ML Adaptive SuperTrend MT5
- Indicators
- Duc Hoan Nguyen
- Version: 2.10
- Updated: 27 February 2025
- Activations: 10
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Unlock the power of advanced machine learning with the Machine Learning Adaptive SuperTrend, a cutting-edge indicator designed to seamlessly adapt to changing market conditions. By integrating k-means clustering with the SuperTrend methodology, this indicator enables precise trend identification and volatility assessment, giving traders an invaluable advantage in dynamic markets.
See more MT4 version at: Machine Learning Adaptive SuperTrend MT4
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Precision with Machine Learning and Adaptive SuperTrendThis indicator is engineered to adapt based on real-time market data, categorizing volatility into three levels—high, medium, and low. Using k-means clustering, it classifies ATR (Average True Range) values into clusters, allowing for a more responsive and tailored SuperTrend calculation that aligns with current market sentiment.
Key Features- Customizable Visuals: Adjust colors for bullish and bearish trends to enhance chart readability and focus.
- Flexible Parameter Settings: Control ATR length, SuperTrend factor, and initial volatility estimates to suit specific trading strategies.
- Adaptive Volatility Clustering: Dynamically categorizes volatility to optimize SuperTrend calculations in real-time.
- Alerts: Set notifications for trend shifts and volatility changes, enabling proactive trade management.
- Data Table Insights: View real-time data on cluster centroids, sizes, and current volatility levels directly on the chart, providing essential information at a glance.
- Setup and Personalization: Add the indicator and configure settings such as ATR length and SuperTrend factors. Adjust volatility percentiles to align with specific trading preferences.
- Market Monitoring: Observe color changes and SuperTrend line movements to identify trend reversals. The data table displays real-time volatility clusters, offering clear insights into market conditions.
- Stay Notified: Enable alerts for trend shifts and volatility changes, allowing for prompt responses without needing constant chart observation.
The indicator starts by calculating ATR values over a defined training period to assess market volatility. Using initial estimates for high, medium, and low volatility levels, the k-means clustering algorithm iteratively refines these categories, enabling accurate volatility classification. As market conditions evolve, the indicator continuously adjusts, providing up-to-date insights on trend and volatility. The data table also presents vital details, including cluster centroids and sizes, to support informed trading decisions.
The Machine Learning Adaptive SuperTrend offers a sophisticated approach to trend analysis, designed to adapt dynamically to market changes and provide deeper insights for traders aiming to refine their strategies.