Portfolio Management of Commodity Trading Advisors with Volatility Targeting

Abstract

I show analytically that a volatility-targeted allocation methodology improves the risk-adjusted performance of portfolios under a broad set of assumptions regarding the serial correlation of returns, the variability of volatility and dependence of the expected Sharpe ratio on the level of volatility. I examine the impact of volatility targeting on portfolios of Commodity Trading Advisors within the large-scale simulation framework of Molyboga and L'Ahelec (2016) that accounts for the realistic constraints on institutional investors. I find a consistent and statistically significant improvement in the out-of-sample returns that ranges between 0.53% and 0.80% per annum, on average. The performance enhancement is robust to portfolio size and manager selection, and is implementable inside managed account investments.