本文基于研发“投入—产出”弹性构建研发回报指标，发现制造业技术前沿化提升了企业研发回报。结构分析显示，行业与国际技术前沿均促进研发回报，其中国际前沿作用更显著。作用机制体现为投融资协同与供需协同两个方面。异质性研究表明，高精尖行业/企业对技术前沿化敏感度更高；创新型产业集群及制度保障完善区域的促进效应更明显。经济后果分析发现，技术前沿化对研发回报的提升存在长期影响，其通过创新成果转化提高企业生产效率与经营业绩。

本文以沪深港通交易制度实施为准自然实验，选取2011-2023年沪深A股上市公司数据，探究金融开放对企业产品竞争力的影响机制。研究发现：（1）沪深港通交易制度的实施显著提升了企业的产品竞争力，此结论经过一系列稳健性检验后仍成立；（2）机制检验表明，沪深港通交易制度主要通过两条路径来提升企业产品竞争力，一是竞争压力倒逼效应，推动企业实施产品差异化战略和提升创新能力，重塑竞争优势。二是资源配置效应，通过优化人力资本结构，改善融资环境和拓展出口渠道，帮助企业实现要素升级，进而增强产品竞争力；（3）异质性检验发现，政策效果在资本密集型行业、盈利能力低及环境信息披露质量低样本中更为显著。本文丰富了金融开放对企业影响的实证研究，为党的二十大提出的“推进高水平制度型开放”提供了微观证据。

Using unique account-level data from a leading Chinese fintech platform, we investigate how financial influencers, the key information intermediaries in social finance, attract followers through a process of social transmission bias. We document a robust performance-following pattern wherein retail investors overextrapolate influencers’ past returns rather than rational learning in the social network from their past performance. The transmission bias is amplified by two mechanisms: (1) influencers’ active social engagement and (2) their index fund-heavy portfolios. Evidence further reveals influencers’self-enhancing reporting through selective performance disclosure. Crucially, the dynamics ultimately increase risk exposure and impair returns for follower investors.

A strong reputation is a cornerstone of corporate finance theory, widely believed to relax financial constraints and lower capital costs. We challenge this view by identifying an ‘reputation paradox’: under modern risk-sensitive regulation, for firms with long-term liabilities, a better reputation may paradoxically increase capital strain. We argue that the improvement of firm’s reputation alters customer behavior , , which extends liability duration and amplifies measured risk. By using the life insurance industry as an ideal laboratory, we develop an innovative framework that integrates LLMs with actuarial cash flow models, which confirms that the improved reputation increases regulatory capital demands. A comparative analysis across major regulatory regimes—C-ROSS, Solvency II, and RBC—and two insurance products, we further demonstrate that improvements in reputation affect capital requirements unevenly across product types and regulatory frameworks. Our findings challenge the conventional view that reputation uniformly alleviates capital pressure, emphasizing the necessity for insurers to strategically align reputation management with solvency planning.

This paper provides evidence that some seasoned equity offerings are motivated by public information. We test this channel in the supply chain setting, where supplier managers are more attentive than outside investors to customer news. We find that supplier firms are more likely to issue seasoned equity when their customer firms have negative earnings surprises. The results are mitigated when there is common scrutiny on the customer-supplier firm pairs by outside investors and analysts. Furthermore, long-run stock market performance appears to be worse for firms that issue seasoned equity following the negative earnings surprise of their customer firms.

This study examines the economic consequences of China’s Three-Red-Lines policy—introduced in 2021 to cap real estate developers’ leverage by imposing strict thresholds on debt ratios and liquidity. Developers breaching these thresholds experienced sharp declines in financing, land acquisitions, and financial performance, with privately-owned developers disproportionately affected relative to state-owned firms. Using granular project-level data, we document significant drops in sales and a demand shift from private to state-owned developers. The policy also reduced local governments’ land sale revenues, prompting greater reliance on hidden local government financing vehicles for land purchases. The policy induced broad structural changes in China’s housing and land markets.

摘 要：随着互联网与电子贸易的发展，用户的个人隐私保护机制已成为当今社会的热点议 题之一。本文探讨《中华人民共和国个人信息保护法》实施对企业创新的影响。选取2021年《个 人信息保护法》的实施作为准自然实验以构建双重差分模型，并以机构投资者和分析师关注度为 中介变量构建机制分析。在《个人信息保护法》实施后，实验组比对照组的每年专利数量增量减 少了 12.4%。《个人信息保护法》的实施短期内对企业获职数据的能力造成限制，因此会抑制数 字化转型程度较高的企业的创新活动。此外，机制分析表明《个人信息保护法》通过抑制机构持 股比例和分析师关注度进而抑制企业创新，这一结论与异质性检验结果一致，即尽管长远看有助 于构建健康数字经济环境，该抑制效应短期内在国有高数字化转型水平企业及非四大审计的企业 中更为显著。

We study the influence of investor attention on mutual fund investors' fund selection and fund managers' portfolio choice. Using the Google Search Volume Index to measure investor attention on individual stocks, we find fund investors tend to direct more capital to mutual funds holding more high-attention stocks; fund managers tend to perform window-dressing trading to increase the portfolio holdings of high-attention stocks displayed to investors. Our results suggest that funds, particularly those with strong incentives, strategically trade on stock attention to attract investor flows. This strategic trading behaviour is also associated with fund underperformance and leads to larger non-fundamental volatility of holding stocks.

We construct a novel risk-based similarity peer network by applying machine learning techniques to extract a comprehensive set of disclosed risk factors from firms' annual reports. We find that a firm's future returns can be significantly predicted by the past returns of its risk-similar peers, even after excluding firms within the same industry. A long-short portfolio, formed based on the returns of these risk-similar peers, generates an alpha of 84 basis points per month. This return predictability is particularly pronounced for negative-return stocks and those with limited investor attention, suggesting that the effect is driven by slow information diffusion across firms with similar risk exposures. Our findings highlight that the risk factors disclosed in 10-K filings contain valuable information that is often overlooked by investors.

We utilize the Bayesian model scan approach to examine the best performing models in a set of 15 factors discovered in the literature, plus principal components (PCs) of anomalies unexplained by the initial factors in the Chinese A-share market. The Bayesian comparison of approximately eight million models shows that HML, MOM, IA, EG, PEAD, SMB, VMG,PMO, plus the four PCs, PC1, PC6, PC7, PC8 are the best supported specification in terms of marginal likelihoods and posterior model probabilities. We also find that the best model outperforms existing factor models in terms of pricing tests and out-of-sample Sharpe ratio.