Abstract
The mechanism of risk responses to market shocks is considered as stagnant in recent financial literature, whether during normal or stress periods. Since the returns are heteroskedastic, a little consideration was given to volatility structural breaks and diverse states. In this study, we conduct extensive simulations to prove that the switching regime GARCH model, under the highly flexible skewed generalized t (SGT) distribution, is remarkably efficient in detecting different volatility states. Next, we examine the switching regime in the S&P 500 volatility for weekly, daily, 10-minute and 1-minute returns. Results show that the volatility switches regimes frequently, and differences between the distributions of the high and low volatility states become more accentuated as the frequency increases. Moreover, the SGT is highly preferable to the usually employed skewed t distribution.
•We investigate the volatility switching regimes over different frequencies.•The MS-GARCH under the SGT can remarkably detect high and normal stress regimes.•The volatility switches regimes frequently.•Distributions of the diverse states become divergent as the frequency increases.•The skewed generalized t distribution outperforms the usual skewed t distribution.