North American Journal of Economics and Finance最新文献

{"title":"Cryptocurrencies as safe havens for geopolitical risk? A quantile analysis approach","authors":"Bin Mo ,&nbsp;Jiaru Chen ,&nbsp;Qinling Shi ,&nbsp;Zichun Zeng","doi":"10.1016/j.najef.2025.102439","DOIUrl":"10.1016/j.najef.2025.102439","url":null,"abstract":"<div><div>In recent years, global geopolitical risk (GPR) events have had profound effects on economies and financial markets. This paper systematically analyzes the hedging capabilities of traditional safe-haven assets (gold, USD, and oil) in comparison to cryptocurrencies (Bitcoin, Ethereum, and Litecoin) under varying levels of GPR. Utilizing quantile analysis approaches, the study explores the dynamic nonlinear impacts of GPR on various assets and empirically analyzes the influence of key geopolitical events on asset markets. The findings reveal that cryptocurrencies have relatively weaker hedging functions in the context of geopolitical risks, while traditional safe-haven assets like gold, USD, and oil, demonstrate more consistent and robust hedging characteristics during periods of uncertainty. Notably, the correlation between GPR and asset prices is more pronounced under extreme market conditions. This research offers new asset allocation recommendations for investors and enhances the understanding of the hedging properties of cryptocurrencies.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"79 ","pages":"Article 102439"},"PeriodicalIF":3.8,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143895294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The resonance effect of economic policy uncertainty worldwide: A time–frequency analysis","authors":"Xiaojun Zhao ,&nbsp;Xinru Geng ,&nbsp;Yurui Huang ,&nbsp;Yuhang Wu ,&nbsp;Na Zhang","doi":"10.1016/j.najef.2025.102437","DOIUrl":"10.1016/j.najef.2025.102437","url":null,"abstract":"<div><div>This paper investigates global systematic risk through the resonance effect of economic policy uncertainty (EPU) across 11 major countries worldwide. We propose a theoretical framework to explain the potential cross-correlations of EPU between countries and how they may change with different time scales. In the empirical analysis, we use 326 months of EPU data from January 1997 to February 2024, and decompose the time series into high-, medium-, and low-frequency components to provide insights from a multi-scale perspective. Random matrix theory (RMT) is then applied to analyze the frequency ranges where these cross-correlations emerge. The results reveal that strong cross-correlations in EPU across countries exist, with the source of the correlations varying by frequency. Notably, the cross-correlation is most pronounced and highly robust at the low frequency. It suggests that long-term economic policy trends and global economic conditions have a substantial and widespread impact across countries, highlighting the interconnected nature of global economies and the importance of considering these correlations in international economic policymaking.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102437"},"PeriodicalIF":3.8,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143876713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The dynamics of corporate climate risk and market volatility: International evidence","authors":"Mirza Muhammad Naseer ,&nbsp;Yongsheng Guo ,&nbsp;Xiaoxian Zhu","doi":"10.1016/j.najef.2025.102435","DOIUrl":"10.1016/j.najef.2025.102435","url":null,"abstract":"<div><div>This study investigates the impact of firm climate risk exposure on market volatility, with a particular focus on the moderating roles of firm-specific and country-level characteristics. Using a comprehensive global panel of 38,808 firm-year observations across 54 countries from 2002 to 2023, we employ fixed-effects regressions, two-step GMM, and an instrumental variable approach to address endogeneity and unobserved heterogeneity. The analysis reveals that higher climate risk exposure is associated with significantly greater market volatility, reflecting investors’ heightened sensitivity to climate-related risks. Importantly, firm-level factors such as strong corporate governance, high R&amp;D intensity, and strategic positioning are found to mitigate these effects. At the country level, weaker environmental policy frameworks and underdeveloped financial systems amplify climate-induced volatility, underscoring the role of institutional quality. We also examine the influence of major climate policy events such as the Paris Agreement and find evidence of a post-policy decline in volatility, suggesting increased investor confidence in global climate governance. Overall, this study contributes to the climate finance literature by offering novel insights into how both corporate strategies and institutional environments shape the financial consequences of climate risk, providing practical implications for firms, investors, and policymakers.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102435"},"PeriodicalIF":3.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143842517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting volatility of China’s crude oil futures based on hybrid ML-HAR-RV models","authors":"Genhua Hu ,&nbsp;Xiaoqing Ma ,&nbsp;Tingting Zhu","doi":"10.1016/j.najef.2025.102428","DOIUrl":"10.1016/j.najef.2025.102428","url":null,"abstract":"<div><div>Crude oil futures are central to global economic stability, with their volatility shaping financial markets worldwide. Forecasting volatility in China’s emerging crude oil futures market presents unique challenges, particularly during market stress events such as the COVID-19 pandemic and geopolitical disruptions. This study develops hybrid ML-HAR-RV models that integrate machine learning with econometric methods to enhance predictive accuracy and economic interpretability. Our analysis reveals pronounced jumps in volatility, with asymmetric responses to market shocks. Notably, the HAR-RV model incorporating signed jumps significantly improves predictive performance. Hybrid ML-HAR-RV models, especially those leveraging signed jumps, demonstrate superior forecasting capability. These findings refine the understanding of volatility dynamics in emerging futures markets and offer actionable insights for risk management and policy design. Beyond China, our framework provides a scalable approach for modeling commodity market volatility under external shocks, contributing to broader financial modeling and economic strategy.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102428"},"PeriodicalIF":3.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143842518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carbon emission control, tariff-carbon tax reform and intersectoral migration in the presence of international capital inflows","authors":"Tai-Liang Chen ,&nbsp;Mingjie Yang ,&nbsp;Yuxiang Zou","doi":"10.1016/j.najef.2025.102434","DOIUrl":"10.1016/j.najef.2025.102434","url":null,"abstract":"<div><div>As highlighted by the World Bank (2023), multinational enterprises (MNEs) can provide both a fundamental risk to and an opportunity for climate change mitigation. It is critical for policymakers to consider policies involving MNEs for both trade openness and carbon emission controls. This paper employs a modified version of the urban–rural migration model, incorporating mobile capital and multinational firms, to analyze the policy effects of carbon tax and tariff on urban unemployment and national income. Assuming independent policy implementation, the study finds that increasing the carbon tax on pollution-generating production raises urban unemployment rates, while increasing tariffs reduces them. The intersectoral wage gap is a key determinant of the policy effect on urban unemployment levels. The paper further highlights that the elasticity of factor demand in relation to the carbon tax is crucial for understanding its effects on national income. An increase in carbon tax on dirty factor increases (decreases) the national income if, and only if the dirty factor demand elasticity relating to carbon tax is smaller (larger) than one. Likewise, an import tariff on the importable manufacturing good increases the national income if, and only if, the import elasticity with respect to the tariff is smaller than one. Additionally, a point-by-point tariff-tax reform unambiguously raises urban unemployment rates, though it may reduce unemployment levels under certain conditions. If the import elasticity related to the tariff is significantly high (low), then the policy reform will increase (decrease) national income.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102434"},"PeriodicalIF":3.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143876712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Managerial integrity and stock returns","authors":"Mo Yang ,&nbsp;Jiawei Cao ,&nbsp;Yifan Meng ,&nbsp;Hao Gong","doi":"10.1016/j.najef.2025.102436","DOIUrl":"10.1016/j.najef.2025.102436","url":null,"abstract":"<div><div>This study creates a monthly managerial integrity index (<em>MII</em>) by analyzing managers’ responses in information disclosure during site visits, and assesses its effectiveness in predicting returns. The empirical results indicate that a higher <em>MII</em> significantly predicts a lower Chinese A-share market return in the next month, with in-sample and out-of-sample R²s of 4.0133 % and 4.5714 %, respectively. This conclusion remains consistent after conducting various robustness tests. Additionally, the study reveals that managerial integrity influences stock market returns by boosting trading activity and reducing the liquidity premium.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102436"},"PeriodicalIF":3.8,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143850647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How can media attention reveal ESG improvement opportunities? A multi-algorithm machine learning-based approach for Taiwan’s electronics industry","authors":"Shu Ling Lin ,&nbsp;Yu Rou Lin ,&nbsp;Xiao Jin","doi":"10.1016/j.najef.2025.102431","DOIUrl":"10.1016/j.najef.2025.102431","url":null,"abstract":"<div><div>The wave of discussions on ESG (environment, social, governance) issues widely suggest that ESG goals can benefit companies and provide corresponding advantages to investors. However, few studies consider the actual value that ESG performance can deliver, leading to overly high expectations regarding ESG investments (<span><span>Cornell &amp; Damodaran, 2020</span></span>). Companies with high ESG expectations may overinvest in such initiatives. To counteract the potential biases this could introduce, ESG ratings agencies might discreetly adjust their weighting methods to ensure more accurate assessments. Owning to differing focal points among stakeholders, ESG scores lack persuasive reform suggestions for corporations to improve ESG actions, reducing corporate enthusiasm and confidence in ESG resource allocation. This study employs the Refinitiv news database and multi-algorithm machine learning methods to target the ESG scores of Taiwan-listed companies in the electronics industry. Neural networks (NN), support vector machine (SVM) learning, and random forest algorithms are used to construct a multi-algorithm machine learning-based approach to explore the predictive ability of media attention.</div><div>The results show that specific ESG practices of listed corporations in Taiwan’s electronics industry need to be strengthened, especially regarding CSR (corporate social responsibility) strategies and <em>Human Rights</em>. Media attention positively impacted the comprehensive ESG scores of companies in Taiwan’s electronics industry; however, the impact on individual companies was inconsistent. Finally, <em>integrating stacked generalization models</em> can improve the prediction accuracy of ESG analysis; the contribution of support vector machine algorithms was most prominent in the study sample.</div><div>This study uses multi-algorithm machine learning methods to establish a prediction model for the impact of the comprehensive ESG scores within Taiwan’s listed electronics industry on media attention. The empirical findings suggest the practical application value of the <em>semi-supervised learning</em> and <em>integrated stacking generalization models</em> for conducting ESG research; exploring enterprise shortcomings in ESG investment allocation provides feedback for enterprise planning via ESG management decision-makers and resource allocation. We recommend that listed corporations in Taiwan’s electronics industry prioritize issues related to <em>Human Rights</em> and <em>Emissions Reduction</em> when implementing future ESG actions. This study suggests potential directions for future ESG research, such as employing semi-supervised learning or support vector machines to enhance research methods.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102431"},"PeriodicalIF":3.8,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A note on the relationship between Bitcoin price and sentiment: New evidence obtained from a cryptocurrency heist","authors":"Mingnan Li,&nbsp;Viktor Manahov,&nbsp;John Ashton","doi":"10.1016/j.najef.2025.102432","DOIUrl":"10.1016/j.najef.2025.102432","url":null,"abstract":"<div><div>This study utilises the Cryptocurrency Fear &amp; Greed Index (CFGI) to analyse the bidirectional relationship between Bitcoin’s price and market sentiment during the KuCoin exchange heist. The time-varying Granger causality test reveals no significant bidirectional causality before the heist, but a strong bidirectional relationship emerges afterwards, indicating heightened interaction under increased market uncertainty. Furthermore, this relationship does not extend to other cryptocurrency heists unless they have an indirect impact on the Bitcoin market. Finally, the TVP-VAR-based connectedness approach analysis shows that the Bitcoin market panic induced by the KuCoin exchange heist has limited spillover effects on other cryptocurrency markets. Our findings help address gaps in understanding the bidirectional dynamics of the relationship between price and investor sentiment, providing valuable insights for managing Bitcoin trades and cryptocurrency portfolios during extreme market events.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102432"},"PeriodicalIF":3.8,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Asymmetric impact of global crude oil on Chinese sectors and optimal portfolio strategies: An analysis of the higher-order moment tail risk spillovers","authors":"Ruibin Liang ,&nbsp;Sheng Cheng ,&nbsp;Xinran Li","doi":"10.1016/j.najef.2025.102433","DOIUrl":"10.1016/j.najef.2025.102433","url":null,"abstract":"<div><div>In the context of highly volatile international crude oil markets, tail risk connections among sectors have become increasingly strengthened. This research analyses the tail risk connectedness of Chinese sectors from a higher-order moments perspective, and how such connectedness is driven by crude oil. We propose a novel QVAR-DY-NARDL framework and the results show prominent asymmetry features of the tail effects. In particular, when the skewness risk of Chinese industries is at an extremely low quantile, an upward trend in oil prices significantly reduces long-term connectedness. When the market is overheated, an upward trend in oil prices will contribute to a short-term decline in systemic risk. In contrast, it may slightly increase sectoral connectedness over the long term. Furthermore, the kurtosis-based connectedness of sectoral markets is more sensitive to crises and becomes virtually unaffected by crude oil at extremely high quantiles. Finally, from the perspective of portfolio construction, the minimum connectedness portfolios considering extreme negative skewness or extreme high kurtosis outperform other allocation strategies.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102433"},"PeriodicalIF":3.8,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carbon finance development, industrial structure and green financial instruments","authors":"Chenyuan Zhao ,&nbsp;Zhaolongyu Lei ,&nbsp;Xu Zhao ,&nbsp;Yuxuan Wang","doi":"10.1016/j.najef.2025.102430","DOIUrl":"10.1016/j.najef.2025.102430","url":null,"abstract":"<div><div>Based on panel data from 30 provinces (cities) in China from 2006 to 2022, this study empirically analyzes the impact of carbon finance development on the optimization and upgrading of the industrial structure with the moderating effect of green financial instruments. This study constructs a new indicator to evaluate the level of carbon finance from financial environment, energy efficiency, and technological development, and finds that the development of carbon finance has a positive impact on the optimization and upgrading of industrial structure. Green finance instruments such as green loans play a positive role in promoting development. The innovation of this study lies in redefining the indicators of industrial structure optimization across three dimensions: rationalization, advancement, and upgrading of the industrial structure. This innovation is of practical significance in exploring the direction of industrial structure optimization and upgrading.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102430"},"PeriodicalIF":3.8,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}