A non-linear time series approach to modelling asymmetry in stock market indexes

作     者：Amendola, Alessandra Storti, Giuseppe 

作者机构：Dipartimento di Scienze Economiche e Statistiche Università di Salerno 84084 Fisciano (SA) Via Ponte Don Melillo Italy 

出 版 物：《Statistical Methods and Applications》 (Stat. Methods and Appl.)

年 卷 期：2002年第11卷第2期

页      面：201-216页

学科分类：0202[经济学-应用经济学] 02[经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 

主　　题：Constrained Changing Parameters Volatility model EM algorithm Leverage effect TAR 

摘      要：In this paper we analyse the performances of a novel approach to modelling non-linear conditionally heteroscedastic time series characterised by asymmetries in both the conditional mean and variance. This is based on the combination of a TAR model for the conditional mean with a Constrained Changing Parameters Volatility (CPV-C) model for the conditional variance. Empirical results are given for the daily returns of the S&P 500, NASDAQ composite and FTSE 100 stock market indexes. © Springer-Verlag 2002.