Project description:Using 5-minute high frequency data from the Chinese stock market, we employ a non-parametric method to estimate Fama-French portfolio realized jumps and investigate whether the estimated positive, negative and sign realized jumps could forecast or explain the cross-sectional stock returns. The Fama-MacBeth regression results show that not only have the realized jump components and the continuous volatility been compensated with risk premium, but also that the negative jump risk, the positive jump risk and the sign jump risk, to some extent, could explain the return of the stock portfolios. Therefore, we should pay high attention to the downside tail risk and the upside tail risk.
Project description:The COVID-19 outbreak generates various types of news that affect economic and financial systems. No studies have assessed the effects of such news on financial markets. This study sheds light on the impact of non-fundamental news related to the COVID-19 pandemic on the liquidity and returns volatility. Because we examined extreme events, we performed quantile regression on daily data from December 31, 2019 to the end of lockdown restrictions in China on April 7, 2020. Results showed that the non-fundamental news, as the number of deaths and cases related to the COVID-19, raised the stock market returns volatility and reduced the level of stock market liquidity, increasing overall risk, whereas fundamental macroeconomic news remained largely immaterial for the stock market. These findings are explained by a knock-on effect because the health system's inability to manage and treat a high number of COVID-19 patients in intensive care led the country to implement a lockdown and the global economy to largely shut down.
Project description:This paper introduces the market framing bias (MFB): a framing effect that affects the return-risk tradeoff under different frameworks of aggregate market losses and profits, which is measured by the absolute difference between betas in the rising and falling markets. The paper finds that the MFB can predict lower future stock return on the cross-section. Specifically, after controlling for various firm-specific characteristics, this predictive power of the FMB declines over time. Furthermore, the predictive power of the FMB is stable in the short term even after controlling for various pricing factors and firm-specific characteristics.
Project description:Using a daily foreign and institution flows data, this paper studies how institutional and foreign investors respond to the COVID-19 pandemic events in China. The results indicate that during the COVID-19 crisis foreign investors play a market stabilization role showing significant negative feedback trading, whereas institution investors do not stabilize the market. And compared to the pre-COVID-19 period, foreign investors even exhibit stronger negative feedback trading. Further analyses confirm that foreign investors' negative feedback is mainly driven by their response to negative returns. Moreover, both institutional and foreign investors' trading show stronger forecastability of future returns during the pandemic period. And the negative returns after foreigners' selling and positive returns after institutional buying are much stronger during the crisis period.
Project description:This article presents a dataset to investigate the determinants of firms' decision for primary share issuance and the effects of market timing on primary share issues in the Brazilian stock market. The data refer to Brazilian nonfinancial firms that issued primary shares (IPOs and SEOs) in the 2004-2015 period. The data were gathered from the online bases of Economatica® and the São Paulo Securities, Commodities and Futures Exchange (BM&FBovespa). The final sample was composed of 123 firms and 165 primary share issues: 97 initial public offerings and 68 follow-on offerings. The dataset was developed to support a model that captures market timing behavior through cumulative abnormal returns and shows the effects of this behavior on the amount of proceeds raised. The dataset contains subsamples and different analysis time windows, processed and unprocessed data. Researchers can use the dataset for future research and comparisons with other markets and models. The related research article using part of the current dataset was published under the following title: "Effects of market timing on primary share issues in the Brazilian capital market" (Gomes et al.).
Project description:•I investigate the stock market's reaction to coronavirus news in the top six most affected countries by the pandemic.•The fake news exerts a negative nonlinear influence on the inferior and the middle quantiles throughout the distribution of returns.•The media coverage leads to a decrease in returns across middle and superior quantiles and has no effects on the inferior ones.•During COVID19 turmoil superior quantiles of returns distribution exhibit negative dependence on past performances, while inferior and middle quantiles are not affected by this phenomenon.•The gold return has a positive correlation with the stock markets, which amplifies during extreme bearish and bullish periods indicating that it does not behave as a "Safe Havens" asset.
Project description:We use stock market returns and a new, weekly available, GDP tracker to estimate a structural VAR identified with long-run restrictions. We find that global 'news' contribute more than local 'news' shocks to explaining the recent variance of equity returns from developing and small developed countries. Since data do not (yet) point to an increase in financial integration during the current pandemic, our investigations support the alternative that these markets hold too optimistic views on their prospects and future ties with the global economy.
Project description:We studied globally representative data to quantify how daily fine particulate matter (PM2.5) concentrations influence both daily stock market returns and volatility. Time-series analysis was applied on 47 city-level environmental and economic datasets and meta-analysis of the city-specific estimates was used to generate a global summary effect estimate. We found that, on average, a 10 μg/m3 increase in PM2.5 reduces same day returns by 1.2% (regression coefficient: - 0.012, 95% confidence interval: - 0.021, - 0.003) Based on a meta-regression, these associations are stronger in areas where the average PM2.5 concentrations are lower, the mean returns are higher, and where the local stock market capitalization is low. Our results suggest that a 10 μg/m3 increase in PM2.5 exposure increases stock market volatility by 0.2% (regression coefficient 0.002, 95% CI 0.000, 0.004), but the city-specific estimates were heterogeneous. Meta-regression analysis did not explain much of the between-city heterogeneity. Our results provide global evidence that short-term exposure to air pollution both reduces daily stock market returns and increases volatility.
Project description:This paper examines the impact of non-pharmaceutical intervention by government on stock market return as well as volatility. Using daily Malaysian equity data from January 28, 2020 to May 31, 2022, the regression analysis with bootstrapping technique reveals that the government's response in combating the deadly virus through Stringency index has shown a positive direct effect on both stock market returns and volatility, and indirect negative effect on stock market returns. The study revealed that international travel restriction and cancelling public events are the major contributors to the growth of volatility when estimated for Malaysia stock market index. On the one hand, heterogenous impact is expected from the perspective of different sectors when the individual social distancing measures were taken into account in determining stock return and volatility. Apart from that, the robustness check for the main findings remains intact in majority of the regression models after incorporating daily COVID-19 death rate, log (daily vaccination) and day-of-the-week effect as additional control variable in alternative.
Project description:The implementation of Shanghai-Hong Kong Stock Connect marks the maturity of China's capital market, and the effect of the implementation has been the focus of academic attention. Based on this quasi-natural experiment, We select 3248 samples of heavily polluting enterprises listed in China in 2010-2020 to examine the impact of capital market liberalization and on corporate environmental performance.The results show that capital market liberalization significantly improves the environmental performance of heavy polluting enterprises. The results of the heterogeneity analysis indicate that the positive effect varies across firms with different ownership and internal controls. Finally, mechanism analysis results find that capital market liberalization promotes the environmental performance of heavily polluting firms by increasing environmental assets,reducing stock price volatility,and improving the quality of information disclosure.