Conditional correlations and volatility spillovers between crude oil and stock index returns

By Chia‐Lin Chang, Michael Mcaleer, Roengchai Tansuchat. 2010

238 citations recorded by the source corpus.

This paper investigates the conditional correlations and volatility spillovers between the crude oil and financial markets, based on 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 stock 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.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/310d889d41cc343f794fffd7394273bf3133a6e3

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Citations in the corpus

Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries (2016, unknown): “…between the oil and stock market returns is indeed dynamic (see, Aloui and Jammazi, 2009; Choi and Hammoudeh, 2010; Bharn and Nikolovann, 2010; Filis et al., 2011; Broadstock et al., 2012; Sadorsky, 2012; Broadstock and Filis, 2013; Chang et al., 2013; Antonakakis and Filis, 2013; Filis, 2014).”
Oil shocks and their impact on energy related stocks in China (2012, unknown): “There are alternative approaches, for example Chang et al. (2011) examine the performance of several multivariate volatility models using crude oil spot and future returns including the DCC model. They showed that the diagonal BEKK method provided the highest `hedge effectiveness' (noting the contex”
Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH ☆ (2015, unknown): “2 There is a large and growing literature looking at the volatility dynamics between equities and various commodities (eg. Malik and Hammoudeh, 2007; Malik and Ewing, 2009; Hakem and McAleer, 2010; Filis et al, 2011; Chang et al., 2013; Mollick and Assefa, 2013; Hwan et al., 2013; Guesmi and Fattoum”
The contagion effect of international crude oil price fluctuations on Chinese stock market investor sentiment (2017, background): “[3], Broadstock and Filis [4], Kang et al.”
Oil volatility, oil and gas firms and portfolio diversification (2018, background): “Nevertheless, the focus is either on aggregate stock market data or industrial sectors (see, among others, Choi and Hammoudeh, 2010; Filis et al., 2011; Broadstock et al., 2012; Chang et al., 2013; Degiannakis et al., 2013; Antonakakis and Filis, 2013; Broadstock and Filis, 2014; Filis, 2014).”
Oil shocks and stock markets: dynamic connectedness under the prism of recent geopolitical and economic unrest (2017, unknown): “By contrast, Chang et al. (2013) do not report any volatility spillover effects between the oil market and key global stock market indices (FTSE100, Dow Jones, NYSE and S&P500).”
Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression (2017, background): “Despite the increased interest in the oil-stock relationships, there are relatively few papers that investigate the time-varying relationships between them (e.g., Chang et al., 2013; Broadstock and Filis, 2014; Joo and Park, 2017).”
Dynamic correlation between stock market and oil prices: The case of oil-importing and oil-exporting countries (2011, unknown): “Chang et al. (2010) based on a symmetric DCC-GARCH model also investigated the conditional correlations and volatility spillovers between crude oil (WTI and Brent markets) and FTSE100, NYSE, Dow Jones and S&P500 stock indices.”
Interpreting the crude oil price movements: Evidence from the Markov regime switching model (2015, methodology): “[11] The CCC model, VARMA-GARCH model, VARMA-AGARCH model and DCC model There is no evidence to support assumptions of constant conditional correlations, and there is little evidence of volatility spillovers between crude oil and financial markets through the VARMA-GARCH and VARMA-AGARCH models Fan ”