Expected Idiosyncratic Skewness Data
Below you can find updated estimates of expected idiosyncratic skewness through the end of 2016, similar to those described in Boyer, Mitton, and Vorkink (2010). The first column identifies the year and month for date t, where t ranges from July 1969 through December 2016. The second column identifies the permno. The third column gives the forecast of expected idiosyncratic skewness observed at the end of month t for the distribution of daily returns over months t+1 through t+60. The fourth column gives the forecast of expected total skewness observed at the end of month t for the distribution of daily returns over months t+1 through t+60. The data file is approximately 80 megs.
Data Methodology
To investigate the pricing of idiosyncratic skewness we sort securities into
quintiles by expected idiosyncratic skewness at the end of month
t and examine returns over month t+1 (as in our paper). Below
we report the average value-weighted return, as well as the Fama-French
alpha for the value-weighted return of each quintile portfolio for
t+1 equal to January 1987 through December 2016. Standard errors are
Newey-West adjusted. (We begin the sample in January 1987 due to data
restrictions on turnover. See "Methodology" link for further details.)
We also compare the returns of a typical stock with high ex-ante skewness to that of a typical stock with low ex-ante skewness. To investigate this issue, we calculate the median return (in the cross section) each month for each skewness bin, and report both the time-series average and Fama-French alpha.
We also compare the returns of a typical stock with high ex-ante skewness to that of a typical stock with low ex-ante skewness. To investigate this issue, we calculate the median return (in the cross section) each month for each skewness bin, and report both the time-series average and Fama-French alpha.