Table 5.
Sentiment Effect | Reverse Effect | Region Effect | ||||
---|---|---|---|---|---|---|
FE | FGLS | FE | FGLS | FE | FGLS | |
SENTi | 0.005*** | 0.004*** | 0.005*** | 0.004*** | 0.005*** | 0.004*** |
(114.55) | (113.85) | (114.79) | (114.07) | (114.79) | (114.07) | |
MKT | 1.010*** | 1.011*** | 1.016*** | 1.017*** | 1.016*** | 1.017*** |
(187.81) | (187.86) | (187.52) | (187.57) | (187.52) | (187.57) | |
SMB | 0.604*** | 0.607*** | 0.625*** | 0.628*** | 0.625*** | 0.628*** |
(54.62) | (54.86) | (55.40) | (55.65) | (55.40) | (55.65) | |
HML | -0.108*** | -0.120*** | -0.058*** | -0.070*** | -0.058*** | -0.070*** |
(-5.09) | (-5.63) | (-2.67) | (-3.18) | (-2.67) | (-3.18) | |
EW | -0.002*** | -0.002*** | -0.002*** | -0.002*** | ||
(-9.27) | (-9.31) | (-9.27) | (-9.31) | |||
Location | ||||||
Other Hubei regions | 0 | -0.000 | ||||
(.) | (-0.29) | |||||
Wuhan City | 0 | -0.001 | ||||
(.) | (-0.77) | |||||
α0 | -0.003*** | -0.002*** | -0.001*** | -0.001*** | -0.001*** | -0.001*** |
(-25.43) | (-23.89) | (-4.74) | (-3.92) | (-4.74) | (-3.85) | |
adj. R-sq | 0.477 | 0.477 | 0.477 | |||
F | 17404.1 | 13956.8 | 13956.8 | |||
N | 74455 | 74455 | 74455 | 74455 | 74455 | 74455 |
Notes: Table 5 provides the results from the estimation of the following regression specification.
Dependent variable Ri,t represents the return of individual stock i on day t and SENTi,t represents the sentiment index of individual stock i on day t. EWt is a dummy variable representing the event window(0: the event window, 1: the post-event window). Li is the dummy variable representing the region, and the values are 2, 1 and 0, which respectively indicate whether the company is located in Wuhan, other cities in Hubei and other regions in China. First, we run the regression using SENT as the independent variable alone and then gradually add EW and L to test the regional and reversal effects. The adjusted R squares of the three fixed effect models are approximately equal. That is to say, the reverse and regional effect dummy variables have little effect on improving the fitting degree. Accordingly, the coefficients of EW and L are close to zero. T-stats are in parentheses below the coefficient estimates. ***, **, * indicate significance at the 1%, 5%, and 10% levels, respectively.