A multi-factor trading strategy that combines technical momentum analysis with machine learning to identify high-probability entry points across cryptocurrency exchanges. The approach uses a dual-signal confirmation system that blends rule-based indicators with a lightweight ML classifier trained on historical price patterns, while simultaneously monitoring cross-exchange pricing inefficiencies for statistical arbitrage opportunities. Built with conservative parameters and a train-once methodology to minimize overfitting, the strategy employs adaptive risk management through dynamic stop-losses and operates on daily timeframes with hourly execution checks. The hybrid design balances interpretability with predictive power, making it suitable for systematic backtesting and potential live deployment. GPT'ed this paragraph btw cuz can't give out alpha.