This paper assesses the roles of various factors influencing the volatility of crude oil prices and the possible linkage between this volatility and agricultural commodity markets. Stochastic volatility models are applied to weekly crude oil, corn, and wheat futures prices from November 1998 to January 2009. Model parameters are estimated using Bayesian Markov chain Monte Carlo methods. The main results are as follows. Speculation, scalping, and petroleum inventories are found to be important in explaining oil price variation. Several properties of crude oil price dynamics are established, including mean-reversion, a negative correlation between price and volatility, volatility clustering, and infrequent compound jumps. We find evidence of volatility spillover among crude oil, corn, and wheat markets after the fall of 2006. This could be largely explained by tightened interdependence between these markets induced by ethanol production.
This working paper was published as Du, Xiaodong, Cindy L. Yu, Dermot J. Hayes, "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," Energy Economics 33 (2011): 497–503, doi:10.1016/j.eneco.2010.12.015.
Du, Xiaodong; Yu, Cindy L.; and Hayes, Dermot J., "Speculation and Volatility Spillover in the Crude Oil and Agricultural Commodity Markets: A Bayesian Analysis" (2009). CARD Working Papers. 531.