Volatility Targeting and Its Trade-offs in Trend-Following Returns

Summary

The document considers whether volatility targeting improves a trend-following strategy. Its motivating example is a long position that gains as price rises but is reduced because the position’s risk has increased. The author notes that trend following often has frequent small losses and occasional large gains, which may occur when other asset classes are under stress; reducing exposure during a rising trend could therefore affect the strategy’s payoff shape.

The empirical comparison uses account curves and monthly return distributions with and without volatility targeting. Because histories are short for many instruments, the procedure estimates volatility from the first four years and backfills that value, then uses a very slow moving average with a 30-year half-life thereafter. The reported comparison associates targeting with higher skew but worse kurtosis and a substantially lower Sharpe ratio. The author cautions that skew differences may depend on one or two outliers and says the apparent skew improvement does not produce a better right tail. The excerpt provides no detailed sample composition or chart values, so the findings should be treated as a limited empirical comparison rather than a universal conclusion.

Key ideas

• Volatility targeting reduces position size when estimated risk rises, potentially cutting exposure during profitable trends.
• Trend following can combine many small losses with occasional large gains, making the return distribution important.
• The comparison uses a backfilled initial volatility estimate and then a very slow moving average.
• The reported results show lower Sharpe and worse kurtosis with targeting, despite an apparent increase in skew.
• Outliers may strongly affect skew estimates, and the excerpt does not provide enough detail to generalize the findings.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.