Pub Date : 2026-01-01DOI: 10.1016/j.najef.2025.102573
Abdulaziz A. Alshamrani , David Rakowski , Salil Sarkar
We examine whether credit ratings reflect the political ideology of the broader top management team rather than that of the CEO alone. Using political donation data for top executives from 1992 to 2017, we show that firms with more conservative executive teams receive higher credit ratings and are more likely to be investment grade. While CEO conservatism is positively associated with ratings, the ideology of non-CEO executives has comparable and often greater explanatory power. In firms where CEO and executive team ideologies diverge, ratings align more closely with the ideology of non-CEO managers. Additional analyses exploiting CEO turnover, firm fixed effects, and matched samples largely rule out alternative explanations based on firm culture or selection. Overall, the results suggest that credit rating agencies condition on the risk preferences of senior leadership teams rather than solely on CEOs.
{"title":"Credit ratings and top executives’ political ideology","authors":"Abdulaziz A. Alshamrani , David Rakowski , Salil Sarkar","doi":"10.1016/j.najef.2025.102573","DOIUrl":"10.1016/j.najef.2025.102573","url":null,"abstract":"<div><div>We examine whether credit ratings reflect the political ideology of the broader top management team rather than that of the CEO alone. Using political donation data for top executives from 1992 to 2017, we show that firms with more conservative executive teams receive higher credit ratings and are more likely to be investment grade. While CEO conservatism is positively associated with ratings, the ideology of non-CEO executives has comparable and often greater explanatory power. In firms where CEO and executive team ideologies diverge, ratings align more closely with the ideology of non-CEO managers. Additional analyses exploiting CEO turnover, firm fixed effects, and matched samples largely rule out alternative explanations based on firm culture or selection. Overall, the results suggest that credit rating agencies condition on the risk preferences of senior leadership teams rather than solely on CEOs.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"82 ","pages":"Article 102573"},"PeriodicalIF":3.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884168","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 study examines the impact of full-fledged inflation targeting (IT) regime adoption on stock market liquidity in emerging markets, addressing a critical yet underexplored dimension of monetary policy’s financial market effects. Understanding how IT influences financial market stability is crucial, particularly for emerging economies where liquidity constraints exacerbate financial fragility. Analyzing 35 emerging countries, of which 15 are inflation targeters, over the period 1990–2023, we employ Difference-in-Differences and Doubly Robust methods to assess the influence of IT on stock market liquidity, utilizing several proxies for liquidity. Our findings indicate that IT has a significant impact on liquidity, particularly during crises such as the Global Financial Crisis (GFC) and the COVID-19 pandemic. The positive impact of IT adoption on stock market liquidity emerges after a three-year delay and becomes statistically significant once key economic and financial variables are controlled for. Robust across multiple checks, our study extends prior literature by offering a broad multi-country perspective, isolating IT’s unique role, and using advanced methods to address selection bias. It highlights IT as a key policy tool for financial stability, equipping central bankers with strategies to prevent liquidity dry-ups and strengthen economic resilience in turbulent times.
{"title":"Inflation targeting and stock market liquidity: a difference-in-difference and doubly robust analysis of emerging markets","authors":"Ichrak Dridi , Mohamed Malek Belhoula , Adel Boughrara","doi":"10.1016/j.najef.2025.102580","DOIUrl":"10.1016/j.najef.2025.102580","url":null,"abstract":"<div><div>This study examines the impact of full-fledged inflation targeting (IT) regime adoption on stock market liquidity in emerging markets, addressing a critical yet underexplored dimension of monetary policy’s financial market effects. Understanding how IT influences financial market stability is crucial, particularly for emerging economies where liquidity constraints exacerbate financial fragility. Analyzing 35 emerging countries, of which 15 are inflation targeters, over the period 1990–2023, we employ Difference-in-Differences and Doubly Robust methods to assess the influence of IT on stock market liquidity, utilizing several proxies for liquidity. Our findings indicate that IT has a significant impact on liquidity, particularly during crises such as the Global Financial Crisis (GFC) and the COVID-19 pandemic. The positive impact of IT adoption on stock market liquidity emerges after a three-year delay and becomes statistically significant once key economic and financial variables are controlled for. Robust across multiple checks, our study extends prior literature by offering a broad multi-country perspective, isolating IT’s unique role, and using advanced methods to address selection bias. It highlights IT as a key policy tool for financial stability, equipping central bankers with strategies to prevent liquidity dry-ups and strengthen economic resilience in turbulent times.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"82 ","pages":"Article 102580"},"PeriodicalIF":3.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884266","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 : 2026-01-01DOI: 10.1016/j.najef.2025.102576
Hina Mushtaq , Muhammad Ishtiaq , Surayya Jamal , Syed Maisam Raza Rizvi , Hamad Raza
This study investigates volatility regime dynamics and risk quantification across the developed stock markets of the NYSE and SSEC, and the emerging markets of South Asia, using the Markov-Switching GARCH framework. By employing both Maximum-Likelihood Estimation (MLE) and Bayesian Markov Chain Monte Carlo (MCMC) methods, the study captured volatility clustering that depends on regimes, their persistence, and transition probabilities. The findings of the MLE have revealed significant regime shifts in the markets of South Asia and have displayed frequent transitions, high volatility clustering, especially during low-volatility regimes, and a higher level of instability than in developed equity markets. Moreover, the MCMC findings further substantiate these findings by providing robust parameter estimates and revealing stronger volatility persistence during the calm regime and greater volatility persistence during turbulent periods in the developing South Asian stock markets.
Then, volatility forecasting shows sustained market uncertainty, with emerging South Asian stock markets exhibiting higher volatility than developed markets. Moreover, the findings on Value-at-Risk (VaR) and Expected Shortfall (ES) have confirmed the elevated tail risk in the developing South Asian market, especially in Nepal and the Dhaka Stock Exchange. These findings contribute to the literature by providing an empirical comparison of risk and volatility across developed and developing markets, validating the efficiency of regime-switching models when combined with Bayesian estimation techniques for capturing the complex behaviour of financial markets.
{"title":"Regime-Switching volatility and risk quantification in South Asian and developed stock Markets: A Comparative perspective using Markov-Switching GARCH with MLE and MCMC estimations","authors":"Hina Mushtaq , Muhammad Ishtiaq , Surayya Jamal , Syed Maisam Raza Rizvi , Hamad Raza","doi":"10.1016/j.najef.2025.102576","DOIUrl":"10.1016/j.najef.2025.102576","url":null,"abstract":"<div><div>This study investigates volatility regime dynamics and risk quantification across the developed stock markets of the NYSE and SSEC, and the emerging markets of South Asia, using the Markov-Switching GARCH framework. By employing both Maximum-Likelihood Estimation (MLE) and Bayesian Markov Chain Monte Carlo (MCMC) methods, the study captured volatility clustering that depends on regimes, their persistence, and transition probabilities. The findings of the MLE have revealed significant regime shifts in the markets of South Asia and have displayed frequent transitions, high volatility clustering, especially during low-volatility regimes, and a higher level of instability than in developed equity markets. Moreover, the MCMC findings further substantiate these findings by providing robust parameter estimates and revealing stronger volatility persistence during the calm regime and greater volatility persistence during turbulent periods in the developing South Asian stock markets.</div><div>Then, volatility forecasting shows sustained market uncertainty, with emerging South Asian stock markets exhibiting higher volatility than developed markets. Moreover, the findings on Value-at-Risk (VaR) and Expected Shortfall (ES) have confirmed the elevated tail risk in the developing South Asian market, especially in Nepal and the Dhaka Stock Exchange. These findings contribute to the literature by providing an empirical comparison of risk and volatility across developed and developing markets, validating the efficiency of regime-switching models when combined with Bayesian estimation techniques for capturing the complex behaviour of financial markets.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"82 ","pages":"Article 102576"},"PeriodicalIF":3.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884265","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 : 2025-12-29DOI: 10.1016/j.najef.2025.102574
George K. Zestos , Yixiao Jiang , Robert C. Winder , Charles Matzen
This study investigates the long-run relationship between public debt and economic growth in Canada from 1960 to 2022 using an Autoregressive Distributed Lag (ARDL) model. By incorporating key macroeconomic variables such as world GDP, the current account balance, and long-term interest rates, the analysis captures the macroeconomic dynamics of Canada’s small open economy. The findings reveal a negative relationship between public debt and economic growth in Canada, suggesting that fiscal prudence is crucial for sustained economic performance. Specifically, a 1% annual increase in public debt results in a 0.6–0.7% reduction in real GDP. Moreover, external factors such as global economic conditions and interest rates significantly influence Canada’s economic trajectory. These insights offer valuable policy implications not only for Canada, but also for similar open economies grappling with rising public debt levels.
{"title":"The debt-growth nexus in Canada: evidence from an open-economy ARDL model","authors":"George K. Zestos , Yixiao Jiang , Robert C. Winder , Charles Matzen","doi":"10.1016/j.najef.2025.102574","DOIUrl":"10.1016/j.najef.2025.102574","url":null,"abstract":"<div><div>This study investigates the long-run relationship between public debt and economic growth in Canada from 1960 to 2022 using an Autoregressive Distributed Lag (ARDL) model. By incorporating key macroeconomic variables such as world GDP, the current account balance, and long-term interest rates, the analysis captures the macroeconomic dynamics of Canada’s small open economy. The findings reveal a negative relationship between public debt and economic growth in Canada, suggesting that fiscal prudence is crucial for sustained economic performance. Specifically, a 1% annual increase in public debt results in a 0.6–0.7% reduction in real GDP. Moreover, external factors such as global economic conditions and interest rates significantly influence Canada’s economic trajectory. These insights offer valuable policy implications not only for Canada, but also for similar open economies grappling with rising public debt levels.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"83 ","pages":"Article 102574"},"PeriodicalIF":3.9,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980229","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 : 2025-12-27DOI: 10.1016/j.najef.2025.102575
Zekeriya Yildirim, Fuat Erdal
How do world interest rate shocks propagate globally, and what role does the US dollar play in transmitting these shocks and amplifying them through its interaction with global financial risk? This study addresses this question using three classes of VAR models: linear, threshold, and time-varying parameter VARs. We find that world rate shocks have significant adverse effects and that the dollar serves as a key transmission channel. Specifically, these shocks heighten global financial risk and uncertainty, trigger US dollar appreciation, depress global trade, and ultimately contract global GDP.
We emphasize the pivotal role of the dollar in the transmission of such shocks, showing that not only its movements (its appreciation) but also its state (strong vs. weak) matter. Our counterfactuals also reveal a novel amplification mechanism in which the dollar serves as a central actor, operating within a self-reinforcing feedback loop with global financial risk. These counterfactuals further show that global financial risk is a primary driver of dollar appreciation.
Using threshold and time-varying analyses, we document further evidence. Threshold analysis provides strong evidence of the state-dependent effects of world rate shocks, identifying three sources of state dependence: uncertainty state dependence, dollar state dependence, and business-cycle state dependence. It shows that dollar state dependence dominates the remaining sources in global financial dynamics. Time-varying analysis shows that the contractionary effects of such shocks have intensified during the early 2000s and after the global financial crisis, while the dollar’s transmission role has strengthened in the post-GFC period, especially in the post-COVID period.
{"title":"Global interest rates, US dollar, and global risk","authors":"Zekeriya Yildirim, Fuat Erdal","doi":"10.1016/j.najef.2025.102575","DOIUrl":"10.1016/j.najef.2025.102575","url":null,"abstract":"<div><div>How do world interest rate shocks propagate globally, and what role does the US dollar play in transmitting these shocks and amplifying them through its interaction with global financial risk? This study addresses this question using three classes of VAR models: linear, threshold, and time-varying parameter VARs. We find that world rate shocks have significant adverse effects and that the dollar serves as a key transmission channel. Specifically, these shocks heighten global financial risk and uncertainty, trigger US dollar appreciation, depress global trade, and ultimately contract global GDP.</div><div>We emphasize the pivotal role of the dollar in the transmission of such shocks, showing that not only its movements (its appreciation) but also its state (strong vs. weak) matter. Our counterfactuals also reveal a novel amplification mechanism in which the dollar serves as a central actor, operating within a self-reinforcing feedback loop with global financial risk. These counterfactuals further show that global financial risk is a primary driver of dollar appreciation.</div><div>Using threshold and time-varying analyses, we document further evidence. Threshold analysis provides strong evidence of the state-dependent effects of world rate shocks, identifying three sources of state dependence: uncertainty state dependence, dollar state dependence, and business-cycle state dependence. It shows that dollar state dependence dominates the remaining sources in global financial dynamics. Time-varying analysis shows that the contractionary effects of such shocks have intensified during the early 2000s and after the global financial crisis, while the dollar’s transmission role has strengthened in the post-GFC period, especially in the post-COVID period.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"83 ","pages":"Article 102575"},"PeriodicalIF":3.9,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980228","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 : 2025-12-17DOI: 10.1016/j.najef.2025.102571
Yusaku Nishimura , Yang Ji , Bianxia Sun
This paper examines intraday volatility spillovers in global financial markets in the context of recent geopolitical crises. We extend the intraday volatility spillover index (IVSI) framework to analyze high-frequency transmission patterns across financial markets during two recent geopolitical events, Russia-Ukraine war and the Israel-Hamas conflict. Our findings reveal that the Russia-Ukraine war significantly amplified volatility spillovers, particularly during periods of heightened market stress. In contrast, the Israel-Hamas conflict exhibited more limited spillover effects. Notably, we observe that geopolitical risk surged prior to February 2022, suggesting that markets had partially priced in the impending conflict. To capture nonlinear dynamics under varying risk conditions, we further employ a quantile vector autoregression (QVAR) model, which uncovers asymmetric spillover patterns across quantiles. These results underscore the importance of accounting for both the intensity and nature of geopolitical shocks when assessing financial contagion in high-frequency environments.
{"title":"Geopolitical crises, financial markets, and intraday volatility spillovers","authors":"Yusaku Nishimura , Yang Ji , Bianxia Sun","doi":"10.1016/j.najef.2025.102571","DOIUrl":"10.1016/j.najef.2025.102571","url":null,"abstract":"<div><div>This paper examines intraday volatility spillovers in global financial markets in the context of recent geopolitical crises. We extend the intraday volatility spillover index (IVSI) framework to analyze high-frequency transmission patterns across financial markets during two recent geopolitical events, Russia-Ukraine war and the Israel-Hamas conflict. Our findings reveal that the Russia-Ukraine war significantly amplified volatility spillovers, particularly during periods of heightened market stress. In contrast, the Israel-Hamas conflict exhibited more limited spillover effects. Notably, we observe that geopolitical risk surged prior to February 2022, suggesting that markets had partially priced in the impending conflict. To capture nonlinear dynamics under varying risk conditions, we further employ a quantile vector autoregression (QVAR) model, which uncovers asymmetric spillover patterns across quantiles. These results underscore the importance of accounting for both the intensity and nature of geopolitical shocks when assessing financial contagion in high-frequency environments.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"82 ","pages":"Article 102571"},"PeriodicalIF":3.9,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840949","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 : 2025-12-17DOI: 10.1016/j.najef.2025.102570
László Kamocsai , Mihály Ormos
We propose a new variant of the heterogeneous autoregressive model, the pseudo leverage HAR model, which exploits the well-known leverage effect to improve forecasting performance. Built on the fact there is an interconnectedness among commodities we employ a common leverage factor in forecasting exercises which is derived by principal component regression. Including this common leverage variable in HAR framework leads to significant improvements in both in-sample estimates and out-of-sample forecasts, suggesting that the factor structure is a valid assumption not just for return and volatility, but for volatility asymmetry too. The robustness tests confirm the usefulness of the common leverage factor, since the model incorporating this variable consistently remains in the model confidence set, implying that the model’s performance independent of the choice of the leverage structure or volatility proxy. Moreover, the portfolio evaluation exercise and the cumulative sum of forecast errors revealed the incremental gain of using the common leverage variable at all forecasting horizons, especially in turbulent periods.
{"title":"Modeling and forecasting commodity price volatility using a common leverage factor","authors":"László Kamocsai , Mihály Ormos","doi":"10.1016/j.najef.2025.102570","DOIUrl":"10.1016/j.najef.2025.102570","url":null,"abstract":"<div><div>We propose a new variant of the heterogeneous autoregressive model, the pseudo leverage HAR model, which exploits the well-known leverage effect to improve forecasting performance. Built on the fact there is an interconnectedness among commodities we employ a common leverage factor in forecasting exercises which is derived by principal component regression. Including this common leverage variable in HAR framework leads to significant improvements in both in-sample estimates and out-of-sample forecasts, suggesting that the factor structure is a valid assumption not just for return and volatility, but for volatility asymmetry too. The robustness tests confirm the usefulness of the common leverage factor, since the model incorporating this variable consistently remains in the model confidence set, implying that the model’s performance independent of the choice of the leverage structure or volatility proxy. Moreover, the portfolio evaluation exercise and the cumulative sum of forecast errors revealed the incremental gain of using the common leverage variable at all forecasting horizons, especially in turbulent periods.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"82 ","pages":"Article 102570"},"PeriodicalIF":3.9,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840950","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 : 2025-12-15DOI: 10.1016/j.najef.2025.102567
Fabian Alex
The neutrality of SRI in the AD-GE model by Arnold (2023) ceases to hold once the law of one price is violated for an asset that sufficiently many individuals (a single one may suffice) are not indifferent towards. The introduction of a green bond priced at a premium leads to an illusory gain, that is, a pure utility gain accompanied by a reduction of consumption, of green investors. Their financial losses are allocated to those that were sufficiently un-green to not buy too many green bonds themselves. To profit financially this way, an individual needs to start out as (partial) owner of a firm that “turns out” to be a green bond issuer. Impact investing still does not generate environmental impact in this model.
{"title":"On the non-neutrality of socially responsible investing in the presence of a greenium","authors":"Fabian Alex","doi":"10.1016/j.najef.2025.102567","DOIUrl":"10.1016/j.najef.2025.102567","url":null,"abstract":"<div><div>The neutrality of SRI in the AD-GE model by Arnold (2023) ceases to hold once the law of one price is violated for an asset that sufficiently many individuals (a single one may suffice) are not indifferent towards. The introduction of a green bond priced at a premium leads to an illusory gain, that is, a pure utility gain accompanied by a reduction of consumption, of green investors. Their financial losses are allocated to those that were sufficiently un-green to not buy too many green bonds themselves. To profit financially this way, an individual needs to start out as (partial) owner of a firm that “turns out” to be a green bond issuer. Impact investing still does not generate environmental impact in this model.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"82 ","pages":"Article 102567"},"PeriodicalIF":3.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791083","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 : 2025-12-15DOI: 10.1016/j.najef.2025.102569
António Miguel Martins , Bruno Albuquerque , Luís Sardinha , Nuno Moutinho
This study examines the short-term market effect of the US and European largest defence firms on the 2024 US presidential election (November 5, 2024) and the Trump-Zelensky meeting (February 28, 2025). By employing an event study methodology, our results show a positive and statistically significant stock price impact for both events. The results for the 2024 US presidential election are consistent with political business cycle theory. National elections in the arms-producing country drive a growth in sales revenues for defence firms, which tend to be higher when the Republican Party candidate wins the US elections. Our results also show the presence of heterogeneous abnormal returns between US and European defence firms around the Trump-Zelensky meeting, with European firms showing high and statistically significant positive returns while US firms show non-significant returns. This result is explained by the failure of security guarantees given by the US to the European countries and the awareness of the need for a rapid increase in military spending for self-defence purposes in Europe. This meeting reinforced the application of the principle of “Europe preference” in the acquisition of weapons. Finally, we conclude that stock market responses are reinforced or mitigated by firm-specific characteristics.
{"title":"Short-Term market impact of 2024 US President elections and Trump-Zelensky meeting in defence industry","authors":"António Miguel Martins , Bruno Albuquerque , Luís Sardinha , Nuno Moutinho","doi":"10.1016/j.najef.2025.102569","DOIUrl":"10.1016/j.najef.2025.102569","url":null,"abstract":"<div><div>This study examines the short-term market effect of the US and European largest defence firms on the 2024 US presidential election (November 5, 2024) and the Trump-Zelensky meeting (February 28, 2025). By employing an event study methodology, our results show a positive and statistically significant stock price impact for both events. The results for the 2024 US presidential election are consistent with political business cycle theory. National elections in the arms-producing country drive a growth in sales revenues for defence firms, which tend to be higher when the Republican Party candidate wins the US elections. Our results also show the presence of heterogeneous abnormal returns between US and European defence firms around the Trump-Zelensky meeting, with European firms showing high and statistically significant positive returns while US firms show non-significant returns. This result is explained by the failure of security guarantees given by the US to the European countries and the awareness of the need for a rapid increase in military spending for self-defence purposes in Europe. This meeting reinforced the application of the principle of “Europe preference” in the acquisition of weapons. Finally, we conclude that stock market responses are reinforced or mitigated by firm-specific characteristics.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"82 ","pages":"Article 102569"},"PeriodicalIF":3.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791084","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 : 2025-12-15DOI: 10.1016/j.najef.2025.102568
Vasileios Gkonis , Ioannis Tsakalos , Ilias Kampouris
Over the years, the challenge of portfolio optimization has gained increasing attention from scientists and experienced investors, where maximizing returns with the least possible risk is the major goal. In recent times, there has been a significant surge in interest in metaheuristic algorithms across various industries. In this study, we propose the use of the Artificial Gorilla Troops Optimizer (AGTO) for portfolio optimization. We evaluate its effectiveness and compare it against sixteen other swarm intelligence-based metaheuristic algorithms under varying population and epoch sizes. Our evaluation is based on the Sharpe ratio, utilizing a portfolio composed of stocks from the Dow Jones Industrial Average. The results indicate that AGTO demonstrates strong potential as an effective method for optimal portfolio selection. In addition, this work provides valuable insights into metaheuristic algorithms that have seen relatively limited application in the existing portfolio optimization literature.
{"title":"Constrained portfolio optimization via Artificial Gorilla Troops: Benchmarking against swarm-intelligence metaheuristic algorithms","authors":"Vasileios Gkonis , Ioannis Tsakalos , Ilias Kampouris","doi":"10.1016/j.najef.2025.102568","DOIUrl":"10.1016/j.najef.2025.102568","url":null,"abstract":"<div><div>Over the years, the challenge of portfolio optimization has gained increasing attention from scientists and experienced investors, where maximizing returns with the least possible risk is the major goal. In recent times, there has been a significant surge in interest in metaheuristic algorithms across various industries. In this study, we propose the use of the Artificial Gorilla Troops Optimizer (AGTO) for portfolio optimization. We evaluate its effectiveness and compare it against sixteen other swarm intelligence-based metaheuristic algorithms under varying population and epoch sizes. Our evaluation is based on the Sharpe ratio, utilizing a portfolio composed of stocks from the Dow Jones Industrial Average. The results indicate that AGTO demonstrates strong potential as an effective method for optimal portfolio selection. In addition, this work provides valuable insights into metaheuristic algorithms that have seen relatively limited application in the existing portfolio optimization literature.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"82 ","pages":"Article 102568"},"PeriodicalIF":3.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791085","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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