Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach

This paper shows the effects of COVID-19 pandemic on energy markets. We estimate daily volatilities and correlations among commodities relying a mixed-frequency approach that exploits information from number weekly deaths related to in United States. The takes advantage MIxing-Data Sampling (MIDAS) methods. compare our results those obtained by employing two well-known models do not account for low-frequency variable, namely Dynamic EquiCorrelation (DECO) corrected Conditional Correlation (cDCC). Moreover, we consider four possible specifications volatility: GARCH, GJR, GARCH-MIDAS, Double-Asymmetric GARCH-MIDAS. empirical show is statistically superior other represents valuable methodology can be used risk managers, investors, policy makers assess spillovers