High-frequency volatility connectedness and time-frequency correlation among Chinese stock and major commodity markets around COVID-19

This study examines the connectedness and time-frequency correlation of price volatility across Chinese stock market major commodity markets. paper applies a DCC-GARCH-based model cross-wavelet transform to examine transmission risk patterns in these markets before during COVID-19 outbreak, as well leading lag relationship synergistic movements between different time domains. First, findings DCC-GARCH show dynamic total spillovers are stronger after outbreak. stocks corn have been net system throughout sample period, but plays role receiver relative other (net pairwise directional connectedness) whole. In terms wavelet results, there is some connection with all markets, except soybeans wheat, showing significant dependence on equities medium/long term following Secondly, medium-to long-term frequency crude oil copper highly dependent market, especially Meanwhile, main source for while wheat sends least shocks market. The this will direct impact number important decisions made by investors policymakers.