Asymmetric Commodity Tails and Index Futures Returns

Abstract

This paper proposes that the tail risk associated with commodity futures returns performs well at predicting the S&P 500 index futures returns in- and out-of-sample, even after controlling business cycles, economic factors, investor sentiment factors, other forms of tail risk factors, and macroeconomic conditions. Following Kelly and Jiang (2014), we directly estimate the commodity tail risk factor from the cross-section of commodity futures returns, which can efficiently capture the prevailing level of tail risk in the cross-sectional distribution. Our empirical analysis involves forecasting regressions, which aim to predict index futures returns using lagged up-tail risk, down-tail risk, and overall tail risk. We uncover asymmetric forecasting power between up-tail risk and down-tail risk, highlighting their distinct influences. Notably, our return decomposition analysis shows that the commodity tail risk factors primarily drive index futures returns through the discount rate channel.