box. In fact, its simplicity requires just one user setting, making it incredibly straightforward to manage.
Strategy type is the only setting that controls Impulse IQ’s functionality.
Traders don’t have to spend hours adjusting settings and trying to find what works best - Impulse IQ handles this on its own.
Key Features of Impulse IQ
Self-Learning Breakout Detection
Employs IQ Technology to identify breakouts.
AI-Generated Trading Signals
Provides breakout trading signals derived from self-learning algorithms.
Comprehensive Trading System
Offers clear entry and exit labels.
AI-Determined Trailing Profit Target and Stop Loss
Position exit levels are clearly defined and calculated by the AI once the trade is entered.
Performance Tracking
Records and presents trading performance data, easily accessible for user analysis.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
IQ Meter
The IQ Meter details where price is trading relative to a higher timeframe trend and lower timeframe trend. Fibonacci levels are interlaced along the meter, offering unique insights on trend retracement opportunities.
Self Learning, Multi Timeframe IQ Zig Zags
The Zig Zag IQ is a self-learning, multi-timeframe indicator that adapts to market volatility, providing a clearer representation of market movements than traditional zig zag indicators.
Dual Strategy Execution
Impulse IQ integrates two distinct strategy types: Breakout and Cheap (details explained later).
How It Works
Before diving deeper into Impulse IQ, it's essential to understand the core terminology:
Zig Zag IQ : A self-learning trend and breakout identification mechanism that serves as the foundation for Impulse IQ. Although it belongs to the “Zig Zag” class of technical indicators, it's powered by IQ Technology.
Impulse IQ : A self-learning trading strategy that executes trades based on Zig Zag IQ. Zig Zag IQ identifies market trends, while Impulse IQ adapts, learns, and executes trades based on these trend characterizations.
Impulse IQ operates on a simple heuristic: go long during upside volatility and go short during downside volatility, essentially capturing price breakouts.
The definition of a “price breakout” is determined by IQ Technology, TradingIQ's exclusive AI algorithm. In Impulse IQ, the algorithm utilizes two IQ Zig Zags (self-learning, multi-timeframe zig zags) to analyze and learn from market trends.
It identifies breakout opportunities by recognizing violations of established price levels marked by the IQ Zig Zags. Impulse IQ then adapts and evolves to trade similar future violations in a recurring and dynamic manner.
Put simply, IQ Zig Zags continuously learn from both historical and real-time price updates to adjust themselves for an "optimal fit" to price data. The aim is to adapt so that the marked price tops and bottoms, when violated, reveal potential breakout opportunities.
The strategy layer of IQ Zig Zags, known as Impulse IQ, incorporates an additional level of self-learning with IQ Technology. It learns from breakout signals generated by the IQ Zig Zags, enabling it to dynamically identify and signal tradable breakouts. Moreover, Impulse IQ learns from historical price data to manage trade exits.
All positions start with an initial fixed stop loss and a trailing stop target. Once the trailing stop target is reached, the fixed stop loss converts into a trailing stop, allowing Impulse IQ to remain in the breakout/trend until the trailing stop is triggered.
What Classifies as a Breakout, Price Top, and Price Bottom?
For Impulse IQ:
Price tops are considered the highest price achieved before a price bottom forms.
Price bottoms are the lowest price reached before a price top forms.
For price tops, the highest price continues to be calculated until a significant downside price move occurs. Similarly, for price bottoms, the lowest price is calculated until a significant upside price move happens.
What distinguishes Zig Zag IQ from other zig zag indicators is its unique mechanism for determining a "significant counter-trend price move." Zig Zag IQ evaluates multiple fits to identify what best suits the current market conditions. Consequently, a "significant counter-trend price move" in one market might differ in magnitude from what’s considered "significant" in another, allowing it to adapt to varying market dynamics.
For example, a 1% price move in the opposite direction might be substantial in one market but not in another, and Zig Zag IQ figures this out internally.
The image above illustrates the IQ Zig Zags in action. The solid Zig Zag IQ lines represent the most recent price move being calculated, while the dotted, shaded lines display historical price moves previously analyzed by IQ Zig Zag.
Notice how the green zig zag aligns with a larger trend, while the purple zig zag follows a smaller trend. This mechanism is crucial for generating breakout signals in Impulse IQ: for a position to be entered, the breakout of the smaller trend must occur in the same direction as the larger trend.
The image above depicts the IQ Meters—an exclusive TradingIQ tool designed to help traders evaluate trend strength and retracement opportunities.
When the lower timeframe Zig Zag IQ and the higher timeframe Zig Zag IQ are out of sync (i.e., one is uptrending while the other is downtrending, with no active positions), the meters display a neutral color, as shown in the image.
The key to using these meters is to identify trend unison and pinpoint key trend retracement entry opportunities. Fibonacci retracement levels for the current trend are interlaced along each meter, and the current price is converted to a retracement ratio of the trend.
These meters can mathematically determine where price stands relative to the larger and smaller trends, aiding in identifying entry opportunities.
The top of each meter indicates the highest price achieved during the current price move.
The bottom of each meter indicates the lowest price achieved during the current price move.
When both the larger and smaller trends are in sync and uptrending, or when a long position is active, the IQ meters turn green, indicating uptrend strength.
When both trends are in sync and downtrending, or when a short position is active, the IQ meters turn red, indicating downtrend strength.
The image above shows the Point of Change for both the larger and smaller Zig Zag IQ trends. A distinctive feature of Zig Zag IQ is its ability to calculate these turning points in advance—unlike most traditional zig zag indicators that lack predetermined turning points and often lag behind price movements. In contrast, Zig Zag IQ offers a minimal-lag trend detection capability, providing a more responsive representation of market trends.
Simply put, once the market Zig Zag anchors are touched, the corresponding Zig Zag IQ will change direction.
Trade Signals
Impulse IQ can trade in one of two ways: Entering breakouts as soon as they happen (Breakout Strategy Type) or entering the pullback of a price breakout (Cheap Strategy Type).
Generally, the Breakout Strategy type will take a greater number of trades and enter a breakout quicker. The Cheap Strategy type will usually take less trades, but potentially enter at a better time/price point, prior to the next leg up of a break up, or the next leg down of a break down.
Entry signals are given when price breaks out to the upside or downside for the "Breakout" strategy type, or for the "Cheap" strategy type, when price retraces to the level it broke out from!
Breakout Strategy Example
The image above demonstrates a long position entered and exited using the Breakout strategy. The price breakout level is marked by the dotted, horizontal green line, representing a previously established price high identified by IQ Zig Zag. Once the price breaks and closes above this level, a long position is initiated.
After entering a long position, Impulse IQ immediately displays the initial fixed stop price. As the price moves favorably for the long position, the trailing stop conversion level is reached, and the indicator switches to a trailing stop, as shown in the image. Impulse IQ continues to "ride the trend" for as long as it persists, exiting only when the trailing stop is triggered.
Cheap Strategy Example
The image above shows a short entry executed using the Cheap strategy. The aim of the Cheap strategy is to enter on a pullback before the breakout occurs. While this results in fewer trades if price doesn’t pull back before the breakout, it typically allows for a better entry time and price point when a pullback does happen.
The image above illustrates the remainder of the trade until the trailing stop was hit.
Green Arrow = Long Entry
Red Arrow = Short Entry
Blue Arrow = Trade Exit
Impulse IQ calculates the initial stop price and trailing stop distance before any entry signals are triggered. This means users don’t need to constantly tweak these settings to improve performance—Impulse IQ handles this process internally.
Verifying Impulse IQ’s Effectiveness
Impulse IQ automatically tracks its performance and displays the profit factor for both its long and short strategies, visible in a table located in the top-right corner of your chart.
The image above shows the profit factor for both the long and short strategies used by Impulse IQ.
A profit factor greater than 1 indicates that the strategy was profitable when trading historical price data.
A profit factor less than 1 indicates that the strategy was unprofitable when trading historical price data.
A profit factor equal to 1 indicates that the strategy neither gained nor lost money on historical price data.
Using Impulse IQ
While Impulse IQ functions as a comprehensive trading system with its own entry and exit signals, it was designed for the manual trader to take its trading signals and analysis indications to greater heights - offering numerous applications beyond its built-in trading system.
The standout feature of Impulse IQ is its ability to characterize and capitalize on trends. Keeping a close eye on “Breakout” labels and making use of the IQ meter is the best way to use Impulse IQ.
The IQ Meters can be used to:
Find entry points during trend retracements
Assess trend alignment across higher and lower timeframes
Evaluate overall trend strength, indicating where the price lies on both IQ Meters.
Additionally, "Break Up" and "Break Down" labels can be identified for anticipating breakouts. Impulse IQ self-learns to capture breakouts optimally, making these labels dynamic signals for predicting a breakout.
The Zig Zag IQ indicators are instrumental in characterizing the market's current state. As a self-learning tool, Zig Zag IQ constantly adapts to improve the representation of current price action. The price tops and bottoms identified by Zig Zag IQ can be treated as support/resistance and breakout levels.
Of course, you can set alerts for all Impulse IQ entry and exit signals, effectively following along its systematic conquest of price movement.
TradingIQ - Nova IQIntroducing "Nova IQ" by TradingIQ
Nova IQ is an exclusive Trading IQ algorithm designed for extended price move scalping. It spots overextended micro price moves and bets against them. In this way, Nova IQ functions similarly to a reversion strategy.
Nova IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Nova IQ
Nova IQ integrates AI with the concept of central-value reversion scalping. On lower timeframes, prices may overextend for small periods of time - which Nova IQ looks to bet against. In this sense, Nova IQ scalps against small, extended price moves on lower timeframes.
Nova IQ is designed to work straight out of the box. In fact, its simplicity requires just one user setting, making it incredibly straightforward to manage.
Use HTF (used to apply a higher timeframe trade filter) is the only setting that controls how Nova IQ works.
Traders don’t have to spend hours adjusting settings and trying to find what works best - Nova IQ handles this on its own.
Key Features of Nova IQ
Self-Learning Market Scalping
Employs AI and IQ Technology to scalp micro price overextensions.
AI-Generated Trading Signals
Provides scalping signals derived from self-learning algorithms.
Comprehensive Trading System
Offers clear entry and exit labels.
Performance Tracking
Records and presents trading performance data, easily accessible for user analysis.
Higher Timeframe Filter
Allows users to implement a higher timeframe trading filter.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
Nova Oscillator (NOSC)
The Nova IQ Oscillator (NOSC) is an exclusive self-learning oscillator developed by Trading IQ. Using IQ Technology, the NOSC functions as an all-in-one oscillator for evaluating price overextensions.
Nova Bands (NBANDS)
The Nova Bands (NBANDS) are based on a proprietary calculation and serve as a custom two-layer smoothing filter that uses exponential decay. These bands adaptively smooth prices to identify potential trend retracement opportunities.
How It Works
Nova IQ operates on a simple heuristic: scalp long during micro downside overextensions and short during micro upside overextensions.
What constitutes an "overextension" is defined by IQ Technology, TradingIQ's proprietary AI algorithm. For Nova IQ, this algorithm evaluates the typical extent of micro overextensions before a reversal occurs. By learning from these patterns, Nova IQ adapts to identify and trade future overextensions in a consistent manner.
In essence, Nova IQ learns from price movements within scalping timeframes to pinpoint price areas for capitalizing on the reversal of an overextension.
As a trading system, Nova IQ enters all positions using market orders at the bar’s close. Each trade is exited with a profit-taking limit order and a stop-loss order. Thanks to its self-learning capability, Nova IQ determines the most suitable profit target and stop-loss levels, eliminating the need for the user to adjust any settings.
What classifies as a tradable overextension?
For Nova IQ, tradable overextensions are not manually set but are learned by the system. Nova IQ utilizes NOSC to identify and classify micro overextensions. By analyzing multiple variations of NOSC, along with its consistency in signaling overextensions and its tendency to remain in extreme zones, Nova IQ dynamically adjusts NOSC to determine what constitutes overextension territory for the indicator.
When NOSC reaches the downside overextension zone, long trades become eligible for entry. Conversely, when NOSC reaches the upside overextension zone, short trades become eligible for entry.
The image above illustrates NOSC and explains the corresponding overextension zones
The blue lower line represents the Downside Overextension Zone.
The red upper line represents the Upside Overextension Zone.
Any area between the two deviation points is not considered a tradable price overextension.
When either of the overextension zones are breached, Nova IQ will get to work at determining a trade opportunity.
The image above shows a long position being entered after the Downside Overextension Zone was reached.
The blue line on the price scale shows the AI-calculated profit target for the scalp position. The redline shows the AI-calculated stop loss for the scalp position.
Blue arrows indicate that the strategy entered a long position at the highlighted price level.
Yellow arrows indicate a position was closed.
You can also hover over the trade labels to get more information about the trade—such as the entry price and exit price.
The image above depicts a short position being entered after the Upside Overextension Zone was breached.
The blue line on the price scale shows the AI-calculated profit target for the scalp position. The redline shows the AI-calculated stop loss for the scalp position.
Red arrows indicate that the strategy entered a short position at the highlighted price level.
Yellow arrows indicate that NOVA IQ exited a position.
Long Entry: Blue Arrow
Short Entry: Red Arrow
Closed Trade: Yellow Arrow
Nova Bands
The Nova Bands (NBANDS) are based on a proprietary calculation and serve as a custom two-layer smoothing filter that uses exponential decay and cosine factors.
These bands adaptively smooth the price to identify potential trend retracement opportunities.
The image above illustrates how to interpret NBANDS. While NOSC focuses on identifying micro overextensions, NBANDS is designed to capture larger price overextensions. As a result, the two indicators complement each other well and can be effectively used together to identify a broader range of price overextensions in the market.
While the Nova Bands are not part of the core heuristic and do not use IQ technology, they provide valuable insights for discretionary traders looking to refine their strategies.
Use HTF (Use Higher Timeframe) Setting
Nova IQ has only one setting that controls its functionality.
“Use HTF” controls whether the AI uses a higher timeframe trading filter. This setting can be true or false. If true, the trader must select the higher timeframe to implement.
No Higher TF Filter
Nova IQ operates with standard aggression when the higher timeframe setting is turned off. In this mode, it exclusively learns from the price data of the current chart, allowing it to trade more aggressively without the influence of a higher timeframe filter.
Higher TF Filter
Nova IQ demonstrates reduced aggression when the "Use HTF" (Higher Timeframe) setting is enabled. In this mode, Nova IQ learns from both the current chart's data and the selected higher timeframe data, factoring in the higher timeframe trend when seeking scalping opportunities. As a result, trading opportunities only arise when both the higher timeframe and the chart's timeframe simultaneously display overextensions, making this mode more selective in its entries.
In this mode, Nova IQ calculates NOSC on the higher timeframe, learns from the corresponding price data, and applies the same rules to NOSC as it does for the current chart's timeframe. This ensures that Nova IQ consistently evaluates overextensions across both timeframes, maintaining its trading logic while incorporating higher timeframe insights.
AI Direction
The AI Direction setting controls the trade direction Nova IQ is allowed to take.
“Trade Longs” allows for long trades.
“Trade Shorts” allows for short trades.
Verifying Nova IQ’s Effectiveness
Nova IQ automatically tracks its performance and displays the profit factor for the long strategy and the short strategy it uses. This information can be found in a table located in the top-right corner of your chart showing the long strategy profit factor and the short strategy profit factor.
The image above shows the long strategy profit factor and the short strategy profit factor for Nova IQ.
A profit factor greater than 1 indicates a strategy profitably traded historical price data.
A profit factor less than 1 indicates a strategy unprofitably traded historical price data.
A profit factor equal to 1 indicates a strategy did not lose or gain money when trading historical price data.
Using Nova IQ
While Nova IQ is a full-fledged trading system with entries and exits - it was designed for the manual trader to take its trading signals and analysis indications to greater heights, offering numerous applications beyond its built-in trading system.
The hallmark feature of Nova IQ is its to ignore noise and only generate signals during tradable overextensions.
The best way to identify overextensions with Nova IQ is with NOSC.
NOSC is naturally adept at identifying micro overextensions. While it can be interpreted in a manner similar to traditional oscillators like RSI or Stochastic, NOSC’s underlying calculation and self-learning capabilities make it significantly more advanced and useful than conventional oscillators.
Additionally, manual traders can benefit from using NBANDS. Although NBANDS aren't a core component of Nova IQ's guiding heuristic, they can be valuable for manual trading. Prices rarely extend beyond these bands, and it's uncommon for prices to consistently trade outside of them.
NBANDS do not incorporate IQ Technology; however, when combined with NOSC, traders can identify strong double-confluence opportunities.
[Pandora] Vast Volatility Treasure TroveINTRODUCTION:
Volatility enthusiasts, prepare for VICTORY on this day of July 4th, 2024! This is my "Vast Volatility Treasure Trove," intended mostly for educational purposes, yet these functions will also exhibit versatility when combined with other algorithms to garner statistical excellence. Once again, I am now ripping the lid off of Pandora's box... of volatility. Inside this script is a 'vast' collection of volatility estimators, reflecting the indicators name. Whether you are a seasoned trader destined to navigate financial strife or an eagerly curious learner, this script offers a comprehensive toolkit for a broad spectrum of volatility analysis. Enjoy your journey through the realm of market volatility with this code!
WHAT IS MARKET VOLATILITY?:
Market volatility refers to various fluctuations in the value of a financial market or asset over a period of time, often characterized by occasional rapid and significant deviations in price. During periods of greater market volatility, evolving conditions of prices can move rapidly in either direction, creating uncertainty for investors with results of sharp declines as well as rapid gains. However, market volatility is a typical aspect expected in financial markets that can also present opportunities for informed decision-making and potential benefits from the price flux.
SCRIPT INTENTION:
Volatility is assuredly omnipresent, waxing and waning in magnitude, and some readers have every intention of studying and/or measuring it. This script serves as an all-in-one armada of volatility estimators for TradingView members. I set out to provide a diverse set of tools to analyze and interpret market volatility, offering volatile insights, and aid with the development of robust trading indicators and strategies.
In today's fast-paced financial markets, understanding and quantifying volatility is informative for both seasoned traders and novice investors. This script is designed to empower users by equipping them with a comprehensive suite of volatility estimators. Each function within this script has been meticulously crafted to address various aspects of volatility, from traditional methods like Garman-Klass and Parkinson to more advanced techniques like Yang-Zhang and my custom experimental algorithms.
Ultimately, this script is more than just a collection of functions. It is a gateway to a deeper understanding of market volatility and a valuable resource for anyone committed to mastering the complexities of financial markets.
SCRIPT CONTENTS:
This script includes a variety of functions designed to measure and analyze market volatility. Where applicable, an input checkbox option provides an unbiased/biased estimate. Below is a brief description of each function in the original order they appear as code upon first publish:
Parkinson Volatility - Estimates volatility emphasizing the high and low range movements.
Alternate Parkinson Volatility - Simpler version of the original Parkinson Volatility that I realized.
Garman-Klass Volatility - Estimates volatility based on high, low, open, and close prices using a formula that adjusts for biases in price dynamics.
Rogers-Satchell-Yoon Volatility #1 - Estimates volatility based on logarithmic differences between high, low, open, and close values.
Rogers-Satchell-Yoon Volatility #2 - Similar estimate to Rogers-Satchell with the same result via an alternate formulation of volatility.
Yang-Zhang Volatility - An advanced volatility estimate combining both strengths of the Garman-Klass and Rogers-Satchell estimators, with weights determined by an alpha parameter.
Yang-Zhang (Modified) Volatility - My experimental modification slightly different from the Yang-Zhang formula with improved computational efficiency.
Selectable Volatility - Basic customizable volatility calculation based on the logarithmic difference between selected numerator and denominator prices (e.g., open, high, low, close).
Close-to-Close Volatility - Estimates volatility using the logarithmic difference between consecutive closing prices. Specifically applicable to data sources without open, high, and low prices.
Open-to-Close Volatility - (Overnight Volatility): Estimates volatility based on the logarithmic difference between the opening price and the last closing price emphasizing overnight gaps.
Hilo Volatility - Estimates volatility using a method similar to Parkinson's method, which considers the logarithm of the high and low prices.
Vantage Volatility - My experimental custom 'vantage' method to estimate volatility similar to Yang-Zhang, which incorporates various factors (Alpha, Beta, Gamma) to generate a weighted logarithmic calculation. This may be a volatility advantage or disadvantage, hence it's name.
Schwert Volatility - Estimates volatility based on arithmetic returns.
Historical Volatility - Estimates volatility considering logarithmic returns.
Annualized Historical Volatility - Estimates annualized volatility using logarithmic returns, adjusted for the number of trading days in a year.
If I omitted any other known varieties, detailed requests for future consideration can be made below for their inclusion into this script within future versions...
BONUS ALGORITHMS:
This script also includes several experimental and bonus functions that push the boundaries of volatility analysis as I understand it. These functions are designed to provide additional insights and also are my ideal notions for traders looking to explore other methods of volatility measurement.
VOLATILITY APPLICATIONS:
Volatility estimators serve a common role across various facets of trading and financial analysis, offering insights into market behavior. These tools are already in instrumental with enhancing risk management practices by providing a deeper understanding of market dynamics and the inherent uncertainty in asset prices. With volatility estimators, traders can effectively quantifying market risk and adjust their strategies accordingly, optimizing portfolio performance and mitigating potential losses. Additionally, volatility estimations may serve as indication for detecting overbought or oversold market conditions, offering probabilistic insights that could inform strategic decisions at turning points. This script
distinctly offers a variety of volatility estimators to navigate intricate financial terrains with informed judgment to address challenges of strategic planning.
CODE REUSE:
You don't have to ask for my permission to use/reuse these functions in your published scripts, simply because I have better things to do than answer requests for the reuse of these functions.
Notice: Unfortunately, I will not provide any integration support into member's projects at all. I have my own projects that require way too much of my day already.
Machine Learning : Dominant Cycle Elastic Volume KNNAbout the Script
Dominant Cycle Elastic Volume KNN ,
is a non-parametric algorithm, which means that, initially it makes no assumptions about the underlying distribution of the time-series price as well as volume.
This approach gives it flexibility so that it can be used on a wide variety of securities at variety of timeframes.(even on lower timeframes such as seconds)
The main purpose of this indicator is to predict the trend of the underlying, by converging price, volume and dominant cycle as dimensions and generate signals of action.
Key terms :
Dominant cycle is a time cycle that has a greater influence on the overall behaviour of a system than other cycles.
The system uses Ehlers method to calculate Dominant Cycle/ Period.
Dominant cycle is used to determine the influencing period for the underlying.
Once the dominant cycle/ period is identified, it is treated as a dynamic length for considering further calculations
Elastic Volume MA is a volume based moving average which is generally used to converge the volume with price, the dominant period is used here as the length parameter
KNN K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on Supervised Learning technique.
K-NN algorithm assumes the similarity between the new case/data and available cases and put the new case into the category that is most similar to the available categories.
K-NN algorithm stores all the available data and classifies a new data point based on the similarity. This means when new data appears then it can be easily classified into a well suite category by using K- NN algorithm. K-NN algorithm can be used for Regression as well as for Classification but mostly it is used for the Classification problems.
So, K-NN is used here to classify the trend of the Dominant Cycle Elastic Volume, and Generate Signals on top of it
How to Use the Indicator ?
The Buy Signal Candle
The Sell Signal Candle
The Buy Setup
The Sell Setup
Stop and Reverse Structure
What Timeframes and Symbols can this indicator be used on ?
The above indicator can be used on any liquid security which has volume information intact with ticker
and it can be used on any timeframe, but the best timeframes are
The indicator can also be used as a trend confirmatory indicators on lower time frames, like 30second
The Script has provision for alerts
Two alerts are there :
Alert 1= "LONG CONDITION : DCEV-ML"
Alert 2= "SHORT CONDITION : DCEV-ML"
How to request for access ?
Simply private message me !
Endpointed SSA of Price [Loxx]The Endpointed SSA of Price: A Comprehensive Tool for Market Analysis and Decision-Making
The financial markets present sophisticated challenges for traders and investors as they navigate the complexities of market behavior. To effectively interpret and capitalize on these complexities, it is crucial to employ powerful analytical tools that can reveal hidden patterns and trends. One such tool is the Endpointed SSA of Price, which combines the strengths of Caterpillar Singular Spectrum Analysis, a sophisticated time series decomposition method, with insights from the fields of economics, artificial intelligence, and machine learning.
The Endpointed SSA of Price has its roots in the interdisciplinary fusion of mathematical techniques, economic understanding, and advancements in artificial intelligence. This unique combination allows for a versatile and reliable tool that can aid traders and investors in making informed decisions based on comprehensive market analysis.
The Endpointed SSA of Price is not only valuable for experienced traders but also serves as a useful resource for those new to the financial markets. By providing a deeper understanding of market forces, this innovative indicator equips users with the knowledge and confidence to better assess risks and opportunities in their financial pursuits.
█ Exploring Caterpillar SSA: Applications in AI, Machine Learning, and Finance
Caterpillar SSA (Singular Spectrum Analysis) is a non-parametric method for time series analysis and signal processing. It is based on a combination of principles from classical time series analysis, multivariate statistics, and the theory of random processes. The method was initially developed in the early 1990s by a group of Russian mathematicians, including Golyandina, Nekrutkin, and Zhigljavsky.
Background Information:
SSA is an advanced technique for decomposing time series data into a sum of interpretable components, such as trend, seasonality, and noise. This decomposition allows for a better understanding of the underlying structure of the data and facilitates forecasting, smoothing, and anomaly detection. Caterpillar SSA is a particular implementation of SSA that has proven to be computationally efficient and effective for handling large datasets.
Uses in AI and Machine Learning:
In recent years, Caterpillar SSA has found applications in various fields of artificial intelligence (AI) and machine learning. Some of these applications include:
1. Feature extraction: Caterpillar SSA can be used to extract meaningful features from time series data, which can then serve as inputs for machine learning models. These features can help improve the performance of various models, such as regression, classification, and clustering algorithms.
2. Dimensionality reduction: Caterpillar SSA can be employed as a dimensionality reduction technique, similar to Principal Component Analysis (PCA). It helps identify the most significant components of a high-dimensional dataset, reducing the computational complexity and mitigating the "curse of dimensionality" in machine learning tasks.
3. Anomaly detection: The decomposition of a time series into interpretable components through Caterpillar SSA can help in identifying unusual patterns or outliers in the data. Machine learning models trained on these decomposed components can detect anomalies more effectively, as the noise component is separated from the signal.
4. Forecasting: Caterpillar SSA has been used in combination with machine learning techniques, such as neural networks, to improve forecasting accuracy. By decomposing a time series into its underlying components, machine learning models can better capture the trends and seasonality in the data, resulting in more accurate predictions.
Application in Financial Markets and Economics:
Caterpillar SSA has been employed in various domains within financial markets and economics. Some notable applications include:
1. Stock price analysis: Caterpillar SSA can be used to analyze and forecast stock prices by decomposing them into trend, seasonal, and noise components. This decomposition can help traders and investors better understand market dynamics, detect potential turning points, and make more informed decisions.
2. Economic indicators: Caterpillar SSA has been used to analyze and forecast economic indicators, such as GDP, inflation, and unemployment rates. By decomposing these time series, researchers can better understand the underlying factors driving economic fluctuations and develop more accurate forecasting models.
3. Portfolio optimization: By applying Caterpillar SSA to financial time series data, portfolio managers can better understand the relationships between different assets and make more informed decisions regarding asset allocation and risk management.
Application in the Indicator:
In the given indicator, Caterpillar SSA is applied to a financial time series (price data) to smooth the series and detect significant trends or turning points. The method is used to decompose the price data into a set number of components, which are then combined to generate a smoothed signal. This signal can help traders and investors identify potential entry and exit points for their trades.
The indicator applies the Caterpillar SSA method by first constructing the trajectory matrix using the price data, then computing the singular value decomposition (SVD) of the matrix, and finally reconstructing the time series using a selected number of components. The reconstructed series serves as a smoothed version of the original price data, highlighting significant trends and turning points. The indicator can be customized by adjusting the lag, number of computations, and number of components used in the reconstruction process. By fine-tuning these parameters, traders and investors can optimize the indicator to better match their specific trading style and risk tolerance.
Caterpillar SSA is versatile and can be applied to various types of financial instruments, such as stocks, bonds, commodities, and currencies. It can also be combined with other technical analysis tools or indicators to create a comprehensive trading system. For example, a trader might use Caterpillar SSA to identify the primary trend in a market and then employ additional indicators, such as moving averages or RSI, to confirm the trend and generate trading signals.
In summary, Caterpillar SSA is a powerful time series analysis technique that has found applications in AI and machine learning, as well as financial markets and economics. By decomposing a time series into interpretable components, Caterpillar SSA enables better understanding of the underlying structure of the data, facilitating forecasting, smoothing, and anomaly detection. In the context of financial trading, the technique is used to analyze price data, detect significant trends or turning points, and inform trading decisions.
█ Input Parameters
This indicator takes several inputs that affect its signal output. These inputs can be classified into three categories: Basic Settings, UI Options, and Computation Parameters.
Source: This input represents the source of price data, which is typically the closing price of an asset. The user can select other price data, such as opening price, high price, or low price. The selected price data is then utilized in the Caterpillar SSA calculation process.
Lag: The lag input determines the window size used for the time series decomposition. A higher lag value implies that the SSA algorithm will consider a longer range of historical data when extracting the underlying trend and components. This parameter is crucial, as it directly impacts the resulting smoothed series and the quality of extracted components.
Number of Computations: This input, denoted as 'ncomp,' specifies the number of eigencomponents to be considered in the reconstruction of the time series. A smaller value results in a smoother output signal, while a higher value retains more details in the series, potentially capturing short-term fluctuations.
SSA Period Normalization: This input is used to normalize the SSA period, which adjusts the significance of each eigencomponent to the overall signal. It helps in making the algorithm adaptive to different timeframes and market conditions.
Number of Bars: This input specifies the number of bars to be processed by the algorithm. It controls the range of data used for calculations and directly affects the computation time and the output signal.
Number of Bars to Render: This input sets the number of bars to be plotted on the chart. A higher value slows down the computation but provides a more comprehensive view of the indicator's performance over a longer period. This value controls how far back the indicator is rendered.
Color bars: This boolean input determines whether the bars should be colored according to the signal's direction. If set to true, the bars are colored using the defined colors, which visually indicate the trend direction.
Show signals: This boolean input controls the display of buy and sell signals on the chart. If set to true, the indicator plots shapes (triangles) to represent long and short trade signals.
Static Computation Parameters:
The indicator also includes several internal parameters that affect the Caterpillar SSA algorithm, such as Maxncomp, MaxLag, and MaxArrayLength. These parameters set the maximum allowed values for the number of computations, the lag, and the array length, ensuring that the calculations remain within reasonable limits and do not consume excessive computational resources.
█ A Note on Endpionted, Non-repainting Indicators
An endpointed indicator is one that does not recalculate or repaint its past values based on new incoming data. In other words, the indicator's previous signals remain the same even as new price data is added. This is an important feature because it ensures that the signals generated by the indicator are reliable and accurate, even after the fact.
When an indicator is non-repainting or endpointed, it means that the trader can have confidence in the signals being generated, knowing that they will not change as new data comes in. This allows traders to make informed decisions based on historical signals, without the fear of the signals being invalidated in the future.
In the case of the Endpointed SSA of Price, this non-repainting property is particularly valuable because it allows traders to identify trend changes and reversals with a high degree of accuracy, which can be used to inform trading decisions. This can be especially important in volatile markets where quick decisions need to be made.
Bogdan Ciocoiu - LitigatorDescription
The Litigator is an indicator that encapsulates the value delivered by the Relative Strength Index, Ultimate Oscillator, Stochastic and Money Flow Index algorithms to produce signals enabling users to enter positions in ideal market conditions. The Litigator integrates the value delivered by the above four algorithms into one script.
This indicator is handy when trading continuation/reversal divergence strategies in conjunction with price action.
Uniqueness
The Litigator's uniqueness stands from integrating the above algorithms into the same visual area and leveraging preconfigured parameters suitable for short term scalping (1-5 minutes).
In addition, the Litigator allows configuring the above four algorithms in such a way to coordinate signals by colour-coding or shape thickness to aid the user with identifying any emerging patterns quicker.
Furthermore, Moonshot's uniqueness is also reflected in the way it has standardised the outputs of each algorithm to look and feel the same, and in doing so, enabling users to plug them in/out as needed. This also includes ensuring the ratios of the shapes are similar (applicable to the same scale).
Open-source
The indicator uses the following open-source scripts/algorithms:
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
Bogdan Ciocoiu - MoonshotDescription
Moonshot is an indicator that encapsulates the value delivered by the TSI, MACD, Awesome Oscillator and CCI algorithms to produce signals to enable users to enter positions in ideal market conditions. Moonshot integrates the value delivered by the above four algorithms into one script.
This indicator is particularly useful when trading continuation/reversal divergence strategies.
Uniqueness
The Moonshot's uniqueness stands from integrating the above algorithms into the same visual area and leveraging preconfigured parameters suitable for 1-3 minute scalping techniques.
In addition, Moonshot allows swapping or furthermore configuring the above four algorithms in such a way to align signals by colour-coding or shape thickness to aid the users with identifying any emerging patterns quicker.
Furthermore, Moonshot's uniqueness is also reflected in the way it has standardised the outputs of each algorithm to look and feel the same (including the scale at which the shapes are shown) and, in doing so, enables users to plug them in/out as needed.
Open-source
The indicator leverages the following open-source scripts/algorithms:
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
The Chartless TraderThe Chartless Trader
The chartless trader is a trade management system designed to remove the randomness from the market. It is loosely based on the martingales betting system, but takes advantage of position sizing, minimum profit targets, dollar cost averaging, and trailing take profit.
The chart can be traded with or without a signal. There is a built in signal based on SB Master Chart's Buy the Dip algorithm.
The configurable settings include:
Account Value
Starting Account Value - This is the value of the account when you start using this system.
Current Cash - This is the amount of cash you have available to trade. This setting needs to be updated each time a trade is made.
TP/TTP Algo Settings
Take Profit % - This setting is otherwise known as minimum profit target. This algo will not advise you to sell or increase your trailing stop until this minimum profit target is met.
Trailing Stop % - This is the trailing stop. The default setting is 75%. As a basic example, if the stock is up 10%, the trailing stop would be set to 7.5% (10% * 75%). The algo may override and advise an alternative trailing stop should an overbought condition be detected.
DCA/BTD Algo
DCA/BTD Algo Time Frame - Default is 120 (2hrs). This algo looks for oversold periods on the 2h chart by default.
DCA % - The default for this setting is 5%. This is a trigger for the BTD Algo. The BTD algo will start looking for trades when the stock is 5% below your cost basis. This is to help you average down making it easier to turn a profit when the stock starts making gains.
Position #
The Chartless Trader supports a maximum of 20 symbols. This is a limitation of the security() function as a maximum of 40 calls are allowed and the script calls the security() function twice per symbol.
S# QTY - The number of open positions of the symbol. This has to be manually updated by the user after each buy/sell of the stock.
S# CB - This is the cost basis of the stock. Your broker should give you this after each buy/sell and it has to be updated here on the chart after each buy/sell.
S# TTP - The script will advise you to increase your Trailing Take Profit in your broker when its necessary. This should be updated manually after you update your order in your broker. This should be configured manually in your broker as a Stop Order.
Now that I have covered the configurable options, its important to understand the basis of this system. The martingales betting system is a system that seeks to double its position size each time you enter a losing trade. Eventually when you make a winning trade, it will be enough to cover the previous losses and net you one winning position.
Bet 1, lose 1, down 1.
Bet 2, lose 2, down 3.
Bet 4, lose 4, down 7.
Bet 8, lost 8, down 15.
Bet 16, win 16, up 1.
So the theory goes, if you have deep enough pockets, its a 100% win rate. Such a system is flawed and proven to cause an account to blow up given enough time. You can search Google/YouTube for others that have back tested the martingales system with stocks.
I advise that "The Chartless Trading" system be traded with a similar system, but instead of doubling your position, you simply increase your position size by 1%.
Bet 1%, lose 1%, down 1%
Bet 1%, lose 1%, down 2%
Bet 1%, lose 1%, down 3%.
In such a manner, your risk of ruin is significantly reduced. Lets say you lose 10 times in a row betting on a stock. You now have 10% of your account value in this particular stock. Because you only invested at times where you were more than 5% down and when an oversold position occurred, because of dollar cost averaging and buying during oversold periods, you may only be down 2-3% on your invested value. Eventually when the stock turns positive, you will have met your minimum profit target and the script will alert you to set a trailing stop. You log into your broker, set a stop loss and wait for it to either trigger or inform you to increase it again. Once the trailing stop is triggered, you deleverage the position by closing it and starting a single new position in either the same stock or a different one and the cycle repeats.
The key is to follow the stock down, follow it back up, and not back down. We repeat this cycle with many positions in many stocks to minimize risk and compound our balance sheet.
This is " The Chartless Trader ".
1920x1080p Monitor Required if using all 20 symbols.
The more symbols loaded, the longer the initial processing to load the table. Please be patient.
Directional AnalyzerThis script attempts to equip users with the necessary information about the direction of an instrument, and essentially it is a synergy of 3 algorithms.
The first algorithm (plotted as dots at level 0) studies the balance of delta volatility that constitutes the current bar and answers if bulls or bears are in control at that exact bar time
The second algorithm (plotted as an area) studies the development of delta volatility over the defined period by means of a polynomial regression. Effectively, it provides an overall picture of the trend strength.
The third algorithm (plotted as a line with arrow labels) utilizes simple elements of neural network in conjunction with some custom filters to predict the focal point that a trend will reverse its direction. This is predictive in nature, hence always adopt this with caution. While the labels display the predicted direction, the colors of the line also reflect the state of the current bar as well, adding to the confirmation of the first algorithm.
May you be on the right side of the trade.
Anticipated Market TypeDisplays the anticipated market type based on the last 300 bars of data:
Trending Market: High probability that the next bar will be in the same direction as previous. Best conditions for a trend trading strategy
Neutral Market: High probability that price is random - the next bar direction is a coin toss. Many "typical" indicators fail in a random market
Sideways Market: High probability that price is autoregressive and the next bar direction is opposite the previous - compressed markets often have sudden fast breakouts
This tool does not give you entries and exits, but assists in deciding to use a Trend-following or Mean-reverting strategy.
Blue (3.5-6) indicates a trending market.
Yellow (0-2.5) indicates a sideways market.
Green (2.5-3.5) indicates a random market
This algorithm tells you when it breaks down by indicating a Neutral/Random market.
In short, it can't say the market type and advises you to not trade or simply use another tool in the meantime.
I personally use this tool to configure my trading robots on a weekly basis. I combine manual TA and stats algos to
try and determine what type of market the next week holds, with a fair bit of success.
The algorithms incorporated are Market Meanness Index (which I've made Open Source) and Fractal Dimension , a significantly faster algo than the MMI, but using a different set of maths.
Cheers!
MyAlgo EXTREMEPLEASE READ THE ENTIRE POST BEFORE PURCHASING & USING THE MyAlgo Tool. Saves you and me some time in emails and messages. :)
This is the official version of MyAlgo EXTREME
PLEASE UNDERSTAND THAT THIS IS A DIFFERENT AND SEPARATE PRODUCT AND SCRIPT FROM "MyAlgo SLIM" FROM THE MyAlgo TRADING TOOL SERIES
Description
Buy & Sell Alerts can be set on all Tickers. This includes, but is not limited to Crypto, Commodities , FOREX, Equities and Indices. Also all candle Types are compatible.
Recommended Time-frames - Due to the complexity of MyAlgo-SLIM the user has a choice between three algorithms and is like that able to trade on all timeframes with the highest returns.
MyAlgo combines many different aspects at the same time, scans multiple other Algorithms and comes to a conclusion based on over 1350 lines of code.
It is based on Divergences, Elliott Waves , Ichimoku , MACD , MACD Histogram, RSI , Stoch , CCI , Momentum, OBV, DIOSC, VWMACD, CMF and multiple EMAs.
Every single aspect is weighted into the decision before giving out an indication.
Most buy/sell Algorithms FAIL because they try to apply the same strategy to every single chart, which
are as individual as humans. To conquer this problem, MyAlgo has a wide range of settings and variables which can be easily
modified.
To make it a true strategy, MyAlgo has as well settings for Take Profit Points and Stop
Losses. Everything with an Alert Feature of course so that FULL AUTOMATION IS POSSIBLE.
I know from experience that many people take one Algorithm and are simply too LAZY to add multiple Algorithms to make a rational choice. The result of that is that they lose money, by following blatantly only one Algorithm.
MyAlgo has additional 15 Indicators, perfect for all markets, which can be turned on and off individually.
Side Notes
MyAlgo is being updated and upgraded very frequently to suit the requests of our customers.
This is not financial advice. Please read our disclaimer before using it.
Please refer to the signature field if you are interested in gaining access to this script.
Anything below this sentence will be Updates regarding MyAlgo
SMU Stock ThermometerThis script shows various technical indicators in a stacked vertical candle called Market Termometer.
It helps to see the price action in one single vertical column where the actual price moves up or down. So you can see the price change based on your custom setting levels.
I've been studying ALGO for over a year and made many live experiment trades long and shorts. So, I'm trying to find a way to see what is ALGos next move. If it sounds far-fetch, then you should see my other published scripts.
Here is example of how ALGo dance around old indicators, which is why I started creating a bunch of new indicators that ALGO doesn't know
Example:
Impact-driven-algorithm= Large volume masked as small volume to keep the price at desired level. So, your chart says overbought but market doesn't drop for days
Cost-driven-algorithm= Hedge fund buy every time at lower price and prevent others to buy low, moving up fast. Is like a clock with millisecond timing and ALGO owners know when to buy low and when to sell high
If you have a good idea, let me know so i can include it the future versions.
Enjoy and think outside the box, the only way to beat the ALGO
Thiru TOI TrackerProfessional-grade Time-of-Interest (TOI) tracker that identifies critical trading windows using proprietary institutional flow analysis and dynamic line extension algorithms.
🎯 WHAT THIS INDICATOR DOES
The Thiru TOI Tracker is a sophisticated trading tool that identifies and visualizes critical Time-of-Interest (TOI) periods in the market. Unlike traditional time-based indicators that use static markers, this system employs proprietary algorithms to dynamically adapt to market conditions, providing institutional-grade timing analysis.
🔬 UNIQUE METHODOLOGY & ALGORITHM
1. Proprietary Time Window Detection - Multi-Session Analysis
2. Dynamic Line Extension Technology - Adaptive Support/Resistance
3. Advanced Memory Management - Intelligent Cleanup
4. Multi-Dimensional Visualization - Comprehensive Market Structure
🚀 UNIQUE VALUE PROPOSITION
- Dynamic vs Static: Adapts to market conditions
- Institutional Logic: Based on trading pattern analysis
- Multi-Session Correlation: Comprehensive analysis
- Advanced Performance: Optimized memory management
- Customizable Interface: Adapts to trading styles
📊 HOW TO USE
- Apply to 1m-15m timeframes for best results
- Configure session settings based on trading style
- Customize visual elements for chart clarity
- Use timeframe filter to prevent false signals
🔒 PROPRIETARY PROTECTION JUSTIFIED BY:
- Unique methodology based on institutional analysis
- Dynamic adaptation algorithms
- Performance innovation
- Extensive research investment
- Competitive advantages
Developer: ThiruDinesh | Contact: TradingView @ThiruDinesh
Copyright: © 2025 ThiruDinesh - All Rights Reserved
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Market Profile based Support/ResistanceBrought to you by Stock Kaka - Your trading sidekick 🦜📈 - pay your visit at stockkaka.my.canva.site or find us on X #StockKaka
📊 What This Indicator Does
Ever wish the market would just tell you where the important levels are? Well, buckle up, because this indicator is like having a market whisperer on your chart!
Based on cutting-edge hierarchical market structure analysis (fancy words for "smart support and resistance"), this bad boy uses ATR-based Directional Change to identify turning points that actually matter. No more guessing where price might bounce or break—let the algorithm do the heavy lifting while you sip your coffee ☕
🎯 The Five Levels Explained (From Noisy to Mighty)
Think of these levels like a pyramid of importance. Level 0 is your chatty friend who notices everything, while Level 4 is the wise oracle who only speaks when it really matters.
Level 0: The Hyperactive Scout 🐿️
What it does: Catches every little zigzag in price using ATR confirmation
Significance: Very short-term, intraday noise
Best for: Scalpers who love action every few minutes
Trader Type: "I refresh my chart 100 times an hour"
Reliability: ⭐⭐ (It's enthusiastic but easily excitable)
Level 1: The Day Trader's Buddy 🎯
What it does: Filters Level 0 to show minor swing highs/lows
Significance: Intraday support/resistance, hourly structure
Best for: Day traders, scalpers looking for better entries
Trader Type: "I close all positions before dinner"
Reliability: ⭐⭐⭐ (Solid for quick moves)
Level 2: The Swing Trader's Sweet Spot 🎪
What it does: Identifies multi-day to weekly structure points
Significance: Intermediate support/resistance where battles happen
Best for: Swing traders, position traders
Trader Type: "I hold for days, not minutes"
Reliability: ⭐⭐⭐⭐ (Now we're talking real structure!)
Level 3: The Big Money Magnet 💰
What it does: Shows major market structure—where the whales play
Significance: Weekly to monthly levels, institutional zones
Best for: Position traders, trend followers
Trader Type: "I think in weeks and months, not hours"
Reliability: ⭐⭐⭐⭐⭐ (These levels have gravitational pull!)
Level 4: The Market Prophet 🔮
What it does: Reveals ultra-major turning points (think: quarterly/yearly pivots)
Significance: Long-term macro structure, investment-grade levels
Best for: Investors, long-term position traders
Trader Type: "Warren Buffett is my spirit animal"
Reliability: ⭐⭐⭐⭐⭐⭐ (When these break, market's rewrite the story)
⚙️ Parameter Setup Guide (The Secret Sauce)
The magic ingredient is the ATR Lookback Period—think of it as teaching the indicator your timeframe's "dialect." Here's your cheat sheet:
2-Minute Chart ⚡
ATR Lookback: 720 (24 hours of 2-min bars)
Who uses this: Crypto degens, futures scalpers, adrenaline junkies
Show Levels: L0, L1, L2 (L3+ won't budge much)
Pro Tip: Enable only L1 and L2 or your chart will look like spaghetti
5-Minute Chart 🏃
ATR Lookback: 288 (24 hours of 5-min bars)
Who uses this: Active day traders, news traders
Show Levels: L1, L2, L3
Pro Tip: L2 is your best friend here—perfect for intraday swings
15-Minute Chart 📈
ATR Lookback: 96 (24 hours of 15-min bars)
Who uses this: Swing traders, patient day traders
Show Levels: L1, L2, L3
Pro Tip: This is the "Goldilocks zone"—not too fast, not too slow
1-Hour Chart ⏰
ATR Lookback: 168 (1 week of hourly bars)
Who uses this: Swing traders, position traders
Show Levels: L2, L3, L4
Pro Tip: L3 levels here are like magnets for price action
Daily Chart 📅
ATR Lookback: 30 to 50 (1-2 months)
Who uses this: Investors, long-term traders, people with patience
Show Levels: L2, L3, L4
Pro Tip: L4 on dailies = "Don't fight this level, respect it"
🎨 How to Use This Thing
Add to Chart - Duh! 😄
Set Your ATR Lookback - Use the guide above (don't wing it!)
Enable Relevant Levels - Less is more! Turn off levels that just clutter
Watch the Magic - See horizontal lines appear at key S/R zones
Check the Table - Top-right corner shows current levels (fancy!)
Set Alerts - Get notified when price approaches or breaks levels
Trading Strategies 🎲
The Bounce Play:
Price approaches Level 2 or 3 support → Look for bullish reversal signals
Take profit at the next level resistance
Stop loss just below the support level
The Breakout Play:
Price breaks through Level 2/3 resistance with volume → Go long
Next level becomes your target
Failed breakout? Level becomes resistance again (classic fake-out)
The Confluence Play:
When Level 3 aligns with your favorite indicator (RSI oversold, moving average, Fibonacci) → Chef's kiss! 👨🍳💋
These multi-confirmation setups are where the money lives
🚨 Important Notes (Read This or Blame Yourself Later)
⚠️ This indicator REPAINTS on the current bar until an extreme is confirmed. That's not a bug, it's how directional change works. The past levels are solid as a rock, but the pending one is still... pending.
⚠️ More levels ≠ Better results. Showing all 5 levels is like having 5 GPS apps shouting directions at once. Pick 2-3 levels max.
⚠️ ATR Lookback matters! Wrong setting = garbage results. Use the guide above or experiment carefully.
⚠️ Volatile markets (crypto, meme stocks) work GREAT with this. Choppy, range-bound markets? Meh.
⚠️ Combine with other tools! This shows you WHERE, not WHEN. Use momentum indicators, volume, or your favorite chicken entrails for timing 🐔
🦜 Final Word from Stock Kaka
Remember: Indicators don't make money, traders do. This tool shows you where the market has historically respected structure. What you do with that info? That's on you, champ!
Use proper risk management, don't YOLO your rent money, and may your stops never get hunted 🎯
Trade smart, trade safe, and let Stock Kaka be your guide!
📝 Credits
Algorithm: neurotrader888 (Python implementation)
Pine Script Conversion: Your friendly neighborhood Stock Kaka team!!
Inspiration: Ginger chai, market inefficiencies, and a dash of chaos
📌 Tags
support-and-resistance market-structure atr directional-change multi-timeframe swing-trading day-trading levels hierarchical-analysis algo-trading
Entries + FVG SignalsE+FVG: A Masterclass in Institutional Trading Concepts
Chapter 1: The Modern Trader's Dilemma—Decoding the Institutional Footprint
In the vast, often chaotic ocean of the financial markets, retail traders navigate with the tools they are given: conventional indicators like moving averages, RSI, and MACD. While useful for gauging momentum and general trends, these tools often fall short because they were not designed to interpret the primary force that moves markets: institutional order flow. The modern trader faces a critical challenge: the tools and concepts taught in mainstream trading education are often decades behind the sophisticated, algorithm-driven strategies employed by banks, hedge funds, and large financial institutions.
This leads to a frustrating cycle of seemingly inexplicable price movements. A trader might see a perfect breakout from a classic pattern, only for it to reverse viciously, stopping them out. They might identify a strong trend, yet struggle to find a logical entry point, consistently feeling "late to the party." These experiences are not random; they are often the result of institutional market manipulation designed to engineer liquidity.
The fundamental problem that E+FVG (Entries + FVG Signals) addresses is this informational asymmetry. It is a sophisticated, institutional-grade framework designed to move a trader's perspective from a retail mindset to a professional one. It does not rely on lagging, derivative indicators. Instead, it focuses on the two core elements of price action that reveal the true intentions of "Smart Money": liquidity and imbalances.
This is not merely another indicator to add to a chart; it is a complete analytical engine designed to help you see the market through a new lens. It deconstructs price action to pinpoint two critical things:
Where institutions are likely to hunt for liquidity (running stop-loss orders).
The specific price inefficiencies (Fair Value Gaps) they are likely to target.
By focusing on these core principles, E+FVG provides a logical, rules-based solution to identifying high-probability trade setups. It is built for the discerning trader who is ready to evolve beyond conventional technical analysis and learn a methodology that is aligned with how the market truly operates at an institutional level. It is, in essence, an operating system for "Smart Money" trading.
Chapter 2: The Core Philosophy—Liquidity is the Fuel, Imbalances are the Destination
To fully grasp the power of this tool, one must first understand its foundational philosophy, which is rooted in the core tenets of institutional trading, often referred to as Smart Money Concepts (SMC). This philosophy can be distilled into two simple, powerful ideas:
1. Liquidity is the Fuel that Moves the Market:
The market does not move simply because there are more buyers than sellers, or vice-versa. It moves to seek liquidity. Large institutions cannot simply click "buy" or "sell" to enter or exit their multi-million or billion-dollar positions. Doing so would cause massive slippage and alert the entire market to their intentions. Instead, they must strategically accumulate and distribute their positions in areas where there is a high concentration of orders.
Where are these orders located? They are clustered in predictable places: above recent swing highs (buy-stop orders from shorts, and breakout buy orders) and below recent swing lows (sell-stop orders from longs, and breakout sell orders). This collective pool of orders is called liquidity. Institutions will often drive price towards these liquidity pools in a "stop hunt" or "liquidity grab" to trigger those orders, creating the necessary volume for them to fill their own large positions, often in the opposite direction of the liquidity grab itself. Understanding this concept is the key to avoiding being the "fuel" and instead learning to trade alongside the institutions.
2. Imbalances (Fair Value Gaps) are the Magnets for Price:
When institutions enter the market with overwhelming force, they create an imbalance in the order book. This energetic, one-sided price movement often leaves behind a gap in the market's pricing mechanism. On a candlestick chart, this appears as a Fair Value Gap (FVG)—a three-candle formation where the wicks of the first and third candles do not fully overlap the range of the middle candle.
These are not random gaps; they represent an inefficiency in the market's price delivery. The market, in its constant quest for equilibrium, has a natural tendency to revisit these inefficiently priced areas to "rebalance" the order book. Therefore, FVGs act as powerful magnets for price. They serve as high-probability targets for a price move and, critically, as logical points of interest where price may reverse after filling the imbalance. A fresh, unfilled FVG is one of the most significant clues an institution leaves behind.
E+FVG is built entirely on this philosophy. The "Entries Simplified" engine is designed to identify the liquidity grabs, and the "FVG Signals" engine is designed to identify the imbalances. Together, they provide a complete, synergistic framework for institutional-grade analysis.
Chapter 3: The Engine, Part I—"Entries Simplified": A Framework for Precision Entry
This is the primary trade-spotting engine of the E+FVG tool. It is a multi-layered system designed to identify a very specific, high-probability entry model based on institutional behavior. It filters out market noise by focusing solely on the sequence of a liquidity sweep followed by a clear and energetic displacement.
Feature 1: The Multi-Timeframe Liquidity Engine
The first and most crucial step in the engine's logic is to identify a valid liquidity grab. The script understands that the most significant reversals are often initiated after price has swept a key high or low from a higher timeframe. A sweep of yesterday's high holds far more weight than a sweep of the last 5-minute high.
Automatic Timeframe Adaptation: The engine intelligently analyzes your current chart's timeframe and automatically selects an appropriate higher timeframe (HTF) for its core analysis. For instance, if you are on a 15-minute chart, it might reference the 4-hour or Daily chart to identify key structural points. This is done seamlessly in the background, ensuring the analysis is always anchored to a significant structural context without requiring manual input.
The "Sweep" Condition: The script is not looking for a simple touch of a high or low. It is looking for a definitive sweep (also known as a "stop hunt" or "Judas swing"). This is defined as price pushing just beyond a key prior candle's high or low and then closing back within its range. This specific price action pattern is a classic signature of a liquidity grab, indicating that the move's purpose was to trigger stops, not to start a new, sustained trend. The "Entries Simplified" engine is constantly scanning the HTF price action for these sweep events, as they are the necessary precondition for any potential setup.
Feature 2: The Upshift/Downshift Signal—Confirming the Reversal
Once a valid HTF liquidity sweep has occurred, the engine moves to its next phase: identifying the confirmation. A sweep alone is not enough; institutions must show their hand and reveal their intention to reverse the market. This confirmation comes in the form of a powerful structural breakout (for bullish reversals) or breakdown (for bearish reversals). We call these events Upshifts and Downshifts.
Defining the Upshift & Downshift: This is the critical moment of confirmation, the market "tipping its hand."
An Upshift occurs after a liquidity sweep below a key low. Following the sweep, price reverses with energy and produces a decisive breakout to the upside, closing above a recent, valid swing high. This action confirms that the prior downtrend's momentum is broken, the downward move was a trap to engineer liquidity, and institutional buyers are now in aggressive control.
A Downshift occurs after a liquidity sweep above a key high. Following the sweep, price reverses aggressively and produces a sharp breakdown to the downside, closing below a recent, valid swing low. This confirms that the prior uptrend's momentum has failed, the upward move was a liquidity grab, and institutional sellers have now taken control of the market.
Algorithmic Identification: The E+FVG engine uses a proprietary algorithm to identify these moments. It analyzes the candle sequence immediately following a sweep, looking for a specific type of market structure break characterized by high energy and displacement—often leaving imbalances (Fair Value Gaps) in its wake. This is not a simple "pivot break"; the algorithm is designed to distinguish between a weak, indecisive wiggle and a true, institutionally-backed Upshift or Downshift.
The Signal: When this precise sequence—a HTF liquidity sweep followed by a valid Upshift or Downshift on the trading timeframe—is confirmed, the indicator plots a clear arrow on the chart. A green arrow below a low signifies a Bullish setup (confirmed by an Upshift), while a red arrow above a high signifies a Bearish setup (confirmed by a Downshift). This is the core entry signal of the "Entries Simplified" engine.
Feature 3: Automated Price Projections—A Built-In Trade Management Framework
A valid entry signal is only one part of a successful trade. A trader also needs a logical framework for taking profits. The E+FVG engine completes its trade-spotting process by providing automated, mathematically-derived price projections.
Fibonacci-Based Logic: After a valid Upshift or Downshift signal is generated, the script analyzes the price leg that created the setup (i.e., the range from the liquidity sweep to the confirmation breakout/breakdown). It then uses a methodology based on standard Fibonacci extension principles to project several potential take-profit (TP) levels.
Multiple TP Levels: The indicator projects four distinct TP levels (TP1, TP2, TP3, TP4). This provides a comprehensive trade management framework. A conservative trader might aim for TP1 or TP2, while a more aggressive trader might hold a partial position for the higher targets. These levels are plotted on the chart as clear, labeled lines, removing the guesswork from profit-taking.
Dynamic and Adaptive: These projections are not static. They are calculated uniquely for each individual setup, based on the specific volatility and range of the price action that generated the signal. This ensures that the take-profit targets are always relevant to the current market conditions.
The "Entries Simplified" engine, therefore, provides a complete, end-to-end framework: it waits for a high-probability condition (HTF sweep), confirms it with a specific entry model (Upshift/Downshift), and provides a logical road map for managing the trade (automated projections).
Chapter 4: The Engine, Part II—"FVG Signals": Mapping Market Inefficiencies
This second, complementary engine of the E+FVG tool operates as a market mapping system. Its sole purpose is to identify, plot, and monitor Fair Value Gaps (FVGs)—the critical price inefficiencies that act as magnets and potential reversal points.
Feature 1: Dual Timeframe FVG Detection
The significance of an FVG is directly related to the timeframe on which it forms. A 1-hour FVG is a more powerful magnet for price than a 1-minute FVG. The FVG engine gives you the ability to monitor both simultaneously, providing a richer, multi-dimensional view of the market's inefficiencies.
Chart TF FVGs: The indicator will, by default, identify and plot the FVGs that form on your current, active chart timeframe. These are useful for short-term scalping and for fine-tuning entries.
Higher Timeframe (HTF) FVGs: With a single click, you can enable the HTF FVG detection. This allows you to overlay, for example, 1-hour FVGs onto your 5-minute chart. This is an incredibly powerful feature. Seeing a 5-minute price rally approaching a fresh, unfilled 1-hour bearish FVG gives you a high-probability context for a potential reversal. The HTF FVGs act as major points of interest that can override the short-term price action.
Feature 2: The Intelligent "Tap-In" Logic—Beyond a Simple Touch
Many FVG indicators will simply alert you when price touches an FVG. The E+FVG engine employs a more sophisticated, two-stage logic to generate its signals, which helps to filter out weak reactions and focus on confirmed reversals.
Stage 1: The Entry. The first event is when price simply enters the FVG zone. This is a "heads-up" moment, and the indicator can be configured to provide an initial alert for this event.
Stage 2: The Confirmed "Tap-In." The official signal, however, is the "Tap-In." This is a more stringent condition. For a bullish FVG, a Tap-In is only confirmed after price has touched or entered the FVG zone and then closed back above the FVG's high. For a bearish FVG, the price must touch or enter the zone and then close back below the FVG's low. This confirmation logic ensures that the FVG has not just been touched, but has been respected and rejected by the market, making the resulting arrow signal significantly more reliable than a simple touch alert.
Feature 3: Interactive and Clean Visuals
The FVG engine is designed to provide maximum information with minimum chart clutter.
Clear, Color-Coded Boxes: Bullish FVGs are plotted in one color (e.g., green or blue), and bearish FVGs in another (e.g., red or orange), with a clear distinction between Chart TF and HTF zones.
Optional Box Display: Recognizing that some traders prefer a cleaner chart, you have the option to hide the FVG boxes entirely. Even with the boxes hidden, the underlying logic remains active, and the script will still generate the crucial Tap-In arrow signals.
Automatic Fading: Once an FVG has been successfully "tapped," the script can be set to automatically fade the color of the box. This provides a clear visual cue that the zone has been tested and may have less significance going forward.
Expiration: FVGs do not remain relevant forever. The script automatically removes old FVG boxes from the chart after a user-defined number of bars, ensuring your analysis is always focused on the most recent and relevant market inefficiencies.
Chapter 5: The Power of Synergy—How the Two Engines Work Together
While both the "Entries Simplified" engine and the "FVG Signals" engine are powerful standalone tools, their true potential is unlocked when used in combination. They are designed to provide confluence—a scenario where two or more independent analytical concepts align to produce a single, high-conviction trade idea.
Scenario A: The A+ Setup (Upshift into FVG). This is the highest probability setup. Imagine the "Entries Simplified" engine detects a HTF liquidity sweep below a key low, followed by a bullish Upshift signal. You look at your chart and see that this strong upward displacement is heading directly towards a fresh, unfilled bearish HTF FVG. This provides you with both a high-probability entry signal and a logical, high-probability target for the trade.
Scenario B: The FVG Confirmation. A trader might see the "Entries Simplified" engine generate a bearish Downshift signal. They feel it is a valid setup but want one extra layer of confirmation. They wait for price to rally a little further and "tap-in" to a nearby bearish FVG that formed during the Downshift's displacement. The FVG Tap-In signal then serves as their final confirmation trigger to enter the trade.
Scenario C: The Standalone FVG Trade. The FVG engine can also be used as a primary trading tool. A trader might notice that price is in a strong uptrend. They see price pulling back towards a fresh, bullish HTF FVG. They are not waiting for a full Upshift/Downshift setup; instead, they are simply waiting for the FVG Tap-In signal to confirm that the pullback is likely over and the trend is ready to resume.
By learning to read the interplay between these two engines, a trader can elevate their analysis from a one-dimensional process to a multi-dimensional, context-aware methodology.
Chapter 6: The Workflow—A Step-by-Step Guide to Practical Application
Step 1: The Pre-Market Analysis (Mapping the Battlefield). Before your session begins, enable the HTF FVG detection. Identify the key, unfilled HTF FVGs above and below the current price. These are your major points of interest for the day—your potential targets and reversal zones.
Step 2: Await the Primary Condition (Patience for Liquidity). During your trading session, your primary focus should be on the "Entries Simplified" engine. Your job is to wait patiently for the script to identify a valid HTF liquidity sweep. Do not force trades in the middle of a price range where no significant liquidity has been taken.
Step 3: The Upshift/Downshift Alert (The Call to Action). When the red or green arrow from the "Entries Simplified" engine appears, it is your cue to focus your attention. This is a potential high-probability setup.
Step 4: The Confluence Check (Building Conviction). With the Upshift or Downshift signal on your chart, ask the key confluence questions:
Did the displacement from the Upshift/Downshift create a new FVG?
Is the projected path of the trade heading towards a pre-identified HTF FVG?
Has an FVG Tap-In signal appeared shortly after the initial signal, offering further confirmation?
Step 5: Execute and Manage. If you have sufficient confluence, execute the trade. Use the automated price projections as your guide for profit-taking. A logical stop-loss is typically placed just beyond the high or low of the liquidity sweep that initiated the entire sequence.
Chapter 7: The Trader's Mind—Mastering the Institutional Mindset
This tool is more than a set of algorithms; it is a training system for professional trading psychology.
From Chasing to Trapping: You stop chasing breakouts and instead learn to identify where others are being trapped.
From FOMO to Patience: The strict, sequential logic of the entry model (Sweep -> Upshift/Downshift) forces you to wait for the highest quality setups, curing the Fear Of Missing Out.
Probabilistic Thinking: By focusing on liquidity and imbalances, you begin to think in terms of probabilities, not certainties. You understand that you are putting on trades where the odds are statistically in your favor, which is the cornerstone of any professional trading career.
Clarity and Confidence: The clear, rules-based signals remove ambiguity and second-guessing. This builds the confidence needed to execute trades decisively when the opportunity arises.
Chapter 8: Frequently Asked Questions & Scenarios
Q: The "Entries Simplified" code looks complex. Do I need to understand all of it?
A: No. The engine is designed to perform its complex analysis in the background. Your job is to understand the principles—liquidity sweep and the resulting Upshift or Downshift—and to recognize the clear arrow signals that the script generates when those conditions are met.
Q: Can I turn one of the engines off?
A: Yes, the indicator is modular. If you only want to focus on Fair Value Gaps, for example, you can disable the plot shapes for the "Entries Simplified" signals in the settings, and vice-versa.
Q: Does this work on all assets and timeframes?
A: The principles of liquidity and imbalance are universal and apply to all markets, from cryptocurrencies to forex to indices. The fractal nature of the analysis means the concepts are valid on all timeframes. However, it is always recommended that a trader backtest and forward-test the tool on their specific instrument and timeframe of choice to understand its unique behavior.
Author's Instructions
To request access to this script, please send me a direct private message here on TradingView.
Alternatively, you can find more information and contact details via the link on my profile signature.
Please DO NOT request access in the Comments section. Comments are for questions about the script's methodology and for sharing constructive feedback.
