Journal of Risk and Financial Management

13 pages, 706 KB

Open AccessArticle

The Reform Study and Recommendation of Public Labor Pension in Taiwan: Considering the Effect of Reemployed Retired Laborers

by Yung-Cheng Liao and Mei-Su Chen

J. Risk Financial Manag. 2026, 19(4), 299; https://doi.org/10.3390/jrfm19040299 - 21 Apr 2026

Viewed by 1112

Abstract

Reform and sustainability of the defined benefit pension system has received considerable attention because it addresses the challenges of an aging population and the risk of fund insolvency. However, previous studies have little consideration to the effects of reemployed retired laborers and the [...] Read more.

Reform and sustainability of the defined benefit pension system has received considerable attention because it addresses the challenges of an aging population and the risk of fund insolvency. However, previous studies have little consideration to the effects of reemployed retired laborers and the sensitivity of each key reform element. The study established a financial forecasting model incorporating reemployed retired laborers and employed comparative static analysis to examine the effects of several variables on Taiwan’s public labor pension. In Scenario Three, the fund balance was projected to remain positive until 2064. Furthermore, increasing the premium rate to 17% had the strongest positive effect on the fund balance with 16-year delay, while an annual government subsidy of NT$100 billion had the second-most positive effect with 10-year delay. Moreover, solely reducing the old-age annuity amount by 10% had a positive impact on the fund balance with 7-year delay. Furthermore, allowing 50% of reemployed retired laborers to reenroll in the system had the positive effect with 9-year delay before bankruptcy. Finally, the study proposes a comprehensive reform plan for the public labor pension and offers valuable insights for other countries. Full article

(This article belongs to the Section Sustainability and Finance)

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28 pages, 1664 KB

Open AccessArticle

Failing to Use the Balance Sheet to Manage Cycle Shocks: Evidence from Nigeria

by Akolisa Ufodike

J. Risk Financial Manag. 2026, 19(4), 298; https://doi.org/10.3390/jrfm19040298 - 20 Apr 2026

Viewed by 879

Abstract

Nigeria entered the 2020 COVID-19-related oil price downturn without the fiscal buffers that numerous resource-rich economies had built over time. Despite heavy dependence on petroleum revenues, the country has made limited use of stabilization tools such as structured hedging programs, sovereign savings mechanisms, [...] Read more.

Nigeria entered the 2020 COVID-19-related oil price downturn without the fiscal buffers that numerous resource-rich economies had built over time. Despite heavy dependence on petroleum revenues, the country has made limited use of stabilization tools such as structured hedging programs, sovereign savings mechanisms, or strategic reserves, leaving public finances exposed to external shocks. Drawing on political choice theory and the resource governance literature, this study examines how institutional conditions shaped crisis management during the 2020 oil price collapse and the COVID-19 pandemic. The study combines qualitative institutional analysis with a stochastic counterfactual simulation. It compares Nigeria’s policy approach with those of oil-producing countries including Mexico, Saudi Arabia, the United Arab Emirates, Angola, and Ghana, using data from the IMF, World Bank, Afreximbank, and peer-reviewed sources. The counterfactual simulation is calibrated to Nigeria’s 2019 federal budget oil benchmark of US $60 per barrel, with the IMF’s 2019 petroleum price assumption used as a robustness check. The model treats hedging as a form of partial fiscal insurance rather than full stabilization. Results suggest that hedging sufficient to offset 10%, 20%, and 30% of the shock would have improved 2020 GDP decline from −1.80% to approximately −1.62%, −1.44%, and −1.26%, respectively. The analysis identifies institutional gaps in Nigeria’s use of hedging, sovereign savings, and reserve infrastructure. The counterfactual results indicate that even modest oil hedging could have meaningfully softened the 2020 downturn, with the 20% scenario reducing GDP contraction by an estimated 0.36 percentage points. These findings suggest that governance constraints contributed materially to fiscal vulnerability. The study proposes a four-pillar framework centered on risk hedging, revenue savings, strategic investment, and institutional reform to strengthen fiscal stability and resilience to external shocks. Full article

(This article belongs to the Special Issue Commodity Price Risk and Corporate Valuation)

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22 pages, 697 KB

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Breaking Barriers: How Fintech Expands Access to Finance?

by Andromahi Kufo, Ardit Gjeçi, Gentjan Çera and Kserdi Cenolli

J. Risk Financial Manag. 2026, 19(4), 297; https://doi.org/10.3390/jrfm19040297 - 20 Apr 2026

Viewed by 1316

Abstract

Financial technologies (Fintech) have rapidly reshaped access to financial services, particularly in developing countries where traditional banking remains limited. This study investigates fintech’s role in advancing financial inclusion by analyzing panel data from 89 developing economies gathered from Global Findex reports (2011–2021), complemented [...] Read more.

Financial technologies (Fintech) have rapidly reshaped access to financial services, particularly in developing countries where traditional banking remains limited. This study investigates fintech’s role in advancing financial inclusion by analyzing panel data from 89 developing economies gathered from Global Findex reports (2011–2021), complemented by International Monetary Fund (IMF), UNU-WIDER, and PRIO datasets. We applied a random-effects regression model and GMM, incorporating fintech adoption alongside macroeconomic and institutional variables such as education, governance quality, and trade openness. Our results show that fintech is the most significant driver of financial inclusion, especially in expanding account ownership, with education and institutional quality further enhancing outcomes. Conversely, we show that population growth and income disparities constrain progress, while government expenditure and GDP growth display mixed effects. We also find that fintech reduces transaction costs and barriers, yet its impact depends on digital literacy, infrastructure, and governance. In conclusion, our findings highlight that fintech represents a transformative but unevenly utilized tool, capable of fostering broader economic participation and reducing inequality when paired with supportive policies and institutional frameworks. Full article

(This article belongs to the Special Issue Emerging Trends and Innovations in Corporate Finance and Governance)

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27 pages, 733 KB

Open AccessArticle

Capital Structure in Small Firms: A Conditional Approach Based on Accounting Variables

by Isabel Oliveira, Amândio Silva, Jorge Figueiredo, Antonio Cardoso and Manuel Sousa Pereira

J. Risk Financial Manag. 2026, 19(4), 296; https://doi.org/10.3390/jrfm19040296 - 19 Apr 2026

Viewed by 1139

Abstract

This study examines the accounting determinants of the capital structure of Portuguese firms in the textile, clothing, and leather sectors, based on a sample of 6469 firms over the period 2010–2022, using panel data models. The relevance of this study lies in its [...] Read more.

This study examines the accounting determinants of the capital structure of Portuguese firms in the textile, clothing, and leather sectors, based on a sample of 6469 firms over the period 2010–2022, using panel data models. The relevance of this study lies in its focus on specific industrial sectors characterized by a high predominance of small and medium-sized enterprises (SMEs) and a strong dependence on bank financing. In addition to the traditional analysis of leverage determinants, this study introduces a conditional approach to accounting variables based on firms’ structural characteristics, namely size and age. Robustness checks and data treatment procedures were conducted to mitigate the potential impact of outliers in the financial variables. The results show that profitability, liquidity, and risk negatively affect indebtedness, whereas asset structure and growth exert positive effects. The effective tax rate has a negative impact on debt. Firm size and age significantly condition the relationship between variables. SMEs’ financing decisions exhibit differentiated patterns depending on firm size and age. The findings support the predictions of the Pecking Order Theory and, to a lesser extent, the Trade-Off Theory. The study highlights the importance of considering firm heterogeneity when designing financing policies and strategies for Portuguese SMEs. Full article

(This article belongs to the Section Business and Entrepreneurship)

36 pages, 1257 KB

Open AccessArticle

Artificial Intelligence in European Union Tax Administrations: A Comparative Assessment

by Angel Angelov

J. Risk Financial Manag. 2026, 19(4), 295; https://doi.org/10.3390/jrfm19040295 - 19 Apr 2026

Cited by 1 | Viewed by 1855

Abstract

The study aims to examine trends in the integration of artificial intelligence within the operational processes of tax administrations across the Member States of the European Union. It explores both the functional domains in which AI can be deployed and the institutional, ethical, [...] Read more.

The study aims to examine trends in the integration of artificial intelligence within the operational processes of tax administrations across the Member States of the European Union. It explores both the functional domains in which AI can be deployed and the institutional, ethical, regulatory and technological constraints that shape its deeper integration. The analysis relies on publicly available data from the Organisation for Economic Co-operation and Development (OECD), complemented by information from other open sources. Based on this dataset, the study develops a Tax AI Index (TAI) to provide a comparative quantitative assessment of the extent to which AI systems have been operationally integrated into EU tax administrations. The index is constructed from four subindices capturing (1) the use of artificial intelligence in communication between tax administrations and economic agents (TAIIS); (2) the integration of artificial intelligence in data management systems (TAIDS); (3) the application of algorithmic systems in tax enforcement, compliance control and administrative decisions (TAIRES); and (4) mechanisms for accountability, transparency and ethical oversight in the use of artificial intelligence (TAIGS). The empirical results indicate significant heterogeneity in the levels of digital transformation among the EU-27 Member States. In most countries, the adoption of artificial intelligence remains at an experimental or pilot stage, suggesting that its broader operational application is still evolving. To place these findings in a broader context, the analysis is complemented by an external measure of digital government development, allowing for a comparative assessment between AI adoption in tax administrations and overall public sector digital maturity. Full article

(This article belongs to the Section Sustainability and Finance)

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22 pages, 366 KB

Open AccessArticle

Information Discovery, Interpretation, and Analysis by Institutional Investors Around Earnings Announcements

by Sami Keskek and Abdullah Kumas

J. Risk Financial Manag. 2026, 19(4), 294; https://doi.org/10.3390/jrfm19040294 - 19 Apr 2026

Viewed by 904

Abstract

This study examines how institutional investors allocate trading across the earnings announcement cycle and whether industry trading concentration strengthens that activity. The analysis is motivated by two complementary ideas: public disclosures can increase the value of investors’ prior information, and even sophisticated investors [...] Read more.

This study examines how institutional investors allocate trading across the earnings announcement cycle and whether industry trading concentration strengthens that activity. The analysis is motivated by two complementary ideas: public disclosures can increase the value of investors’ prior information, and even sophisticated investors face costly information processing. These perspectives imply that institutional trading need not be concentrated only before disclosure and may be strongest after earnings announcements, when investors combine newly released public information with prior firm- and industry-specific signals. Using daily institutional trading data from Ancerno, we find that institutional net trading is positively related to earnings surprises before, during, and after earnings announcements, with the strongest relation occurring in the post-announcement period. We also document a clear asymmetry: trading is strongly related to positive earnings surprises across all three stages, whereas trading related to negative earnings surprises is concentrated mainly after disclosure. In addition, industry trading concentration strengthens the relation between institutional trading and earnings news across the announcement cycle, especially for positive surprises. These findings provide an integrated view of institutional information processing around a major recurring disclosure event, show that the timing of institutional trading is informative about how earnings news is incorporated into prices, and support the view that industry specialization is linked to stronger earnings-related trading. Full article

(This article belongs to the Special Issue Financial Reporting Quality and Capital Markets Efficiency)

26 pages, 572 KB

Open AccessArticle

Financing Post-War Circular Reconstruction: Digital Tools and Investment Pathways for Ukraine’s Industrial Regions

by Tetiana Gorokhova and Žaneta Simanavičienė

J. Risk Financial Manag. 2026, 19(4), 293; https://doi.org/10.3390/jrfm19040293 - 18 Apr 2026

Cited by 1 | Viewed by 1099

Abstract

Ukraine’s reconstruction, estimated at $524 billion over the next decade, presents an unprecedented opportunity to embed circular economy principles into industrial rebuilding, but the financial architecture currently deployed for reconstruction is structurally blind to circular outcomes. This paper examines how digital tools and [...] Read more.

Ukraine’s reconstruction, estimated at $524 billion over the next decade, presents an unprecedented opportunity to embed circular economy principles into industrial rebuilding, but the financial architecture currently deployed for reconstruction is structurally blind to circular outcomes. This paper examines how digital tools and innovative financing mechanisms can channel investment toward circular industrial reconstruction in Ukraine, drawing on Germany’s National Circular Economy Strategy (NCES, adopted December 2024) as a reference model. A comparative institutional analysis combines a documentary review of Ukrainian reconstruction policy frameworks (Ukraine Plan 2024–2027, RDNA4, Ukraine Facility) and German NCES instruments with the construction of a financing−technology pathway typology. Five pathways are proposed: circular bond issuance with Digital Product Passport integration; blended finance with blockchain impact verification; EU Facility conditionality with AI-driven resource management; war risk insurance with circular construction standards; and SME digitalisation credit with circular economy competency building. Each pathway is assessed against five criteria: investment scale, risk mitigation, circular measurement, digital readiness, and institutional feasibility, and applied to four industrial corridors (Dnipro region, Zaporizhzhia region, Kharkiv region, and Donetsk region). The analysis reveals that no single pathway is sufficient; a layered strategy differentiating by region is required. Digital tools, particularly the Digital Product Passport and blockchain traceability, serve as partial substitutes for institutional trust in post-conflict settings, reducing information asymmetry between investors and project operators. The paper contributes a practically oriented framework at the under-theorised intersection of post-conflict reconstruction finance and circular economy scholarship. Full article

(This article belongs to the Special Issue Financing the Digital Circular Economy: Business Models, Risk, and Economic Perspectives in Industry 5.0)

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18 pages, 744 KB

Open AccessArticle

Evaluating the Impact of Intelligent Data Processing for Corporate Finance with the Use of Real Options Analysis

by Stanimir Ivanov Kabaivanov and Veneta Metodieva Markovska

J. Risk Financial Manag. 2026, 19(4), 292; https://doi.org/10.3390/jrfm19040292 - 18 Apr 2026

Viewed by 553

Abstract

Technological innovation is changing virtually every aspect of business practices and operational procedures. The introduction of large language models and various types of intelligent processing, commonly referred to as artificial intelligence, presents significant change to cope with. In this paper, we suggest an [...] Read more.

Technological innovation is changing virtually every aspect of business practices and operational procedures. The introduction of large language models and various types of intelligent processing, commonly referred to as artificial intelligence, presents significant change to cope with. In this paper, we suggest an estimation method, based on real options analysis (ROA), that improves the assessment and valuation of intelligent data processing’s impact on organizations. The presented approach can reflect direct and indirect effects from introducing artificial intelligence methods and is therefore better suited than traditional financial metrics for the assessment of contemporary intelligent tools and solutions. Using Monte Carlo simulation and American-style real options, we have estimated two sample use cases to compare the ROA results against other common valuation methods. Numerical experiments indicate that the suggested approach is capable of capturing both the direct and indirect impact of new technologies, which improves relevant financial and management decisions. Full article

(This article belongs to the Special Issue The Role of Digitization in Corporate Finance)

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34 pages, 926 KB

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Basel III Capital and Conservation Buffers: Implications for the Credit Risk and Financial Stability of Indonesian Banks

by Titi Khoiriah, Rofikoh Rokhim and Buddi Wibowo

J. Risk Financial Manag. 2026, 19(4), 291; https://doi.org/10.3390/jrfm19040291 - 17 Apr 2026

Cited by 1 | Viewed by 1134 | Correction

Abstract

The stability of Indonesia’s banking sector is closely linked to the effectiveness of capital regulations, particularly as a country that aligns its policies with Basel III standards. Ensuring that banks have adequate capital buffers is crucial for mitigating systemic risk. However, the interaction [...] Read more.

The stability of Indonesia’s banking sector is closely linked to the effectiveness of capital regulations, particularly as a country that aligns its policies with Basel III standards. Ensuring that banks have adequate capital buffers is crucial for mitigating systemic risk. However, the interaction between regulatory requirements and actual banking behavior in developing countries remains poorly understood. This study aims to evaluate the impact of Indonesia’s capital requirement instruments, including the countercyclical capital buffer (CCyB), the capital conservation buffer (CCB), and the capital surcharge, on credit performance and financial stability across various bank categories. Using a quantitative approach, the analysis utilizes panel data from commercial banks, state-owned banks and regional development banks over several periods, using the panel regression method and Difference-in-Differences (DID) to assess how changes in buffer levels affect credit growth, Non-Performing Loans (NPLs), and the Capital Adequacy Ratio (CAR). The results show that capital buffers have a statistically significant effect on lending behavior: a 1% increase in buffer levels is associated with a measurable decrease in credit expansion across several bank groups, while CCBs exhibit a stronger stabilizing effect than CCyBs. Although these instruments do not eliminate financial uncertainty, they contribute to more prudent risk-taking. This study also revealed that the CCyB rate increases when the financial cycle is in an expansionary phase. Conversely, if the economy slows (as during the pandemic), the CCyB rate can be lowered back to 0% to encourage bank intermediation, thus shaping the bank’s responses to regulation. Several implications of implementing a capital buffer in Indonesia include the benefits of resilience and bank behavior during credit expansion. Overall, this study concludes that aligning regulatory frameworks with real-world banking behavior is crucial for enhancing financial stability in developing countries, such as Indonesia. Full article

(This article belongs to the Section Banking and Finance)

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26 pages, 1151 KB

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Institutional Governance and Capital Mobility: Evidence from India’s Trends in FDI and ODI

by Rishu Singh, Nishant Ranjan, Himanshu Thakkar, Haresh Barot and Siddharth Dabhade

J. Risk Financial Manag. 2026, 19(4), 290; https://doi.org/10.3390/jrfm19040290 - 17 Apr 2026

Viewed by 1142

Abstract

This paper examines how emerging economies, with a focus on India, transition from being primarily recipients of capital to becoming outward investors. It investigates whether domestic institutional governance, rather than rapid liberalization or extensive investment treaty networks, accounts for the sustained growth of [...] Read more.

This paper examines how emerging economies, with a focus on India, transition from being primarily recipients of capital to becoming outward investors. It investigates whether domestic institutional governance, rather than rapid liberalization or extensive investment treaty networks, accounts for the sustained growth of both inward FDI and outward ODI. The study combines a detailed timeline of institutional developments with structural break tests, vector autoregression (VAR), and dynamic panel GMM analysis. This approach tracks the timing, spread, and longevity of reforms like the shift from FERA to FEMA and the digitalization of administration, examining their effect on capital flow patterns. Results show that major turning points in India’s FDI and ODI movements correspond with key governance reforms, such as replacing the Foreign Exchange Regulation Act with the Foreign Exchange Management Act, unifying investment policies, digitizing administration, and renegotiating treaties post-2016. Improvements in governance have a more significant and enduring impact on FDI than macroeconomic factors, while clearer regulation and stronger institutions are vital for boosting ODI. Once domestic institutional capacity is taken into account, the number of investment treaties does not significantly influence capital movements. The paper introduces a “transferability matrix” that highlights effective, low-cost reforms, such as civil penalty systems and digital governance, which other emerging economies can implement. It stresses that integrating into global capital markets depends more on developing solid domestic regulations than on rapid deregulation. The study also advances previous research by (1) combining FDI and ODI within a single institutional framework explaining both flows; (2) moving beyond static, perception-based measures to develop a comprehensive timeline showing how regulatory credibility is built over three decades; and (3) providing empirical proof that credible domestic institutions can replace large treaty networks in ensuring capital mobility. Full article

(This article belongs to the Section Economics and Finance)

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17 pages, 321 KB

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Economic Consequences of Mandatory Adoption of International Financial Reporting Standards in Iraqi Banks

by Mohammed Al-Rammahi, Amin Rostami and Alireza Rahrovi Dastjerdi

J. Risk Financial Manag. 2026, 19(4), 289; https://doi.org/10.3390/jrfm19040289 - 17 Apr 2026

Viewed by 733

Abstract

This study examines the economic consequences associated with the mandatory adoption of International Financial Reporting Standards (IFRS) in the Iraqi banking sector. Motivated by growing evidence that the outcomes of IFRS adoption depend on institutional and market conditions, the study focuses on a [...] Read more.

This study examines the economic consequences associated with the mandatory adoption of International Financial Reporting Standards (IFRS) in the Iraqi banking sector. Motivated by growing evidence that the outcomes of IFRS adoption depend on institutional and market conditions, the study focuses on a bank-based emerging economy characterized by relatively underdeveloped capital markets and evolving enforcement mechanisms. Using a balanced panel of 24 banks listed on the Iraq Stock Exchange over the period 2014–2018, the analysis exploits the mandatory IFRS adoption in 2016 within a before–after regulatory framework. Panel regression techniques are employed to examine the associations between IFRS adoption and stock market liquidity, firm value, information asymmetry, and the cost of debt, while controlling for bank-specific characteristics and macroeconomic conditions. The results indicate that IFRS adoption is positively significantly associated with stock market liquidity, and negatively significantly associated with information asymmetry, consistent with improvements in the informational environment of Iraqi banks following enhanced disclosure and comparability. The findings also reveal a positive and significant relationship between IFRS adoption and the cost of debt, suggesting higher perceived financial risk by creditors. In contrast, no statistically significant association is observed between IFRS adoption and bank market valuation, highlighting the limited sensitivity of equity prices to accounting reforms in thin and institutionally constrained markets. Overall, the study contributes to the literature on the economic consequences of IFRS adoption by providing evidence from an underexplored emerging market and a highly regulated banking sector. The findings underscore the role of institutional context in shaping the outcomes of accounting standard convergence and offer policy-relevant insights for regulators and standard-setters in bank-oriented financial systems. Full article

(This article belongs to the Special Issue Accounting, Finance, Banking in Emerging Economies)

26 pages, 702 KB

Open AccessArticle

Risk Perception, Trust, and Investor Awareness in Crypto-Crowdfunding: An Empirical Analysis

by Gioia Arnone

J. Risk Financial Manag. 2026, 19(4), 288; https://doi.org/10.3390/jrfm19040288 - 17 Apr 2026

Viewed by 1203

Abstract

The rapid evolution of fintech has accelerated the integration of blockchain technology and cryptocurrencies into crowdfunding platforms, reshaping entrepreneurial finance and challenging traditional conceptions of money, intermediation, and financial risk. This study empirically examines the socio-cultural, demographic, and behavioural factors influencing funders’ perceptions [...] Read more.

The rapid evolution of fintech has accelerated the integration of blockchain technology and cryptocurrencies into crowdfunding platforms, reshaping entrepreneurial finance and challenging traditional conceptions of money, intermediation, and financial risk. This study empirically examines the socio-cultural, demographic, and behavioural factors influencing funders’ perceptions and investment decisions in crypto-crowdfunding, an emerging model situated at the intersection of digital currencies, financial inclusion, and decentralised capital formation. Using primary survey data from a focus group of 50 respondents measuring perceptions through a structured five-point Likert questionnaire, the analysis investigates how risk perception, trust and security, investor awareness, and perceived benefits shape participation in crypto-crowdfunded projects. The findings indicate that blockchain-based features such as transparency and decentralisation are associated with variations in perceived trust and risk assessment, rather than uniformly enhancing investor confidence. Socio-demographic characteristics emerge as significant determinants of investor awareness, perceived risks, and expected benefits, confirming pronounced behavioural heterogeneity in digital-finance participation. Regression results reveal strong interdependencies between trust, risk perception, and awareness, underscoring the importance of informational quality and risk-governance mechanisms in supporting sustainable adoption. By providing empirical evidence on individual-level determinants of participation in crypto-crowdfunding, the study contributes to the literature on the future of money by clarifying how crypto-crowdfunding operates as a behavioural-financial phenomenon embedded in decentralised governance structures. 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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43 pages, 626 KB

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The Moderating Effect of Economic Policy Uncertainty on the Relationship Between Working Capital Management Policy and Financial Distress: Evidence from Egyptian Firms

by Ghada Ahmed Nabil Ibrahim and Hoda Essam Hassan Khaled

J. Risk Financial Manag. 2026, 19(4), 287; https://doi.org/10.3390/jrfm19040287 - 16 Apr 2026

Viewed by 1269

Abstract

This study examines the impact of working capital management policy (WCMP), including working capital investment policy (WCIP), working capital financing policy (WCFP), and cash holding policy (CHP) on financial distress (FD) among non-financial firms listed on the Egyptian Stock Exchange during 2010–2024. FD [...] Read more.

This study examines the impact of working capital management policy (WCMP), including working capital investment policy (WCIP), working capital financing policy (WCFP), and cash holding policy (CHP) on financial distress (FD) among non-financial firms listed on the Egyptian Stock Exchange during 2010–2024. FD is proxied by the Altman Z-score, where higher values indicate lower distress risk. The study further investigates whether economic policy uncertainty (EPU) moderates the relationship between WCMP and FD. Using panel data analysis and the Fixed Effects Model, the results show that conservative WCIP and higher cash holdings significantly reduce FD risk, whereas greater reliance on short-term financing increases firms’ vulnerability to distress. The findings also reveal that EPU amplifies the effects of WCMP on FD. Overall, the study highlights the strategic importance of prudent liquidity management in enhancing firms’ financial resilience in emerging market environments characterized by macroeconomic uncertainty. Full article

(This article belongs to the Collection Financial Accounting)

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35 pages, 2173 KB

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UTAUT Antecedents Shaping Institutional Investors’ Intentions to Utilize ESG Information

by Jae Young Jang and So Ra Park

J. Risk Financial Manag. 2026, 19(4), 286; https://doi.org/10.3390/jrfm19040286 - 15 Apr 2026

Viewed by 1138

Abstract

This study examines how institutional investors adopt and utilize Environmental, Social, and Governance (ESG) information by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT). Using the Analytic Hierarchy Process (AHP) with expert-based pairwise comparisons from 20 senior investment professionals at [...] Read more.

This study examines how institutional investors adopt and utilize Environmental, Social, and Governance (ESG) information by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT). Using the Analytic Hierarchy Process (AHP) with expert-based pairwise comparisons from 20 senior investment professionals at major South Korean financial institutions, we identify and weight key determinants influencing ESG information use among South Korean institutional investors. The results show that performance expectancy emerged as the most influential determinant (33.7%), followed by facilitating conditions (24.6%), social influence (22.8%), and effort expectancy (18.9%). At the sub-criterion level, usefulness for investment decision-making (11.2%), institutional encouragement (10.2%), and utilization of ESG information as a fiduciary duty (9.4%) recorded the highest global weights, whereas psychological comfort in utilizing ESG information (2.0%) and practical guidelines and training programs (3.7%) exhibited the lowest. These findings suggest that ESG adoption has evolved beyond early legitimacy-seeking behavior toward substantive and performance-driven integration, consistent with UTAUT predictions that performance expectancy and facilitating conditions gain salience in mature adoption phases, while effort expectancy and social influence diminish. This weight distribution indicates that ESG has been internalized as core analytical infrastructure informing investment decision-making and risk management, rather than functioning as a peripheral compliance tool. By empirically mapping ESG adoption determinants into a hierarchical structure, this study contributes to the literature on ESG diffusion, institutional investor behavior, and adoption theory, offering practical implications for regulators and financial institutions seeking to deepen substantive ESG integration. Full article

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

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27 pages, 882 KB

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Digital Asset Inheritance: Perceptions, Readiness, and Challenges in a Developing Economy

by Pongsakorn Limna, Rattawut Nivornusit and Yarnaphat Shaengchart

J. Risk Financial Manag. 2026, 19(4), 285; https://doi.org/10.3390/jrfm19040285 - 15 Apr 2026

Viewed by 1513

Abstract

The rapid expansion of digital assets has transformed contemporary financial systems, yet their role in inheritance planning remains underexplored, particularly in developing economies. Employing a mixed-methods design, this study examines the factors influencing individuals’ acceptance of digital assets as inheritance and explores their [...] Read more.

The rapid expansion of digital assets has transformed contemporary financial systems, yet their role in inheritance planning remains underexplored, particularly in developing economies. Employing a mixed-methods design, this study examines the factors influencing individuals’ acceptance of digital assets as inheritance and explores their perceptions and readiness to adopt such assets within estate planning in Thailand. The quantitative phase analyzes survey data using descriptive statistics and binary logistic regression, focusing on investment experience, risk orientation, emotional responses to financial risk, financial capacity, and perceived suitability. The results indicate that investment orientation, discretionary financial capacity, familiarity with diverse digital asset types, and psychological resilience toward financial volatility significantly increase acceptance, with Preferred Investment Group emerging as the strongest predictor. In contrast, anxiety toward high-risk investments reduces acceptance. Qualitative findings, derived from content analysis of in-depth interviews, reveal persistent skepticism regarding asset stability, legal and institutional uncertainty, technological barriers, and subjective valuation. Despite these concerns, participants expressed conditional readiness to adopt digital assets in inheritance planning given clearer legal frameworks, professional guidance, and user-friendly technologies. This study contributes to the emerging literature on digital wealth transfer and offers practical implications for policymakers, financial advisors, and legal professionals seeking to develop regulatory frameworks, financial literacy initiatives, and technological infrastructures that support the secure intergenerational transfer of digital assets. Full article

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

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15 pages, 264 KB

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Digital Financial Inclusion and Economic Growth: Multi-Dimensional Evidence from Coverage, Depth, and Digitisation

by Shancheng Hu, Weiyi Xiang and Yichao Wan

J. Risk Financial Manag. 2026, 19(4), 284; https://doi.org/10.3390/jrfm19040284 - 14 Apr 2026

Viewed by 965

Abstract

Using panel data from 278 Chinese prefecture-level cities during 2011–2019, this study employs two-way fixed effects and instrumental variable (2SLS) models to investigate how the distinct dimensions of digital financial inclusion (DFI)—coverage breadth, usage depth, and digitisation level—affect urban economic growth. The results [...] Read more.

Using panel data from 278 Chinese prefecture-level cities during 2011–2019, this study employs two-way fixed effects and instrumental variable (2SLS) models to investigate how the distinct dimensions of digital financial inclusion (DFI)—coverage breadth, usage depth, and digitisation level—affect urban economic growth. The results reveal substantial heterogeneity across these DFI dimensions. The expansion of coverage breadth significantly and robustly promotes city-level economic growth. In contrast, greater usage depth exerts a negative effect, possibly due to regulatory lags in internet credit and insurance that intensify financial risks. The digitisation level shows a positive but statistically insignificant impact, indicating that digital infrastructure has not yet been fully transformed into growth-enhancing productivity. Furthermore, the regional heterogeneity analysis reveals a stark divergence: DFI acts as a crucial growth engine in the financially underserved central and western regions, whereas excessive financialisation has exerted a crowding-out effect in eastern cities. These findings suggest that policy efforts should prioritise broadening DFI coverage while strengthening the regulation of usage-related activities, thereby balancing financial innovation with systemic stability. Full article

(This article belongs to the Special Issue Digital Finance and Economic Transformation in the New Era)

13 pages, 638 KB

Open AccessArticle

Entropy-Filtered Machine Learning for Risk-Aware Algorithmic Trading and Portfolio Decision Making

by Florentin Șerban and Bogdan Petru Vrinceanu

J. Risk Financial Manag. 2026, 19(4), 283; https://doi.org/10.3390/jrfm19040283 - 14 Apr 2026

Viewed by 1069

Abstract

Modern financial markets are increasingly shaped by algorithmic trading systems and artificial intelligence techniques that process large volumes of financial data in real time. However, machine learning-based trading systems often suffer from signal instability and excessive sensitivity to market noise, which may lead [...] Read more.

Modern financial markets are increasingly shaped by algorithmic trading systems and artificial intelligence techniques that process large volumes of financial data in real time. However, machine learning-based trading systems often suffer from signal instability and excessive sensitivity to market noise, which may lead to overtrading and increased financial risk. In highly volatile environments such as cryptocurrency markets, the reliability of trading signals becomes a critical issue for both portfolio allocation and risk management. This study proposes an entropy-filtered machine learning framework designed to enhance the stability and risk-awareness of algorithmic trading strategies. The proposed approach integrates entropy-based filtering techniques with machine learning classifiers in order to reduce noise in market signals, thereby improving the risk-adjusted stability of trading strategies. Entropy measures are employed as a filtering mechanism that evaluates the informational content of predictive signals and suppresses unreliable model outputs. The empirical analysis is conducted using cryptocurrency market data, where the entropy-filtered framework is applied to trading signal generation and decision making. The results indicate that the proposed approach improves the stability of trading signals and reduces the occurrence of false signals compared to conventional machine learning models. In addition, entropy filtering contributes to a more balanced risk–return profile and enhances the overall robustness of trading strategies. Moreover, entropy filtering contributes to a more balanced risk–return profile and enhances the overall robustness of trading strategies. The findings suggest that entropy-based filtering substantially improves the reliability and risk-awareness of machine learning trading systems, providing a promising direction for the development of more robust AI-driven financial decision frameworks. Full article

(This article belongs to the Special Issue Advanced Methods in AI-Driven Portfolio Optimization and Financial Risk Management)

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15 pages, 588 KB

Open AccessArticle

The Irrelevance of Lending-Value Constraints in Long-Term Portfolio Optimization: A Twenty-Year Analysis Spanning Two Financial Crises

by Leonardo Cid, Arturo Cifuentes and Michael McAdams

J. Risk Financial Manag. 2026, 19(4), 282; https://doi.org/10.3390/jrfm19040282 - 14 Apr 2026

Viewed by 749

Abstract

This study examines the potential benefits of incorporating a lending-value criterion into the design of portfolios with long-term objectives. Because such portfolios often include significant positions in illiquid assets—typically difficult to sell under stressful market conditions—it has been argued that they should be [...] Read more.

This study examines the potential benefits of incorporating a lending-value criterion into the design of portfolios with long-term objectives. Because such portfolios often include significant positions in illiquid assets—typically difficult to sell under stressful market conditions—it has been argued that they should be designed with this constraint in mind. The underlying idea is that portfolios with adequate borrowing capacity may be better able to withstand adverse market conditions and thus avoid the losses incurred when managers are forced to sell assets under duress. Using returns data over a twenty-year period, which included two major financial crises, the study finds that the potential benefits of this approach are minimal. In other words, adding a lending-value constraint to the optimization problem is largely irrelevant, since in most cases the constraint is not binding. Put differently, the asset weights selected under the standard optimization framework already yield portfolios with an adequate lending value. Full article

(This article belongs to the Special Issue Portfolio Choice and Asset Allocation)

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25 pages, 2824 KB

Open AccessArticle

Unsupervised Machine Learning for Financial Behavior Profiling of Tourism Firms in Barranquilla, Colombia

by Leidy Haidy Perez Coronell, Tomás José Fontalvo Herrera, Gloria Naranjo Africano, Emiro De-La-Hoz-Franco, José Escorcia-Gutierrez and Tito José Crissien Borrero

J. Risk Financial Manag. 2026, 19(4), 281; https://doi.org/10.3390/jrfm19040281 - 13 Apr 2026

Viewed by 734

Abstract

This study aims to identify and characterize the financial profiles of tourism-sector firms in Barranquilla through the application of unsupervised Machine Learning techniques, with the purpose of analyzing patterns of financial behavior based on profitability, capital structure, and liquidity. The research adopts a [...] Read more.

This study aims to identify and characterize the financial profiles of tourism-sector firms in Barranquilla through the application of unsupervised Machine Learning techniques, with the purpose of analyzing patterns of financial behavior based on profitability, capital structure, and liquidity. The research adopts a quantitative and descriptive design, using secondary financial data for fiscal year 2024 obtained from the Barranquilla Chamber of Commerce. The initial sample comprised 563 active tourism firms. Based on basic accounting variables, normalized financial indicators were constructed through a feature engineering process that included correlation analysis, variable selection, and robust scaling. A range of clustering algorithms representing different methodological paradigms as partitional, hierarchical, density-based, and probabilistic, were evaluated using a multicriteria validation framework combining internal cluster quality metrics and cluster size balance. The OPTICS algorithm was selected as the most suitable method for the final segmentation. The results revealed two regular financial clusters and a group of atypical firms. One cluster corresponds to firms with no observable financial activity, characterized by zero profitability, absence of leverage, and exclusive reliance on equity financing. The second cluster groups financially active firms exhibiting high indebtedness, low equity participation, negative profitability, and liquidity constraints, reflecting conditions of financial distress. Non-parametric statistical tests confirmed significant differences between clusters, primarily in indicators related to capital structure and profitability, while firm size did not account for the observed segmentation. Overall, the findings demonstrate that behavior-based financial segmentation supported by unsupervised Machine Learning and normalized financial ratios enables the identification of robust and interpretable financial archetypes, with capital structure and profitability emerging as the main differentiating factors. Full article

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

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17 pages, 306 KB

Open AccessArticle

Enterprise Risk Management and Cyber Fraud Mitigation: Evidence from Indonesian State-Owned Enterprises

by Imam Ghozali, Raden Roro Karlina Aprilia Kusumadewi, Hersugondo Hersugondo and Imang Dapit Pamungkas

J. Risk Financial Manag. 2026, 19(4), 280; https://doi.org/10.3390/jrfm19040280 - 13 Apr 2026

Viewed by 1124

Abstract

This study examines the role of Enterprise Risk Management (ERM) in mitigating cyber fraud in Indonesian State-Owned Enterprises (SOEs). As digital transformation increases organizational exposure to cyber risks, effective risk governance mechanisms become essential for safeguarding financial integrity. This research investigates how ERM [...] Read more.

This study examines the role of Enterprise Risk Management (ERM) in mitigating cyber fraud in Indonesian State-Owned Enterprises (SOEs). As digital transformation increases organizational exposure to cyber risks, effective risk governance mechanisms become essential for safeguarding financial integrity. This research investigates how ERM implementation is associated with cyber fraud prevention and detection within SOEs. The study employs a mixed-methods approach using quantitative firm-year observations from 48 non-financial SOEs during the 2020–2024 period, resulting in 112 pooled observations, complemented by qualitative insights from 25 key informants, including auditors, risk officers, and IT/cybersecurity specialists. The empirical analysis indicates that stronger ERM implementation is positively associated with higher levels of cyber fraud mitigation and improved coordination between financial risk management and information technology governance. The findings also highlight the importance of integrated risk governance structures in strengthening internal controls and organizational resilience against digital threats. However, given the cross-sectional and perception-based nature of the data, the findings should be interpreted as associative rather than causal relationships. This study contributes to the literature on risk governance and digital risk management by providing empirical evidence on the role of ERM in supporting financial accountability and cyber risk mitigation in emerging market SOEs. Full article

(This article belongs to the Topic Artificial Intelligence, Banking, and Financial Risk Management)

40 pages, 1626 KB

Open AccessArticle

ESG Determinants of Financial Development: Integrating Econometrics and Machine-Learning Evidence

by Angelo Leogrande, Massimo Arnone, Alberto Costantiello and Carlo Drago

J. Risk Financial Manag. 2026, 19(4), 279; https://doi.org/10.3390/jrfm19040279 - 13 Apr 2026

Viewed by 1395

Abstract

The objective of this research is to analyze the relationship between ESG factors and financial development, measured by Domestic Credit to the Private Sector by Banks (DCB). The empirical analysis employs a balanced panel of 82 countries for the years 2016 to 2022, [...] Read more.

The objective of this research is to analyze the relationship between ESG factors and financial development, measured by Domestic Credit to the Private Sector by Banks (DCB). The empirical analysis employs a balanced panel of 82 countries for the years 2016 to 2022, obtained from the World Bank database. The proposed econometric model incorporates multiple ESG factors, including environmental (E), social (S), and governance (G). The list of econometric models under consideration includes fixed effects, random effects, WLS (weighted least squares), dynamic panel, and fixed effects with HAC estimation. Based on the conducted tests, the fixed effects estimation method has been chosen because the presence of serial correlation, heteroskedasticity, and cross-sectional dependence suggests that other methods will not provide an adequate model. As a result, fixed effects enable obtaining reliable estimates regarding the relationships between ESG factors and DCB. In addition, a KNN (K-Nearest Neighbors) regression was used to analyze potential nonlinear effects of the factors. The results show the strong positive relationship between ESG factors and financial development. More specifically, the presence of clean energy sources is associated with a positive DCB, and the depletion of natural resources is negatively associated with DCB. Moreover, social and governance factors are positively associated with financial development. Full article

(This article belongs to the Special Issue Advancing Research in International Finance)

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20 pages, 557 KB

Open AccessArticle

The Determinants of Financial Flexibility: Evidence from JSE-Listed Non-Financial Firms

by Joseph Kayiira, Vusani Moyo and Freddy Munzhelele

J. Risk Financial Manag. 2026, 19(4), 278; https://doi.org/10.3390/jrfm19040278 - 11 Apr 2026

Viewed by 1072

Abstract

Corporate financial policy requires managers to balance financing, investment, and payout decisions while maintaining sufficient financial flexibility to respond to unexpected shocks and investment opportunities. Despite the importance of financial flexibility, limited empirical evidence exists on its determinants in African capital markets. Using [...] Read more.

Corporate financial policy requires managers to balance financing, investment, and payout decisions while maintaining sufficient financial flexibility to respond to unexpected shocks and investment opportunities. Despite the importance of financial flexibility, limited empirical evidence exists on its determinants in African capital markets. Using panel data from 106 non-financial firms listed on the Johannesburg Stock Exchange over the period 2000–2019, this study examines the determinants of financial flexibility. Financial flexibility is identified by comparing actual and predicted leverage and classifying firms with persistent spare debt capacity as financially flexible. The main empirical model is estimated as a random-effects linear probability model with heteroscedasticity-robust standard errors. The results show that financial flexibility is significantly negatively associated with leverage and Tobin’s Q, indicating that firms with higher debt levels and stronger growth opportunities are less likely to preserve borrowing capacity. Retained earnings and financing cost show weak negative associations at the 10% significance level, while dividend payout, profitability, cash holdings, and tangibility are statistically insignificant. The study contributes to the corporate finance literature by providing new evidence from an African emerging market context, incorporating payout policy into the financial flexibility framework, and showing how leverage discipline and growth-related financing demands shape firms’ financial flexibility. Full article

(This article belongs to the Special Issue Risk Management and Financial Decision-Making in Managerial Finance)

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17 pages, 326 KB

Open AccessArticle

The Impact of Trade Openness on Economic Activity and Tax Revenue in Developing Countries: Panel Evidence from the MENA Region

by Jihane Chahib, Zakariae Bel Mkaddem and Imane Tesse

J. Risk Financial Manag. 2026, 19(4), 277; https://doi.org/10.3390/jrfm19040277 - 10 Apr 2026

Viewed by 1166

Abstract

This paper examines the effect of trade openness on corporate tax revenue in the Middle East and North Africa (MENA) region, where increased economic integration might incite more business activity and expand taxable corporate income but also intensify losses due to practices such [...] Read more.

This paper examines the effect of trade openness on corporate tax revenue in the Middle East and North Africa (MENA) region, where increased economic integration might incite more business activity and expand taxable corporate income but also intensify losses due to practices such as profit shifting. The study follows a quantitative empirical approach and applies a panel ARDL model to secondary data collected from international databases (World Bank and IMF), such as GDP, trade openness (exports and imports as % of GDP), inflation, corporate tax revenues, foreign direct investment inflows and tax evasion via informal economies, for a sample of ten developing countries from the MENA region, including Morocco, Tunisia, Egypt, Jordan, Lebanon, Algeria, Saudi Arabia, Oman, the United Arab Emirates, and Bahrain, over the period 2010–2023. We employ a PMG ARDL model to study our panel data, allowing the analysis of both short-run and long-run effects to investigate the relationship between trade openness and tax revenues. Our results show that in the long run, export-driven economies generate higher corporate tax revenues by expanding profitability and the tax base, and imports also positively affect revenues, indicating that trade openness stimulates economic activity. Conversely, FDI inflows reduce corporate tax revenues, consistent with profit shifting and tax incentives in developing countries. GDP growth does not necessarily increase tax receipts, likely due to tax elasticity effects and growth-oriented tax structures. Also, tax evasion appears to decline, likely reflecting improved compliance, and no significant short-run effects are observed. The results contribute to the literature on tax compliance and economic integration in the case of open economies in developing countries. From a practical perspective, our findings have implications for policymakers and tax regulators in the MENA region, as they highlight the dual nature of globalization for developing countries and their tax systems and underscore the need for effective compliance measures in trade and investment policies. Full article

(This article belongs to the Section Economics and Finance)

15 pages, 926 KB

Open AccessArticle

Public Pensions, Trade Unions, and Employment in Manufacturing

by Emmanouil Apergis, Nicholas Apergis and Chi Keung Lau

J. Risk Financial Manag. 2026, 19(4), 276; https://doi.org/10.3390/jrfm19040276 - 10 Apr 2026

Viewed by 1187

Abstract

Demographic decline in many Organization for Economic Co-operation and Development (OECD) countries is widely considered the principal source of hurling public pension disbursements, whilst trade unions are often blamed for staunch antagonism towards any transformations that might alleviate the fiscal encumbrance. If financialization [...] Read more.

Demographic decline in many Organization for Economic Co-operation and Development (OECD) countries is widely considered the principal source of hurling public pension disbursements, whilst trade unions are often blamed for staunch antagonism towards any transformations that might alleviate the fiscal encumbrance. If financialization is state-acquiesced, with the state being considered fundamental for market integration and social regulation of markets to protect against market failures, how then should inter-generational equity be addressed? This work tests the hypothesis that deindustrialization (measured as the declining proportion of employment in manufacturing) and lower trade-union density are quintessential channels through which demographic change translates into ascending pension outlays. Using OECD data from 1960 to 2013, we utilize longitudinal and panel quantile statistical methods to dissect these links across assorted pension system clusters (total, mandatory private, mandatory public, mandatory public & voluntary, and mandatory public & private). This study highlights the mediating role of labor market structure in pension financing. Full article

(This article belongs to the Special Issue Pensions and Retirement Planning)

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17 pages, 293 KB

Open AccessArticle

ESG Disclosure and Financial Analysts’ Accuracy in Saudi Arabia: The Moderating Role of the 2021 ESG Guidelines

by Taoufik Elkemali

J. Risk Financial Manag. 2026, 19(4), 275; https://doi.org/10.3390/jrfm19040275 - 9 Apr 2026

Cited by 1 | Viewed by 566

Abstract

This study explores how environmental, social and governance (ESG) disclosure relates to analysts’ forecast accuracy in Saudi Arabia, focusing on the ESG disclosure guidelines introduced by the Saudi Stock Exchange (Tadawul) in 2021. It suggests that ESG disclosure enhances corporate transparency, decreases information [...] Read more.

This study explores how environmental, social and governance (ESG) disclosure relates to analysts’ forecast accuracy in Saudi Arabia, focusing on the ESG disclosure guidelines introduced by the Saudi Stock Exchange (Tadawul) in 2021. It suggests that ESG disclosure enhances corporate transparency, decreases information asymmetry, and provides analysts with additional non-financial information that can improve the earnings forecast quality. Furthermore, the introduction of ESG guidelines is likely to enhance the consistency and reliability of sustainability reporting, thereby strengthening the informational environment of the capital market. Based on a sample of listed firms from 2017 to 2024 and employing panel regression techniques, including fixed-effects and two-step system generalized method of moments (GMM) estimations, the results indicate that a higher ESG disclosure is associated with lower analyst forecast errors, reflecting an improved forecast accuracy. The findings also reveal that the forecast accuracy increased following the ESG guidelines’ introduction and that the connection between ESG disclosure and analysts’ forecast accuracy became greater after the implementation of the guidelines. Our results demonstrate the informational value of ESG disclosure and suggest that ESG reporting initiatives can boost the quality of financial information in emerging markets. Full article

(This article belongs to the Special Issue Emerging Trends and Innovations in Corporate Finance and Governance)

33 pages, 2020 KB

Open AccessArticle

Machine Learning, Thematic Feature Grouping, and the Magnificent Seven: A Forecasting Analysis

by Mirarmia Jalali, Mohammad Najand and Andrew Cohen

J. Risk Financial Manag. 2026, 19(4), 274; https://doi.org/10.3390/jrfm19040274 - 9 Apr 2026

Viewed by 1143

Abstract

This study examines the predictability of monthly excess returns for the “Magnificent Seven” U.S. technology firms using machine learning and economically motivated thematic feature grouping. Framed as a focused study of the most systemically consequential equity panel in modern markets—seven firms representing over [...] Read more.

This study examines the predictability of monthly excess returns for the “Magnificent Seven” U.S. technology firms using machine learning and economically motivated thematic feature grouping. Framed as a focused study of the most systemically consequential equity panel in modern markets—seven firms representing over 30% of the S&P 500—the analysis confronts a small-N, large-P environment where economically structured dimensionality reduction is essential. Using 154 firm-level characteristics categorized into 13 economic themes, we evaluate linear, penalized, tree-based, and neural network models in a small-N, large-P setting. Unrestricted models suffer substantial overfitting and fail to outperform the historical average benchmark out-of-sample. In contrast, theme-based models generate economically meaningful and regime-dependent predictive gains. Short-Term Reversal and seasonality exhibit stronger expansion-period predictability, while size and profitability perform better during recessions. Regularized linear models provide the most stable performance in limited-data environments, whereas nonlinear ensemble methods improve only when training windows are extended. The findings underscore the importance of economically structured dimensionality reduction and adaptive factor allocation in managing concentration risk among systemically important mega-cap firms. Full article

(This article belongs to the Section Financial Markets)

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16 pages, 292 KB

Open AccessArticle

Board Characteristics and Corporate Cash Flow Risk: Evidence from an Emerging Market

by Tuan Dang Anh and Huy Cao Tan

J. Risk Financial Manag. 2026, 19(4), 273; https://doi.org/10.3390/jrfm19040273 - 8 Apr 2026

Viewed by 872

Abstract

This study explores how board characteristics impact corporate cash flow risk in an emerging market setting. While previous research has examined firm risk, crash risk, and earnings quality, there is limited evidence on cash flow risk and its governance factors, especially in developing [...] Read more.

This study explores how board characteristics impact corporate cash flow risk in an emerging market setting. While previous research has examined firm risk, crash risk, and earnings quality, there is limited evidence on cash flow risk and its governance factors, especially in developing economies. To fill this gap, this study differentiates between volatility-based and distortion-based measures of cash flow risk and assesses how board attributes influence these aspects. Using a balanced panel of 327 non-financial firms listed in Vietnam from 2013 to 2023, cash flow risk is measured by the rolling five-year volatility of operating cash flows and short-term distortions shown in earnings–cash flow mismatches. To address endogeneity and dynamic persistence, the analysis uses the system generalized method of moments estimator, along with fixed-effects and feasible generalized least squares models for robustness. The findings suggest that board independence, gender diversity, and financial expertise are linked to lower cash flow risk, highlighting the importance of effective monitoring. Conversely, board meeting frequency is positively linked to risk, suggesting that boards tend to increase meeting frequency as a reactive response to heightened uncertainty. Board size and CEO duality do not show consistent effects. Focusing on Vietnam’s institutional context, this study provides evidence that governance mechanisms influence different dimensions of cash flow risk through separate channels, offering valuable insights for enhancing board effectiveness in emerging markets. Full article

(This article belongs to the Section Business and Entrepreneurship)

24 pages, 622 KB

Open AccessArticle

How Do IFRS S2 Climate Risks Affect IAS 36 Impairments? A Constructive Accounting Framework Calibrated to European Steel

by Khaled Muhammad Hosni Sobehy, Lassaad Ben Mahjoub and Sahbi Gabsi

J. Risk Financial Manag. 2026, 19(4), 272; https://doi.org/10.3390/jrfm19040272 - 8 Apr 2026

Viewed by 1360

Abstract

A major connectivity gap arises from the misalignment between the forward-looking climate disclosures required by IFRS S2 and the historically rooted asset valuations mandated by IAS 36. This misalignment can cause the overvaluation of carbon-intensive assets and disrupt capital allocation decisions. This research [...] Read more.

A major connectivity gap arises from the misalignment between the forward-looking climate disclosures required by IFRS S2 and the historically rooted asset valuations mandated by IAS 36. This misalignment can cause the overvaluation of carbon-intensive assets and disrupt capital allocation decisions. This research specifically examines transition risks, such as carbon pricing, regulatory shocks, and technological disruption, and quantifies the financial externality using a combination of deterministic impairment testing and stochastic climate scenarios. We create a constructive framework and develop a model of a Synthetic Representative Firm, calibrated to major integrated steel producers in Europe. To generate nonlinear Green Swan shocks for Value-in-Use, the process combines Monte Carlo simulation with the Merton Jump-Diffusion model. This comparison shows the difference between the steady Management View and the volatile Market View. Empirical results reveal a material Sustainability Discount, representing a substantial erosion in the recoverable amount under IFRS S2 transition risk scenarios compared to the IAS 36 Deterministic Baseline. Simulations show a strong probability of asset stranding due to restricted cost pass-through, indicating that older assets may face elevated impairment risks under disorderly transition scenarios. Traditional deterministic models may not fully capture aspects of Double Materiality, potentially leaving balance sheets less responsive to transition risks. Integrating digitalization and the Circular Carbon Economy (CCE) framework presents a strategic method for averting value destruction. Therefore, this research supports the integration of stochastic transition risk modeling into impairment testing to achieve faithful financial representation. Full article

(This article belongs to the Topic Sustainable and Green Finance)

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23 pages, 873 KB

Open AccessArticle

When AI Disclosure Intensifies: Nonlinear Effects on Governance-Risk Disclosures in Selected U.S. Public Firms

by Marco I. Bonelli

J. Risk Financial Manag. 2026, 19(4), 271; https://doi.org/10.3390/jrfm19040271 - 8 Apr 2026

Viewed by 1228

Abstract

Artificial intelligence (AI) has become increasingly prominent in corporate disclosure, yet its relationship with governance-risk disclosure remains unclear. This study examines whether AI disclosure intensity is nonlinearly associated with governance-risk disclosures among selected U.S. public firms. Drawing on competing governance mechanisms, it argues [...] Read more.

Artificial intelligence (AI) has become increasingly prominent in corporate disclosure, yet its relationship with governance-risk disclosure remains unclear. This study examines whether AI disclosure intensity is nonlinearly associated with governance-risk disclosures among selected U.S. public firms. Drawing on competing governance mechanisms, it argues that rising AI disclosure may initially coincide with heightened control and accountability concerns during periods of organizational and technological transition, but at higher levels may be associated with more stable governance-reporting environments. Using a balanced panel of 53 selected large U.S. public firms observed from 2020 to 2024, the study measures AI disclosure intensity through dictionary-based counts of AI-related terminology in annual Form 10-K filings and captures governance-risk disclosure through references to internal-control weaknesses, restatements, non-reliance statements, and regulatory investigations. Firm and year fixed-effects models with a quadratic specification indicate a robust inverted U-shaped association: governance-risk disclosures rise at low to moderate levels of AI disclosure intensity and decline at higher levels. The findings support a stage-dependent interpretation of AI-related disclosure patterns while underscoring that the evidence is disclosure-based rather than a direct measure of AI governance capability or implementation quality. Full article

(This article belongs to the Special Issue Emerging Trends and Innovations in Corporate Finance and Governance)

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23 pages, 740 KB

Open AccessArticle

The Effect of Innovation on Climate Resilience in Developing Countries: Evidence from a Panel Quantile Regression Approach

by Kesaobaka Mmelesi and Joel Hinaunye Eita

J. Risk Financial Manag. 2026, 19(4), 270; https://doi.org/10.3390/jrfm19040270 - 8 Apr 2026

Viewed by 945

Abstract

This study examines the effect of innovation on climate resilience in developing countries, covering annual data from 2008 to 2022, with a focus on how this relationship varies across different levels of vulnerability. The primary purpose is to understand whether innovation contributes uniformly [...] Read more.

This study examines the effect of innovation on climate resilience in developing countries, covering annual data from 2008 to 2022, with a focus on how this relationship varies across different levels of vulnerability. The primary purpose is to understand whether innovation contributes uniformly to climate resilience or if its impact differs depending on a country’s resilience status. Addressing this question is crucial for developing evidence-based and context-specific climate policies. To capture these heterogeneous effects, this study employs a panel quantile regression approach using data from developing countries. This method allows the estimation of the influence of innovation proxied by the Global Innovation Index (GII) and the climate resilience Index. The findings show that innovation has a consistently positive and statistically strong impact on climate resilience across all quantiles, with the strongest impact at the median. The results carry important policy implications. Firstly, developing countries should prioritize innovation-driven strategies to strengthen resilience across different climate risk profiles. Secondly, policies supporting renewable energy deployment should target countries with higher emissions to maximize their impact. Thirdly, fiscal tools, such as environmentally aligned tax policies, should be emphasized particularly in more vulnerable contexts. Finally, trade policies, population dynamics and integration of climate finance variables must be integrated into climate strategies to enhance long-term sustainability. Full article

(This article belongs to the Section Energy and Environment: Economics, Finance and Policy)

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