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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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保護スクリプト
このスクリプトのソースコードは非公開で投稿されています。 無料かつ制限なしでご利用いただけます ― 詳細についてはこちらをご覧ください。
免責事項
これらの情報および投稿は、TradingViewが提供または保証する金融、投資、取引、またはその他の種類のアドバイスや推奨を意図したものではなく、またそのようなものでもありません。詳しくは利用規約をご覧ください。