对PIN在公告前后异常及其原因分析

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。

An Analysis on PIN’s Anomaly around Information Disclosure and Its Causes

Aktas et al(2007) found lower PIN estimates in periods with information leakage prior to the announcements of merger and acquisition and label the inconsistency as "PIN’s anomaly".Using the EKOP model and DY model,this paper selects 17 stocks punished by CSRC(China Securities Regulatory Commission) for the existence of information leakage or insider trading as sample to study the reasons for PIN’s anomaly based on the perspective of trading volume and public information.The results indicate that trading volume and public information have important effects on PIN estimation.Specifically,the phenomenon of PIN’s decrease prior to information disclosures with insider trading disappears after taking trading volume and public information into consideration.It should be pointed out that PIN undergoes another increase after the information disclosure,which is resulted from the order imbalance caused by the public information disclosed in the announcements.A new algorithm is proposed to eliminate the numerical overflow and underflow problems in PIN estimation,which sheds light on heavily traded stocks.