The existing literature studies the relationship between institutional investors and the risk of stock price crash from multiple dimensions. Based on the phenomenon that institutional investors hold the shares of several listed companies in the same industry, this paper takes the A-share listed companies in Shanghai and Shenzhen stock markets from 2008 to 2018 as the research samples to explore the relationship between institutional common ownership and stock price crash risk. The results show that: institutional common ownership significantly increases the risk of stock price crash. After a series of robustness tests, the conclusion remains unchanged. The impact mechanism test shows that institutional common ownership improves the stock price synchronization, investor sentiment and stock liquidity, and then aggravates the risk of stock price crash. Further tests show that the higher the product market competition, the more media coverage, and the weaker the protection of regional investors, the positive impact of institutional common ownership on the risk of stock price crash is more significant.

This study investigates Chinese equity mutual funds’ performances while holding those that are well behaved in financial disclosure (transparent) companies, so-called peace of mind investing. This study uses detailed semi-annual data on mutual funds from 2011 to 2020, and finds that holding these transparent companies’ stocks is profitable for mutual funds and trusted by investors, thereby boosting their inflows. However, there is no significant evidence that mutual funds can beat the market portfolio when fees are considered. The study then provides possible explanations for the above findings from mutual fund managers’ skills and mutual holdings between institutional shareholders of fund management and transparent companies.

This paper investigates the intertemporal relation between expected aggregate stock market returns and conditional variance considering periodic trading breaks. We propose a modified version of Merton’s intertemporal asset pricing model that merges two different processes driving asset prices, (i) a continuous process modeling diffusive risk during the trading day and, (ii) a discontinuous process modeling overnight price changes of random magnitude. Relying on high-frequency data, we estimate distinct premia for diffusive trading volatility and volatility induced by overnight jumps. While diffusive trading volatility plays a minor role in explaining the expected market risk premium, overnight jumps carry a significant risk premium and establish a positive risk-return trade-off. Our study thereby contributes to the ongoing debate on the sign of the intertemporal risk-return relation.

This paper investigates the trading behavior of ambiguity-loving investors and the corresponding impacts on asset price. The ambiguity-loving attitude increases investors' willingness to participate in the risky asset market. Their rising participation gradually crowds out ambiguity-averse and sophisticated investors, extending their nonparticipation region. When the market supply is small, the discontinuous and non-unique properties of ambiguity-loving investors' demand mapping can cause flat ranges in the equilibrium price. When the market supply is moderate or large, an increase in the fraction of ambiguity-loving investors or ambiguity level reduces equity premium. We find the effect of ambiguity-loving attitudes remains with short-sales constraints except for ambiguity-loving investors' positions and the equity premium. Their positions shrink, and equity premium decreases when the market supply is small. Besides, the rising fraction of ambiguity-level investors and ambiguity level increases equity premium when ambiguity-loving investors with heterogenous opinions only sell the risky asset.

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.

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.

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.

We study investors’ responses to increasing tax reporting awareness and scrutiny in the crypto markets. Using novel data on retail investors’ trading, we ocument significant taxation effects on investors’ behavior and preferences for crypto-exchanges. Investors engage in tax-loss harvesting through wash trading and trading new products such as non-fungible tokens, consistent with the motive to minimize taxable events, improve tax reporting quality, and balance portfolio losses. U.S.-based traders engage in more tax-loss harvesting at the end of the year than their international peers. We further examine billions of trades on the trading books of large crypto exchanges and discover widespread tax-loss harvesting trades on U.S.-based crypto exchanges, amounting to billions of dollars in tax revenue losses for the government. Finally, we discuss ongoing anti-tax-loss harvesting proposals in anticipation of traders’ likely reactions.