Oil shocks and stock market volatility: New evidence

This paper investigates the effect of oil shocks on U.S. stock market volatility based on a new hybrid model that combines the least absolute shrinkage and selection operator (LASSO) with the Markov regime-switching model (MS-LASSO). Considering five oil shocks, the results show that the LASSO method containing Markov regime-switching improves forecasting accuracy from the statistical and economic perspectives. These results are confirmed in robustness checks of alternative evaluation method, alternative forecasting horizons, and alternative historical years. Moreover, we find that the net price increase indicator (NPI2) is an effective oil shock, while the large price increase (LPI) has nearly no influence during the sample period. Furthermore, we find that oil shocks have time-varying performance, which highlights the importance of considering regime switching. •This paper investigates the effect of five oil shocks on the U.S. stock market volatility;•The MIDAS-LASSO and LASSO model with Markov-regime switching are better;•We investigates the forecast performance in different conditions;•Our findings offer novel insights regarding oil shock’s predictability for stock market volatility.