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AI Volume-KNN SuperTrend - by Trading Pine Lab
🇬🇧 English
The AI Volume-KNN SuperTrend is an advanced trading strategy that combines the robustness of the SuperTrend indicator with a machine-learning inspired KNN (K-Nearest Neighbors) model. The baseline is built from a volume-weighted moving average with ATR-based bands, while the KNN classifier validates trend direction in real time. This dual-layer approach reduces false signals and improves trend confirmation.
Entries are triggered when the SuperTrend flips direction and the KNN classifier confirms the move as bullish or bearish. Exits are managed with a dynamic trailing stop, automatically adjusting to SuperTrend ± ATR × factor. The strategy includes visual markers for AI start/continuation signals, as well as customizable coloring for bullish, bearish, and neutral phases.
All parameters are fully configurable:
-Trading direction filter: Long / Short / Both.
-KNN settings: number of neighbors (K), dataset size (N).
-Label smoothing: price and SuperTrend smoothing lengths (WMAs).
-SuperTrend settings: length, ATR factor, and moving average source.
-Visualization: trend markers and per-trend coloring.
The AI Volume-KNN SuperTrend is an advanced trading strategy that combines the robustness of the SuperTrend indicator with a machine-learning inspired KNN (K-Nearest Neighbors) model. The baseline is built from a volume-weighted moving average with ATR-based bands, while the KNN classifier validates trend direction in real time. This dual-layer approach reduces false signals and improves trend confirmation.
Entries are triggered when the SuperTrend flips direction and the KNN classifier confirms the move as bullish or bearish. Exits are managed with a dynamic trailing stop, automatically adjusting to SuperTrend ± ATR × factor. The strategy includes visual markers for AI start/continuation signals, as well as customizable coloring for bullish, bearish, and neutral phases.
All parameters are fully configurable:
-Trading direction filter: Long / Short / Both.
-KNN settings: number of neighbors (K), dataset size (N).
-Label smoothing: price and SuperTrend smoothing lengths (WMAs).
-SuperTrend settings: length, ATR factor, and moving average source.
-Visualization: trend markers and per-trend coloring.
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受保護腳本
此腳本以閉源形式發佈。 不過，您可以自由使用，沒有任何限制 — 點擊此處了解更多。
免責聲明
這些資訊和出版物並非旨在提供，也不構成TradingView提供或認可的任何形式的財務、投資、交易或其他類型的建議或推薦。請閱讀使用條款以了解更多資訊。