上市公司股价异动的数据建模诊断

上市公司股价异动为证券市场监管层和投资者所重点关注，因其与证券市场的秩序和投资者的切身利益密切相关。以中国证监会公布的三起违规案例为样本，以股价为响应变量，以市盈率和涨跌幅绝对值为自变量建立回归模型。利用数据建模诊断方法，根据学生化残差、杠杆值、Cook距离、马氏距离等诊断统计量，对股价是否存在异动进行检测，并进行综合交叉印证，确定重点怀疑数据，然后，删除这些可疑数据，再将删除前后表征模型优劣的若干个指标的变化情况进行比对。实证研究表明，三起查处案例中交易异常行为都较好地得到定位，与实际结果相符较好，这对于规范证券市场健康发展及保护投资者合法权益有积极意义。

Data Modeling Diagnostic of Listed Companies in the Stock Transaction

Securities market regulators and investors are very concerned about the abnormal fluctuation issues in stock price, because it is important to keep the securities order and investors. The author selected three stocks which had been punished as samples, simultaneously, a regression model was established with the price as response variable and the earning ratio and the absolute value of the change as independent variable. The author used data modeling diagnostic methods, according to the the diagnostic statistics of the studentized residuals, leverage values, cook distance, mahalanobis distance, then, this paper detected whether the price was abnormal and determined the suspect data by integrated crossing-confirms. After deleting the suspicious data, the author compared the characteristics about the qualities of model. Empirical studies have shown that the abnormal behaviors of the three cases had been located and conformed actual results, which was of positive significance for the keeping the healthy securities market and protecting the legitimate rights and benefits of investors.