Information content of insider trading in Germany - three empirical essays

Abstract

This dissertation employs an empirical strategy to investigate the information content of insider trading. The analysis is based on the basic premise that insiders, while possessing private information, trade for many reasons and perform a variety of roles. By identifying information motivated trades (trades outside blackout periods) and examining their interest positive interaction to Corporate Social Responsibility (CSR), we show that legal insider trading contributes to market efficiency and fairness. Further, we find substantial abnormal returns (most in cases of purchases) that indicates valuable content of information in insider trades. MAR regulation though mitigates the informativeness of insider trading, the impact appears mostly for trades of firms with high level of litigation risk. In addition, the MAR effect on trades in alternative trading venues is weak. Last, in exploiting the predictability of aggregate insider trading, this work demonstrates that insider trades in aggregate deliver us a precise predictor for future market returns, at least three months before the market moves. The stock market price predictivity effect of aggregate insider trades is even higher when market transparency is stronger (in the period after MAR introduction). Following to the results of this work, insiders’ predictive ability becomes especially valuable during periods of significant market disruption such as during Covid-19 pandemic.