Dynamic volatility behaviour in agricultural commodity markets: Evidence from VIRF analysis and spillover index calculations

This paper provides an empirical analysis of volatility time structures in agricultural markets (sugar, wheat, soybeans and coffee) for a time period from 2008 to 2016. The time period covers at least three food crises which make the analysis interesting for both researches and policy makers. In order to investigate the behaviour of agricultural market's volatility after a shock, I calculated the volatility impulse response function based on a VAR(1) BEKK(1,1)-in-mean model. The result indicates that extreme weather events do have large impact on volatility. Furthermore, with the application of the spillover index, it is possible to calculate the quantity of volatility spillovers across time. There is evidence for a high news sensitiveness in certain agricultural products and a dominant position of wheat and soybeans.