Journal of Risk and Financial Management

23 pages, 598 KB

Open AccessArticle

The Correlation Between Income Inequality and per Capita GDP in Georgia’s Counties

by Jonathan E. Leightner, Kacey Axon and Simon Medcalfe

J. Risk Financial Manag. 2026, 19(3), 234; https://doi.org/10.3390/jrfm19030234 - 23 Mar 2026

Viewed by 301

We use Reiterative Truncated Projected Least Squares (RTPLS) to estimate the correlation between real GDP per capita and income inequality for the 159 counties in Georgia, USA, from 2011 to 2021. RTPLS produces a separate slope estimate for every observation (data point), where [...] Read more.

We use Reiterative Truncated Projected Least Squares (RTPLS) to estimate the correlation between real GDP per capita and income inequality for the 159 counties in Georgia, USA, from 2011 to 2021. RTPLS produces a separate slope estimate for every observation (data point), where differences in these slope estimates are due to omitted variables. Our measure of inequality is the ratio of household income at the 80th percentile divided by income at the 20th percentile. We find that the negative marginal correlation between income inequality and real per capita income has strengthened over time, and there are large differences between the effects for different counties. For example, in 2021, our estimate for d(real per capita GDP)/d(income inequality) ranged from −3.70 to −28.48. We find that this estimate becomes more negative when there are increases in the percentage of the county population with some college education, the percentage of the county population that is Black, the percentage of the county population that is Hispanic, as well as when unemployment increases. However, d(real percapita GDP)/d(income inequality) becomes less negative as the percentage of the county that is rural increases and as the percentage of the population that is less than 18 years old increases. Full article

(This article belongs to the Special Issue Recent Developments in Finance and Economic Growth)

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17 pages, 1133 KB

Open AccessArticle

Does Political Proximity Enhance Business Cycle Synchronization in the G7?

by Lotfi Ben Jedidia and Imed Medhioub

J. Risk Financial Manag. 2026, 19(3), 233; https://doi.org/10.3390/jrfm19030233 - 20 Mar 2026

Viewed by 327

Abstract

This paper aims to assess the main drivers influencing business cycle synchronization within the G7 countries. In addition to key elements such as the intensity of bilateral trade and the influence of financial linkages on synchronization; we introduce a new variable that represents [...] Read more.

This paper aims to assess the main drivers influencing business cycle synchronization within the G7 countries. In addition to key elements such as the intensity of bilateral trade and the influence of financial linkages on synchronization; we introduce a new variable that represents the political alignment, which can substantially impact synchronization. In this study, we utilize the variable political distance as a proxy for political alignment, alongside traditional measures of trade intensity, and financial metrics, to examine their effects on business cycle synchronization within the G7. By considering annual data for the period 2013–2023, our findings reveal a positive and significant relationship between trade intensity and financial linkages and synchronization, while political distance exerts a negative and significant impact on synchronization. Consequently, in addition to trade intensity and financial linkages, it is essential for policymakers to take political alignment with their partners into account, even when trade volumes are similar. Full article

(This article belongs to the Section Economics and Finance)

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29 pages, 612 KB

Open AccessSystematic Review

From Cash to Digital Wallets: A PRISMA-Based Systematic Review of Microentrepreneur Adoption in Asia and Latin America

by Luz Maribel Vásquez-Vásquez, Elena Jesús Alvarado-Cáceres, Jose Antonio Caicedo-Mendoza and Víctor Hugo Fernández-Bedoya

J. Risk Financial Manag. 2026, 19(3), 232; https://doi.org/10.3390/jrfm19030232 - 20 Mar 2026

Viewed by 379

Abstract

The transition from cash-based transactions to digital wallet usage represents a structural change in the business practices of micro and small enterprises (MSEs) in emerging economies. This study aims to synthesize scientific evidence on digital wallet adoption among microentrepreneurs, analyze the geographical distribution [...] Read more.

The transition from cash-based transactions to digital wallet usage represents a structural change in the business practices of micro and small enterprises (MSEs) in emerging economies. This study aims to synthesize scientific evidence on digital wallet adoption among microentrepreneurs, analyze the geographical distribution of research, and consolidate key empirical findings, with a specific focus on Asia and Latin America. These regions are of particular interest because they share high levels of economic informality, strong reliance on cash-based transactions, and rapid expansion of digital financial technologies, while also facing institutional, regulatory, and infrastructural constraints that shape technology adoption among microentrepreneurs. A systematic review was conducted following the PRISMA 2020 guidelines. Searches were performed in the Scopus and Web of Science databases, including open access empirical studies published between 2021 and 2025 in English or Spanish. After applying predefined eligibility criteria and removing duplicates, 39 studies were included in the final analysis. The results indicate that most publications originate from Asian countries, particularly India, Indonesia, Malaysia, and Vietnam, whereas Latin America is mainly represented by Colombia and Peru. Across both regions, digital wallet adoption is consistently influenced by trust, perceived security, perceived usefulness, and ease of use, while perceived risk and institutional weaknesses emerge as contextual barriers. Although several primary studies adopt a consumer-level analytical perspective, their findings are extrapolated to microentrepreneur contexts by emphasizing transaction-related behaviors directly linked to business operations. This review acknowledges that the predominance of consumer-focused evidence represents a limitation when interpreting firm-level outcomes. Overall, the findings suggest that digital wallet adoption among microentrepreneurs is a socio-technical process shaped by behavioral, institutional, and regulatory factors rather than technology alone. Full article

(This article belongs to the Special Issue The Future of Money: Central Bank Digital Currencies, Cryptocurrencies and Stablecoins, 2nd Edition)

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17 pages, 1087 KB

Open AccessArticle

Interest Rate Parity Deviations, Excess Returns, and Exchange Rates: Evidence from the Yen–Dollar Exchange Rate

by Gab-Je Jo

J. Risk Financial Manag. 2026, 19(3), 231; https://doi.org/10.3390/jrfm19030231 - 19 Mar 2026

Viewed by 409

Abstract

This study investigates the forward discount puzzle by examining the dynamic relationships among excess returns arising from interest rate parity deviations, interest rate differentials, and the USD/JPY exchange rate. The empirical analysis employs correlation analysis, the Autoregressive Distributed Lag (ARDL) cointegration test, and [...] Read more.

This study investigates the forward discount puzzle by examining the dynamic relationships among excess returns arising from interest rate parity deviations, interest rate differentials, and the USD/JPY exchange rate. The empirical analysis employs correlation analysis, the Autoregressive Distributed Lag (ARDL) cointegration test, and variance decomposition together with impulse response functions derived from a Toda–Yamamoto augmented Vector Autoregressive (VAR) model, using data spanning January 2001 to September 2025. The correlation results indicate that the spot exchange rate is negatively related to both the swap rate and the interest rate differential. Impulse response analysis shows that the USD/JPY rate responds positively to swap rate shocks in the medium to long run, while responding negatively to interest rate differential shocks in the short run. Variance decomposition results are consistent with the impulse response analysis and underscore the dominant bilateral linkage between the exchange rate and the swap rate. The long-run ARDL estimates further reveal that the swap rate is positively associated with dollar appreciation, whereas both the interest rate differential and relative output are negatively related. Overall, although short-run arbitrage appears temporarily, the cointegration and dynamic results provide robust evidence that the forward discount puzzle persists for a substantial period rather than interest rate parity holding. Full article

(This article belongs to the Section Applied Economics and Finance)

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36 pages, 3324 KB

Open AccessArticle

Rand, Rates, and Returns: Unravelling the Volatility Nexus in South Africa’s Financial Markets

by Kazeem Abimbola Sanusi and Zandri Dickason-Koekemoer

J. Risk Financial Manag. 2026, 19(3), 230; https://doi.org/10.3390/jrfm19030230 - 19 Mar 2026

Viewed by 489

Abstract

This study investigates the volatility nexus between exchange rates, interest rates, and stock market returns in South Africa, an emerging economy characterised by deep financial integration and exposure to global capital flows. Using monthly data from January 2003 to February 2025, the analysis [...] Read more.

This study investigates the volatility nexus between exchange rates, interest rates, and stock market returns in South Africa, an emerging economy characterised by deep financial integration and exposure to global capital flows. Using monthly data from January 2003 to February 2025, the analysis employs a multi-layered econometric framework combining asymmetric GARCH models (EGARCH and GJR-GARCH), an Asymmetric Dynamic Conditional Correlation (ADCC-GARCH) specification, and a GARCH-MIDAS–DCC approach that decomposes volatility into long-run and short-run components while modelling time-varying cross-market dependence. The findings indicate that exchange rate volatility is the dominant and most persistent driver of financial market risk, highlighting the central role of the South African rand in transmitting global shocks to domestic markets. Equity market volatility is largely shock driven and mean reverting, with sharp increases during major crisis episodes such as the Global Financial Crisis and the COVID-19 pandemic. Dynamic correlations across markets are persistent but predominantly negative between stock returns and exchange rates, while linkages involving interest rates are weaker and more episodic. Overall, the results suggest that South Africa’s financial volatility nexus operates primarily through exchange rate-driven transmission rather than short-run contagion effects. Full article

(This article belongs to the Section Financial Markets)

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29 pages, 2045 KB

Open AccessArticle

Artificial Intelligence (AI) Adoption and Enterprise Risk Management (ERM): The Roles of Information Technology (IT) Infrastructure Flexibility, Technology Competence, and Organizational Culture in Ghana

by Kumah Takyi Kwasi Godson and Syed Ahmed Salman

J. Risk Financial Manag. 2026, 19(3), 229; https://doi.org/10.3390/jrfm19030229 - 19 Mar 2026

Viewed by 585

Abstract

Artificial Intelligence (AI) is transforming audit practice by redefining traditional frameworks and enabling the automation of data analysis, risk assessment, substantive testing, and continuous monitoring. This study investigates the effect of AI adoption by audit firms on enterprise risk management (ERM). It further [...] Read more.

Artificial Intelligence (AI) is transforming audit practice by redefining traditional frameworks and enabling the automation of data analysis, risk assessment, substantive testing, and continuous monitoring. This study investigates the effect of AI adoption by audit firms on enterprise risk management (ERM). It further assesses the mediating role of Information Technology (IT) infrastructure flexibility and the moderating roles of technology competencies and organizational culture in this relationship. Data were collected from 355 top managers in Ghana using a judgmental sampling technique based on predefined inclusion and exclusion criteria. The analysis was conducted using Partial Least Squares Structural Equation Modelling (PLS-SEM) with SmartPLS 4.1.1.7. The findings indicate that AI adoption positively and significantly influences ERM and IT infrastructure flexibility. IT infrastructure flexibility also has a positive effect on ERM and partially mediates the relationship between AI adoption and ERM. In addition, technology competencies significantly strengthen the relationship between AI adoption and ERM. Organizational culture positively moderates the relationship between IT infrastructure flexibility and ERM. These insights underscore the need for strategic alignment between AI investments and organizational capabilities. The study contributes to the limited empirical literature on AI-driven ERM in emerging economies and offers insights for policymakers and regulators seeking to promote technology-aided ERM. Full article

(This article belongs to the Section Risk)

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47 pages, 5103 KB

Open AccessReview

Financial-Market Forecasting and Modelling from Econometrics to AI: An Integrated Systematic and Bibliometric Review with Content Synthesis (1990–2024)

by Ahmed S. Wafi, Sherif El-Halaby and Hussien Ahmed

J. Risk Financial Manag. 2026, 19(3), 228; https://doi.org/10.3390/jrfm19030228 - 19 Mar 2026

Viewed by 702

Abstract

This study offers a comprehensive assessment of financial market modeling through a PRISMA-based systematic review, bibliometric analysis, and content synthesis. We examined 67 review articles (1990–2024) from Web of Science to build a conceptual framework, and 4982 articles (1990–2024) were analyzed with Biblioshiny. [...] Read more.

This study offers a comprehensive assessment of financial market modeling through a PRISMA-based systematic review, bibliometric analysis, and content synthesis. We examined 67 review articles (1990–2024) from Web of Science to build a conceptual framework, and 4982 articles (1990–2024) were analyzed with Biblioshiny. Five main clusters emerge: AI and deep learning for prediction; hybrid models that combine traditional and computational approaches; theoretical foundations, including the Efficient Market Hypothesis and critiques; high-frequency prediction and volatility analysis; and modeling of cryptocurrencies and digital assets. Temporal patterns show a shift from traditional econometrics to hybrid and deep learning methods, heightened attention to uncertainty and volatility during crises, rapid growth in crypto-focused modeling, and increased use of sentiment/news data after 2017. The content analysis highlights key gaps and future directions: standardized open benchmarks and reproducible frameworks; regime-sensitive validation; interpretable hybrid models that merge econometric structure with machine-learning flexibility; and wider applicability across assets, markets, and data types. The study provides a structured guide to intellectual and applied modeling, supporting future advances in forecasting, risk management, and policy design. Full article

(This article belongs to the Section Financial Markets)

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18 pages, 1996 KB

Open AccessArticle

Asymmetric Risk–Return Dynamics of Sustainable Portfolios: A Regime-Switching Analysis on Borsa Istanbul

by Turgay Yavuzarslan, Selman Aslan and Bülent Çelebi

J. Risk Financial Manag. 2026, 19(3), 227; https://doi.org/10.3390/jrfm19030227 - 18 Mar 2026

Viewed by 364

Abstract

(1) Background: In integrated financial markets where traditional diversification often fails, analyzing sustainability-oriented investments under non-linear dynamics is critical to averting erroneous decisions. This study investigates whether corporate sustainability provides effective downside mitigation against volatility in emerging markets, using Borsa Istanbul as a [...] Read more.

(1) Background: In integrated financial markets where traditional diversification often fails, analyzing sustainability-oriented investments under non-linear dynamics is critical to averting erroneous decisions. This study investigates whether corporate sustainability provides effective downside mitigation against volatility in emerging markets, using Borsa Istanbul as a case study. (2) Methods: The analysis employs US Dollar-denominated excess returns of an equal-weighted portfolio from the longest-tenured BIST Sustainability Index constituents versus the broader BIST 100 Index (2014–2025), utilizing Markov Regime Switching (MS-AR) and Regime-Switching CAPM methodologies to model non-linear dynamics. (3) Results: Empirical results reveal two distinct regimes, where market variance surges approximately 8.5-fold during crises. The sustainable portfolio exhibits a low systematic risk sensitivity (Beta: 0.76) in normal conditions, driven by its distinct structural composition without generating statistically significant Alpha. In crisis regimes, despite increased sensitivity (Beta: 0.90), the portfolio remains resilient with a beta strictly below 1.00. While BIST 100 investors suffered a massive 40.86% USD wealth erosion over the full period, the sustainability portfolio significantly mitigated this damage, limiting the total capital loss to 20.73% due to substantial compounding accumulated during normal regimes. (4) Conclusions: Consequently, sustainability proves to be not merely an ethical preference but a rational financial strategy offering diversification benefits in tranquility and acting as an effective partial hedge during turbulence in high-volatility markets. Full article

(This article belongs to the Special Issue Evaluating Risk and Return in Modern Financial Markets)

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18 pages, 270 KB

Open AccessArticle

Methodology for Quantitative Risk Assessment in the Integration and Use of ERP Systems in Enterprises

by Kiril Luchkov and Nadya Velinova-Sokolova

J. Risk Financial Manag. 2026, 19(3), 226; https://doi.org/10.3390/jrfm19030226 - 18 Mar 2026

Viewed by 321

Abstract

ERP systems significantly optimize many business processes and activities, but often their implementation and use in companies is a risky endeavor. They are the subject of various scientific studies and analyses in the fields of business, accounting and finance. The main focus in [...] Read more.

ERP systems significantly optimize many business processes and activities, but often their implementation and use in companies is a risky endeavor. They are the subject of various scientific studies and analyses in the fields of business, accounting and finance. The main focus in them falls on the process of implementing these systems, while the subsequent stages, risk analysis and long-term strategy are less affected. On this basis, this research paper proposes a methodology for quantitative assessment of identified ERP risks. It is based on a five-level matrix measuring three risk factors—influence, impact and vulnerability. The methodology has been empirically tested in three companies, different in size and operating in different economic sectors. The results show that the level of risk depends not only on the scale and complexity of the business, but also on the degree of integration of ERP solutions. Periodic application of the risk assessment methodology helps identify problem areas and facilitates management decision-making. Full article

(This article belongs to the Special Issue Digital Economy and the Role of Accounting and Finance)

26 pages, 388 KB

Open AccessArticle

When Governance Fails to Govern: Rethinking Audit Quality and Firm Value in Weak Institutional Environments

by Dramani Angsoyiri, Fadi Alkaraan, Judith John and Mohammad Al Bahloul

J. Risk Financial Manag. 2026, 19(3), 225; https://doi.org/10.3390/jrfm19030225 - 18 Mar 2026

Viewed by 687

Abstract

Corporate governance reforms in emerging and frontier markets frequently assume that strengthening board oversight, audit committees, and ownership monitoring will improve audit quality and enhance firm value. Yet, in weak institutional environments, these mechanisms often function symbolically rather than substantively. This study rethinks [...] Read more.

Corporate governance reforms in emerging and frontier markets frequently assume that strengthening board oversight, audit committees, and ownership monitoring will improve audit quality and enhance firm value. Yet, in weak institutional environments, these mechanisms often function symbolically rather than substantively. This study rethinks the governance–audit–value nexus by integrating Agency Theory, Institutional Theory, and the concept of symbolic governance to explain why governance may appear structurally robust while failing to constrain managerial discretion. Using panel data from Ghanaian listed firms between 2015 and 2023, the analysis shows that audit committee independence and board independence are negatively associated with both audit quality and firm value, indicating that formal independence without expertise, authority, or enforcement capacity does not translate into meaningful oversight. By contrast, institutional and managerial ownership positively influence both outcomes, suggesting that incentive alignment and informed monitoring can substitute for weak formal governance. Foreign ownership improves firm value but does not consistently enhance audit quality, while macroeconomic conditions such as inflation and GDP growth further shape firm performance. The study advances the literature by reconceptualising governance effectiveness in weak institutional environments, demonstrating that governance mechanisms may exist in form without functioning in substance. The findings underscore the need for governance reforms that prioritise enforcement capacity, board expertise, and audit committee competence rather than structural compliance alone. Full article

(This article belongs to the Special Issue Accounting, Auditing, and Reporting Quality: Challenges Under Uncertainty Conditions)

34 pages, 475 KB

Open AccessArticle

Applications and Management of Blockchain Technologies in Financial Services

by Nasser Arshadi and Timothy Dombrowski

J. Risk Financial Manag. 2026, 19(3), 224; https://doi.org/10.3390/jrfm19030224 - 17 Mar 2026

Viewed by 622

Abstract

Using transaction cost economics (TCE) and agency theory, this paper examines how blockchain, smart contracts, and decentralized autonomous organizations (DAOs) reconfigure financial services across payments, wealth management, real estate, and corporate governance. Three research questions are addressed: (1) What are the quantifiable efficiency [...] Read more.

Using transaction cost economics (TCE) and agency theory, this paper examines how blockchain, smart contracts, and decentralized autonomous organizations (DAOs) reconfigure financial services across payments, wealth management, real estate, and corporate governance. Three research questions are addressed: (1) What are the quantifiable efficiency gains from blockchain-based real-time settlement compared with legacy systems? (2) How do blockchain technologies reduce intermediation and agency costs in wealth management and real estate? (3) Finally, to what extent do DAOs resolve or transform traditional corporate governance problems? By combining a present-value model calibrated to U.S. Automated Clearing House (ACH) data ($86.2 trillion in annual volume), comparative institutional analysis, and synthesis of empirical evidence from pilot implementations and on-chain governance metrics, this paper makes three principal contributions. First, real-time settlement yields approximately $12 billion in annual opportunity cost savings at the baseline 7.5% discount rate, with sensitivity analysis producing a range of $8–15 billion. The majority of gains accrue from moving to same-day or within-hour settlement. Second, tokenization and smart contract escrow substantially reduce real estate intermediation costs, blockchain-based digital identity streamlines wealth management onboarding, and a stablecoin taxonomy classifies fiat-collateralized, crypto-collateralized, and algorithmic designs by risk profile. Third, on-chain data reveal persistent governance token concentration (Gini > 0.98) and low voter participation (typically below 10%), exposing a gap between DAO theory and practice. Blockchain-specific risks are mapped to National Institute of Standards and Technology (NIST) Cybersecurity Framework 2.0, and mechanism design solutions, such as quadratic voting and AI-assisted proposal evaluation, are proposed to address whale dominance. Effective adoption requires hybrid architecture combining on-chain automation with off-chain structures for accountability and regulatory compliance. Full article

(This article belongs to the Special Issue Financial Technology (Fintech) and Sustainable Financing, 4th Edition)

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22 pages, 360 KB

Open AccessArticle

The Role of Audit Committee Characteristics in Enhancing the Quality of ESG Accounting Disclosures: Panel Data Evidence from Saudi-Listed Firms

by Fateh Belouadah

J. Risk Financial Manag. 2026, 19(3), 223; https://doi.org/10.3390/jrfm19030223 - 17 Mar 2026

Viewed by 343

Abstract

This study focuses on the impact of the audit committee features on the quality of environmental, social, and governance (ESG) disclosure of the Saudi Stock Exchange-listed companies. Grounded in agency theory, stakeholder theory, and resource dependence theory, this research considers key audit committee [...] Read more.

This study focuses on the impact of the audit committee features on the quality of environmental, social, and governance (ESG) disclosure of the Saudi Stock Exchange-listed companies. Grounded in agency theory, stakeholder theory, and resource dependence theory, this research considers key audit committee characteristics, such as independence, expertise, and tenure, to determine the manner in which they contribute to the improvement of ESG disclosure through enhanced monitoring, accountability, and access to critical reporting-related resources. This study employed a regression model as a hypothesis-testing model using panel data of 78 Saudi-listed firms, which represent 234 firm-years until 2023. ESG disclosure quality is measured using the standardized ESG score obtained from the Refinitiv Eikon database. The results indicate that a positive and statistically significant relationship exists between ESG disclosure quality and audit committee independence and expertise. Conversely, the tenure of audit committees has a negative relationship with ESG disclosure quality. This research contributes to the ESG and corporate governance literature by extending audit committee research beyond traditional financial reporting oversight into ESG oversight in an emerging-market context, and by providing context-specific evidence from Saudi Arabia, where ESG reporting frameworks and enforcement mechanisms are still evolving. Practically, the implications of the findings provide useful recommendations to regulators and firms that intend to enhance their governance practices in accordance with the Saudi Vision 2030 and reforms at the Capital Market Authority. Full article

(This article belongs to the Section Business and Entrepreneurship)

22 pages, 348 KB

Open AccessArticle

Exchange Rate Volatility and Corporate Cash-Flow Resilience: Firm-Level Evidence from MENA Emerging Markets

by Soufiane Jamali and Said Elbouazizi

J. Risk Financial Manag. 2026, 19(3), 222; https://doi.org/10.3390/jrfm19030222 - 17 Mar 2026

Viewed by 526

Abstract

Exchange rate volatility creates uncertainty for firms in open economies, especially in emerging markets with structural vulnerability and shallow financial markets. This work examines the impact of exchange rate volatility on the cash-flow performance of non-financial firms in the Middle East and North [...] Read more.

Exchange rate volatility creates uncertainty for firms in open economies, especially in emerging markets with structural vulnerability and shallow financial markets. This work examines the impact of exchange rate volatility on the cash-flow performance of non-financial firms in the Middle East and North Africa (MENA) region of 292 firms across 11 countries from 2014 to 2023. Heteroskedasticity, serial correlation and cross-sectional dependence were estimated using fixed effects, random effects and robustness estimation using Driscoll–Kraay standard errors and Feasible Generalized Least Squares (FGLS). Exchange rate volatility has no statistically significant impact on corporate cash flows across all specifications, confirming the existence of an exchange rate exposure puzzle in emerging markets. Firm size always appears to be the strongest and most robust predictor of liquidity performance. The macroeconomic growth effect is weaker and context dependent: It is insignificant with baseline panel estimations, is negative with Driscoll–Kraay corrections and is marginally positive with FGLS structural controls. Profitability and inflation are virtually nonexistent. These insights inform both financial risk management and policy actions aimed at enhancing corporate stability and supporting sustainable development in emerging markets. Full article

(This article belongs to the Section Financial Markets)

19 pages, 667 KB

Open AccessArticle

A Machine Learning Approach to Audit Modification Risk Prediction in Financial Reporting: Methods, Data, and Human-Centered Challenges

by Gökhan Silahtaroğlu, Feyza Dereköy and Esra Baytören

J. Risk Financial Manag. 2026, 19(3), 221; https://doi.org/10.3390/jrfm19030221 - 17 Mar 2026

Viewed by 425

Abstract

Financial reporting irregularities and audit modifications represent important warning signals of elevated fraud and financial distress risk. While recent studies report high predictive accuracy in fraud detection, most approaches frame the problem as a purely algorithmic classification task and offer limited interpretability for [...] Read more.

Financial reporting irregularities and audit modifications represent important warning signals of elevated fraud and financial distress risk. While recent studies report high predictive accuracy in fraud detection, most approaches frame the problem as a purely algorithmic classification task and offer limited interpretability for auditors, regulators, and decision-makers. This study reframes financial statement analysis as a human-interpretable audit modification risk prediction problem. It integrates domain-informed feature engineering with machine learning models. Using firm-level financial data and audit disclosures, audit opinions are used as a proxy indicator of elevated fraud-related reporting risk rather than confirmed fraudulent behavior. Logistic Regression, Random Forest, and Gradient Boosting models are trained under class imbalance using cost-sensitive learning and evaluated with recall, ROC–AUC, precision, F1-score, and accuracy. The results demonstrate that humanized categorical representations preserve predictive performance while substantially enhancing interpretability. Permutation-based feature importance analysis further identifies financially intuitive risk patterns and threshold-like conditions associated with elevated audit modification risk. The findings suggest that interpretable, risk-oriented machine learning frameworks can support more transparent and actionable financial reporting risk monitoring systems. Beyond predictive performance, the study discusses human-centered challenges related to model interpretability, decision support, and the integration of machine-learning systems into real-world financial reporting and audit-risk assessment workflows. Full article

(This article belongs to the Section Financial Technology and Innovation)

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19 pages, 658 KB

Open AccessArticle

Cohesion as Concentration: Exclusion-Driven Fragility in Financial Organizations

by Foong Soon Cheong

J. Risk Financial Manag. 2026, 19(3), 220; https://doi.org/10.3390/jrfm19030220 - 16 Mar 2026

Viewed by 256

Abstract

Financial crises repeatedly reveal organizations that appear internally aligned while failing to recognize accumulating tail risks. This paper argues that cohesion is observationally ambiguous. It can arise from information integration, in which heterogeneous inputs are debated and synthesized, or from exclusion, in which [...] Read more.

Financial crises repeatedly reveal organizations that appear internally aligned while failing to recognize accumulating tail risks. This paper argues that cohesion is observationally ambiguous. It can arise from information integration, in which heterogeneous inputs are debated and synthesized, or from exclusion, in which variance is removed through conformity pressure, gatekeeping, and intolerance of dissent. This distinction is formalized using a signal aggregation model in which an organization maintains an anchor belief and achieves agreement through two exclusion channels: report shrinkage toward the anchor and a tolerance rule that discards reports deviating beyond a threshold. Relative to a full inclusion benchmark, exclusion based cohesion jointly produces state contingent bias that is small in normal regimes but grows sharply under displacement, illusory precision in which observed disagreement falls as tail regime estimation error rises, effective concentration of decision inputs below the nominal participant count, and, when the anchor updates from filtered aggregates, dynamic lock in with delayed regime recognition and abrupt correction. External inputs that bypass internal filtering shorten recognition delays. The model yields testable governance diagnostics linking latent fragility to observable patterns in recorded dissent, anonymous to formal voting gaps, scenario set diversity, pipeline and method concentration, and anchor lag. The central implication is that governance systems should treat low internal conflict and unanimity as potentially diagnostic of variance depletion and should monitor whether heterogeneity is integrated or excluded before stress reveals the difference. Full article

(This article belongs to the Section Risk)

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27 pages, 495 KB

Open AccessArticle

Hierarchical Fuzzy Cognitive Maps for Financial Risk Monitoring Using Aggregated Financial Concepts

by George A. Krimpas, Georgios Thanasas, Nikolaos A. Krimpas, Maria Rigou and Konstantina Lampropoulou

J. Risk Financial Manag. 2026, 19(3), 219; https://doi.org/10.3390/jrfm19030219 - 16 Mar 2026

Viewed by 318

Abstract

This study addresses the gap between predictive optimization and monitoring-oriented risk concentration by introducing a hierarchical Fuzzy Cognitive Map (FCM) framework for financial risk assessment. Financial distress prediction models are employed to estimate firm-level default probabilities and are required to comply with regulatory [...] Read more.

This study addresses the gap between predictive optimization and monitoring-oriented risk concentration by introducing a hierarchical Fuzzy Cognitive Map (FCM) framework for financial risk assessment. Financial distress prediction models are employed to estimate firm-level default probabilities and are required to comply with regulatory standards. IFRS 9 and Basel III/IV frameworks emphasize model explainability, scenario analysis and causal transparency, which are essential for compliance purposes. The methodology aggregates correlated financial ratios into financial concepts through unsupervised clustering. Concepts interact through a learned coupling matrix and a controlled multi-step propagation, which enables the amplification of risk signals. A small residual correction is applied at the final readout, preserving the interpretability of the proposed framework. The framework was applied to two severely imbalanced benchmark bankruptcy datasets. It achieved higher precision–recall performance than Logistic Regression (PR–AUC

\approx 0.32

vs.

0.27

), improved calibration (Brier score

\approx 0.046

vs.

0.089

) and maintained competitive Recall@Top–K under tight supervisory monitoring budgets. Hierarchical FCM achieved predictive performance comparable to nonlinear models while maintaining concept-level interpretability. Our findings demonstrate that structured concept aggregation combined with interaction-based propagation provides a transparent alternative to purely predictive black-box models in financial distress assessment and is aligned with regulatory frameworks. Full article

(This article belongs to the Special Issue AI and Machine Learning for Credit Risk and Financial Distress Prediction)

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32 pages, 1008 KB

Open AccessArticle

Transfer Pricing and Macroeconomic Stability: A Multi-Country Analysis of European Economies

by Mohammed Amine Hajjaj, Zakariae Bel Mkaddem, Hicham Es-Saadi, Imane Tesse and Jihane Chahib

J. Risk Financial Manag. 2026, 19(3), 218; https://doi.org/10.3390/jrfm19030218 - 16 Mar 2026

Viewed by 397

Abstract

Transfer pricing has become a major channel through which multinational enterprises shift profits across countries. This study examines the macroeconomic and institutional determinants of transfer pricing in seven European economies (France, Spain, Germany, the United Kingdom, Italy, the Netherlands, and Portugal) over the [...] Read more.

Transfer pricing has become a major channel through which multinational enterprises shift profits across countries. This study examines the macroeconomic and institutional determinants of transfer pricing in seven European economies (France, Spain, Germany, the United Kingdom, Italy, the Netherlands, and Portugal) over the period 1985–2025. The main objective is to identify the key factors influencing profit shifting and to analyze the mechanisms through which multinational firms allocate profits across jurisdictions. The study employs panel data techniques and uses two different proxies to capture transfer pricing practices (trade-based and intangible-based channels). To analyze both long-run and short-run relationships between transfer pricing, exchange rate dynamics, foreign direct investment, inflation and institutional quality, the analysis relies on heterogeneous panel estimators and cointegration tests, supported by several robustness checks. The empirical results reveal the existence of a long-run relationship between transfer pricing and its macroeconomic and institutional determinants. Exchange rate fluctuations and inflation exert a negative effect on transfer pricing, whereas Foreign Direct Investment has a positive impact by expanding multinational investment networks and intra-group transactions. The effect of institutional quality, proxied by control of corruption, appears more heterogeneous and may vary across jurisdictions as well as across the type of transfer pricing channel, whether related to tangible trade or intangible assets. These results emphasize the importance of institutional quality and international tax coordination in limiting aggressive profit-shifting practices. Full article

(This article belongs to the Section Economics and Finance)

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24 pages, 1861 KB

Open AccessArticle

Financial Wellbeing and Financial Resilience: Insights from Personal Experiences and Gender Differences

by Arturo Garcia-Santillan, Jacob Owusu Sarfo and Francisco Venegas-Martínez

J. Risk Financial Manag. 2026, 19(3), 217; https://doi.org/10.3390/jrfm19030217 - 13 Mar 2026

Viewed by 405

Abstract

This study aims to examine the relationships between perceived financial health indicators, lived financial experiences, and actions taken to cope with economic crises, as well as exploring potential gender differences. A non-experimental, quantitative, cross-sectional design is applied to a sample of 499 working [...] Read more.

This study aims to examine the relationships between perceived financial health indicators, lived financial experiences, and actions taken to cope with economic crises, as well as exploring potential gender differences. A non-experimental, quantitative, cross-sectional design is applied to a sample of 499 working professionals who graduated from universities in Veracruz, Mexico, and were employed in the public or private sector. A 24-item Likert scale instrument assessed financial health perceptions, experiences, and crisis-related behaviors. In this study, reliability indices (Cronbach’s alpha and McDonald’s omega) exceeded the acceptability threshold of 0.70. Data were analyzed using Exploratory Factor Analysis, Structural Equation Modeling, and Bayesian estimation to examine gender effects. The results supported a four-factor structure explaining 64.86% of the variance. Financial wellbeing showed a moderate association with resilience (r = 0.32), a weaker relationship with financial experiences (r = 0.18), and a strong association between experiences and crisis-related actions (r = 0.47). No statistically significant gender differences were identified. These findings contribute to understanding how experiential and behavioral components interact to shape financial outcomes, and we propose a refined three-factor framework linking financial experiences and adaptive actions to overall financial wellbeing. Full article

(This article belongs to the Special Issue From Financial Fragility to Resilience: Households, Investors, and Small Businesses)

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22 pages, 359 KB

Open AccessSystematic Review

The Future of External Audit: A Systematic Literature Review of Emerging Technologies and Their Impact on External Audit Practices

by Ahmad Salim Moh’d Abderrahman and Naser Makarem

J. Risk Financial Manag. 2026, 19(3), 216; https://doi.org/10.3390/jrfm19030216 - 12 Mar 2026

Viewed by 687

Abstract

Purpose: This study systematically reviews research on six emerging technologies in external auditing, Big Data, Blockchain, Machine Learning, Deep Learning, Artificial Intelligence (AI), and Robotic Process Automation (RPA), to clarify what is currently known and to identify where the main gaps remain. [...] Read more.

Purpose: This study systematically reviews research on six emerging technologies in external auditing, Big Data, Blockchain, Machine Learning, Deep Learning, Artificial Intelligence (AI), and Robotic Process Automation (RPA), to clarify what is currently known and to identify where the main gaps remain. Rather than treating each technology in isolation, this study brings them together under a single integrative review to provide a consolidated reference point for scholars assessing their impact on external audit practices. Design/Methodology/Approach: Following a structured systematic review protocol, searches were conducted in Scopus, ScienceDirect and SpringerLink (2000–2024) using technology-related keywords combined with “audit”, “auditor” and “auditing”. After applying explicit inclusion and exclusion criteria, 471 records were reduced to 32 ABS-listed journal articles, which were analysed thematically. Findings: The review shows that research on emerging technologies in external auditing is still fragmented, with substantial variation in the depth and maturity of evidence across the six technologies. The strongest empirical base is concentrated in Big Data analytics and ML-based predictive models (including more advanced Deep Learning variants), whereas Blockchain and RPA work remains predominantly conceptual or confined to small-scale design-science implementations. Across technologies, most studies are single-country and either rely on auditors’ self-reported perceptions of adoption and impact or evaluate model performance without tracing effects on audit strategies and engagement outcomes, which limits external validity and construct measurement. Very few articles explicitly integrate the Audit Risk Model or other formal theories, and almost no work examines multi-technology “audit stacks” or generative AI, leaving substantial gaps in understanding how these tools jointly reshape inherent, control and detection risk across the audit cycle. Originality/Value: By integrating six technologies within a single external audit framework, the review offers a technology-specific evidence map and a targeted future research agenda that can guide scholars, audit firms and regulators in designing studies and policies aligned with actual gaps in the current literature. Full article

(This article belongs to the Special Issue Accounting and Auditing in the Age of Sustainability and AI)

21 pages, 1772 KB

Open AccessArticle

Bitcoin and Gold Causality Across Quantiles, Frequencies, and Market Regimes

by Tsolmon Sodnomdavaa

J. Risk Financial Manag. 2026, 19(3), 215; https://doi.org/10.3390/jrfm19030215 - 12 Mar 2026

Viewed by 454

Abstract

This study investigates directional causality between Bitcoin and gold across different market conditions. Rather than relying on mean-based dependence, we examine how causal effects vary across return quantiles, investment horizons, and market regimes. To address this question, we apply a Causal–Frequency–Quantile–Regime (CFQR) framework. [...] Read more.

This study investigates directional causality between Bitcoin and gold across different market conditions. Rather than relying on mean-based dependence, we examine how causal effects vary across return quantiles, investment horizons, and market regimes. To address this question, we apply a Causal–Frequency–Quantile–Regime (CFQR) framework. The approach combines frequency-domain Granger causality, quantile-based non-causality tests, and endogenous regime classification within a unified setting. Macroeconomic controls are included to reduce omitted variable bias. Statistical inference relies on bootstrap procedures with false discovery rate correction to account for multiple testing. Using daily data from 2013 to 2025, we find that the full-sample directional dominance between Bitcoin and gold is generally weak after multiple testing adjustments. However, under stress regimes, the causal relationship of gold to Bitcoin becomes more pronounced at longer investment horizons. Under normal conditions, causal effects remain unstable and fragmented. Economic effects are modest. Variance-based hedging gains are limited, while downside risk measures show moderate improvement during stress periods. Overall, the evidence suggests that gold does not serve as a universal hedge for Bitcoin, but may exert conditional informational influence during high-uncertainty states. The CFQR framework provides a structured way to identify such state-dependent causal patterns. Full article

(This article belongs to the Section Currencies)

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16 pages, 1565 KB

Open AccessArticle

Shrimp Market Under Innovation Schemes: Hidden Markov Modeling

by Johnny Javier Triviño-Sanchez, Alexander Fernando Haro-Sarango, Julián Coronel-Reyes, Carlos Alfredo De Loor-Platón and Dayanna Soria-Encalada

J. Risk Financial Manag. 2026, 19(3), 214; https://doi.org/10.3390/jrfm19030214 - 12 Mar 2026

Viewed by 321

Abstract

This article models the Ecuadorian shrimp market as a nonlinear system with recurring latent regimes that affect margins and planning decisions. A multivariate Hidden Markov Model (HMM) with Gaussian emissions in log space is estimated via the Baum–Welch algorithm to segment the joint [...] Read more.

This article models the Ecuadorian shrimp market as a nonlinear system with recurring latent regimes that affect margins and planning decisions. A multivariate Hidden Markov Model (HMM) with Gaussian emissions in log space is estimated via the Baum–Welch algorithm to segment the joint dynamics of pounds produced, dollars invoiced, and average price. The analysis uses monthly data from January 2017 to May 2025 (T = 101). The selected four-state specification shows strong fit and outperforms linear alternatives (log likelihood = 480.9; AIC = 859.8; BIC = 729.5). The dominant regime (State 2) concentrates high prices (~USD 2.97/lb) with intermediate production and acts as an attractor (stationary probability ≈ 1), while States 0 and 1 capture orderly expansion and oversupply conditions, and State 3 reflects episodic demand rallies. Adverse regimes (States 0–1) exhibit expected durations of 6–8 months, suggesting natural reversion toward the profitable regime. These estimates enable probabilistic regime forecasting and Monte Carlo scenario simulation to support hedging, inventory management, and financial stress testing. Overall, the proposed HMM framework provides an operational decision tool for producers, traders, and policymakers seeking to anticipate regime shifts, mitigate oversupply cycles, and stabilize margins. Full article

(This article belongs to the Section Mathematics and Finance)

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22 pages, 659 KB

Open AccessArticle

What Determines Corporate Board Diligence? Evidence from Emerging Market

by Badar Alshabibi, Hidaya Al Lawati, Mohd Abass Bhat, Naser Makarem and Shagufta Tariq Khan

J. Risk Financial Manag. 2026, 19(3), 213; https://doi.org/10.3390/jrfm19030213 - 12 Mar 2026

Viewed by 413

Abstract

This study investigates the impact of board attributes (board size, board independence, gender diversity, and nationality diversity) on corporate board diligence through employing panel data of listed firms in Muscat Securities Market from 2014 to 2024. Through the application of multiple regression analysis, [...] Read more.

This study investigates the impact of board attributes (board size, board independence, gender diversity, and nationality diversity) on corporate board diligence through employing panel data of listed firms in Muscat Securities Market from 2014 to 2024. Through the application of multiple regression analysis, the paper determines predictors for board diligence and offers an agency theory-based and resource dependence theory-based perspective on this construct. The findings reveal positive relations between board independence and board diligence, which suggests that the independent director has monitoring function. On the other hand, board size and nationality diversity are negatively related to diligence levels indicating a lack of coordination and communication. However, board gender diversity does not seem statistically related to board diligence. Several robustness tests, such as lagged independent variables, fixed industry effects, alternative estimation techniques, and instrumental variable approach, support the validity of our findings. This research helps investors and policymakers to better understand the extent to which board structure is related to meeting activity and director engagement in emerging markets. The study contributes to the literature on board diligence in emerging markets and evidence the impact of gender and nationality diversity on corporate board performance in Oman. Full article

(This article belongs to the Section Business and Entrepreneurship)

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40 pages, 907 KB

Open AccessArticle

The Silver Economy and Fiscal Outcomes in Aging Europe: A Governance-Conditioned Panel Analysis

by Ralitsa Veleva

J. Risk Financial Manag. 2026, 19(3), 212; https://doi.org/10.3390/jrfm19030212 - 12 Mar 2026

Viewed by 421

Abstract

Population aging is widely regarded as a major fiscal risk for European welfare states and a central challenge to long-term fiscal sustainability. The article critically reexamines the deterministic assumption by assessing whether the fiscal implications of demographic aging in the European Union (EU) [...] Read more.

Population aging is widely regarded as a major fiscal risk for European welfare states and a central challenge to long-term fiscal sustainability. The article critically reexamines the deterministic assumption by assessing whether the fiscal implications of demographic aging in the European Union (EU) are mechanically driven or conditioned by policy context and institutional capacity. Using panel data for the EU-27 over the period 2014–2024, the study employs a two-way fixed-effects framework and interaction models to examine the relationship between demographic aging and key fiscal outcomes, including public pension expenditures, total social protection spending, and the general government balance. Furthermore, the analysis examines whether indicators associated with the silver economy, such as employment at older ages and digital inclusion, condition the fiscal effects of aging within countries over time. The results suggest that demographic aging does not exhibit a statistically significant association with pension or social protection expenditures once institutional heterogeneity and common shocks are controlled. In contrast to deterministic expectations, aging is positively associated with general government balance, suggesting the presence of policy-mediated fiscal adjustment dynamics rather than automatic fiscal deterioration. Interaction estimates further indicate that digital inclusion among older cohorts conditions the relationship between demographic aging and fiscal balance, while silver economy indicators do not display robust standalone fiscal effects. These findings should be interpreted as evidence of policy-mediated adjustment dynamics rather than as causal estimates of demographic effects. Building on these findings, the article advances a conceptual interpretation of the aging–fiscal nexus in which demographic pressures interact with institutional adaptation and policy capacity. Fiscal sustainability under demographic aging emerges as a policy-mediated outcome that may reflect broader institutional and governance contexts, rather than demographic structure alone. While governance quality is not directly estimated as an observable variable, the analysis interprets fiscal outcomes within a governance-conditioned institutional framework that emphasizes policy mediation rather than deterministic demographic effects. The findings contribute to ongoing debates on fiscal sustainability in aging societies by demonstrating that fiscal outcomes in the European Union are best understood as institutionally conditioned and policy-mediated rather than mechanically driven by demographic structure alone. Full article

(This article belongs to the Special Issue Applied Public Finance and Fiscal Analysis)

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24 pages, 1689 KB

Open AccessArticle

Inflation and CO₂ Emissions: Asymmetric Moderating Effects of Financial Development in Fiji

by Nikeel Nishkar Kumar, Ravinay Amit Chandra and Rajesh Mohnot

J. Risk Financial Manag. 2026, 19(3), 211; https://doi.org/10.3390/jrfm19030211 - 11 Mar 2026

Viewed by 398

Abstract

This study explores the asymmetric moderating effect of inflation and financial development on carbon (CO₂) emissions using annual data from Fiji over the period from 1970 to 2023. This study is motivated by the dearth of evidence on the ecological implications [...] Read more.

This study explores the asymmetric moderating effect of inflation and financial development on carbon (CO₂) emissions using annual data from Fiji over the period from 1970 to 2023. This study is motivated by the dearth of evidence on the ecological implications of macroeconomic variables in climate-vulnerable small island developing states. We find that an increase in inflation more strongly reduces CO₂ emissions compared to by how much an equivalently sized decrease in inflation increases CO₂ emissions. We further find that positive shocks to financial development accentuate the negative effect of inflation on CO₂ emissions. Negative shocks, by contrast, attenuate the negative effect of inflation on CO₂ emissions. This pattern of asymmetries implies the presence of credit-constrained consumers who may be highly sensitive to cost-of-living pressures. The results further imply the role of demand suppression in mitigating CO₂ emissions. The policy implication is that macroeconomic indicators such as inflation tend to have ecological implications, which must be recognized by policymakers in determining stabilization policies. Full article

(This article belongs to the Special Issue Climate and Financial Markets)

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21 pages, 474 KB

Open AccessArticle

Performance Evaluation of Machine Learning and Deep Learning Models for Credit Risk Prediction

by Irvine Mapfumo and Thokozani Shongwe

J. Risk Financial Manag. 2026, 19(3), 210; https://doi.org/10.3390/jrfm19030210 - 11 Mar 2026

Viewed by 578

Abstract

Credit risk prediction is essential for financial institutions to effectively assess the likelihood of borrower defaults and manage associated risks. This study presents a comparative analysis of deep learning architectures and traditional machine learning models on imbalanced credit risk datasets. To address class [...] Read more.

Credit risk prediction is essential for financial institutions to effectively assess the likelihood of borrower defaults and manage associated risks. This study presents a comparative analysis of deep learning architectures and traditional machine learning models on imbalanced credit risk datasets. To address class imbalance, we employ three resampling techniques: Synthetic Minority Over-sampling Technique (SMOTE), Edited Nearest Neighbors (ENN), and the hybrid SMOTE-ENN. We evaluate the performance of various models, including multilayer perceptron (MLP), convolutional neural network (CNN), long short-term memory (LSTM), gated recurrent unit (GRU), logistic regression, decision tree, support vector machine (SVM), random forest, adaptive boosting, and extreme gradient boosting. The analysis reveals that SMOTE-ENN combined with MLP achieves the highest F1-score of 0.928 (accuracy 95.4%) on the German dataset, while SMOTE-ENN with random forest attains the best F1-score of 0.789 (accuracy 82.1%) on the Taiwanese dataset. SHapley Additive exPlanations (SHAP) are employed to enhance model interpretability, identifying key drivers of credit default. These findings provide actionable guidance for developing transparent, high-performing, and robust credit risk assessment systems. Full article

(This article belongs to the Section Financial Technology and Innovation)

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32 pages, 1608 KB

Open AccessReview

From Adoption to Audit Quality: Mapping the Intellectual Structure of Artificial Intelligence-Enabled Auditing

by Sheela Sundarasen, Kamilah Kamaludin and Deepa Nakiran

J. Risk Financial Manag. 2026, 19(3), 209; https://doi.org/10.3390/jrfm19030209 - 11 Mar 2026

Viewed by 769

Abstract

This study conducts a bibliometric and content analysis of ‘artificial intelligence-enabled auditing’ over three decades. The use of artificial intelligence (AI) tools in auditing has evolved and is now an imperative practice in the auditing space. Using bibliometric methods via Bibliometrix R-package (Biblioshiny) [...] Read more.

This study conducts a bibliometric and content analysis of ‘artificial intelligence-enabled auditing’ over three decades. The use of artificial intelligence (AI) tools in auditing has evolved and is now an imperative practice in the auditing space. Using bibliometric methods via Bibliometrix R-package (Biblioshiny) and VOSviewer, this research mainly examines the scholarly discussion on AI-enabled auditing, using the Scopus database. The main themes identified are: Theme 1: AI in auditing: readiness, representation, and implementation; Theme 2: data-driven audit ecosystems and digital technologies; and Theme 3: audit quality, professional skepticism, and ethical governance. On the descriptive end, publication trends, prominent authors, articles, and sources are identified. The findings highlight a significant increase in AI-enabled auditing studies since 2018, coinciding with growing global awareness on the importance of AI across all spheres of business. The outcome of this research contributes to a wide array of stakeholders, including businesses, audit firms, shareholders, and policymakers; it should give insights to business organizations on the capabilities of AI-assisted auditing, while policymakers should have access to verifiable, auditable and regulatory-compliant systems for the implementation of their regulations. Investors may further enhance their knowledge in terms of how AI-assisted auditing increases the quality of their investment decisions and, at the same time, the risks involved. Finally, auditing firms should further invest in improving the application of technology in the auditing environment and ensure quality, evidence-based audit outcomes, and reporting. Full article

(This article belongs to the Special Issue Accounting and Auditing in the Age of Sustainability and AI)

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21 pages, 315 KB

Open AccessEditorial

Introduction: Globalization and Economic Integration

by Bruno Dallago and Sara Casagrande

J. Risk Financial Manag. 2026, 19(3), 208; https://doi.org/10.3390/jrfm19030208 - 11 Mar 2026

Viewed by 649

Abstract

The purpose of this Special Issue is to explore the challenges and trends of the process of globalization and its coevolution with integration processes in different parts of the world [...] Full article

(This article belongs to the Special Issue Globalization and Economic Integration)

16 pages, 498 KB

Open AccessArticle

Economic Policy Uncertainty and Bond Returns Under Different Market Conditions: A Focus on South Africa

by Simiso Msomi, Damien Kunjal and Fabian Moodley

J. Risk Financial Manag. 2026, 19(3), 207; https://doi.org/10.3390/jrfm19030207 - 10 Mar 2026

Viewed by 423

Abstract

Economic policy uncertainty (EPU) has emerged as a critical variable influencing financial markets, especially bond returns. The relationship between EPU and bond returns is rooted in theories of asset pricing, risk premiums, and market behaviour under uncertainty. There are varying conclusions about the [...] Read more.

Economic policy uncertainty (EPU) has emerged as a critical variable influencing financial markets, especially bond returns. The relationship between EPU and bond returns is rooted in theories of asset pricing, risk premiums, and market behaviour under uncertainty. There are varying conclusions about the EPU’s effect on bond returns across business cycles. In some instances, for example, during recessions, EPU increased the likelihood of low-return regimes for corporate bonds, while government bond prices rose due to increased demand for safe assets. In this study, the Markov Switching regime was used to analyse the asymmetric nature of the EPU in relation to bond market returns. The study demonstrates that the EPU bond returns response is regime-dependent and segment-specific. Therefore, market regulation and policy design incorporating dynamic regime-aware investment strategies will effectively enhance the stability and resilience of the bond market. Full article

(This article belongs to the Section Financial Markets)

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17 pages, 899 KB

Open AccessArticle

Towards a Consolidation of the Prominent Firm-Related Capital Structure Determinants

by Marise Mouton and Ilsé Botha

J. Risk Financial Manag. 2026, 19(3), 206; https://doi.org/10.3390/jrfm19030206 - 10 Mar 2026

Viewed by 416

Abstract

The heterogeneous empirical evidence in the vast literature on capital structure determinants is puzzling to scholars and practitioners. Various leverage measurements, in conjunction with the inconclusiveness of the significant firm-related capital structure determinants, complicate comparability. Practitioners also find it challenging to determine optimal [...] Read more.

The heterogeneous empirical evidence in the vast literature on capital structure determinants is puzzling to scholars and practitioners. Various leverage measurements, in conjunction with the inconclusiveness of the significant firm-related capital structure determinants, complicate comparability. Practitioners also find it challenging to determine optimal financing strategies with real precision. This paper provides an integrative position that consolidates firm-related capital structure determinants with their respective measurements and suggests a preferred proxy for capital structure. A qualitative design has been applied, which is rarely done in the context of capital structure. This paper also offers a methodological contribution by utilising a combination of documentary analysis with PRISMA and forward-looking citation analysis, named the adapted documentary analysis. Capital structure determinant studies were targeted from inception until 2023. The synthesis of the results from 335 articles identified the six most prominent capital structure determinants: profitability, tangibility, growth proxied by the market-to-book value of equity (MTB), firm size, non-debt tax shield (NDTS), and business risk. Capital structure book value measurements seem more reliable than market-based measures. Profitability, MTB, and tangibility are the key firm-related determinants informing practitioners’ financing decisions. A consolidated list of the most prominent capital structure determinants, with their associated measurements, and a reliable proxy for capital structure are novel contributions that enable comparability in capital structure research across companies, industries, and countries. It creates a consolidated, integrative platform that adds to the academic debate and assists practitioners in their capital structure decision-making. Full article

(This article belongs to the Special Issue Contemporary Studies on Corporate Finance and Business Research, 2nd Edition)

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21 pages, 365 KB

Open AccessArticle

Investment Risk Appetite (IRA): Scale Development and Validation

by Tariq Qaysi and M. M. Sulphey

J. Risk Financial Manag. 2026, 19(3), 205; https://doi.org/10.3390/jrfm19030205 - 10 Mar 2026

Viewed by 533

Abstract

Investment Risk Appetite (IRA) is a pivotal concept in risk management, reflecting an investor’s willingness to tolerate financial risks within acceptable thresholds. As empirical investigations into this construct gain momentum, there is a growing need for a scientifically validated tool to facilitate in-depth [...] Read more.

Investment Risk Appetite (IRA) is a pivotal concept in risk management, reflecting an investor’s willingness to tolerate financial risks within acceptable thresholds. As empirical investigations into this construct gain momentum, there is a growing need for a scientifically validated tool to facilitate in-depth examinations of risk appetite. There are no scales to measure risk appetite. The present study addresses this gap by developing and validating a scale on risk appetite. Leveraging data collected from 405 respondents and employing established methodologies, the study introduces the Investment Risk Appetite (IRA) Scale. The questionnaire had a five-point scale. The scale consists of two factors: risk tolerance (α = 0.837, composite reliability = 0.836) and risk aversion (α = 0.905, composite reliability = 0.906). The validation was done by exploratory and confirmatory factor analysis (EFA and CFA). The loadings for EFA and CFA exceeded the threshold limit of 0.40. The scale demonstrates robust internal consistency, content, and construct validity. Hence, this scale has all the required validity. Overall, this scale demonstrates robust validity and reliability. In addition, this study examined the differences based on the demographics of the respondents. The scale, poised to make a significant contribution to the literature on risk appetite, will provide a theoretical foundation for future in-depth investigations. This study is expected to inspire future empirical examinations of this compelling construct. Full article

(This article belongs to the Section Mathematics and Finance)

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J. Risk Financial Manag., Volume 19, Issue 3 (March 2026) – 72 articles

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