Volatility estimators are a useful tool in volatility trading and risk management. We have discussed several types of volatility estimators, ranging from the simple Close-to-Close Historical Volatility to more complex ones like the Garman-Klass-Yang-Zhang volatility.

As discussed in Reference [1], volatility estimators can also be used directly in delta-one trading by Commodity Trading Advisors. The article pointed out that using a more efficient volatility estimator, specifically the Yang and Zhang volatility estimator, trading strategies’ turnover can be reduced while maintaining the same level of risk-adjusted returns. Another interesting result is that the turnover can also be improved by using a more efficient momentum indicator.

*First, we show that the turnover of the strategy can be significantly reduced with the use of more efficient volatility estimates like the ones suggested by Yang and Zhang (2000) or the use of alternative trading rules that depart from the typical binary setup (+1: long, and -1: short). The turnover gains can reach levels of up to approximately 36% (for our sample period and underlying universe), when both methodological amendments are employed, without causing a statistically significant performance penalty.*

Finally, the authors showed that including pairwise correlations in the portfolio construction also improves trading strategy performance,

*We find that the correlation-adjusted variant of the strategy outperforms its naive implementation and the outperformance is more pronounced in the post-GFC period. Importantly, the higher turnover due to dynamic leverage is fully counter-balanced when the earlier turnover reduction techniques are also employed.*

Intuitively, the role of correlation in the trading of long/short commodity portfolios is similar to that in pairs or basket trading of other asset classes.

These results have interesting implications not only in the management of volatility-target portfolios but also in trading and risk management in general.

**References**

[1] Baltas, Nick and Kosowski, Robert, *Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations*. “Market Momentum: Theory and Practice”, Wiley, 2020