BTC Strategy Institutional Multi-Factor Engine

This indicator is designed to bring an institutional grade analytical framework to Bitcoin trading by synthesizing technical price action with deeper market drivers such as Open Interest, volume flow, and macro correlations. Unlike standard indicators that often rely on a single metric, this tool employs an ensemble Machine Learning engine that aggregates and weights various factors ranging from momentum and mean reversion to cross-market data to generate high-probability entry signals. To ensure these signals remain robust against typical crypto volatility, the raw data is processed through an adaptive Kalman Filter rather than traditional moving averages, providing a significantly clearer view of the true underlying trend.

What distinguishes this tool is its built in paper trading simulation engine. While it functions technically as an indicator, it actively tracks hypothetical trade execution in the background to display real time performance metrics such as Win Rate, Profit Factor, and Drawdown directly on the dashboard, giving you immediate insight into the strategy's current effectiveness without needing to run a separate backtest. The system also integrates advanced risk management modules, including a Liquidation Cascade detection system that temporarily blocks signals during violent sell-offs to prevent catching "falling knives," as well as dynamic signal thresholds that automatically adjust based on market stress. By further contextualizing price action within the 4-year halving cycle and filtering out low-liquidity weekend noise, this strategy aims to align short-term execution with the broader market regime, offering a complete, data-driven trading system in a single chart overlay.