North American Journal of Economics and Finance最新文献

英文中文

Dynamic distortions of the security market line: Evidence from asymmetric volatility and regime-switching models 证券市场线的动态扭曲：来自不对称波动和制度转换模型的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-12-14 DOI: 10.1016/j.najef.2025.102566

Hatem Brik

This study re-examines the empirical validity of the Capital Asset Pricing Model (CAPM) by asking whether the Security Market Line (SML) remains stable when markets experience asymmetric volatility and regime transitions. Using high-frequency data from 2015 to 2024 for four major U.S. large-cap firms, we implement a unified empirical framework that integrates quantile regression, rolling-window CAPM estimation, and a two-state Markov-Switching AR(1) model.

The results reveal that the beta–return relationship is non-linear, time-varying, and state-dependent. Beta significance concentrates around the median of the return distribution but vanishes in the tails, confirming distributional asymmetry. Rolling estimations indicate persistent yet gradual beta drift, while the Markov-Switching model uncovers regime-contingent SML slopes—positive in stable phases and inverted during stress periods. These findings demonstrate that systematic risk is not uniformly priced and that the classical CAPM’s assumptions of linearity, stationarity, and rational expectations fail under dynamic market conditions.

Beyond U.S. equities, the framework offers a diagnostic tool for risk monitoring and portfolio management in environments characterized by volatility shocks and behavioral frictions—conditions typical of many emerging markets. By integrating dynamic, distributional, and regime dimensions, the paper contributes to a more adaptive understanding of asset pricing under uncertainty.

本研究通过询问证券市场线（SML）在市场经历不对称波动和制度转变时是否保持稳定，重新检验了资本资产定价模型（CAPM）的实证有效性。利用2015年至2024年美国四家大型公司的高频数据，我们实现了一个统一的经验框架，该框架集成了分位数回归、滚动窗口CAPM估计和两状态马尔可夫切换AR(1)模型。结果表明，β -回归关系是非线性的、时变的和状态相关的。贝塔显著性集中在收益分布的中位数附近，但在尾部消失，证实了分布的不对称性。滚动估计表明持续而渐进的β漂移，而马尔可夫切换模型揭示了状态随状态变化的SML斜率-在稳定阶段为正，在应力期间为反转。这些发现表明，系统风险不是统一定价的，经典CAPM的线性、平稳性和理性预期假设在动态市场条件下失效。除了美国股市之外，该框架还为以波动冲击和行为摩擦为特征的环境中的风险监测和投资组合管理提供了一个诊断工具，这些环境是许多新兴市场的典型条件。通过整合动态、分配和制度维度，本文有助于对不确定性下的资产定价有更适应性的理解。

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引用次数: 0

Does inter-industry risk spillover network predict financial crisis? Evidence from a gated graph neural networks approach 行业间风险溢出网络能否预测金融危机？来自门控图神经网络方法的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-12-11 DOI: 10.1016/j.najef.2025.102565

Yinghua Ren , Xin Chen , Han Chen , Huiming Zhu

This study proposes a novel binary-classification model for systemic risk warning, utilizing inter-industry tail-risk spillover networks as input. These networks are constructed using the Tail-Event driven network (TENET) model, which captures high-dimensional and non-linear characteristics of risk contagion. The model leverages the Gated Graph Neural Network (GGNN) framework to uncover the ambiguous specification of crisis prediction. Applied to 11 key U.S. industry indices, the empirical results demonstrate that: (i) the topology of the risk spillover network is strongly correlated with financial crises during critical periods; and (ii) the GGNN model based on the TENET network provides superior reliability in early warning compared to traditional machine learning and other graph-based models.

本文以行业间尾部风险溢出网络为输入，提出了一种新的系统性风险预警二元分类模型。这些网络使用尾事件驱动网络（TENET）模型构建，该模型捕获了风险传染的高维和非线性特征。该模型利用门控图神经网络（GGNN）框架揭示了危机预测的模糊规范。运用美国11个关键行业指数，实证结果表明：(1)风险溢出网络的拓扑结构与关键时期金融危机具有较强的相关性；（ii）与传统机器学习和其他基于图的模型相比，基于TENET网络的GGNN模型在预警方面具有更高的可靠性。

引用次数: 0

Simultaneous inference in testing conditional alphas of momentum portfolios 同时推理在动量组合条件阿尔法检验中的应用

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-12-04 DOI: 10.1016/j.najef.2025.102557

Jinyong Kim , Yongsik Kim , Seunghyun Lee

We evaluate the conditional performance of intermediate and recent past momentum portfolios using nonparametric estimation and simultaneous inference. The outperformance of intermediate past momentum is driven by the relative performance of winners. The largest contributors to the outperformance are negative and positive exposures of the intermediate and recent past momentum to the value factor, respectively, which are strengthened when the market risk premium is high and coincide with the significant outperformance of the intermediate momentum. These contrasting signs of exposures are robust to a sub-period analysis and controls for the January effect. The outperformance disappears when prior Months 12 and 2 are excluded from constructing the momentum portfolios, due to changes in losers’ returns. However, the opposing exposures to the value factor remain consistent.

我们使用非参数估计和同步推理来评估中间和最近的过去动量组合的条件性能。中间过去势头的优异表现是由赢家的相对表现驱动的。表现优异的最大贡献者分别是中期和最近的过去势头对价值因素的负和正风险敞口，当市场风险溢价较高并与中期势头的显著表现相吻合时，这种风险敞口得到加强。这些对比鲜明的暴露迹象对于1月效应的子周期分析和控制是稳健的。当之前的第12个月和第2个月被排除在动量投资组合之外时，由于输家回报的变化，优异的表现就会消失。然而，对价值因素的相反敞口保持一致。

引用次数: 0

Dynamic Agency, financial hedging and optimal investment 动态代理、金融对冲与最优投资

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-19 DOI: 10.1016/j.najef.2025.102556

Yehong Yang, Xun You, Yuqian Sun

Based on the continuous-time contract framework (DeMarzo et al., 2012), hereinafter referred to as the DFHW model), we develop an enhanced continuous-time contract framework incorporating an optimal financial hedging strategy to effectively mitigate firm-specific risks. This paper confirms the presence of a lagged effect of the hedging strategy on a firm’s investment. Compared with the DFHW model, our findings reveal that the optimal hedging strategy has a significant influence on dynamic contracts, including investors’ value, dynamic investment, dividend payments, and so on. Especially in an equilibrium state, the investors tend to distribute dividends at lower levels and earlier than those predicted by the DFHW model, thereby mitigating the risk burden on entrepreneurs. Finally, the hedging strategy is significantly influenced by hedging costs, which in turn have an impact on firms’ investment and dividend boundary. This paper further validates the rationality and feasibility of our devised financial hedging strategy.

基于连续时间契约框架（DeMarzo et al., 2012），以下简称DFHW模型)，我们开发了一个增强的连续时间契约框架，其中包含了最优的财务对冲策略，以有效降低企业特定风险。本文证实了套期保值策略对企业投资存在滞后效应。与DFHW模型相比，我们的研究结果表明，最优对冲策略对动态合约有显著影响，包括投资者价值、动态投资、股息支付等。特别是在均衡状态下，投资者倾向于比DFHW模型预测的水平更低、更早地分配股息，从而减轻了企业家的风险负担。最后，套期保值策略受套期保值成本的显著影响，套期保值成本又对企业的投资和股息边界产生影响。本文进一步验证了所设计的财务套期保值策略的合理性和可行性。

引用次数: 0

Time-frequency quantile effect of global uncertainty on stock markets: evidence from wavelet decomposition 全球不确定性对股票市场的时频分位数效应：来自小波分解的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-15 DOI: 10.1016/j.najef.2025.102554

Jiayuan Yuan , Weineng Zhu , Zishan Huang , Huiming Zhu

This study explores the time–frequency effect of the World Uncertainty Index (WUI) on the stock markets across quantile levels.We utilize wavelet decomposition and quantile regression to measure the time–frequency relationship between WUI and stock markets. Our empirical results are as follows. First, there exists a significant long-term Granger causality between WUI and stock markets. Second, the impacts of WUI on stock markets change with time-scales, the short term impacts being more intense than that of the other time scale. Third, there is significant asymmetric impacts of WUI on the stock markets. At extreme quantile levels, the absolute values of quantile regression coefficients become significantly larger relationship, indicating the relationship between the two becomes more pronounced. Overall, our findings provide a investors and policymakers with a more deeper perspective on dynamic market risk management.

本研究探讨了世界不确定性指数（WUI）对股票市场的时频效应。我们利用小波分解和分位数回归来衡量WUI与股票市场之间的时频关系。我们的实证结果如下：首先，WUI与股市之间存在显著的长期格兰杰因果关系。第二，WUI对股票市场的影响随时间尺度变化，短期影响强于其他时间尺度。第三，WUI对股票市场存在显著的不对称影响。在极端分位数水平上，分位数回归系数的绝对值关系变得显著变大，表明两者之间的关系变得更加明显。总体而言，我们的研究结果为投资者和政策制定者提供了更深入的动态市场风险管理视角。

引用次数: 0

Physical climate risk and banks’ credit risk: Worldwide evidence 物理气候风险与银行信用风险：全球证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-13 DOI: 10.1016/j.najef.2025.102550

Isabel Abinzano, Pilar Corredor, José Manuel Mansilla-Fernández

This paper examines the impact of physical climate risk on banks’ credit risk and, by extension, on global financial stability. We use the S&P Physical Risk Index as a proxy for banks’ exposure to physical climate risk. Credit risk is measured using the forward-looking probability of default from the Chan-Lau and Sy (2007) model, which adapts the structural Black–Scholes–Merton framework to the banking context. Based on a worldwide sample of 374 listed banks, our results show that physical climate risk increases banks’ credit risk. This effect is particularly pronounced for banks with greater informativeness, intrinsically vulnerable, and operating in more fragile countries. The findings provide empirical support for the financial regulators’ proposal to incorporate climate risks into capital requirements to more effectively manage climate-related financial risks. Importantly, the results indicate that such regulatory adjustments should be calibrated to each bank’s specific characteristics and operating environment.

本文考察了物理气候风险对银行信用风险的影响，进而对全球金融稳定的影响。我们使用s&p；P物理风险指数作为银行对物理气候风险敞口的代理。信用风险是使用Chan-Lau和Sy（2007）模型的前瞻性违约概率来衡量的，该模型将结构性布莱克-斯科尔斯-默顿框架适用于银行环境。基于全球374家上市银行的样本，我们的研究结果表明，物理气候风险增加了银行的信用风险。这种影响对于那些信息量更大、本质上脆弱、在更脆弱的国家经营的银行尤为明显。研究结果为金融监管机构将气候风险纳入资本要求以更有效地管理气候相关金融风险的建议提供了实证支持。重要的是，结果表明，这种监管调整应根据每家银行的具体特点和经营环境进行校准。

引用次数: 0

The spillover effect of customer extreme climate risk: Evidence from supplier trade credit 顾客极端气候风险的溢出效应：来自供应商贸易信用的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-12 DOI: 10.1016/j.najef.2025.102553

Zhen Huang, Tianyu Dou

This study examines the spillover effect of customer extreme climate risk on suppliers’ trade credit provision to their customers, and the moderating effects of customer climate sensitivity and customer green investment. We find that suppliers decrease trade credit provision as customer extreme climate risk increases. This adverse impact is stronger when firms have higher customer climate sensitivity and lower customer green investment. The negative effect continues to hold under several robustness tests, such as instrumental variable regression and propensity score matching. We further find that the influencing mechanism through which customer extreme climate risk impacts supplier trade credit is to increase the likelihood of customer credit risk. Additionally, the effect of customer extreme climate risk on suppliers’ trade credit provision is more significant when customers are non-state-owned or have a low market position. Our findings highlight the importance of customer extreme climate risk and offer valuable insights for suppliers to refine their business strategies in the context of supply chain risk spillover.

本研究考察了客户极端气候风险对供应商向其客户提供贸易信贷的溢出效应，以及客户气候敏感性和客户绿色投资的调节效应。我们发现，随着客户极端气候风险的增加，供应商减少了贸易信贷供应。当企业具有较高的客户气候敏感性和较低的客户绿色投资时，这种不利影响更强。在几个稳健性测试下，如工具变量回归和倾向得分匹配，负面影响继续保持。进一步发现客户极端气候风险影响供应商贸易信用的影响机制是增加客户信用风险的可能性。此外，当客户是非国有企业或市场地位较低时，客户极端气候风险对供应商贸易信贷提供的影响更为显著。我们的研究结果强调了客户极端气候风险的重要性，并为供应商在供应链风险溢出的背景下完善其业务策略提供了有价值的见解。

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引用次数: 0

Does climate policy uncertainty affect expected shortfall (and Value-at-Risk) in the Chinese sector? Evidence from the mixed-frequency dynamic semi-parametric approach 气候政策的不确定性是否会影响中国行业的预期缺口（和风险价值）？来自混合频率动态半参数方法的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-12 DOI: 10.1016/j.najef.2025.102555

Kunliang Jiang , Pengfei Luo , Wenxiao Gan , Jiashan Song , Yuejing Wang

Climate policy uncertainty (CPU) increases risks across sectors by affecting the economic environment, stock price volatility, corporate transformations, and investor confidence. However, incorporating such low-frequency information into sector risk assessments remains insufficiently addressed. This study combines the GARCH-MIDAS model with the Fissler–Ziegel (FZ) loss function to jointly model Value-at-Risk (VaR) and expected shortfall (ES), and explores the heterogeneous impact of CPU on risk measures across eleven sectors from 1 January 2008 to 31 December 2022 in China. Our findings indicate that CPU positively affects the VaR and ES in five sectors: energy, material, industry, consumer discretionary, and utility, while negatively impacting six sectors: consumer staple, healthcare, information technology, telecommunication service, real estate, and finance. The effect of CPU on the VaR and ES in the energy and material sectors demonstrates strong long memory, whereas the impact on telecommunication service is the opposite. Incorporating CPU into the model significantly improves the accuracy of sector risk measures across various risk levels, while the FZ loss function method provides effective risk measurement results primarily under extreme risk conditions.

气候政策的不确定性（CPU）通过影响经济环境、股价波动、企业转型和投资者信心，增加了各行业的风险。然而，将这种低频率信息纳入部门风险评估的问题仍然没有得到充分解决。本研究结合GARCH-MIDAS模型和Fissler-Ziegel （FZ）损失函数对风险价值（VaR）和预期缺口（ES）进行联合建模，并探讨了2008年1月1日至2022年12月31日期间中国11个行业的CPU对风险措施的异质性影响。研究结果表明，CPU对能源、材料、工业、非必需消费品和公用事业五个行业的VaR和ES有正向影响，而对主要消费品、医疗保健、信息技术、电信服务、房地产和金融六个行业的VaR和ES有负向影响。CPU对能源和材料行业VaR和ES的影响表现出较强的长记忆性，而对电信服务的影响则相反。将CPU纳入模型显著提高了各行业风险度量的准确性，而FZ损失函数法主要在极端风险条件下提供有效的风险度量结果。

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引用次数: 0

Quantile-frequency dependence between U.S. sector stock indices and macro-financial indicators: A quantile coherence approach 美国行业股票指数和宏观金融指标之间的分位数频率依赖性：分位数一致性方法

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-07 DOI: 10.1016/j.najef.2025.102552

Halilibrahim Gökgöz , Aamir Aijaz Syed , Catalin Gheorghe , Ahmed Jeribi

This study explores the quantile–frequency linkages between U.S. sectoral stock indices and four macro-financial indicators: market volatility (VIX), geopolitical risk (GPR), inflation expectations (T5YIE), and the yield curve (T10Y3M), using the Quantile Coherence (QC) framework. The method captures nonlinear and asymmetric interactions across quantiles and horizons. The dataset covers daily observations from January 2016 to July 2025, encompassing episodes such as Brexit, the China–U.S. trade war, and recent geopolitical conflicts. Results reveal strong sectoral heterogeneity: dependence on VIX is predominantly negative in the short term during bullish phases, with reversals at longer horizons; the influence of GPR is asymmetric and forward-looking; inflation expectations, captured by T5YIE, show a stable long-run positive association with all sectors; while the yield curve (T10Y3M) generates systematic long-term co-movements, with leadership alternating between financial indicators and sector indices across regimes. These findings demonstrate uneven sectoral responses to macro-financial drivers and provide guidance for risk management and portfolio design in uncertain environments.

本研究利用分位数一致性（QC）框架，探讨了美国行业股票指数与四个宏观金融指标：市场波动率（VIX）、地缘政治风险（GPR）、通胀预期（t5ie）和收益率曲线（T10Y3M）之间的分位数-频率联系。该方法捕获了跨分位数和视界的非线性和非对称相互作用。该数据集涵盖了从2016年1月到2025年7月的每日观测数据，包括英国脱欧、中美关系和气候变化等事件。贸易战和最近的地缘政治冲突。结果显示了很强的行业异质性：在看涨阶段，对VIX的依赖在短期内主要为负，在较长时间内出现逆转；探地雷达的影响是非对称的、前瞻性的；t5ye反映的通胀预期显示，通胀预期与所有行业都存在稳定的长期正相关关系；而收益率曲线（T10Y3M）则产生系统性的长期协同运动，在不同体制的金融指标和行业指数之间交替领导。这些发现表明，行业对宏观金融驱动因素的反应不均衡，并为不确定环境下的风险管理和投资组合设计提供指导。

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引用次数: 0

Asymmetric drivers of inflation: new evidence from machine learning and quantile method 通货膨胀的不对称驱动因素：来自机器学习和分位数方法的新证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-07 DOI: 10.1016/j.najef.2025.102551

Kingsley Imandojemu , Adetutu Omotola Habib , Omozele Lynda Showunmi , Loveth Oribhabor Agboola

This paper investigates the complex, nonlinear forces behind price movements in Nigeria by applying quantile econometric techniques. Using monthly data from December 2012 to August 2024, the analysis applies Elastic Net Regression for variable selection and employs Quantile-on-Quantile Kernel Regularized Least Squares (QQKRLS) alongside Quantile-on-Quantile Granger Causality (QQGC) tests. The results show that while money supply consistently drives inflation, the effects of other variables are regime-dependent; for instance, private sector credit fuels inflation in moderate-to-high periods, while bank reserves can dampen it in moderate ones. Furthermore, the analysis confirms a directional causality from these variables of interest to inflation, with the strength of the relationship varying significantly across quantiles. The results reveal that uniform policies are inadequate. Policymakers should, therefore, adopt quantile-specific and context-sensitive fiscal and monetary strategies to ensure durable price stability in Nigeria.

本文通过应用分位数计量经济学技术调查了尼日利亚价格变动背后的复杂非线性力量。利用2012年12月至2024年8月的月度数据，采用弹性网络回归进行变量选择，并采用分位数对核正则化最小二乘（QQKRLS）和分位数对格兰杰因果关系（QQGC）检验。结果表明，虽然货币供应量持续推动通胀，但其他变量的影响是依赖于制度的；例如，在中高时期，私人部门信贷会推动通胀，而在中高时期，银行准备金则会抑制通胀。此外，分析证实了这些感兴趣的变量与通货膨胀之间的方向性因果关系，这种关系的强度在分位数之间存在显著差异。结果表明，统一的政策是不够的。因此，政策制定者应采取具体分位数和对环境敏感的财政和货币战略，以确保尼日利亚的持久价格稳定。

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