Mean Reversion is a quantitative strategy based on the statistical principle that asset prices eventually return to their historical average. To measure this with precision, analysts utilize the Z-Score, a metric that indicates how many standard deviations a current price is from its mean (typically the VWAP or a moving average). When the Z-Score reaches extreme levels, such as +2sigma or -3 sigma, it signals that the market is statistically overextended. This data-driven approach removes emotional bias, allowing for a systematic assessment of when a trend is losing momentum and is likely to revert, providing a high-conviction framework for identifying exhaustion points and potential reversals.