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BINARY RANDOM POWER APPROACH TO MODELING ASYMMETRIC CONDITIONAL HETEROSCEDASTICITY  

KIM S. (Department of Statistics, Chungang University)
HWANG S.Y. (Department of Statistics, Sookmyung Women’s University)
Publication Information
Journal of the Korean Statistical Society / v.34, no.1, 2005 , pp. 61-71 More about this Journal
Abstract
A class of asymmetric ARCH processes is proposed via binary random power transformations. This class accommodates traditional nonlinear models such as threshold ARCH (Rabemanjara and Zacoian (1993)) and Box-Cox type ARCH models(Higgins and Bera (1992)). Stationarity condition of the model is addressed. Iterative least squares(ILS) and pseudo maximum like-lihood(PML) methods are discussed for estimating parameters and related algorithms are presented. Illustrative analysis for Korea Stock Prices Index (KOSPI) data is conducted.
Keywords
Asymmetric ARCH; binary random power; iterative least squares(ILS); KOSPI data; pseudo maximum likelihood(PML);
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