Using Chinese data, we find that analysts’ earnings forecasts are more accurate and less biased when analysts are socially connected with the company’s signatory auditor. We also find that forecast performance improves following mandatory auditor rotations that result in new analyst-auditor connections and declines following mandatory rotations that terminate existing connections. We further find that our results become stronger when the information that auditors possess is likely to be more useful to analysts, that connected analysts have better career outcomes than unconnected analysts, and that investors and other analysts are more responsive to forecast revisions issued by connected analysts. Finally, we find that connected auditors provide higher quality audits to their connected clients and are more likely to retain those clients. Overall, our findings are consistent with connected analysts benefitting from private information obtained from their social connections with auditors by providing better earnings forecasts, and in turn, with auditors benefitting from information they receive from connected analysts by delivering higher quality audits that improve client retention.

The 2020 Holding Foreign Companies Accountable (HFCA) Act will force China-based firms to delist from U.S. exchanges if China fails to permit audit inspections during a two-year period. The Act also requires such firms, as soon as China blocks such inspections, to disclose ties to the Chinese party-state. We first explain why the delisting provisions, while well-intentioned, may well harm U.S. investors. We then turn to the disclosure provisions, explaining that they appear to be motivated by a desire to name-shame Chinese firms rather than to protect investors. While China-based firms do pose unique risks to U.S. investors, the Act fails to mitigate—and may well exacerbate—these risks.

Digital transformation empowers enterprises with new kinetic energy for high-quality development, can digital transformation enhance the transparency of capital market? This study constructs a corporate digital transformation index, and examines its impact on Chinese capital market transparency from the perspective of information senders. We find that corporate digital transformation significantly improves transparency, and this finding is more pronounced in non-SOEs, firms with low political connection, high industry environment uncertainty, and low regional marketization level. Channel tests show that lowering management myopia and increasing analyst attention are possible mechanisms. Furthermore, digital transformation improves stock liquidity by enhancing enterprises’ information transparency. Overall, our findings provide critical insights for improving transparency in China’s capital market.

The debate on whether legalization or prohibition is more effective in conserving species and curbing illicit black-market trade remains controversial, with insufficient evidence available. Here we investigate the effects of China’s ivory ban on elephant poaching. We find that the enaction of the total ivory ban corresponds with a sharp 50% decrease in poaching and a significant reduction of the number of seizure cases. Further, although China has taken restrictive measures in 2015 and signaled a total ivory ban in 2016, no occurrence of “last minute rush” in smuggling activity was found preceding the implementation of the ivory ban.

The rise of automated trading systems has made stock trading more accessible and convenient, reducing the link between traditional illiquidity measures and stock returns. However, empirical data in China’s stock market shows conflicting results. We find a significantly positive correlation between intraday illiquidity and future returns in China’s stock market. We offer that the pricing ability of this intraday illiquidity originates from the correlation between trading activity and intraday return. This finding provides compelling out-of-sample evidence for the debate regarding the pricing of the Amihud (2002) measure in the U.S. market. Additionally, we create an intradayreturn illiquidity factor that outperforms Liu, Stambaugh, and Yuan (2019) sentiment factors in China’s stock market.

Emissions data collection and management are crucial to operationalizing an emissions trading scheme (ETS). Regulators need high-quality data to allocate emissions allowances and monitor compliance. However, collecting such data can be costly, challenging various actors. Emitters may misreport data, weighing the cost against their interest, while governments may struggle with limited resources in managing compliance. Third-party verification is a solution but tends to be ineffectual and causes new problems unless with sufficient oversight and support. This quality-cost dilemma becomes even more complex in multi-level ETSs, as in China’s national ETS (NETS). Despite increased regulatory efforts to address data challenges, there remains a lack of in-depth legal analysis on the relationship between data quality and cost. This Article establishes a three-element analytical framework—data quality, cost concerns, and intergovernmental relations in data management—to shed light on the nuances of data regulation. Using China’s NETS as a case study, we gain a deeper understanding of the three elements in a specific jurisdiction and the legal institutions, practices, and challenges involved. Governments, emitters, and third-party verifiers each have unique roles and limitations in this process. We suggest legal and regulatory strategies for finding solutions. Our actor-centered analytical model and practical recommendations for the NETS can serve as a valuable guide for jurisdictions facing similar data challenges.

Empowered by comprehensive data on smartphone fund investors’ trading and browsing histories from a Chinese financial company, we explore the role of investors’ financial attention in influencing the relationship between unrealized profits and investors’ selling decisions. Against a backdrop in which retail investors are not attentive to their portfolio information, we find supportive evidence suggesting that investors exhibit realization preference when we condition on days when investors pay financial attention. Further, we show that failing to account for investors’ financial inattention may induce observers to reject the realization-preference hypothesis. This paper also offers insights into the determinants of financial attention and the influence of financial attention on investor disposition effect.

Based on the expected utility under uncertain probability distribution, we explore whether the ambiguity of individual stocks is priced in China’s A-share market and the mechanism behind the ambiguity premium phenomenon. Theoretically, when the asset price is in a specific price range, investors with ambiguity aversion do not participate in the transaction of the asset. As the ambiguity of assets increases, investors with high ambiguity aversion withdraw from the market, and investors with low ambiguity aversion remain in the market (the limited market participation phenomenon); investors who remain in the market due to lower ambiguity aversion are also willing to accept a low ambiguity premium. Empirically, we use "the volatility of the distributions of daily stock returns within a month" to measure monthly ambiguity; and find that (1) the equal-weighted average returns of the most ambiguous portfolios (top 20%) are significantly lower 1.38% than those of the least ambiguous portfolios (bottom 20%); (2) ambiguity still significantly negatively affects the cross-sectional stock return after controlling for common firm characteristics; (3) the higher the ambiguity, the lower the future trading activity, the empirical results are consistent to the theoretical predictions. Those findings reveal the mechanism of the negative ambiguity premium in the A-share market, provide new ideas for further building a factor pricing model suitable for the A-share market, and provide a fresh perspective for preventing systemic financial risk.

Exploiting a unique market-oriented media reform initiated in 1996 in China, we investigate the role of media environment in affecting firm behaviour. We find robust evidence that market-oriented media environment is conductive to firm innovation, with the reform promoting patent quantity and quality substantially. The effect is more pronounced for firms with higher information asymmetry. Matching firm data with 1.3 million news reports, we find the market-oriented media reform significantly improves the criticalness and unbiasedness of news coverage and shapes an innovation-friendly environment. Our findings highlight economic outcomes of relaxing media control and underline substantial gains from deepening the reform.

Using a proprietary granular database of a major Chinese stock exchange, we examine heterogenous investors’ trading dynamics around one of the most important macro announcements of the Chinese central bank, the monthly release of monetary aggregates data. Exploiting the trading heterogeneity across assets and across investor types, we find that before announcements, institutional investors reduce their aggregate stock exposure while over-weighing riskier stocks of smaller caps, whereas retail investors provide liquidity by increasing their aggregate stock exposure and avoiding the riskier stocks. Large retail and institutional investors become more informed before announcements and trade in correct directions consistent with the news surprises after announcements, while smaller retail investors trade in opposite directions. While the institutional investors accumulate positive returns with risk compensated, the market realizes sizable pre-announcement equity premium.