Volatility spillovers for spot, futures, and ETF prices in agriculture and energy
The agricultural and energy industries are closely related, both biologically and financially. The paper discusses the relationship and the interactions on price and volatility, and on the covolatility spillover effects for these two industries. The interaction and covolatility spillovers, or the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset, between the energy and agricultural industries is the primary emphasis of the paper. Although there has already been significant research on biofuel and biofuel-related crops, only a few published papers have been concerned with volatility spillovers. It must be emphasized that there have been numerous technical errors in the theoretical and empirical research, which need to be addressed. The paper considers futures prices as a widely-used hedging instrument, and also considers an interesting new hedging instrument, ETF, which is regarded as index futures when investors manage their portfolios. In the empirical analysis, multivariate conditional volatility diagonal BEKK models are estimated for comparing patterns of covolatility spillovers. The paper provides a new way of analyzing and describing the patterns of covolatility spillovers, which should be useful for the future empirical analysis of estimating and testing covolatility spillover effects.
|Keywords||Biofuels, Covolatility spillovers, Energy and agriculture, Exchange traded funds, Futures prices, Optimal dynamic hedging, Spot prices|
|JEL||Time-Series Models; Dynamic Quantile Regressions (jel C32), Financial Econometrics (jel C58), Contingent Pricing; Futures Pricing (jel G13), Agricultural Finance (jel Q14), Alternative Energy Sources (jel Q42)|
|Persistent URL||dx.doi.org/10.1016/j.eneco.2019.04.017, hdl.handle.net/1765/117293|
|Series||VSNU Open Access deal|
Chang, C-L, Liu, C.-P. (Chia-Ping), & McAleer, M.J. (2019). Volatility spillovers for spot, futures, and ETF prices in agriculture and energy. Energy Economics, 81, 779–792. doi:10.1016/j.eneco.2019.04.017