 Explosive volatilities for threshold-GARCH processes generated by asymmetric innovationsS.Y. Hwang, J.S. Baek, J.A. Park and M.S. Choi Statistics & Probability Letters, 2010, vol. 80, issue 1, 26-33 Abstract: The threshold-asymmetric GARCH (TGARCH, for short) models have been useful for analyzing asymmetric volatilities arising mainly from financial time series. Most of the research on TGARCH has been directed to the stationary case. In this article, motivated by unstable features in recent time series in Korea amid worldwide financial crisis, we introduce "explosive volatilities" in TGARCH processes. The term of explosive volatility in TGARCH context is defined and is justified. Moreover, asymmetric innovations such as normal mixtures are considered in modeling explosive TGARCH and hence we are concerned with a class of explosive TGARCH models generated by asymmetric innovations. Assuming normal mixture innovations, maximum likelihood (ML) estimation method is discussed and procedures for computing ML-estimates are described. To illustrate, exchange rate data of Korea-Won to US dollars are analyzed and it is observed that the data exhibit a certain explosive volatility and in turn, our model performs better than various competing models. Date: 2010 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:80:y:2010:i:1:p:26-33 Ordering information: This journal article can be ordered from Access Statistics for this article Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul More articles in Statistics & Probability Letters from Elsevier |
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