Cross-asset time-series momentum: Crude oil volatility and global stock markets

We examine the profitability of a cross-asset time-series momentum strategy (XTSMOM) constructed using past changes in crude oil-implied volatility (OVX) and stock market returns as joint predictors. We show that employing the past changes in OVX in addition to past stock returns helps better predict future stock market returns globally. The XTSMOM outperforms the single-asset time-series momentum (TSMOM) and buy & hold strategies with higher mean returns, lower standard deviations, and higher Sharpe ratios. The XTSMOM can also forecast economic cycles. We contribute to the literature on cross asset momentum spillovers as well as on the impacts of crude oil uncertainty on stock markets.(c) 2022 Elsevier B.V. All rights reserved.

Automated summary

This study examines the profitability of a cross-asset time-series momentum strategy constructed using past changes in crude oil-implied volatility and stock market returns as joint predictors. The results show that this strategy outperforms the single-asset time-series momentum and buy & hold strategies with higher mean returns, lower standard deviations, and higher Sharpe ratios. It can also forecast economic cycles and contributes to the literature on cross asset momentum spillovers and the impacts of crude oil uncertainty on stock markets.