International Journal of Financial Studies

18 pages, 4633 KiB

Open AccessArticle

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

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

► Show Figures

Figure 1

19 pages, 677 KiB

Open AccessFeature PaperArticle

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

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

► Show Figures

Figure 1

25 pages, 1750 KiB

Open AccessArticle

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

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)

► Show Figures

Figure 1

24 pages, 469 KiB

Open AccessArticle

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

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

► Show Figures

Figure 1

22 pages, 1347 KiB

Open AccessArticle

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

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)

► Show Figures

Figure 1

18 pages, 836 KiB

Open AccessArticle

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

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

► Show Figures

Figure 1

21 pages, 1316 KiB

Open AccessArticle

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

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

► Show Figures

Figure 1

27 pages, 318 KiB

Open AccessArticle

Corporate Social Responsibility and Firm Financial Performance: Evidence from America’s Best Corporate Citizens

by Kelly Huang, Yanglin Li, Kabir Oyewale and Emily Tworoger

Int. J. Financial Stud. 2025, 13(3), 119; https://doi.org/10.3390/ijfs13030119 - 1 Jul 2025

Abstract

This paper examines the relation between corporate social responsibility (CSR) and firm financial performance—a topic that continues to generate debate among academics and practitioners. We focus on firms included in the 100 Best Corporate Citizens (BCC) rankings from 2009 to 2022, a list [...] Read more.

This paper examines the relation between corporate social responsibility (CSR) and firm financial performance—a topic that continues to generate debate among academics and practitioners. We focus on firms included in the 100 Best Corporate Citizens (BCC) rankings from 2009 to 2022, a list that highlights companies recognized for CSR transparency and performance. Using panel data regression analyses and matched sample comparison, we examine whether BCC firms outperform their peers. Our findings show that, relative to matched firms not included in the rankings, BCC firms demonstrate significantly stronger future operating performance. Among BCC firms, CSR rankings are positively associated with future operating performance, although this positive relation has diminished in more recent years. Furthermore, we find no significant association between operating performance and most individual CSR component rankings except for employee relations. Finally, our evidence indicates that more socially responsible firms engage in less tax avoidance and pay higher audit fees, suggesting that CSR-oriented firms exhibit stronger ethical considerations across a broad range of corporate activities. This study contributes to the CSR literature by providing updated empirical evidence and practical insights for stakeholders evaluating corporate behavior and outcomes through the BCC rankings. Full article

(This article belongs to the Special Issue Sustainable Corporate Governance and Financial Performance)

34 pages, 723 KiB

Open AccessArticle

ESG, Climate Risk, and Debt Management—Evidence from Chinese Listed Companies

by Yang Zhao, Kamarul Bahrain bin Abdul Manaf and Hazeline bt Ayoup

Int. J. Financial Stud. 2025, 13(3), 118; https://doi.org/10.3390/ijfs13030118 - 1 Jul 2025

Abstract

The United Nations Sustainable Development Goals emphasize the need to assist developing countries in achieving long-term debt sustainability. Global corporate debt has repeatedly reached record levels, and the associated financial costs pose a significant threat to sustainable development. This study uses panel data [...] Read more.

The United Nations Sustainable Development Goals emphasize the need to assist developing countries in achieving long-term debt sustainability. Global corporate debt has repeatedly reached record levels, and the associated financial costs pose a significant threat to sustainable development. This study uses panel data from Chinese listed companies for regression analysis. The findings show that ESG reduces the interest-bearing debt ratio, the equity pledge of controlling shareholders, and the deviation from the target debt ratio, all of which contribute to improved debt management. Climate risk further strengthens the impact of ESG on debt management. Additionally, green credit policies help reduce the interest-bearing debt ratio in high-pollution industries through ESG practices. Full article

► Show Figures

Figure 1

11 pages, 225 KiB

Open AccessArticle

Analyzing Climate Change Exposure and CEO Turnover: Evidence from U.S. Firms

by Dmitriy Chulkov

Int. J. Financial Stud. 2025, 13(3), 117; https://doi.org/10.3390/ijfs13030117 - 1 Jul 2025

Abstract

This work explores the link between CEO turnover patterns and firms’ climate change exposure in a data set of over two thousand U.S. publicly traded firms. The findings demonstrate that CEO turnover is negatively associated with measures of climate change exposure developed with [...] Read more.

This work explores the link between CEO turnover patterns and firms’ climate change exposure in a data set of over two thousand U.S. publicly traded firms. The findings demonstrate that CEO turnover is negatively associated with measures of climate change exposure developed with machine learning based on the frequency of discussions linked to climate change in the firms’ earnings conference calls. The results further indicate that this significant negative relationship exists in the year after the CEO’s departure from the firm, not before their departure. CEO turnover scenarios differ in their impact on a firm’s climate change exposure and sentiment. The focus of a firm’s management and financial analysts covering the firm can shift away from the issues of climate change. The negative and significant relationship with firms’ climate change exposure is observed particularly for forced CEO departures in firings or resignations, as well as for outsider CEO replacements. No significant relationship is found for CEO departures due to retirement or for cases of internal CEO succession. The results provide insights for decision makers, investors and boards of directors trying to evaluate the role of CEO turnover in climate change exposure at firms. Full article

(This article belongs to the Special Issue Sustainable Investing and Financial Services)

17 pages, 601 KiB

Open AccessArticle

Loans to Family and Friends and the Formal Financial System in Latin America

by Susana Herrero, Jeniffer Rubio and Micaela León

Int. J. Financial Stud. 2025, 13(3), 116; https://doi.org/10.3390/ijfs13030116 - 25 Jun 2025

Abstract

In Latin America, over 50% of the population has relied on loans from family members or friends, reflecting the importance of trust-based networks in response to financial exclusion. This study examines how distrust in the formal financial system influences the use of informal [...] Read more.

In Latin America, over 50% of the population has relied on loans from family members or friends, reflecting the importance of trust-based networks in response to financial exclusion. This study examines how distrust in the formal financial system influences the use of informal borrowing. Using data from 17 countries for the years 2014, 2017, and 2021, and applying a fixed-effects logistic regression model by country and time, we confirm that rising distrust significantly increases the likelihood of turning to loans from personal networks. This relationship intensifies in times of crisis. Beyond this, we find that macroeconomic variables such as GDP per capita and unemployment also significantly affect informal borrowing behavior. This research contributes to the literature by integrating institutional, economic, and social variables, highlighting the role of interpersonal trust as a form of social capital. It also advances the field of personal finance by revealing an everyday strategy of financial resilience. Finally, this study offers relevant implications for public policy, advocating for a more realistic and context-sensitive approach to financial inclusion, especially in regions where credit constraints in the formal sector have pushed households to seek more accessible and flexible alternatives. Full article

► Show Figures

Figure 1

17 pages, 776 KiB

Open AccessArticle

Developing an Enhanced Proxy Benchmark for the Private Debt Market

by Seung Kul Lee and Hohyun Kim

Int. J. Financial Stud. 2025, 13(3), 115; https://doi.org/10.3390/ijfs13030115 - 24 Jun 2025

Abstract

Institutional investors increasingly value alternative assets in strategic asset allocation, with private debt emerging as a key asset class. However, its shortage of market history has hindered the development of standardized proxy benchmarks. For that, many institutional investors still do not recognize or [...] Read more.

Institutional investors increasingly value alternative assets in strategic asset allocation, with private debt emerging as a key asset class. However, its shortage of market history has hindered the development of standardized proxy benchmarks. For that, many institutional investors still do not recognize or manage private debt as a distinct asset class. Thus, this study aims to develop an optimized benchmark that reflects the unique characteristics of private debt, thereby contributing to establishing private debt as an independent investment asset class for strategic asset allocation among institutional investors. This study seeks to address this gap by constructing a proxy benchmark for the Preqin private debt index, which, despite its comprehensive market coverage, has a three-month reporting delay. This study employs quarterly performance data for private debt indices, spanning 31 December 2006 to 31 March 2023, and is sourced from Bloomberg and the index providers’ websites. Using regression analyses with timely asset-based indexes, the research develops a multivariate model that integrates multiple indexes, demonstrating superior tracking performance compared to existing methods. The findings provide a practical framework for improving the recognition, management, and allocation of private debt in institutional portfolios, addressing the need for reliable and timely performance metrics in this growing asset class. Full article

► Show Figures

Figure 1

20 pages, 308 KiB

Open AccessArticle

Banks’ Sustainability Reporting in Brazil

by Alexandre Pacheco and Manuel Branco

Int. J. Financial Stud. 2025, 13(3), 114; https://doi.org/10.3390/ijfs13030114 - 20 Jun 2025

Abstract

The purpose of this study is to evaluate the quality of sustainability reporting from banks operating in Brazil from the perspective of the GRI reporting principles and the coverage of reported content and its correlation with the SDGs. We also examine whether there [...] Read more.

The purpose of this study is to evaluate the quality of sustainability reporting from banks operating in Brazil from the perspective of the GRI reporting principles and the coverage of reported content and its correlation with the SDGs. We also examine whether there is some association between the quality of such reporting and some characteristics of the banks (e.g., national vs. foreign, publicly traded vs. privately held, government vs. privately controlled). We used two different methodologies proposed in existing literature to assess quality based on economic, social, and environmental contents and developed our own methodology, based on previous studies and official documents, to analyze compliance with GRI principles. The results indicate that the reports are generally of low quality, although there are some cases of medium or very low quality, demonstrating the need for improvement in their preparation. The best evaluations were for reports produced by private banks that publicly trade, are based in Brazil, and use integrated reporting. Full article

(This article belongs to the Special Issue Sustainable Investing and Financial Services)

26 pages, 456 KiB

Open AccessArticle

ESG Risks and Market Valuations: Evidence from the Energy Sector

by Rahul Verma and Arpita A. Shroff

Int. J. Financial Stud. 2025, 13(2), 113; https://doi.org/10.3390/ijfs13020113 - 18 Jun 2025

Abstract

The link between ESG and financial performance is still under debate. In this study, we explore which aspects of ESG specifically drive market valuations through both systematic and idiosyncratic risk channels. We analyze the impact of the three core ESG pillars, 10 subcategories, [...] Read more.

The link between ESG and financial performance is still under debate. In this study, we explore which aspects of ESG specifically drive market valuations through both systematic and idiosyncratic risk channels. We analyze the impact of the three core ESG pillars, 10 subcategories, and associated controversies on market valuations in the energy sector. This analysis reveals that the environmental factor has a stronger impact (regression coefficient = 0.05) than the governance factor (regression coefficient = 0.003), emphasizing the need to prioritize environmental performance in ESG strategies. The positive coefficients for environmental resource use (0.005) and innovation (0.008) indicate that investments in efficiency and clean technologies are beneficial, while the negative coefficient for emissions (−0.004) underscores the risks associated with poor emissions management. These findings suggest that environmental risks currently outweigh governance risks for the energy sector, reinforcing the importance of aligning governance practices with environmental goals. To maximize ESG effectiveness, energy firms should focus on measurable improvements in resource efficiency, innovation, and emissions reduction and transparently communicate this progress to stakeholders. The evidence suggests that energy firms approach the ESG landscape differently, with sustainability leaders benefiting from higher valuations, particularly when ESG efforts are aligned with core competencies. However, many energy companies under-invest in value-creating environmental initiatives, focusing instead on emission management, which erodes value. While they excel in emission control, they lag in innovation, missing opportunities to enhance valuations. This underscores the potential for ESG risk analysis to improve portfolio performance, as sustainability can both create value and mitigate risks by factoring into valuation equations as both risks and opportunities. This study uniquely contributes to the ESG–financial performance literature by disentangling the specific ESG dimensions that drive market valuations in the energy sector, revealing that value is created not through emission control but through strategic alignment with eco-innovation, governance, and social responsibility. Full article

► Show Figures

Figure 1

19 pages, 682 KiB

Open AccessArticle

Analysis of the Behavior of Insider Traders Who Disclose Information to External Traders

by Xingxing Cao, Jing Wang and Zhi Yang

Int. J. Financial Stud. 2025, 13(2), 112; https://doi.org/10.3390/ijfs13020112 - 17 Jun 2025

Abstract

This paper establishes an insider trading model under market supervision, which includes four types of trading entities: an insider trader, n external traders, noise traders, and market makers. The insider trader voluntarily discloses information to the external traders during the trading process. The [...] Read more.

This paper establishes an insider trading model under market supervision, which includes four types of trading entities: an insider trader, n external traders, noise traders, and market makers. The insider trader voluntarily discloses information to the external traders during the trading process. The research findings are as follows: (1) strengthening market supervision can significantly reduce the insider’s expected profit and increase the external traders’ expected profits; (2) the optimal market supervision strategy is closely related to the number of external traders; (3) the insider trader tends to disclose low-precision information to maximize their profits; (4) the precision of information disclosed by the insider trader and the intensity of market supervision affect price efficiency and the amount of residual information. The research results provide a basis for how the insider trader discloses information to external traders in market supervision and offer a reference for regulatory authorities to formulate differentiated supervision strategies. Full article

► Show Figures

Figure 1

17 pages, 2116 KiB

Open AccessArticle

Dynamic Financial Valuation of Football Players: A Machine Learning Approach Across Career Stages

by Danielle Khalife, Jad Yammine, Elias Chbat, Chamseddine Zaki and Nada Jabbour Al Maalouf

Int. J. Financial Stud. 2025, 13(2), 111; https://doi.org/10.3390/ijfs13020111 - 17 Jun 2025

Abstract

The financial valuation of professional football players is influenced by multiple factors that evolve throughout a player’s career. This study examines these determinants using Gradient Boosting Machine Learning models, segmented by three age categories and three playing positions to capture the dynamic nature [...] Read more.

The financial valuation of professional football players is influenced by multiple factors that evolve throughout a player’s career. This study examines these determinants using Gradient Boosting Machine Learning models, segmented by three age categories and three playing positions to capture the dynamic nature of player valuation. K-fold cross-validation is applied to measure accuracy, with results indicating that incorporating a player’s projected future potential improves model precision from an average of 74% to 84%. The findings reveal that the relevance of valuation factors diminishes with age, and the most influential features vary by position—shooting for attackers, passing for midfielders, and defensive skills for defenders. The study adopts a dynamic segmentation approach, providing financial insights relevant to club managers, investors, and stakeholders in sports finance. The results contribute to sports analytics and financial modeling in sports, with applications in contract negotiations, talent scouting, and transfer market decisions. Full article

(This article belongs to the Special Issue Sports Finance (2nd Edition))

► Show Figures

Figure 1

23 pages, 4406 KiB

Open AccessArticle

The Impact of Geographical Factors on the Banking Sector in El Salvador

by Anders Lundvig Hansen and Luís Lima Santos

Int. J. Financial Stud. 2025, 13(2), 110; https://doi.org/10.3390/ijfs13020110 - 13 Jun 2025

Abstract

This study explores how geographical factors shape El Salvador’s banking sector, particularly focusing on regional disparities, urbanization, and vulnerability to natural disasters affecting access to financial services. By employing a mixed-methods approach that combines quantitative data and qualitative interviews, the research analyzes how [...] Read more.

This study explores how geographical factors shape El Salvador’s banking sector, particularly focusing on regional disparities, urbanization, and vulnerability to natural disasters affecting access to financial services. By employing a mixed-methods approach that combines quantitative data and qualitative interviews, the research analyzes how these geographical challenges impact financial inclusion and banking development. Data from the Central Reserve Bank of El Salvador and financial institutions is examined alongside Geographic Information Systems (GISs) to illustrate the spatial distribution of banking services. Interviews with stakeholders, including bank representatives and clients from urban and rural areas, reveal a significant urban–rural divide, with approximately 75% of bank branches and 80% of ATMs situated in urban centers, particularly in San Salvador. Rural areas face limited access to formal banking due to challenging topography and inadequate infrastructure, leading to increased financial exclusion and reliance on informal systems. Natural disasters further disrupt banking infrastructure and heighten the need for emergency loans. While urbanization has spurred financial growth, it has also resulted in informal settlements with restricted access to formal services. As its main contribution, this study provides one of the first in-depth, geographically grounded analyses of financial exclusion in El Salvador, offering original insights into how spatial inequalities and disaster vulnerability intersect to shape banking access and economic participation. The study calls for a more inclusive banking sector, recommending mobile and digital banking expansion, agent banking in underserved areas, and improved disaster risk management to enhance economic participation across all regions. Full article

► Show Figures

Figure 1

24 pages, 318 KiB

Open AccessArticle

Bridging Digital Finance and ESG Success: The Role of Financing Constraints, Innovation, and Governance

by Zhengren Luo, Pick Schen Yip and Robert Brooks

Int. J. Financial Stud. 2025, 13(2), 109; https://doi.org/10.3390/ijfs13020109 - 9 Jun 2025

Abstract

This study investigates the impact of digital finance on corporate ESG performance, using panel data from A-share listed companies on the Shanghai and Shenzhen stock markets between 2011 and 2022. Our findings demonstrate that digital finance significantly enhances corporate ESG outcomes, with financing [...] Read more.

This study investigates the impact of digital finance on corporate ESG performance, using panel data from A-share listed companies on the Shanghai and Shenzhen stock markets between 2011 and 2022. Our findings demonstrate that digital finance significantly enhances corporate ESG outcomes, with financing constraints and digital transformation serving as partial mediators and internal control quality acting as a moderating factor. The results from channel tests indicate that digital finance facilitates notable improvements in social performance and corporate governance, while its influence on environmental performance remains limited. Further analysis reveals that the positive impacts of digital finance on ESG are more evident in small-scale, technology-intensive, and non-polluting firms. This study concludes by proposing tailored recommendations for government, financial institutions, and corporations, emphasizing the need for differentiated policies to elevate ESG practices and promote higher quality, sustainable economic, and social development in China. Full article

(This article belongs to the Special Issue Investment and Sustainable Finance)

16 pages, 350 KiB

Open AccessFeature PaperArticle

Bitcoin Return Dynamics Volatility and Time Series Forecasting

by Punit Anand and Anand Mohan Sharan

Int. J. Financial Stud. 2025, 13(2), 108; https://doi.org/10.3390/ijfs13020108 - 9 Jun 2025

Abstract

Bitcoin and other cryptocurrency returns show higher volatility than equity, bond, and other asset classes. Increasingly, researchers rely on machine learning techniques to forecast returns, where different machine learning algorithms reduce the forecasting errors in a high-volatility regime. We show that conventional time [...] Read more.

Bitcoin and other cryptocurrency returns show higher volatility than equity, bond, and other asset classes. Increasingly, researchers rely on machine learning techniques to forecast returns, where different machine learning algorithms reduce the forecasting errors in a high-volatility regime. We show that conventional time series modeling using ARMA and ARMA GARCH run on a rolling basis produces better or comparable forecasting errors than those that machine learning techniques produce. The key to achieving a good forecast is to fit the correct AR and MA orders for each window. When we optimize the correct AR and MA orders for each window using ARMA, we achieve an MAE of 0.024 and an RMSE of 0.037. The RMSE is approximately 11.27% better, and the MAE is 10.7% better compared to those in the literature and is similar to or better than those of the machine learning techniques. The ARMA-GARCH model also has an MAE and an RMSE which are similar to those of ARMA. Full article

► Show Figures

Figure 1

Journal Description

International Journal of Financial Studies

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Topical Collections

Further Information

Guidelines

MDPI Initiatives

Follow MDPI