We extend the ex-ante mean-variance (SVIX) asset pricing models of Martin (2017) and Martin-Wagner (2019) to a mean-variance-asymmetry (AVIX) framework by incorporating higher-moment and co-moment risk in asset pricing. Our proposed AVIX model is risk-neutral with left-tail asymmetries in returns to correct the SVIX approach's downside bias. We derive an option implied market beta of a stock as the weighted average of the betas of SVIX and AVIX. Empirically, the implied beta has significant predictability of risk/return relationship We develop an investible portfolio (MKT*) that mimics realized outcomes on the implied market index adjusted for volatility asymmetry.

This study investigates the effect of enterprise digital transformation on stock price crash risk using a sample of Chinese listed companies during the period 2007-2020. We find that the digital transformation of enterprises can significantly reduce stock price crash risk, and shows a certain structural heterogeneity. The above conclusions still hold after a series of robustness tests. Further, we identify that the relationship is more pronounced in high-tech enterprises and economically developed regions. Overall, the paper can provide empirical evidence for understanding how to reduce stock price crash risk in the capital market, and provide relevant implications for better driving the digital transformation of enterprises.

Using the Targeted Poverty Alleviation (TPA) disclosure policy in China as a quasi-natural experiment, this paper analyzes the impact of firm TPA disclosure on analyst forecast accuracy using a staggered difference-in-differences model. The results show a significant increase in the accuracy of analysts’ forecasts after firm disclosure of TPA information, and this effect is more pronounced in firms with more greater information asymmetry and firms with less experienced analyst following. Our study provides theoretical and empirical evidence for regulators concerned with information environment of capital market.

In China's labor market, there is a phenomenon that enterprises choose whether to provide "social insurance and housing fund" to laborers autonomously. This paper use micro-data from two leading Internet recruitment platforms and empirically finds that in a labor market with double-side information asymmetry, "social insurance and housing fund" is not only a cost but also a signal. Providing workers with "social insurance and housing fund" can both send a signal of stable operation to the labor market and identify high-quality workers for enterprises. With an instrument variable of local average social security payment rate, this paper excludes the endogenous effect of labor supply on wages while the signaling effect above is still significant. In addition, "housing fund" has a stronger signaling effect than "social insurance", and the strength of the two signaling effects is affected by the scale of the enterprises and the level of local payment rates. This paper also introduces a theoretical framework of two micro-mechanisms — signaling and screening — into the analysis. In terms of policies, this paper proposes to strengthen the information disclosure and the propagation of social security payment, and further reduce the financial burden of enterprises.

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 recent years, numerous Chinese peer-to-peer (P2P) lending platforms have collapsed, prompting us to investigate the regulation and monitoring of the fintech industry. Using a unique dataset of P2P lending platforms in China, we investigate the effect of the information environment on regulatory monitoring and platform collapse. Using the platforms’ proximity to regulatory offices as a proxy for information asymmetry, we show that an increase in distance reduces regulatory monitoring and increases the likelihood of platform collapse. Specifically, for every 1% increase in the driving distance between the local regulatory office and a P2P lending platform’s office, the platform’s likelihood of collapse increases by 1.011%. To establish causality, we conduct a difference-in-differences analysis that exploits two exogenous shocks: government office relocation and subway station openings. We provide evidence that proximity enhances monitoring quality by facilitating soft information collection, reducing platform failures. We further find two channels of this effect: (1) the information channel through which greater regulatory distance reduces the likelihood and frequency of regulators’ on-site visits and (2) the resource-constraint channel, through which greater regulatory distance significantly increases the local regulatory office’s monitoring costs. Overall, this study highlights the importance of the acquisition of soft information for regulatory monitoring to ensure the viability of fintech firms.

We investigate whether suppliers value their clients’ ESG profiles in China, the largest emerging market featured with low ESG awareness and severe agency problems. We find a robust and negative impact of Chinese firms’ ESG scores on their access to trade credit. The 2SLS regression results based on the instrumental variable indicate that the impact is casual. Additionally, the impact is more pronounced for firms with higher agency costs, greater information asymmetry, and worse financial performance. These results suggest that suppliers in China view clients’ ESG engagement as costly investments caused by agency problems. Finally, we highlight the economic importance of the impact by showing that trade credit access helps Chinese firms decrease debt costs, increase trade credit supply to downstream firms, and promote R&D inputs.

This study investigates the effect of financial technology (FinTech) development on stock price crash risk. We show that the development of FinTech can inhibit management from deliberately hiding bad news and alleviate information asymmetry, thereby reducing stock price crash risk. This effect is more pronounced among non-state-owned enterprises, firms with poor information environments and low-quality internal controls, and those in competitive industries and regions with high marketization. Overall, these findings suggest that the development of FinTech can mitigate the deliberate concealment of bad news by management and improve the timeliness of disclosure, leading to lower risks faced by investors.

We provide firm-level evidence on the real effects of shadow banking in terms of technological innovation. Firm-to-firm entrusted loans, the largest part of the shadow banking sector in China, enhance the borrowers’ innovation output. The effects are more prominent when the borrowers are subject to severer financial constraints, information asymmetry, and takeover exposures. A plausible underlying channel is capital reallocations from less productive but easy-financed lender firms to more innovative but financially less-privileged borrower firms. Our paper suggests shadow banking helps correct bank credit misallocations and thus serves as a second-best market design in financing the real economy

China’s shadow banking system has experienced surprisingly high growth since the global financial crisis. We develop a model to understand this puzzling phenomenon. With local government interventions in bank loans for low-quality projects and information asymmetry between banks and regulators, a policy combination of tightening formal banking and loosening shadow banking can reduce inefficiency, because the higher funding liquidity risk of shadow banking incentivizes banks to be more disciplined about the quality of projects. We find consistent empirical evidence that when on-balance-sheet financing was constrained by regulators, banks primarily shifted high-quality projects into their controlled shadow banking system.