Backtesting vs Feature Store

Backtesting is the process of running a trading strategy's logic against historical price data to produce a statistical performance estimate before committing any real capital to live deployment.

A centralized infrastructure system that manages the computation, storage, and serving of machine learning features—derived market data like moving averages, volatility metrics, and on-chain indicators—enabling consistent feature availability for model training and live trading prediction.