期刊名称：International Journal of Economics and Finance
印刷版ISSN：1916-971X
电子版ISSN：1916-9728
出版年度：2014
卷号：2
期号：1
页码：51
DOI：10.5539/ijef.v2n1p51
语种：English
出版社：Canadian Center of Science and Education
摘要：In this paper, we aim at comparing semi-parametric method, LSSVM (Least square support vector machine), with the classical GARCH(1,1), EGARCH(1,1) and GJR(1,1) models to forecast financial volatilities of three major ASEAN stock markets. More precisely, the experimental results suggest that using hybrid models, GARCH-LSSVM, EGARCH-LSSVM and GJR-LSSVM provides improved performances in forecasting the leverage effect volatilities, especially during the recently global financial market crashes in 2008.
