基于混合分布的中国股票波动风险因素的识别与分析

doi:10.16381/j.cnki.issn1003-207x.2018.02.010

中国管理科学 ›› 2018, Vol. 26 ›› Issue (2): 86-95.doi: 10.16381/j.cnki.issn1003-207x.2018.02.010

基于混合分布的中国股票波动风险因素的识别与分析

王安兴¹, 谭鲜明²

1. 上海财经大学金融学院, 上海 200433;
2. 加拿大麦吉尔大学健康中心, 加拿大魁北克 H4A 3J1

收稿日期:2015-04-07 修回日期:2017-06-07 出版日期:2018-02-20 发布日期:2018-04-20
通讯作者: 谭鲜明(1973-),男(汉族),湖南人,加拿大麦吉尔大学健康中心,统计师,研究方向:混合模型、临床试验的设计与分析,E-mail:nktanxm@aliyun.com. E-mail:nktanxm@aliyun.com
基金资助:
国家自然科学基金委重大研究计划重点项目（91546202）

The Analysis of Chinese Stock Volatile Risk Factors based on Mixture Distribution

WANG An-xing¹, TAN Xian-ming²

1. School of Finance, Shanghai University of Finance and Economics, Shanghai 200433, China;
2. Health Center, McGill University Quebec H4A 3J1, Canada

Received:2015-04-07 Revised:2017-06-07 Online:2018-02-20 Published:2018-04-20

摘要/Abstract

摘要： 论文用GARCH模型描述股票的波动特性，应用混合分布对中国上市公司按照股票波动特性进行分组，发现中国上市公司的波动特性可以被分为4个子总体。其中，子总体1主要包含表现异常的公司股票，其他三个子总体的参数向量的相关性相似，风险大小不同。应用列联表法分析和多元logistic模型统计分析发现，非国有股权分散公司、制造业公司相对偏向低风险公司，社会服务业、房地产公司相对偏向高风险公司，制造业的公司（股票）波动的持续性相对较低。混合分布是对股票特性进行分组的良好工具。

关键词: 混合分布, GARCH模型, 股票波动率

Abstract: GARCH models have been widely used in modeling financial time series that exhibit time-varying volatility clustering. In this study, the model-based clustering approach is employed to examine clusters of 1165 stocks on Chinese security market on the basis of the estimated GARCH model parameters. It is found that the 1165 stocks could be divided into 4 clusters:cluster 1 consists of stocks with abnormal volatility features, while for stocks in the other three clusters. The distributions of the GARCH parameters have a similar shape but with different values.Stocks of manufacturing companies and decentralized non-state-owned companies are more likely in the cluster with low volatility.Stocks of public utility companies (electricity, gas, water supply)and real-estate companies are more likely in the cluster with high volatility.

Key words: mixture distribution, GARCH model, stock volatility

中图分类号:

F124

王安兴, 谭鲜明. 基于混合分布的中国股票波动风险因素的识别与分析[J]. 中国管理科学, 2018, 26(2): 86-95.

WANG An-xing, TAN Xian-ming. The Analysis of Chinese Stock Volatile Risk Factors based on Mixture Distribution[J]. Chinese Journal of Management Science, 2018, 26(2): 86-95.

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基于混合分布的中国股票波动风险因素的识别与分析

The Analysis of Chinese Stock Volatile Risk Factors based on Mixture Distribution

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