Abstract

We construct a multivariate heterogeneous autoregressive model specified with common stochastic volatility and the student-t distribution, the MHAR-CSV-t model, to investigate co-movements and high-frequency volatility transmissions between the WTI futures market and China's stock and commodity futures markets. Additionally, we analyse the time-varying volatility connectedness between these markets. We find that between these markets, the WTI futures market features the most episodes of volatility spikes, particularly since 2014. We find several structural breaks in realised volatility and its decomposition in positive and negative volatility. The results of the time-varying volatility connectedness identify corn, gold, and equity futures as persistent transmitters; the copper futures market as a net receiver; and oil futures as assuming both roles in the spillovers of volatility shocks across markets. We also find significant asymmetries in their volatility decomposition and their spillovers across these markets.

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