For example, if X equals to three, the portfolio of January 2008 includes all stocks with insiders’ trades in November 2007, December 2007 or January 2008. There is higher change for multiple observations on the same firm in the portfolio that occur within X months of the initial observation, for example, an insider buys stocks of firm B in January 1, 2007 and another insider buys stock of firm B in March 1, 2007. Hence, in the March 2007 portfolio, firm B will have double weight in the portfolio compared to other firms. To overcome this problem, we would consider a number of firms in a portfolio not a number of trades. By following a number of firms in the portfolio, we would provide equal weights to each company, not each trade.
The measurement of performance of the portfolio
A central empirical issue to measure the performance of any portfolio condition on any event is to control all other factors that may produce excess returns except a particular event. Therefore, we require a model that seems to capture much of the cross-sectional variance in average stock returns. (Fama and French, 1998). We...
... middle of paper ...
...ion model would be
〖IAb〗_bt-〖TA〗_bt=α_ +β(R_(m,t)-R_(f,t) )+Ψ〖SMB〗_t+〖γHML〗_t+λ〖MOM〗_t+ ε_t (7)
In similar way, to test the extent to which insiders’ sell of intangible assets companies earn less profit than those in tangible assets, we would follow equation (8). In the equation (8), the dependent variable is the difference between the calendar –time portfolio return of tangible assets and intangible assets(〖TA〗_s-〖IA〗_s). For example, for Jun 2007 month portfolio, 〖IA〗_s, is equal weighted average return for all intangible assets companies whose insiders were net buyers between January 2007 and Jun 2007 , over 〖TA〗_s is equal weighted average return for all tangible assets companies whose insiders were net sellers between January 2007 and Jun 2007.
The regression model would be
〖IA〗_st-〖TA〗_st=α_ +β(R_(m,t)-R_ft )+Ψ〖SMB〗_t+〖γHML〗_t+λ〖MOM〗_t+ ε_t (8)
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