Conditional Correlations and Volatility Spillovers Between Crude Oil and Stock Index Returns
This paper investigates the conditional correlations and volatility spillovers between crude oil returns and stock index returns. Daily returns from 2 January 1998 to 4 November 2009 of the crude oil spot, forward and futures prices from the WTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500 index returns, are analysed using the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer, Hoti and Chan (2008), and DCC model of Engle (2002). Based on the CCC model, the estimates of conditional correlations for returns across markets are very low, and some are not statistically significant, which means the conditional shocks are correlated only in the same market and not across markets. However, the DCC estimates of the conditional correlations are always significant. This result makes it clear that the assumption of constant conditional correlations is not supported empirically. Surprisingly, the empirical results from the VARMA-GARCH and VARMA-AGARCH models provide little evidence of volatility spillovers between the crude oil and financial markets. The evidence of asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances suggests that VARMA-AGARCH is superior to VARMA-GARCH and CCC.
|Keywords||conditional correlations, crude oil prices, forward and futures prices, multivariate GARCH, spot, stock indices, volatility spillovers|
|JEL||C22, Time-Series Models; Dynamic Quantile Regressions (jel), C32, Time-Series Models; Dynamic Quantile Regressions (jel), G17, Financial Forecasting (jel), G32, Financing Policy; Capital and Ownership Structure (jel)|
|Publisher||Erasmus School of Economics (ESE)|
Tansuchat, R, Chang, C-L, & McAleer, M.J. (2010). Conditional Correlations and Volatility Spillovers Between Crude Oil and Stock Index Returns (No. EI 2010-12). Report / Econometric Institute, Erasmus University Rotterdam (pp. 1–44). Erasmus School of Economics (ESE). Retrieved from http://hdl.handle.net/1765/18043