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Int. J. Financial Stud., Volume 13, Issue 3 (September 2025) – 36 articles

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20 pages, 324 KiB  
Article
Evolutions in the Financial Reporting Quality: A Comparative Analysis of Romanian Companies Listed on the Bucharest Stock Exchange
by Costel Istrate
Int. J. Financial Stud. 2025, 13(3), 149; https://doi.org/10.3390/ijfs13030149 - 20 Aug 2025
Abstract
The permanent evolution of accounting and financial reporting standards, in particular for listed companies, is justified by the need to adapt these standards to economic, societal, financial, institutional and technological developments. The main objective of the standard setters is that the financial statements [...] Read more.
The permanent evolution of accounting and financial reporting standards, in particular for listed companies, is justified by the need to adapt these standards to economic, societal, financial, institutional and technological developments. The main objective of the standard setters is that the financial statements reflect as closely as possible the reality of the entities they describe. The Romanian financial market (Bucharest Stock Exchange—BSE) has two segments: the regulated market, where, since 2012, IFRS are mandatory for the individual financial statements, and the alternative market AeRo, where the Romanian standards (RAS) are applied. This structure allows us to compare a financial reporting quality (FRQ) score, first, longitudinally (IFRS period 2012–2023 vs. non-IFRS period 2000–2011, for companies listed on the regulated market) and, second, IFRS observations (regulated market) vs. RAS observations (alternative market), for the same period (2012–2023). Following and partially replicating a methodology found in the literature, this study found that FRQ scores over the analyzed periods show us an increase in FRQ in the case of IFRS application, but also a favorable evolution of FRQ score for RAS observation. The evolution of accounting rules (including the transition from RAS to IFRS) is important, but the enforcement of the application of the reporting standards and other factors could have a significant impact on the quality of financial reporting. Full article
18 pages, 447 KiB  
Article
Islamic vs. Conventional Banking in the Age of FinTech and AI: Evolving Business Models, Efficiency, and Stability (2020–2024)
by Abdelrhman Meero
Int. J. Financial Stud. 2025, 13(3), 148; https://doi.org/10.3390/ijfs13030148 - 19 Aug 2025
Abstract
This study explores how FinTech and artificial intelligence (AI) adoption shape efficiency and financial stability in dual-banking systems. It focuses on 26 listed Islamic and conventional banks across 11 countries in the MENA and Southeast Asia regions between 2020 and 2024. To measure [...] Read more.
This study explores how FinTech and artificial intelligence (AI) adoption shape efficiency and financial stability in dual-banking systems. It focuses on 26 listed Islamic and conventional banks across 11 countries in the MENA and Southeast Asia regions between 2020 and 2024. To measure digital adoption, we create a seven-component FinTech Adoption Index. We use fixed-effects regressions to examine its impact on cost efficiency, profitability, solvency stability, and credit risk. This analysis also controls bank size, capitalization, and macroeconomic conditions. The results show a clear adoption gap. Conventional banks consistently score 0.5–0.8 points higher on the FinTech Index compared to Islamic banks. Each additional FinTech component raised operating costs by about 0.8%, but improved profitability slightly by only 0.03%. This suggests that technological integration creates upfront costs before any real efficiency gains are seen. However, the stability benefits are stronger. FinTech adoption increases the Z-score by 3.6 points and lowers the non-performing loan ratio by 0.1%. Islamic banks gain more stability benefits due to their risk-sharing contracts and asset-backed financing structures. Overall, an efficiency–stability trade-off emerges. Conventional banks focus more on profitability, while Islamic banks gain resilience, but face slower efficiency improvements. By combining the Resource-Based View and Financial Stability Theory, this study provides the first multi-country evidence of how governance structures shape digital transformation in dual-banking markets. The findings offer practical guidance for regulators and bank managers around balancing innovation, efficiency, and stability. Full article
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23 pages, 701 KiB  
Article
ESG Rating Divergence and Stock Price Crash Risk
by Chuting Zhang and Wei-Ling Hsu
Int. J. Financial Stud. 2025, 13(3), 147; https://doi.org/10.3390/ijfs13030147 - 19 Aug 2025
Viewed by 22
Abstract
ESG has emerged as a key non-financial indicator, drawing significant investor focus. Disparities in ESG ratings may skew investor perceptions, potentially endangering stock values and financial market stability. This paper examines the link between ESG rating divergences and stock price crash risk, drawing [...] Read more.
ESG has emerged as a key non-financial indicator, drawing significant investor focus. Disparities in ESG ratings may skew investor perceptions, potentially endangering stock values and financial market stability. This paper examines the link between ESG rating divergences and stock price crash risk, drawing on data from six Chinese and global ESG rating agencies. Focusing on Shanghai and Shenzhen A-share listed firms, it analyzes information from 2015 to 2022 within the theoretical contexts of information asymmetry and external monitoring. This study finds that ESG rating divergence markedly elevates stock price crash risk, a relationship that persists through a series of robustness checks. Specifically, the mechanisms operate through two key pathways: increased reputational damage risk due to information asymmetry and reduced external monitoring due to weakened external governance. The results of the heterogeneity analysis indicate that ESG rating divergence exacerbates stock price crash risk more significantly for non-state-owned firms, firms with low levels of marketization, and firms in high-pollution industries. This study provides clear actionable strategic paths and policy intervention points for investors to avoid risks, firms to optimize management, and regulators to formulate policies. Full article
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30 pages, 1592 KiB  
Article
The Role of Accounting Conservatism in the Decreasing Book Equity of U.S. Firms
by Haowen Luo, Bing Luo and S. Drew Peabody
Int. J. Financial Stud. 2025, 13(3), 146; https://doi.org/10.3390/ijfs13030146 - 19 Aug 2025
Viewed by 77
Abstract
We offer a novel explanation for the widespread decline in U.S. firms’ reported book equity. We find that accounting conservatism is negatively associated with book equity, a result that is both economically and statistically significant, as well as robust to a variety of [...] Read more.
We offer a novel explanation for the widespread decline in U.S. firms’ reported book equity. We find that accounting conservatism is negatively associated with book equity, a result that is both economically and statistically significant, as well as robust to a variety of model specifications. Our findings suggest that the rise in accounting conservatism has significantly contributed to the declines in book equity over the decades. Full article
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24 pages, 566 KiB  
Article
Liquidity Drivers in Illiquid Markets: Evidence from Simulation Environments with Heterogeneous Agents
by Lars Fluri, Ahmet Ege Yilmaz, Denis Bieri, Thomas Ankenbrand and Aurelio Perucca
Int. J. Financial Stud. 2025, 13(3), 145; https://doi.org/10.3390/ijfs13030145 - 18 Aug 2025
Viewed by 157
Abstract
This study investigates the liquidity dynamics in non-traditional financial markets by simulating trading environments for fractional ownership of illiquid alternative investments, grounded in empirical tick data from a Swiss FinTech platform covering December 2022 to June 2024. The research translates an operational digital [...] Read more.
This study investigates the liquidity dynamics in non-traditional financial markets by simulating trading environments for fractional ownership of illiquid alternative investments, grounded in empirical tick data from a Swiss FinTech platform covering December 2022 to June 2024. The research translates an operational digital secondary market into a heterogeneous agent-based simulation model within the theoretical framework of market microstructure and complex systems theory. The main objective is to assess whether a simple agent-based model (ABM) can replicate empirical liquidity patterns and to evaluate how market rules and parameter changes influence simulated liquidity distributions. The findings show that (i) the simulated liquidity closely matches empirical distributions not only in mean and variance but also in higher-order moments; (ii) the ABM reproduces key stylized facts observed in the data; and (iii) seemingly simple interventions in market rules can have unintended consequences on liquidity due to the complex interplay between agent behavior and trading mechanics. These insights have practical implications for digital platform designers, investors, and regulators, highlighting the importance of accounting for agent heterogeneity and endogenous market dynamics when shaping secondary market structures. Full article
(This article belongs to the Special Issue Market Microstructure and Liquidity)
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31 pages, 891 KiB  
Article
Corporate Digital Transformation and Capacity Utilization Rate: The Functionary Path via Technological Innovation
by Yang Liu, Hongyan Zhang, Xiang Gao and Yanxiang Xie
Int. J. Financial Stud. 2025, 13(3), 144; https://doi.org/10.3390/ijfs13030144 - 7 Aug 2025
Viewed by 536
Abstract
The rapid development of digital technology is reshaping the global economic landscape. However, its impact on firms’ capacity utilization rate (CUR), particularly through technological innovation, remains unclear. This study investigates this issue by developing an endogenous growth model that connects digital technology to [...] Read more.
The rapid development of digital technology is reshaping the global economic landscape. However, its impact on firms’ capacity utilization rate (CUR), particularly through technological innovation, remains unclear. This study investigates this issue by developing an endogenous growth model that connects digital technology to CUR. The empirical analysis is based on data from Chinese A-share manufacturing firms. The methods employed include quantile regression, instrumental variable techniques, and various tests to explore underlying mechanisms. CUR is calculated using a special model that looks at random variations, and digital transformation is assessed using text analysis powered by machine learning. The findings indicate that digital transformation significantly enhances CUR, especially for firms with average capacity utilization levels, but has a limited effect on low- and high-end firms. Moreover, technological innovation mediates this relationship; however, factors like “double arbitrage” (involving policy and capital markets) and “herd effects” tend to prioritize quantity over quality, which constrains innovation potential. Improvements in CUR lead to enhanced firm performance and productivity, generating industry spillovers and demonstrating the broader economic externalities of digitalization. This study uniquely applies endogenous growth theory to examine the role of digital transformation in optimizing CUR. It introduces the “quantity-quality” technology innovation paradox as a crucial mechanism and highlights industry spillovers to address overcapacity while offering insights for fostering sustainable economic and social development in emerging markets. Full article
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30 pages, 20256 KiB  
Article
From Fields to Finance: Dynamic Connectedness and Optimal Portfolio Strategies Among Agricultural Commodities, Oil, and Stock Markets
by Xuan Tu and David Leatham
Int. J. Financial Stud. 2025, 13(3), 143; https://doi.org/10.3390/ijfs13030143 - 6 Aug 2025
Viewed by 371
Abstract
In this study, we investigate the return propagation mechanism, hedging effectiveness, and portfolio performance across several common agricultural commodities, crude oil, and S&P 500 index, ranging from July 2000 to June 2024 by using a time-varying parameter vector autoregression (TVP-VAR) connectedness approach and [...] Read more.
In this study, we investigate the return propagation mechanism, hedging effectiveness, and portfolio performance across several common agricultural commodities, crude oil, and S&P 500 index, ranging from July 2000 to June 2024 by using a time-varying parameter vector autoregression (TVP-VAR) connectedness approach and three common multiple assets portfolio optimization strategies. The empirical results show that, the total connectedness peaked during the 2008 global financial crisis, followed by the European debt crisis and the COVID-19 pandemic, while it remained relatively lower at the onset of the Russia-Ukraine conflict. In the transmission mechanism, commodities and S&P 500 index exhibit distinct and dynamic characteristics as transmitters or receivers. Portfolio analysis reveals that, with exception of the COVID-19 pandemic, all three dynamic portfolios outperform the S&P 500 benchmark across major global crises. Additionally, the minimum correlation and minimum connectedness strategies are superior than transitional minimum variance method in most scenarios. Our findings have implications for policymakers in preventing systemic risk, for investors in managing portfolio risk, and for farmers and agribusiness enterprises in enhancing economic benefits. Full article
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22 pages, 288 KiB  
Article
An X-Ray Using NLP Techniques of Financial Reporting Quality in Central and Eastern European Countries
by Tatiana Dănescu and Roxana Maria Stejerean
Int. J. Financial Stud. 2025, 13(3), 142; https://doi.org/10.3390/ijfs13030142 - 6 Aug 2025
Viewed by 229
Abstract
This study assesses the quality of financial reporting in ten Central and Eastern European countries using a methodology based on natural language processing (NLP) techniques. 570 annual reports of companies listed on the main index on the stock exchanges of 10 Central and [...] Read more.
This study assesses the quality of financial reporting in ten Central and Eastern European countries using a methodology based on natural language processing (NLP) techniques. 570 annual reports of companies listed on the main index on the stock exchanges of 10 Central and Eastern European (CEE) countries, over the period 2019–2023, were evaluated to determine the degree of convergence of the following four measurable qualitative characteristics: relevance, exact representation, comparability and understandability. The main objective is to identify consistency in the quality of accounting information based on the application of an international financial reporting framework. The applied methodology eliminates subjective variability by implementing a standardized scoring system, aligned with the criteria developed by NiCE, using libraries such as spaCy and NLTK for term extraction, respective sentiment analysis and word frequency evaluation. The results reveal significant heterogeneity in all characteristics examined, with statistical tests confirming substantial differences between countries. The investigation of relevance revealed partial convergence, with three dimensions achieving complete uniformity, while the exact representation showed the highest variability. The assessment of comparability showed a significant difference between countries’ extreme values, and in terms of comprehensibility a formalistic approach was evident, with technical dimensions outweighing user-oriented aspects. The overall quality index varied significantly across countries, with a notable average deterioration in 2023, indicating structural vulnerabilities in financial reporting systems. These findings support initial hypotheses on the lack of homogeneity in the quality of financial reporting in the selected region, despite the implementation of international standards. Full article
26 pages, 344 KiB  
Article
The Impact of Green Bond Issuance on Corporate Environmental and Financial Performance: An Empirical Study of Japanese Listed Firms
by Yutong Bai
Int. J. Financial Stud. 2025, 13(3), 141; https://doi.org/10.3390/ijfs13030141 - 1 Aug 2025
Viewed by 652
Abstract
Based on firm-level data of Japanese listed companies for the period of 2013–2022, this study conducts an empirical analysis to investigate how the issuance of green bonds influences corporate environmental and financial performance. The results show that the green bond issuance demonstrates a [...] Read more.
Based on firm-level data of Japanese listed companies for the period of 2013–2022, this study conducts an empirical analysis to investigate how the issuance of green bonds influences corporate environmental and financial performance. The results show that the green bond issuance demonstrates a reduction in corporate greenhouse gas emission intensity and energy consumption intensity in the long term. Moreover, the issuance of green bonds enhances the financial performance of firms in the long run. However, the positive effect of green bond issuance on corporate environmental and financial performance is significant only among firms that have set specific quantitative environmental targets. In addition, for manufacturing and transportation green bond issuers that have set specific quantitative environmental targets, the improvement in environmental performance is evident in both the long and short term. Full article
(This article belongs to the Special Issue Investment and Sustainable Finance)
16 pages, 263 KiB  
Article
Hospitality in Crisis: Evaluating the Downside Risks and Market Sensitivity of Hospitality REITs
by Davinder Malhotra and Raymond Poteau
Int. J. Financial Stud. 2025, 13(3), 140; https://doi.org/10.3390/ijfs13030140 - 1 Aug 2025
Viewed by 389
Abstract
This study evaluates the risk-adjusted performance of Hospitality REITs using multi-factor asset pricing models and downside risk measures with the aim of assessing their diversification potential and crisis sensitivity. Unlike prior studies that examine REITs in aggregate, this study isolates Hospitality REITs to [...] Read more.
This study evaluates the risk-adjusted performance of Hospitality REITs using multi-factor asset pricing models and downside risk measures with the aim of assessing their diversification potential and crisis sensitivity. Unlike prior studies that examine REITs in aggregate, this study isolates Hospitality REITs to explore their unique cyclical and macroeconomic sensitivities. This study looks at the risk-adjusted performance of Hospitality Real Estate Investment Trusts (REITs) in relation to more general REIT indexes and the S&P 500 Index. The study reveals that monthly returns of Hospitality REITs increasingly move in tandem with the stock markets during financial crises, which reduces their historical function as portfolio diversifiers. Investing in Hospitality REITs exposes one to the hospitality sector; however, these investments carry notable risks and provide little protection, particularly during economic upheavals. Furthermore, the study reveals that Hospitality REITs underperform on a risk-adjusted basis relative to benchmark indexes. The monthly returns of REITs show significant volatility during the post-COVID-19 era, which causes return-to-risk ratios to be below those of benchmark indexes. Estimates from multi-factor models indicate negative alpha values across conditional models, indicating that macroeconomic variables cause unremunerated risks. This industry shows great sensitivity to market beta and size and value determinants. Hospitality REITs’ susceptibility comes from their showing the most possibility for exceptional losses across asset classes under Value at Risk (VaR) and Conditional Value at Risk (CvaR) downside risk assessments. The findings have implications for investors and portfolio managers, suggesting that Hospitality REITs may not offer consistent diversification benefits during downturns but can serve a tactical role in procyclical investment strategies. Full article
20 pages, 1978 KiB  
Review
Banking Profitability: Evolution and Research Trends
by Francisco Sousa and Luís Almeida
Int. J. Financial Stud. 2025, 13(3), 139; https://doi.org/10.3390/ijfs13030139 - 29 Jul 2025
Viewed by 527
Abstract
This study aims to map the scientific knowledge of bank profitability and its determinants. It identifies trends and gaps in existing research through a bibliometric analysis. To this end, 634 documents published in the Web of Science database over the last 54 years [...] Read more.
This study aims to map the scientific knowledge of bank profitability and its determinants. It identifies trends and gaps in existing research through a bibliometric analysis. To this end, 634 documents published in the Web of Science database over the last 54 years were analyzed using the bibliometric package. The results indicate an increase in the volume of publications following the 2008 financial crisis, focusing on analyzing the factors influencing bank profitability and economic growth. The Journal of Banking and Finance is the preeminent publication in this field. The literature reviewed shows that bank profitability depends on internal factors (size, credit risk, liquidity, efficiency, and management) and external factors (such as GDP, inflation, interest rates, and unemployment). In addition to the traditional determinants, the recent literature highlights the importance of innovation and technological factors such as digitalization, mobile banking, and electronic payments as relevant to bank profitability. ESG (environmental, social, and governance) and governance indicators, which are still emerging but have been extensively researched in companies, indicate a need for evidence in this area. This paper also provides relevant insights for the formulation of monetary policy and the strategic formulation of banks, helping managers and owners to improve bank performance. It also provides directions for future empirical studies and research collaborations in this field. Full article
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29 pages, 498 KiB  
Article
Modeling the Determinants of Stock Market Investment Intention and Behavior Among Studying Adults: Evidence from University Students Using PLS-SEM
by Dostonbek Eshpulatov, Gayrat Berdiev and Andrey Artemenkov
Int. J. Financial Stud. 2025, 13(3), 138; https://doi.org/10.3390/ijfs13030138 - 25 Jul 2025
Viewed by 779
Abstract
The development of stock markets is pivotal for economic growth, particularly through the mobilization of idle resources into productive investments. Despite recent reforms to enhance Uzbekistan’s capital market, public engagement remains limited. This study examines the behavioral determinants of stock market investment intention [...] Read more.
The development of stock markets is pivotal for economic growth, particularly through the mobilization of idle resources into productive investments. Despite recent reforms to enhance Uzbekistan’s capital market, public engagement remains limited. This study examines the behavioral determinants of stock market investment intention and participation among university students, employing the Theory of Planned Behavior (TPB) and Partial Least Squares Structural Equation Modeling (PLS-SEM). The model investigates the influence of digital literacy, financial literacy, social interaction, herding behavior, overconfidence bias, risk tolerance, and financial well-being on investment intention and behavior. A survey of 369 university students was conducted to assess the proposed relationships. The results reveal that risk tolerance, overconfidence bias, and herding behavior significantly and positively affect investment intention, while digital literacy demonstrates a notable negative effect, suggesting caution in assuming technology readiness automatically translates to investment readiness. Investment intention, in turn, strongly predicts actual participation and mediates several of these effects. Conversely, financial literacy, financial well-being, and social interaction showed no significant direct or mediating influence. Additionally, differences according to gender and academic background were observed in how intention translates into behavior. The findings underscore the need for integrated financial and behavioral education to enhance market participation and contribute to policy discourse on youth financial engagement in emerging economies. Full article
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20 pages, 4490 KiB  
Article
Mapping Trends in Green Finance: A Bibliometric and Topic Modeling Analysis
by Orlando Joaqui-Barandica, Jesús Heredia-Carroza, Sebastian López-Estrada and Daniela-Tatiana Agheorghiesei
Int. J. Financial Stud. 2025, 13(3), 137; https://doi.org/10.3390/ijfs13030137 - 25 Jul 2025
Viewed by 917
Abstract
This study presents a comprehensive bibliometric and topic modeling analysis of the academic literature on green and sustainable finance. Using 1372 peer-reviewed articles indexed in the Web of Science up to 2024, we identify key publication trends, influential authors, prominent journals, and thematic [...] Read more.
This study presents a comprehensive bibliometric and topic modeling analysis of the academic literature on green and sustainable finance. Using 1372 peer-reviewed articles indexed in the Web of Science up to 2024, we identify key publication trends, influential authors, prominent journals, and thematic clusters shaping the field. The analysis reveals an exponential growth in publications since 2017 and highlights the dominance of journals such as Journal of Sustainable Finance & Investment and Sustainability. Text mining techniques, including TF-IDF and Latent Dirichlet Allocation (LDA), are applied to abstracts to extract the most relevant terms and classify articles into four latent topics. The findings suggest a growing focus on the impact of green finance on carbon emissions, energy efficiency, and firm performance, particularly in the context of China. This study offers valuable insights for researchers and policymakers by mapping the intellectual structure and identifying emerging research frontiers in the rapidly evolving field of green finance. Full article
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26 pages, 333 KiB  
Article
Financial Discrimination: Consumer Perceptions and Reactions
by Miranda Reiter, Di Qing, Kenneth White and Morgen Nations
Int. J. Financial Stud. 2025, 13(3), 136; https://doi.org/10.3390/ijfs13030136 - 24 Jul 2025
Viewed by 417
Abstract
Access to traditional financial institutions plays a key role in enhancing positive financial outcomes. However, some consumers within the United States experience discrimination from these same institutions. In particular, discrimination based on race and gender has historically been tied to outcomes such as [...] Read more.
Access to traditional financial institutions plays a key role in enhancing positive financial outcomes. However, some consumers within the United States experience discrimination from these same institutions. In particular, discrimination based on race and gender has historically been tied to outcomes such as lower service quality and a lack of access to credit. While the previous literature has discussed some of the discriminatory practices that these groups have faced, there is a lack of research on how these groups respond to discrimination from financial institutions. Through a series of logistic regressions, the authors analyzed how race, ethnicity, and gender are related to reporting experiences of discrimination. The authors then explored how consumers react to discrimination by looking at five reported reactions. Primary results show that Black consumers were more likely than most other racial groups to experience financial discrimination. Additionally, women were less likely than men to report financial discrimination. Race was shown to be a significant factor in four of the five reactions to discrimination, while gender was a factor in two of the reactions. The findings further show that after experiencing financial discrimination, most individuals turned to non-traditional financial services as a direct result of the bias or racism. Full article
19 pages, 1667 KiB  
Article
Mapping the Literature on Short-Selling in Financial Markets: A Lexicometric Analysis
by Nitika Sharma, Sridhar Manohar, Bruce A. Huhmann and Yam B. Limbu
Int. J. Financial Stud. 2025, 13(3), 135; https://doi.org/10.3390/ijfs13030135 - 23 Jul 2025
Viewed by 640
Abstract
This study provides a comprehensive assessment and synthesis of the literature on short-selling. It performs a lexicometric analysis, providing a quantitative review of 1093 peer-reviewed journal articles to identify and illustrate the main themes in short-selling research. Almost half the published literature on [...] Read more.
This study provides a comprehensive assessment and synthesis of the literature on short-selling. It performs a lexicometric analysis, providing a quantitative review of 1093 peer-reviewed journal articles to identify and illustrate the main themes in short-selling research. Almost half the published literature on short-selling is thematically clustered around portfolio management techniques. Other key themes involve short-selling as it relates to risk management, strategic management, and market irregularities. Descending hierarchical classification examines the overall structure of the textual corpus of the short-selling literature and the relationships between its key terms. Similarity analysis reveals that the short-selling literature is highly concentrated, with most conceptual groups closely aligned and fitting into overlapping or conceptually similar areas. Some notable groups highlight prior short-selling studies of market dynamics, behavioral factors, technological advancements, and regulatory frameworks, which can serve as a foundation for market regulators to make more informed decisions that enhance overall market stability. Additionally, this study proposes a conceptual framework in which short-selling can be either a driver or an outcome by integrating the literature on its antecedents, consequences, explanatory variables, and boundary conditions. Finally, it suggests directions for future research. Full article
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26 pages, 4918 KiB  
Article
Is Bitcoin a Safe-Haven Asset During U.S. Presidential Transitions? A Time-Varying Analysis of Asset Correlations
by Pathairat Pastpipatkul and Htwe Ko
Int. J. Financial Stud. 2025, 13(3), 134; https://doi.org/10.3390/ijfs13030134 - 22 Jul 2025
Viewed by 991
Abstract
Amid the growing debate over how cryptocurrencies are reshaping global finance, this study explores the nexus between Bitcoin, Brent Crude Oil, Gold and the U.S. Dollar Index. We used a time-varying vector autoregressive (tvVAR) model to examine the connection among these four assets [...] Read more.
Amid the growing debate over how cryptocurrencies are reshaping global finance, this study explores the nexus between Bitcoin, Brent Crude Oil, Gold and the U.S. Dollar Index. We used a time-varying vector autoregressive (tvVAR) model to examine the connection among these four assets during the Trump (2017–2020) and Biden (2021–2024) governments. The 48-week return forecast of the Bitcoin–Gold correlation was also conducted by using the Bayesian Structural Time Series (BSTS) model. Results indicate that Bitcoin was the most volatile asset, while the U.S. Dollar remained the least volatile under both regimes. Under Trump, U.S. Dollar significantly influenced Oil and Bitcoin while Bitcoin and Gold were negatively linked to Oil and positively associated with U.S. Dollar. An inverse relationship between Bitcoin and Gold also emerged. Under Biden, Bitcoin, Gold, and U.S. Dollar all significantly affected Oil with Bitcoin showing a positive impact. Bitcoin and Gold remained negatively correlated though not significantly, and the Dollar maintained positive ties with both. Forecasts show a positive link between Bitcoin and Gold in the coming year. However, Bitcoin does not exhibit consistent characteristics of a safe-haven asset during the U.S. presidential transitions examined, largely due to its high volatility and unstable correlations with a traditional safe-haven asset, Gold. This study contributes to the understanding of shifting relationships between digital and traditional assets across political regimes. Full article
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35 pages, 1123 KiB  
Article
AI-Based Bankruptcy Prediction for Agricultural Firms in Central and Eastern Europe
by Dominika Gajdosikova, Jakub Michulek and Irina Tulyakova
Int. J. Financial Stud. 2025, 13(3), 133; https://doi.org/10.3390/ijfs13030133 - 16 Jul 2025
Viewed by 685
Abstract
The agriculture sector is increasingly challenged to maintain productivity and sustainability amidst environmental, marketplace, and geopolitical pressures. While precision agriculture enhances physical production, the financial resilience of agricultural firms has been understudied. In this study, machine learning (ML) methods, including logistic regression (LR), [...] Read more.
The agriculture sector is increasingly challenged to maintain productivity and sustainability amidst environmental, marketplace, and geopolitical pressures. While precision agriculture enhances physical production, the financial resilience of agricultural firms has been understudied. In this study, machine learning (ML) methods, including logistic regression (LR), decision trees (DTs), and artificial neural networks (ANNs), are employed to predict the bankruptcy risk for Central and Eastern European (CEE) farming firms. All models consistently showed high performance, with AUC values exceeding 0.95. DTs had the highest overall accuracy (95.72%) and F1 score (0.9768), LR had the highest recall (0.9923), and ANNs had the highest discrimination power (AUC = 0.960). Visegrad, Balkan, Baltic, and Eastern Europe subregional models featured economic and structural heterogeneity, reflecting the need for local financial risk surveillance. The results support the development of AI-based early warning systems for agricultural finance, enabling smarter decision-making, regional adaptation, and enhanced sustainability in the sector. Full article
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27 pages, 5958 KiB  
Review
Trends and Trajectories: A Bibliometric Analysis of Financial Risk (2015–2024)
by Jiajia Liu, Yibin Liu, Lijun Ren, Xuerong Li and Shouyang Wang
Int. J. Financial Stud. 2025, 13(3), 132; https://doi.org/10.3390/ijfs13030132 - 15 Jul 2025
Viewed by 603
Abstract
This study conducts a comprehensive bibliometric analysis and predictive modeling of financial risk research from 2015 to 2024, integrating conceptual, knowledge, and collaboration perspectives. Utilizing the PRISMA framework for literature screening, the study identifies publications, research areas, and research institutions. A co-citation network [...] Read more.
This study conducts a comprehensive bibliometric analysis and predictive modeling of financial risk research from 2015 to 2024, integrating conceptual, knowledge, and collaboration perspectives. Utilizing the PRISMA framework for literature screening, the study identifies publications, research areas, and research institutions. A co-citation network approach reveals the intellectual structure and milestone works, while emergent keyword detection highlights cutting-edge topics such as economic policy uncertainty, climate risk, and green innovation. Furthermore, the study proposes a novel semantic forecasting model, SEF-ACLSTM (Semantic Evolution Forecasting with Aligned Clustered LSTM), to predict the evolution of research themes through 2030. The results identify three major thematic clusters: methodological innovation, traditional risk management, and green finance. The predictive analysis indicates a growing emphasis on methodological and sustainability-oriented topics, suggesting a paradigmatic shift in financial risk research. The findings offer theoretical insights and strategic guidance for future academic inquiry and policy formulation. Full article
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21 pages, 311 KiB  
Article
How Does Corporate Information Environment Influence CSR?
by Ehsan Poursoleyman, Amin Pourrezaei Nav, Gholamreza Mansourfar and Hamzeh Didar
Int. J. Financial Stud. 2025, 13(3), 131; https://doi.org/10.3390/ijfs13030131 - 10 Jul 2025
Viewed by 536
Abstract
This study investigates the impact of outsiders’ demand for more information (or transparency) on corporate social responsibility (CSR) initiatives. Drawing on a dataset of U.S. companies from 2010 to 2023, CSR performance is measured using ASSET4 ratings, while CSR disclosure levels are captured [...] Read more.
This study investigates the impact of outsiders’ demand for more information (or transparency) on corporate social responsibility (CSR) initiatives. Drawing on a dataset of U.S. companies from 2010 to 2023, CSR performance is measured using ASSET4 ratings, while CSR disclosure levels are captured through the number of words and sentences in reports. Utilizing within-industry and -firm OLS regressions, our analyses reveal a positive relationship between the demand for more information and future CSR investments, showing that firms with higher demand for information not only enhance their CSR performance but also expand the length of their CSR reports. These results suggest that increased pressures for information encourage organizations to engage more deeply with social responsibility, resulting in more robust CSR activities and more comprehensive reporting practices. This study contributes to the existing literature by highlighting the strong predictive role of outsiders’ demand for more information in promoting CSR investment and disclosure, and by offering important insights for policymakers and practitioners on fostering corporate responsibility through enhanced transparency. Full article
(This article belongs to the Special Issue Accounting and Financial/Non-financial Reporting Developments)
23 pages, 584 KiB  
Article
Effects of Debt Financing Decisions on Profitability: A Comparison of USA and Europe Biopharmaceutical Industry
by Emmanuel Nkansah
Int. J. Financial Stud. 2025, 13(3), 130; https://doi.org/10.3390/ijfs13030130 - 9 Jul 2025
Viewed by 540
Abstract
Debt financing is important for financing major investments in the biopharmaceutical industry. Debt financing allows companies to raise funds without giving up ownership or control through indenture and covenants of the company. In this study, I analyze the effects of debt financing decisions [...] Read more.
Debt financing is important for financing major investments in the biopharmaceutical industry. Debt financing allows companies to raise funds without giving up ownership or control through indenture and covenants of the company. In this study, I analyze the effects of debt financing decisions on profitability in the biopharmaceutical industry. I find that short-term debt, long-term debt, and total debt negatively impact the return on assets (ROA) as a firm’s profitability measure. A comparison is made between American and European biopharmaceutical firms, and the result shows the negative effects of short-term and long-term debt on profitability persist more for US biopharmaceutical firms than European firms. Short-term and long-term debt both impact profitability negatively with 10-year lagged R&D intensity and financial distress. Short-term debt’s negative impact is stronger post-COVID-19, indicating increased financial strain. Long-term debt consistently affects profitability negatively, with relatively stable effects during the pre- and post-COVID-19 pandemic. Full article
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30 pages, 945 KiB  
Article
Digital Finance, New Quality Productive Forces, and Government Environmental Governance: Empirical Evidence from Chinese Provincial Panel Data
by Yunsong Xu and Shanfei Zhang
Int. J. Financial Stud. 2025, 13(3), 129; https://doi.org/10.3390/ijfs13030129 - 8 Jul 2025
Viewed by 512
Abstract
As the mainstream financial modality in the digital economy era, digital finance drives industrial digitization and green transformation through capital and technological support, enabling governments to advance environmental governance with greater precision, efficiency, and sustainability. Utilizing 2012–2023 panel data from 31 Chinese provinces, [...] Read more.
As the mainstream financial modality in the digital economy era, digital finance drives industrial digitization and green transformation through capital and technological support, enabling governments to advance environmental governance with greater precision, efficiency, and sustainability. Utilizing 2012–2023 panel data from 31 Chinese provinces, this study innovatively constructs a multidimensional panel data model for the quantitative analysis of the overall impact, heterogeneous effects, and spatial spillover effects of digital finance on government environmental governance. It further examines the mediating effect and the threshold effects of new quality productive forces, and the moderated mediation effects of green technological innovation and industrial collaborative agglomeration. In this study, (1) digital finance significantly drives government environmental governance, and this finding exhibits robustness; (2) digital finance exerts heterogeneous impact on government environmental governance, with more pronounced effects in eastern and sub-developed regions; (3) digital finance generates positive spatial spillover effects on government environmental governance; (4) new quality productive forces positively mediate the relationship between digital finance and government environmental governance; (5) green technological innovation exhibits dual moderation characteristics, moderating both “digital finance → new quality productive forces” and “new quality productive forces → government environmental governance,” while industrial collaborative agglomeration shows single moderation, specifically moderating “new quality productive forces → government environmental governance”; (6) the impact of digital finance on government environmental governance presents a nonlinear feature of “increasing marginal returns.” On these accounts, this study proposes targeted recommendations from six dimensions. Full article
(This article belongs to the Special Issue Digital and Conventional Assets (2nd Edition))
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23 pages, 331 KiB  
Article
Harnessing the Power of Past Triumphs: Unleashing the MAX Effect’s Potential in Emerging Market Returns
by Ştefan Cristian Gherghina, Durmuş Yıldırım and Mesut Dogan
Int. J. Financial Stud. 2025, 13(3), 128; https://doi.org/10.3390/ijfs13030128 - 8 Jul 2025
Viewed by 613
Abstract
This study investigates the presence of the MAX effect, as defined by Bali et al. (2011), in the stock market of Borsa Istanbul, aiming to validate and extend previous findings in international markets. A comprehensive analysis of 439 firms from December 2013 to [...] Read more.
This study investigates the presence of the MAX effect, as defined by Bali et al. (2011), in the stock market of Borsa Istanbul, aiming to validate and extend previous findings in international markets. A comprehensive analysis of 439 firms from December 2013 to November 2023 reveals that stocks with low performance in previous periods tend to show strong performance in subsequent periods. This finding indicates that the MAX effect is also applicable to Borsa Istanbul and suggests that this effect can significantly influence stock price movements in the market. Additionally, this study highlights that past maximum returns, especially those accumulated over long periods, have a distinct impact on future returns. These findings contribute to a deeper understanding of the MAX effect’s presence in and impact on financial markets and offer valuable guidance for market participants. Full article
29 pages, 3409 KiB  
Article
Optimal Portfolio Analysis Using Power and Natural Logarithm Utility Functions with E-Commerce Data
by Apni Diyanti, Moch. Fandi Ansori, Susilo Hariyanto and Ratna Herdiana
Int. J. Financial Stud. 2025, 13(3), 127; https://doi.org/10.3390/ijfs13030127 - 4 Jul 2025
Viewed by 498
Abstract
Determining the optimal portfolio is important in the investment process because it includes the selection of appropriate fund allocation to manage financial risk effectively. Although risk cannot be entirely eliminated, it is managed through strategic allocation based on investor preferences. Therefore, this research [...] Read more.
Determining the optimal portfolio is important in the investment process because it includes the selection of appropriate fund allocation to manage financial risk effectively. Although risk cannot be entirely eliminated, it is managed through strategic allocation based on investor preferences. Therefore, this research aimed to use mathematical models, including the power utility function, the natural logarithm utility function, and a combination of both, to capture varying degrees of risk aversion. The optimal allocation was obtained by analytically maximizing the expected end-of-period wealth utility under each specification, where the investor level of risk aversion was derived by determining the constant. The utility function that failed to produce closed-form solutions was solved through the use of a numerical method to approximate the optimal portfolio weight. Furthermore, numerical simulations were performed using data from two stocks in the e-commerce sector to prove the impact of parameter changes on investment decisions. The result showed explicit analytical values for each utility function, providing investors with a structured framework for determining optimal portfolio weights consistent with their risk profile. Full article
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18 pages, 4633 KiB  
Article
Comparison of the CAPM and Multi-Factor Fama–French Models for the Valuation of Assets in the Industries with the Highest Number of Transactions in the US Market
by Karime Chahuán-Jiménez, Luis Muñoz-Rojas, Sebastián Muñoz-Pizarro and Erik Schulze-González
Int. J. Financial Stud. 2025, 13(3), 126; https://doi.org/10.3390/ijfs13030126 - 4 Jul 2025
Viewed by 950
Abstract
This study comparatively evaluated the Capital Asset Pricing Model (CAPM), the Fama and French three-factor model (FF3), and the Fama and French five-factor model (FF5) in key US market sectors (finance, energy, and utilities). The goals were to optimize financial decisions and reduce [...] Read more.
This study comparatively evaluated the Capital Asset Pricing Model (CAPM), the Fama and French three-factor model (FF3), and the Fama and French five-factor model (FF5) in key US market sectors (finance, energy, and utilities). The goals were to optimize financial decisions and reduce valuation errors. The historical daily returns of ten-stock portfolios, selected from sectors with the highest trading volume in the S&P 500 Index between 2020 and 2024, were analyzed. Companies with the lowest beta were prioritized. Models were compared based on the metrics of the root mean square error (RMSE) and mean absolute error (MAE). The results demonstrate the superiority of the multifactor models (FF3 and FF5) over the CAPM in explaining returns in the analyzed sectors. Specifically, the FF3 model was the most accurate in the financial sector; the FF5 model was the most accurate in the energy and utilities sectors; and the FF4 model, with the SMB factor eliminated in the adjustment of the FF5 model, was the least error-prone. The CAPM’s consistent inferiority highlights the need to consider factors beyond market risk. In conclusion, selecting the most appropriate asset valuation model for the US market depends on each sector’s inherent characteristics, favoring multifactor models. Full article
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19 pages, 677 KiB  
Article
The Effect of Corporate Environmental Performance (CEP) of an Acquirer on Post-Merger Firm Value: Evidence from the US Market
by Md Shahiduzzaman, Priyantha Mudalige, Omar Al Farooque and Mohammad Alauddin
Int. J. Financial Stud. 2025, 13(3), 125; https://doi.org/10.3390/ijfs13030125 - 3 Jul 2025
Cited by 1 | Viewed by 585
Abstract
Purpose: The acquirer’s corporate environmental performance (CEP) in mergers and acquisitions has been a subject of debate, yielding mixed results. This paper uses the US firm-level data of 1437 M&A deals from 2002–2019 to examine the impact of overall CEP, resource use, emissions, [...] Read more.
Purpose: The acquirer’s corporate environmental performance (CEP) in mergers and acquisitions has been a subject of debate, yielding mixed results. This paper uses the US firm-level data of 1437 M&A deals from 2002–2019 to examine the impact of overall CEP, resource use, emissions, and innovation on the acquirers’ post-merger market value. Design/methodology/approach: This study employs multi-level fixed effects panel regression using Ordinary Least Squares (OLS) and the instrumental variable (IV) 2SLS method to estimate the models and compare the results with those from robust estimation. Absorbing the multiple levels of fixed effects (i.e., firm, industry, and year) offers a novel and robust algorithm for efficiently accounting for unobserved heterogeneity. The results from IV (2SLS) are more convincing, as the method overcomes the problem of endogeneity due to reverse causality and sample selection bias. Findings: The authors find that CEP has a significant impact on market value, particularly in the long term. While both resource use and emissions performance have positive effects, emissions performance has a stronger impact, presumably because external stakeholders and market participants are more concerned about emissions reduction. The performance of environmental innovation is relatively weak compared to other pillars. Descriptive analysis shows low average scores in environmental innovation compared to the resource use and emissions performance of the acquirers. However, large deals yield significant returns from investing in environmental innovation in both the short and long term compared to small deals. Practical implications: This paper offers several practical implications. First, environmental performance can help improve the acquirer’s long-term market value. Second, managers can focus on the strategic side of environmental performance, based on its pillars, and benchmark their relative position against peers. Third, environmental innovation can be considered a new potential, as the market as a whole in this area is still lagging. Given the growing pressure to improve environmental technology and innovation, prospective acquirers should confidently prioritise actions on green revenue, product innovation, and capital expenditure now rather than ticking these boxes later. Originality value: The key contribution is offering valuable insights into the impact of acquirers’ environmental performance on long-term value creation in mergers and acquisitions (M&A). These results fill the gap in the literature focusing mainly on the effect of environmental pillar and sub-pillar scores on acquirer’s firm value. The authors claim that analysing sub-pillar-level granularity is crucial for accurately measuring the effects on firm-level performance. Full article
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25 pages, 1750 KiB  
Article
Blockchain, Cryptocurrencies, and Decentralized Finance: A Case Study of Financial Inclusion in Morocco
by Soukaina Abdallah-Ou-Moussa, Martin Wynn and Omar Kharbouch
Int. J. Financial Stud. 2025, 13(3), 124; https://doi.org/10.3390/ijfs13030124 - 3 Jul 2025
Viewed by 1025
Abstract
Blockchain technology is being increasingly deployed to store and process transactions and information in the global financial sector. Blockchain underpins cryptocurrencies such as Bitcoin and facilitates decentralized finance (DeFi), representing a paradigm shift in the global financial landscape, offering alternative solutions to traditional [...] Read more.
Blockchain technology is being increasingly deployed to store and process transactions and information in the global financial sector. Blockchain underpins cryptocurrencies such as Bitcoin and facilitates decentralized finance (DeFi), representing a paradigm shift in the global financial landscape, offering alternative solutions to traditional banking, and fostering financial inclusion. In developing economies such as Morocco, where a significant portion of the population remains unbanked, these digital financial innovations present both opportunities and challenges. This study examines the potential role of cryptocurrencies and DeFi in enhancing financial inclusion in Morocco, where cryptocurrencies have been banned since 2017. However, the public continues to use cryptocurrencies, circumventing restrictions, and the Moroccan Central Bank is now preparing to introduce new regulations to legalize their use within the country. In this context, this article analyses the potential of cryptocurrencies to mitigate barriers such as high transaction costs, restricted access to financial services in rural areas, and limited financial literacy in the country. The study pursues a mixed-methods approach, which combines a quantitative survey with qualitative expert interviews and adapts the Unified Theory of Acceptance and Use of Technology (UTAUT) model to the Moroccan context. The findings reveal that while cryptocurrencies offer cost-efficient financial transactions and improved accessibility, their adoption may be constrained by regulatory uncertainty, security risks, and technological limitations. The novelty of the article thus lies in its focus on the key mechanisms that influence the adoption of cryptocurrencies and their potential impact in a specific national context. In so doing, the study highlights the need for a structured regulatory framework, investment in digital infrastructure, and targeted financial literacy initiatives to optimize the potential role of cryptocurrencies in progressing financial inclusion in Morocco. This underscores the need for integrated models and guidelines for policymakers, financial institutions, and technology providers to ensure the responsible introduction of cryptocurrencies in developing world environments. Full article
(This article belongs to the Special Issue Cryptocurrency Markets, Centralized Finance and Decentralized Finance)
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24 pages, 469 KiB  
Article
Financial Performance and Corporate Governance on Firm Value: Evidence from Spain
by Leslie Rodríguez Valencia
Int. J. Financial Stud. 2025, 13(3), 123; https://doi.org/10.3390/ijfs13030123 - 3 Jul 2025
Viewed by 1503
Abstract
This paper investigates the financial performance and corporate governance variables that influence firm valuation. This study analyzes 91 Spanish small and medium-sized enterprises (SMEs) listed on BME Growth using a fixed effects panel data model based on 5760 observations. This study covered a [...] Read more.
This paper investigates the financial performance and corporate governance variables that influence firm valuation. This study analyzes 91 Spanish small and medium-sized enterprises (SMEs) listed on BME Growth using a fixed effects panel data model based on 5760 observations. This study covered a period of five years from 2015 to 2019. This study concludes that profitability, capital structure and ownership concentration are key value drivers, while liquidity and efficiency are not statistically significant and require further contextual examination. Regarding corporate governance, the presence of controlling shareholders was found to have a significant positive impact on firm value, reinforcing the importance of ownership concentration in reducing agency conflicts and enhancing oversight. Other governance frameworks, such as firm structure and managerial concentration, did not exhibit significant effects. Full article
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22 pages, 1347 KiB  
Article
Financial Pathways to Sustainability—The Effects of Financial Inclusion, Development, and Innovation on Shaping ESG Readiness in Low- and Middle-Income Countries
by Yongsheng Guo and Mirza Muhammad Naseer
Int. J. Financial Stud. 2025, 13(3), 122; https://doi.org/10.3390/ijfs13030122 - 2 Jul 2025
Cited by 1 | Viewed by 593
Abstract
This study investigates the impacts of financial inclusion, development, and technological innovation on ESG readiness across low-income, lower-middle-income, and upper-middle-income countries from 2004 to 2020. Grounded in an augmented environmental Kuznets curve framework, financial intermediation, and financial literacy theories, the analysis employs a [...] Read more.
This study investigates the impacts of financial inclusion, development, and technological innovation on ESG readiness across low-income, lower-middle-income, and upper-middle-income countries from 2004 to 2020. Grounded in an augmented environmental Kuznets curve framework, financial intermediation, and financial literacy theories, the analysis employs a panel data approach. Results from panel and quantile regressions reveal that financial inclusion and financial development positively influence ESG readiness, with stronger effects in less financially developed countries. However, in upper-middle-income countries, excessive credit may increase energy-intensive consumption, moderating sustainability gains. Financial inclusion negatively affects ESG readiness at lower quantiles in low-innovation contexts but enhances it at higher quantiles in high-innovation settings. Financial development consistently supports ESG readiness, which is amplified by technological innovation. Effects are stronger in less financially developed countries, moderated by energy-intensive consumption in upper-middle-income economies. The findings underscore the critical role of technological infrastructure in maximising the sustainability benefits of financial systems, advocating for technology-supported financial inclusion and green financing. This study enriches the sustainable development literature and informs policies for achieving the UN Sustainable Development Goals. Full article
(This article belongs to the Special Issue Investment and Sustainable Finance)
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18 pages, 836 KiB  
Article
Training Set Optimization for Machine Learning in Day Trading: A New Financial Indicator
by Angelo Darcy Molin Brun and Adriano César Machado Pereira
Int. J. Financial Stud. 2025, 13(3), 121; https://doi.org/10.3390/ijfs13030121 - 2 Jul 2025
Viewed by 736
Abstract
Predicting and trading assets in the global financial market represents a complex challenge driven by the dynamic and volatile nature of the sector. This study proposes a day trading strategy that optimizes asset purchase and sale parameters using differential evolution. To this end, [...] Read more.
Predicting and trading assets in the global financial market represents a complex challenge driven by the dynamic and volatile nature of the sector. This study proposes a day trading strategy that optimizes asset purchase and sale parameters using differential evolution. To this end, an innovative financial indicator was developed, and machine learning models were employed to improve returns. The work highlights the importance of optimizing training sets for machine learning algorithms based on probable asset behaviors (scenarios), which allows the development of a robust model for day trading. The empirical results demonstrate that the LSTM algorithm excelled, achieving approximately 98% higher returns and an 82% reduction in DrawDown compared to asset variation. The proposed indicator tracks asset fluctuation with comparable gains and exhibits lower variability in returns, offering a significant advantage in risk management. The strategy proves to be adaptable to periods of turbulence and economic changes, which is crucial in emerging and volatile markets. Full article
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21 pages, 1316 KiB  
Article
An Empirical Analysis of the Impact of Global Risk Sentiment, Gold Prices, and Interest Rate Differentials on Exchange Rate Dynamics in South Africa
by Palesa Milliscent Lefatsa, Simiso Msomi, Hilary Tinotenda Muguto, Lorraine Muguto and Paul-Francios Muzindutsi
Int. J. Financial Stud. 2025, 13(3), 120; https://doi.org/10.3390/ijfs13030120 - 1 Jul 2025
Viewed by 740
Abstract
Exchange rate volatility poses significant challenges for emerging markets, influencing trade balances, inflation, and capital flows. South Africa’s Rand is particularly vulnerable to global risk sentiment, gold price fluctuations, and interest rate differentials, yet prior studies often analyse these factors in isolation. This [...] Read more.
Exchange rate volatility poses significant challenges for emerging markets, influencing trade balances, inflation, and capital flows. South Africa’s Rand is particularly vulnerable to global risk sentiment, gold price fluctuations, and interest rate differentials, yet prior studies often analyse these factors in isolation. This study integrates them within an autoregressive distributed lag framework, using monthly data from 2005 to 2023 to capture both short-term fluctuations and long-term equilibrium effects. The findings confirm that higher global risk sentiment triggers immediate Rand depreciation, driven by capital outflows to safe-haven assets. Conversely, rising gold prices and favourable interest rate differentials stabilise the Rand, strengthening trade balances and attracting capital inflows. These results underscore the interconnected nature of global financial conditions and exchange rate movements. This study highlights the importance of economic diversification, foreign reserve accumulation, and proactive monetary policies in mitigating currency instability in emerging markets. Full article
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