Buy stocks that have dropped significantly below their moving average and sell those trading well above. Based on the statistical tendency for prices to revert to the mean.
History
Mean reversion as a concept dates back to Francis Galton's 1886 work on 'regression to the mean' in biological systems. In finance, it was formalized by Poterba and Summers (1988) and Fama and French (1988), who found evidence that stock returns are negatively autocorrelated over long horizons. The strategy became a cornerstone of quantitative trading in the 1990s. Renaissance Technologies and DE Shaw are widely believed to exploit short-term mean reversion across multiple asset classes. The concept underpins the broader contrarian investing philosophy championed by practitioners like David Dreman.
How It Works
Monitor stocks for extreme deviations from a moving average (e.g., 20-day or 50-day SMA)
Use indicators like RSI (Relative Strength Index), Bollinger Bands, or z-scores to identify oversold/overbought conditions
Enter long positions when RSI drops below 30 or price touches the lower Bollinger Band; short when RSI exceeds 70
Set profit targets at the moving average (mean) and stop-losses at further deviation levels
Filter signals using volume confirmation, sector momentum, and volatility regimes
Works best on liquid, large-cap stocks where temporary dislocations are more likely to revert
Example Trades
AAPL drops 8% in 3 days on broad market selloff, RSI hits 22
entry Long AAPL at $168 with stop at $162
exit RSI recovers to 50, price at $178
result +5.9% in 6 trading days
MSFT trades 3 sigma above 20-day SMA after earnings euphoria
entry Short MSFT at $432 (or reduce long exposure)
exit Price reverts to 20-day SMA at $418
result +3.2% in 9 trading days
Related Charts
Who Runs This
When It Works vs. Fails
works
Range-bound, choppy markets with high volatility but no directional trend. Works well in liquid, large-cap names with stable fundamentals.
fails
Strong trending markets where momentum dominates. Financial crises where 'cheap' stocks keep getting cheaper (value traps).
Risks
01 Catching a falling knife: price drops can continue far beyond statistical expectations in genuine distress
02 Regime-dependent: mean reversion breaks down in trending markets and during momentum crashes
03 Requires precise position sizing and stop-losses to avoid catastrophic losses on the tail events
04 Transaction costs can erode thin profit margins, especially with frequent trading
Research
Mean Reversion in Stock Prices: Evidence and Implications
Poterba, Summers, 1988
Permanent and Temporary Components of Stock Prices
Fama, French, 1988
Lakonishok, Shleifer, Vishny, 1994