Extreme Events and the Oil Market: Conditional Jump Process

Abstract

Purpose: This research aims to analyse price movements in the oil market stimulated by extreme events such as oil platform explosions, geopolitical events, and financial crises and to understand the reaction and the persistence of these effects on the commodity’s price. Originality/value: The prominent position of oil raises the concerns of investors, producers, and policymakers because of the unstable behaviour of its price level and pattern of volatility. This justifies the need to investigate the dynamics of this behaviour for the purposes of economic policy formation, strategies around trade and costs, and revenue calculations for companies of this sector, as well as investment decisions for other sources of energy. Design/methodology/approach: In order to model the occurrence of volatility jumps caused by extreme events, four specifications were used for the ARJI-GARCH conditional jumping methodology developed by Chan and Maheu (2002). The data consist of 2008 daily records of the closing price of light oil (WTI) from January 2010 to December 2017 obtained from NYMEX. Findings: Among several results it was verified that the occurrence of extreme events causes significant changes in the oil price, which goes against the efficient market hypothesis, and that a time-varying conditional jump process can be specified, but it has little sensibility to past shocks and very short-term persistence.