A mean reversion strategy is built on the principle that price movements tend to reverse over time, and can be developed professionally by: (1) calculating log returns from price data, (2) creating lagged auto-regression columns to predict future movements, (3) encoding direction into discrete values, (4) grouping and aggregating data to identify statistical patterns, (5) performing out-of-sample validation to ensure pattern persistence, and (6) analyzing performance metrics like win rate, expected value, and Sharpe ratio to assess strategy viability.
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