This paper analyzes the degree of dynamic connectedness between energy and metal commodity prices in the pre and post-COVID-19 era, using the time-varying parameter vector autoregressive connectedness approach of Antonakakis et al. (J Risk Financ Manag 13(4):84, 2020). The results suggest that...

This paper uses the Markov-switching multifractal (MSM) model and generalized autoregressive conditional heteroscedasticity (GARCH)-type models to forecast oil price volatility over the time periods from January 02, 1875 to December 31, 1895 and from January 03, 1977 to March 24, 2014. Based on...

Information on economic policy uncertainty (EPU) does matter in predicting oil returns especially when accounting for omitted nonlinearities in the relationship between these two variables via a time-varying coefficient approach. In this work, we compare the forecastability of standard, Bayesian...

This paper examines the propagation of oil price uncertainty shocks to real equity prices using a large-scale Global Vector Autoregressive (GVAR) model of 26 advanced and emerging stock markets. The GVAR framework allows us to capture the transmission of local and global shocks, while...

We contribute to the literature on the international propagation of uncertainty shocks with a Global Vector Autoregressive (GVAR) model that quantifies the spillover effects of uncertainty shocks in the US on to real equity prices of 32 advanced and emerging countries (besides the US). In this...