North American Journal of Economics and Finance最新文献

英文中文

Dynamic q-dependent cross-correlation test for investment classification and its application on green finance 投资分类的动态q相关检验及其在绿色金融中的应用

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-09-02 DOI: 10.1016/j.najef.2025.102535

Turker Acikgoz

This study develops a novel methodological framework, the dynamic

q

-dependent cross-correlation (DQCC) test, to evaluate the diversification, hedging, and safe-haven properties of financial assets under conditions of fractality and nonlinear dependence. Traditional econometric approaches often fail to capture three critical aspects of financial markets: time-varying structures, heterogeneous investment horizons, and fluctuation-dependent dynamics. To address these limitations, the proposed framework integrates fractal theory and econophysics-based cross-correlation measures, enabling a simultaneous analysis of time, scale, and moment dimensions. Empirically, the model is applied to the nexus between green bonds and equity markets. Methodologically, both quantile-based and event-based specifications are employed to assess asset behavior under normal conditions and during systemic crises, including the COVID-19 pandemic, the Russia–Ukraine war, and the Hamas–Israel conflict. The results reveal strong evidence of multifractality and nonlinear dynamics across all return series, rejecting market efficiency. Green bonds are found to provide persistent diversification benefits against both advanced and emerging market equities under ordinary conditions, while their safe-haven properties emerge during extreme downturns, particularly at lower quantiles and longer horizons. Event-based results confirm the safe-haven role of green bonds during COVID-19, with more mixed evidence during geopolitical crises. No robust hedging capacity is observed. The study contributes to the literature by introducing a comprehensive testing framework for investment classification under fractal dynamics and by extending the understanding of the green bond–equity nexus across advanced and emerging markets. The findings carry significant implications for portfolio construction, risk management, and sustainable finance, and the model can be applied to other asset classes to evaluate their potential roles as diversifiers, hedges, or safe-haven.

本研究开发了一种新的方法框架，即动态q相关互相关（DQCC）检验，以评估分形和非线性依赖条件下金融资产的多样化、套期保值和避险特性。传统的计量经济学方法往往无法捕捉到金融市场的三个关键方面：时变结构、异质投资视野和依赖波动的动态。为了解决这些限制，提出的框架集成了分形理论和基于经济物理学的相互关联度量，能够同时分析时间、尺度和力矩维度。实证研究表明，该模型适用于绿色债券与股票市场之间的关系。在方法上，采用基于分位数和基于事件的规范来评估正常情况下和系统性危机期间的资产行为，包括COVID-19大流行、俄罗斯-乌克兰战争和哈马斯-以色列冲突。结果揭示了多重分形和非线性动力学在所有收益序列的有力证据，拒绝市场效率。研究发现，在一般情况下，绿色债券对发达市场和新兴市场股票都能提供持续的多元化收益，而在极端低迷时期，尤其是在较低的分位数和较长的时间跨度时，绿色债券的避险属性会显现出来。基于事件的结果证实了绿色债券在2019冠状病毒病期间的避险作用，在地缘政治危机期间的证据则更为复杂。没有观察到稳健的对冲能力。本研究通过引入分形动态下投资分类的综合测试框架，并通过扩展对发达市场和新兴市场绿色债券-股票关系的理解，为文献做出了贡献。研究结果对投资组合构建、风险管理和可持续金融具有重要意义，该模型可应用于其他资产类别，以评估其作为多元化、对冲或避险的潜在作用。

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引用次数: 0

On completing the connectedness analysis—A bootstrap-based DCC-GARCH approach 完成连通性分析——基于bootstrap的DCC-GARCH方法

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-08-29 DOI: 10.1016/j.najef.2025.102526

Jingliang Huai , Adrian (Wai Kong) Cheung , Bin Wang

By mapping high-dimensional systems to directed weighted networks, VAR-based Diebold-Yilmaz connectedness framework provides a novel and nuanced perspective on spillovers. Nonetheless, its reliance on rolling windows and the absence of formal statistical evidence for event-based analysis may limit its applicability. To overcome these two shortcomings, this study develops an alternative connectedness framework based on the dynamic conditional correlation—generalized autoregressive conditional heteroskedasticity (DCC-GARCH) model and a bootstrap technique, augmented by a probabilistic analysis of an increase in connectedness in response to major events. We apply our framework to four major currencies against the US dollar. In terms of event probability analysis, it is observed that 15 out of the 20 identified events correspond to a probability exceeding 90% for an increase in total connectedness, which predominantly pertain to geopolitical crises, financial market collapses, and global health emergencies. Therefore, although traditional event analysis frequently capture increases in connectedness, our methodology underscores that these associations may lack statistical rigor. Beside this, we find that the total connectedness also responds instantaneously to such events with rapid dissipation or manifests a delayed reaction.

通过将高维系统映射到有向加权网络，基于var的Diebold-Yilmaz连通性框架为溢出效应提供了一种新颖而细致的视角。尽管如此，它对滚动窗口的依赖以及对基于事件的分析缺乏正式的统计证据可能限制了它的适用性。为了克服这两个缺点，本研究开发了一个基于动态条件相关-广义自回归条件异方差（DCC-GARCH）模型和自举技术的替代连通性框架，并通过对重大事件响应的连通性增加的概率分析进行了增强。我们将我们的框架应用于四种主要货币对美元的汇率。在事件概率分析方面，可以观察到，在已确定的20个事件中，有15个事件对应于总连通性增加的概率超过90%，这主要涉及地缘政治危机、金融市场崩溃和全球突发卫生事件。因此，尽管传统的事件分析经常捕捉到连通性的增加，但我们的方法强调这些关联可能缺乏统计严谨性。除此之外，我们还发现，总连通性对此类事件也有瞬时响应，并具有快速消散或表现出延迟反应。

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引用次数: 0

The impact of green cryptocurrency and nongreen cryptocurrency on energy markets: Evidence from geopolitical risk and higher-order moment connectedness 绿色加密货币和非绿色加密货币对能源市场的影响：来自地缘政治风险和高阶时刻连通性的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-08-21 DOI: 10.1016/j.najef.2025.102527

Wan-Lin Yan , Adrian (Wai Kong) Cheung , Jiawei Yuan

Cryptocurrency market has a significant impact on energy markets due to the intensive usage of energy in the mining process. This study analyzes the impact of green and nongreen cryptocurrency markets on traditional and clean energy markets by using a TVP-VAR connectedness approach. Moreover, the higher-order moment connectedness is investigated. The empirical results show that there is a time varying connectedness between cryptocurrency and energy markets and extreme events can intensify the connectedness. The transmission of volatility spillover and return asymmetry is more obvious between nongreen cryptocurrency and energy markets, while the probability of occurring extreme events is higher between green cryptocurrency and energy markets. Energy markets act as the net shock receiver, while cryptocurrencies are mainly the net shock transmitters in each order moment connectedness. The impact of geopolitical acts is mostly negative and the moderating impact of geopolitical threats on skewness is different between green and nongreen cryptocurrencies. This study significantly contributes to a deeper understanding of the impacts of green and non-green cryptocurrencies on energy markets, which has significant implications for investors and policymakers.

由于在采矿过程中大量使用能源，加密货币市场对能源市场产生了重大影响。本研究通过使用tpv - var连通性方法分析了绿色和非绿色加密货币市场对传统和清洁能源市场的影响。此外，还研究了高阶矩连通性。实证结果表明，加密货币与能源市场之间存在时变的连通性，极端事件可以强化这种连通性。非绿色加密货币与能源市场之间波动溢出和收益不对称的传导更为明显，而绿色加密货币与能源市场之间发生极端事件的概率更高。能源市场是净冲击接受者，而加密货币在各阶矩连通性上主要是净冲击发送者。地缘政治行为的影响大多是负面的，地缘政治威胁对偏度的缓和影响在绿色和非绿色加密货币之间是不同的。这项研究有助于更深入地了解绿色和非绿色加密货币对能源市场的影响，这对投资者和政策制定者具有重要意义。

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引用次数: 0

Corporate cash value and ESG management: Panel data analyses of stock indices across countries 企业现金价值与ESG管理：各国股票指数的面板数据分析

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-08-18 DOI: 10.1016/j.najef.2025.102521

Kei-Ichiro Inaba

By conducting international panel-data regressions to investigate the determinants of listed companies’ average qs in 18 countries’ representative stock market indices over the period 2009–2019 in consideration of the companies’ market capitalization differences, I find that better social and governance management levels were associated with higher qs, and that corporate cash value was positively priced across the countries. This positive pricing of corporate cash was strengthened in countries with better environment, social, and governance management levels, and in those with higher R&D investments. Pricing was more positive in the United Kingdom than in the United States (U.S.) or Japan. It was weakened as national indices with greater market capitalization were downplayed more in the regression analysis. It was strengthened in the U.S. index in response to increasing passive index funds.

考虑到公司市值差异，通过国际面板数据回归研究2009-2019年期间18个国家代表性股票市场指数中上市公司平均qs的决定因素，我发现更好的社会和治理管理水平与更高的qs相关，并且公司现金价值在各国都是正定价的。在环境、社会和治理管理水平较好的国家，以及在研发投资较高的国家，这种对企业现金的积极定价得到了加强。与美国或日本相比，英国的定价更为积极。由于在回归分析中，市值较大的国家指数被淡化，导致该指数被削弱。由于被动指数基金的增加，该指数在美国指数中得到加强。

引用次数: 0

Systemically important commodity futures in China 中国具有系统重要性的大宗商品期货

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-08-18 DOI: 10.1016/j.najef.2025.102525

Yang Chen , Mengxia Xu , Qing Liu

To depict the increasing interdependence of commodity prices and thus higher systemic risk under financialization, this paper investigates the risk spillover levels in the Chinese commodity futures market using the TENET model and directed acyclic graphs, based on which it innovatively identifies Systemically Important Commodity Futures (SICFs). This paper demonstrates the commodity financialization in China, and finds that agricultural futures are SICFs. This finding is robust across years, financial cycles, business cycles, and even other tail-dependence indicators. The paper provides several regulatory takeaways: Firstly, financialization has amplified price interconnections among commodity networks, elevating the probability of systemic risk. Accordingly, regulatory authorities should expand their oversight to include SICFs, in addition to the traditional Systemically Important Financial Institutions (SIFIs). Secondly, agricultural futures are identified as SICFs, underscoring the need for diligent monitoring and attention. Moreover, enhancing cross-border and cross-market risk coordination mechanisms is essential to mitigate systemic risk.

为了描述金融化条件下商品价格之间日益增长的相互依赖性以及由此带来的更高的系统性风险，本文利用TENET模型和有向无环图研究了中国商品期货市场的风险溢出水平，并在此基础上创新地识别了系统重要性商品期货（SICFs）。本文对中国商品金融化进行了实证研究，发现农产品期货是SICFs。这一发现在历年、金融周期、商业周期，甚至其他尾部相关指标中都是强有力的。本文提供了几个监管要点：首先，金融化放大了商品网络之间的价格相互联系，提高了系统性风险的可能性。因此，除了传统的系统重要性金融机构（sifi）外，监管机构应扩大监管范围，将sicf纳入监管范围。其次，农业期货被确定为sicf，强调需要认真监测和关注。此外，加强跨境和跨市场风险协调机制对缓解系统性风险至关重要。

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引用次数: 0

Extreme weather events as the main driver of electricity price volatility in Italy: A GARCH-MIDAS approach with machine learning-based variable selection 极端天气事件是意大利电价波动的主要驱动因素：基于机器学习变量选择的GARCH-MIDAS方法

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-08-13 DOI: 10.1016/j.najef.2025.102512

Marco Guerzoni , Luigi Riso , M. Grazia Zoia

This paper investigates the impact of extreme weather events on electricity price volatility in Italy, employing a novel combination of advanced econometric techniques and a robust variable selection process. First, we provide empirical evidence that extreme weather events significantly predict electricity price volatility. We compile a comprehensive set of economic and financial variables known in the literature to influence electricity price volatility and apply the Best Path Algorithm (BPA) for variable selection, identifying the most relevant predictors. A Granger causality analysis of the selected variables confirms that extreme weather events not only emerge as the primary factor driving volatility but also exhibit a clear unidirectional causal relationship.

Second, we integrate weather variables into a GARCH-MIDAS model, to combine high-frequency electricity price data with low-frequency climate data, thereby capturing both short- and long-term volatility components. Additionally, we incorporate external shocks—such as the Russia–Ukraine war—as exogenous variables to account for broader geopolitical influences on the energy market. Our findings underscore the substantial predictive power of extreme weather events and external shocks on electricity price dynamics.

This study enhances forecasting capabilities for policymakers and energy stakeholders, highlighting the urgent need for resilient energy market planning. Future research may extend this methodology to other regions and incorporate additional variables to further improve predictive accuracy.

本文研究了极端天气事件对意大利电价波动的影响，采用了先进计量经济学技术和稳健变量选择过程的新颖组合。首先，我们提供了极端天气事件显著预测电价波动的实证证据。我们编制了一套全面的经济和金融变量在文献中已知的影响电价波动，并应用最佳路径算法（BPA）进行变量选择，确定最相关的预测因子。对所选变量的格兰杰因果分析证实，极端天气事件不仅是波动率的主要驱动因素，而且表现出明显的单向因果关系。其次，我们将天气变量整合到GARCH-MIDAS模型中，将高频电价数据与低频气候数据结合起来，从而捕获短期和长期波动成分。此外，我们将外部冲击（如俄乌战争）纳入外生变量，以解释更广泛的地缘政治对能源市场的影响。我们的研究结果强调了极端天气事件和外部冲击对电价动态的实质性预测能力。本研究提高了决策者和能源利益相关者的预测能力，强调了弹性能源市场规划的迫切需要。未来的研究可能会将这种方法扩展到其他地区，并纳入额外的变量，以进一步提高预测的准确性。

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引用次数: 0

Heterogeneous beliefs with information processing constraints and asset pricing in presence of non-tradable goods 具有信息处理约束和非贸易商品资产定价的异质信念

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-08-12 DOI: 10.1016/j.najef.2025.102520

Hailong Wang , Duni Hu

This paper proposes an international financial model with two investors to explore the influences of heterogeneous beliefs and capacity constraints on asset prices. The capacity constraints not only impose influences on the investors’ posterior means and variances, but also generate persistent disagreements. We present that even though the non-tradable goods are only domestically consumed, the investors can partially mitigate their non-tradable goods consumption risks by adjusting tradable goods consumptions. We also show that introducing the non-tradable goods leads the investors’ optimal portfolio choices to depend on hedging demands motivated by uncertainties of the stocks with claims to the non-tradable goods. The previous mechanism of the non-tradable goods plays an important role in determining the effects of heterogeneous beliefs on asset pricing moments.

本文提出了一个包含两个投资者的国际金融模型，以探讨异质性信念和能力约束对资产价格的影响。能力约束不仅会影响投资者的后验均值和方差，还会产生持续的分歧。本文认为，即使非贸易品仅为国内消费，投资者也可以通过调整非贸易品消费来部分缓解其非贸易品消费风险。我们还表明，引入非流通品会导致投资者的最优投资组合选择依赖于对非流通品有索赔权的股票的不确定性所激发的对冲需求。非贸易商品的前一机制在决定异质性信念对资产定价时刻的影响方面起着重要作用。

引用次数: 0

Corporate investment amid trade policy uncertainty: Past lessons, future presidency 贸易政策不确定性下的企业投资：过去的教训，未来的总统

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-08-11 DOI: 10.1016/j.najef.2025.102514

Vaibhav Keshav

What insights can we glean from the prior trade conflict between the US and China amidst its prominence in the 2025–2028 presidential term? Between 2016 and 2019, the US–China trade dispute, with US tariffs and Chinese retaliation, surged trade policy uncertainty (TPU). Departing from prior studies focusing on overall economic policy uncertainty (EPU), this study reports an inverse causal relation between aggregate and firm-level TPU and corporate investment by employing a novel instrumental variable. Apart from confirming the real options channel, I identify a foreign exchange channel, highlighting the susceptibility of firms to TPU based on exposure to exchange rate fluctuations. Lastly, I discuss the implications of this study in the context of the upcoming US presidential elections and beyond.

在2025-2028年美国总统任期内，我们可以从之前的中美贸易冲突中得到什么启示？2016年至2019年期间，中美贸易争端，美国的关税和中国的报复，贸易政策的不确定性（TPU）激增。与以往关注总体经济政策不确定性（EPU）的研究不同，本研究通过使用一个新的工具变量，报告了总体和企业层面的TPU与企业投资之间的反向因果关系。除了确认实物期权渠道外，我还确定了一个外汇渠道，突出了企业对基于汇率波动的TPU的敏感性。最后，我讨论了这项研究在即将到来的美国总统大选及其后的背景下的含义。

引用次数: 0

Can volatility spread fully capture the put–call parity violation? 波动率价差能否完全捕捉到买卖权平价的违规行为？

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-08-11 DOI: 10.1016/j.najef.2025.102493

Shican Liu , Songping Zhu

Put–call parity (PCP) is a well-known relationship between call and put option prices and their underlying for complete markets. It is equally well known for its violation in incomplete markets. However, unlike all the previously documented reasons in the literature, we show in this paper, through convincing empirical evidence, that the density spread of the put and call is also “blamed” for such a violation. We also provide a theoretical framework to financially explain such an imbalance in incomplete markets.

看跌期权平价（PCP）是一种在完整市场中看涨期权和看跌期权价格及其标的之间众所周知的关系。它在不完全市场中的违规行为也是众所周知的。然而，与之前文献中记录的所有原因不同，我们在本文中通过令人信服的经验证据表明，看跌期权和看涨期权的密度扩散也被“归咎于”这种违规行为。我们还提供了一个理论框架来解释不完全市场中的这种不平衡。

引用次数: 0

Unveiling the bright side of rice-farming culture in shaping innovation: Evidence from Chinese listed firms 揭示水稻种植文化在塑造创新中的光明一面：来自中国上市公司的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-08-09 DOI: 10.1016/j.najef.2025.102522

Xiaoliang Zhang , Qilin Wang , Xin Wang

This study aims to unveil the bright side of rice-farming culture in driving firm innovation and discuss the possible underlying mechanisms. Using hand-collected city-level data on rice cultivation, we examine the impact of regional rice-farming culture on the innovation activities of Chinese listed companies. The results show that firms located in regions with stronger rice-farming culture intensity exhibit both higher innovation quantity and quality, as evidenced by an increased number of patent applications and citations. These findings persist across a variety of robustness tests. Mechanism tests indicate that rice-farming culture fosters institutional collectivism and facilitates innovation through two channels: reducing agency costs and enhancing collaborative innovation. The positive impact of rice-farming culture on firm innovation is more pronounced in regions with weaker legal environment, slower urbanization process, and limited exposure to foreign cultural influence. Additionally, firms located in rice-cultivating areas are more likely to appoint CEOs from these regions, which further correlates with higher innovation output. Moreover, rice-farming culture facilitates the translation of innovation into improved financial performance. Overall, this study sheds light on the role of informal institutions in shaping firm innovation, offering valuable insights into the cultural foundations of economic behavior.

本研究旨在揭示稻作文化推动企业创新的光明面，并探讨其可能的潜在机制。本文利用城市层面的水稻种植数据，考察了区域水稻种植文化对中国上市公司创新活动的影响。研究结果表明，水稻种植强度越强的地区企业创新数量和质量越高，专利申请量和引用量均有所增加。这些发现在各种稳健性测试中仍然存在。机制检验表明，稻作文化通过降低代理成本和促进协同创新两个渠道促进制度集体主义和创新。在法律环境较弱、城市化进程较慢、外来文化影响有限的地区，水稻种植文化对企业创新的积极影响更为明显。此外，位于水稻种植区的公司更有可能任命来自这些地区的首席执行官，这进一步与更高的创新产出相关。此外，水稻种植文化有助于将创新转化为改善的财务绩效。总的来说，这项研究揭示了非正式制度在塑造企业创新中的作用，为经济行为的文化基础提供了有价值的见解。

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