Mean Reversion Strategy
A statistical trading approach that capitalizes on asset price deviations from their historical average.
Overview
Mean reversion trading is based on the principle that asset prices tend to return to their average value over time. This strategy identifies and exploits temporary price deviations.
Most effective in ranging markets with clear support and resistance levels.
Key Components
Statistical Measures
- Moving Averages
Simple and exponential moving averages for trend identification
- Bollinger Bands
Standard deviation-based channels for volatility measurement
- Z-Score
Measures deviation from the mean in standard deviation units
Entry/Exit Rules
- Entry Signals
Price deviations beyond statistical thresholds
- Exit Signals
Return to mean or opposite threshold breach
- Stop Loss
Based on historical volatility measures
Configuration
Key Parameters
Lookback Period
Time window for calculating average price (default: 20 periods)
Deviation Threshold
Number of standard deviations for entry (default: 2)
Stop Loss
Percentage or volatility-based stop loss
Position Sizing
Based on account size and volatility
Risk Management
Key Considerations
- • Monitor market conditions for regime changes
- • Adjust position sizes based on volatility
- • Use correlation analysis for portfolio diversification
- • Implement time-based exit rules for non-reverting scenarios
Best Practices
- • Test strategy on different market conditions
- • Start with wider deviation thresholds
- • Use multiple timeframe analysis
- • Consider fundamental factors that might prevent mean reversion