首页 | 本学科首页   官方微博 | 高级检索  
     检索      


A non-linear time series approach to modelling asymmetry in stock market indexes
Authors:Alessandra Amendola  Giuseppe Storti
Institution:(1) Dipartimento di Scienze Economiche e Statistiche, Università di Salerno, Via Ponte Don Melillo, 84084 Fisciano (SA), Italy
Abstract: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.
Keywords:Constrained Changing Parameters Volatility model  TAR  Leverage effect  EM algorithm
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号