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。
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.
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