Use of implied volatility index to study spillovers between oil and stock market prices with structural breaks

The Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH) model has been widely used for studying the relationships between oil prices and stock market volatility. In the presence of heteroscedasticity, the standard errors and confidence intervals estimated by traditional methods may lead to a false sense of precision. It is known that structural breaks attributed tounexpected political or economic influences play an important role in altering the historic market volatility in financial markets. The authors have observed the existence of one-way volatility effects from the crude oil market to the American stock market, while there is no evidence of such effects for the Chinese market. Other research on spillover effects has demonstrated that volatility dynamics can be overestimated using the historic volatility index. In this paper, we propose to use the implied volatility index to examine the spillover effects because this index can reflect the market expectation for future volatility, regarding both the realized volatility and future returns. The index implicitly includes the understanding of stakeholders’ views on historic volatility and expected returns, and provides realistic reflection of the market volatility trends. We employ the crude oil volatility index and the stock volatility index created by the Chicago Board Options Exchange for testing the time-varying GARCH model for the period of 2008-2018. The spill-over effects are quantified for pre- and post-periods of structural breaks, and the dynamics of oil and stock markets are examined in the presence of structural breaks. This research makes a new contribution to the literature by providing a unique approach to better understanding the market volatility caused by structural breaks.