摘要
基于内幕交易后股票收益率的变动特征,通过构建内幕交易行为的识别方法——信息泄露模型,并利用沪市A股的分时高频交易数据可以实现对可疑内幕交易行为的监测,进而实证分析内幕交易对股票信息效率的影响方向和程度。研究结果表明,内幕交易会导致股票信息效率的下降,转换数据频率和分市场行情检验结果依旧稳健。在分市场行情检验中,内幕交易对信息效率的不利影响往往在股票市场上涨和反弹时更为突出,而在股票市场震荡和下跌时有所减弱。
Based on the variation characteristics of stock returns after insider trading,this paper constructs an identification method of insider trading behavior—information leakage model,and utilizes high-frequency trading data of the Shanghai stock market to monitor suspicious insider trading behavior.Furthermore,this paper appropriates panel data regression to analyze the direction and degree of insider trading affecting stock information efficiency.The results illustrate that insider trading leads to a decline in stock information efficiency,yet the test results of data conversion frequency and sub-market performance are still robust.In the sub-market test,the adverse effect of insider trading on information efficiency is more prominent when the stock market is rising and rebounding,while it is weakened when the stock market is fluctuating and falling.
作者
李志辉
孙广宇
Li Zhihui;Sun Guangyu
出处
《南开学报（哲学社会科学版）》
CSSCI
北大核心
2020年第5期136-145,共10页
Nankai Journal:Philosophy,Literature and Social Science Edition
基金
国家自然科学基金面上项目(71973070)
中国工程院咨询研究项目(2017-XZ-43)
关键词
内幕交易
高频交易数据
信息泄露
信息效率
Insider Trading
High-Frequency Trading Data
Information Leakage
Information Efficiency
