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Normal mixture method for stock daily returns over different sub-periods

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作者:Han, LY (Han, Liyan)[ 1 ] ; Yan, HH (Yan, Hanhuan)[ 1 ] ; Zheng, CL (Zheng, Chengli)[ 2 ]

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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION

卷: 48期: 2

页: 447-457

DOI: 10.1080/03610918.2017.1383423

出版年: FEB 7 2019

文献类型:Article

摘要

In this paper, the normal mixture model, as an alternative distribution, is utilized to represent the characteristics of stock daily returns over different bull and bear markets. Firstly, we conduct the normality test for the return data and compare the Kolmogorov-Smirnov statistics of normal mixture models with different components. Secondly, we analyze the likely reasons why parameters change over different sub-periods. Our empirical examination proves that majority of the data series reject the normality assumption and mixture models with three components can model the behavior of daily returns more appropriately and steadily. This result has both statistical and economic significance.

关键词

作者关键词:Stock daily returns; Bull and bear markets; Normal mixture model; Different components

KeyWords Plus:MODELS; PRICE

作者信息

通讯作者地址:

Beihang University Beihang Univ, Sch Econ & Management, 37 Xueyuan Rd, Beijing, Peoples R China.

通讯作者地址: Yan, HH (通讯作者)

Beihang Univ, Sch Econ & Management, 37 Xueyuan Rd, Beijing, Peoples R China.

地址:

[ 1 ]‎ Beihang Univ, Sch Econ & Management, 37 Xueyuan Rd, Beijing, Peoples R China

[ 2 ]‎ Cent China Normal Univ, Sch Econ, Wuhan, Hubei, Peoples R China

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