Pub Date : 2024-11-04DOI: 10.1016/j.intfin.2024.102075
Gbenga Adamolekun
This study examines the relationship between firms’ biodiversity risk, climate susceptibility, and bankruptcy risk. The findings indicate that firm exposure to biodiversity risk increases the likelihood of financial distress. Furthermore, we document that firms’ susceptibility to climate risk increases the likelihood of bankruptcy risk. We also demonstrate that financial constraints, growth opportunities, and membership in carbon-intensive industries can worsen or alleviate the bankruptcy implications of climate-related risk. Firms’ continent of operation is also an important consideration. The findings imply that severe climate-related vulnerabilities and firm biodiversity risk have profound consequences for corporate outcomes. This study sheds more light on how corporate financial outlook is impacted by ecological degradation and climate-related vulnerabilities.
{"title":"Firm biodiversity risk, climate vulnerabilities, and bankruptcy risk","authors":"Gbenga Adamolekun","doi":"10.1016/j.intfin.2024.102075","DOIUrl":"10.1016/j.intfin.2024.102075","url":null,"abstract":"<div><div>This study examines the relationship between firms’ biodiversity risk, climate susceptibility, and bankruptcy risk. The findings indicate that firm exposure to biodiversity risk increases the likelihood of financial distress. Furthermore, we document that firms’ susceptibility to climate risk increases the likelihood of bankruptcy risk. We also demonstrate that financial constraints, growth opportunities, and membership in carbon-intensive industries can worsen or alleviate the bankruptcy implications of climate-related risk. Firms’ continent of operation is also an important consideration. The findings imply that severe climate-related vulnerabilities and firm biodiversity risk have profound consequences for corporate outcomes. This study sheds more light on how corporate financial outlook is impacted by ecological degradation and climate-related vulnerabilities.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"97 ","pages":"Article 102075"},"PeriodicalIF":5.4,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-31DOI: 10.1016/j.intfin.2024.102074
Ioannis Chasiotis , Georgios Loukopoulos , Kanellos Toudas
This study investigates the relationship between organization capital, dividends, and firm value across 61 countries. We find that firms with higher organization capital distribute more dividends. By exploiting changes in the stringency of national labor regulations, we demonstrate that this effect strengthens when labor markets become more flexible. Additionally, we document that the market places a premium on dividend payouts from firms with higher organization capital. Further analysis reveals that this premium differential and the positive organization capital-dividend payouts relationship, are more pronounced in firms and countries marked by substantial agency issues. The robustness of our evidence is affirmed through several endogeneity tests, supporting the agency view of organization capital.
{"title":"Organization capital, dividends and firm value: International evidence","authors":"Ioannis Chasiotis , Georgios Loukopoulos , Kanellos Toudas","doi":"10.1016/j.intfin.2024.102074","DOIUrl":"10.1016/j.intfin.2024.102074","url":null,"abstract":"<div><div>This study investigates the relationship between organization capital, dividends, and firm value across 61 countries. We find that firms with higher organization capital distribute more dividends. By exploiting changes in the stringency of national labor regulations, we demonstrate that this effect strengthens when labor markets become more flexible. Additionally, we document that the market places a premium on dividend payouts from firms with higher organization capital. Further analysis reveals that this premium differential and the positive organization capital-dividend payouts relationship, are more pronounced in firms and countries marked by substantial agency issues. The robustness of our evidence is affirmed through several endogeneity tests, supporting the agency view of organization capital.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"97 ","pages":"Article 102074"},"PeriodicalIF":5.4,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-30DOI: 10.1016/j.intfin.2024.102076
Huong Le , Tung Nguyen , Andros Gregoriou
This study examines the link between CEO age and firm environmental performance. Building on the upper echelons theory, we predict that a firm is more environmentally friendly if CEOs are younger. Using hand-collected data of a total 12,512 plant-year observations for 1,074 individual firms in the period from 2010 to 2022, we document evidence that younger CEOs release significantly less greenhouse gas emissions, consistent with our conjecture. Additionally, we note that younger CEOs outperform older CEOs in terms of greenhouse gas emissions by investing more in abatement initiatives, increasing manufacturing efficiency, and increasing their use of ecologically friendly fuel. Our evidence of CEO age offers relevant implications for directors, shareholders, and financial regulators.
{"title":"CEO age and corporate environmental policies","authors":"Huong Le , Tung Nguyen , Andros Gregoriou","doi":"10.1016/j.intfin.2024.102076","DOIUrl":"10.1016/j.intfin.2024.102076","url":null,"abstract":"<div><div>This study examines the link between CEO age and firm environmental performance. Building on the upper echelons theory, we predict that a firm is more environmentally friendly if CEOs are younger. Using hand-collected data of a total 12,512 plant-year observations for 1,074 individual firms in the period from 2010 to 2022, we document evidence that younger CEOs release significantly less greenhouse gas emissions, consistent with our conjecture. Additionally, we note that younger CEOs outperform older CEOs in terms of greenhouse gas emissions by investing more in abatement initiatives, increasing manufacturing efficiency, and increasing their use of ecologically friendly fuel. Our evidence of CEO age offers relevant implications for directors, shareholders, and financial regulators.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"97 ","pages":"Article 102076"},"PeriodicalIF":5.4,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1016/j.intfin.2024.102066
Zixian Li, Fernando Moreira
Employing a panel dataset encompassing 4,412 banks from 87 countries from 1990 to 2020, we apply the autoregressive distributed lag (ARDL) model to investigate the relationship between financial openness, banks’ liability composition, and bank risk. Our findings reveal that financial openness can directly lead to an increase in bank risk in the short term but a reduction in bank risk over the long term. Additionally, we identify the composition of bank liabilities as a novel channel between financial openness and bank risk. Specifically, in the short term, financial openness amplifies bank risk through an escalation in the ratio of short-term liabilities juxtaposed with a decrease in the ratio of long-term liabilities. Conversely, in the long term, financial openness diminishes bank risk by diminishing short-term liabilities’ ratios while concurrently enhancing the proportions of long-term liabilities. Furthermore, it is noted that the direct effects of financial openness on banking risk, whether short- or long-term, may exhibit heterogeneity across different periods, country development levels, and types of capital flow.
{"title":"Financial openness, liability composition of banks, and bank risk: International evidence","authors":"Zixian Li, Fernando Moreira","doi":"10.1016/j.intfin.2024.102066","DOIUrl":"10.1016/j.intfin.2024.102066","url":null,"abstract":"<div><div>Employing a panel dataset encompassing 4,412 banks from 87 countries from 1990 to 2020, we apply the autoregressive distributed lag (ARDL) model to investigate the relationship between financial openness, banks’ liability composition, and bank risk. Our findings reveal that financial openness can directly lead to an increase in bank risk in the short term but a reduction in bank risk over the long term. Additionally, we identify the composition of bank liabilities as a novel channel between financial openness and bank risk. Specifically, in the short term, financial openness amplifies bank risk through an escalation in the ratio of short-term liabilities juxtaposed with a decrease in the ratio of long-term liabilities. Conversely, in the long term, financial openness diminishes bank risk by diminishing short-term liabilities’ ratios while concurrently enhancing the proportions of long-term liabilities. Furthermore, it is noted that the direct effects of financial openness on banking risk, whether short- or long-term, may exhibit heterogeneity across different periods, country development levels, and types of capital flow.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"97 ","pages":"Article 102066"},"PeriodicalIF":5.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1016/j.intfin.2024.102065
Menachem Meni Abudy , Guy Kaplanski , Yevgeny Mugerman
We explore the ability of the distance between short- and long-run moving averages, called MAD, to predict future returns of international market-wide indices. MAD portfolios yield abnormal profits after transaction costs, which do not reverse in the long run. This suggests that anchoring to long-run moving averages is a global phenomenon that applies also to market-wide indices. The annualized MAD portfolios’ alpha values are double-digit, with Sharpe ratios significantly higher than the global benchmarks. Similar results for developed economies and developed markets indicate that international diversification is still effective and offers significant economic benefits even among developed countries.
{"title":"Market timing with moving average distance: International evidence","authors":"Menachem Meni Abudy , Guy Kaplanski , Yevgeny Mugerman","doi":"10.1016/j.intfin.2024.102065","DOIUrl":"10.1016/j.intfin.2024.102065","url":null,"abstract":"<div><div>We explore the ability of the distance between short- and long-run moving averages, called <em>MAD</em>, to predict future returns of international market-wide indices. <em>MAD</em> portfolios yield abnormal profits after transaction costs, which do not reverse in the long run. This suggests that anchoring to long-run moving averages is a global phenomenon that applies also to market-wide indices. The annualized <em>MAD</em> portfolios’ alpha values are double-digit, with Sharpe ratios significantly higher than the global benchmarks. Similar results for developed economies and developed markets indicate that international diversification is still effective and offers significant economic benefits even among developed countries.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"97 ","pages":"Article 102065"},"PeriodicalIF":5.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.intfin.2024.102064
Zih-Chun Huang , Ivan Sangiorgi , Andrew Urquhart
This paper studies the Bitcoin volatility forecasting performance between popular traditional econometric models and machine learning techniques. We compare the 1-day to 2-month ahead forecasting performance of the Long Short-Term Memory (LSTM) and a hybrid Convolutional Neural Network-LSTM (CNN-LSTM) model to the traditional models. We find that neural networks outperform Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models for all forecasting horizons. Furthermore, the LSTM model outperforms the Heterogeneous Autoregressive (HAR) model and by integrating the Markov Transition Field (MTF) into the CNN-LSTM model, we achieve superior forecasting results in the short-term, particularly for the 7-day forecasts.
{"title":"Forecasting Bitcoin volatility using machine learning techniques","authors":"Zih-Chun Huang , Ivan Sangiorgi , Andrew Urquhart","doi":"10.1016/j.intfin.2024.102064","DOIUrl":"10.1016/j.intfin.2024.102064","url":null,"abstract":"<div><div>This paper studies the Bitcoin volatility forecasting performance between popular traditional econometric models and machine learning techniques. We compare the 1-day to 2-month ahead forecasting performance of the Long Short-Term Memory (LSTM) and a hybrid Convolutional Neural Network-LSTM (CNN-LSTM) model to the traditional models. We find that neural networks outperform Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models for all forecasting horizons. Furthermore, the LSTM model outperforms the Heterogeneous Autoregressive (HAR) model and by integrating the Markov Transition Field (MTF) into the CNN-LSTM model, we achieve superior forecasting results in the short-term, particularly for the 7-day forecasts.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"97 ","pages":"Article 102064"},"PeriodicalIF":5.4,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.intfin.2024.102062
Jan Sila, Evzen Kocenda, Ladislav Kristoufek, Jiri Kukacka
Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. We investigate the volatility connectedness dynamics of a representative set of eight major crypto assets. Methodologically, we decompose the measured volatility into positive and negative components and employ the time-varying parameters vector autoregression (TVP-VAR) framework to show distinct dynamics associated with market booms and downturns. Our findings indicate that crypto connectedness reflects important events and oscillates substantially while reaching lower limit values when compared to traditional financial markets. Periods of extremely high or low connectedness are clearly linked to specific events in the crypto market and macroeconomic or monetary history. Furthermore, existing asymmetry from good and bad volatility indicates that market downturns spill over substantially faster than comparable market surges. Overall, the connectedness dynamics are driven by a combination of both crypto (momentum, on-chain activity, off-chain activity) and legacy financial and economic (financial and economic uncertainty, and financial market performance) factors, while the asymmetry is more connected to the off-chain crypto activity and the combination of economic, financial, and monetary factors. In both the total connectedness and asymmetry modeling, these can serve as hands-on indicators to be further translated into specific portfolio re-balancing decisions, risk management, and regulatory frameworks.
{"title":"Good vs. bad volatility in major cryptocurrencies: The dichotomy and drivers of connectedness","authors":"Jan Sila, Evzen Kocenda, Ladislav Kristoufek, Jiri Kukacka","doi":"10.1016/j.intfin.2024.102062","DOIUrl":"10.1016/j.intfin.2024.102062","url":null,"abstract":"<div><div>Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. We investigate the volatility connectedness dynamics of a representative set of eight major crypto assets. Methodologically, we decompose the measured volatility into positive and negative components and employ the time-varying parameters vector autoregression (TVP-VAR) framework to show distinct dynamics associated with market booms and downturns. Our findings indicate that crypto connectedness reflects important events and oscillates substantially while reaching lower limit values when compared to traditional financial markets. Periods of extremely high or low connectedness are clearly linked to specific events in the crypto market and macroeconomic or monetary history. Furthermore, existing asymmetry from good and bad volatility indicates that market downturns spill over substantially faster than comparable market surges. Overall, the connectedness dynamics are driven by a combination of both crypto (momentum, on-chain activity, off-chain activity) and legacy financial and economic (financial and economic uncertainty, and financial market performance) factors, while the asymmetry is more connected to the off-chain crypto activity and the combination of economic, financial, and monetary factors. In both the total connectedness and asymmetry modeling, these can serve as hands-on indicators to be further translated into specific portfolio re-balancing decisions, risk management, and regulatory frameworks.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"96 ","pages":"Article 102062"},"PeriodicalIF":5.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article investigates the relationship between countries’ financial sector development and the loans extended to micro, small, and medium-sized enterprises (MSMEs or small firms) by microfinance institutions (MFIs). Using 4,801 MFI-year observations worldwide, we find a negative relationship between financial sector development and MSME lending by microfinance institutions. In other words, improvement in financial development, defined as a combination of depth, access, and efficiency, decreases micro-lending to small firms due essentially to intense competition from banks. Moreover, looking at the ownership status of microfinance institutions, we find that the intense competition between profit-oriented microfinance institutions and banks mainly drives the observed negative relationship. For nonprofit microfinance institutions, financial sector development is not significantly associated with their lending to small firms. In a less developed financial sector, microfinance institutions lend more to small firms, fulfilling their social mission.
{"title":"Financial sector development and microcredit to small firms","authors":"Désiré Kanga , Issouf Soumare , Hubert Tchakoute Tchuigoua","doi":"10.1016/j.intfin.2024.102063","DOIUrl":"10.1016/j.intfin.2024.102063","url":null,"abstract":"<div><div>This article investigates the relationship between countries’ financial sector development and the loans extended to micro, small, and medium-sized enterprises (MSMEs or <em>small firms</em>) by microfinance institutions (MFIs). Using 4,801 MFI-year observations worldwide, we find a negative relationship between financial sector development and MSME lending by microfinance institutions. In other words, improvement in financial development, defined as a combination of depth, access, and efficiency, decreases micro-lending to small firms due essentially to intense competition from banks. Moreover, looking at the ownership status of microfinance institutions, we find that the intense competition between profit-oriented microfinance institutions and banks mainly drives the observed negative relationship. For nonprofit microfinance institutions, financial sector development is not significantly associated with their lending to small firms. In a less developed financial sector, microfinance institutions lend more to small firms, fulfilling their social mission.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"96 ","pages":"Article 102063"},"PeriodicalIF":5.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.intfin.2024.102061
Ramzi Benkraiem , Khaled Guesmi , Gideon Ndubuisi , Christian Urom , Samuel Vigne
This paper analyzes the dependence and connectedness among fourth-industrial revolution technology markets (including big data and artificial intelligence, blockchain, and financial technology) and global and regional (US, Europe, and Asia) green energy markets. In particular, we consider the dynamic dependence among these markets in terms of both returns and volatility across different market conditions and investment horizons using the cross-spectral coherence and Quantile-VAR connectedness approach. Three main results emerge from our analysis. First, the return dependence is relatively stronger than volatility dependence and is stronger across most time scales among the technology markets and the European and Asian regional green energy indexes. Second, the return and volatility connectedness is stronger during extreme than normal market conditions. Unless under bullish market times, volatility connectedness appears smaller than return connectedness, implying that market volatility risks spread less forcefully among these markets than return risks under normal and bearish market periods. Third, geopolitical risks, business environment, economic policy, fixed-income, and oil and gold markets’ uncertainties are significant predictors of the degree of return and volatility connectedness. Overall, our findings offer crucial insights for short- and long-term investors interested in portfolios with modern technology and green assets. They also emphasize the roles of market and macroeconomic factors in shock propagation and their implications for low-carbon transition.
{"title":"Dependence of green energy markets on big data and other fourth industrial revolution technologies","authors":"Ramzi Benkraiem , Khaled Guesmi , Gideon Ndubuisi , Christian Urom , Samuel Vigne","doi":"10.1016/j.intfin.2024.102061","DOIUrl":"10.1016/j.intfin.2024.102061","url":null,"abstract":"<div><div>This paper analyzes the dependence and connectedness among fourth-industrial revolution technology markets (including big data and artificial intelligence, blockchain, and financial technology) and global and regional (US, Europe, and Asia) green energy markets. In particular, we consider the dynamic dependence among these markets in terms of both returns and volatility across different market conditions and investment horizons using the cross-spectral coherence and Quantile-VAR connectedness approach. Three main results emerge from our analysis. First, the return dependence is relatively stronger than volatility dependence and is stronger across most time scales among the technology markets and the European and Asian regional green energy indexes. Second, the return and volatility connectedness is stronger during extreme than normal market conditions. Unless under bullish market times, volatility connectedness appears smaller than return connectedness, implying that market volatility risks spread less forcefully among these markets than return risks under normal and bearish market periods. Third, geopolitical risks, business environment, economic policy, fixed-income, and oil and gold markets’ uncertainties are significant predictors of the degree of return and volatility connectedness. Overall, our findings offer crucial insights for short- and long-term investors interested in portfolios with modern technology and green assets. They also emphasize the roles of market and macroeconomic factors in shock propagation and their implications for low-carbon transition.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"96 ","pages":"Article 102061"},"PeriodicalIF":5.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-27DOI: 10.1016/j.intfin.2024.102060
Helena Glebocki , Sujata Saha
Economic and financial conditions respond significantly to increased measures of uncertainty, particularly in economic policy, monetary policy, and financial markets. This research employs the global vector autoregression (global VAR) model to assess the response of bilateral exchange rates, exchange rate volatility, exchange market pressure, and nominal and real effective exchange rates to shocks in global economic and financial uncertainty, along with U.S. monetary policy uncertainty, U.S. equity market volatility, and U.S. financial stress indicators. Spikes in uncertainty correspond to immediate increases in exchange rate volatility, buildup of exchange market pressure, and depreciation for emerging markets. The results are compared to advanced economies, China, and Russia separately, identifying key differences across markets.
{"title":"Global uncertainty and exchange rate conditions: Assessing the impact of uncertainty shocks in emerging markets and advanced economies","authors":"Helena Glebocki , Sujata Saha","doi":"10.1016/j.intfin.2024.102060","DOIUrl":"10.1016/j.intfin.2024.102060","url":null,"abstract":"<div><div>Economic and financial conditions respond significantly to increased measures of uncertainty, particularly in economic policy, monetary policy, and financial markets. This research employs the global vector autoregression (global VAR) model to assess the response of bilateral exchange rates, exchange rate volatility, exchange market pressure, and nominal and real effective exchange rates to shocks in global economic and financial uncertainty, along with U.S. monetary policy uncertainty, U.S. equity market volatility, and U.S. financial stress indicators. Spikes in uncertainty correspond to immediate increases in exchange rate volatility, buildup of exchange market pressure, and depreciation for emerging markets. The results are compared to advanced economies, China, and Russia separately, identifying key differences across markets.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"96 ","pages":"Article 102060"},"PeriodicalIF":5.4,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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