An empirical investigation of the volatility spillovers among agricultural commodity markets around news surprises

Abstract

Purpose -- the objective of this thesis is to empirically test the level of interdependence across commodity markets in terms of return volatility spillover, namely, corn, wheat, soybeans and soybeans oil, and to uncover the impact of macroeconomic announcements on the measurement of integration among those commodities. This will help us to investigate the extent to which different agricultural commodities can be considered as an asset class and to determine whether portfolio diversification across different agricultural commodities can still lead to risk reduction benefits, in light of the recent liberalization and financialization. Design/methodology/approach -- this thesis applies the modified iterative cumulative sum of squares (ICSS) algorithm to detect structural breaks in the return variance of four selected agricultural commodities. Then, the detected break points as well as the macroeconomic announcement surprises are incorporated in a GARCH (1, 1) process to model the variance of commodity returns. The resulting variances are then combined in a simultaneous agricultural commodity markets as well as the impact of news surprises. Findings -- There is significant evidence of bidirectional volatility spillovers across major agricultural commodity markets. Particularly, it seems that there is more spillover from soybeans and soybean oil markets, to corn and wheat markets, rather than the inverse. In addition, a news surprise originating in the economy has strong impact on the variance of agricultural commodities. Research limitations -- Given the restricted timeframe provided for the thesis completion, the sample size of commodities is restricted to 3,865 observations per variable. This is mainly due to the lack of available data for a common time span, especially for the macroeconomic variables that were only available on a monthly frequency. Practical implications -- the empirical findings of this study have important implications on portfolio diversification and risk management practices. With the recent financialization of commodity markets, investors worldwide are finding it easier to access funds, seek new investment opportunities and follow innovative hedging strategies. However, the results of this dissertation constitute a perfect proof that there is risk proliferation and volatility transmission among agricultural commodity markets. Yet, a thorough examination of the level of integration of those commodities while taking into account the timing of economic surprises could result in portfolio risk reduction. Originality/value -- this thesis uses an innovative combination of econometric tools –the ICSS, GARCH (1, 1) and 3SLS models, in order to examine cross-market volatility spillovers with structural breaks, around macroeconomic news announcements. While most researchers have concentrated their analyses on few macroeconomic release announcements, our research finds that an aggregated index of 39 U.S. data surprises can act as an ideal proxy for economic surprises.