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Risks
Volume 14
Issue 3
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Risks, Volume 14, Issue 3 (March 2026) – 30 articles

Cover Story (view full-size image): The mean-variance rule (M-V) conforms with the expected utility paradigm only in limited and economically unacceptable scenarios. Thus, the most widely employed portfolio-selection rule seemingly loses ground. We show with the commonly employed utility functions in economics, with a preference for a positive skewness, that choosing from the M-V efficient frontier conforms with expected utility maximization even with long investment horizon and skewed distributions of returns. The economic loss induced by choosing from the M-V frontier is negligible. Thus, the M-V rule is universal, or almost universal, provided that the commonly employed utility functions in economics are employed. This is an astonishing result that even Markowitz has not dreamed of. View this paper
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27 pages, 1156 KB  
Article
Mixed Size-Biased Log-Normal Distribution with Truncated Normal Prior and Its Application in Insurance Ratemaking
by Taehan Bae, Jieun Kim and Jae Youn Ahn
Risks 2026, 14(3), 72; https://doi.org/10.3390/risks14030072 - 23 Mar 2026
Viewed by 236
Abstract
In the insurance literature, accurately predicting extreme losses has been a persistent and important problem. Recently, under the modelling framework of weighted distributions, several finite-mixture size-biased distributions, including size-biased Weibull and size-biased truncated log-normal distributions, have gained popularity for modelling heavy-tailed insurance claim [...] Read more.
In the insurance literature, accurately predicting extreme losses has been a persistent and important problem. Recently, under the modelling framework of weighted distributions, several finite-mixture size-biased distributions, including size-biased Weibull and size-biased truncated log-normal distributions, have gained popularity for modelling heavy-tailed insurance claim data. In this study, unlike existing models, we explicitly account for the individual heterogeneity commonly observed in insurance claims by treating the order of size-biased weighting as a continuous latent variable, thereby constructing a mixed size-biased distribution. In particular, we study the various distributional properties of the mixed log-normal distribution with a truncated normal prior, which serves as a conjugate prior for the size-biased log-normal model. For applications in non-life insurance, we discuss the Bayesian credibility premium and present an estimation of a regression model via the EM algorithm. We further conduct a real-data analysis using insurance loss data, comparing goodness-of-fit and tail risk measures with those of standard heavy-tailed distributions. Full article
(This article belongs to the Special Issue Statistical Models for Insurance)
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21 pages, 448 KB  
Article
Residualized Big Five Traits and Financial Risk Tolerance: Connecting Tolerance to Behavior
by John E. Grable and Eun Jin Kwak
Risks 2026, 14(3), 71; https://doi.org/10.3390/risks14030071 - 23 Mar 2026
Viewed by 257
Abstract
Research on financial risk tolerance and risk-taking increasingly incorporates personality traits into predictive and descriptive models of risk-taking behavior; however, intercorrelations among traits can obscure the unique contributions of individual traits. This is known as the suppressor effect. This study employed a two-stage [...] Read more.
Research on financial risk tolerance and risk-taking increasingly incorporates personality traits into predictive and descriptive models of risk-taking behavior; however, intercorrelations among traits can obscure the unique contributions of individual traits. This is known as the suppressor effect. This study employed a two-stage analytic framework to test and adjust for suppressor effects across the Big Five personality dimensions in describing financial risk tolerance. In Stage 1, correlation and OLS regression analyses identified suppression patterns, revealing that the explanatory validity of some factors was distorted by shared variance. In Stage 2, suppression-adjusted trait estimates were used to reassess their unique association with financial risk-taking mediated through financial risk tolerance. Results indicate that Openness to Experience and Extraversion are the strongest descriptors of financial risk-taking once suppressor effects are controlled. At the same time, Agreeableness and Conscientiousness contribute modestly and context-dependently to descriptions of financial risk-taking. These findings demonstrate that ignoring suppression effects can lead to mischaracterizing the role of personality in financial decision-making. This study shows that more precise estimates of trait influences can improve theoretical models of investor behavior and enhance the delivery of financial advice and education. Full article
33 pages, 3280 KB  
Article
Time-Varying Global Financial Stress Contagion in a Decade of Trade Wars and Geopolitical Fractures
by Mosab I. Tabash, Suzan Sameer Issa, Mohammed Alnahhal, Zokir Mamadiyarov and Krzysztof Drachal
Risks 2026, 14(3), 70; https://doi.org/10.3390/risks14030070 - 19 Mar 2026
Viewed by 310
Abstract
The objective of this study is to explore the time-varying shock transmission mechanism between aggregated financial stress indices (FSIs) of developed economies (the U.S., the U.K., the European Union (EU) and Japan) and the emerging economy of China. We employ a novel Time-Varying [...] Read more.
The objective of this study is to explore the time-varying shock transmission mechanism between aggregated financial stress indices (FSIs) of developed economies (the U.S., the U.K., the European Union (EU) and Japan) and the emerging economy of China. We employ a novel Time-Varying Parameter Vector Auto-Regression (TVP-VAR)-based “connectedness approach” to capture dynamic shock spillovers without the limitations of arbitrarily chosen rolling windows, loss of observations, or excessive sensitivity to outliers, as it is grounded in a multivariate Kalman filter structure. The aggregated measures of the FSIs of China, the U.S., the U.K., the EU and Japan are incorporated from the Asian Development Bank’s data repository by using time-series observations from January 2010 to September 2023. The findings indicate that the FSI of China is influenced by financial stress shocks originating from Japan (18.35%) and the U.S. (16.86%) the most, whereas the U.K. (EU) contributes to only 8.42% (6.54%) of FSI shocks in China. This research article significantly captures China’s heightened vulnerability to external financial stress shocks from developed economic systems and underscores the critical importance of reinforcing financial resilience, strengthening macro-prudential regulations and early-warning systems, and expanding financial buffers during episodes of trade uncertainty like restrictions on China’s rare earth exports and solar panels, U.S. restrictions on industrial metal imports, Brexit, supply chain disruptions amid COVID-19, and geopolitical uncertainties like the Russia–Ukraine war. Overall, this study provides actionable guidance for mitigating the impact of global financial stresses, improving risk management, and safeguarding economic stability in an increasingly interconnected and volatile international environment. Full article
(This article belongs to the Special Issue Emerging Risks in Banking and Finance: Technological Disruption, Climate Change, and Geopolitical Tensions)
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23 pages, 636 KB  
Article
The Impact of Climate Change on Banking System Stability in Southern Africa Development Communities (SADC)
by Oliver Takawira, Emmanuel Amo-Bediako, Dimakatso Sekwati and Silas Marimo
Risks 2026, 14(3), 69; https://doi.org/10.3390/risks14030069 - 18 Mar 2026
Viewed by 347
Abstract
In today’s world, climate change has become a global predicament. The implications for financial sector activities have given rise to ample literature on the climate change and banking system stability nexus in developing economies. However, there still remain important knowledge gaps pertaining to [...] Read more.
In today’s world, climate change has become a global predicament. The implications for financial sector activities have given rise to ample literature on the climate change and banking system stability nexus in developing economies. However, there still remain important knowledge gaps pertaining to areas such as the asymmetric impact of climate change on banking system relationships, threshold effects, and transmission channels. Therefore, this research investigated the impact of climate change on banking system stability in the Southern Africa Development Communities (SADC). The study employed a panel data estimation technique, analysing fixed and random effects to test these hypotheses in SADC. In doing so, it not only explored how climate-related risks affect banking stability but also assessed how economic, environmental, and institutional dynamics mediate this relationship. The findings contribute to informing regional policy on financial resilience and adaptive climate strategies within fragile banking environments. Full article
(This article belongs to the Special Issue Climate Change and Financial Risks)
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18 pages, 421 KB  
Article
Digital Financial Literacy and Hyperbolic Discounting: Evidence from Japanese Investors
by Shiiku Asahi, Gideon Otchere-Appiah, Mostafa Saidur Rahim Khan and Yoshihiko Kadoya
Risks 2026, 14(3), 68; https://doi.org/10.3390/risks14030068 - 17 Mar 2026
Viewed by 453
Abstract
This study investigates the relationship between digital financial literacy (DFL) and hyperbolic discounting among 104,993 active securities account holders in Japan. As digital financial services expand rapidly, individuals increasingly require not only traditional financial knowledge but also the capacity to understand digital platforms, [...] Read more.
This study investigates the relationship between digital financial literacy (DFL) and hyperbolic discounting among 104,993 active securities account holders in Japan. As digital financial services expand rapidly, individuals increasingly require not only traditional financial knowledge but also the capacity to understand digital platforms, evaluate online financial information, and manage emerging technological risks. Using data from the 2025 wave of the Survey on Life and Money, hyperbolic discounting is measured through intertemporal monetary choice scenarios, while DFL is constructed as a multidimensional index encompassing digital knowledge, financial knowledge, service awareness, attitudes, behaviors, practical capability, and protection against digital fraud. Probit regression results reveal a statistically significant negative association between DFL and hyperbolic discounting, indicating that individuals with stronger digital financial competencies are less likely to exhibit hyperbolic discounting. Attitudinal components of DFL exhibit the strongest effects, suggesting that internalized financial beliefs may play a more decisive role than technical knowledge in promoting time-consistent decision-making. Subsample analyses further highlight gender-differentiated patterns in demographic and economic influences on present bias. These findings contribute to behavioral finance by integrating digital capability into intertemporal choice research and provide policy-relevant implications for designing comprehensive financial education and digital literacy initiatives in increasingly digitalized financial environments. Full article
22 pages, 403 KB  
Article
Business Strategy, Audit Risk, and Auditor–Client Disagreement: Evidence from Korea
by Jihwan Choi
Risks 2026, 14(3), 67; https://doi.org/10.3390/risks14030067 - 16 Mar 2026
Viewed by 334
Abstract
This study examines the extent to which a firm’s business strategy shapes its strategic and audit risk profiles, and whether these risk characteristics ultimately manifest as measurable auditor–client disagreements. Auditor–client disagreement is operationalized using a direct, disclosure-based measure constructed as the scaled difference [...] Read more.
This study examines the extent to which a firm’s business strategy shapes its strategic and audit risk profiles, and whether these risk characteristics ultimately manifest as measurable auditor–client disagreements. Auditor–client disagreement is operationalized using a direct, disclosure-based measure constructed as the scaled difference between unaudited preliminary net income—manually collected from mandatory timely filings disclosed through the Korea Financial Supervisory Service’s Electronic Disclosure System (DART)—and final audited net income reported in the audited financial statements. Using a sample of 6504 firm-year observations drawn from firms listed on the Korea Exchange (KOSPI and KOSDAQ) over the period 2020–2024, I find that a higher strategic score, reflecting a more innovation-oriented, prospector-type strategic posture, is consistently and significantly positively associated with the likelihood of auditor–client disagreement. Conversely, firms pursuing a cost-efficiency-oriented, defender-type strategy exhibit a significantly lower likelihood and smaller magnitude of disagreement. These findings suggest that business strategy functions as a fundamental, ex-ante determinant of inherent risk and audit risk, directly shaping auditors’ effort allocation and financial reporting outcomes. Collectively, this study contributes to the auditing literature by providing empirical evidence that a client’s strategic positioning constitutes a material, firm-level risk factor—consistent with the risk assessment framework mandated by International Standard on Auditing (ISA) 315—and should therefore be explicitly incorporated into auditors’ engagement risk assessments and the design of risk-based audit procedures. Full article
16 pages, 614 KB  
Article
Loan Defaults and Credit Risk in Microfinance
by Perpetual Andam Boiquaye, Bernadette Aidoo and Samuel Asante Gyamerah
Risks 2026, 14(3), 66; https://doi.org/10.3390/risks14030066 - 16 Mar 2026
Viewed by 349
Abstract
This study investigates the probability of consumer default across both secured and unsecured assets, with a particular focus on borrower behavior and the role of moral hazard in shaping individual credit risk. It examines how different borrower decisions, such as investing in secured [...] Read more.
This study investigates the probability of consumer default across both secured and unsecured assets, with a particular focus on borrower behavior and the role of moral hazard in shaping individual credit risk. It examines how different borrower decisions, such as investing in secured and unsecured projects after loan disbursement, affect default outcomes, especially under limited lender supervision. The Ornstein–Uhlenbeck process is used to capture the dynamics of risky asset returns and identifies the conditions under which borrowers are likely to switch from safer to riskier investments. We assume that borrowers may allocate loan funds to both secured and unsecured projects, thereby recognizing that credit risk assessment inherently involves behavioral factors that are difficult to quantify. Monte Carlo simulations are used to assess how return volatility influences borrower decision-making, showing that higher uncertainty increases the probability of returns exceeding the repayment obligation, thereby incentivizing risk-shifting behavior. The results indicate that unsecured lending is more exposed to strategic risk shifting and experiences more frequent and severe default outcomes than secured lending. As a result, this study recommends that microfinance institutions prioritize collateral-backed lending as a more effective strategy for mitigating credit risk and reducing exposure to borrower opportunism. Full article
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19 pages, 1224 KB  
Article
Investigating the Systematically Important Equity Sectors in Extreme Conditions: A Case of Johannesburg Stock Exchange
by Babatunde Lawrence, Anurag Chaturvedi, Adefemi A. Obalade and Mishelle Doorasamy
Risks 2026, 14(3), 65; https://doi.org/10.3390/risks14030065 - 13 Mar 2026
Viewed by 295
Abstract
This study examined the ‘too central to fail’ concept in the South African equity sector. We employed the Granger causality framework and PageRank algorithm to generate the centrality scores of the sectors on the Johannesburg Stock Exchange under extreme market conditions. Using the [...] Read more.
This study examined the ‘too central to fail’ concept in the South African equity sector. We employed the Granger causality framework and PageRank algorithm to generate the centrality scores of the sectors on the Johannesburg Stock Exchange under extreme market conditions. Using the realized volatilities of sectoral returns for the full sample period (3 January 2006–31 December 2021), as well as during the global financial crisis (GFC), European debt crisis (EDC), COVID-19 pandemic, and US–China trade war sub-periods, we analyzed the sectors’ interconnections and calculated each sector’s centrality score across the entire sample and under different extreme market conditions. This allowed us to rank sectors relative to their centrality scores. The results indicate that, in the full sample, the insurance sector has the highest PageRank centrality score, suggesting it is too central to fail. This implies that the insurance sector acts as a systemic receiver of risks and provides stability within the network of sectors. However, the sub-period analyses reveal that General Industrial and Automobiles emerged as the key sectors with the highest PageRank centrality scores, and shocks from other sectors can disproportionately affect these industries during crisis periods. Underperformance in these sectors could have destabilizing effects on the South African economy. The findings have significant implications for regulators and policymakers, portfolio and fund managers, local and international investors, and researchers in the field of finance. Full article
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16 pages, 728 KB  
Article
A Comparison of Risk Willingness Between Same-Sex and Different-Sex Couples: A Quasi-Experimental Approach
by Matthew Jaramillo, Donald Lacombe, Leobardo Diosdado and Laura Ricaldi
Risks 2026, 14(3), 64; https://doi.org/10.3390/risks14030064 - 13 Mar 2026
Viewed by 480
Abstract
Household composition in the United States is increasingly diverse; however, research into the diversity of the financial decision maker’s sexual orientation has yet to be explored. This analysis examines whether there are differences in financial risk tolerance between same-sex and different-sex couples using [...] Read more.
Household composition in the United States is increasingly diverse; however, research into the diversity of the financial decision maker’s sexual orientation has yet to be explored. This analysis examines whether there are differences in financial risk tolerance between same-sex and different-sex couples using data from the Survey of Consumer Finances. The results from a propensity score matching technique, a Mann–Whitney U test, and interpretations of average treatment effects and average treatment effects of the treated suggest there is a statistical difference in risk tolerance between couples and that, on average, same-sex households are significantly more likely to report higher risk tolerance scores, at the 10% alpha level, when compared to their counterparts. Both treatment effect estimates suggest a high impact of the treatment at the 1% alpha level. This highlights the importance of not assuming homogeneous risk preferences across household types. These findings emphasize the importance of recognizing diversity in household composition. Thus, this study identifies the need for inclusiveness in all segments of financial planning. Full article
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27 pages, 1070 KB  
Article
Human-AI Synergy in Statistical Arbitrage: Enhancing Robustness Across Volatile Financial Markets
by Binxu Lei
Risks 2026, 14(3), 63; https://doi.org/10.3390/risks14030063 - 12 Mar 2026
Viewed by 659
Abstract
This study provides a structured review of statistical arbitrage research in the context of artificial intelligence, with a particular focus on machine learning based methods. The reviewed literature highlights the evolution from linear, rule-based strategies to increasingly complex data-driven models, while also documenting [...] Read more.
This study provides a structured review of statistical arbitrage research in the context of artificial intelligence, with a particular focus on machine learning based methods. The reviewed literature highlights the evolution from linear, rule-based strategies to increasingly complex data-driven models, while also documenting persistent challenges related to tail-risk exposure, regime instability, limited interpretability, and regulatory and governance constraints in practical applications. Building on this literature synthesis, the paper develops a conceptual AI-led, human-in-the-loop statistical arbitrage framework that integrates ML-generated signal modeling with structured human oversight—encompassing risk calibration, discretionary intervention, and interpretability review. This framework resonates with human-AI collaboration systems across other financial domains, collectively supporting the proposition that collaborative systems show potential to enhance resilience compared to purely AI-driven alternatives under specific market stress scenarios. It is positioned as a governance-oriented synthesis that qualitatively extends existing human-in-the-loop concepts by structurally embedding adaptive oversight within the statistical arbitrage decision architecture. Full article
(This article belongs to the Special Issue AI-Driven Financial Econometrics and Risk Management)
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24 pages, 3858 KB  
Article
At Cross-Purposes: How Prudential and Monetary Rate Policies Create Asymmetric Frictions in the Banking Sector
by Shandra Widiyanti, Hermanto Siregar, Anny Ratnawati, Suwandi and Noer Azam Achsani
Risks 2026, 14(3), 62; https://doi.org/10.3390/risks14030062 - 11 Mar 2026
Viewed by 285
Abstract
Indonesia’s financial system is bank-centric, with banks managing approximately 78% of the nation’s financial assets; therefore, the effectiveness of monetary policy transmission depends on banks’ responsiveness to the central bank’s interest rate policy (the BI Rate). However, a policy-relevant anomaly persists: deposit rate [...] Read more.
Indonesia’s financial system is bank-centric, with banks managing approximately 78% of the nation’s financial assets; therefore, the effectiveness of monetary policy transmission depends on banks’ responsiveness to the central bank’s interest rate policy (the BI Rate). However, a policy-relevant anomaly persists: deposit rate pricing is more strongly anchored to the Deposit Insurance benchmark (IDIC Rate) than to the BI Rate. This study argues that this research is significant because it identifies a “Dual Benchmark System” that traditional single-anchor models fail to address, representing a critical friction in emerging market transmission. This study examines this dual-benchmark paradigm and the associated asymmetric risks using a panel VAR with a Generalized Impulse Response Function (GIRF) on quarterly data for 63 commercial banks from 2010 to 2024. The results indicate that IDIC Rate shocks have a larger and more persistent effect on deposit rates than BI Rate shocks, generating asymmetric transmission risks. This dominance creates a structural “price ceiling” that keeps funding costs high, ultimately raising lending rates for borrowers and distorting deposit growth rates. Furthermore, this analysis reveals that external policy signals are far more influential than internal financial performance. This suggests that under the Basel III framework and prevailing financial regulations, banks prioritize liquidity compliance and safety net protection over internal operational efficiency. Macroeconomic shocks remain weaker than policy shocks and dissipate more quickly. This finding reveals a potential systemic coordination risk, implying an urgent need for tighter policy coordination between the Central Bank and the IDIC to reduce structural frictions, maintain transmission effectiveness, and protect long-term financial stability. Full article
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22 pages, 434 KB  
Article
Firm Performance, Liquidity and Capital Structure Nexus: Evidence from the PMG Panel-ARDL Approach
by Godfrey Marozva
Risks 2026, 14(3), 61; https://doi.org/10.3390/risks14030061 - 11 Mar 2026
Viewed by 542
Abstract
Utilising data from the selected companies listed on the Johannesburg Stock Exchange and using the Panel Autoregressive Distributed Lag (ARDL) specifically employing the Pooled Mean Group approach, this study examines the cointegrating and causal relationships among firm liquidity, performance and firm leverage. The [...] Read more.
Utilising data from the selected companies listed on the Johannesburg Stock Exchange and using the Panel Autoregressive Distributed Lag (ARDL) specifically employing the Pooled Mean Group approach, this study examines the cointegrating and causal relationships among firm liquidity, performance and firm leverage. The results reveal a negative and significant long-run and short-run relationship between profitability and leverage. Conversely, higher leverage is found to diminish firm performance, consistent with trade-off theory implications regarding financial distress costs. On liquidity, results revealed a bidirectional long-run relationship among liquidity, leverage, and firm value as measured by Tobin’s Q. Also, liquidity plays a pivotal moderating role, where firms with stronger liquidity and profitability exhibit reduced reliance on external debt, highlighting the interplay between financial health and capital structure decisions. Additionally, a positive bidirectional relationship between Tobin’s Q and leverage suggests that growth opportunities and market valuation influence firms’ debt utilisation. The error correction terms confirm stable long-run equilibrium and moderate adjustment speeds. These results contribute to the understanding of optimal capital structure by integrating liquidity and performance factors and provide practical insights for corporate financial management and policy formulation. Full article
(This article belongs to the Special Issue Empirical Advances in Corporate Finance and Governance Under Emerging Risks and Strategic Challenges)
31 pages, 612 KB  
Article
Collusion Between Retailers and Customers: The Case of Insurance Fraud in Taiwan
by Pierre Picard, Jennifer Wang and Kili C. Wang
Risks 2026, 14(3), 60; https://doi.org/10.3390/risks14030060 - 9 Mar 2026
Viewed by 327
Abstract
This study analyzes how the insurance distribution channel can affect insurance fraud. It uses econometric models that confirm the existence of claim manipulation as a form of insurance fraud, whereby policyholders circumvent the bonus–malus system and reduce the actual burden of insurance deductibles. [...] Read more.
This study analyzes how the insurance distribution channel can affect insurance fraud. It uses econometric models that confirm the existence of claim manipulation as a form of insurance fraud, whereby policyholders circumvent the bonus–malus system and reduce the actual burden of insurance deductibles. The econometric approach is based on joint regression models for the probability that a claim is manipulated on one hand, and the probability that the policyholder has strong incentives to do so, on the other hand. The estimation shows that there is a significantly positive residual correlation between these regressions, which establishes the likelihood of fraudulent claim manipulation. The econometric modelling of claim cost allows us to disentangle the manipulation of claims that correspond to true losses and small false claims filed at the end of the policy year, and also to highlight the role of the insurance distribution channel in these fraud mechanisms. Using data from two Taiwanese car insurers with very different distribution channels in 2010, we compare an insurer that relies heavily on dealer-owned agents (DOAs) with another insurer that does not rely on DOAs at all. We find strong evidence of severe claim manipulation when insurance is sold through DOAs. Moreover, as the first insurer significantly reduced its reliance on the DOA channel over time, we perform a before–after comparison using data from 2010 and 2018. The results show that the claim manipulation fraud previously observed in the DOA channel decreases as the market share of this distribution channel is reduced. All these results highlight the role of automobile insurance agencies in facilitating this fraud process. The theoretical underpinnings of our analysis are provided by a claim fraud model considering collusion and audit. Full article
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28 pages, 1054 KB  
Article
An Age Grouping Framework for Multi-Population Mortality Modeling
by Cezar A. Câmpeanu and Yechao Meng
Risks 2026, 14(3), 59; https://doi.org/10.3390/risks14030059 - 9 Mar 2026
Viewed by 278
Abstract
This study extends existing mortality prediction frameworks by incorporating information borrowed from population–gender–age subgroups that exhibit similar mortality patterns. The borrowed information is integrated into classical mortality models to improve the accuracy of future mortality rate forecasts. To capture structural similarities among mortality [...] Read more.
This study extends existing mortality prediction frameworks by incorporating information borrowed from population–gender–age subgroups that exhibit similar mortality patterns. The borrowed information is integrated into classical mortality models to improve the accuracy of future mortality rate forecasts. To capture structural similarities among mortality trajectories, several distance measures are evaluated in combination with four linkage methods, particularly when each subgroup comprises multiple age-specific mortality trajectories. Extensive empirical analyses using data from the Human Mortality Database demonstrate the superior predictive performance of the proposed approach. Full article
(This article belongs to the Special Issue Advancement in Mortality Forecasting and Mortality/Longevity Risk Management)
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18 pages, 516 KB  
Article
On Return Probabilities of Adverse Events Under Dependence and Lessons to Learn for Decision-Making
by Marius Hofert
Risks 2026, 14(3), 58; https://doi.org/10.3390/risks14030058 - 5 Mar 2026
Viewed by 339
Abstract
Considering achieving a goal in each of several time intervals when, in every time interval, an adverse event may lead to a failure raises the question of the return probability of adverse events, so the probability of at least one failure to happen [...] Read more.
Considering achieving a goal in each of several time intervals when, in every time interval, an adverse event may lead to a failure raises the question of the return probability of adverse events, so the probability of at least one failure to happen during the time period of interest. Through basic mathematical arguments in tractable cases, we investigate the behavior of the return probability of adverse events in various setups. In the univariate case, we consider the independent and identically distributed setup, the independent setup, the dependent but not necessarily identically distributed setup, and the dependent and identically distributed setup. In the multivariate case, we consider several goals to be achieved in each time period. Besides different setups for the marginal failure probabilities, we study dependence in terms of comonotone blocks and independent blocks and via nested copulas. In case closed form expressions are not available, we derive bounds on the return probability of at least one failure. Our results are interpretable in terms of decision-making, provide insight into what affects such return probabilities and thus may help to develop strategies to lower them. Full article
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22 pages, 2128 KB  
Article
Risk-Informed Machine Learning Models for Renewal Classification in Motor Insurance
by Pichit Boonkrong, Junwei Yang, Xueyuan Huang and Teerawat Simmachan
Risks 2026, 14(3), 57; https://doi.org/10.3390/risks14030057 - 3 Mar 2026
Viewed by 576
Abstract
This study develops an interpretable machine learning framework for type 1 motor insurance renewal classification using 70,290 real-world Thai policies, providing essential insights for pricing, customer retention, and operational decision making. The dataset was partitioned into a 70% training set, utilizing 5-fold cross-validation [...] Read more.
This study develops an interpretable machine learning framework for type 1 motor insurance renewal classification using 70,290 real-world Thai policies, providing essential insights for pricing, customer retention, and operational decision making. The dataset was partitioned into a 70% training set, utilizing 5-fold cross-validation for hyperparameter tuning and model selection, and a 30% hold-out testing set to evaluate final model performance. Five machine learning models including Binary Logistic Regression, K-Nearest Neighbors, Support Vector Machines, Random Forests, and XGB are systematically evaluated across multiple curated feature sets generated through statistical filtering, stepwise selection, and permutation-based importance. Non-parametric tests are employed to compare model performance across scenarios. Experimental results show that a reduced four-feature Random Forest model (car age, net premium, sum insured, and car group) achieves the highest predictive performance (AUC = 99.62%; F1 = 98.15%), outperforming full-feature models while maintaining superior computational efficiency. Consequently, H2OAutoML serves as an external validation tool to verify that this manually curated, interpretable pipeline remains highly competitive with fully automated systems. Integrating a SHAP-based explainability layer quantifies predictor influence, ensuring transparency and regulatory alignment. Prioritizing feature parsimony, this study provides integrable insights for dynamic pricing and risk-adjusted retention, enhancing decision support within evolving motor insurance markets through transparent systems. Full article
(This article belongs to the Special Issue Financial Risk, Actuarial Science, and Applications of AI Techniques)
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18 pages, 387 KB  
Article
The Association Between Time Discounting, Hyperbolic Discounting, and Inflation Expectations: Evidence from Large-Scale Survey Data
by Kota Ogura, Manaka Yamaguchi, Sakiho Aizawa, Mostafa Saidur Rahim Khan and Yoshihiko Kadoya
Risks 2026, 14(3), 56; https://doi.org/10.3390/risks14030056 - 3 Mar 2026
Viewed by 417
Abstract
Inflation expectations play a central role in monetary policy effectiveness, yet relatively little is known about how individual behavioral traits shape expectation formation. This study examines whether time discounting and hyperbolic discounting, key dimensions of intertemporal preferences, are systematically associated with household inflation [...] Read more.
Inflation expectations play a central role in monetary policy effectiveness, yet relatively little is known about how individual behavioral traits shape expectation formation. This study examines whether time discounting and hyperbolic discounting, key dimensions of intertemporal preferences, are systematically associated with household inflation expectations. Using large-scale survey data from Japan that elicit both time preference measures and qualitative inflation expectations, we analyze expectations over one-, three-, and five-year horizons. The empirical analysis employs ordered probit models that fit well with the categorical nature of survey-based inflation expectations and controls for a rich set of demographic, socioeconomic, and behavioral characteristics, including financial literacy and risk preferences. The results reveal clear horizon-dependent patterns. Hyperbolic discounting is positively associated with short-term inflation expectations, suggesting that present-biased individuals place greater weight on recent inflation developments. In contrast, higher time discount rates are associated with higher inflation expectations at medium and longer horizons, indicating that impatience is more relevant for beliefs about distant future prices. These findings provide novel evidence on the behavioral micro-foundations of inflation expectation formation and highlight the importance of heterogeneity in time preferences. From a policy perspective, the results suggest that one-size-fits-all communication strategies may be insufficient and that effective expectation management may require tailoring messages to account for differences in individuals’ time orientation across forecast horizons. Full article
32 pages, 923 KB  
Article
The Impact of Market Dynamics and Geopolitical Uncertainty on Property Return: A Comparative Analysis of BRICS Countries
by Fabian Moodley and Babatunde Lawrence
Risks 2026, 14(3), 55; https://doi.org/10.3390/risks14030055 - 2 Mar 2026
Viewed by 606
Abstract
Rising geopolitical tensions and fluctuating financial market conditions have increased volatility and negatively impacted property returns across BRICS countries, yet this critical area remains underexplored despite its significant implications for policy reform and investor participation. To this extent, the objective of the study [...] Read more.
Rising geopolitical tensions and fluctuating financial market conditions have increased volatility and negatively impacted property returns across BRICS countries, yet this critical area remains underexplored despite its significant implications for policy reform and investor participation. To this extent, the objective of the study is to examine the effect of geopolitical uncertainty on BRICS property market returns under changing market conditions. Using a Markov regime-switching model for the period February 2011 to June 2025, the findings reveal regime-specific effects. That being said, Brazil’s property market returns are affected positively (negatively) by South Africa’s (China’s) geopolitical uncertainty, whereas India’s and South Africa’s property market returns are affected negatively and positively by Russia’s geopolitical uncertainty, respectively. These findings were further evident in the bear market condition, as Russia’s geopolitical uncertainty has a significant negative effect on Brazil’s property market returns. Similarly, BRICS countries’ returns are dominated by bear market conditions, revealing negative returns, suggesting the BRICS property market returns are less resilient to periods of uncertainty. The findings underscore the need for new policy reforms to regulate BRICS members’ participation and minimize spillover effects, while investors should closely monitor geopolitical uncertainty within BRICS countries to manage return prospects effectively. Full article
(This article belongs to the Special Issue Emerging Risks in Banking and Finance: Technological Disruption, Climate Change, and Geopolitical Tensions)
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21 pages, 934 KB  
Article
Analytical Pricing of Discretely Sampled Volatility Swaps Under the 4/2 Stochastic Volatility Model
by Sanae Rujivan, Seyha Lim, Nopporn Thamrongrat and Angelo E. Marasigan
Risks 2026, 14(3), 54; https://doi.org/10.3390/risks14030054 - 2 Mar 2026
Viewed by 404
Abstract
This paper develops a unified analytical framework for pricing discretely sampled volatility-average swaps under the 4/2 stochastic volatility model. The model accommodates a broad range of volatility dynamics by combining affine and inverse-affine components in the instantaneous volatility specification, thereby unifying and extending [...] Read more.
This paper develops a unified analytical framework for pricing discretely sampled volatility-average swaps under the 4/2 stochastic volatility model. The model accommodates a broad range of volatility dynamics by combining affine and inverse-affine components in the instantaneous volatility specification, thereby unifying and extending the structural features of the classical Heston and 3/2 stochastic volatility models. Closed-form expressions for the conditional complex moments of the asset price are derived and serve as the fundamental building blocks for obtaining explicit analytical pricing formulas for volatility-average swaps under discrete sampling. The validity of the proposed pricing formulas is rigorously established within the admissible parameter space of the model. Extensive numerical experiments verify the accuracy and computational efficiency of the analytical results when compared with Monte Carlo simulations. The numerical analysis further reveals that discretely sampled volatility swap prices converge to their continuous-time counterparts in a manner that may be monotonic or non-monotonic, depending on the interaction between the volatility and inverse-volatility components of the 4/2 model, thereby emphasizing the importance of sampling effects in volatility derivative valuation. A detailed sensitivity analysis demonstrates how variations in the parameters governing the volatility and inverse-volatility components influence the fair strike prices, underscoring the structural flexibility of the 4/2 stochastic volatility model. Overall, the proposed framework provides an analytically tractable and computationally efficient approach for pricing volatility-linked derivatives under discrete sampling, offering valuable insights for both theoretical research and practical applications in volatility markets. Full article
(This article belongs to the Special Issue Advances in Mathematical Finance and Insurance)
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27 pages, 950 KB  
Article
Contagion and Default Risks in Derivative Pricing: A Hawkes-Based Model
by Francis Agana and Eben Maré
Risks 2026, 14(3), 53; https://doi.org/10.3390/risks14030053 - 2 Mar 2026
Viewed by 269
Abstract
Modern financial systems do not exist in isolation but form part of a complex global network of interconnected financial systems. This globalization of financial systems significantly increases the risk of contagion in financial markets, impacting asset prices and other important economic factors, including [...] Read more.
Modern financial systems do not exist in isolation but form part of a complex global network of interconnected financial systems. This globalization of financial systems significantly increases the risk of contagion in financial markets, impacting asset prices and other important economic factors, including interest rates and market volatility. This phenomenon informs not only investors’ investment strategies but also the prices of contingent claims. In this article, we present a derivative pricing model in an incomplete and globalized financial market. To appreciate the dynamics and impact of some important market factors, particularly default risks due to contagion, we consider two different financial markets with defaultable assets: in one market, we consider a stock whose price process follows a Heston stochastic volatility model, and in the other, a stock that follows a Hawkes-type jump diffusion model whose intensity is subjected to external systemic shocks. In both markets, we derive an indifference price for a contingent claim that is subject to the risk of default and show the impacts the investor’s risk aversion and external shocks on the price of the contingent claim. Full article
(This article belongs to the Special Issue Financial Investment, Derivatives Hedging, and Risk Management)
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20 pages, 647 KB  
Article
Dynamic Connectiveness and Time-Varying Contagion Risks Amongst East African Stock Markets
by Arnold Gideon Irangi, Paul-Francois Muzindutsi, Hilary Tinotenda Muguto and Malibongwe Cyprian Nyati
Risks 2026, 14(3), 52; https://doi.org/10.3390/risks14030052 - 2 Mar 2026
Viewed by 481
Abstract
Regional financial integration in East Africa remains shallow, yet contagion risks persist due to market fragility and illiquidity. Using daily data from 2014 to 2025 from the Nairobi Securities Exchange (NSE), Dar es Salaam Stock Exchange (DSE), Rwanda Stock Exchange (RSE), and Uganda [...] Read more.
Regional financial integration in East Africa remains shallow, yet contagion risks persist due to market fragility and illiquidity. Using daily data from 2014 to 2025 from the Nairobi Securities Exchange (NSE), Dar es Salaam Stock Exchange (DSE), Rwanda Stock Exchange (RSE), and Uganda Securities Exchange (USE), this study examines volatility spillovers, dynamic connectedness, and contagion through autoregressive moving average – generalised autoregressive conditional heteroscedasticity (ARMA–GARCH) diagnostics, asymmetric dynamic conditional correlation (ADCC–GARCH) correlations, and the Diebold–Yilmaz framework. The results show weak spillovers and limited connectedness in tranquil periods, reflecting persistent segmentation. However, systemic stress triggers abnormal surges in correlations and connectedness, consistent with contagion as a temporary amplification of cross-market linkages. The NSE emerges as the dominant transmitter, driven by liquidity and cross-listings, while the USE acts as a passive absorber. The RSE and DSE alternate between marginal transmitters and receivers depending on conditions. These findings support the Adaptive Market and Financial Instability Hypotheses, underscoring the need for harmonised regulation, liquidity reforms, and adaptive risk management to bolster resilience. Full article
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25 pages, 9078 KB  
Article
Enhancing Bitcoin Trading Signal Prediction in Crisis Periods Using an Improved Machine Learning Approach
by Yaser Sadati-Keneti, Mohammad Vahid Sebt, Reza Tavakkoli-Moghaddam and Orod Ahmadi
Risks 2026, 14(3), 51; https://doi.org/10.3390/risks14030051 - 1 Mar 2026
Viewed by 776
Abstract
The aim of this research is to employ improved machine learning techniques to determine the best Bitcoin trading positions in response to sudden price changes caused by global emergencies such as pandemics, conflicts, and economic disputes. Specifically, this study examines price fluctuations during [...] Read more.
The aim of this research is to employ improved machine learning techniques to determine the best Bitcoin trading positions in response to sudden price changes caused by global emergencies such as pandemics, conflicts, and economic disputes. Specifically, this study examines price fluctuations during the COVID pandemic as a case study to evaluate the performance of the algorithms investigated. We present a novel hybrid approach that merges Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Decision Tree (DT) classification to effectively eliminate noisy data and extract pertinent information for accurate position forecasting. The DBSCAN algorithm organizes the data to reveal important patterns, while the DT classifier sorts the trading signals. The performance of the proposed DBSCAN-DT model is rigorously compared with established alternatives, including the Multi-Layer Perceptron (MLP), Support Vector Classifier (SVC), and traditional Decision Trees. Findings from the experiments show that the DBSCAN-DT hybrid consistently outperforms these benchmarks during the outbreak, epidemic, and pandemic phases of COVID, attaining greater accuracy in forecasting both trading positions and market trends. These findings emphasize the essential importance of incorporating pandemic-related disruptions into cryptocurrency price prediction models and showcase the flexibility of our method in addressing sudden market changes. Full article
(This article belongs to the Special Issue Cryptocurrency Pricing and Trading)
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21 pages, 2842 KB  
Article
ESG Disclosure Quality and Banking Risk: A Dynamic Panel Analysis of Middle East and African Banks
by Ibrahim Elsiddig Ahmed
Risks 2026, 14(3), 50; https://doi.org/10.3390/risks14030050 - 28 Feb 2026
Viewed by 509
Abstract
This study aims to analyze the impact of environmental, social, and governance (ESG) disclosure quality on banking risk. Data were collected from the 100 largest commercial banks in the Middle East and Africa over ten years and examined using econometric analysis to measure [...] Read more.
This study aims to analyze the impact of environmental, social, and governance (ESG) disclosure quality on banking risk. Data were collected from the 100 largest commercial banks in the Middle East and Africa over ten years and examined using econometric analysis to measure the influence of ESG disclosure quality on banking risks. The findings indicate that both social and environmental disclosures have high predictability, while governance disclosure shows lower predictability. A significant negative relationship exists between the ESG disclosure quality and risk. Governance disclosure, Tier 1 capital, has a strong influence, and capital adequacy has the least. Managerial and practical implications are based on bank compliance, coverage, and debt. Unlike previous studies, this study moves from ESG performance to its disclosure quality and combines the random forest method (machine learning) with dynamic panel analysis (econometrics), bringing innovation and contribution to knowledge (the stakeholder theory) and practice. Full article
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23 pages, 899 KB  
Article
The Mean-Variance Paradigm Is Almost Universal: The Skewness Effect
by Haim Levy
Risks 2026, 14(3), 49; https://doi.org/10.3390/risks14030049 - 28 Feb 2026
Viewed by 383
Abstract
The mean-variance rule (M-V) conforms with the expected utility paradigm only in limited and economically unacceptable scenarios. Thus, the most widely employed portfolio-selection rule seemingly loses ground. We show with the commonly employed utility functions in economics, with a preference for a positive [...] Read more.
The mean-variance rule (M-V) conforms with the expected utility paradigm only in limited and economically unacceptable scenarios. Thus, the most widely employed portfolio-selection rule seemingly loses ground. We show with the commonly employed utility functions in economics, with a preference for a positive skewness, that choosing from the M-V efficient frontier conforms with expected utility maximization even with long investment horizon and skewed distributions of returns. The economic loss induced by choosing from the M-V frontier is negligible. Thus, the M-V rule is universal, or almost universal, provided that the commonly employed utility functions in economics are employed. This is an astonishing result that even Markowitz has not dreamed of. Full article
(This article belongs to the Special Issue Portfolio Selection and Asset Pricing)
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28 pages, 950 KB  
Article
The Impact of Corporate Biodiversity Information Disclosure on China Institutional Investors’ CSR Investment Willingness: The Roles of Intergenerational Responsibility and Environmental Risk Management
by Zhibin Tao
Risks 2026, 14(3), 48; https://doi.org/10.3390/risks14030048 - 27 Feb 2026
Viewed by 373
Abstract
The increasing recognition of biodiversity loss as a critical environmental and financial risk has heightened calls for greater emphasis on corporate information disclosures. However, limited understanding remains as to how corporate biodiversity information disclosure affects institutional investors’ willingness to engage in corporate social [...] Read more.
The increasing recognition of biodiversity loss as a critical environmental and financial risk has heightened calls for greater emphasis on corporate information disclosures. However, limited understanding remains as to how corporate biodiversity information disclosure affects institutional investors’ willingness to engage in corporate social responsibility (CSR) investments. To address this gap, this study utilizes a sample of 426 valid data points from institutional investors in China and employs SEM for empirical analysis. The results indicate that (1) corporate biodiversity information disclosure (CB) positively influences institutional investors’ CSR investment willingness; (2) CB fosters the development of institutional investors’ intergenerational responsibility, which, in turn, enhances their CSR investment willingness; (3) institutional investors’ intergenerational responsibility significantly mediates the relationship between CB and their CSR investment willingness; and (4) corporate environmental risk management positive moderates the relationship between CB and institutional investors’ intergenerational responsibility. Theoretically, this study contributes to the CSR literature by providing insights into the interconnections between biodiversity disclosure, intergenerational responsibility, and environmental risk management from a risk-oriented perspective. Practically, it underscores the importance of strategically utilizing biodiversity disclosure and environmental risk management to attract responsible institutional investments, offering valuable guidance for corporate managers, policymakers, and investors, particularly in emerging markets. Full article
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33 pages, 2715 KB  
Article
Navigating ESG Challenges: The Role of Chartered Accountants in Corporate Sustainability
by Alexandros Garefalakis, Kounali Despoina, Erasmia Angelaki, Christos Papademetriou and Ioannis Passas
Risks 2026, 14(3), 47; https://doi.org/10.3390/risks14030047 - 27 Feb 2026
Viewed by 524
Abstract
ESG criteria have become central to corporate sustainability, reshaping governance, reporting, and the accounting profession. This study investigates how chartered accountants engage with ESG by combining micro-level survey evidence from Greece with macro-level bibliometric analysis of global ESG scholarship. The survey explored accountants’ [...] Read more.
ESG criteria have become central to corporate sustainability, reshaping governance, reporting, and the accounting profession. This study investigates how chartered accountants engage with ESG by combining micro-level survey evidence from Greece with macro-level bibliometric analysis of global ESG scholarship. The survey explored accountants’ knowledge, practices, and perceptions of ESG indicators, revealing significant generational differences: younger professionals reported higher familiarity and stronger implementation of ESG practices, while older respondents demonstrated more limited engagement. Training emerged as a decisive factor, with formally trained accountants applying a broader range of ESG criteria and perceiving greater strategic benefits in credibility, competitiveness, and adaptability. Complementing these insights, the bibliometric analysis of 861 articles published between 1993 and 2025 demonstrated exponential growth in ESG-related research, particularly after 2019, with sustainable development emerging as the conceptual anchor of the field. Thematic mapping highlighted climate change, decision-making, and corporate governance as central concerns, while collaborations between countries such as China, Italy, and the United States underscored global research dynamics. Overall, the study shows that accountants are increasingly positioned as gatekeepers of sustainability reporting, but their effectiveness depends on continuous training, regulatory alignment, and integration into global ESG frameworks. Full article
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37 pages, 1391 KB  
Article
Risk Premiums, Market Volatility, and Exchange Rate Dynamics: Evidence from the Yen Carry Trade
by Opale Guyot, Heather A. Montgomery and Peiqing Yang
Risks 2026, 14(3), 46; https://doi.org/10.3390/risks14030046 - 26 Feb 2026
Viewed by 977
Abstract
Persistent deviations from Uncovered Interest Rate Parity (UIRP) represent a central puzzle in international finance and a key source of currency risk for global investors. This study examines the UIRP puzzle in the JPY/USD market through the lens of financial risk transmission, focusing [...] Read more.
Persistent deviations from Uncovered Interest Rate Parity (UIRP) represent a central puzzle in international finance and a key source of currency risk for global investors. This study examines the UIRP puzzle in the JPY/USD market through the lens of financial risk transmission, focusing on how risk premiums, liquidity conditions, and relative equity market performance jointly shape short-run exchange rate dynamics. Using daily data from 2018 to 2024, we employ a vector autoregression (VAR) framework to capture the endogenous interactions between change in the interest rate differentials, foreign exchange liquidity, global risk indicators (including the VIX, oil price shocks, and currency risk reversals), and relative equity returns consistent with the Uncovered Equity Parity (UEP) hypothesis. The results reveal that traditional interest rate differentials do not directly explain short-term exchange rate movements, confirming persistent UIRP deviations. Instead, risk-related financial channels act as indirect financial risk transmission channels. Shocks to global risk sentiment and currency risk premiums significantly affect JPY/USD returns, while relative equity market performance emerges as a key intermediary linking risk conditions to exchange rate adjustments. The findings also support the Japanese Yen’s continued role as a safe-haven currency during periods of heightened market uncertainty and underline the importance of carry trade dynamics in amplifying risk-driven exchange rate fluctuations. Overall, this study highlights the importance of integrating financial risk measures and portfolio-based transmission channels into exchange rate models. The results have direct implications for risk management, currency exposure hedging, and the assessment of systemic risk spillovers across financial markets. Full article
(This article belongs to the Special Issue Applied Econometrics and International Finance: Analysis, Modeling, and Development)
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24 pages, 552 KB  
Article
Going Concern Risk and Bankruptcy Outcomes Associated with Property, Plant, and Equipment Intensity, Impairment, and Age
by Donald Ray Deis, Jr., J. Kenneth Reynolds, Christopher Wertheim, Tian Xu and Daqun Zhang
Risks 2026, 14(3), 45; https://doi.org/10.3390/risks14030045 - 24 Feb 2026
Viewed by 627
Abstract
Corporate management and their auditors are required to evaluate whether there is a risk that the company’s ability to continue as a going concern is impaired. For fixed asset-intensive firms, however, regulatory inspections consistently identify problems with auditors’ testing of property, plant, and [...] Read more.
Corporate management and their auditors are required to evaluate whether there is a risk that the company’s ability to continue as a going concern is impaired. For fixed asset-intensive firms, however, regulatory inspections consistently identify problems with auditors’ testing of property, plant, and equipment (PPE), raising doubts about whether auditors understand the risks associated with these assets. This paper examines whether auditors incorporate the risks associated with PPE into their going concern evaluation and the accuracy of that evaluation. Using probit regression on financial and auditing data of U.S. public firms contained in S&P Global Compustat North America, Audit Analytics, and the Center for Research in Security Prices (CRSP) from 2000 to 2019, this paper examines the effects of PPE intensity, impairment, and age on the likelihood that an auditor issues a going concern modification. We test the accuracy of the auditor’s going concern evaluation by comparing it to the client’s subsequent viability or bankruptcy. Our results find that PPE intensity and PPE impairments are positively associated with the likelihood of an auditor issuing a going concern modification, indicating that auditors view PPE as contributing to substantial doubt about the entity’s ability to continue as a going concern. We do not find a significant association between PPE age and going concern modification. Additionally, the going concern evaluation is more accurate for firms with higher PPE intensity. These findings imply that auditors appropriately consider PPE assets in their going concern evaluations. Full article
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33 pages, 820 KB  
Article
The Kerper–Bowron Method: A Foundational Change for Service Contract Claim Estimation and Accounting
by John Kerper and Lee Bowron
Risks 2026, 14(3), 44; https://doi.org/10.3390/risks14030044 - 24 Feb 2026
Viewed by 682
Abstract
The Kerper–Bowron Method (KB Method) is a patent-pending approach that revolutionizes service contract loss estimation and accounting by introducing a precise, contract-level approach to forecasting expected losses and cancellations. Building on a prior 2007 paper, this update presents the Earned Contract formula, aligning [...] Read more.
The Kerper–Bowron Method (KB Method) is a patent-pending approach that revolutionizes service contract loss estimation and accounting by introducing a precise, contract-level approach to forecasting expected losses and cancellations. Building on a prior 2007 paper, this update presents the Earned Contract formula, aligning with Solvency II and modern accounting standards. By leveraging a probabilistic exposure base and Generalized Linear Models, the KB Method enhances accuracy in claims and cancel liabilities as well as other liability and asset estimates across global service contract markets. This methodology offers superior precision, automation, and compliance, redefining actuarial and financial practices for vehicle and other service contracts. Full article
(This article belongs to the Special Issue Advances in Risk Models and Actuarial Science)
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14 pages, 532 KB  
Article
Diversifier, Hedge, or Safe Haven? Bitcoin’s Role Against the Brazilian Stock Market During the COVID-19 Turmoil
by Vitor Fonseca Machado Beling Dias and Rodrigo Fernandes Malaquias
Risks 2026, 14(3), 43; https://doi.org/10.3390/risks14030043 - 24 Feb 2026
Viewed by 615
Abstract
The main purpose of this study was to analyze the dynamics of the conditional correlation between Bitcoin and BOVA11 (a Brazilian stock market ETF that has seen a significant increase in foreign investors) across the pre-, during, and post-COVID-19 pandemic periods. This analysis [...] Read more.
The main purpose of this study was to analyze the dynamics of the conditional correlation between Bitcoin and BOVA11 (a Brazilian stock market ETF that has seen a significant increase in foreign investors) across the pre-, during, and post-COVID-19 pandemic periods. This analysis allowed us to investigate the Bitcoin characteristics as a diversifier, hedge, or safe haven relative to the ETF. The study employed a DCC-GARCH model using daily closing prices from 2 January 2015 to 26 September 2025. A robustness check was conducted using Large Language Models (LLMs). Results indicated that in the pre- and post-pandemic periods, Bitcoin showed no significant correlation with the ETF, potentially acting as a weak hedge. Conversely, during the pandemic, Bitcoin behaved as a diversifier for the ETF rather than a safe haven. This finding may surprise market participants, particularly given the widespread narrative of Bitcoin as “digital gold” and, therefore, a natural protection in scenarios of high uncertainty. The results suggest that, during the pandemic, Bitcoin’s behavior aligned more closely with risk assets than with safe havens, underscoring the need for cautious, context-specific empirical assessments of its protective properties. Full article
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