We establish a framework to study the factor structure in stock variance under a high-frequency and high-dimensional setup. We prove the consistency of conducting principal component analysis on realized variances in estimating the factor structure. Moreover, based on strong empirical evidence, we propose a multiplicative volatility factor (MVF) model, where stock variance is represented by a common variance factor and a multiplicative lognormal idiosyncratic component. We further show that our MVF model leads to significantly improved volatility prediction. The favorable performance of the proposed MVF model is seen in both US stocks and global equity indices.

In 2013, the Shanghai Futures Exchange (SHFE) introduced a night session in Chinese metal futures markets. Using high-frequency data of gold, silver, and copper futures, we investigate the impact of night trading on intraday return predictability in Chinese metal futures markets. Firstly, we find the intraday return predictability has changed after introducing night trading: before the launch of night trading, the first half-hour daytime returns show significant predictability, whereas the first half-hour night returns exhibit forecasting power after that. Such changes can be explained by the immediate reactions of domestic investors to international news released in the evening. Secondly, the market timing strategy outperforms the always-long and buy-and-hold benchmark strategies. Thirdly, the predictability of night return is stronger on days with higher volatility and volume. Furthermore, stronger intraday predictability is associated with global news releases and positive news sentiment, suggesting enhanced connectedness of Chinese and international metal futures markets after the launch of night trading.

数字金融迅速发展如何影响孩子的学习成绩？本文基于社会资本理论和物质资本理论探究数字金融发展对孩子学习成绩的影响及内在机制。基于中国家庭追踪调查（CFPS）和中国数字普惠金融指数数据，本文发现数字金融发展降低了孩子的学习成绩。 通过分析数字金融对孩子成绩的影响机制，发现数字金融发展促进了父母的就业，增加了父母工作时间， 引起家庭“社会资本”降低，使得父母陪伴和监督孩子的时间减少， 导致孩子的学习成绩下降。祖父母的陪伴、 参加课外辅导班及住校能在一定程度上弥补父母对孩子陪伴时间的减少，缓解数字金融发展对孩子学习成绩的负向影响。 数字金融虽能提升家庭的“物质资本”，但并没有通过显著增加对孩子的教育投资而提升孩子成绩。 本文结论对家长和政策制定者具有一定的启示。

We propose a behavioral signaling framework to explain the positive announcement effects of stock splits. (Retail) investors view stock splits as good news and are loss averse. Thus, a stock split can boost investors’ expectations of the firm’s growth potential and its stock price, but may also cause disproportionally larger price declines if the firm cannot meet investors’ high expectations. In equilibrium, only managers with favorable information use stock splits to signal. Empirical analyses of stock splits in China find supporting evidence for this explanation: (1) investors become more optimistic after stock splits; (2) higher split ratios are associated with stronger market reactions; (3) splitting firms have better future performance than non-splitting firms; and (4) they experience larger price declines when falling short of investors’ expectations. These findings, along with the unique institutional features of the Chinese market, help differentiate our behavioral explanation from alternative explanations within the rational framework.

This study investigates the effect of institutional cross-ownership on stock price crash risk using a sample of Chinese listed companies during the period 2011–2021. We find that institutional cross-ownership can significantly reduce stock crash risk. After a series of robustness tests, the above findings still hold. In addition, we find that the relationship is more pronounced for non-state-owned listed companies and those in less-developed regions. The study finds that the quality of corporate disclosure and financing constraints have the mediating effect. This paper provides new empirical evidence on how to reduce stock crash risk in emerging financial markets.

This paper compares Chinese firms’ IPO performance both in the short- and the long-run on domestic and overseas markets and investigates what factors determine the IPO destinations of Chinese firms. We find China’s domestic IPO market performs well over both time horizons, while some listings in the overseas market perform well in the long run except for small- and mid-cap listings in the US. Analysis based on a capital asset pricing model reveals IPO premiums and short-term returns are less affected by three common risk factors, while longer term returns are mainly driven by market fundamentals. Investigation of the drivers for Chinese firms’ IPO destinations using the binary choice model shows that firm specifics, institutional setups, and market characteristics influence the choice of IPO destinations. The prospect of a high IPO premium and strong trading in IPO shares are substantial drivers for firms to list their shares onshore. On the other hand, indicators of market size and profitability appear to have the highest predictive power for the likelihood of overseas listings, followed by firm’s ownership structure, IPO offering size and IPO underwriting costs. Institutional setups have the least predictive power for overseas listings. These results are in general robust to domestic delisting and IPO suspension events.

In this study, we adjust the hierarchical risk parity (HRP) model by introducing hierarchical information on assets to help manage portfolio risk. The adjusted HRP model with hierarchical information considers both correlation and hierarchical information. Compared with other models, the HRP model with hierarchical information has better out-of-sample robustness for simulation data. Moreover, this model achieves better out-of-sample performance using Chinese industry indices data. The results reveal that the adjusted HRP model is an efficient tool to control out-of-sample portfolio risk.

This paper investigates the impact of the COVID-19 pandemic on the volatility spillover and dependence structure among the major developed and emerging stock markets. The TVP-VAR connectedness decomposition approach and R-vine copula are implemented in this research. The results of the TVP-VAR connectedness decomposition approach reveal that the volatility spillover among the major developed and emerging stock markets has been significantly strengthened by the outbreak of the COVID-19 pandemic, although it has gradually faded over time. In addition, during the pandemic, the UK, German, French and Canadian stock markets are the spillover transmitters, while the Japanese, Chinese Hong Kong, Chinese and Indian stock markets are the receivers. It is also found that the US and Brazilian stock markets have undergone role shifts after the outbreak of the COVID-19 pandemic. The results of the R-vine copula model indicate that during the pandemic, the Canadian, French, and Chinese Hong Kong stock markets are the most important financial centre in the American, European, and Asian stock markets, respectively. Furthermore, the effect of the extreme risk contagion has been strengthened by the pandemic, particularly the downside risk contagion.

Retail investors are rising in prominence but have historically been granted little direct access to question corporate management relative to professionals like sell-side analysts and institutional investors. Because retail investors are relatively less sophisticated and can require hand-holding, we examine whether information asymmetry among investors decreases when firms answer questions from the retail investor base. We exploit ’s investor interactive platforms (IIPs), which were designed to facilitate retail investor access to management. IIPs allow questions to be anonymously and publicly posted, but answers can only pertain to previously disclosed information and there is no explicit penalty for low-quality answers. We find that IIP answers reduce bid-ask spreads, with stronger answer effects when managers respond quickly, provide direct answers, and interact with IIP users who focus on the firm. These information asymmetry reduction benefits are substantially attenuated, and in some cases non-existent, for state-owned enterprises (SOEs), who have less incentive to publicly engage with retail investors. Finally, our findings reveal that on average the marginal effects of answers are smaller than for posted questions, suggesting that while firms benefit from answering questions to lower investor integration costs, IIP activity that lowers awareness and acquisition costs is also important.

In this paper, we argue that investor sentiment is a more direct determinant for asset pricing than information, thus we propose the Sentiment Efficient Markets Hypothesis (S-EMH), complementary to the traditional Efficient Market Hypothesis (EMH), to provide a powerful instrument to interpret financial facts and anomalies inconsistent with the traditional EMH. Besides the theoretical argument, we also verify the hypothesis with a brand-new systematic index of investor sentiment, Gubasenti, derived from textual analysis on more than 200 million posts from an online Chinese stock forum. The examinations are implemented in both market-level and firm-level, and results show that investor sentiment has a significant impact on asset pricing in both levels. It demonstrates the proposed hypothesis.