Table 7.

The impact of day trading on price depth (two-stage regression)

Dependent: ILLQ
Regression models(1)(2)(3)(4)
Intercept1.304 (0.359)−9.945*** (0.000)−10.271*** (0.000)1.297 (0.362)
DV−0.240*** (0.000)−0.299*** (0.000)−0.367*** (0.000)−0.239*** (0.000)
Turnover−12.643*** (0.000)−0.097 (0.901)
Retp−0.181*** (0.000)−0.181*** (0.000)
Retn0.202*** (0.000)0.202*** (0.000)
DR0.163** (0.038)0.172** (0.030)0.175** (0.027)0.163** (0.038)
Size−0.830*** (0.000)−0.478*** (0.000)−0.707*** (0.000)−0.828*** (0.000)
MI−1.147*** (0.002)1.267*** (0.001)1.597*** (0.000)−1.147*** (0.002)
Week_EffectYesYesYesYes
Month_EffectYesYesYesYes
Adjusted-R20.1140.0980.0960.114
N137,123137,123137,123137,123

Note:

The following is the regression model for the analysis of the impact of day trading on price depth using two-stage regression:

ILLQt,i=α+β1DVt,i+β2Turnovert,i+β3Retpt,i+β4Retnt,i+β5DRi+β6Sizei+β7MIt+εt

where ILLQt,i is the illiquidity ratio presenting price depth, DVt,i is the day trading volume, Turnovert,i is the turnover rate and Retpt,i and Retnt,i are positive and negative returns. All aforementioned variables are for stock i at day t. Moreover, DRt is the debt ratio for stock i, Sizet is the logarithm market value for stock i and MIt is the stock market index at day t. This table reports the results of the second stage. The p-values are in parentheses.

** and

***denote the significance at the 5% and 1%, respectively

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