The purpose of this paper is to investigate volatility spillovers between crude oil futures returns and oil company stock returns by using the recent multivariate GARCH model, namely the CCC of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003) and VARMA-AGARCH model of McAleer, et al. (2008). This paper investigates the WTI crude oil futures returns and stock returns of ten oil companies; which are composed of the “supermajor” group of oil companies, namely Exxon Mobil (XOM), Royal Dutch Shell (RDS), Chevron Corporation (CVX), ConocoPhillips (COP), BP (BP) and Total S.A. (TOT), and other large oil and gas companies in the world, namely Petrobras (PBRA), Lukoil (LKOH), Surgutneftegas (SNGS), and Eni S.p.A. (ENI). The empirical results present conditional correlation between WTI crude oil futures returns and very low returns in stock of the CCC model oil company. Surprisingly, for the VARMA-GARCH and VARMA-AGARCH models, no volatility spillover effects are observed in every pairs of return series. The paper also presents the evidence of asymmetric effect of negative and positive shock on conditional variance in every pairs of return series.

Additional Metadata
Keywords Asymmetries, Crude oil futures returns, Multivariate GARCH, Oil company stock returns, Volatility spillovers
JEL Time-Series Models; Dynamic Quantile Regressions (jel C22), Time-Series Models; Dynamic Quantile Regressions (jel C32), Financial Forecasting (jel G17), Financing Policy; Capital and Ownership Structure (jel G32), Energy and the Macroeconomy (jel Q43)
Persistent URL hdl.handle.net/1765/127850
Conference 18th World IMACS Congress and International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, MODSIM 2009
Citation
Tansuchat, R, McAleer, M.J, & Chang, C-L. (2020). Volatility spillovers between crude oil futures returns and oil company stock returns. In 18th World IMACS Congress and MODSIM 2009 - International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, Proceedings (pp. 1356–1362). Retrieved from http://hdl.handle.net/1765/127850