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.
{"title":"Time-frequency quantile effect of global uncertainty on stock markets: evidence from wavelet decomposition","authors":"Jiayuan Yuan , Weineng Zhu , Zishan Huang , Huiming Zhu","doi":"10.1016/j.najef.2025.102554","DOIUrl":"10.1016/j.najef.2025.102554","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"81 ","pages":"Article 102554"},"PeriodicalIF":3.9,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145614736","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}
Pub Date : 2025-11-13DOI: 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.
{"title":"Physical climate risk and banks’ credit risk: Worldwide evidence","authors":"Isabel Abinzano, Pilar Corredor, José Manuel Mansilla-Fernández","doi":"10.1016/j.najef.2025.102550","DOIUrl":"10.1016/j.najef.2025.102550","url":null,"abstract":"<div><div>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 <span><span>Chan-Lau and Sy (2007)</span></span> 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.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"81 ","pages":"Article 102550"},"PeriodicalIF":3.9,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568598","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}
Pub Date : 2025-11-12DOI: 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.
{"title":"The spillover effect of customer extreme climate risk: Evidence from supplier trade credit","authors":"Zhen Huang, Tianyu Dou","doi":"10.1016/j.najef.2025.102553","DOIUrl":"10.1016/j.najef.2025.102553","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"81 ","pages":"Article 102553"},"PeriodicalIF":3.9,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568501","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}
Pub Date : 2025-11-12DOI: 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.
{"title":"Does climate policy uncertainty affect expected shortfall (and Value-at-Risk) in the Chinese sector? Evidence from the mixed-frequency dynamic semi-parametric approach","authors":"Kunliang Jiang , Pengfei Luo , Wenxiao Gan , Jiashan Song , Yuejing Wang","doi":"10.1016/j.najef.2025.102555","DOIUrl":"10.1016/j.najef.2025.102555","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"81 ","pages":"Article 102555"},"PeriodicalIF":3.9,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568502","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}
Pub Date : 2025-11-07DOI: 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.
{"title":"Quantile-frequency dependence between U.S. sector stock indices and macro-financial indicators: A quantile coherence approach","authors":"Halilibrahim Gökgöz , Aamir Aijaz Syed , Catalin Gheorghe , Ahmed Jeribi","doi":"10.1016/j.najef.2025.102552","DOIUrl":"10.1016/j.najef.2025.102552","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"81 ","pages":"Article 102552"},"PeriodicalIF":3.9,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519582","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}
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.
{"title":"Asymmetric drivers of inflation: new evidence from machine learning and quantile method","authors":"Kingsley Imandojemu , Adetutu Omotola Habib , Omozele Lynda Showunmi , Loveth Oribhabor Agboola","doi":"10.1016/j.najef.2025.102551","DOIUrl":"10.1016/j.najef.2025.102551","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"81 ","pages":"Article 102551"},"PeriodicalIF":3.9,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519584","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}
Pub Date : 2025-10-28DOI: 10.1016/j.najef.2025.102548
Yingnan Cong , Yufei Hou , Yuan Ji , Xiaojing Cai
Restructuring energy consumption is essential for promoting green, low-carbon economic and societal development. Innovation-driven policies, particularly those implemented in pilot cities, play a crucial role in this transformation. This study conducts a theoretical analysis to examine how such policies influence urban energy-consumption structures. Using a multitime-point difference-in-differences model, it treats China’s national innovation-driven city pilot policies as a quasi-natural experiment. The results indicate that these policies significantly improve urban energy structures. Mechanism analyses reveal that the improvements occur mainly through green innovation and industrial upgrading. Heterogeneity analysis further indicates that the effects are more pronounced in cities with lower administrative tiers, more challenging geographical conditions, and stronger environmental priorities. These findings provide valuable policy insights for refining innovation-driven strategies, enhancing urban energy-consumption structures, and promoting sustainable economic development in China.
{"title":"Does innovation-driven policy optimize urban energy consumption? Evidence from China’s innovation-driven city pilot policies","authors":"Yingnan Cong , Yufei Hou , Yuan Ji , Xiaojing Cai","doi":"10.1016/j.najef.2025.102548","DOIUrl":"10.1016/j.najef.2025.102548","url":null,"abstract":"<div><div>Restructuring energy consumption is essential for promoting green, low-carbon economic and societal development. Innovation-driven policies, particularly those implemented in pilot cities, play a crucial role in this transformation. This study conducts a theoretical analysis to examine how such policies influence urban energy-consumption structures. Using a multitime-point difference-in-differences model, it treats China’s national innovation-driven city pilot policies as a quasi-natural experiment. The results indicate that these policies significantly improve urban energy structures. Mechanism analyses reveal that the improvements occur mainly through green innovation and industrial upgrading. Heterogeneity analysis further indicates that the effects are more pronounced in cities with lower administrative tiers, more challenging geographical conditions, and stronger environmental priorities. These findings provide valuable policy insights for refining innovation-driven strategies, enhancing urban energy-consumption structures, and promoting sustainable economic development in China.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"81 ","pages":"Article 102548"},"PeriodicalIF":3.9,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465929","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}
Pub Date : 2025-10-28DOI: 10.1016/j.najef.2025.102549
Zhiliang Zhu , Wuqi Song
Credit information sharing allows creditors to access borrowers’ credit histories, serving as an effective tool to monitor and discipline firms. Using China’s Social Credit System (CSCS) as an exogenous shock to credit information sharing, this study employs a difference-in-difference analysis and demonstrates that such sharing extends corporate debt maturity. This increase in debt maturity is attributable to improved information transparency and lowered debt agency costs. We further find that the effect is more pronounced among firms with state ownership and firms with higher leverage ratio. Additional tests show that shared credit files help alleviate firms’ investment and financing maturity mismatch issues. Collectively, this study provides new insights into the economic consequences of credit information sharing through the lens of debt maturity structure.
{"title":"Credit information sharing and corporate debt maturity structure: Evidence from a quasi-natural experiment in China","authors":"Zhiliang Zhu , Wuqi Song","doi":"10.1016/j.najef.2025.102549","DOIUrl":"10.1016/j.najef.2025.102549","url":null,"abstract":"<div><div>Credit information sharing allows creditors to access borrowers’ credit histories, serving as an effective tool to monitor and discipline firms. Using China’s Social Credit System (CSCS) as an exogenous shock to credit information sharing, this study employs a difference-in-difference analysis and demonstrates that such sharing extends corporate debt maturity. This increase in debt maturity is attributable to improved information transparency and lowered debt agency costs. We further find that the effect is more pronounced among firms with state ownership and firms with higher leverage ratio. Additional tests show that shared credit files help alleviate firms’ investment and financing maturity mismatch issues. Collectively, this study provides new insights into the economic consequences of credit information sharing through the lens of debt maturity structure.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"81 ","pages":"Article 102549"},"PeriodicalIF":3.9,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465928","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}
Pub Date : 2025-10-26DOI: 10.1016/j.najef.2025.102547
Marco Gallegati
In this study, we contrast U.S. financial and business cycles using turning point and wavelet analysis. These non-parametric methods enable us to identify the key characteristics of financial cycles and assess their relationship with business cycles without imposing assumptions about their cyclical or secular components. Contrary to the conventional view in the literature, we find that financial and business cycles are more similar than generally assumed. Wavelet analysis reveals that: i) since the 1990s, the dominant frequency range of both cycles has shifted towards lower frequencies; and ii) the observed increase in their average length is linked to a change in the relationship between financial and business cycles − from shorter business cycle frequencies (4–8 years) to higher medium-term frequencies (8–16 years). Focusing on the post-1990s period and using a measure of the financial cycle that includes equity prices, we find that the average lengths of business and financial cycles have become more aligned, at approximately 9 and 10 years, respectively. From a policy perspective, these findings cast doubt on the need for macroprudential policy as a distinct tool separate from traditional macroeconomic stabilization policy.
{"title":"Financial and business cycles in the US: A non-parametric time–frequency investigation","authors":"Marco Gallegati","doi":"10.1016/j.najef.2025.102547","DOIUrl":"10.1016/j.najef.2025.102547","url":null,"abstract":"<div><div>In this study, we contrast U.S. financial and business cycles using turning point and wavelet analysis. These non-parametric methods enable us to identify the key characteristics of financial cycles and assess their relationship with business cycles without imposing assumptions about their cyclical or secular components. Contrary to the conventional view in the literature, we find that financial and business cycles are more similar than generally assumed. Wavelet analysis reveals that: i) since the 1990s, the dominant frequency range of both cycles has shifted towards lower frequencies; and ii) the observed increase in their average length is linked to a change in the relationship between financial and business cycles − from shorter business cycle frequencies (4–8 years) to higher medium-term frequencies (8–16 years). Focusing on the post-1990s period and using a measure of the financial cycle that includes equity prices, we find that the average lengths of business and financial cycles have become more aligned, at approximately 9 and 10 years, respectively. From a policy perspective, these findings cast doubt on the need for macroprudential policy as a distinct tool separate from traditional macroeconomic stabilization policy.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"81 ","pages":"Article 102547"},"PeriodicalIF":3.9,"publicationDate":"2025-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145415996","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}
Pub Date : 2025-10-25DOI: 10.1016/j.najef.2025.102545
Murad A. Bein
The article analyzes the interconnections among ten global industrial sectors and the returns associated with low-carbon investments across a spectrum of investment horizons. The findings derived from a time-varying parameter and quantile connectedness reveal that volatility primarily stems from transient economic and financial events rather than lasting structural changes within the market. The global low-carbon returns exhibit a remarkable resilience against the volatility inherent in the global industrial sectors across diverse market conditions and within various temporal frameworks. The findings from cross-quantilograms indicate that during periods of reduced low-carbon emissions, the utilities, consumer staples, energy, materials, financial, and communication sectors act to hedge against losses, thus providing potential stability to investors seeking refuge during economic downturns. Additionally, the estimation results reveal a significant influence of monetary policy and bitcoin valuation on connectedness. A tightening monetary policy is inversely linked, and this effect is more pronounced in a declining market. Similarly, the increase in bitcoin valuations diminishes interconnectedness, indicating that cryptocurrencies may serve as alternative investment vehicles during episodes characterized by market turbulence. Overall, the outcome highlights the importance of integrating financial strategies that align with environmental sustainability.
{"title":"Dynamic interrelations and the potential of global industrial sectors to function as a refuge for the global transition towards a low-carbon economy","authors":"Murad A. Bein","doi":"10.1016/j.najef.2025.102545","DOIUrl":"10.1016/j.najef.2025.102545","url":null,"abstract":"<div><div>The article analyzes the interconnections among ten global industrial sectors and the returns associated with low-carbon investments across a spectrum of investment horizons. The findings derived from a time-varying parameter and quantile connectedness reveal that volatility primarily stems from transient economic and financial events rather than lasting structural changes within the market. The global low-carbon returns exhibit a remarkable resilience against the volatility inherent in the global industrial sectors across diverse market conditions and within various temporal frameworks. The findings from cross-quantilograms indicate that during periods of reduced low-carbon emissions, the utilities, consumer staples, energy, materials, financial, and communication sectors act to hedge against losses, thus providing potential stability to investors seeking refuge during economic downturns. Additionally, the estimation results reveal a significant influence of monetary policy and bitcoin valuation on connectedness. A tightening monetary policy is inversely linked, and this effect is more pronounced in a declining market. Similarly, the increase in bitcoin valuations diminishes interconnectedness, indicating that cryptocurrencies may serve as alternative investment vehicles during episodes characterized by market turbulence. Overall, the outcome highlights the importance of integrating financial strategies that align with environmental sustainability.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"81 ","pages":"Article 102545"},"PeriodicalIF":3.9,"publicationDate":"2025-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519583","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}
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