Quarterly Review of Economics and Finance最新文献

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Are safe-haven assets really safe? Heterogeneity under economic, political and climate risks 避险资产真的安全吗？经济、政治和气候风险下的异质性

IF 3.1 3区经济学 Q1 ECONOMICS

Quarterly Review of Economics and Finance

Pub Date : 2025-12-04 DOI: 10.1016/j.qref.2025.102088

Lijun Gao , Dongsheng Bei , Junda Wu , Kun Guo , Xianhua Wei

In recent years, rising geopolitical instability, intensifying climate risks, and recurrent systemic shocks have heightened global demand for safe-haven assets. This study develops a novel time-varying Safe-Haven Index (SHI) based on the TVP-VAR model and quantile regression to evaluate the hedging effectiveness of traditional safe-haven assets against systemic risk. The empirical results reveal the dynamic evolution of tail-risk spillovers and the corresponding network structures under different market conditions; extreme shock events, such as the pandemic, lead to structural reversals in the spillover network; moreover, the spillover effects across different quantiles exhibit heterogeneity and asymmetry. Overall, the findings highlight the dynamic and context-dependent nature of safe-haven properties, providing new insights for policymakers to strengthen climate-related macroprudential regulation and for investors to construct diversified, climate-resilient hedging portfolios.

近年来，地缘政治不稳定加剧、气候风险加剧以及经常性系统性冲击增加了全球对避险资产的需求。本文基于tpv -var模型和分位数回归，建立了一种新的时变避险指数（SHI）来评估传统避险资产对系统性风险的对冲效果。实证结果揭示了不同市场条件下尾部风险溢出及其网络结构的动态演化；大流行等极端冲击事件导致溢出网络出现结构性逆转；此外，不同分位数的溢出效应表现出异质性和不对称性。总体而言，研究结果突出了避险资产的动态和环境依赖性质，为政策制定者加强与气候相关的宏观审慎监管和投资者构建多样化、气候适应型对冲投资组合提供了新的见解。

引用次数: 0

Timing commonality in stock market misvaluation – Evidence from hedge funds 股市估值错估的时间共性——来自对冲基金的证据

IF 3.1 3区经济学 Q1 ECONOMICS

Quarterly Review of Economics and Finance

Pub Date : 2025-12-04 DOI: 10.1016/j.qref.2025.102085

Yao Zheng , Eric Osmer , Dingding Zu

This study investigates the ability of hedge fund managers to exploit systematic stock market misvaluation through dynamic adjustments of market exposure. Our findings reveal that managers increase exposure during periods of widespread underpricing, capitalizing on valuation anomalies to enhance returns. The out-of-sample analysis demonstrates a 4 % annual performance gap between top and bottom misvaluation timers, which is robust across subperiods and excluding crisis periods. Additional analysis finds that misvaluation-timing ability is primarily driven by incentive structures, such as high incentive fees and high-water mark provisions, and that younger funds demonstrate superior timing capabilities.

本研究探讨对冲基金经理人透过动态调整市场风险敞口，利用系统性股市错估的能力。我们的研究结果表明，管理者在普遍定价过低的时期增加风险敞口，利用估值异常来提高回报。样本外分析表明，顶部和底部错误估值计时器之间的年度绩效差距为4 %，这在子时期和排除危机时期都是稳健的。另外的分析发现，误估择时能力主要是由激励结构驱动的，例如高激励费用和高水位规定，而较年轻的基金表现出优越的择时能力。

引用次数: 0

Bank government ownership and reaction to SVB collapse: Evidence from emerging markets 银行政府所有权和对瑞典对外银行崩溃的反应：来自新兴市场的证据

IF 3.1 3区经济学 Q1 ECONOMICS

Quarterly Review of Economics and Finance

Pub Date : 2025-12-03 DOI: 10.1016/j.qref.2025.102086

Narjess Boubakri, Efe Cotelioglu, Anis Samet

This study examines the impact of government ownership on bank stock valuations in emerging markets following the collapse of Silicon Valley Bank (SVB). Using 298 banks across 37 emerging markets, we find that banks with higher levels of government ownership experienced smaller declines in stock prices post-SVB collapse. Our results remain robust after controlling for bank-level variables and potential endogeneity concerns. One potential channel for this relationship is through better credit ratings: banks with government ownership tend to have higher government support ratings and better overall ratings and demonstrate a more favorable reaction to the SVB collapse. Our findings highlight the importance of government ownership and financial soundness in mitigating the adverse effects of financial shocks on bank valuations.

本研究考察了在硅谷银行（SVB）倒闭后，政府所有权对新兴市场银行股票估值的影响。我们对37个新兴市场的298家银行进行了分析，发现政府持股水平较高的银行在俄罗斯对外银行崩溃后股价跌幅较小。在控制了银行层面的变量和潜在的内生性问题后，我们的结果仍然稳健。这种关系的一个潜在渠道是通过更好的信用评级：拥有政府所有权的银行往往拥有更高的政府支持评级和更好的整体评级，并且对俄罗斯对外银行的崩溃表现出更有利的反应。我们的研究结果强调了政府所有权和财务健全性在减轻金融冲击对银行估值的不利影响方面的重要性。

引用次数: 0

Does mining activity drive crash risks in bitcoin? 挖矿活动会导致比特币崩盘吗？

IF 3.1 3区经济学 Q1 ECONOMICS

Quarterly Review of Economics and Finance

Pub Date : 2025-12-03 DOI: 10.1016/j.qref.2025.102082

Matteo Bonato , Riza Demirer , Rangan Gupta , Abeeb Olaniran

This paper explores the role of mining activity, proxied by growth rates of electricity consumption and cost of mining, as a driver of pricing inefficiencies in Bitcoin. Utilizing alternative measures of crash risk proxied by the realized negative coefficient of skewness and realized down-to-up volatility, derived from 5-minute intraday Bitcoin data, causality tests, along with sign analysis, captured by the estimates of partial average derivatives, provide evidence that mining activity can, in general, predict an increase in the entire conditional distribution of crash risk, with the strongest impact associated over the normal (median) to moderately high (upper quantiles) levels of risk. Despite the emergence of cryptocurrencies in international transactions and as an investment vehicle, our results suggest that decentralized mining process can contribute to inefficiencies in the pricing of Bitcoin, putting further doubt into the role of these assets as a medium of exchange, alternative to conventional assets.

本文探讨了挖矿活动的作用，以电力消耗和挖矿成本的增长率为代表，作为比特币定价效率低下的驱动因素。利用由已实现的负偏度系数和已实现的上下波动率（从5分钟比特币盘中数据中得出）所代表的崩溃风险替代度量，因果关系检验以及由部分平均衍生品估价值捕获的符号分析提供了证据，证明采矿活动通常可以预测崩溃风险的整个条件分布的增加。与正常（中位数）到中等高（上分位数）风险水平相关的最强影响。尽管加密货币在国际交易中出现，并作为一种投资工具，但我们的研究结果表明，去中心化的采矿过程可能导致比特币定价效率低下，这进一步质疑了这些资产作为交换媒介、替代传统资产的作用。

引用次数: 0

Sentiment, uncertainty, and bond return predictability 情绪、不确定性和债券回报的可预测性

IF 3.1 3区经济学 Q1 ECONOMICS

Quarterly Review of Economics and Finance

Pub Date : 2025-12-03 DOI: 10.1016/j.qref.2025.102083

Hankil Kang , Doojin Ryu

This study examines whether sentiment and uncertainty predict bond excess returns, with a particular focus on their interaction. Individually, both sentiment and uncertainty exhibit limited predictive power. While the interaction term between news-based sentiment and uncertainty does not predict bond excess returns, the interaction term constructed with market-based sentiment significantly enhances predictability. These findings indicate that the market-based sentiment–uncertainty interaction captures the dynamics of behavioral mispricing corrections, whereas the news-based measure primarily reflects macroeconomic confidence rather than behavioral sentiment, explaining its limited forecasting relevance.

本研究考察了情绪和不确定性是否能预测债券超额回报，并特别关注它们的相互作用。单独来看，情绪和不确定性都表现出有限的预测能力。基于新闻的情绪与不确定性之间的交互项不能预测债券超额收益，而基于市场的情绪构建的交互项显著增强了债券超额收益的可预测性。这些发现表明，基于市场的情绪-不确定性相互作用捕捉了行为错误定价修正的动态，而基于新闻的措施主要反映宏观经济信心而不是行为情绪，这解释了其有限的预测相关性。

引用次数: 0

Cross-shareholding and innovation: Do both sides benefit equally? 交叉持股与创新：双方是否受益均等？

IF 3.1 3区经济学 Q1 ECONOMICS

Quarterly Review of Economics and Finance

Pub Date : 2025-12-01 DOI: 10.1016/j.qref.2025.102065

Xinyu Liu , Liufang Xu

Innovation has becoming increasingly important in face of China’s decelerating productivity growth nowadays. At the same time, cross-shareholding has gradually emerged as a significant equity structure that could influence firms’ innovative behavior. This study examines the impact of cross-shareholding on innovation using data from Chinese listed firms spanning from 2003 to 2022. Employing difference-in-differences and propensity score matching approach, we find that cross-shareholding positively influences innovation in terms of patent applications and grants. The observed effects are primarily attributed to knowledge spillovers from high-knowledge to low-knowledge side and reduced financial constraints, while we find no evidence supporting the corporate governance and R&D input mechanisms. Furthermore, the benefits of cross-shareholding are not equally distributed between the involved parties. The effects are more pronounced for larger, high-tech, and state-owned enterprises, highlighting the importance of resources and strategic focus in driving innovation. This study offers critical insights for policymakers grappling with the multifaceted impacts of cross-shareholding.

面对当今中国生产率增长的减速，创新变得越来越重要。与此同时，交叉持股逐渐成为影响企业创新行为的重要股权结构。本文利用2003年至2022年中国上市公司的数据，考察了交叉持股对创新的影响。采用差异中的差异和倾向得分匹配方法，我们发现交叉持股对专利申请和授权方面的创新具有正向影响。上述效应主要归因于知识从高知识方向低知识方的溢出和资金约束的减少，而公司治理和研发投入机制没有证据支持。此外，交叉持股的利益在相关各方之间分配不均。对大型、高科技和国有企业的影响更为明显，凸显了资源和战略重点对推动创新的重要性。这项研究为政策制定者应对交叉持股的多方面影响提供了重要见解。

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引用次数: 0

Does marketplace lending provide liquidity during a crisis? 市场借贷能在危机期间提供流动性吗？

IF 3.1 3区经济学 Q1 ECONOMICS

Quarterly Review of Economics and Finance

Pub Date : 2025-12-01 DOI: 10.1016/j.qref.2025.102077

Miaoyin (Alexandra) Zhang

This paper examines the role of marketplace lending (MPL) as an alternative credit provider during the COVID-19 pandemic. Exploiting variation in monthly COVID-19 exposure across US counties, we find that counties with larger COVID-19 exposure experience higher MPL lending volume. This relationship is more pronounced in areas with more constrained banking, suggesting that marketplace lenders fill borrowing needs in underbanked areas and therefore substitute for the traditional lending sector. However, in contrast to prior work showing that marketplace lenders typically increase credit availability to riskier borrowers in normal times, we find that the increase in loans primarily goes to higher credit-quality borrowers during the pandemic. This result is consistent with a "flight-to-quality" reaction. Additionally, there is some evidence of altruistic lending behaviors, as medical-related loans increase in areas more affected by the pandemic.

本文探讨了市场借贷（MPL）在COVID-19大流行期间作为替代信贷提供者的作用。利用美国各县每月COVID-19风险敞口的差异，我们发现，COVID-19风险敞口较大的县的MPL贷款量较高。这种关系在银行业务受限的地区更为明显，这表明市场贷款机构填补了银行业务不足地区的借贷需求，从而取代了传统的贷款部门。然而，之前的研究表明，在正常时期，市场贷款机构通常会增加对风险较高的借款人的信贷供应，与此相反，我们发现，在疫情期间，贷款的增加主要流向了信用质量较高的借款人。这一结果与“逃向质量”的反应是一致的。此外，有证据表明，在受疫情影响更大的地区，医疗相关贷款有所增加，出现了一些利他贷款行为。

引用次数: 0

Board composition, private sector development, and corporate crime: Evidence from China 董事会构成、私营部门发展与企业犯罪：来自中国的证据

IF 3.1 3区经济学 Q1 ECONOMICS

Quarterly Review of Economics and Finance

Pub Date : 2025-11-19 DOI: 10.1016/j.qref.2025.102081

Xinxin Ma , Ichiro Iwasaki

Using individual firm data from the Orbis and Global Risk Information Database and regional level data, this study investigates the influence of corporate board composition and the regional development of private sector on corporate crimes in China during the period from January 2020 to September 2023. The empirical results indicate that board size and board gender diversity significantly influence the crime rate, whereas the effect of board independence is insignificant. This study first finds that private sector development significantly reduces corporate crime. These findings are robust across various samples and estimation models. Furthermore, the effects of board composition and private sector development differ by corporate crime type.

本研究利用奥比斯和全球风险信息数据库中的单个企业数据以及区域层面的数据，研究了2020年1月至2023年9月期间中国公司董事会构成和私营部门区域发展对公司犯罪的影响。实证结果表明，董事会规模和董事会性别多样性对犯罪率有显著影响，而董事会独立性的影响不显著。这项研究首先发现，私营部门的发展显著减少了企业犯罪。这些发现在各种样本和估计模型中都是稳健的。此外，董事会组成和私营部门发展的影响因公司犯罪类型而异。

引用次数: 0

Forecasting intraday volatility and densities using deep learning 使用深度学习预测日内波动率和密度

IF 3.1 3区经济学 Q1 ECONOMICS

Quarterly Review of Economics and Finance

Pub Date : 2025-11-15 DOI: 10.1016/j.qref.2025.102076

Bruno Morier , Pedro L. Valls Pereira

In this paper, we develop a new model for forecasting high-frequency, intraday, conditional, discrete return densities and volatility using deep learning. Specifically, we model the conditional distribution using a modified Skellam distribution, where the mean follows an auto-regressive specification. We then train feed-forward neural networks to generate predictions for the underlying high-frequency volatility. We test four different specifications, including different sets of features and parameters. Then, we conduct a comprehensive walk-forward forecasting experiment to compare the forecasting accuracy of the proposed models. All of the proposed models outperform the empirical non-parametric forecasting rules considered. The new forecasting procedure also provides better out-of-sample forecasts compared to all state space models based on Koopman et al. (2017). We conclude that the bid–ask spread, high-low interval spread, and the volume traded are predictive variables for the volatility process. According to our model estimates, these variables appear to have a positive non-linear S-shaped relationship with volatility.

在本文中，我们开发了一个新的模型，用于预测高频，即日，条件，离散的回报密度和波动性使用深度学习。具体来说，我们使用改进的Skellam分布对条件分布进行建模，其中平均值遵循自回归规范。然后，我们训练前馈神经网络来生成对潜在高频波动的预测。我们测试了四种不同的规格，包括不同的功能和参数集。然后，我们进行了全面的步进预测实验，比较了所提出模型的预测精度。所有提出的模型都优于考虑的经验非参数预测规则。与基于Koopman等人（2017）的所有状态空间模型相比，新的预测程序还提供了更好的样本外预测。我们得出结论，买卖价差，高低区间价差和交易量是波动过程的预测变量。根据我们的模型估计，这些变量似乎与波动率呈非线性正s型关系。

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引用次数: 0

Optimization model for banking Asset Liability Management 银行资产负债管理优化模型

IF 3.1 3区经济学 Q1 ECONOMICS

Quarterly Review of Economics and Finance

Pub Date : 2025-11-11 DOI: 10.1016/j.qref.2025.102074

Henrique Rosset Ferreira , Marcelo Monteiro Teixeira , Tiago Pascoal Filomena , Guilherme Kirch , Daniel Francisco Vancin , Eduardo Horta

We introduce an optimization model to assist Asset and Liability Management (ALM) departments in mitigating interest rate risk (IRR) within fixed-income portfolios. The model incorporates real-world constraints, including the cost of administering interest rate derivatives and liquidity constraints, aiming to formulate effective hedge strategies across diverse scenarios. In particular, liquidity constraints gain significance, as market limitations can hinder the execution of derivatives hedging strategies, a concern particularly relevant in emerging markets with lower trading volumes. We provide a comprehensive backtesting of the model under various portfolio times-to-maturity, nominal values, and shapes, revealing key insights. The analysis underscores the critical role of Dollar duration and Dollar convexity constraints in determining hedge strategy effectiveness. Liquidity constraints also emerge as a pivotal factor influencing the allocation of future contracts and strategy feasibility. Our main contribution is offering practitioners a valuable decision-making framework that incorporates real-world constraints, adding a nuanced understanding of interest rate risk management.

我们引入了一个优化模型来帮助资产负债管理部门降低固定收益投资组合中的利率风险。该模型结合了现实世界的约束，包括管理利率衍生品的成本和流动性约束，旨在制定不同情景下有效的对冲策略。特别是，流动性限制变得尤为重要，因为市场限制可能会阻碍衍生品对冲策略的执行，这在交易量较低的新兴市场尤为重要。我们在不同的投资组合到期日、名义价值和形状下对模型进行了全面的回溯测试，揭示了关键的见解。分析强调了美元持续时间和美元凸性约束在决定对冲策略有效性方面的关键作用。流动性约束也是影响未来合约配置和策略可行性的关键因素。我们的主要贡献是为从业者提供了一个有价值的决策框架，该框架包含了现实世界的约束，增加了对利率风险管理的细微理解。

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引用次数: 0

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