Statistical Arbitrage is a trading strategy that uses mathematical models to identify price discrepancies between related financial instruments. Traders analyze historical price data to predict future movements, aiming to profit from short-term price inefficiencies. This approach often involves high-frequency trading and relies on algorithms to execute trades quickly. The strategy typically involves pairs trading, where two correlated assets are bought and sold simultaneously. When the price relationship deviates from the historical norm, traders take positions expecting the prices to converge again. This method is popular among hedge funds and institutional investors seeking to capitalize on market inefficiencies.