Comovements and Volatility Spillover in Commodity Markets

This paper analyzes comovements and connectedness of commodity futures in the past two decades. We apply dynamic conditional correlation model (DCC) to capture time-varying dependence structure of a variety of commodities across different sectors. We propose to estimate network connectedness of commodity markets by the modeling framework of Diebold and Yilmaz (2014) that studies direction and magnitude of volatility spillover using reduced-form vector autoregression (VAR) models and generalized forecast error variance decomposition. We find that both DCC and VAR models present consistent results: while comovements and connectedness of commodity markets have dramatically increased during 2007-2009 financial distress, they have returned to the pre-crisis levels after. We also find that recent downward movement of commodity prices does not necessarily indicate stronger connection between commodity markets, which poses challenges on recent studies in commodity financialization.