Mean-Reversion Volatility Filters

Due to the result’s of this MarketSci post, which imply that short-term mean reversion performs better during low volatility versus high volatility, I decided to revisit volatility filters. In Mean-Reversion within Regimes, I previously concluded that high volatility, not low volatility was more conducive to mean-reversion strategies. To test for low volatility/high volatility I decided to use a different filter. Last time I used a static test (60-Day Historical Volatility > 0.01 = High Volatility, <0.01 = Low Volatility). This time I will use a more dynamic filter, which compares short-term volatility to mid-term volatility.

Results

• Testing on SPY from 1/1/1995- 4/28/2013

IBS

Rules (Base-Case):

• Buy if 3-Day IBS < 40
• Sell if 3-Day IBS > 40
• Avg. Trade: 0.56%

Rules (High Vol):

• Buy if 3-Day IBS < 40 AND HV(5) > HV(20) 
• Sell if 3-Day IBS > 40
• Avg. Trade: 0.39%

Rules (Low Vol):

• Buy if 3-Day IBS < 40 and HV(5) < HV(20)
• Sell if 3-Day IBS > 40
• Avg. Trade: 0.68%

RSI

Rules (Base-Case):

• Buy if 2-Day RSI< 50
• Sell if 2-Day RSI > 50
• Avg. Trade: 0.32%

Rules(High Vol):

• Buy if  2-Day RSI< 50 and HV(5) < HV(20)
• Sell if 2-Day RSI > 50
• Avg. Trade: 0.27%

Rules(Low Vol);

• Buy if  2-Day RSI< 50 and HV(5) < HV(20)
• Sell if 2-Day RSI > 50
• Avg. Trade: 0.37%

Conclusion

It seems from this, in combination with my previous conclusion from Mean-Reversion within Regimes, that the specific filter used for volatility has a large influence on profitability. One thing I realized is that there may be different exposures for low vol vs high vol (meaning that a high volatility filter may allow for more trades, resulting in a higher CAGR) which could result in the discrepancy in results (that is why I used Avg. Trade rather than CAGR this time), but even after re-running the different tests under the same conditions, high vol had a higher Avg. Trade vs low vol.