Journal of Banking & Finance最新文献

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Predicting financial stability with TopicGPT: Insights from corporate and central bank communications 用主题gpt预测金融稳定：来自企业和央行沟通的见解

IF 3.8 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance

Pub Date : 2025-12-02 DOI: 10.1016/j.jbankfin.2025.107598

Christian Fieberg , Matthies Hesse , Gerrit Liedtke , Adam Zaremba

Can generative artificial intelligence (GenAI) help us predict financial stability? To address this question, we employ TopicGPT, a prompt-based framework for topic modeling powered by large language models. By analyzing over 238,000 corporate earnings calls and 4300 Federal Reserve speeches over the period from 2002 to 2023, we combine microeconomic and macroeconomic perspectives to forecast key measures of financial stability. TopicGPT’s ability to generate interpretable and tailored topics improves predictions for systemic risk measures, such as the National Financial Conditions Index and a capital shortfall, outperforming traditional models, particularly for long-term horizons. The two data sources complement each other: earnings calls provide dynamic, firm-specific insights critical for short-term forecasts, while Fed speeches highlight systemic risks, offering a long-term perspective. Together, they identify critical themes – such as economic conditions, debt management, and the housing market – and enable real-time risk assessment.

生成式人工智能（GenAI）能否帮助我们预测金融稳定？为了解决这个问题，我们使用了TopicGPT，这是一个基于提示的主题建模框架，由大型语言模型提供支持。通过分析2002年至2023年期间超过238,000个公司财报电话会议和4300个美联储演讲，我们结合微观经济和宏观经济观点来预测金融稳定的关键指标。TopicGPT生成可解释和定制主题的能力提高了对系统性风险指标（如国家金融状况指数和资本短缺）的预测，优于传统模型，特别是在长期范围内。这两种数据来源相辅相成：财报电话会议提供了对短期预测至关重要的动态、特定于公司的见解，而美联储的讲话则强调了系统性风险，提供了长期前景。它们共同确定关键主题——如经济状况、债务管理和住房市场——并实现实时风险评估。

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引用次数: 0

Media reporting and asset pricing models 媒体报道与资产定价模型

IF 3.8 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance

Pub Date : 2025-11-25 DOI: 10.1016/j.jbankfin.2025.107596

Heiko Jacobs, Alexander Lauber

Recent literature shows that investors’ revealed beliefs often point to the use of comparatively simple valuation approaches or heuristics rather than complex models with several dimensions of systematic risk to price assets. Against this background, we comprehensively analyze how different stock-level performance measures affect media tone in firm-specific articles in several major markets. While the realized risk-adjusted abnormal returns of all tested models are positively related to media sentiment, the CAPM-adjusted return as well as the raw stock return have the strongest impact in direct comparisons. Overall, the results are most consistent with the conjecture that, on average, reporting tends to be influenced more by straightforward valuation approaches than by risk adjustments derived from multi-factor asset pricing models. Further largely supportive evidence comes from return decompositions, subsample tests, reporting about mutual funds as well as from survey results.

最近的文献表明，投资者揭示的信念往往指向使用相对简单的估值方法或启发式，而不是使用具有多个系统性风险维度的复杂模型来为资产定价。在此背景下，我们全面分析了不同的股票水平表现指标如何影响几个主要市场中特定公司文章的媒体基调。虽然所有测试模型的风险调整后的实际异常收益与媒体情绪呈正相关，但在直接比较中，capm调整后的收益和原始股票收益的影响最大。总体而言，结果与以下猜想最为一致：平均而言，报告往往更容易受到直接估值方法的影响，而不是受到来自多因素资产定价模型的风险调整的影响。进一步的大部分支持性证据来自回报分解、子样本测试、关于共同基金的报告以及调查结果。

引用次数: 0

Active fund management when ESG matters ESG重要时积极的基金管理

IF 3.8 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance

Pub Date : 2025-11-20 DOI: 10.1016/j.jbankfin.2025.107597

Doron Avramov , Si Cheng , Andrea Tarelli

This paper develops and tests an equilibrium model of active fund management with ESG considerations. Heterogeneous sustainability preferences lead fund managers to intensify information acquisition on assets across the ESG spectrum, broadening the scope of active management. This information channel enhances price informativeness, lowers discount rates, and increases portfolio deviation from benchmarks. The model predicts a negative and concave ESG-expected return relation, stronger for green assets and weaker for brown assets. Using data on U.S. mutual funds and stocks from 2007–2021, we find supporting evidence based on price informativeness and the implied cost of equity capital.

本文建立并检验了一个考虑ESG因素的主动基金管理均衡模型。异质性可持续性偏好导致基金经理加强对ESG资产的信息获取，扩大了主动管理的范围。这种信息渠道提高了价格的信息量，降低了贴现率，并增加了投资组合与基准的偏差。该模型预测了esg -预期收益的负凹关系，绿色资产的esg -预期收益较强，棕色资产的esg -预期收益较弱。利用2007-2021年美国共同基金和股票的数据，我们发现了基于价格信息性和隐含权益资本成本的支持证据。

引用次数: 0

Bidder opportunism, familiarity, and the M&A payment choice 竞标者机会主义、熟悉度和并购支付选择

IF 3.8 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance

Pub Date : 2025-11-19 DOI: 10.1016/j.jbankfin.2025.107595

Nils Lohmeier, Christoph Schneider

A familiarity bias of target shareholders allows bidders to opportunistically choose the payment method in mergers and acquisitions. We employ the Stambaugh, Yu and Yuan (2015) mispricing score to identify overvalued bidders, reconfirming that overvaluation is a central driver of the payment choice. Using an instrumental variable based on exogenous price pressure, we provide causal evidence for bidder opportunism. Further analyses show that target shareholders more familiar with the bidder are more likely to accept equity despite particularly adverse market reactions. Our results suggest that behavioral biases of shareholders contribute to the transmission of stock market inefficiencies to the market for corporate control.

目标股东的熟悉偏向使得竞标者在并购中机会主义地选择支付方式。我们采用Stambaugh， Yu和Yuan（2015）的错误定价评分来识别被高估的投标人，再次确认高估是支付选择的核心驱动因素。使用基于外生价格压力的工具变量，我们提供了投标人机会主义的因果证据。进一步的分析表明，尽管市场反应特别不利，但与竞标者更熟悉的目标股东更有可能接受股权。我们的研究结果表明，股东的行为偏差有助于将股票市场的低效率传导到公司控制权市场。

引用次数: 0

Psychological anchoring effect and cross section of cryptocurrency returns 心理锚定效应与加密货币收益的横截面

IF 3.8 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance

Pub Date : 2025-11-14 DOI: 10.1016/j.jbankfin.2025.107592

Yuecheng Jia , Betty Simkins , Shu Yan , Hongyu Zhang , Jiangyu Zhao

This paper investigates whether investors’ anchoring bias affects cryptocurrency returns. We use the nearness to the 52-week high (

N e a r n e s s_{52}

) as a proxy for anchoring behavior and document a significant positive association between

N e a r n e s s_{52}

and subsequent cross-sectional cryptocurrency returns. The relationship remains robust after controlling for standard return predictors and employing alternative econometric specifications. A value-weighted spread portfolio, cANCHOR, which goes long on cryptocurrencies with high

N e a r n e s s_{52}

and short on those with low

N e a r n e s s_{52}

, generates an average return of around 130 basis points per week. Additional analyses help rule out competing explanations based on risk exposure or market frictions. Augmenting the benchmark three-factor model of Liu, Tsyvinski, and Wu (2019) with our cANCHOR factor yields a novel four-factor model that better explains cross-sectional cryptocurrency returns and outperforms alternative approaches proposed in the literature.

本文调查了投资者的锚定偏见是否会影响加密货币的回报。我们使用接近52周高点（Nearness52）作为锚定行为的代理，并记录了Nearness52与随后的横断面加密货币回报之间的显著正相关。在控制标准收益预测因子和采用替代计量经济规范后，关系仍然稳健。cANCHOR是一个价值加权价差投资组合，它做多接近度52高的加密货币，做空接近度52低的加密货币，每周的平均回报率约为130个基点。额外的分析有助于排除基于风险敞口或市场摩擦的相互矛盾的解释。用cANCHOR因子增强Liu， Tsyvinski和Wu（2019）的基准三因素模型，可以产生一个新的四因素模型，更好地解释横截面加密货币回报，并且优于文献中提出的替代方法。

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引用次数: 0

PayTech on BigTech platforms PayTech在BigTech平台上

IF 3.8 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance

Pub Date : 2025-11-05 DOI: 10.1016/j.jbankfin.2025.107585

Jonathan Chiu , Thorsten V. Koeppl

Why do BigTech platforms introduce payment services? And do their users benefit? Digital platforms often run business models where activities on the platform generate data that can be monetized off the platform. The platform then trades off the value of such data against the cost that arises from subsidizing activities in order to compensate users for their loss of privacy. The way data interact with payments determines whether payments are introduced and how the introduction impacts users. When data help to provide better payments (data-driven payments), platforms have too little incentives to introduce payments, even though users benefit. Introduction is more likely when payments also generate additional data (payment-driven data), but the adoption of better payments may then hurt users.

为什么大科技平台会引入支付服务？他们的用户从中受益了吗？数字平台通常运行的商业模式是，平台上的活动产生的数据可以在平台外货币化。然后，该平台将这些数据的价值与补贴活动所产生的成本进行权衡，以补偿用户失去的隐私。数据与支付互动的方式决定了支付是否被引入，以及这种引入如何影响用户。当数据有助于提供更好的支付（数据驱动的支付）时，即使用户受益，平台也没有太多动力来引入支付。当支付也产生额外的数据（付费驱动的数据）时，引入更有可能，但采用更好的支付方式可能会伤害用户。

引用次数: 0

Housing booms and local capital misallocation 房地产繁荣和地方资本配置不当

IF 3.8 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance

Pub Date : 2025-11-01 DOI: 10.1016/j.jbankfin.2025.107584

Yu Liu , Peng Zhao , Xiaoxue Zhao

How does a booming housing market crowd out credit access of firms and distort resource allocation in the real economy? This paper relies on a housing purchase restriction (HPR) policy in Chinese cities as a natural experiment and shows that an exogenous reduction in housing demand and a halt on housing price growth significantly improved local firms’ access to credit and lowered their financial costs. In addition, because the credit relaxation particularly affected firms that were ex ante more constrained, the policy significantly reduced cross-firm capital misallocation within treated cities and positively affected industrial productivity. We estimate that the HPR policy overall led to a 2% improvement in the total factor productivity (TFP) of Chinese industrial firms. We present empirical evidence to demonstrate that these real effects of a housing market decline can be rationalized by bank capital constraints and a significant crowding-out effect of households’ mortgage loans and credit to local governments, backed by local land sales revenue, on credit to firms.

繁荣的房地产市场是如何排挤企业的信贷渠道并扭曲实体经济中的资源配置的？本文以中国城市的住房限购政策作为自然实验，表明外生住房需求的减少和房价增长的停止显著改善了当地企业获得信贷的机会，降低了他们的财务成本。此外，由于信贷放松特别影响了先前受到更多约束的企业，该政策显著减少了受影响城市内企业间资本错配，并对工业生产率产生了积极影响。我们估计，HPR政策总体上使中国工业企业的全要素生产率（TFP）提高了2%。我们提出的经验证据表明，住房市场下滑的这些实际影响可以通过银行资本约束和家庭抵押贷款和地方政府信贷（以地方土地销售收入为支持）对企业信贷的显著挤出效应来合理化。

引用次数: 0

Uncertain Text and Price Reactions to Earnings Releases 不确定的文本和价格对收益发布的反应

IF 3.8 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance

Pub Date : 2025-11-01 DOI: 10.1016/j.jbankfin.2025.107580

Eunpyo Hong , Badrinath Kottimukkalur , Joonki Noh

We explore how the uncertain text in 10-K/Qs, a form of soft information, affects the stock price reactions to subsequent earnings releases that contain hard and quantitative information. We find that more uncertain language in 10-K/Qs leads to stronger immediate price reactions to earnings surprises but weaker post-earnings announcement drifts. Firms with higher text uncertainty in 10-K/Qs also attract greater institutional attention and more intense trading activity by sophisticated investors around earnings announcements. These findings suggest that firms using more uncertain language in regulatory filings have higher fundamental uncertainty and attract more attention from attention-constrained investors.

我们探讨了10-K/ q中的不确定文本（软信息的一种形式）如何影响股票价格对包含硬信息和定量信息的后续收益发布的反应。我们发现，10-K/ q中更多不确定的语言导致对收益意外的直接价格反应更强，但收益公告后的波动更弱。在10-K/ q中文本不确定性较高的公司也吸引了更多的机构关注，并在收益公告周围吸引了经验丰富的投资者更激烈的交易活动。这些发现表明，在监管文件中使用更多不确定语言的公司具有更高的基本不确定性，并吸引更多注意力有限的投资者的关注。

引用次数: 0

Crowded spaces and anomalies 拥挤的空间和异常

IF 3.8 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance

Pub Date : 2025-10-31 DOI: 10.1016/j.jbankfin.2025.107579

Ludwig Chincarini , Renato Lazo-Paz , Fabio Moneta

This paper investigates the relation between crowded trades, those in which many investors hold the same stocks possibly exhausting their liquidity provision, and future stock returns on a set of well-known stock market anomalies. We find that anomaly risk-adjusted returns are primarily generated by the most (least) crowded stocks for the long-leg (short-leg) portfolio. Moreover, we find that our results remain significant after publication dates. We hypothesize that crowded equity positions in anomaly stocks increase institutional investors’ exposure to crash risk. Our findings are consistent with this hypothesis and suggest that crowding adds a new consideration to the limits of arbitrage.

本文研究了在一组众所周知的股票市场异常情况下，众多投资者持有同一只股票可能耗尽其流动性供应的拥挤交易与未来股票收益之间的关系。我们发现，风险调整后的异常收益主要是由长腿（短腿）投资组合中最（最少）拥挤的股票产生的。此外，我们发现我们的结果在发表日期之后仍然显着。我们假设在异常股票中拥挤的股票头寸增加了机构投资者对崩溃风险的暴露。我们的研究结果与这一假设一致，并表明拥挤增加了对套利限制的新考虑。

引用次数: 0

Time-varying repayment contracts for financial resilience in mortgage lending 抵押贷款金融弹性的时变还款合同

IF 3.8 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance

Pub Date : 2025-10-24 DOI: 10.1016/j.jbankfin.2025.107583

Chung Mai , Harald Scheule

This paper develops time-varying repayment mortgage contract designs based on borrower income expectations and risk profiles over loan age. These contract designs differ between loans and are based on growing annuities. We benchmark these contracts to the traditional 30-year fixed-rate mortgage contracts. The proposed contract innovations reduce illiquidity but increase leverage due to payment delays. The combined effects reduce the probability of default, systematic risk, and regulatory capital. Due to the risk reduction, lenders can increase the gross return on regulatory capital by 10 %, or alternatively, borrowers may benefit from credit spreads that are 17 basis points lower. Overall, our contracts enhance the resilience of mortgage markets.

G01; G20; G21; C51; C55

本文基于借款人的收入预期和贷款年龄的风险特征，开发了时变还款抵押合同设计。这些合同设计因贷款而异，并基于不断增长的年金。我们以传统的30年期固定利率抵押贷款合同为基准。拟议的合同创新减少了流动性不足，但增加了由于付款延迟造成的杠杆。综合效应降低了违约概率、系统性风险和监管资本。由于风险降低，贷款人可以将监管资本的总回报率提高10%，或者，借款人可以从信贷息差降低17个基点中受益。总体而言，我们的合同增强了抵押贷款市场的弹性。20国集团(G20);G21;C51单片机;C55

引用次数: 0

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