A mean reversion strategy is a trading approach that assumes prices will revert to their historical average after deviating significantly. Traders identify overbought or oversold conditions using statistical tools like the Z-score, RSI, or Bollinger Bands, then take positions expecting a return to the mean. This strategy performs best in non-trending, range-bound markets and often involves counter-trend entries. It requires careful timing, as prices can remain extended longer than expected. Risk management is critical, including stop-loss orders to limit losses if the trend continues. Mean reversion strategies are favored by quantitative traders for their mathematical foundation and are often automated using algorithms to detect deviations with precision.