North American Journal of Economics and Finance最新文献

英文中文

Asymmetric spillovers of climate policy uncertainty on financial markets – Evidence from China 气候政策不确定性对金融市场的不对称溢出效应——来自中国的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-07-29 DOI: 10.1016/j.najef.2025.102513

Qiang Liu , Ting Liu , Chen Xu

Climate change is one of the greatest challenges of the 21st century, with its uncertainty significantly impacting financial stability. This study examines the spillover effects of China’s climate policy uncertainty on the stock, money, bond, foreign exchange and futures markets, using data from October 2006 to August 2024 and applying the QVAR-DY spillover index method. The findings reveal: (1) Extreme conditions amplify the spillover effects of China’s climate policy uncertainty on financial markets, especially during market booms. (2) The static analysis shows that under normal conditions, the largest spillovers are seen in the bond and futures markets. Under extreme conditions, the bond market is the most affected. Dynamic analysis shows that spillovers increase significantly during climate events (Copenhagen Summit, Carbon Peaking and Carbon Neutrality Goals). During market downturns, the bond market is impacted most; during market booms, the money market is more susceptible. (3) Net spillover analysis finds significant positive net spillovers to financial sub-markets during market booms. The findings guide efforts to manage climate policy uncertainty and reduce systemic financial risks.

气候变化是21世纪最大的挑战之一，其不确定性严重影响金融稳定。本文利用2006年10月至2024年8月的数据，运用QVAR-DY溢出指数方法，考察了中国气候政策不确定性对股票、货币、债券、外汇和期货市场的溢出效应。研究发现：(1)极端条件放大了中国气候政策不确定性对金融市场的溢出效应，尤其是在市场繁荣时期。(2)静态分析表明，在正常情况下，债券市场和期货市场的溢出效应最大。在极端情况下，债券市场受影响最大。动态分析表明，在气候事件（哥本哈根峰会、碳峰值和碳中和目标）期间，溢出效应显著增加。在市场低迷时期，债券市场受到的影响最大；在市场繁荣时期，货币市场更容易受到影响。(3)净溢出分析发现，在市场繁荣时期，金融子市场存在显著的正净溢出效应。研究结果为管理气候政策不确定性和减少系统性金融风险提供了指导。

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引用次数: 0

Dynamic spillover analysis between FX and cryptocurrency markets across different market conditions: A quantile VAR approach 外汇和加密货币市场在不同市场条件下的动态溢出分析：分位数VAR方法

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-07-28 DOI: 10.1016/j.najef.2025.102503

Young-Sung Kim , Dong-Jun Kim , Sun-Yong Choi

This study analyzes the relationship between foreign exchange (FX) markets and cryptocurrencies, focusing on both major and minor currencies. Using a quantile spillover framework, we examine how this relationship evolves under varying market conditions. The empirical findings reveal three key insights. First, spillover effects between the FX and cryptocurrency markets play a significant role in shaping their interrelationship. Under normal market conditions, the FX market has a limited influence on cryptocurrencies. Second, within the FX market, the U.S. Dollar Index exerts the most substantial impact on both major and minor currencies, while in the cryptocurrency market, Bitcoin holds the biggest influence over other cryptocurrencies. Finally, as market conditions become more extreme, spillover effects between the FX and cryptocurrency markets intensify. These findings highlight the dynamic nature of cross-market interactions and underscore the importance of considering market conditions when evaluating spillover effects between FX and cryptocurrency markets.

本研究分析了外汇（FX）市场与加密货币之间的关系，重点关注主要货币和次要货币。使用分位数溢出框架，我们研究了这种关系在不同市场条件下的演变。实证研究结果揭示了三个关键洞见。首先，外汇和加密货币市场之间的溢出效应在塑造它们之间的相互关系方面发挥着重要作用。在正常的市场条件下，外汇市场对加密货币的影响有限。其次，在外汇市场中，美元指数对主要货币和次要货币的影响最大，而在加密货币市场中，比特币对其他加密货币的影响最大。最后，随着市场条件变得更加极端，外汇和加密货币市场之间的溢出效应会加剧。这些发现突出了跨市场互动的动态性，并强调了在评估外汇和加密货币市场之间的溢出效应时考虑市场状况的重要性。

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引用次数: 0

Geopolitical risk and financial stress 地缘政治风险和金融压力

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-07-24 DOI: 10.1016/j.najef.2025.102510

Giovanni De Luca, Belinda Laura Del Gaudio, Anna Pia Di Iorio

This paper explores the relationship between geopolitical risk and financial stress. We use a quantile regression to investigate the impact of geopolitical risk on financial stress levels, along with its constituent elements, such as credit, equity, volatility, funding and safe assets. The dataset comprises observations collected on a daily basis between January 3, 2000, and November 8, 2024. The time span permits the exploitation of the relationship, with the effect of a structural break in the time series being controlled for. In light of the identified structural break in the financial market, the results indicate that an increase in geopolitical risk exerts a notable influence on financial stress. Furthermore, the findings suggest a positive relationship among all financial components. As the severity of financial stress escalates, the impact concomitantly increases. Notably, the safe assets component of the financial stress index demonstrates the greatest responsiveness to elevated stress levels. The findings are corroborated for all geographical areas examined, except for those situated within emerging markets, which appear to demonstrate a reduced sensitivity to geopolitical risk.

本文探讨了地缘政治风险与金融压力之间的关系。我们使用分位数回归来研究地缘政治风险对金融压力水平的影响，以及其构成要素，如信贷、股权、波动性、融资和安全资产。该数据集包括2000年1月3日至2024年11月8日期间每天收集的观测数据。时间跨度允许利用这种关系，同时控制时间序列中的结构中断的影响。鉴于金融市场的结构性断裂，研究结果表明，地缘政治风险的增加对金融压力产生了显著影响。此外，调查结果表明所有财务组成部分之间存在正相关关系。随着金融压力的严重程度升级，影响也随之增加。值得注意的是，金融压力指数的安全资产组成部分对压力水平升高的反应最大。调查结果在所有被调查的地理区域都得到了证实，除了那些位于新兴市场的地区，新兴市场似乎对地缘政治风险的敏感性较低。

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引用次数: 0

Cross-asset contagion and risk transmission in global financial networks 全球金融网络中的跨资产传染与风险传导

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-07-24 DOI: 10.1016/j.najef.2025.102511

Baoxiu Wu , Qing Wang

This research examines cross-asset contagion and risk transmission by modeling global financial markets as a dynamic network, integrating equities, currencies, commodities, and cryptocurrencies. Using extreme value theory and tail-dependent copulas, we develop novel measures of contagion centrality and risk pathways, uncovering a persistent core-periphery structure where central assets exhibit shock-absorber properties during crises, while peripheral nodes amplify systemic fragility. Our findings reveal that financial contagion intensifies under stress, with enduring post-crisis interconnectedness, challenging traditional diversification strategies. Crucially, network topology-not just asset class-determines vulnerability: central assets demonstrate resilience to tail risks, whereas peripheral nodes face heightened susceptibility. These insights have profound implications for systemic risk monitoring, suggesting regulators prioritize real-time tracking of core-periphery linkages, while investors adjust hedging strategies to account for nonlinear contagion channels. The study advances financial network theory by unifying cross-asset spillovers within a topological framework and offers actionable tools for crisis mitigation in interconnected markets.

本研究通过将全球金融市场建模为一个动态网络，整合股票、货币、商品和加密货币，研究了跨资产传染和风险传导。利用极值理论和尾依赖联结，我们开发了传染中心性和风险路径的新措施，揭示了一个持续的核心-外围结构，其中中心资产在危机期间表现出减震器特性，而外围节点则放大了系统脆弱性。我们的研究结果表明，金融传染在压力下加剧，危机后的相互关联性持续存在，挑战了传统的多元化战略。至关重要的是，网络拓扑——不仅仅是资产类别——决定了脆弱性：中心资产表现出对尾部风险的弹性，而外围节点则面临更高的敏感性。这些见解对系统风险监测具有深远的影响，建议监管机构优先考虑核心与外围联系的实时跟踪，而投资者则调整对冲策略以考虑非线性传染渠道。该研究通过在拓扑框架内统一跨资产溢出来推进金融网络理论，并为相互关联的市场中的危机缓解提供了可行的工具。

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引用次数: 0

Inflation shocks and the New Keynesian model: When should central banks fear inflation expectations? 通胀冲击与新凯恩斯主义模型：央行何时应该担心通胀预期？

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-07-23 DOI: 10.1016/j.najef.2025.102508

Lucio Gobbi , Ronny Mazzocchi , Roberto Tamborini

When inflation picks up, central banks fear that de-anchored expectations trigger ever increasing inflation, but this scenario does not materialize in the standard New Keynesian (NK) blueprint for central banks. Divergent inflation processes may result introducing boundedly rational beliefs about future inflation that de-anchor endogenously, together with indexed wages and persistent shocks. However, by means of simulations of the model, we find that the relevant parameters should be far beyond their consensus empirical values. Either the concern with the de-anchoring of inflation expectations is overrated or it should be given different theoretical underpinnings than the NK ones.

当通胀上升时，央行担心去锚定的预期会引发不断上升的通胀，但这种情况并没有在标准的新凯恩斯主义（NK）央行蓝图中实现。不同的通胀过程可能导致引入对未来通胀的有限理性信念，这些信念会与指数化的工资和持续的冲击一起，内在地去锚定。然而，通过对模型的模拟，我们发现相关参数应该远远超出了它们的共识经验值。要么对通胀预期去锚化的担忧被高估了，要么应该给予与朝鲜不同的理论基础。

引用次数: 0

Price dynamics in artificial stock market with realistic order book mechanism 具有现实订单机制的人工股票市场的价格动态

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-07-23 DOI: 10.1016/j.najef.2025.102504

Uzay Çetin , Şükrü C. Demirtaş , Senem Çakmak Şahin

We analyzed the effect of the daily price margin on artificial stock markets. In our study, we have two distinct market scenarios: One designed to imitate a market akin to that of Türkiye, characterized by the presence of a daily price margin regulation, and the other reflecting a market resembling the United States, where orders are not subject to daily price margin constraints. With daily price margin regulations stock prices become more accessible, positively impacting market volume. We incorporated a realistic order book mechanism for keeping track of the bid and ask orders. Traders are classified as either fundamental or noise, according to their strategies. We have also established a dynamic risk level for each stock, based on its weekly transaction volumes. Only fundamentals are risk-aware. That is, they tend to order stocks with low risk and avoid high risk stocks. We have detected emerging patterns of price fluctuations within the market scenario governed by the daily price margin regulations. Risk-aware herd behavior, despite not being explicitly modeled as an input, emerges also spontaneously within the system. These patterns emerge because of the complex relationship among dynamic risk levels of stocks, risk-aware traders and the daily price margin regulation.

我们分析了日差价对人为股票市场的影响。在我们的研究中，我们有两种不同的市场情景：一种是模仿类似于 rkiye的市场，其特点是存在每日价格保证金监管，另一种反映了类似于美国的市场，其中订单不受每日价格保证金约束。随着每日保证金规定的实施，股票价格变得更容易接近，这对市场交易量产生了积极影响。我们加入了一个现实的订单簿机制，以保持跟踪出价和要价订单。根据交易者的策略，他们可以分为基本面交易者和噪音交易者。我们还根据每只股票的周交易量为其设定了动态风险水平。只有基本面才是有风险意识的。也就是说，他们倾向于购买低风险的股票，而避开高风险的股票。我们发现，在每日保证金规定的市场情况下，出现了价格波动的新模式。有风险意识的群体行为，尽管没有被明确地建模为输入，但也会在系统中自发地出现。这些模式的出现是由于股票的动态风险水平、风险意识强的交易员和每日价格保证金监管之间的复杂关系。

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引用次数: 0

An analytical approximation for European options under a Heston-type model with regime switching 带制度切换的heston型模型下欧式期权的解析逼近

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-07-22 DOI: 10.1016/j.najef.2025.102500

Wenting Chen , Xin-Jiang He

In this paper, we consider the pricing of European options under a generalized regime-switching Heston model. By “generalized”, it means that all parameters of the original Heston model are expected to vary among various economic states. This broad assumption regarding regime switching has impeded the application of existing analytical techniques used to calculate European option prices under Heston-type regime-switching models. Albeit difficult, we have managed to derive an analytical approximation for the price of European options with the use of frozen coefficient technique. Remarkably, an error estimation for the approximation has been established theoretically and verified quantitatively through numerical experiments. Finally, through a preliminary empirical study, the current model is shown to be superior to a class of generally used Heston-type models, implying that the present model, together with the newly derived formula, can be safely used in actual financial market for pricing European options expiring in no more than three months.

本文研究了在广义制度切换赫斯顿模型下欧式期权的定价问题。所谓“普遍化”，是指原赫斯顿模型的所有参数在不同的经济状态下都是不同的。这种关于制度转换的广泛假设阻碍了现有分析技术在赫斯顿型制度转换模型下计算欧洲期权价格的应用。尽管困难重重，我们还是成功地利用冻结系数技术推导出了欧洲期权价格的解析近似。值得注意的是，在理论上建立了近似的误差估计，并通过数值实验进行了定量验证。最后，通过初步的实证研究，本文模型优于一类常用的heston型模型，这意味着本文模型与新导出的公式可以安全地用于实际金融市场中到期不超过3个月的欧式期权定价。

引用次数: 0

Cascading failure, financial network and systemic risk 级联失效、金融网络与系统性风险

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-07-20 DOI: 10.1016/j.najef.2025.102505

Chuangxia Huang , Hualu Miao , Xiaoguang Yang , Jie Cao , Huirui Yang

How to accurately measure the systemic risk is one of the fundamental and challenging problems in the field of risk management. Most previous studies do not fully consider the cascading failure mechanism caused by risk co-contagion and network effects, leading to misestimation of systemic risk. We construct financial institution tail risk networks by LASSO technique and then simulating the cascading process of risk contagion by ΔCoES on the networks. By developing a general cascading failure model, this paper proposes a novel indicator, ESRank, to measure systemic risk. We apply ESRank to analyze Chinese financial institutions and the empirical results suggest that: (i) during the crisis periods, especially the 2015–2016 stock crash period, the Chinese financial system manifests a higher ESRank in comparison to normal periods; (ii) the securities sector is the largest risk contributor before the stock crash, while the diversified financial institutions have displayed increasing risk contributions afterwards; (iii) compared with the traditional systemic risk indicators such as VaR, CoVaR and SRISK, the proposed ESRank demonstrates the outstanding characteristics of better predictive and explanatory capabilities regarding institutional profitability.

如何准确地度量系统性风险是风险管理领域的基础性和挑战性问题之一。以往的研究大多没有充分考虑风险共传染和网络效应导致的级联失效机制，导致对系统性风险的错误估计。利用LASSO技术构建金融机构尾部风险网络，并利用ΔCoES在网络上模拟风险传染的级联过程。通过建立一个通用的级联失效模型，本文提出了一个新的指标ESRank来衡量系统性风险。我们运用ESRank对中国金融机构进行分析，实证结果表明：(1)在危机时期，特别是2015-2016年股灾时期，中国金融体系的ESRank高于正常时期；(2)股灾前证券行业是最大的风险贡献者，股灾后多元化金融机构的风险贡献呈上升趋势；（iii）与传统的系统风险指标VaR、CoVaR和SRISK相比，所提出的ESRank对机构盈利能力具有更好的预测和解释能力。

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引用次数: 0

Enhanced index tracking: A relative downside risk approach 加强指数跟踪：一种相对下行风险的方法

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-07-17 DOI: 10.1016/j.najef.2025.102501

Ronghua Luo , Zeyu Huang , Yangyi Liu

We introduce the Relative Downside Tracking Error (RDTE) model, a dynamic enhanced indexing method that adapts to the time-varying and mean-reverting nature of market volatility. The RDTE model dynamically adjusts the weights assigned to downside deviations based on market volatility, allowing for greater flexibility during high-volatility periods. This flexibility helps the model reduce the emphasis on short-term fluctuations, focusing instead on minimizing overall downside risk. By doing so, the model effectively controls portfolio distortion, leading to more stable long-term performance. Empirical analyses of U.S. and Chinese stock markets demonstrate that the RDTE model consistently outperforms traditional models, delivering higher returns, lower downside risk, and better risk-adjusted performance. This outperformance is driven by the RDTE model’s effective downside risk management during volatile periods, as confirmed by its superior long-term performance in both markets.

我们引入了相对下行跟踪误差（RDTE）模型，这是一种适应市场波动时变和均值回归性质的动态增强索引方法。RDTE模型根据市场波动动态调整分配给下行偏差的权重，从而在高波动时期具有更大的灵活性。这种灵活性有助于模型减少对短期波动的强调，而将重点放在最小化整体下行风险上。通过这样做，该模型有效地控制了投资组合的扭曲，从而导致更稳定的长期表现。对美国和中国股市的实证分析表明，RDTE模型始终优于传统模型，具有更高的回报、更低的下行风险和更好的风险调整绩效。这种优异的表现是由RDTE模型在波动时期有效的下行风险管理所驱动的，正如其在两个市场的卓越长期表现所证实的那样。

引用次数: 0

Understanding the connectedness between US traditional assets and green cryptocurrencies during crises 了解危机期间美国传统资产与绿色加密货币之间的联系

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-07-16 DOI: 10.1016/j.najef.2025.102474

Nikolaos Kyriazis , Shaen Corbet

This research examines the dynamic interaction between conventional financial assets, namely the US dollar, the S&P 500 index, gold and crude oil, and ten major green cryptocurrencies, focusing on their spillover linkages and hedging capacities during major global economic and geopolitical shocks. The study analyses daily data to uncover spillover effects using the innovative Quantile-Vector Autoregressive methodology developed by Cunado et al. (2023). Results indicate that green cryptocurrencies significantly interact with other examined instruments. Algorand, Cardano, IOTA, TRON and Powerledger demonstrate the largest interactive effects, with the latter standing out as a consistent transmitter of influence across both crises, demonstrating that this sub-class of cryptocurrency is exhibiting elevated maturity. Traditional assets predominantly act as receivers of such risk dynamics from more speculative asset classes, with gold identified as an effective absorber of spillovers, especially in bear markets. Conversely, the US dollar and crude oil are identified as large transmitters of spillover impacts, a result found to be particularly influential in periods of geopolitical conflict. The study further reveals that green cryptocurrencies promoting trust, innovation, and renewable energy are more effectively connected with traditional investments than those focusing on financial services or business accessibility, presenting diversification opportunities during crises.

本研究考察了传统金融资产（即美元、标准普尔500指数、黄金和原油）与十大绿色加密货币之间的动态相互作用，重点研究了它们在重大全球经济和地缘政治冲击期间的溢出联系和对冲能力。该研究使用Cunado等人（2023）开发的创新分位数向量自回归方法分析日常数据，以揭示溢出效应。结果表明，绿色加密货币与其他被检查的工具显着相互作用。Algorand、Cardano、IOTA、TRON和Powerledger表现出最大的互动效应，后者在两次危机中都表现出一致的影响力，表明这一子类的加密货币正表现出更高的成熟度。传统资产主要充当来自更具投机性的资产类别的风险动态的接受者，而黄金被认为是溢出效应的有效吸收器，尤其是在熊市中。相反，美元和原油被认为是外溢影响的大传播者，这一结果在地缘政治冲突时期尤为重要。该研究进一步表明，促进信任、创新和可再生能源的绿色加密货币比那些专注于金融服务或商业可及性的加密货币更有效地与传统投资联系在一起，在危机期间提供了多样化的机会。

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