The Stringency of Policy Responses and Stock Market Volatility
The table presents the results of panel data regressions. The dependent variable is the logarithm of daily volatility proxied with absolute daily returns (log|R|), or residual returns from four different models: CAPM (log|RRCAPM|), the Fama and French (1993) model (log|RRFF|), the Asness, Moskowitz, and Pedersen (2013) model (log|RRAMP|), or the Carhart (1997) model (log|RRCAR|). The independent variables are: the Government Policy Response Stringency Index (SI), the logarithm of daily dollar trading volume expressed in USD (log(TV)), the logarithm of market value in USD (log(MV)), the logarithm of market-wide PE ratio (log(PE)), and daily changes in numbers of new COVID-19 infections and deaths (ΔINF, ΔDTH); ShortBan indicates short-selling ban, and ShortNote indicates a requirement to notify large short position to a local market regulator. All the regression equations include also weekday dummies. R2 denotes an adjusted coefficient of determination. The numbers in brackets are t-statistics and asterisks *, **, and *** denote statistical significance at the 5%, 1%, and 0.1% levels, respectively. Panel A demonstrates the baseline results following the random-effects model, while Panel B displays robustness checks assuming several alternative specifications or functional forms: fixed-effects and pooled regression models, a regression equation excluding the weekday dummies, and a regression equation controlling for the total number of deaths and cases.