对PIN在公告前后异常及其原因分析

发布时间：2019-06-05 09:17

【摘要】：以证监会查处的17只公告前存在内幕交易或信息泄漏的股票为样本,分别利用EKOP模型和DY模型,从交易量和公共信息两个视角,研究A k tas等(2007)发现的信息性交易概率P IN在公告前降低在公告后升高的异常现象。结果表明,交易量和公共信息因素对P IN的估计有重要影响,考虑到这两个因素后,P IN在公告前降低的异常现象消失,但是P IN在公告后相对于公告前上升的异常继续存在。本文认为这是由于公共信息造成的指令流不平衡所致,并指出P IN作为总的买卖指令不平衡性的度量包含了比私人信息更多的内容,高估了市场的信息不对称程度。此外,本文提出了一个新的算法,彻底解决了用计算机对EKOP模型的似然函数进行估计时经常遇到的数值溢出问题。
[Abstract]:Taking 17 stocks investigated and dealt with by CSRC with insider trading or information leakage before announcement as samples, using EKOP model and DY model respectively, from the perspective of trading volume and public information, The abnormal phenomenon that information transaction probability P IN found by A k tas et al. (2007) decreased before announcement and increased after announcement was studied. The results show that the transaction volume and public information factors have an important influence on the estimation of P IN. Considering these two factors, the abnormal phenomenon of, P IN decrease before announcement disappears, but the anomaly of P IN rising after announcement continues to exist. This paper holds that this is caused by the imbalance of instruction flow caused by public information, and points out that P IN, as a measure of the overall imbalance of buying and selling instructions, contains more content than private information, and overestimates the degree of information asymmetry in the market. In addition, a new algorithm is proposed to solve the problem of numerical overflow, which is often encountered in the estimation of likelihood function of EKOP model by computer.
【作者单位】：北京航空航天大学经济管理学院;
【基金】：国家自然科学基金资助项目(71071010) 中央高校基本科研业务费专项(YWF-10-06-004)
【分类号】：F830.91;F224

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