Quantile frequency connectedness between crude oil volatility, geopolitical risk and major agriculture and livestock markets

Abstract

ABSTRACT This article investigates the quantile frequency risk connectedness between the global geopolitical risk (GPR) index, the CBOE Crude Oil Volatility Index (OVX), and the major agricultural and livestock indexes using a quantile vector autoregression (QVAR)-based frequency connectedness approach. The empirical results suggest that spillover effects are higher in extreme market conditions than in normal market conditions. The GPR has a more significant impact on other markets in the long-term domain of extreme market conditions. Moreover, grain markets are the primary transmitters of spillovers, while OVX predominantly assumes the role of a net receiver of risk spillover effects in most instances. Meanwhile, although the spillover structure between frequencies is homogeneous at the same quantile level, the connection between major agricultural and livestock index markets and two uncertainty indexes is time-varying, and spillovers are heterogeneous at different quantile levels. Our research provides investors and policymakers with new understandings of the development of differentiated crude oil volatility and geopolitical risk aversion strategies under different market conditions, given the heterogeneity of volatility spillover connectedness under different market conditions and frequency domains.