Forecasting volatility in commodity markets

Abstract This paper uses recent advances in time‐series modeling to derive long‐horizon forecasts of commodity price volatility which incorporate investors' expectations of volatility. Our results are promising. We compare several different forecasts of commodity price volatility, which we divide into three categories: (1) forecasts using only expectations derived from options prices; (2) forecasts using only time‐series modeling; and (3) forecasts which combine market expectations and time‐series methods. The forecasts in (1) and (2) are used extensively in the literature, while those in (3) are new in this paper. On comparing these different forecasts, we find that our proposed forecasts from category (3) outperform both market expectations forecasts and time‐series forecasts. This result holds both in and out of sample for virtually all commodities considered.