Journal Description
International Journal of Financial Studies
International Journal of Financial Studies
is an international, peer-reviewed, scholarly open access journal on financial market, instruments, policy, and management research published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), EconLit, EconBiz, RePEc, and other databases.
- Journal Rank: JCR - Q2 (Business, Finance) / CiteScore - Q2 (Finance)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 19.7 days after submission; acceptance to publication is undertaken in 5.9 days (median values for papers published in this journal in the second half of 2025).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
2.2 (2024);
5-Year Impact Factor:
2.3 (2024)
Latest Articles
Digital Financial Literacy and Investment Grip: A Study of Japanese Active Investors
Int. J. Financial Stud. 2026, 14(2), 25; https://doi.org/10.3390/ijfs14020025 - 27 Jan 2026
Abstract
Investors’ ability to retain investments during bearish and uncertain market periods is a crucial behavioral trait for long-term wealth accumulation and reduces market instability. Nevertheless, little is understood about how digital financial literacy (DFL) shapes the capacity of increasingly digitalized financial environments. This
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Investors’ ability to retain investments during bearish and uncertain market periods is a crucial behavioral trait for long-term wealth accumulation and reduces market instability. Nevertheless, little is understood about how digital financial literacy (DFL) shapes the capacity of increasingly digitalized financial environments. This study investigates the links between DFL and investment grip among Japanese active investors—defined here, following conventional Japanese regulatory and research practice, as individuals who maintain a securities account and have engaged with an online brokerage within the past year—building on several theoretical perspectives from behavioral science. Using survey data from 149,261 individuals with an active account at Rakuten Securities, we estimated ordered probit regression models as the main specification. The findings showed a strong positive association between DFL and investment grip, even after accounting for demographic, socioeconomic, as well as cognitive attributes. These results are supported by robustness tests employing a probit model with a binary outcome. The sample consists exclusively of digitally active retail investors; the findings are therefore most directly applicable to this subpopulation. Overall, the evidence suggests that DFL fosters investors’ capacity to endure market volatility by promoting rational decision-making and reducing panic-driven selloffs. This study offers new empirical findings that will help promote financial resilience in technology-driven markets.
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(This article belongs to the Special Issue Stock Market Developments and Investment Implications)
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Corporate Governance Structures and Firm Value: The Mediating Role of Financial Distress in ASEAN Construction Companies
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Anton Firdaus, Nunuy Nur Afiah, Harry Suharman and Tettet Fitrijanti
Int. J. Financial Stud. 2026, 14(1), 24; https://doi.org/10.3390/ijfs14010024 - 21 Jan 2026
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This study tests the connectionbetween corporate governance structures and firm value, incorporating financial distress as a mediating mechanism among construction companies listed in ASEAN markets. Utilizing a sample of 58 firms drawn from an initial population of 169 companies over the 2018–2021 period,
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This study tests the connectionbetween corporate governance structures and firm value, incorporating financial distress as a mediating mechanism among construction companies listed in ASEAN markets. Utilizing a sample of 58 firms drawn from an initial population of 169 companies over the 2018–2021 period, this study measures governance mechanisms through managerial ownership, institutional ownership, independent commissioners, audit committees, and litigation risk. Firm value is proxied by Tobin’s Q, while financial distress is assessed utilizing the Altman Z-Score. Panel data regression is employed to test the direct connections, and the Sobel test is used to evaluate the mediating role of financial distress. The outcome describes that managerial ownership and audit committees have a favorable effect on firm value, whereas independent commissioners and litigation risk exert a negative influence. Institutional ownership shows no significant association with firm value. Moreover, institutional ownership significantly affects financial distress, whereas the other governance mechanisms show no significant association with financial distress, although financial distress itself has a detrimental impact on firm value. The mediation analysis describes that financial distress mediates only the connection between institutional ownership and firm value. These outcomes help clarify prior inconsistencies in the literature and underscore the importance of strengthening managerial ownership and audit committees, optimizing the role of independent commissioners, and mitigating litigation risk to sustain firm value.
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How Environmental Uncertainty Drives Asymmetric Mispricing in China: Dual Channels and Heterogeneous Media Effect
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Shuya Hu and Shengnian Wang
Int. J. Financial Stud. 2026, 14(1), 23; https://doi.org/10.3390/ijfs14010023 - 14 Jan 2026
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The essay delves into the impact of environmental uncertainty on asymmetric mispricing, utilizing the data from listed firms in China spanning from 2007 to 2023. Our analysis reveals that environmental uncertainty amplifies stock mispricing within capital markets, whether upward or downward. Diverging from
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The essay delves into the impact of environmental uncertainty on asymmetric mispricing, utilizing the data from listed firms in China spanning from 2007 to 2023. Our analysis reveals that environmental uncertainty amplifies stock mispricing within capital markets, whether upward or downward. Diverging from prior research, we distinguish between upward and downward mispricing and reveal the black box of environmental uncertainty affecting stock mispricing from dual channels. Specifically, environmental uncertainty intensifies upward mispricing through heightened earnings management and exacerbates downward mispricing by boosting investor irrationality. Furthermore, we explore the heterogeneous impact of different media coverage. In the downward mispricing sample, negative media exacerbated the relationship between the two, while positive coverage played a mitigating role. In the upward mispricing sample, only negative reports have a significant impact and mitigate the impact of uncertainty on mispricing. Our research on media heterogeneity once again proves that it is a double-edged sword. Our research indicates that improving the capacity to recognize different mispricing mechanisms in various market directions can greatly boost decision-making efficiency. Meanwhile, it is vital to strengthen professional ethics in media organizations and encourage more objective reporting. These efforts can jointly contribute to improving the efficiency of emerging capital markets.
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Risk Aversion, Self-Control, Commitment Savings Device and Benchmark-Defined Undersaving Among Nano Enterprises in Urban Slums: A Logistic Regression Approach
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Edward A. Osifodunrin and José Dias Lopes
Int. J. Financial Stud. 2026, 14(1), 22; https://doi.org/10.3390/ijfs14010022 - 14 Jan 2026
Abstract
Low-income individuals are unlikely to save relatively large sums on a regular basis; however, many still fall short of even the modest threshold required for long-term financial security. This study examines the determinants of benchmark-defined undersaving among retail e-payment agents (REAs) operating in
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Low-income individuals are unlikely to save relatively large sums on a regular basis; however, many still fall short of even the modest threshold required for long-term financial security. This study examines the determinants of benchmark-defined undersaving among retail e-payment agents (REAs) operating in the urban slums of Lagos, Nigeria. We use a contingent valuation survey, descriptive analysis, and logistic regression to examine how selected behavioural and demographic factors, alongside a 60-day experimental intervention—the Programmed Microsaving Scheme (PMSS), a hard daily commitment savings device—affect the likelihood of undersaving, defined as saving less than 12% of each REA’s average daily income. While the PMSS appears to have contributed to improvements in post-treatment saving participation and performance among REAs, it did not significantly increase the likelihood of reaching or exceeding the benchmark savings threshold. Consistent with this, average daily income, age, gender, marital status, education, and religion are statistically insignificant predictors of benchmark-defined undersaving. In contrast, self-control, measured using a literature-validated instrument, exhibits a statistically significant negative association with benchmark-defined undersaving, indicating that higher self-control reduces the likelihood of failing to meet the benchmark. Measured risk aversion similarly shows no significant association. Notably, this study introduces a novel 60-day PMSS, co-designed with REAs and neobanks to accommodate daily income savings—a characteristic of the informal sector largely overlooked in the literature on commitment savings devices. From a policy perspective, the findings suggest that while short-horizon commitment devices (such as the 60-day PMSS) and financial literacy are associated with improvements in microsavings among low-income daily earners, achieving benchmark-level saving might require longer-term and more adaptive mechanisms that address income volatility and mitigate other inherent risks.
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Open AccessArticle
Distance to Governance Regulatory on Financial Performance: Evidence from Managerial Disclosure Activities at Vietnam
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Thi Ngoc Anh Nguyen and Hail Jung
Int. J. Financial Stud. 2026, 14(1), 21; https://doi.org/10.3390/ijfs14010021 - 13 Jan 2026
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This study examines how geographic distance to Vietnam’s centralized securities regulator—the State Securities Commission (SSC)—influences firm-level stock price crash risk. In emerging markets characterized by weak governance, corruption, and political connections, distance can erode monitoring effectiveness and heighten managerial incentives to conceal bad
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This study examines how geographic distance to Vietnam’s centralized securities regulator—the State Securities Commission (SSC)—influences firm-level stock price crash risk. In emerging markets characterized by weak governance, corruption, and political connections, distance can erode monitoring effectiveness and heighten managerial incentives to conceal bad news. Using data on Vietnamese listed firms from 2010 to 2024, we find a robust positive association between a firm’s distance to the SSC headquarters in Hanoi and its future crash risk. The effect is stronger for non-state-owned enterprises (non-SOEs) and in provinces with high corruption, but disappears in SOEs and in more transparent regions, where state-related networks provide insulation from weak formal institutions. Exploiting the 2019 Securities Law as a quasi-natural experiment, we show that the distance effect was more pronounced before the reform, suggesting that improved formal regulation can partially offset geographically induced monitoring frictions. Additional tests reveal that the effect is amplified among firms listed on the Ho Chi Minh Stock Exchange (HOSE) and those with higher financial leverage. Our findings provide novel evidence on the spatial dimension of regulatory enforcement in emerging markets. We highlight geographic distance as a significant but previously overlooked source of crash risk, with implications for regulators in designing risk-based supervision and for investors in pricing location-driven risks.
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Sustainability Practices and Capital Costs: Evidence from Banks and Financial Technology Firms in Global Markets
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Raminta Vaitiekuniene and Alfreda Sapkauskiene
Int. J. Financial Stud. 2026, 14(1), 20; https://doi.org/10.3390/ijfs14010020 - 12 Jan 2026
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This paper examines the impact of environmental, social, and governance (ESG) disclosure on the cost of capital for banks as well as financial technology companies in Europe, America, and Asia from 2010 to 2024. The study investigates how sustainability affects financing conditions in
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This paper examines the impact of environmental, social, and governance (ESG) disclosure on the cost of capital for banks as well as financial technology companies in Europe, America, and Asia from 2010 to 2024. The study investigates how sustainability affects financing conditions in the two institutional settings of conventional and digital financial intermediaries. We estimate the average cost of capital using the traditional WACC (weighted average cost of capital) formula, which calculates the cost and proportions of debt and equity capital. Panel regressions with firm and year fixed effects are used, along with an instrumental variable (IV) approach (2SLS), by way of peer-based ESG instruments to correct for endogeneity. The paper also carries out robustness checks such as the Anderson–Rubin weak IV tests and over identification diagnostics. The findings indicate that more ESG disclosure has a significant negative effect on WACC and debt costs and no robust impact on equity cost. Governance disclosure is revealed to be the dominant dimension and it always correlates with lower financing costs. Environmental disclosure is occasionally associated with a higher cost of equity, owing to investors’ expectation of short-term compliance costs. The results shed light on the dynamic relationship between innovation and sustainability in driving banks and financial technology firms financing environment.
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Open AccessReview
A Review of Gender-Inclusive Green Microfinance Business Models in Tunisia: A Business Model Canvas Perspective
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Nadia Mansour
Int. J. Financial Stud. 2026, 14(1), 19; https://doi.org/10.3390/ijfs14010019 - 9 Jan 2026
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This paper presents a systematic review of Tunisian stakeholders’ perceptions of integrating gender into green microfinance business models, analyzed through the lens of the Business Model Canvas (BMC). This systematic review of 32 studies indicates a dual perception of women as both vulnerable
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This paper presents a systematic review of Tunisian stakeholders’ perceptions of integrating gender into green microfinance business models, analyzed through the lens of the Business Model Canvas (BMC). This systematic review of 32 studies indicates a dual perception of women as both vulnerable victims and active agents in the ecological transition. The BMC-based analysis reveals major weaknesses in the value proposition, distribution channels, and cost structures of gendered green microfinance offerings. Furthermore, we highlight the underexplored role of regulatory frameworks as levers for business model innovation. This study offers an original analytical framework that links gender, environmental sustainability, and microfinance business models, providing actionable insights for policymakers and microfinance institutions seeking to foster inclusive and sustainable financial ecosystems in Tunisia and similar contexts.
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(This article belongs to the Topic Sustainable and Green Finance)
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A Bibliometric Analysis of Digital Financial Literacy and Its Role in Reducing Online Financial Fraud in the European Union
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Carol Wangari Maina, Mahdi Imani Bashokoh and Diána Koponicsné Györke
Int. J. Financial Stud. 2026, 14(1), 18; https://doi.org/10.3390/ijfs14010018 - 8 Jan 2026
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The rapid digitalization of financial services in the European Union (EU) has not only enhanced convenience and inclusion but also increased exposure to sophisticated online financial fraud. Digital financial literacy (DFL) is widely promoted as a key tool for empowering consumers and reducing
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The rapid digitalization of financial services in the European Union (EU) has not only enhanced convenience and inclusion but also increased exposure to sophisticated online financial fraud. Digital financial literacy (DFL) is widely promoted as a key tool for empowering consumers and reducing fraud victimization. However, the empirical and conceptual landscape linking DFL to fraud reduction within the specific sociolegal context of the EU remains fragmented. This study uses bibliometric analysis to map the research area, define major themes within the field, and determine the role of DFL in reducing online financial fraud in the EU. Peer-reviewed journal articles were targeted to ensure academic rigor, with a publication window of 2010–2025 reflecting key fintech and regulatory developments. After adhering to PRISMA principles, 87 peer-reviewed publications were chosen out of a total of 568 records identified through OpenAlex and Web of Science, coauthorship, keyword co-occurrence, citation, temporal, and density representations were analyzed using VOSviewer. Findings indicate an increasingly diffuse research field with new clusters concentrating on macroeconomic policy, business technology, social psychology, and interdisciplinary foundations. Results demonstrate that successful implementation of DFL interventions combines behavioral insights, technological protection, and non-discriminatory policy considerations. The study concludes by identifying major gaps in research and providing a path forward for future evidence-based policy efforts toward enhancing consumer protection in the EU digital financial market.
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Open AccessArticle
The Financial Lobster Bias
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Óscar De los Reyes Marín, Iria Paz Gil, Jose Torres-Pruñonosa and Raúl Gómez-Martínez
Int. J. Financial Stud. 2026, 14(1), 17; https://doi.org/10.3390/ijfs14010017 - 7 Jan 2026
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The Financial Lobster Bias describes how SMEs, driven by distorted liquidity perceptions, engage in aggressive expansion until financial breakdown occurs. Using data from 10,412 Spanish SMEs (2000–2024), this study shows that liquidity misperception—measured through two versions of the Liquidity Misperception Index (PEL), one
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The Financial Lobster Bias describes how SMEs, driven by distorted liquidity perceptions, engage in aggressive expansion until financial breakdown occurs. Using data from 10,412 Spanish SMEs (2000–2024), this study shows that liquidity misperception—measured through two versions of the Liquidity Misperception Index (PEL), one based on financial structure and another on payment–collection timing (PMP–PMC)—is a significant driver of expansion–collapse cycles. The financial PEL displays a strong temporal trend (R2 = 0.736), while the PMP–PMC-based PEL also increases over time (R2 = 0.411), evidencing a persistent widening between perceived and real liquidity. The Illusory Confidence in Liquidity Index (ICEL) reveals that confidence peaks coincide with periods of systemic fragility. The Unsustainable Expansion Index (IEI) identifies pre-crisis overexpansion (IEI = 2.34 in 2005; 2.87 in 2006; 1.72 in 2007), preceding the 2008 failure surge. Together, these indicators provide early-warning mechanisms that uncover hidden fragility and help anticipate liquidity-driven collapse.
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Open AccessArticle
Design and Evaluation of Machine Learning-Based Investment Strategies in Equity Funds
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Danillo Guimarães Cassiano da Silva, Estaner Claro Romão and Fabiano Fernandes Bargos
Int. J. Financial Stud. 2026, 14(1), 16; https://doi.org/10.3390/ijfs14010016 - 7 Jan 2026
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This study examines quantitative investment strategies for Brazilian equity funds, integrating traditional financial performance indicators with machine learning techniques to enhance fund selection. The main objective was to construct and validate predictive models for fund selection. The methodology involved collecting daily data from
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This study examines quantitative investment strategies for Brazilian equity funds, integrating traditional financial performance indicators with machine learning techniques to enhance fund selection. The main objective was to construct and validate predictive models for fund selection. The methodology involved collecting daily data from 2019 to 2025, computing a range of return and risk measures, and trained models to classify 1- and 3-month shifted windows. The 3-month models achieved the strongest predictive accuracy, exceeding 91%, with the Sharpe Ratio emerging as the most influential feature. A 12-month backtest (October/2024–September/2025) showed that ML-constructed portfolios delivered cumulative returns between 14.65% and 91.86%, depending on the selection criterion, substantially outperforming Brazil’s CDI risk-free benchmark (12.70%) and the Ibovespa (11.46%). These findings highlight the practical potential of ML-based fund selection, though successful implementation requires careful risk management and ongoing model validation.
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Open AccessArticle
Quantum-Based Method to Estimate Future Tax Compositions: Application to the Case of Foreign Trade in Mexico
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Sergio Lagunas-Puls and Oliver Cruz-Milán
Int. J. Financial Stud. 2026, 14(1), 15; https://doi.org/10.3390/ijfs14010015 - 7 Jan 2026
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Using a method inspired by quantum principles, this study estimates the composition of various types of tax contributions expected from foreign trade operations. The estimation approach is proposed considering the superposition of expectations and disturbances—fundamental elements of quantum methods—that add complexity to the
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Using a method inspired by quantum principles, this study estimates the composition of various types of tax contributions expected from foreign trade operations. The estimation approach is proposed considering the superposition of expectations and disturbances—fundamental elements of quantum methods—that add complexity to the forecasts of tax collections. For instance, the contributions of international trade-related taxes may be determined not only by the country’s degree of regional integration but also by the composition of tax revenue that depends on the kind and use of merchandise. Using the case of Mexico’s imports, the methodology illustrates how the expectations of collecting certain taxes—like the General Import Tariff (GIT) and the Value Added Tax (VAT)—would be impacted by fluctuations in others—such as the Special Tax on Production and Services (STPS). The hypothesis of this study is that, through the proposed quantum-inspired methodology, it is possible to establish future scenarios of tax revenue compositions while maintaining fiscal consistency by anticipating potential outcomes in the adjustments of contributions if the recently proposed fiscal reform is approved by the Mexican Government. This work contributes to the academic literature on public finance management by advancing a methodology that can support the strategic formulation of fiscal expectations and policy.
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Systemic Operational Risk in Morocco’s Banking Sector: An Empirical Analysis Using Panel VAR
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Kawtar El Khadi and Zakaria Firano
Int. J. Financial Stud. 2026, 14(1), 14; https://doi.org/10.3390/ijfs14010014 - 7 Jan 2026
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This study examines the systemic operational risk in Morocco’s banking sector using a Panel VAR model based on data from three banks over ten years. The model includes real GDP, interbank rate (TMP), and bank credit, alongside indicators of operational, credit, and liquidity
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This study examines the systemic operational risk in Morocco’s banking sector using a Panel VAR model based on data from three banks over ten years. The model includes real GDP, interbank rate (TMP), and bank credit, alongside indicators of operational, credit, and liquidity risks. The Impulse Response Functions (IRF) show that operational risk shocks reduce GDP and affect TMP with a lag, confirming their systemic impact. Forecast Error Variance Decomposition (FEVD) reveals that GDP significantly explains the variance in operational risk. To strengthen the analysis, a dynamic panel GMM model is used to address endogeneity. The GMM results demonstrate that systemic operational risk in Moroccan banks is both persistent and procyclical, highlighting how macro-financial dynamics such as growth, inflation, and monetary conditions, directly shape banks’ resilience. These findings provide new empirical evidence on the determinants of systemic operational risk in emerging markets. This dual approach supports the integration of operational risk into Morocco’s macroprudential policy frameworks.
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Open AccessCorrection
Correction: Moreno-Menéndez et al. (2025). Improving Financial Sustainability Through Effective Credit Risk Management and Human Talent Development in Microfinance Institutions. International Journal of Financial Studies, 13(2), 60
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Fabricio Miguel Moreno-Menéndez, Vicente González-Prida, Diana Pariona-Amaya, Victoriano Eusebio Zacarías-Rodríguez, Víctor Zacarías-Vallejos, Sara Ricardina Zacarías-Vallejos, Luis Alberto Aguilar-Cuevas and Lisette Paola Campos-Carpena
Int. J. Financial Stud. 2026, 14(1), 13; https://doi.org/10.3390/ijfs14010013 - 6 Jan 2026
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In the published paper [...]
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Open AccessArticle
Workforce Shocks and Financial Markets: Asset Pricing Perspectives
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Samreen Akhtar, Jyoti Agarwal, Alam Ahmad, Refia Wiquar and Mohd Shahid Ali
Int. J. Financial Stud. 2026, 14(1), 12; https://doi.org/10.3390/ijfs14010012 - 6 Jan 2026
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Workforce adjustments, such as mass layoffs, are significant corporate events that can influence stock returns and volatility, yet their broader asset-pricing implications remain underexplored. We examine the impact of such workforce shocks on stock performance from an asset-pricing perspective. Grounded in production-based asset-pricing
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Workforce adjustments, such as mass layoffs, are significant corporate events that can influence stock returns and volatility, yet their broader asset-pricing implications remain underexplored. We examine the impact of such workforce shocks on stock performance from an asset-pricing perspective. Grounded in production-based asset-pricing theory, incorporating labor adjustment costs and search-and-matching frictions, our study posits that disruptions in the labor force significantly affect firm risk and value. This focus addresses a clear gap. Previous research has not comprehensively evaluated workforce shocks as systematic risk factors in a cross-sectional asset-pricing model. Using an extensive dataset spanning 1990–2023 and covering thousands of layoff events, we construct a novel “workforce shock” factor and conduct the first large-scale empirical tests of its pricing relevance. Our analysis reveals that workforce shocks lead to lower stock returns and heightened volatility, effects especially pronounced in labor-intensive firms. Moreover, exposure to workforce shock risk carries a significant premium, indicating that these disruptions act as a systematic risk factor priced in the cross-section of equity returns. Overall, our study provides the first comprehensive evidence linking labor force disturbances to equity risk premia, underscoring the importance of incorporating labor market considerations into asset-pricing models.
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(This article belongs to the Special Issue Risks and Uncertainties in Financial Markets)
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Comparative Analysis of Tail Risk in Emerging and Developed Equity Markets: An Extreme Value Theory Perspective
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Sthembiso Dlamini and Sandile Charles Shongwe
Int. J. Financial Stud. 2026, 14(1), 11; https://doi.org/10.3390/ijfs14010011 - 6 Jan 2026
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This research explores the application of extreme value theory in modelling and quantifying tail risks across different economic equity markets, with focus on the Nairobi Securities Exchange (NSE20), the South African Equity Market (FTSE/JSE Top40) and the US Equity Index (S&P500). The study
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This research explores the application of extreme value theory in modelling and quantifying tail risks across different economic equity markets, with focus on the Nairobi Securities Exchange (NSE20), the South African Equity Market (FTSE/JSE Top40) and the US Equity Index (S&P500). The study aims to recommend the most suitable probability distribution between the Generalised Extreme Value Distribution (GEVD) and the Generalised Pareto Distribution (GPD) and to assess the associated tail risk using the value-at-risk and expected shortfall. To address volatility clustering, four generalised autoregressive conditional heteroscedasticity (GARCH) models (standard GARCH, exponential GARCH, threshold-GARCH and APARCH (asymmetric power ARCH)) are first applied to returns before implementing the peaks-over-threshold and block maxima methods on standardised residuals. For each equity index, the probability models were ranked based on goodness-of-fit and accuracy using a combination of graphical and numerical methods as well as the comparison of empirical and theoretical risk measures. Beyond its technical contributions, this study has broader implications for building sustainable and resilient financial systems. The results indicate that, for the GEVD, the maxima and minima returns of block size 21 yield the best fit for all indices. For GPD, Hill’s plot is the preferred threshold selection method across all indices due to higher exceedances. A final comparison between GEVD and GPD is conducted to estimate tail risk for each index, and it is observed that GPD consistently outperforms GEVD regardless of market classification.
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(This article belongs to the Special Issue Financial Markets: Risk Forecasting, Dynamic Models and Data Analysis)
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Open AccessArticle
Influence of ESG on Credit Growth: Moderating Effects of Islamic Bank and Size in MENA
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Aysha Alhamrani, Atif Awoad and Mohamed Albaity
Int. J. Financial Stud. 2026, 14(1), 10; https://doi.org/10.3390/ijfs14010010 - 6 Jan 2026
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This study examined how ESG has influenced credit growth across MENA countries/regions and investigated the extent to which bank size and Islamic banking influence this relationship. Using panel data from 42 listed banks across 10 MENA countries (367 bank-year observations from 2010–2023), the
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This study examined how ESG has influenced credit growth across MENA countries/regions and investigated the extent to which bank size and Islamic banking influence this relationship. Using panel data from 42 listed banks across 10 MENA countries (367 bank-year observations from 2010–2023), the analysis employs quantile regression to capture heterogeneous effects across different levels of credit growth. The findings showed that ESG disclosure has a significant positive influence on credit growth across most quantiles, except at the (25th) quantile where the effect was insignificant. Bank size moderated this relationship, it weakens the ESG effect at the (10th) quantile but enhances it at the (25th, 50th, 75th) quantiles. Although the relationship remained positive at the (90th) quantile, the impact slightly declined, suggesting diminishing marginal gains for larger banks. Islamic banks strengthened the ESG disclosure and credit growth relationship at (10th and 25th, 90th) quantiles but weakened it at the median quantiles. Overall, the results demonstrate that the effect of ESG disclosure on credit growth is heterogeneous and highly dependent on bank characteristics, offering meaningful implications for policymakers and banking practitioners in adapting ESG strategies to enhance credit growth across different quantiles.
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Lender of Last Resort and Financial Systemic Risks in Times of Economic Stability: Evidence from 55 Countries
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Wenlong Miao, Yuxian Ma and Yuanyuan Huo
Int. J. Financial Stud. 2026, 14(1), 9; https://doi.org/10.3390/ijfs14010009 - 6 Jan 2026
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As a cornerstone of the modern financial safety net, the Lender of Last Resort (LOLR) is essential in mitigating liquidity crises and containing financial contagion. However, during periods of economic stability, risk-taking incentives in the banking sector may undermine its effectiveness. Using quarterly
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As a cornerstone of the modern financial safety net, the Lender of Last Resort (LOLR) is essential in mitigating liquidity crises and containing financial contagion. However, during periods of economic stability, risk-taking incentives in the banking sector may undermine its effectiveness. Using quarterly panel data from 55 countries over the period 2010–2023, this study employs a two-way fixed effects model to assess the impact of LOLR support on systemic financial risk and its transmission mechanisms. We find that LOLR support significantly increases systemic risk during stable economic periods. Mechanism analysis indicates that this effect is channeled through the erosion of bank asset liquidity, expansion of financial leverage, and deterioration in asset quality. Moreover, the adverse impact is more pronounced in emerging economies, bank-dominated financial systems, countries with low capital adequacy ratios, underdeveloped regulatory frameworks, and lower levels of digital technology adoption. This study provides cross-country evidence on the potential negative consequences of central bank rescue functions during calm periods and offers important policy insights for optimizing the LOLR framework and building a more resilient financial safety net.
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Open AccessArticle
Market Structure, Efficiency, and the Quest for Banking Performance: New Insights from an Evolving Banking Market
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Naveed Khan, Muhammad Asim Afridi, Muhammad Tahir and Umar Burki
Int. J. Financial Stud. 2026, 14(1), 8; https://doi.org/10.3390/ijfs14010008 - 5 Jan 2026
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This study investigates the impact of market structure on the performance of banks in Pakistan. It explicitly tests two competing hypotheses: the Structure–Conduct–Performance paradigm and the Efficient Structure Hypothesis, providing insights into whether profitability stems from market concentration or efficiency. The study employs
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This study investigates the impact of market structure on the performance of banks in Pakistan. It explicitly tests two competing hypotheses: the Structure–Conduct–Performance paradigm and the Efficient Structure Hypothesis, providing insights into whether profitability stems from market concentration or efficiency. The study employs the Data Envelopment Analysis approach to measure banking efficiency and uses the concentration ratio to capture market structure. A regression framework is applied, with efficiency and market structure as key explanatory variables. Further, bank-specific controls are included to examine their effects on performance, measured by Return on Assets. Results show that although the concentration of the five largest banks slightly declined, it remains relatively high at 58.5%. Banks, on average, operate at 67% efficiency with an upward trend over time. The findings lend more substantial support to the Efficient Structure Hypothesis, indicating that profitability is primarily driven by technical and scale efficiency rather than market concentration, with individual bank market share affecting performance only as an outcome of efficiency gains. The analysis highlights that efficiency improvements are crucial in enhancing banks’ performance in Pakistan. Over the years, the banking sector of Pakistan has evolved in terms of market structure, efficiency, and banks’ performance. This study interprets the changes in the market structure in the context of the structure conduct performance hypothesis and/or the efficient structure performance hypothesis and answers the question regarding whether market power and/or efficient structure is relevant to the banks’ performance. For policymakers, the results suggest that efforts to improve competitive efficiency, such as encouraging innovation, risk management, and capacity utilization, are more effective than focusing solely on altering market concentration.
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Open AccessArticle
Financing Startups and Impact Investing: Evidence Across MENA Countries
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Slim Mseddi
Int. J. Financial Stud. 2026, 14(1), 7; https://doi.org/10.3390/ijfs14010007 - 5 Jan 2026
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This study empirically investigates the determinants of financial success for startups engaged in impact versus conventional investment, performing a landscape analysis of the MENA region’s financial ecosystem. Using the total equity funding amount (TEFA) as a performance proxy, we analyzed data from Crunchbase
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This study empirically investigates the determinants of financial success for startups engaged in impact versus conventional investment, performing a landscape analysis of the MENA region’s financial ecosystem. Using the total equity funding amount (TEFA) as a performance proxy, we analyzed data from Crunchbase on 6772 deals involving 4381 startups and 1771 investors across 23 countries from 2009 to 2023. The sample was categorized into impact (702 firms) and conventional (2431 firms) investment groups. The results reveal a significant negative effect of impact investment on startup funding levels; a nonparametric test confirmed that impact-backed startups exhibit a significantly lower mean TEFA than their conventional counterparts. Other factors, including the number of funding rounds, founders, employees, and investors, positively influenced financial success. The study concludes that, within the MENA context, a discernible trade-off exists, with startups pursuing impact investment receiving less equity funding than those utilizing conventional investment models. Our study provides the first large-scale empirical evidence from the MENA region, revealing a significant funding penalty for impact-aligned startups. This quantifies a structural trade-off between socio-environmental goals and equity capital access. These findings address a critical literature gap and provide actionable insights for investors and policymakers in this emerging ecosystem.
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Open AccessArticle
Has IPO Market Structure Fundamentally Changed? Evidence from Negative Binomial Regression with Structural Breaks
by
Michael D. Herley
Int. J. Financial Stud. 2026, 14(1), 6; https://doi.org/10.3390/ijfs14010006 - 5 Jan 2026
Abstract
This paper introduces Bai-Perron structural break detection combined with negative binomial regression to model overdispersed U.S. IPO count data. Using monthly data from 1995 to 2024, we identify five breaks that partition IPO activity into six distinct regimes, each with fundamentally different variance
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This paper introduces Bai-Perron structural break detection combined with negative binomial regression to model overdispersed U.S. IPO count data. Using monthly data from 1995 to 2024, we identify five breaks that partition IPO activity into six distinct regimes, each with fundamentally different variance characteristics. We then employ negative binomial regression that incorporates these breaks. IPO data show substantial overdispersion (variance-to-mean ratios: 2.77 to 33.74). The negative binomial model reveals that market uncertainty (as measured by the VIX) and financing costs (as indicated by 10-year Treasury rates) reduce IPO activity, while lagged IPO volume drives activity in the current period. Regime-specific likelihood ratio tests reveal that statistically significant overdispersion first emerges during the 2008 financial crisis, subsides during the post-recession period, and returns with unprecedented intensity after May 2020. An OLS model without the identified structural breaks incorrectly suggests positive interest rate effects.
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(This article belongs to the Special Issue Advances in Financial Econometrics)
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