The nonlinear relationship between autocorrelation and volatility: the case of the Asian financial crisis
Chiao-Yi Chang and
Fu-Shuen Shie
Applied Economics Letters, 2012, vol. 19, issue 4, 305-311
Abstract:
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.
Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/13504851.2011.576997 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:apeclt:v:19:y:2012:i:4:p:305-311
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20
DOI: 10.1080/13504851.2011.576997
Access Statistics for this article
Applied Economics Letters is currently edited by Anita Phillips
More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().