Measuring risk spillover effects among biofuel-related financial derivatives: based on the modified CoVaR and S-vine copula methods

This paper investigates the risk spillover effects among nine biofuel-related assets across three countries. Both dependence structure and tail causal relations are studied with the stationary vine (S-vine) copula model and the quantile Granger causality test. The modified conditional value-at-risk (CoVaR) is proposed to measure the intertemporal risk spillover effects. It extends the traditional CoVaR to account for intertemporal dynamics. Comparatively, the traditional CoVaR may overestimate the risk spillover effects. The empirical results exhibit geographical clusters and potential paths of risk spillovers among biofuel-related assets. The spillover path runs from American markets to Chinese markets via the Malaysian market. American soybean oil is the risk transmitter, while Chinese palm oil is the primary risk recipient. Moreover, the spillover effects of downside risks have increased since the COVID-19. This research provides significant implications for risk management and investment in the biofuel-related markets.