Table 5.

The impact of day trading on stock volatility

Dependent: Sigma
Regression models(1)(2)(3)(4)
Intercept−55.353*** (0.000)−23.422*** (0.000)−22.483*** (0.000)−55.128*** (0.000)
DV0.176*** (0.000)0.327*** (0.000)0.533*** (0.000)0.162*** (0.000)
Turnover38.076*** (0.000)3.398 (0.324)
Retp0.499*** (0.000)0.492*** (0.000)
Retn−0.591*** (0.000)−0.587*** (0.000)
DR−0.428 (0.219)−0.445 (0.203)−0.457 (0.191)−0.428 (0.219)
Size−2.271*** (0.000)−3.256*** (0.000)−2.616*** (0.000)−2.329*** (0.000)
MI16.374*** (0.000)9.510*** (0.000)8.579*** (0.000)16.381*** (0.000)
Weekday_EffectYesYesYesYes
Month_EffectYesYesYesYes
Adjusted-R20.0290.0220.0210.029
N137,649137,649137,649137,649

Note:

The regression model for the analysis of day trading impact on stock volatility is as follows:

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

where Sigmat,i is the stock volatility, DVt,i is the day trading volume, Turnovert,i is the turnover rate and Retpt,i and Retnt,i are positive and negative returns, respectively. The 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. The analysis is conducted using panel regression. The p-values are in parentheses.

***denotes the significance at the 1%

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