Risks

38 pages, 1971 KB

Open AccessArticle

Guaranteed Annuity Option Under Correlated and Regime-Switching Risks

by Jude Martin B. Grozen and Rogemar S. Mamon

Risks 2026, 14(2), 42; https://doi.org/10.3390/risks14020042 - 23 Feb 2026

Viewed by 992

Guaranteed annuity options (GAOs) allow policyholders to convert accumulated funds into life annuities at maturity at a guaranteed minimum rate. Thus, insurers are exposed to both investment and longevity risks. Accurate valuation of these long-term, survival-contingent contracts is essential for solvency assessment and [...] Read more.

Guaranteed annuity options (GAOs) allow policyholders to convert accumulated funds into life annuities at maturity at a guaranteed minimum rate. Thus, insurers are exposed to both investment and longevity risks. Accurate valuation of these long-term, survival-contingent contracts is essential for solvency assessment and risk management. Many existing approaches assume independence between interest rate and mortality risks. This paper develops a computationally efficient pricing framework for GAOs that jointly models interest and mortality rates as correlated stochastic processes with regime-switching dynamics governed by a finite-state continuous-time Markov chain. Model parameters are estimated using U.S. interest rates and cohort mortality data via quasi-maximum likelihood estimation. A semi-analytic valuation formula is derived based on the joint distribution of the underlying processes. Numerical results show that incorporating correlation and regime-switching materially increases GAO prices relative to conventional one-state models. The proposed semi-analytic approach delivers substantial computational advantages over standard Monte Carlo simulations. Sensitivity analysis further identifies the parameters most relevant for long-horizon pricing and solvency considerations. This highlights the practical relevance of the framework for managing longevity-linked guarantees under economic and demographic uncertainty. Full article

(This article belongs to the Special Issue Mathematical Methods Applied in Pricing and Investment Problems)

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36 pages, 776 KB

Open AccessArticle

Carbon Risk Without a Stable Premium: Nonlinear and State-Dependent Evidence from European ESG Leaders

by Eleonora Salzmann

Risks 2026, 14(2), 41; https://doi.org/10.3390/risks14020041 - 20 Feb 2026

Viewed by 611

Abstract

Despite the economic relevance of climate-transition risk, firm-level carbon exposure often fails to appear as a robustly priced factor when ESG measures and sustainability shocks are conflated. This study examines whether carbon exposure is conditionally priced in European equity returns using a strongly [...] Read more.

Despite the economic relevance of climate-transition risk, firm-level carbon exposure often fails to appear as a robustly priced factor when ESG measures and sustainability shocks are conflated. This study examines whether carbon exposure is conditionally priced in European equity returns using a strongly balanced quarterly panel of 238 firms from the MSCI Europe ESG Leaders universe (2018–2024). Total greenhouse gas emissions act as a proxy for carbon exposure, mapped to within-year percentiles and standardized by sector-year. Regressions control for ESG scores and controversies and include firm and quarter fixed effects with firm-clustered, dependence-robust standard errors. The linear carbon coefficient is small and statistically indistinguishable from zero, indicating no stable return premium from within-firm changes in carbon exposure. Functional-form tests reject linearity: quadratic and quintile specifications reveal curvature and a non-monotonic pattern, with return differences concentrated in the middle of the carbon distribution. Conditioning on macro-financial stress, measured by the ECB Composite Indicator of Systemic Stress, yields limited evidence of a uniform carbon penalty. However, high-controversy states are associated with lower returns, while ESG scores show negative associations under dependence-robust inference. Overall, carbon-related pricing appears to be nonlinear and state-dependent, whereas controversy risk is the most robust sustainability predictor of returns. Full article

18 pages, 424 KB

Open AccessFeature PaperArticle

How Framing Susceptibility Is Associated with Investment Grip: Evidence from Japanese Retail Investors

by Gideon Otchere-Appiah, Yu Kuramoto, Aliyu Ali Bawalle and Yoshihiko Kadoya

Risks 2026, 14(2), 40; https://doi.org/10.3390/risks14020040 - 14 Feb 2026

Viewed by 1100

Abstract

This study builds on the concept of loss tolerance by introducing investment grip, a behavioral interpretation that captures investors’ commitment to long-term objectives under adverse market conditions. While loss tolerance traditionally measures the maximum financial loss an investor can withstand, investment grip focuses [...] Read more.

This study builds on the concept of loss tolerance by introducing investment grip, a behavioral interpretation that captures investors’ commitment to long-term objectives under adverse market conditions. While loss tolerance traditionally measures the maximum financial loss an investor can withstand, investment grip focuses on the behavioral and psychological dimensions of maintaining long-term investment objectives when facing short-term setbacks, thus providing a more behaviorally grounded and operationalizable approach for evaluating client risk profiles. The investment grip framework integrates insights from self-control theory, emotional regulation research, and goal-commitment models. Using data from 92,792 Japanese retail investors in the 2025 “Survey on Life and Money,” we examine how gain-framed and loss-framed messages are associated with investment grip, controlling for digital financial literacy and demographic, socioeconomic, and psychological factors. Our findings reveal that loss framing is robustly associated with stronger investment grip, whereas gain framing demonstrates no statistically meaningful effect. These findings offer new insights into Japanese household financial behavior, explaining why conservative savings patterns persist despite the availability of better investment alternatives. The results underscore the role of information framing in shaping household investment behavior, with implications for investor protection and financial communication policy. Full article

19 pages, 461 KB

Open AccessArticle

The Impact of Financial Derivatives on European Bank Value and Performance

by Bassam Al-Own, Mohannad Obeid Al Shbail, Zaid Jaradat and Ghaith N. Al-Eitan

Risks 2026, 14(2), 39; https://doi.org/10.3390/risks14020039 - 12 Feb 2026

Viewed by 971

Abstract

Using a panel dataset of 385 European bank-year observations covering the 2012 to 2022 period, this study aimed to investigate the impact of derivatives on bank value and performance. We used bank-level panel data and conducted several multivariate statistical analyses, i.e., ordinary least [...] Read more.

Using a panel dataset of 385 European bank-year observations covering the 2012 to 2022 period, this study aimed to investigate the impact of derivatives on bank value and performance. We used bank-level panel data and conducted several multivariate statistical analyses, i.e., ordinary least squares (OLS), random-effects, and feasible generalized least squares (FGLS) regressions, to examine the ways in which using derivatives for different purposes influences bank value and performance. The regression results indicated a positive and significant association between hedging derivatives and bank performance, while trading derivatives had a negative effect on bank performance and value. Furthermore, the findings suggest that using such derivatives for hedging does not enhance value. Regarding the practical implications of this study and banking sector soundness, financial market regulators and policymakers should be cautious of the potential negative consequences of extensive trading derivative use. In particular, maintaining an acceptable level in this regard is essential to ensuring that the costs of engaging in derivative markets do not surpass their benefits. Hedging through derivatives may not translate into higher bank value, thus managers should justify to investors how such hedging derivatives enhance shareholder wealth. Additional research could focus on whether using derivatives in the banking industry offers any palpable advantage in the intermediate to long term; whether their use by non-financial organizations has different implications that than of financial firms; and the extent to which such financial instruments are useful for enhancing bank value. Full article

(This article belongs to the Special Issue Financial Investment, Derivatives Hedging, and Risk Management)

18 pages, 1311 KB

Open AccessArticle

Bayesian Causal Inference for Credit Default Risk

by Sello Dalton Pitso and Taryn Michael

Risks 2026, 14(2), 38; https://doi.org/10.3390/risks14020038 - 12 Feb 2026

Viewed by 784

Abstract

Banks often assume that higher credit limits increase customer default risk because greater exposure appears to imply greater vulnerability. This reasoning, however, conflates correlation with causation. Whether increasing a customer’s credit limit truly raises the likelihood of default remains an open empirical question [...] Read more.

Banks often assume that higher credit limits increase customer default risk because greater exposure appears to imply greater vulnerability. This reasoning, however, conflates correlation with causation. Whether increasing a customer’s credit limit truly raises the likelihood of default remains an open empirical question that this work seeks to answer. We applied Bayesian causal inference to estimate the causal effect of credit limits on default probability. The analysis incorporated Directed Acyclic Graphs (DAGs) for causal structure, d-separation for identification, and Bayesian logistic regression using a dataset of 30,000 credit card holders in Taiwan (April–September 2005). Twenty-two confounding variables were adjusted for, covering demographics, repayment history, and billing and payment behavior. Continuous covariates were standardized, and posterior inference was performed using NUTS sampling with posterior predictive simulations to compute Average Treatment Effects (ATEs). We found that a one-standard-deviation increase in credit limit reduces default probability by 1.44 percentage points (94% HDI: [−2.0%, −1.0%]), corresponding to a 6.3% relative decline from the baseline default rate of 22.1%. The effect was consistent across demographic subgroups, with homogeneous treatment effects observed for age, education, and gender categories, and remained robust under sensitivity analysis addressing potential unmeasured confounding. The findings suggest that increasing credit limits can causally reduce default risk, likely by enhancing financial flexibility and lowering utilization ratios. These results have practical implications for credit policy design and motivate further investigation into mechanisms and applicability across broader lending environments. These estimates are explicitly interpreted as context-specific causal effects for a pre-crisis consumer credit environment, with external validity assessed conceptually rather than assumed. Full article

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18 pages, 1252 KB

Open AccessFeature PaperArticle

A VaR-Based Price-Based Unit Commitment Framework for Generation Asset Valuation Under Electricity Price Risk

by Shih-Ying Chen, Kuen-Lin Lin and Ming-Tang Tsai

Risks 2026, 14(2), 37; https://doi.org/10.3390/risks14020037 - 11 Feb 2026

Viewed by 431

Abstract

In deregulated electricity markets, Generation Companies (GENCOs) are exposed to substantial financial risk due to volatile and uncertain electricity prices. Traditional generation asset valuation approaches, which rely primarily on expected profit, fail to adequately capture downside risk under market uncertainty. This study proposes [...] Read more.

In deregulated electricity markets, Generation Companies (GENCOs) are exposed to substantial financial risk due to volatile and uncertain electricity prices. Traditional generation asset valuation approaches, which rely primarily on expected profit, fail to adequately capture downside risk under market uncertainty. This study proposes an integrated risk-aware framework for generation asset valuation by embedding Value-at-Risk (VaR) into a Price-Based Unit Commitment (PBUC) model. VaR is employed to quantify potential profit losses at different confidence levels, enabling GENCOs to explicitly assess downside exposure associated with electricity price fluctuations. Spot price uncertainty is modeled using the Delta-Normal approach based on historical PJM market data. The resulting nonlinear mixed-integer optimization problem is solved using an Improved Immune Algorithm (IIA) enhanced with the Taguchi Method to improve convergence stability and solution diversity. Case studies on the IEEE 15-unit system demonstrate that the proposed IIA consistently outperforms conventional evolutionary algorithms in terms of profitability, robustness, and convergence reliability. The VaR analysis further reveals pronounced left-tail risk in profit distributions, particularly during peak-load periods, highlighting the importance of risk-adjusted commitment strategies. The proposed framework provides a practical decision-support tool for GENCOs to balance profitability and downside risk in competitive electricity markets. Full article

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28 pages, 1869 KB

Open AccessArticle

Green Investment: Examining the Influencing Factors and Mechanisms on the Investment Willingness of China Retail Investors Towards Green Bonds

by Zhibin Tao

Risks 2026, 14(2), 36; https://doi.org/10.3390/risks14020036 - 11 Feb 2026

Viewed by 806

Abstract

As global climate and sustainable challenges gain more attention, green finance has emerged as a significant focus of worldwide financial reform, with green bonds serving as a key indicator. Retail investors, as an important part of the financial market, have a significant impact [...] Read more.

As global climate and sustainable challenges gain more attention, green finance has emerged as a significant focus of worldwide financial reform, with green bonds serving as a key indicator. Retail investors, as an important part of the financial market, have a significant impact on the development of green finance through their investment willingness. This study aims to explore the influencing factors and mechanisms on the investment willingness of China retail investors towards green bonds. Based on empirical analysis of data from 2219 valid respondents in China, carried out using the SEM method, the results suggest that perceived usefulness (PU), investment literacy (IL), and information transparency (IT) all positively influence retail investors’ willingness to invest in green bonds. Additionally, PU, IL, and IT contribute to fostering an open attitude toward change (OATC) among retail investors, which, in turn, significantly promotes their investment willingness. This study also identifies the mediation effect of OATC. The findings provide both theoretical and practical insights to promote the development of green finance, enhance market activity, and support policy frameworks. Full article

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22 pages, 465 KB

Open AccessArticle

Modeling Audit Outcomes Under Information Asymmetry: A Game-Theoretic Analysis of Delay and Fees

by Güler Ferhan Ünal Uyar, Mustafa Terzioğlu, Neylan Kaya and Aslıhan Ersoy Bozcuk

Risks 2026, 14(2), 35; https://doi.org/10.3390/risks14020035 - 9 Feb 2026

Viewed by 776

Abstract

This study models the auditor–client relationship as a strategic game shaped by two-sided information asymmetry and examines how this structure influences key audit outcomes, namely audit delay and audit fees, in Türkiye. Using a game-theoretic framework complemented by empirical analysis, the study analyzes [...] Read more.

This study models the auditor–client relationship as a strategic game shaped by two-sided information asymmetry and examines how this structure influences key audit outcomes, namely audit delay and audit fees, in Türkiye. Using a game-theoretic framework complemented by empirical analysis, the study analyzes independent audit reports dated 31 December 2024 for 201 Borsa Istanbul firms audited by Big Four auditors. Two ordinary least squares models are estimated: one for audit delay and one for the logarithm of audit fees. The findings indicate that firm size and effort-related cost proxies play a central role in explaining audit fees, reflecting scale-related audit complexity. Financial risk, while not significantly associated with audit fees, is found to be negatively related to audit delay, suggesting that riskier firms may accelerate the reporting process through stronger monitoring, earlier planning, or tighter regulatory scrutiny. Audit opinion, by contrast, does not exhibit a statistically meaningful association with reporting delay, likely due to limited variation within the sample. Overall, the results partially support the risk–effort–cost mechanism proposed by the game-theoretic framework and highlight how institutional features of the Turkish audit market shape the relationship between risk and reporting timeliness. The study contributes to the literature by framing the audit process as a strategic decision environment and by providing updated evidence from an emerging market context. Full article

45 pages, 9784 KB

Open AccessArticle

Building a Life Table for Lebanon: Towards a Deeper Understanding of Our Future

by Natalia Bou Sakr, Stéphane Loisel, Gihane Mansour and Yahia Salhi

Risks 2026, 14(2), 34; https://doi.org/10.3390/risks14020034 - 5 Feb 2026

Viewed by 739

Abstract

Lebanon does not have a national mortality table that reflects its demographic and health conditions. Despite ongoing changes in mortality patterns driven by economic crises, political instability, and social changes, outdated foreign tables such as AM80 remain in use in the insurance and [...] Read more.

Lebanon does not have a national mortality table that reflects its demographic and health conditions. Despite ongoing changes in mortality patterns driven by economic crises, political instability, and social changes, outdated foreign tables such as AM80 remain in use in the insurance and public sectors. This dependency introduces significant risks in actuarial calculations, policy design, and long-term planning. This study addresses this gap by building a mortality table specifically adapted to the Lebanese insurance context, together with a first estimation of population-level mortality. In the absence of any official mortality database, we collaborated directly with local insurance companies to access and organize internal records of insured lives. These data, which represent one of the few available structured sources of mortality information in the country, form the core of our analysis. We apply actuarial methods to estimate age-specific death rates and life expectancy and benchmark the results against national and international references to assess consistency and range. By offering a locally grounded, data-driven alternative to imported mortality assumptions, this work fills a critical statistical need. The resulting table supports more accurate forecasting, pricing, and demographic modeling, with applications across insurance, pensions, and public health planning in Lebanon. Full article

(This article belongs to the Special Issue Advances in Risk Models and Actuarial Science)

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23 pages, 430 KB

Open AccessArticle

Risk or Reward? Assessing the Market Value Implications of CSR Disclosure and Family Ownership

by Farzaneh Nassirzadeh, Davood Askarany and Fatemeh Keyvani

Risks 2026, 14(2), 33; https://doi.org/10.3390/risks14020033 - 3 Feb 2026

Viewed by 727

Abstract

This study investigates whether Corporate Social Responsibility Disclosure (CSRD) serves as a risk-mitigating or cost-inducing signal for firms’ market value in an emerging market. Utilising a panel dataset of 120 companies listed on the Tehran Stock Exchange (2015–2023) and employing content analysis alongside [...] Read more.

This study investigates whether Corporate Social Responsibility Disclosure (CSRD) serves as a risk-mitigating or cost-inducing signal for firms’ market value in an emerging market. Utilising a panel dataset of 120 companies listed on the Tehran Stock Exchange (2015–2023) and employing content analysis alongside panel regression and System GMM models, we find that disclosure quality in social, employee, and environmental dimensions is positively associated with market value, while customer-related disclosure is not. The role of family ownership is nuanced: baseline specifications suggest no broad moderating influence, yet robust dynamic modelling reveals that family ownership significantly enhances the positive market valuation of environmental disclosure. The primary contribution is a nuanced, dimension-specific analysis of CSRD’s value relevance, challenging blanket assumptions about family firm behaviour and offering granular, methodologically informed insights for stakeholders in institutionally complex environments. Full article

(This article belongs to the Special Issue Empirical Advances in Corporate Finance and Governance Under Emerging Risks and Strategic Challenges)

19 pages, 387 KB

Open AccessFeature PaperArticle

Mission Drift or Strategic Expansion? Non-Core Lending, Risk, and Capital in US Credit Unions

by Changjie Hu, Zhu Chen and Ting Cao

Risks 2026, 14(2), 32; https://doi.org/10.3390/risks14020032 - 2 Feb 2026

Viewed by 566

Abstract

This study investigates credit unions’ expansion into non-core lending and its association with risk and financial resilience. Using US credit union call report data from 1994 to 2024, we measure the share of purchased loans, lease receivables, and loans held for sale in [...] Read more.

This study investigates credit unions’ expansion into non-core lending and its association with risk and financial resilience. Using US credit union call report data from 1994 to 2024, we measure the share of purchased loans, lease receivables, and loans held for sale in non-core lending. We document robust conditional, within-credit-union associations that point to a clear risk trade-off. Credit unions with higher non-core exposure grow faster in terms of loans and membership but exhibit weaker financial buffers, including lower net worth ratios and weaker economic solvency, alongside higher delinquency. Decomposition tests indicate that loans held for sale are most strongly associated with adverse buffer and asset quality patterns, while purchased loans and lease receivables display smaller and less uniform relationships. Scale interactions suggest that these associations are generally weaker for larger institutions for both membership and assets. Post-COVID estimates indicate that the baseline relationships are broadly stable, while the growth link is becoming stronger. Full article

18 pages, 679 KB

Open AccessArticle

The Corrosive Grip: How Corruption Inhibits Green Finance in Enhancing Environmental Sustainability

by Levi Mbaka Matimbia, Abraham Deka, Huseyin Ozdeser and Sindiso Deka

Risks 2026, 14(2), 31; https://doi.org/10.3390/risks14020031 - 2 Feb 2026

Viewed by 641

Abstract

Ecological sustainability is one of the key dimensions of sustainable development in any economy. Developing economies exhibit high-risk levels in terms of political stability and corruption, thereby inhibiting them from successfully adopting techniques for ecological sustainability. A framework that comprises a strong financial [...] Read more.

Ecological sustainability is one of the key dimensions of sustainable development in any economy. Developing economies exhibit high-risk levels in terms of political stability and corruption, thereby inhibiting them from successfully adopting techniques for ecological sustainability. A framework that comprises a strong financial system for green financial investment, coupled with correct policy frameworks becomes fundamental in the attainment of sustainable environments. Pervasive corruption in developing nations is a formidable barrier that impedes financial development and undermines green finance initiatives’ efficacy in fostering ecological sustainability. This research takes the data of the Central African nations, which is analyzed with the ‘Methods of Moments Quantile Regression’ technique. The major results presented show that digitalization, renewable energy, and governance support ecological sustainability. Institutional quality and green finance are expected to increase ecological sustainability, but the findings show that in the Central African countries with high corruption they tend to reduce ecological sustainability. The poor institutional quality in the Central African nations, because of high corruption and political instabilities, impedes the efficacy of financial development and green finance in advancing ecological sustainability. The Central African nations can achieve sustainability by fostering digitalization and renewable energy, as well as reducing corruption and political instabilities. Full article

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25 pages, 3568 KB

Open AccessArticle

Entropic Geometry and Information Dynamics in Green Cryptocurrency Markets

by Sana Gaied Chortane and Kamel Naoui

Risks 2026, 14(2), 30; https://doi.org/10.3390/risks14020030 - 2 Feb 2026

Viewed by 630

Abstract

Cryptocurrencies play a central role in modern financial markets; however, geopolitical tensions and environmental concerns raise critical questions about their stability and informational efficiency. This study distinguishes between green cryptocurrencies (GCs), based on low-energy validation mechanisms, and dirty cryptocurrencies (DCs), which rely on [...] Read more.

Cryptocurrencies play a central role in modern financial markets; however, geopolitical tensions and environmental concerns raise critical questions about their stability and informational efficiency. This study distinguishes between green cryptocurrencies (GCs), based on low-energy validation mechanisms, and dirty cryptocurrencies (DCs), which rely on energy-intensive protocols, to examine their behaviour under geopolitical stress. The objective of this paper is to assess how information dynamics, market resilience, and efficiency differ between GCs and DCs during periods of heightened geopolitical uncertainty, with particular focus on the Russia–Ukraine war. Using daily data from 28 April 2019 to 5 October 2023, we employ advanced information-theoretic measures, including mutual information, the rolling local nearest-neighbour entropy estimator (RLNNEE), and approximate entropy. The results show that DCs exhibit stronger information dominance than GCs, with this gap widening during the conflict. In contrast, GCs display lower but more stable mutual information, indicating greater informational resilience. Approximate entropy further reveals a decline in market complexity during the war period. Overall, the findings highlight the relevance of entropy-based tools for evaluating stability and risk in cryptocurrency markets facing geopolitical shocks. Full article

(This article belongs to the Special Issue Stochastic Modelling in Financial Mathematics, 2nd Edition)

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23 pages, 2225 KB

Open AccessArticle

Financial Stability Under Climate Stress: Empirical Evidence from Namibia

by Jaungura Kaune, Andy Esterhuizen and Valdemar J. Undji

Risks 2026, 14(2), 29; https://doi.org/10.3390/risks14020029 - 2 Feb 2026

Viewed by 692

Abstract

Climate change has emerged as one of the defining risks in recent years. These risks are associated with economic losses and, ultimately, the stability of the financial system. This study examines the impact of climate change on financial stability in Namibia using quarterly [...] Read more.

Climate change has emerged as one of the defining risks in recent years. These risks are associated with economic losses and, ultimately, the stability of the financial system. This study examines the impact of climate change on financial stability in Namibia using quarterly data spanning from the period 2009 to 2023. The Nonlinear Autoregressive Distributed Lag (NARDL) approach is employed to assess how climate change asymmetrically affects the stability of Namibia’s financial system. The findings reveal that both increases and decreases in rainfall, as well as higher temperatures, exert negative long-term asymmetric effects on financial stability, while rises in CO₂ emissions appear to enhance it. Accordingly, this study recommends the integration of climate-related risks into financial institutions’ risk assessment frameworks, together with the adoption of long-term monitoring and mitigation strategies. Finally, regulators are also encouraged to conduct climate stress tests to assess the resilience of the financial system under varying climate scenarios. Full article

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

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22 pages, 482 KB

Open AccessArticle

Corporate Leverage and Geopolitical Risks: Evidence from Vietnam

by Nam Thinh Vong and Thinh Tien Bui

Risks 2026, 14(2), 28; https://doi.org/10.3390/risks14020028 - 1 Feb 2026

Viewed by 1318

Abstract

This study investigates the impacts of geopolitical risks on corporate leverage decisions of Vietnamese listed firms from 2017 to 2024. The research findings reveal a negative impact of geopolitical risks on both corporate leverage and short-term leverage. That is, Vietnamese listed firms actively [...] Read more.

This study investigates the impacts of geopolitical risks on corporate leverage decisions of Vietnamese listed firms from 2017 to 2024. The research findings reveal a negative impact of geopolitical risks on both corporate leverage and short-term leverage. That is, Vietnamese listed firms actively reduce corporate leverage and short-term leverage as firms face rising geopolitical risks and uncertainties. Additionally, the effects of geopolitical risks are more pronounced for financially unconstrained firms, HOSE- and HNX-listed firms. Based on the main findings, policymakers at government levels and managers at corporate levels should consider the impacts of geopolitical risks when designing and implementing new policies in order to mitigate the negative effects of these risks and increase the resilience of Vietnamese firms considering geopolitical risks and uncertainties. Full article

(This article belongs to the Special Issue Emerging Risks in Banking and Finance: Technological Disruption, Climate Change, and Geopolitical Tensions)

35 pages, 3963 KB

Open AccessFeature PaperArticle

Systemic Risk Transmission in Commodity Markets

by Irina Georgescu

Risks 2026, 14(2), 27; https://doi.org/10.3390/risks14020027 - 1 Feb 2026

Viewed by 892

Abstract

This paper investigates tail-risk transmission and asymmetric dependence in commodity markets using an asymmetric fuzzy vine copula framework applied to gold, crude oil, natural gas, and silver from 1 January 2015 to 1 January 2025, extracted from Yahoo Finance. Bootstrap-based trapezoidal fuzzy numbers [...] Read more.

This paper investigates tail-risk transmission and asymmetric dependence in commodity markets using an asymmetric fuzzy vine copula framework applied to gold, crude oil, natural gas, and silver from 1 January 2015 to 1 January 2025, extracted from Yahoo Finance. Bootstrap-based trapezoidal fuzzy numbers are used to estimate fuzzy tail dependence, VaR, and CoVaR, capturing both sampling variability and parameter uncertainty. Results show generally weak and symmetric dependence among commodities, except for strong lower-tail dominance between crude oil and natural gas, indicating downside contagion within the energy sector. Adding the SKEW index as a market-implied tail-risk proxy has negligible effects on dependence and spillovers, revealing that equity-market tail-risk sentiment does not influence commodity markets. Systemic risk remains localized within energy and precious-metal linkages, underscoring the need for sector-specific monitoring. Full article

(This article belongs to the Special Issue Fundamentals and Risk Factors in Commodity Markets)

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16 pages, 567 KB

Open AccessFeature PaperArticle

Insuring Algorithmic Operations: Liability Risk, Pricing, and Risk Control

by Zhiyong (John) Liu, Jin Park, Mengying Wang and He Wen

Risks 2026, 14(2), 26; https://doi.org/10.3390/risks14020026 - 31 Jan 2026

Viewed by 1059

Abstract

Businesses increasingly rely on algorithmic systems and machine learning models to make operational decisions about customers, employees, and counterparties. These “algorithmic operations” can improve efficiency but also concentrate liability in a small number of technically complex, drifting models. Algorithmic operations liability (AOL) risk [...] Read more.

Businesses increasingly rely on algorithmic systems and machine learning models to make operational decisions about customers, employees, and counterparties. These “algorithmic operations” can improve efficiency but also concentrate liability in a small number of technically complex, drifting models. Algorithmic operations liability (AOL) risk arises when these systems generate legally cognizable harm. We develop a simple taxonomy of AOL risk sources: model error and bias, data quality failures, distribution shift and concept drift, miscalibration, machine learning operations (MLOps) and integration failures, governance gaps, and ecosystem-level externalities. Building on this taxonomy, we outline a simple analysis of AOL risk pricing using some basic actuarial building blocks: (i) a confusion-matrix-based expected-loss model for false positives and false negatives; (ii) drift-adjusted error rates and stress scenarios; and (iii) credibility-weighted rates when insureds have limited experience data. We then introduce capital and loss surcharges that incorporate distributional uncertainty and tail risk. Finally, we link the framework to AOL risk controls by identifying governance, documentation, model-monitoring, and MLOps practices that both reduce loss frequency and severity and serve as underwriting prerequisites. Full article

(This article belongs to the Special Issue AI for Financial Risk Perception)

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15 pages, 2051 KB

Open AccessArticle

Interpretable Multi-Model Framework for Early Warning of SME Loan Delinquency

by Ardak Akhmetova, Assem Shayakhmetova and Nurken Abdurakhmanov

Risks 2026, 14(2), 25; https://doi.org/10.3390/risks14020025 - 31 Jan 2026

Viewed by 901

Abstract

The rapid expansion of small and medium enterprise (SME) lending has intensified the need for accurate and interpretable credit risk forecasting. Financial institutions must anticipate potential business loan delinquency to maintain portfolio stability and meet regulatory standards. This study proposes an interpretable multi-model [...] Read more.

The rapid expansion of small and medium enterprise (SME) lending has intensified the need for accurate and interpretable credit risk forecasting. Financial institutions must anticipate potential business loan delinquency to maintain portfolio stability and meet regulatory standards. This study proposes an interpretable multi-model framework that integrates statistical (correlation screening and ordinary least squares regression), probabilistic (Gaussian Naïve Bayes), and classical time-series (SARIMA) methods to balance explanatory insight and predictive accuracy in delinquency forecasting. Ordinary least squares regression is used to quantify the direction and strength of each driver and yields statistically significant coefficients (β ≈ 1.336 for the overdue 15+ days bucket, p < 10⁻²²). The Naïve Bayes classifier provides a probabilistic early-warning signal with an out-of-sample accuracy of 55%, precision of 43%, recall of 75%, and ROC AUC of 0.371. Finally, a seasonal ARIMA model fitted on the selected regressors achieves a mean absolute percentage error (MAPE) of 7.6% and an out-of-sample R² of 0.49, demonstrating competitive forecasting performance while maintaining interpretability. The results show that the framework offers actionable insights for risk managers by identifying key risk drivers, providing probabilistic alarms, and generating calibrated point forecasts. The proposed approach contributes to the development of intelligent and explainable forecasting and control systems for modern financial institutions. Full article

(This article belongs to the Special Issue AI for Financial Risk Perception)

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27 pages, 3266 KB

Open AccessArticle

Monetary Asymmetry and ESG Governance in the Eurozone: Mapping Evolving Risk Narratives Through Bibliometric Analysis

by Alexandros Garefalakis, Erasmia Angelaki, Christos Papademetriou, Panagiotis Giannopoulos and Markos Kourgiantakis

Risks 2026, 14(2), 24; https://doi.org/10.3390/risks14020024 - 30 Jan 2026

Viewed by 636

Abstract

This paper investigates how monetary and ESG-related risks—especially those stemming from asymmetric policy transmission across Eurozone economies—have evolved over time, with a focus on the post-COVID-19 era. Using a mixed-method bibliometric analysis of 216 peer-reviewed articles (1996–2025), it maps thematic developments in monetary [...] Read more.

This paper investigates how monetary and ESG-related risks—especially those stemming from asymmetric policy transmission across Eurozone economies—have evolved over time, with a focus on the post-COVID-19 era. Using a mixed-method bibliometric analysis of 216 peer-reviewed articles (1996–2025), it maps thematic developments in monetary governance and sustainability discourse. Findings reveal a post-2020 surge in scholarly engagement, marked by a decisive shift: ESG risks, once peripheral, are now central to discussions of macro-financial stability and institutional resilience. This thematic realignment aligns with major EU regulatory milestones (e.g., SFDR, EU Taxonomy, CSRD), signaling a structural transformation in EU governance. The study concludes that the convergence of monetary asymmetry and ESG integration represents a new frontier in economic policy and academic inquiry, raising critical questions about institutional convergence, regulatory capacity, and sustainability-informed monetary frameworks in post-crisis Europe. Full article

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14 pages, 1488 KB

Open AccessFeature PaperArticle

A Framework for Interpreting Machine Learning Models in Bond Default Risk Prediction Using LIME and SHAP

by Yan Zhang, Lin Chen and Yixiang Tian

Risks 2026, 14(2), 23; https://doi.org/10.3390/risks14020023 - 28 Jan 2026

Cited by 1 | Viewed by 1280

Abstract

Interpretability analysis methods, such as LIME and SHAP, are widely employed to explain the predictions of artificial intelligence models; however, they primarily function as post hoc tools and do not directly quantify the intrinsic interpretability of the models. Although it is commonly assumed [...] Read more.

Interpretability analysis methods, such as LIME and SHAP, are widely employed to explain the predictions of artificial intelligence models; however, they primarily function as post hoc tools and do not directly quantify the intrinsic interpretability of the models. Although it is commonly assumed that model transparency decreases with increasing complexity, there is currently no standardized framework for evaluating interpretability as an inherent property of AI models. In this study, we examine the prediction of bond defaults using several widely used machine learning algorithms. The classification performance of each algorithm is first evaluated, followed by the application of LIME and SHAP to assess the influence of input features on model outputs. Based on these analyses, we propose a novel approach for quantifying intrinsic model interpretability. The results align with theoretical expectations and provide insights into the trade-off between model complexity and interpretability. Full article

(This article belongs to the Special Issue Artificial Intelligence Risk Management)

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Open AccessArticle

Can Macroprudential Policy for Retail Banks Reduce Bank Runs? Evidence from WAEMU’s Banking Sector

by Toure Talnan Aboulaye, Ouattara Zieh Moussa, Kacou Yves Thierry Kacou and Tuo Siele Jean

Risks 2026, 14(2), 22; https://doi.org/10.3390/risks14020022 - 28 Jan 2026

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Abstract

Motivated by the coexistence of retail and wholesale banks with distinct risk profiles under uniform capital regulation, and by the lack of quantitative evidence on whether differentiated capital requirements can reduce bank runs and interbank frictions in low-income monetary unions, this paper aims [...] Read more.

Motivated by the coexistence of retail and wholesale banks with distinct risk profiles under uniform capital regulation, and by the lack of quantitative evidence on whether differentiated capital requirements can reduce bank runs and interbank frictions in low-income monetary unions, this paper aims to determine a capital ratio for retail banks that can reduce the likelihood of bank runs in the WAEMU area. The study also compares the impact of imposing capital requirements on retail banks versus implementing the same level of regulation for wholesale banks. The key findings are as follows: A capital ratio of 10 percent for retail banks is found to be sufficient to reduce the probability of bank runs and mitigate interbank market frictions in the WAEMU area. Similarly, applying the same requirements to wholesale banks also reduces the likelihood of bank runs. Implementing capital requirements on retail banks does not significantly affect interbank lending costs, whereas imposing the same requirements on wholesale banks leads to an increase in these costs. Consequently, regulating retail banks tends to shift assets towards wholesale banks, while regulating wholesale banks reallocates assets towards retail banks. The calculated capital ratio of 10 percent for retail banks maximizes welfare, surpassing the welfare achieved when the same requirements are imposed on wholesale banks. Therefore, the same capital ratio offers greater stability benefits for retail banks than wholesale banks, highlighting the mismatch between uniform capital regulations and heterogeneous banking models. Full article

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Risks, Volume 14, Issue 2 (February 2026) – 21 articles

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