Literature

Insider trading at firm level

Whether insider buy and sell transactions have any cross-sectional and time series forecasting ability for future stock returns.

Insider trading at micro-level

Insider trading scilence

Hong and LI (2017) examine the information content of insider silence. -

Data

Regulations

United States of America

1. "Short Swing"Rule

   The short swing rule of the 1934 security exchange act enforce insiders to return any profit that is made from making round trading within 6 months to the firm.

Example

To conduct Fama Macbeth regression on insider trading. The dependent Variable is the stock return in month $t$, denominate in U.S. dollars. The independent variables are insider trading activity proxy and Other firm characteristics. Firm characteristics include

• $ME$, Market capitalization at the end of month $t-1$
• $B/M$, Book-to-market equity ratio at the end of month $t-1$
• $MMT$, Past 11-month stock return in U.S dollar from month $t-12$ to $t-2$
• $LRET$, Past 1-month stock return in U.S dollar in month $t-1$

Specifically, the time series model is specified as follows:

$R_{it}=\alpha_i+\gamma_{1i}PNPR_{it}+\gamma_{2i}NNPR_{it}+\beta_{1i}ME_{it}+\beta_{2i}BM_{it}+\beta_{3i}MMT_{it}+\beta_{4i}LRET_{it}+\epsilon_{it}$

$PNPR$ and $NNPR$ are dummy variables which act as insider trading activity proxies. $PNPR$ equals 1 if the firms has a positive $NPR$; NNPR equals 1 if the firms has negative $NPR$.
NPR is calculated as

$NPR_it = (P_{it}-S_{itt})/(P_{it}+S_{it})$

Where $P_{it}$ and $P_{it}$ represents the number of purchase and sales of firm $i$ at month $t$, respectively.

An alternative Model is $R_{it}=\alpha_i+\gamma_{3i}NPR_{it}+\beta_{1i}ME_{it}+\beta_{2i}BM_{it}+\beta_{3i}MMT_{it}+\beta_{4i}LRET_{it}+\epsilon_{it}$