This paper examines the relationship between aggregate insider trading (AIT) and stock market volatility using monthly data on insider transactions by UK executives in public limited companies for the period January 2002 - December 2020. More...
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ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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This paper examines the relationship between aggregate insider trading (AIT) and stock market volatility using monthly data on insider transactions by UK executives in public limited companies for the period January 2002 - December 2020. More specifically, a Vector Autoregression (VAR) model is estimated and Impulse Response analysis as well as Forecast Error Variance Decomposition are carried out. The main finding is that higher AIT (more specifically, insider purchases) leads to a short-run increase in stock market volatility; this can be attributed to a combination of insiders manipulating the timing and content of the information they release and the revelation of new economy-wide information to the market. The UK being a well-regulated market, it is plausible that the main driver of the increase in stock market volatility should be the information effect. These results are shown to be robust to using alternative (direct) measures of AIT.
