Next Issue
Volume 18, May
Previous Issue
Volume 18, March
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.5
Journals
JRFM
Volume 18
Issue 4
share announcement

J. Risk Financial Manag., Volume 18, Issue 4 (April 2025) – 54 articles

Cover Story (view full-size image): Accurate inflation forecasts are crucial for effective monetary policy, particularly during turning points that demand policy realignment. This study examines the efficacy of Neural Network Ensemble Models in predicting U.S. inflation turning points more precisely than traditional methods, i.e., the Survey of Professional Forecasters. Results based on monthly data between 1970 and 2024 indicate that Neural Network Ensemble Models consistently outperform conventional approaches and detect inflation turning points earlier, projecting a return to target levels several months ahead of the Survey of Professional Forecasters’ average forecast. Our findings demonstrate that neural networks capture complex nonlinear relationships in macroeconomic data and hold great promise for guiding policymakers’ decisions under conditions of economic uncertainty. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
15 pages, 1071 KiB  
Article
The Effects of Bilateral and Multilateral Official Development Assistance on Vietnam’s Economic Growth
by Loc Dong Truong, H. Swint Friday and Anh Thoai Ly
J. Risk Financial Manag. 2025, 18(4), 221; https://doi.org/10.3390/jrfm18040221 - 21 Apr 2025
Viewed by 148
Abstract
This study investigates the effects of bilateral and multilateral official development assistance on Vietnam’s economic growth from 1986 to 2022. Utilizing the autoregressive distributed lag (ARDL) bounds testing approach, our results show that in the shortrun, bilateral official development assistance has a significant [...] Read more.
This study investigates the effects of bilateral and multilateral official development assistance on Vietnam’s economic growth from 1986 to 2022. Utilizing the autoregressive distributed lag (ARDL) bounds testing approach, our results show that in the shortrun, bilateral official development assistance has a significant positive influence on economic growth, whereas multilateral official development assistance has a significant negative influence on economic growth. However, the empirical findings reveal that both bilateral and multilateral official development assistance have no influence on economic growth in the longterm. Given that bilateral official development assistance has a significantly positive impact on economic growth in the shortrun, Vietnam should strengthen partnerships with donor countries. Tailoring projects to align with bilateral donors’ interests can lead to more effective interventions. In addition, multilateral official development assistance has been found to have a negative impact on economic growth in the shortrun, possibly due to complex approval and implementation processes. Therefore, the government should advocate for more flexible project requirements and reduce bureaucratic hurdles. Simplifying the approval process can help accelerate project implementation and enhance immediate economic benefits. Moreover, because official development assistance does not impact on economic growth in the longterm, Vietnam should focus on sustainable development strategies that reduce dependency on external aid. This includes investing in human capital, innovation, and technology to foster endogenous growth. Full article
(This article belongs to the Section Applied Economics and Finance)
►▼ Show Figures

Figure 1

7 pages, 169 KiB  
Editorial
Featured Papers in Corporate Finance and Governance
by Ștefan Cristian Gherghina
J. Risk Financial Manag. 2025, 18(4), 220; https://doi.org/10.3390/jrfm18040220 - 21 Apr 2025
Viewed by 162
Abstract
Amid global uncertainties and economic fluctuations, enterprises play a crucial role in fostering sustainable growth and high-quality development through innovative and responsible practices (Xin et al [...] Full article
(This article belongs to the Special Issue Featured Papers in Corporate Finance and Governance)
15 pages, 274 KiB  
Article
Financial Literacy and Leadership Skills Among Healthcare Professionals in Greece
by Georgios Pakos and Panagiotis Mpogiatzidis
J. Risk Financial Manag. 2025, 18(4), 219; https://doi.org/10.3390/jrfm18040219 - 18 Apr 2025
Viewed by 495
Abstract
Healthcare professionals require comparable knowledge and abilities in hospital financial administration. In addition, many physicians are not equipped to manage the leadership roles that healthcare systems require, namely the capacity to express a vision, convey it to others, garner willing support for it, [...] Read more.
Healthcare professionals require comparable knowledge and abilities in hospital financial administration. In addition, many physicians are not equipped to manage the leadership roles that healthcare systems require, namely the capacity to express a vision, convey it to others, garner willing support for it, and enable others to be leaders in return. Previous studies have demonstrated that physicians often lack financial literacy, while a recent systematic review and meta-analysis showed that healthcare professionals lack adequate financial literacy, although top healthcare practitioners and executive nurse leaders are encouraged to develop knowledge and abilities outside of their clinical specialty. The need for medical practitioners to receive training and experience in medical leadership has also been discussed in earlier studies. In Greece, evidence regarding the financial literacy levels and leadership skills among healthcare professionals is lacking, although physicians and nurses are required to obtain managerial and administrative roles as they progress in their positions. Our objective was to assess healthcare professionals’ levels of financial literacy and investigate the relationship between financial literacy and leadership skills in Greece. We conducted a prospective, multi-centered, question-based survey among healthcare professionals in several institutions in Northern Greece. Participants were asked to fill out basic demographic questions, the OECD/INFE Toolkit for Measuring Financial Literacy and Financial Inclusion 2022, and the Leadership Skills questionnaire, translated into Greek. The factorability of the questionnaires was examined with factor analysis, while the internal consistency was examined with Cronbach’s alpha. A linear correlation of leadership scores with financial literacy scores was performed with the Spearman rho, and multivariate regression analysis examined the correlation of the leadership score with financial literacy scores, adjusted for the type of task, education, status, gender, and age. The overall financial literacy score for all healthcare professionals was 69.14 ± 13.25%, which was higher compared to the average for the Greek population. Male healthcare professionals with administrative tasks had significantly higher overall financial literacy and digital financial literacy scores than females, or professionals without administrative tasks, as well as higher scores in all areas of leadership. Physicians had significantly higher overall financial literacy scores than nurses and significantly lower digital financial behavior and digital finance trend scores. Still, physicians scored significantly lower than nurses in all areas of leadership skills. There was a strong correlation between overall financial and digital financial literacy scores with leadership skills scores. Future research is warranted to explore how formal financial and leadership education included in the training programs of healthcare professionals would empower physicians by enabling them to make proactive decisions regarding their financial and managerial destiny. Full article
(This article belongs to the Section Financial Markets)
16 pages, 465 KiB  
Article
Multi-Period Portfolio Optimization Model with Cone Constraints and Discrete Decisions
by Ümit Sağlam and Hande Y. Benson
J. Risk Financial Manag. 2025, 18(4), 218; https://doi.org/10.3390/jrfm18040218 - 18 Apr 2025
Viewed by 141
Abstract
This work develops a practical multi-period optimization approach that incorporates real-world constraints, including discrete decisions and conic risk constraints. Expanding upon earlier single-period models, our framework employs a binary scenario tree derived from monthly returns of randomly selected S&P 500 stocks to represent [...] Read more.
This work develops a practical multi-period optimization approach that incorporates real-world constraints, including discrete decisions and conic risk constraints. Expanding upon earlier single-period models, our framework employs a binary scenario tree derived from monthly returns of randomly selected S&P 500 stocks to represent market evolution across multiple periods. The formulation captures essential portfolio constraints, such as transaction fees, sector diversification, and minimum investment thresholds, resulting in a robust and comprehensive optimization approach. To efficiently solve the resulting mixed-integer second-order cone programming (MISOCP) problem, we employ an outer approximation algorithm with a warmstart strategy, which significantly improves solution runtimes and computational efficiency. Numerical experiments demonstrate the model’s effectiveness, showing an average improvement of 10.71% in iteration count and 15.24% in computational time when using the warmstart approach. Full article
(This article belongs to the Special Issue Computational Finance and Financial Econometrics)
►▼ Show Figures

Figure 1

24 pages, 1243 KiB  
Article
Adoption of Artificial Intelligence-Driven Fraud Detection in Banking: The Role of Trust, Transparency, and Fairness Perception in Financial Institutions in the United Arab Emirates and Qatar
by Hadeel Yaseen and Asma’a Al-Amarneh
J. Risk Financial Manag. 2025, 18(4), 217; https://doi.org/10.3390/jrfm18040217 - 18 Apr 2025
Viewed by 386
Abstract
This paper examines the uptake of AI-driven fraud detection systems among financial institutions in the UAE and Qatar, with a special focus on trust, transparency, and perceptions of fairness. Despite the promise of AI operations in identifying financial anomalies, unclear decision-making processes and [...] Read more.
This paper examines the uptake of AI-driven fraud detection systems among financial institutions in the UAE and Qatar, with a special focus on trust, transparency, and perceptions of fairness. Despite the promise of AI operations in identifying financial anomalies, unclear decision-making processes and algorithmic bias constrain its extensive acceptance, especially in regulation-driven banking sectors. This study uses a quantitative strategy based on Partial Least Squares Structural Equation Modeling (PLS-SEM) and Multi-Group Analysis (MGA) of survey responses from 409 bank professionals, such as auditors and compliance officers. This study shows that transparency greatly enhances trust, which is the leading predictor of AI uptake. Fairness perception mediates the negative impacts of algorithmic bias, emphasizing its important role in establishing system credibility. The analysis of subgroups shows differential regional and professional variations in trust and fairness sensitivity, where internal auditors and highly AI-exposed subjects are found to exhibit higher adoption preparedness. Compliance with regulations also emerges as a positive enabler of adoption. This paper concludes with suggestions for practical implementation by banks, developers, and regulators to align AI deployment with ethical and regulatory aspirations. It recommends transparent, explainable, and fairness-sensitive AI tools as essential for promoting adoption in regulation-driven sectors. The findings provide a guide for promoting responsible, trust-driven AI implementation in fraud detection. Full article
(This article belongs to the Special Issue Innovations in Accounting Practices)
►▼ Show Figures

Figure 1

18 pages, 260 KiB  
Article
Balancing Financial Risks with Social and Economic Benefits: Two Case Studies of Private Sector Water, Sanitation, and Hygiene Suppliers in Rural Vietnam
by Lien Pham
J. Risk Financial Manag. 2025, 18(4), 216; https://doi.org/10.3390/jrfm18040216 - 17 Apr 2025
Viewed by 152
Abstract
This paper examines the financial health risks that private sector water, sanitation, and hygiene (WASH) businesses in rural Vietnam face. It investigates the challenges faced by water operators and sanitation suppliers involved in donor-funded development projects aimed at supporting poor and vulnerable households. [...] Read more.
This paper examines the financial health risks that private sector water, sanitation, and hygiene (WASH) businesses in rural Vietnam face. It investigates the challenges faced by water operators and sanitation suppliers involved in donor-funded development projects aimed at supporting poor and vulnerable households. Through surveys and focus group discussions with 15 suppliers who worked in public–private partnerships, this research examines the financial risk factors affecting water and sanitation suppliers and their impact on financial viability through two case studies. For water operators, the risks primarily involve infrastructure management, operational costs, and revenue instability. In the sanitation sector, risks center around fluctuating material prices, limited business expansion capital, and household affordability. This study highlights the dual role of government and donor subsidies, which enhance service accessibility but potentially distort market dynamics. It also underscores the need for targeted financial and policy interventions, including better access to microfinance, regulatory improvements, and human resource development. The findings aim to inform strategies for government, donors, and private sector actors in similar WASH development contexts to enhance financial sustainability, ensuring inclusive WASH services in underserved areas. This paper contributes to policy discussions by proposing mechanisms to balance public–private collaboration while fostering market resilience and equitable access to WASH services in emerging economies similar to that of Vietnam. Full article
(This article belongs to the Special Issue Finance, Risk and Sustainable Development)
30 pages, 9138 KiB  
Article
Accuracy Comparison Between Feedforward Neural Network, Support Vector Machine and Boosting Ensembles for Financial Risk Evaluation
by Dat Tran and Allan W. Tham
J. Risk Financial Manag. 2025, 18(4), 215; https://doi.org/10.3390/jrfm18040215 - 15 Apr 2025
Viewed by 339
Abstract
Loan defaults have become an increasing concern for lending institutions, presenting significant challenges to profitability and operational stability. However, with the advent of advanced data processing capabilities, greater data availability, and the development of sophisticated machine learning techniques—particularly neural networks—new opportunities have emerged [...] Read more.
Loan defaults have become an increasing concern for lending institutions, presenting significant challenges to profitability and operational stability. However, with the advent of advanced data processing capabilities, greater data availability, and the development of sophisticated machine learning techniques—particularly neural networks—new opportunities have emerged for classifying and predicting loan defaults beyond traditional manual methods. This, in turn, can reduce risk and enhance overall financial performance. In recent years, institutions have increasingly employed these advanced techniques to mitigate the risk of non-performing loans (NPLs) by improving loan approval efficiency. This study aims to address a gap in the literature by examining the predictive performance of different neural network architectures on financial loan datasets. Specifically, it compares the effectiveness of Feedforward Neural Networks (FNNs), Long Short-Term Memory (LSTM) networks, and one-dimensional Convolutional Neural Networks (1D-CNNs) in forecasting loan defaults. Despite the growing body of research in this area, comparative studies focusing on the application of various neural network techniques to loan default prediction remain relatively scarce. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
►▼ Show Figures

Figure 1

26 pages, 1285 KiB  
Review
Financial and Administrative Management Models for Digital Ventures: A Literature Review
by Laura Constanza Gallego Cossio, Ludivia Hernández Aros, Darío Rodríguez Perdomo and Mario Samuel Rodríguez Barrero
J. Risk Financial Manag. 2025, 18(4), 214; https://doi.org/10.3390/jrfm18040214 - 15 Apr 2025
Viewed by 287
Abstract
Financial and administrative management models are crucial to the success of digital ventures, providing practices that optimize resource management and support strategic decision-making in dynamic digital environments. This study presents an original systematic literature review (SLR) following the PRISMA guidelines, analyzing 354 articles [...] Read more.
Financial and administrative management models are crucial to the success of digital ventures, providing practices that optimize resource management and support strategic decision-making in dynamic digital environments. This study presents an original systematic literature review (SLR) following the PRISMA guidelines, analyzing 354 articles extracted from Scopus and Web of Science databases. Bibliometric techniques, including VOSViewer 1.6.19 version and R-Bibliometrix software 4.3.3 version, were used to identify key research themes, emerging trends, and future directions in the field. A notable 114.29% increase in academic output from 2019 to 2024 underscores the growing importance of these management models. The analysis reveals a focus on financial management tools (e.g., Valuation, Discounted Cash Flow models) and administrative models (e.g., RocaSalvatella, INCIPY), while also exploring the challenges and opportunities present in digital environments. The interaction between external variables (resource management, operational efficiency, adaptability, financial planning, technological innovation) and internal variables (market conditions, government regulations, economic trends) is discussed. This study highlights the integration of agile methodologies, such as Lean Startup, and the growing emphasis on digital resilience, organizational agility, and the impact of digital transformation on business models. The theoretical contribution of this study lies in offering a comprehensive framework that synthesizes existing models, highlights key research gaps, and emphasizes the need for future studies on the dynamic interaction between financial planning, technological innovation, and organizational agility. From a practical perspective, the findings provide digital entrepreneurs and managers with valuable insights into implementing financial tools and administrative frameworks that enhance decision-making, while also underscoring the importance of agility, operational efficiency, and market adaptability to navigate digital disruptions. Full article
(This article belongs to the Section Business and Entrepreneurship)
►▼ Show Figures

Figure 1

19 pages, 337 KiB  
Article
The Moderating Role of Worldwide Governance Indicators on ESG–Firm Performance Relationship: Evidence from Europe
by Rezart Demiraj, Enida Demiraj and Suzan Dsouza
J. Risk Financial Manag. 2025, 18(4), 213; https://doi.org/10.3390/jrfm18040213 - 14 Apr 2025
Viewed by 307
Abstract
Engaging in Environmental, Social, and Governance (ESG) activities entails costs that influence a firm’s financial and market performance. However, it is expected that the long-term benefits of ESG engagement outweigh these costs, leading to superior performance. Despite extensive research on the ESG–performance relationship, [...] Read more.
Engaging in Environmental, Social, and Governance (ESG) activities entails costs that influence a firm’s financial and market performance. However, it is expected that the long-term benefits of ESG engagement outweigh these costs, leading to superior performance. Despite extensive research on the ESG–performance relationship, findings remain mixed. This study examines the moderating effect of country governance, measured by the Worldwide Governance Indicators (WGIs), on the relationship between firms’ ESG scores and their financial and market performance in the European context. Using a two-stage least squares (2SLS) regression model and a dataset spanning 12 years (2011–2022) for 2083 listed European firms, we find that WGI significantly moderates the ESG–performance relationship. Our results indicate that ESG engagement alone has a negative impact on financial performance (ROA), suggesting that the costs associated with ESG investments often outweigh their short-term benefits. However, strong governance structures mitigate these costs, transforming ESG investments into value-enhancing activities. Conversely, ESG engagement positively influences market performance (Tobin’s Q), signaling long-term value to investors. Yet, in jurisdictions with strong governance frameworks, this effect diminishes, as ESG compliance becomes a baseline expectation rather than a differentiating factor. Full article
(This article belongs to the Special Issue Finance, Risk and Sustainable Development)
27 pages, 1726 KiB  
Article
Fintechs and Institutions: Evidence from an Emerging Economy
by Diogo Campos-Teixeira, Jorge Tello-Gamarra, João Reis, André Andrade Longaray and Martin Hernani-Merino
J. Risk Financial Manag. 2025, 18(4), 212; https://doi.org/10.3390/jrfm18040212 - 14 Apr 2025
Viewed by 316
Abstract
Institutions play a vital role in restricting or encouraging the performance of any economic agent. In this context, fintechs represent a vector of exponential change in the global financial system and its institutions. However, despite the existing relationship between fintechs and institutions, there [...] Read more.
Institutions play a vital role in restricting or encouraging the performance of any economic agent. In this context, fintechs represent a vector of exponential change in the global financial system and its institutions. However, despite the existing relationship between fintechs and institutions, there is a need for more studies exploring the connections between them. Beginning with a framework that integrates aspects of the relation between fintechs and institutions in the financial system, the objective of this article is to empirically demonstrate the interaction between fintechs and financial system institutions in an emerging country. To do so, the chosen research method was an embedded case study, which involved documental analysis and semi-structured interviews conducted with different agents in the Brazilian financial system, belonging to the following categories: technology providers, fintechs, regulatory institutions, financial institutions, and consumers. The findings validate the applicability of the theoretical framework, highlighting that fintechs drive institutional changes across stakeholders with different characteristic traits. Based on these results, we created theoretical propositions that guide future studies on the topic of fintechs and institutions. This study’s contributions provide valuable insights for financial policymakers, regulators, and technology providers, particularly regarding the adaptation of regulatory frameworks and technological infrastructures in emerging economies. For policymakers, this study suggests guidelines to foster financial inclusion through fintech initiatives, while managers are encouraged to develop strategies that reduce operational gaps in digital financial services. Full article
(This article belongs to the Special Issue Fintech, Business, and Development)
►▼ Show Figures

Figure 1

22 pages, 349 KiB  
Article
Sustainable Banking and Bank Stability in Nigeria: Empirical Evidence from Deposit Money Banks
by Olusola Enitan Olowofela, Hermann Azemtsa Donfack and Celestin Wafo Soh
J. Risk Financial Manag. 2025, 18(4), 211; https://doi.org/10.3390/jrfm18040211 - 14 Apr 2025
Viewed by 236
Abstract
We investigated the impact of sustainable banking practices on bank stability in the Nigerian banking sector. We focused on data from 2012 to 2022, which were extracted from the balance sheets of deposit money banks in Nigeria. We employed the Dynamic Ordinary Least [...] Read more.
We investigated the impact of sustainable banking practices on bank stability in the Nigerian banking sector. We focused on data from 2012 to 2022, which were extracted from the balance sheets of deposit money banks in Nigeria. We employed the Dynamic Ordinary Least Squares (DOLS) estimator with E-Views to analyze the data. Our findings show that environmental emissions and waste reduction have minimal effects on bank assets, capital adequacy, and liquidity, though they do not directly cause financial instability. Investments in environmental innovation reduce asset growth and increase liquidity constraints but lower non-performing loans, emphasizing a trade-off between sustainability and stability. Environmental resource use efficiency remains neutral regarding asset stability and capital adequacy but poses liquidity challenges. Social welfare investments have little impact on asset growth and profitability, potentially reducing financial stability. Human resource development improves capital adequacy and liquidity strengthening bank stability, while community investments aid societal growth but create liquidity pressures. Macroeconomic factors like GDP growth and inflation are significant, yet economic growth does not always increase bank assets, whereas inflation increases non-performing loans. Sustainable banking in Nigeria is evolving; therefore, there is a need for robust regulation, financial incentives for compliance, a high level of awareness, and alignment between banking operations and sustainability principles. Full article
(This article belongs to the Section Banking and Finance)
23 pages, 380 KiB  
Article
Green Bond Yield Determinants in Indonesia: The Moderating Role of Bond Ratings
by Mutia Wahyuningsih, Wiwik Utami, Augustina Kurniasih and Endri Endri
J. Risk Financial Manag. 2025, 18(4), 210; https://doi.org/10.3390/jrfm18040210 - 13 Apr 2025
Viewed by 397
Abstract
This study investigates the relationship between bond-specific factors, macroeconomic variables, and green bond (GB) yields issued in the Indonesian bond market. The study sample includes 468 GBs issued by 30 issuers from both corporate and government entities from 2018 to 2023. This research [...] Read more.
This study investigates the relationship between bond-specific factors, macroeconomic variables, and green bond (GB) yields issued in the Indonesian bond market. The study sample includes 468 GBs issued by 30 issuers from both corporate and government entities from 2018 to 2023. This research method uses panel regression techniques with the random effects models to test hypotheses on two estimation model specifications. The study results reveal that interest, inflation, and exchange rates are significantly and positively related to GB yields. Bond-specific factors have different impacts, where coupons and maturity have a positive relationship with GB yields, while bond issuers have an adverse effect. Bond rating and issuance size as specific factors are shown to have no impact on GB yields. In the model with the moderating role of rating, the study’s results show that coupons still directly impact GB yields positively, while the influence of maturity is negative. The interaction of maturity and rating positively impacts GB yield. Different findings suggest that interactions with coupons weaken the impact of ratings on GB yields. The results of this study contribute to the financial literature on the determinants of the GB market and the role of bond ratings as a moderator. The study also provides new insights into Indonesia’s GB market, which includes developing countries. The findings can also help companies, investors, regulators, and researchers better understand the GB market. Full article
(This article belongs to the Special Issue Green Finance and Corporate Governance)
24 pages, 581 KiB  
Article
An Empirical Evaluation of the Technology Acceptance Model for Peer-to-Peer Insurance Adoption: Does Income Really Matter?
by Sylvester Senyo Horvey, Euphemia Godspower-Akpomiemie and Richard Asare Boateng
J. Risk Financial Manag. 2025, 18(4), 209; https://doi.org/10.3390/jrfm18040209 - 13 Apr 2025
Viewed by 275
Abstract
One essential component of insurance technology (Insurtech) is peer-to-peer (P2P) insurance, which represents a transformative shift from conventional insurance to digital platforms by fostering community-based risk sharing. This study contributes to the body of knowledge by engaging the Technology Acceptance Model (TAM2) to [...] Read more.
One essential component of insurance technology (Insurtech) is peer-to-peer (P2P) insurance, which represents a transformative shift from conventional insurance to digital platforms by fostering community-based risk sharing. This study contributes to the body of knowledge by engaging the Technology Acceptance Model (TAM2) to explore how perceived usefulness, perceived ease of use, subjective norms, and perceived trust influence the adoption of P2P insurance, and the moderating influence of income on these relationships. This study used a self-administered survey questionnaire to collect data from short-term insurance clients in South Africa. The survey was analysed using the confirmatory factor analysis and structural equation modelling (SEM) approach. The findings demonstrate that perceived usefulness, ease of use, and subjective norms present a significant positive influence on the adoption of P2P insurance, underscoring the relevance of value, ease of use, and social influence in predicting the adoption of insurance technologies, particularly P2P insurance. However, perceived risk and trust exhibit a positive but statistically insignificant relationship. Additionally, this study reveals that income exerts a significant positive moderating influence on perceived usefulness, ease of use, and subjective norms in affecting P2P adoption, implying that individuals with higher incomes are responsive to these factors when considering P2P insurance. This study highlights the need for policies that support the development of digital infrastructure, as its accessibility and ease of use, including social norms, are predicted as essential drivers of P2P insurance adoption. Also, policymakers should focus on creating a regulatory environment that encourages accountability and openness to P2P insurance. Full article
(This article belongs to the Special Issue InsurTech Development and Insurance Inclusion)
►▼ Show Figures

Figure 1

16 pages, 421 KiB  
Article
Cash Conversion Cycle and Profitability: Evidence from Greek Service Firms
by Angelos-Stavros Stavropoulos and Stella Zounta
J. Risk Financial Manag. 2025, 18(4), 208; https://doi.org/10.3390/jrfm18040208 - 13 Apr 2025
Viewed by 351
Abstract
The present study examines the relationship between the cash conversion cycle (CCC) and profitability in major service sectors in Greece, including hotels, education, healthcare, transfer—rentals, and information technology. Using financial data from 343 public limited companies for the year 2023, the research applies [...] Read more.
The present study examines the relationship between the cash conversion cycle (CCC) and profitability in major service sectors in Greece, including hotels, education, healthcare, transfer—rentals, and information technology. Using financial data from 343 public limited companies for the year 2023, the research applies descriptive statistics, Pearson correlation analysis, and ANOVA to evaluate how CCC components affect profitability, measured through return on assets (ROA). The results indicate that firms across all sectors maintain a negative CCC, suggesting efficient liquidity management, with the education sector exhibiting the most negative CCC due to upfront tuition payments. Additionally, the study finds a significant positive correlation between CCC and ROA, implying that firms with longer negative CCC values tend to achieve higher profitability. However, firm size, measured by total assets and sales, does not appear to influence CCC efficiency or profitability. These findings underscore the importance of industry-specific financial strategies and highlight the role of CCC optimization in enhancing financial performance. The study contributes to the literature on working capital management and provides practical implications for improving liquidity and profitability in service-oriented firms. Full article
(This article belongs to the Special Issue AI and Sustainable Growth in Economics and Finance: Global Trends and Challenges)
►▼ Show Figures

Figure 1

18 pages, 349 KiB  
Article
Fiscal Sustainability and the Informal Economy: A Non-Linear Perspective
by Dănuț Georgian Mihai, Bogdan Andrei Dumitrescu and Andreea-Mădălina Bozagiu
J. Risk Financial Manag. 2025, 18(4), 207; https://doi.org/10.3390/jrfm18040207 - 12 Apr 2025
Viewed by 224
Abstract
This study examines the issue of fiscal sustainability—measured through the response of the budgetary balance to public debt levels—for 36 OECD countries and candidate countries, and it shows that the relationship is non-linear and depends on the level of the informal economy as [...] Read more.
This study examines the issue of fiscal sustainability—measured through the response of the budgetary balance to public debt levels—for 36 OECD countries and candidate countries, and it shows that the relationship is non-linear and depends on the level of the informal economy as a threshold variable. Using the Panel Smooth Transition Regression model, the analysis uncovers regime-dependent fiscal behavior, indicating that the effect of public debt on the budget deficit varies significantly under different economic conditions. In regime 1—at a low level of the informal economy-, the impact of debt on the budgetary deficit is negative and significant, but in regime 2—when the informal economy exceeds the transition threshold-, this impact becomes positive and significant. These results indicate that, in an economic context with a larger informal economy, debt may have a different effect on the budgetary deficit, possibly due to factors such as reduced fiscal efficiency or loss of government revenue. Therefore, fiscal sustainability can be affected by the level of the informal economy. Full article
(This article belongs to the Special Issue Macroeconomic Dynamics and Economic Growth)
14 pages, 958 KiB  
Article
The Moderating Role of Auditor Experience on Determinants of Computer-Assisted Auditing Tools and Techniques
by Tasneem Alsarayrah and Basel J. A. Ali
J. Risk Financial Manag. 2025, 18(4), 206; https://doi.org/10.3390/jrfm18040206 - 11 Apr 2025
Viewed by 260
Abstract
This study indicates that internal auditors need to fully adopt CAATs to improve the efficiency of auditing tasks. This paper investigates the determinants influencing CAAT adoption among internal auditors in Jordanian firms. This study investigates the roles of performance expectancy, effort expectancy, social [...] Read more.
This study indicates that internal auditors need to fully adopt CAATs to improve the efficiency of auditing tasks. This paper investigates the determinants influencing CAAT adoption among internal auditors in Jordanian firms. This study investigates the roles of performance expectancy, effort expectancy, social influence, and facilitating conditions on the adoption of CAATs. Also, this study investigates the moderating variable of auditor experience. The data were collected using a survey that was sent to 420 internal auditors in auditing firms in Jordan. A total of 291 responses were collected, of which 279 proved to be valid for study. This study found that the adoption of CAATs is influenced by performance expectancy, facilitating conditions, social influence, and auditor experience. Conversely, effort expectancy has no influence. Furthermore, auditor experience moderates the relationship between performance expectancy and facilitating conditions for CAAT adoption. This study found that auditor experience does not moderate the relationship between effort expectancy or social influence and CAATs in auditing firms in Jordan. Full article
(This article belongs to the Special Issue The Future of Sustainable Finance: Digital and Circular Synergies)
►▼ Show Figures

Figure 1

24 pages, 349 KiB  
Article
Disclosure of Sustainability Practices in Annual Reports and the Funding Cost of Cooperative Financial Organizations
by Bruno de Medeiros Teixeira, Clea Beatriz Macagnan, Cenaide Francieli Justen and Israel Patiño-Galvan
J. Risk Financial Manag. 2025, 18(4), 205; https://doi.org/10.3390/jrfm18040205 - 10 Apr 2025
Viewed by 241
Abstract
This study aimed to analyze the level of disclosure of information representing sustainability practices from the stakeholders’ perspective and its relationship with the funding cost of cooperative financial organizations. The level of disclosure was measured using 46 information indicators representing sustainability practices from [...] Read more.
This study aimed to analyze the level of disclosure of information representing sustainability practices from the stakeholders’ perspective and its relationship with the funding cost of cooperative financial organizations. The level of disclosure was measured using 46 information indicators representing sustainability practices from the stakeholders’ perspective, identified in the annual reports of cooperative financial organizations (CFOs) listed in the World Cooperative Monitor 2023, totaling 155 observations. The relationship between disclosure and the cost of financing was analyzed using a random effects estimator with cluster-robust standard errors. The results demonstrate a negative relationship between the disclosure of sustainability practices and the funding cost. When disaggregated by sustainability pillar, the results show that disclosure in the social, environmental, and cultural pillars is negatively associated with funding cost, while the economic pillar shows no statistically significant effect. This suggests that disclosing sustainability-related information from the stakeholders’ perspective reduces the cost of funding and enhances the legitimacy of CFO managers, setting them apart from traditional banks. This study examines the relationship between sustainability disclosure and funding cost in CFOs by adapting validated indicators and applying a robust econometric approach. Unlike existing literature focused on traditional banks, it empirically investigates how sustainability disclosure affects information asymmetry, funding costs, and managerial legitimacy within the cooperative financial sector. Full article
(This article belongs to the Special Issue Sustainability Reporting and Corporate Governance)
28 pages, 1373 KiB  
Article
South African Government Bond Yields and the Specifications of Affine Term Structure Models
by Malefane Molibeli and Gary van Vuuren
J. Risk Financial Manag. 2025, 18(4), 204; https://doi.org/10.3390/jrfm18040204 - 9 Apr 2025
Viewed by 238
Abstract
This study adopts a three-factor approach to the affine term structure models, aiming to analyse South African (SA) government bond yields across various maturities. The primary objective is to evaluate whether these models offer robust pricing capabilities—being both admissible and flexible—while capturing the [...] Read more.
This study adopts a three-factor approach to the affine term structure models, aiming to analyse South African (SA) government bond yields across various maturities. The primary objective is to evaluate whether these models offer robust pricing capabilities—being both admissible and flexible—while capturing the conditional correlations and volatilities of yield factors specific to SA bond yields. For a model to be considered admissible, it must also demonstrate economic identification and maximal flexibility. We thus investigate the short-, medium-, and long-term dynamics of bond yields concurrently. Model estimation involves deriving joint conditional densities through the inversion of the Fourier transform applied to the characteristic function of the state variables. This enables the use of maximum likelihood estimation as an efficient method. We assume that the market prices of risk are proportional to the volatilities of the state variables. The analysis reveals negative correlations between factors. Among the models tested, the A1(3) model outperforms the A2(3) model in terms of fit, both in sample and out of sample. Full article
(This article belongs to the Special Issue Computational Finance and Financial Econometrics)
►▼ Show Figures

Figure 1

28 pages, 1606 KiB  
Article
Modelling Value-at-Risk and Expected Shortfall for a Small Capital Market: Do Fractionally Integrated Models and Regime Shifts Matter?
by Wafa Souffargi and Adel Boubaker
J. Risk Financial Manag. 2025, 18(4), 203; https://doi.org/10.3390/jrfm18040203 - 9 Apr 2025
Viewed by 297
Abstract
In this study, we examine the relevance of the coexistence of structural change and long memory to model and forecast the volatility of Tunisian stock returns and to deliver a more accurate measure of risk along the lines of VaR and expected shortfall. [...] Read more.
In this study, we examine the relevance of the coexistence of structural change and long memory to model and forecast the volatility of Tunisian stock returns and to deliver a more accurate measure of risk along the lines of VaR and expected shortfall. To this end, we propose three time-series models that incorporate long-term dependence on the level and volatility of returns. In addition, we introduce structural change points using the iterated cumulative sums of squares (ICSS) and the modified ICSS algorithms, synonymous with stock market turbulence, into the conditional variance equations of the models studied. We choose a conditional innovation density function other than the normal distribution, that is, a Student distribution, to account for excess kurtosis. The empirical results show that the inclusion of structural breakpoints in the conditional variance equation and Dual LM provides better short- and long-term predictability. Within such a framework, the ICSS-ARFIMA-HYGARCH model with Student’s t distribution was able to account for the long-term dependence in the level and volatility of TUNINDEX index returns, excess kurtosis, and structural changes, delivering an accurate estimator of VaR and expected shortfall. Full article
(This article belongs to the Special Issue Machine Learning Based Risk Management in Finance and Insurance)
►▼ Show Figures

Figure 1

19 pages, 638 KiB  
Article
The Influence of Board Diversity on Capital Structure Decisions: Examining Financial Risk Management Across Different Market Conditions in UK-Listed Firms
by Hanan Elmoursy, Mohammed Bouaddi, Mohamed A. K. Basuony, Nariman Kandil and Rehab EmadEldeen
J. Risk Financial Manag. 2025, 18(4), 202; https://doi.org/10.3390/jrfm18040202 - 8 Apr 2025
Viewed by 347
Abstract
This study examines how board diversity affects the capital structure decisions of United Kingdom (UK)-listed firms on the London Stock Exchange (LSE) under varying market conditions for the period from 2002 to 2021. Data were gathered from BoardEx, ORBIS, and DataStream databases. Linear [...] Read more.
This study examines how board diversity affects the capital structure decisions of United Kingdom (UK)-listed firms on the London Stock Exchange (LSE) under varying market conditions for the period from 2002 to 2021. Data were gathered from BoardEx, ORBIS, and DataStream databases. Linear regression and fixed-effect models were used, along with transition two- and three-regime regression models. The findings reveal that educational diversity consistently negatively affects capital structure across all market conditions. Gender diversity and board independence improve capital structure, except in extreme market states. However, age diversity negatively influences capital structure only in extremely bad market conditions, while board size positively impacts capital structure in good, moderate, and extremely good markets. Nationality diversity has no significant effect across all market conditions. These results align with pecking order, trade-off, and agency theories, emphasizing the need to balance debt and equity. This study highlights the importance of tailoring board composition to market conditions. Enhancing gender diversity and board independence can improve debt financing, especially in stable markets. Companies are encouraged to continually assess board diversity to align with shifting market dynamics for better capital structure decisions. Full article
(This article belongs to the Section Business and Entrepreneurship)
►▼ Show Figures

Figure 1

21 pages, 1745 KiB  
Article
Hybrid Machine Learning Models for Long-Term Stock Market Forecasting: Integrating Technical Indicators
by Francis Magloire Peujio Fozap
J. Risk Financial Manag. 2025, 18(4), 201; https://doi.org/10.3390/jrfm18040201 - 8 Apr 2025
Viewed by 645
Abstract
Stock market forecasting is a critical area in financial research, yet the inherent volatility and non-linearity of financial markets pose significant challenges for traditional predictive models. This study proposes a hybrid deep learning model, integrating Long Short-Term Memory (LSTM) networks and Convolutional Neural [...] Read more.
Stock market forecasting is a critical area in financial research, yet the inherent volatility and non-linearity of financial markets pose significant challenges for traditional predictive models. This study proposes a hybrid deep learning model, integrating Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) with technical indicators to enhance the predictive accuracy of stock price movements. The model is evaluated using Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and R2 score on the S&P 500 index over a 14-year period. Results indicate that the LSTM-CNN hybrid model achieves superior predictive performance compared to traditional models, including Support Vector Machines (SVMs), Random Forest (RF), and ARIMAs, by effectively capturing both long-term trends and short-term fluctuations. While Random Forest demonstrated the highest raw accuracy with the lowest RMSE (0.0859) and highest R2 (0.5655), it lacked sequential learning capabilities. The LSTM-CNN model, with an RMSE of 0.1012, MAE of 0.0800, MAPE of 10.22%, and R2 score of 0.4199, proved to be highly competitive and robust in financial time series forecasting. The study highlights the effectiveness of hybrid deep learning architectures in financial forecasting and suggests further enhancements through macroeconomic indicators, sentiment analysis, and reinforcement learning for dynamic market adaptation. It also improves risk-aware decision-making frameworks in volatile financial markets. Full article
(This article belongs to the Special Issue Risk Management in Capital Markets)
►▼ Show Figures

Figure 1

21 pages, 1145 KiB  
Article
The Role of Project Description in the Success of Sustainable Crowdfunding Projects
by Li-Yun Yin, Fleur C. Khalil, Lionel J. Khalil and Jeanne A. Kaspard
J. Risk Financial Manag. 2025, 18(4), 200; https://doi.org/10.3390/jrfm18040200 - 7 Apr 2025
Viewed by 337
Abstract
Crowdfunding nowadays has become a significant source of financing for all those entrepreneurs who require funds to start their operations, specifically for social ventures. Furthermore, determining what factors decide whether a project will successfully raise funds is a very relevant question. Past literature [...] Read more.
Crowdfunding nowadays has become a significant source of financing for all those entrepreneurs who require funds to start their operations, specifically for social ventures. Furthermore, determining what factors decide whether a project will successfully raise funds is a very relevant question. Past literature has examined various factors that influence fundraising success. Of these factors, information efficiency is the determinant of successful fundraising due to precise project descriptions and effective message delivery. Despite this fact, few studies have investigated how such project descriptions affect the success of crowdfunding campaigns, specifically sustainable projects. The present study tries to fill this gap by examining the relation between the length and readability of the crowdfunding project descriptions and the success rate for sustainable projects in a reward-based model. For the analysis, data were obtained from Kickstarter, the largest crowdfunding platform in the world, with a sample of 12,613 projects, employing a multiple logistic regression model. The results show that the word count and readability of the project descriptions are positively related to crowdfunding success. Furthermore, the analysis shows that using more words related to SDG keywords results in positive fundraising. Such insights reflect that good project descriptions are important for crowdfunding success and, on the theoretical level, provide practical value for project owners. Full article
(This article belongs to the Special Issue Financial Technology (Fintech) and Sustainable Financing, 3rd Edition)
►▼ Show Figures

Figure 1

18 pages, 990 KiB  
Article
Determinants of SME Internationalisation: An Empirical Assessment of Born Global Firms
by Syed Khusro Chishty, Sonia Sayari, Amani Hamza Mohamed, Asra Inkesar, Mohammed Faishal Mallick and Nusrat Khan
J. Risk Financial Manag. 2025, 18(4), 199; https://doi.org/10.3390/jrfm18040199 - 7 Apr 2025
Viewed by 380
Abstract
The research concentrates on determining the degree of internationalization of born global SMEs, believing that some push factors determine internationalization, pull factors, and internal firm-specific factors. Three important factors were found in looking into the causes of internationalization in born global firms: push, [...] Read more.
The research concentrates on determining the degree of internationalization of born global SMEs, believing that some push factors determine internationalization, pull factors, and internal firm-specific factors. Three important factors were found in looking into the causes of internationalization in born global firms: push, pull, and internal firm-specific factors. The study used a survey instrument with a sample of 280 manufacturing-related SMEs chosen from manufacturing clusters in India. A metric called the “index of internationalization” is used to gauge how internationalization in SMEs takes shape. The results demonstrated that internal firm-specific factors influence the internationalization of firms relatively highly compared to push and pull factors. The results unequivocally demonstrate that developing economies have distinct factors that cause internationalization, opening up new avenues for further study. The research aids in the identification of the elements that will enhance early internationalization and tries to draw the attention of young entrepreneurs. This research also helps prioritize the factors responsible for early internationalization. These findings are pertinent for the practitioners and researchers working in this area. This research is helpful for start-ups looking for global opportunities; this research categorizes factors significant in the global journey of the born global firms. Full article
(This article belongs to the Special Issue Entrepreneurship in Emerging Economies)
►▼ Show Figures

Figure 1

15 pages, 299 KiB  
Article
Risk Management Practices and Financial Performance: Analysing Credit and Liquidity Risk Management and Disclosures by Nigerian Banks
by Omobolade Stephen Ogundele and Lethiwe Nzama
J. Risk Financial Manag. 2025, 18(4), 198; https://doi.org/10.3390/jrfm18040198 - 4 Apr 2025
Viewed by 567
Abstract
Nigerian banks encounter persistent difficulties in efficiently managing and disclosing credit and liquidity risks, considerably affecting their financial performance and shareholders’ confidence. This study, therefore, examined the effect of risk-management practices and disclosures on the financial performance of Nigerian commercial banks. The population [...] Read more.
Nigerian banks encounter persistent difficulties in efficiently managing and disclosing credit and liquidity risks, considerably affecting their financial performance and shareholders’ confidence. This study, therefore, examined the effect of risk-management practices and disclosures on the financial performance of Nigerian commercial banks. The population of the study comprised 13 Nigerian commercial banks, of which 12 were purposively chosen, subject to data availability. The data explored in this study originate from World Development Indicators and the annual reports and accounts of the selected Nigerian commercial banks from 2012 to 2023. The data analysis technique used was panel regression analysis, which was further extended to the generalized method of moments in a bid to account for potential endogeneity. The study made use of EViews 12 software to analyse the data. The results reveal that liquidity risk disclosure and firm size had significant and positive effects on financial performance, while credit risk disclosure, credit risk, firm age, and leverage had significant and negative effects. This study concludes that credit risks significantly undermine commercial banks’ financial performance, as an upsurge in non-performing loans results in reduced financial performance. Conversely, effective liquidity risk disclosure characterized by transparent reporting on liquidity position was found to enhance financial performance. This study, therefore, recommends, among others, that banks should strengthen their credit risk assessment framework and enhance transparent risk reporting to improve performance and financial stability. Full article
(This article belongs to the Special Issue Financial Management)
31 pages, 1781 KiB  
Article
A Majority Voting Mechanism-Based Ensemble Learning Approach for Financial Distress Prediction in Indian Automobile Industry
by Manoranjitham Muniappan and Nithya Darisini Paruvachi Subramanian
J. Risk Financial Manag. 2025, 18(4), 197; https://doi.org/10.3390/jrfm18040197 - 4 Apr 2025
Viewed by 374
Abstract
Financial distress poses a significant risk to companies worldwide, irrespective of their nature or size. It refers to a situation where a company is unable to meet its financial obligations on time, potentially leading to bankruptcy and liquidation. Predicting distress has become a [...] Read more.
Financial distress poses a significant risk to companies worldwide, irrespective of their nature or size. It refers to a situation where a company is unable to meet its financial obligations on time, potentially leading to bankruptcy and liquidation. Predicting distress has become a crucial application in business classification, employing both Statistical approaches and Artificial Intelligence techniques. Researchers often compare the prediction performance of different techniques on specific datasets, but no consistent results exist to establish one model as superior to others. Each technique has its own advantages and drawbacks, depending on the dataset. Recent studies suggest that combining multiple classifiers can significantly enhance prediction performance. However, such ensemble methods inherit both the strengths and weaknesses of the constituent classifiers. This study focuses on analyzing and comparing the financial status of Indian automobile manufacturing companies. Data from a sample of 100 automobile companies between 2013 and 2019 were used. A novel Firm-Feature-Wise three-step missing value imputation algorithm was implemented to handle missing financial data effectively. This study evaluates the performance of 11 individual baseline classifiers and all the 11 baseline algorithm’s combinations by using ensemble method. A manual ranking-based approach was used to evaluate the performance of 2047 models. The results of each combination are inputted to hard majority voting mechanism algorithm for predicting a company’s financial distress. Eleven baseline models are trained and assessed, with Gradient Boosting exhibiting the highest accuracy. Hyperparameter tuning is then applied to enhance individual baseline classifier performance. The majority voting mechanism with hyperparameter-tuned baseline classifiers achieve high accuracy. The robustness of the model is tested through k-fold Cross-Validation, demonstrating its generalizability. After fine-tuning the hyperparameters, the experimental investigation yielded an accuracy of 99.52%, surpassing the performance of previous studies. Furthermore, it results in the absence of Type-I errors. Full article
(This article belongs to the Special Issue Machine Learning Applications in Finance, 2nd Edition)
►▼ Show Figures

Figure 1

22 pages, 727 KiB  
Article
The Role of Digital Transformation Capabilities in Improving Banking Performance in Jordanian Commercial Banks
by Ehsan Ali Alqararah, Maha Shehadeh and Hadeel Yaseen
J. Risk Financial Manag. 2025, 18(4), 196; https://doi.org/10.3390/jrfm18040196 - 4 Apr 2025
Viewed by 590
Abstract
In today’s competitive business environment, digital transformation is crucial for organizational success. The Jordanian banking sector faces the challenges of adapting to rapid digital advancements, evolving customer expectations, and intense competition. This study investigated the impact of digital transformation capabilities—technological adaptation, strategic positioning, [...] Read more.
In today’s competitive business environment, digital transformation is crucial for organizational success. The Jordanian banking sector faces the challenges of adapting to rapid digital advancements, evolving customer expectations, and intense competition. This study investigated the impact of digital transformation capabilities—technological adaptation, strategic positioning, and competitive positioning—on perceived performance among 129 bank managers from 16 Jordanian commercial banks. Data were collected via a web-based survey that included a 29-item perceptual scale using a 5-point Likert scale. Multiple linear regression analysis revealed a significant positive relationship between these capabilities and perceived performance, explaining 68% of the variance. Specifically, technological adaptation (β = 0.310), strategic positioning (β = 0.260), and competitive positioning (β = 0.360) all significantly predicted perceived performance. Harman’s single-factor test indicated minimal common method bias, and strong positive correlations were found among all study variables. This research underscores the importance of a holistic digital transformation strategy for Jordanian banks, emphasizing the need for strategic investments in technology, competitive differentiation, and alignment with business objectives. Future research should explore additional factors such as organizational culture and regulatory frameworks and incorporate objective performance measures to provide a more comprehensive understanding of the impact of digital transformation. This study offers valuable insights for practitioners, policymakers, and researchers seeking to navigate digital disruption and foster business growth. Full article
(This article belongs to the Section Financial Technology and Innovation)
►▼ Show Figures

Figure 1

16 pages, 2180 KiB  
Article
A Multi-Stage Financial Distress Early Warning System: Analyzing Corporate Insolvency with Random Forest
by Katsuyuki Tanaka, Takuo Higashide, Takuji Kinkyo and Shigeyuki Hamori
J. Risk Financial Manag. 2025, 18(4), 195; https://doi.org/10.3390/jrfm18040195 - 4 Apr 2025
Viewed by 424
Abstract
As corporate sector stability is crucial for economic resilience and growth, machine learning has become a widely used tool for constructing early warning systems (EWS) to detect financial vulnerabilities more accurately. While most existing EWS research focuses on bankruptcy prediction models, bankruptcy signals [...] Read more.
As corporate sector stability is crucial for economic resilience and growth, machine learning has become a widely used tool for constructing early warning systems (EWS) to detect financial vulnerabilities more accurately. While most existing EWS research focuses on bankruptcy prediction models, bankruptcy signals often emerge too late and provide limited early-stage insights. This study employs a random forest approach to systematically examine whether a company’s insolvency status can serve as an effective multi-stage financial distress EWS. Additionally, we analyze how the financial characteristics of insolvent companies differ from those of active and bankrupt firms. Our empirical findings indicate that highly accurate insolvency models can be developed to detect status transitions from active to insolvent and from insolvent to bankrupt. Furthermore, our analysis reveals that the financial determinants of these transitions differ significantly. The shift from active to insolvent is primarily driven by structural and operational ratios, whereas the transition from insolvent to bankrupt is largely influenced by further financial distress in operational and profitability ratios. Full article
(This article belongs to the Special Issue The Role of Digitization in Corporate Finance)
►▼ Show Figures

Figure 1

23 pages, 352 KiB  
Article
Unmasking Delistings: A Multifactorial Analysis of Financial, Non-Financial, and Macroeconomic Variables
by Peter Lansdell, Ilse Botha and Ben Marx
J. Risk Financial Manag. 2025, 18(4), 194; https://doi.org/10.3390/jrfm18040194 - 4 Apr 2025
Viewed by 388
Abstract
The stability of financial markets is influenced by the strength and transparency of companies listed on stock exchanges. This paper explores how financial, non-financial, and macroeconomic factors influence delisting likelihood among companies listed on the Johannesburg Stock Exchange (JSE), addressing a limitation in [...] Read more.
The stability of financial markets is influenced by the strength and transparency of companies listed on stock exchanges. This paper explores how financial, non-financial, and macroeconomic factors influence delisting likelihood among companies listed on the Johannesburg Stock Exchange (JSE), addressing a limitation in the current body of knowledge that often overlooks the combination of these factors, especially within the context of developing economies. Using a sample of 302 companies delisted between 2010 and 2023 and 302 as a control group, we analyzed 72 variables through a multivariate panel probit regression model. Our findings reveal that delisting decisions are driven by a complex interplay of financial health, governance practices, and macroeconomic conditions. Financial health, including liquidity and market valuation, is crucial in mitigating delisting risk. Non-financial factors, such as corporate governance and shareholder composition, further reduce the likelihood of delisting. Macroeconomic conditions, including inflation and interest rates, introduce significant external pressures. This study is especially relevant in developing economies like South Africa, where economic volatility adds risks for listed companies. The results provide insights for companies, investors, regulators, and policymakers to ensure a stable and robust stock market and financial system and identify early warning signals for delisting. Full article
(This article belongs to the Section Applied Economics and Finance)
20 pages, 976 KiB  
Article
Application of a Slack-Based DEA Approach to Measure Efficiency in Public Sector Banks in India with Non-Performing Assets as an Undesirable Output
by Hitesh Arora, Ram Pratap Sinha, Padmasai Arora and Sonika Sharma
J. Risk Financial Manag. 2025, 18(4), 193; https://doi.org/10.3390/jrfm18040193 - 2 Apr 2025
Viewed by 290
Abstract
Ignoring the presence of non-performing assets makes efficiency measurement inappropriate and incomplete. Thus, the present study considers non-performing assets as an undesirable output and applies the slack-based efficiency model to measure the efficiency of public sector banks in India during 2004–2005 to 2018–2019. [...] Read more.
Ignoring the presence of non-performing assets makes efficiency measurement inappropriate and incomplete. Thus, the present study considers non-performing assets as an undesirable output and applies the slack-based efficiency model to measure the efficiency of public sector banks in India during 2004–2005 to 2018–2019. A two-metric performance assessment of sample banks is carried out using mean efficiency and the non-performing assets management ratio. This study is extended to investigate determinants of bank efficiency using a fixed effects model and dynamic panel data regression on the contextual variables. Results show that profitability as measured by return on equity (ROE) and priority sector exposure have had no impact on efficiency. However, cost of deposits and capital adequacy ratio have a significant negative impact on the efficiency of public sector banks in India. Most importantly, the study finds a decline in efficiency in recent years, indicating a necessity of serious efforts for revamping these state-owned banks. Full article
(This article belongs to the Special Issue Post SVB Banking Sector Outlook)
►▼ Show Figures

Figure 1

32 pages, 12006 KiB  
Article
Hedging via Perpetual Derivatives: Trinomial Option Pricing and Implied Parameter Surface Analysis
by Jagdish Gnawali, W. Brent Lindquist and Svetlozar T. Rachev
J. Risk Financial Manag. 2025, 18(4), 192; https://doi.org/10.3390/jrfm18040192 - 2 Apr 2025
Viewed by 285
Abstract
We introduce a fairly general, recombining trinomial tree model in the natural world. Market completeness is ensured by considering a market consisting of two risky assets, a riskless asset and a European option. The two risky assets consist of a stock and a [...] Read more.
We introduce a fairly general, recombining trinomial tree model in the natural world. Market completeness is ensured by considering a market consisting of two risky assets, a riskless asset and a European option. The two risky assets consist of a stock and a perpetual derivative of that stock. The option has the stock and its derivative as its underlying. Using a replicating portfolio, we develop prices for European options and generate the unique relationships between the risk-neutral and real-world parameters of the model. We discuss calibration of the model to empirical data in the cases in which the risky asset returns are treated as either arithmetic or logarithmic. From historical price and call option data for select large cap stocks, we develop implied parameter surfaces for the real-world parameters in the model. Full article
(This article belongs to the Special Issue Financial Innovations and Derivatives)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-54
Previous Issue
Next Issue
Back to TopTop