Detecting of Insider Trading prior M&A Deals in USA

Student: Knyazev Artem

Supervisor: Dmitrii Vyacheslavovich Timofeev

Educational Programme: Economics (Bachelor)

Year of Graduation: 2017

This paper investigates empirical models devoted to detection of illegal insider trading of public companies’ stocks before the announcement of M&A deals using data about their abnormal returns. Results obtained are the following: both CAR for the period prior the announcement of deal and AR for the day of the announcement may be considered as good means to detect insider trading. At the same time, the evidence that insiders prefer underestimated companies’ stocks was found. But it is important to emphasize that due to forecasting (not a causality explaining) purpose of models used under this work further investigation is needed in order to shed the light on the details of causality which connects probability of insider trading and degree of underestimation for the company.

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