The nonlinear relationship between autocorrelation and volatility: the case of the Asian financial crisis

In this article we explore how autocorrelation impacts volatility in stock markets. We use the Threshold Autoregressive-Generalized Autoregressive Conditional Heteroscedasticity (TAR-GARCH) model to obtain a better approximation of the volatility pattern with the threshold of a positive or negative prior return autocorrelation. In contrast to the general regime-switching model that focuses on the mean equation or on the variance equation with prior shocks as the threshold variable, we consider the asymmetric response of volatility to the autocorrelation of stock returns and apply a nonlinear relationship between autocorrelation and volatility to refine the volatility equation. The empirical results indicate that different levels of autocorrelation are related to stock return volatility. Regardless of whether there is positive or negative correlation, the volatility increases under larger absolute values of autocorrelation both during and after the Asian financial crisis. Stock returns are observed in 10 countries before, during and after the 1997 Asian financial crisis.