This study reconsiders the timing of the equity risk factors by using the flexible neural networks specified for image recognition to determine the timing weights. The performance of each factor is visualized to be standardized price and volatility charts and `learned' by flexible image recognition methods with timing weights as outputs. The performance of all groups of factors can be significantly improved by using these ``deep learning--based'' timing weights. In addition, visualizing the volatility of factors and using deep learning methods to predict volatility can significantly improve the performance of the volatility-managed portfolio for most categories of factors. Our further investigation reveals that the timing success of our method hinges on its ability in identifying ex ante regime switches such as jumps and crashes of the factors and its predictability on future macroeconomic risk.

要建立“长钱长投”的投资者市场，企业优质的文本披露必不可少。本文基于政企双向利益交换视角，利用深度学习技术（Word2Vec模型）构建年报文本可读性指标，检验寻租行为对企业年报文本可读性的影响。研究发现，寻租行为显著降低了企业年报文本可读性。在机制分析阶段，研究证明了寻租行为会通过企业自利行为和管理者自利行为影响年报文本可读性，同时排除了官员主动敲诈能促进寻租对可读性负面影响的情况。异质性分析发现，内部治理手段、市场监督力量以及政府治理政策均能有效抑制寻租对可读性的负面影响。本文从信息披露视角拓展了寻租行为的经济后果研究，为优化资本市场信息披露监管和深化反腐治理提供了理论依据与实践启示。

在专精特新企业培育工作持续推进和投融资体制改革不断深化的大背景下，从专精特新认定的视角探讨其对企业的投资促进效应具有重大意义。本文以2015—2023年中国A股上市公司和新三板挂牌公司为样本，将2019年开始分批实施的国家级专精特新“小巨人”认定为准自然实验，实证检验了专精特新认定对企业投资效率的影响、作用机制和经济后果。研究发现，专精特新认定会显著提升企业投资效率，且这一效应在投资过度企业、小规模企业、北交所和新三板上市、地区政策响应度高和行业“小巨人”密集度高的企业中更为显著。机制分析表明，专精特新认定通过缓解信息不对称、降低代理成本和抑制经营不确定性，进而提升了企业的投资效率。进一步研究发现，专精特新认定抑制了企业投融资期限错配，提高了企业价值，并推动了地区资本配置效率的提升。此外，专精特新“小巨人”企业对未获得认定的企业不存在挤出效应；失去认定资格的企业对同行其他企业非效率投资具有威慑作用；专精特新认定存在供应链溢出效应。本文研究有助于揭示专精特新认定对企业投资效率的影响及其溢出效应，为进一步培育专精特新企业，发挥投资对优化供给结构的关键性作用和发展新质生产力提供有益参考。

This paper investigates the impact of curation algorithms through the lens of stock market dynamics. By innovatively incorporating the dynamic interactions between social media platforms, investors, and stock markets, we construct the Social-Media-augmented Artificial Stock marKet (SMASK) model under the agent-based computational framework. Our findings reveal that curation algorithms, by promoting polarized and emotionally charged content, exacerbate behavioral biases among retail investors, leading to worsened stock market quality and investor wealth levels. Moreover, through our experiment on the debated topic of algorithmic regulation, we find limiting the intensity of these algorithms may reduce unnecessary trading behaviors, mitigates investor biases, and enhances overall market quality. This study provides new insights into the dual role of curation algorithms in both business ethics and public interest, offering a quantitative approach to understanding their broader social and economic impact.

We provide a novel explanation for the geographic dispersion of borrower-lender relationships based on information frictions rather than competition. Firms may strategically select distant banks to increase lenders’ information production costs, securing larger loans under information-insensitive contracts. Our model predicts that higher-quality firms prefer distant lenders for information-insensitive contracts, while lower-quality firms use local lenders with information-sensitive terms. Using transaction-level data from a major Chinese bank, we find strong empirical support: higher-rated firms exhibit greater propensity for distant borrowing; local loans show stronger negative correlation between amounts and interest rates; and distant loan pricing demonstrates weaker sensitivity to defaults.

We develop an information choice model where information costs are sticky and co-move with firm-level intrinsic uncertainty as opposed to temporal variations in uncertainty. Incorporating analysts' forecasts, we predict a negative relationship between information costs and information acquisition, as proxied by the predictability of analysts' forecast biases. Finally, the model shows a contrasting pattern between information acquisition and intrinsic and temporal uncertainty, where intrinsic uncertainty strengthens return predictability of analysts' biases through the information cost channel, while temporal uncertainty weakens it through the information benefit channel. We empirically confirm these opposing relationships that existing theories struggle to explain.

Why is price momentum absent in China? Since momentum is commonly considered arising from investors’ under-reaction to fundamental news, we decompose monthly stock returns into news- and non-news-driven components and document a news day return continuation along with an offsetting non-news day reversal in China. The non-news day reversal is particularly strong for stocks with high retail ownership, relatively less recent positive news articles, and limits to arbitrage. Evidence on order imbalance suggests that stock returns overshoot on news days due to retail investors' excessive attention-driven buying demands, and mispricing gets corrected by institutional investors on subsequent non-news days. To avoid this tug-of-war in stock price, we use a signal that directly captures the recent news performance and re-document a momentum-like underreaction to fundamental news in China.

Reputation is widely regarded as a stabilizing factor in financial institutions, reducing capital constraints and enhancing firm resilience. However, in the insurance industry, where capital requirements are shaped by solvency regulations and policyholder behavior, the effects of reputation on capital management remain unclear. This paper examines the unintended consequences of reputation in insurance asset-liability management, focusing on its impact on capital allocation. Using a novel reputation risk measure based on large language models (LLMs) and actuarial models, we show that reputation shifts influence surrender rates, altering capital requirements. While higher reputation reduces surrender risk, it increases capital demand for investment-oriented insurance products, whereas protection products remain largely unaffected. These findings challenge the conventional wisdom that reputation always eases capital constraints, highlighting the need for insurers to integrate reputation management with capital planning to avoid unintended capital strain.

Using “the Measures for the Administration of Bank Wealth Management (henceforth BWM) Funds Sales” as an exogenous shock in fund distribution channels in Chinese BWM industry, we investigate the impact of non-affiliated distribution on fund performance. We find that the adoption of non-affiliated distribution brokers has a positive effect on BWM fund performance. We further find that the effect is more pronounced when the non-affiliated distribution broker has more market power and when the fund issuer has better governance. We interpret our findings to indicate that non-affiliated distribution brokers alleviate the agency problems of fund managers by introducing both ex-ante and ex-post monitoring, highlighting the role of non-affiliated distribution brokers as an external governance mechanism in wealth management industry.

This study empirically investigates the impact of supply chain network centrality on corporate greenwashing behavior. By constructing supply chain networks of Chinese A-share listed companies, we find a strong positive correlation between supply chain network centrality and corporate greenwashing behavior, with an increase of approximately 6.20%. The paper identifies the underlying mechanism as the contagion of the green bandwagon effect within the supply chain, which is observed specifically in the downstream network, particularly among corporate-customers. Additionally, we observe that the positive effects are more pronounced in companies with lower information asymmetry, as well as in labor- and capital-intensive industries and regions with disadvantaged economic conditions. These findings offer important insights for improving corporate environmental responsibility and curbing greenwashing practices.