Price Volatility Dependence Structure Change Among Agricultural Commodity Futures Due to Extreme Event: An Analysis with the Vine Copula

Abstract

Since the COVID-19 spreads, global food prices have continued to rise and become more volatile because of food security panic, global food supply chain disruption, and unfavorable weather conditions for cultivation. This paper aims to study and compare the dependence structure in price volatility among agricultural commodity futures before and during the COVID-19 pandemic, with different vine copulas, namely the R-vine, C-vine, and D-vine. The daily closing prices of the agricultural commodity futures are used in the investigation, including Corn, Wheat, Oat, Soybean, Rice, Sugar, Coffee, Cocoa, and Orange, traded in the Chicago Board of Trade (CBOT) from January 2016 to July 2021. The conditional volatilities were estimated using the best fit GARCH model with the student-t distribution. The empirical results highlight the dependence structures captured by the C-vine, D-vine, and R-vine copula-based models before and during the COVID-19 pandemic. Although the C-vine copula structures of the two different periods are unchanged, the details of the copula family in such a structure differ. In the case of D-vine and R-vine copulas, the details of the copula families and their vine structures of two different periods are significantly different, meaning that COVID-19 impacts the price volatility dependence structure among the agricultural commodity futures examined. Based on the AIC, the most appropriate dependence structure for pre-COVID-19 period is the C-vine copula, while the during-COVID-19 period is the D-vine copula. The dependence structure of agricultural commodity futures prices can be used in other risk analysis and management methods such as value at risk (VaR), portfolio optimization, and hedging.