The literature agrees that bad news increases volatility but disagrees over the impact of good news on stock market volatility and often report it as statistically insignificant. This article shows that accounting for endogenously determined structural breaks within the asymmetric Generalized Autoregressive Conditional Heteroscedastic (GARCH) model reduces volatility persistence and good news significantly decreases volatility. However, good news does not affect volatility if structural breaks are ignored. We validate our empirical results with Monte Carlo simulations and provide an intuitive explanation for our results. Our results resolve earlier inconsistencies in the literature and have important practical implications for building accurate asset pricing models and forecasting of stock market volatility.
ASJC Scopus subject areas
- Economics and Econometrics