North American Journal of Economics and Finance最新文献

英文中文

Stock market volatility and multi-scale positive and negative bubbles 股市波动与多尺度正负泡沫

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2024-10-16 DOI: 10.1016/j.najef.2024.102300

Rangan Gupta , Jacobus Nel , Joshua Nielsen , Christian Pierdzioch

We study whether booms and busts in the stock market of the United States (US) drives its volatility. Given this, first, we employ the Multi-Scale Log-Periodic Power Law Singularity Confidence Indicator (MS-LPPLS-CI) approach to identify both positive and negative bubbles in the short-, medium, and long-term. We successfully detect major crashes and rallies during the weekly period from January 1973 to December 2020. Second, we utilize a nonparametric causality-in-quantiles approach to analyze the predictive impact of our bubble indicators on daily data-based weekly realized volatility (RV). This econometric framework allows us to circumvent potential misspecification due to nonlinearity and instability, rendering the results of weak causal influence derived from a linear framework invalid. The MS-LPPLS-CIs reveal strong evidence of predictability for RV over its entire conditional distribution. We observe relatively stronger impacts for the positive bubbles indicators, with our findings being robust to an alternative metric of volatility, namely squared returns, and weekly realized volatilities derived from 5 (RV5)- and 10 (RV10)-minutes interval intraday data. Furthermore, we detect evidence of predictability for RV5 and RV10 of nine other developed and emerging stock markets. In addition, we also find strong evidence of causal feedbacks from RV5 and RV10 on to the MS-LPPLS-CIs of the 10 countries considered. Finally, time-varying connectedness of the RVs of the G7 stock markets is also shown to be strongly (positively) predicted by the connectedness of the six bubbles indicators. Our findings have significant implications for investors and policymakers.

我们研究了美国股市的繁荣和萧条是否会导致其波动。有鉴于此，我们首先采用多尺度对数周期幂律奇异性置信度指标（MS-LPPLS-CI）方法来识别短期、中期和长期的正负泡沫。我们成功地检测到了 1973 年 1 月至 2020 年 12 月期间每周的重大暴跌和反弹。其次，我们利用非参数因果关系-量化方法来分析我们的泡沫指标对基于每日数据的每周已实现波动率（RV）的预测影响。这种计量经济学框架使我们能够规避非线性和不稳定性导致的潜在规格错误，从而使线性框架得出的微弱因果影响结果失效。MS-LPPLS-CIs 揭示了 RV 在其整个条件分布中的可预测性的有力证据。我们观察到正向气泡指标的影响相对更强，我们的研究结果对另一种波动率指标（即收益平方）以及由 5 分钟（RV5）和 10 分钟（RV10）区间盘中数据得出的每周已实现波动率都是稳健的。此外，我们还发现了其他九个发达和新兴股票市场的 RV5 和 RV10 的可预测性证据。此外，我们还发现了从 RV5 和 RV10 到所考虑的 10 个国家的 MS-LPPLS-CI 的因果反馈的有力证据。最后，七国集团股票市场 RV 的时变关联性也被证明可以通过六个泡沫指标的关联性进行强（正）预测。我们的研究结果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

Unveiling asymmetric return spillovers with portfolio implications among Indian stock sectors during Covid-19 pandemic 揭示科维德-19 大流行病期间印度股票行业的非对称回报溢出效应及投资组合影响

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2024-10-16 DOI: 10.1016/j.najef.2024.102297

Aswini Kumar Mishra, Kamesh Anand K, Akhil Venkatasai Kappagantula

This paper aims to provide a systematic inquiry into the return spillover dynamics between a network of Indian sectoral indices during the pre- and post-pandemic periods. To analyze the same, this paper uses the asymmetric time-varying parameter vector autoregressions (TVP-VAR) framework. Furthermore, in the spirit of Broadstock et al. (2020), we perform dynamic portfolio exercises based on common hedging techniques and the minimum connectedness portfolio approach to determine what better captures asymmetry. Our daily dataset includes 12 sectoral stocks spanning from January 01, 2017, to May 5, 2023. The findings reveal that negative connectedness dominates throughout the sample period, demonstrating that profit-maximizing agents and risk-averse investors are more likely to react negatively to news. We also show that in the network, the average net transmitters are the banking and other financial service sectors, whereas the net receivers are the information technology, pharmaceutical, and fast-moving consumer goods sectors throughout the period under consideration. Our results show that the minimum connectedness portfolio (MCoP) approach is a very useful method based on Sharpe ratios, as it is either the first or second most profitable among these three competing methods. These results, therefore, yield valuable insights for policymakers and investors.

本文旨在系统探究印度行业指数网络在大流行前后的回报溢出动态。为了进行分析，本文使用了非对称时变参数向量自回归（TVP-VAR）框架。此外，本着 Broadstock 等人（2020 年）的精神，我们根据常见的对冲技术和最小连通性投资组合方法进行了动态投资组合练习，以确定哪种方法能更好地捕捉不对称现象。我们的每日数据集包括 12 种行业股票，时间跨度为 2017 年 1 月 1 日至 2023 年 5 月 5 日。研究结果表明，在整个样本期间，负连通性占主导地位，这表明利润最大化代理人和风险规避型投资者更有可能对新闻做出负面反应。我们还发现，在整个样本期内，网络中的平均净传播者是银行业和其他金融服务业，而净接收者则是信息技术、医药和快速消费品行业。我们的研究结果表明，基于夏普比率，最小关联度投资组合（MCoP）方法是一种非常有用的方法，因为在这三种竞争方法中，它是第一或第二大盈利方法。因此，这些结果为政策制定者和投资者提供了宝贵的见解。

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引用次数: 0

Active portfolio management in the face of ESG uncertainty: An agile framework for adaptive investment strategies 面对环境、社会和治理不确定性的积极投资组合管理：适应性投资战略的敏捷框架

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2024-10-14 DOI: 10.1016/j.najef.2024.102295

Limin Wen , Junxue Li , Jiliang Sheng , Yi Zhang

This paper establishes an active portfolio model that considers corporate Environmental, Social, and Governance (ESG) ratings, examining the impact of ESG information on portfolio performance. Based on the exponential utility function, the paper incorporates ESG scores and ESG risk (uncertainty factors) into active portfolio management and derives the analytical solution of the model. Theoretical findings indicate that ESG risk adjusts the optimal portfolio, helping to mitigate losses due to ESG divergence. The paper conducts empirical research using ESG ratings from three well-known rating agencies and the CSI300 index. The empirical results demonstrate that ESG preferences enhance the ESG quality of the portfolio. Consistent with theoretical predictions, reliance on a single ESG rating may lead to adverse outcomes, especially when the selected rating agency’s standards deviate from market norms. In contrast, portfolios that include ESG uncertainty exhibit higher stability and lower loss risk, showing good robustness across different stages and industries.

本文建立了一个考虑企业环境、社会和治理（ESG）评级的主动投资组合模型，研究了ESG信息对投资组合绩效的影响。基于指数效用函数，本文将 ESG 分数和 ESG 风险（不确定性因素）纳入主动投资组合管理，并推导出该模型的分析解决方案。理论研究结果表明，ESG 风险会调整最优投资组合，有助于减少 ESG 分歧造成的损失。本文利用三家知名评级机构的 ESG 评级和沪深 300 指数进行了实证研究。实证结果表明，ESG 偏好会提高投资组合的 ESG 质量。与理论预测一致，依赖单一的 ESG 评级可能会导致不利的结果，尤其是当所选择的评级机构的标准偏离市场规范时。与此相反，包含 ESG 不确定性的投资组合表现出更高的稳定性和更低的损失风险，在不同阶段和不同行业都表现出良好的稳健性。

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引用次数: 0

Going Green: Effect of green bond issuance on corporate debt financing costs 走向绿色发行绿色债券对企业债务融资成本的影响

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2024-10-11 DOI: 10.1016/j.najef.2024.102299

Qingsong Ruan , Chengyu Li , Dayong Lv , Xiaokun Wei

This paper investigates the influence of green bond (GB) issuance on the credit spread of non-green bonds (NGBs) issued by the same firm. Based on Chinese bond market data from 2013 to 2021, our results show that GB issuers experience a decline in NGB credit spreads after issuing GBs, indicating that “going green” can lower corporate debt financing costs. This beneficial effect is more salient among firms with lower bond liquidity, supporting the “bond liquidity story” that investors anticipate increased bond liquidity following GB issuance and thus charge lower credit spreads. In contrast, we find limited evidence for alternative explanations such as the “default risk story,” “halo effect story,” or “information asymmetry story.” Our research highlights the financial benefits of GB issuance and contributes to related literature on the economic implications of green finance. The findings also offer valuable insights for policymakers and corporate executives seeking to promote sustainable investment.

本文研究了发行绿色债券（GB）对同一企业发行的非绿色债券（NGB）信用利差的影响。基于 2013 年至 2021 年的中国债券市场数据，我们的研究结果表明，绿色债券发行人在发行绿色债券后，非绿色债券的信用利差有所下降，这表明 "绿色化 "可以降低企业的债务融资成本。这种有利效应在债券流动性较低的企业中更为突出，支持了 "债券流动性故事"，即投资者预期国债发行后债券流动性会增加，从而收取较低的信用利差。相比之下，我们发现 "违约风险说"、"光环效应说 "或 "信息不对称说 "等其他解释的证据有限。我们的研究强调了国标发行的金融效益，并为有关绿色金融的经济影响的相关文献做出了贡献。研究结果还为寻求促进可持续投资的政策制定者和企业高管提供了有价值的见解。

引用次数: 0

Optimal control problem for hybrid pension plans under longevity risk for alpha-maxmin expected utility minimization 阿尔法-最大最小预期效用最小化的长寿风险下混合养老金计划的最优控制问题

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2024-10-09 DOI: 10.1016/j.najef.2024.102285

Ya Chen, Wei Liu, Zhen Zhao

This paper investigates the problem of portfolio selection and adjustment of hybrid pension plans under longevity risk. The longevity risk is described by a time-varying mortality rate, which is an extension of Markham’s law. Suppose that the financial market assets consist of a risk-free asset, a stock, and a defaultable bond. Specifically, the stock price is described by a constant elasticity of variance (CEV) model. The objective is to minimize interim adjustments to contributions and benefits under an exponential loss function, as well as the loss of terminal wealth. It is difficult for investors to fully understand the market information, so there is uncertainty in the financial market. By applying robust control theory to formulate investors’ aversion to uncertainty, we obtain the

α

-robust optimal investment strategies and the adjustment strategies. Finally, numerical analysis is presented to discuss the influence of the model parameters on the

α

-robust optimal control strategies.

本文研究了长寿风险下混合养老金计划的投资组合选择和调整问题。长寿风险由随时间变化的死亡率来描述，它是马卡姆定律的延伸。假设金融市场资产由无风险资产、股票和可违约债券组成。具体来说，股票价格由恒定方差弹性模型（CEV）描述。目标是在指数损失函数下最大限度地减少缴费和福利的中期调整，以及最终财富的损失。投资者很难完全了解市场信息，因此金融市场存在不确定性。通过运用鲁棒控制理论来阐述投资者对不确定性的厌恶，我们得到了α-鲁棒最优投资策略和调整策略。最后，通过数值分析讨论模型参数对 α- 稳健最优控制策略的影响。

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引用次数: 0

Multiscale dynamic interdependency between China’s crude oil futures and petrochemical-related commodity futures: An integrated perspective from the industry chain system 中国原油期货与石化相关商品期货的多尺度动态相互依存关系：产业链体系的综合视角

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2024-10-04 DOI: 10.1016/j.najef.2024.102296

Jie Yang , Yun Feng , Hao Yang

This paper examines the coupling of China’s petrochemical-related commodity futures from the perspective of an integrated system as well as the multiscale interdependency between this system and Shanghai crude oil futures (SCM) with two globally influential benchmarks, i.e., Brent and WTI, as comparisons. Our methods innovatively build on the multifractal theory and provide in-depth analysis across various time scales. The results show the dynamic coupling of China’s oil industry chain system (ICS) can reflect its level of systemic risk concentration well. The greater the time scale, the stronger the coupling. The abrupt deterioration of the external economic environment enhanced the impact of crude oil on the ICS, but the impact from SCM increased the most. Furthermore, the higher dependency preference of ICS for SCM confirms the effectiveness of this emerging futures market in reflecting domestic oil supply and demand but continuously weakens as the time scale increases, indicating the dominance of Brent and WTI in the long run.

本文以布伦特原油期货（Brent）和WTI原油期货（WTI）这两个具有全球影响力的基准为比较对象，从综合系统的角度研究了中国石油化工相关商品期货的耦合性，以及该系统与上海原油期货（SCM）之间的多尺度相互依存关系。我们的方法创新性地建立在多分形理论的基础上，提供了跨时间尺度的深入分析。结果表明，中国石油产业链系统（ICS）的动态耦合能够很好地反映其系统性风险的集中程度。时间尺度越大，耦合度越强。外部经济环境的突然恶化增强了原油对 ICS 的影响，但来自单片机的影响增幅最大。此外，ICS 对 SCM 的依赖偏好较高，证实了这一新兴期货市场在反映国内石油供需方面的有效性，但随着时间尺度的增加，这种依赖偏好持续减弱，表明布伦特和 WTI 在长期内占据主导地位。

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引用次数: 0

Momentum mechanisms under heterogeneous beliefs 异质信念下的动量机制

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2024-10-01 DOI: 10.1016/j.najef.2024.102262

Yu Yan , Yan Tong , Yiming Wang

We establish a continuous-time heterogeneous beliefs model to discuss the mechanisms of Momentum and Reversal. Price learning, information transmission and extrapolative expectation are incorporated into a unified framework for the Momentum and Reversal. The calibration results from SP500 show that the presence of Extrapolators and Information-driven Traders are important influences of Momentum and Reversal in all phases. We also find that momentum and reversal become significantly stronger as belief weights approach true belief weights.

我们建立了一个连续时间异质信念模型来讨论动量和反转的机制。价格学习、信息传递和外推预期被纳入动量与反转的统一框架。SP500 指数的校准结果表明，外推者和信息驱动交易者的存在是动量和反转在所有阶段的重要影响因素。我们还发现，当信念权重接近真实信念权重时，动量和反转会变得明显更强。

引用次数: 0

Multiscale tail risk integration between safe-haven assets and Africa’s emerging equity market 避险资产与非洲新兴股票市场之间的多尺度尾部风险整合

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2024-09-30 DOI: 10.1016/j.najef.2024.102294

Dan Owusu Amponsah , Mohammad Abdullah , Emmanuel Joel Aikins Abakah , Joshua Yindenaba Abor , Chi-Chuan Lee

This study examines the multiscale tail risk integration between safe-haven assets and top equity markets in Africa (South Africa, Kenya, Egypt, Ghana, Nigeria, Botswana, Zambia, and Morocco) as well as portfolio implications. We further investigate the role of global economic factors in these relationships by employing Conditional Autoregressive Value at Risk and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise-based TVP-VAR with data spanning from January 2010 to September 2024. Our findings show that while the equity market in South Africa is a net transmitter of tail risk spillovers, the rest of the equity markets are net receivers. They also reveal that while gold and silver transmit significant shocks to the other assets, Bitcoin receives considerable shocks from the other assets. We conclude that global economic factors and spillovers from safe-haven assets significantly affect the tail risk exposures of Africa’s equity markets. Our findings have significant implications for investment decision-making.

本研究探讨了避险资产与非洲顶级股票市场（南非、肯尼亚、埃及、加纳、尼日利亚、博茨瓦纳、赞比亚和摩洛哥）之间的多尺度尾部风险整合以及投资组合的影响。我们利用 2010 年 1 月至 2024 年 9 月的数据，采用条件自回归风险价值和基于自适应噪声的完全集合经验模式分解 TVP-VAR，进一步研究了全球经济因素在这些关系中的作用。我们的研究结果表明，南非股票市场是尾部风险溢出效应的净传播者，而其他股票市场则是净接受者。研究还显示，黄金和白银会向其他资产传递大量冲击，而比特币则会从其他资产中接收大量冲击。我们的结论是，全球经济因素和避险资产的溢出效应极大地影响了非洲股票市场的尾部风险敞口。我们的研究结果对投资决策具有重要意义。

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引用次数: 0

Introducing a novel fragility index for assessing financial stability amid asset bubble episodes 引入新的脆弱性指数，评估资产泡沫事件中的金融稳定性

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2024-09-24 DOI: 10.1016/j.najef.2024.102291

Radu Lupu , Adrian Cantemir Călin , Dan Gabriel Dumitrescu , Iulia Lupu

This paper is devoted to the development of an innovative fragility index designed to capture comprehensively the dynamics of financial stability during periods characterized by asset bubbles. Utilizing a multifaceted methodological framework, the study begins by identifying bubble occurrences and calculating the delta CoVaR systemic risk metric. Building on established macroeconomic methodologies, we then propose an indicator to quantify the impact of financial bubbles on the stability of an emerging market. Specifically, we construct two coincident indicators based on daily observations of financial stability for the twenty most liquid Romanian companies. The first indicator is derived from the delta CoVaR values of these companies, while the second is computed using the residuals of a model that employs the same financial stability metric as the dependent variable, with a binary variable representing the presence of asset bubbles as the explanatory factor. This second coincident indicator tracks financial stability in the absence of bubble effects. The disparity between these two indicators forms the basis for the creation of an index, termed the “bubble fragility index,” which measures the overall susceptibility of financial stability to asset bubbles. In the context of the Romanian market, this study demonstrates that periods marked by asset bubbles are associated with elevated systemic risks. Our findings indicate that the presence of bubbles significantly intensifies financial risk factors, creating conditions conducive to severe market corrections and economic downturns. We identify specific intervals during which fragility reaches peak levels, including June to September 2018, December 2018 to March 2019, March 2020, and March 2022.

本文致力于开发一种创新的脆弱性指数，旨在全面捕捉以资产泡沫为特征的时期的金融稳定动态。本研究利用多方面的方法框架，首先识别泡沫的发生，并计算出 delta CoVaR 系统性风险指标。然后，我们以既定的宏观经济方法为基础，提出了量化金融泡沫对新兴市场稳定性影响的指标。具体来说，我们根据对罗马尼亚 20 家流动性最好的公司财务稳定性的每日观察，构建了两个重合指标。第一个指标来源于这些公司的 CoVaR 三角洲值，第二个指标则是利用一个模型的残差计算得出的，该模型采用了相同的金融稳定性指标作为因变量，并以代表资产泡沫存在的二进制变量作为解释因素。第二个重合指标跟踪的是没有泡沫效应时的金融稳定性。这两个指标之间的差异构成了创建 "泡沫脆弱性指数 "的基础，该指数衡量金融稳定性对资产泡沫的整体易感性。在罗马尼亚市场的背景下，本研究表明，资产泡沫时期与系统性风险上升有关。我们的研究结果表明，泡沫的存在大大加剧了金融风险因素，为严重的市场调整和经济衰退创造了有利条件。我们确定了脆弱性达到峰值的具体时间段，包括 2018 年 6 月至 9 月、2018 年 12 月至 2019 年 3 月、2020 年 3 月和 2022 年 3 月。

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引用次数: 0

ESG risk, economic policy uncertainty, and the downside risk: Evidence from US firms 环境、社会和公司治理风险、经济政策不确定性和下行风险：来自美国公司的证据

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2024-09-24 DOI: 10.1016/j.najef.2024.102293

Chia-Hsien Tang , Hung-Chun Liu , Yen-Hsien Lee , Yuan-Teng Hsu

This study investigates the relationship between risk factors of Environmental, Social, and Governance (ESG) and the downside risk of U.S. firms and tackles the role of economic policy uncertainty (EPU) in this relationship. Our results show that the downside risk of firms, as measured by value-at-risk and lower partial moment, is positively affected by ESG risk scores, and that this effect becomes more pronounced as EPU rises. These results are robust to two other alternative measures of ESG risk. We argue that enhancing ESG management and adaptability to economic uncertainty is crucial for aligning with sustainable development goals. Our findings provide valuable insights for U.S. firms, investors, and policymakers looking to navigate the evolving risk landscape.

本研究调查了环境、社会和治理（ESG）风险因素与美国公司下行风险之间的关系，并探讨了经济政策不确定性（EPU）在这一关系中的作用。我们的研究结果表明，以风险价值和下偏矩值衡量的企业下行风险受到 ESG 风险评分的积极影响，而且随着 EPU 的上升，这种影响变得更加明显。这些结果对其他两种衡量环境、社会和治理风险的方法都是稳健的。我们认为，加强 ESG 管理和对经济不确定性的适应性对于实现可持续发展目标至关重要。我们的研究结果为美国公司、投资者和决策者在不断变化的风险环境中寻找导航提供了宝贵的见解。

引用次数: 0

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