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Featured Papers in Finance and Society Wellbeing—in Honor of Professors...
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Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Mathematics and Finance".

Deadline for manuscript submissions: 1 June 2025 | Viewed by 17785

Special Issue Editors

Dr. Shuangzhe Liu

E-Mail Website
Guest Editor
Department of Mathematics and Statistics, University of Canberra, Canberra, Australia
Interests: financial time series; multivariate analysis; statistical diagnostics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Svetlozar (Zari) Rachev

E-Mail Website
Guest Editor
Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409, USA
Interests: mathematical and empirical finance; probability metrics; mass transportation problems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is a heartfelt tribute to the remarkable Professors Joseph Mark Gani and Christopher Charles Heyde. Their legacies continue to illuminate the path of applied mathematics, financial and social wellbeing. As we approach the centennial of Prof. Gani and the 85th year of Prof. Heyde, we are reminded of their unparalleled contributions that have profoundly influenced probability, statistics and the broader spectrum of applied mathematics and finance.

Prof. Gani, revered for masterfully integrating theoretical precision with practical insights, has left an indelible mark on generations of scholars. Prof. Heyde, remembered for his pioneering work in probability theory and statistical methods, has deeply impacted diverse domains with his analytical prowess. This volume is a convergence of contributions from esteemed peers and protégés, mirroring the vast expanse of influence wielded by these two giants of mathematics. It is a compendium that celebrates not only their academic brilliance, but also the perpetual relevance of their work, fortifying the foundations of the mathematical community.

Scope and Topics: This issue invites a rich tapestry of contributions across various facets of finance, such as:

  1. Stochastic Modeling in Financial Risk: Exploration of advanced stochastic processes and their applications in financial modeling, particularly in the context of epidemic events.
  2. Statistical Methods for Risk Assessment: Cutting-edge methodologies for evaluating financial risks during epidemic times, focusing on extreme value analysis and post-COVID dynamics.
  3. Portfolio Optimization and Asset Allocation: Insightful approaches to optimize investment portfolios, incorporating epidemic-induced uncertainties using probabilistic models.
  4. Insurance and Actuarial Science: Innovative applications in assessing and managing epidemic-related risks within insurance and actuarial frameworks.
  5. Economic Impact Assessment: Utilizing statistical tools to gauge the influence of epidemics on financial markets and global economic structures.
  6. Statistical Learning and Predictive Analytics: Advanced predictive models for financial risk forecasting during or after epidemic events, encompassing credit risk and market prediction.
  7. Dynamic Asset Pricing: Delving into asset pricing models that capture long-range dependencies, heavy-tailed distributions and market asymmetries.
  8. Health Care Finance: Analyzing how financial resources are used in health systems, including revenue raising, the pooling of funds and purchasing services, with a focus on ensuring that the health system can adequately cover the collective health needs of every person.
  9. Alternative Financial Markets—ESG Finance and Investing: Exploring how financial wellbeing is closely linked to perceptions of social relationships, with a focus on financial wellbeing for a sustainable society.

Dr. Shuangzhe Liu
Prof. Dr. Svetlozar (Zari) Rachev
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Risk and Financial Management is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • stochastic modeling in financial risk
  • statistical methods for risk assessment
  • portfolio optimization and asset allocation
  • insurance and actuarial science
  • economic impact assessment
  • statistical learning and predictive analytics
  • dynamic asset pricing
  • health care finance
  • alternative financial markets
  • ESG finance and investing

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (13 papers)

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Research

20 pages, 1830 KiB  
Article
The t-Distribution in Financial Mathematics and Multivariate Testing Contexts
by Eugene Seneta and Thomas Fung
J. Risk Financial Manag. 2025, 18(5), 224; https://doi.org/10.3390/jrfm18050224 - 22 Apr 2025
Viewed by 184
Abstract
The Student’s t-distribution provides a thematic connection between the historical and technical elements of this paper. The historical section offers a brief account of the early contributions of Chris Heyde and his collaborations with Madan and Seneta in the development of financial [...] Read more.
The Student’s t-distribution provides a thematic connection between the historical and technical elements of this paper. The historical section offers a brief account of the early contributions of Chris Heyde and his collaborations with Madan and Seneta in the development of financial mathematics. The technical section focuses on hypothesis testing, motivated by the observation that, in a setting with pairwise exchangeable dependence for test statistics, the cutoff methods proposed by Sarkar and colleagues in 2016 can be viewed as a first iteration of the classical approach developed by Holm in 1979. These methods had already been refined earlier by Seneta and Chen in their work from 1997 and 2005, which laid the foundation for further improvements. Building on this, a new iteration of the Seneta-Chen method is presented, offering enhancements over the Sarkar approach. Numerical and graphical comparisons are provided, focusing on equal tails testing within the multivariate t-distribution framework. While the tabulated results clearly show improvements with the new procedure, the simulated family-wise error rates across varying correlations reveal only minor practical differences between the iterative methods. This suggests that, under suitable conditions, a single iteration suffices in practice. The paper concludes with personal reflections from the first author, sharing memories of Joe Gani and Chris Heyde, in keeping with the commemorative nature of this issue. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
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30 pages, 9138 KiB  
Article
Accuracy Comparison Between Feedforward Neural Network, Support Vector Machine and Boosting Ensembles for Financial Risk Evaluation
by Dat Tran and Allan W. Tham
J. Risk Financial Manag. 2025, 18(4), 215; https://doi.org/10.3390/jrfm18040215 - 15 Apr 2025
Viewed by 360
Abstract
Loan defaults have become an increasing concern for lending institutions, presenting significant challenges to profitability and operational stability. However, with the advent of advanced data processing capabilities, greater data availability, and the development of sophisticated machine learning techniques—particularly neural networks—new opportunities have emerged [...] Read more.
Loan defaults have become an increasing concern for lending institutions, presenting significant challenges to profitability and operational stability. However, with the advent of advanced data processing capabilities, greater data availability, and the development of sophisticated machine learning techniques—particularly neural networks—new opportunities have emerged for classifying and predicting loan defaults beyond traditional manual methods. This, in turn, can reduce risk and enhance overall financial performance. In recent years, institutions have increasingly employed these advanced techniques to mitigate the risk of non-performing loans (NPLs) by improving loan approval efficiency. This study aims to address a gap in the literature by examining the predictive performance of different neural network architectures on financial loan datasets. Specifically, it compares the effectiveness of Feedforward Neural Networks (FNNs), Long Short-Term Memory (LSTM) networks, and one-dimensional Convolutional Neural Networks (1D-CNNs) in forecasting loan defaults. Despite the growing body of research in this area, comparative studies focusing on the application of various neural network techniques to loan default prediction remain relatively scarce. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
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24 pages, 1074 KiB  
Article
Stochastic Modelling of the COVID-19 Epidemic
by Eckhard Platen
J. Risk Financial Manag. 2025, 18(2), 97; https://doi.org/10.3390/jrfm18020097 - 13 Feb 2025
Viewed by 484
Abstract
The need to manage the risks related to the COVID-19 epidemic in health, economics, finance, and insurance became obvious after its outbreak. As a basis for the respective quantitative methods, this paper models, in a novel manner, the dynamics of an epidemic via [...] Read more.
The need to manage the risks related to the COVID-19 epidemic in health, economics, finance, and insurance became obvious after its outbreak. As a basis for the respective quantitative methods, this paper models, in a novel manner, the dynamics of an epidemic via a four-dimensional stochastic differential equation. Crucial time-dependent input parameters include the reproduction number, the average number of externally and newly infected cases, and the average number of new vaccinations. The proposed model is driven by a single Brownian motion process. When fitted to COVID-19 data, it generates the observed features. It captures widely observed fluctuations in the number of newly infected cases. The fundamental probabilistic properties of the dynamics of an epidemic can be deduced from the proposed model. These can form the basis for successfully managing an epidemic and the related economic and financial risks. As a general tool for quantitative studies, a simulation algorithm is provided. A case study illustrates the model and discusses strategies for reopening an economy during an epidemic. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
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16 pages, 658 KiB  
Article
On the Use of the Harmonic Mean Estimator for Selecting the Hypothetical Income Distribution from Grouped Data
by Kazuhiko Kakamu
J. Risk Financial Manag. 2025, 18(2), 72; https://doi.org/10.3390/jrfm18020072 - 1 Feb 2025
Viewed by 579
Abstract
It is known that the harmonic mean estimator is a consistent estimator of the marginal likelihood and is easy to implement, but it has severe biases and does not change as much as the prior distribution changes. In this study, we investigate the [...] Read more.
It is known that the harmonic mean estimator is a consistent estimator of the marginal likelihood and is easy to implement, but it has severe biases and does not change as much as the prior distribution changes. In this study, we investigate the use of the harmonic mean estimator to select the hypothetical income distribution from grouped data through Monte Carlo simulations and apply it to real data in Japan. From the results, we confirm that there are significant biases, but it can be reliably used to select an appropriate model only when the sample size is large enough under appropriate prior settings. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
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20 pages, 699 KiB  
Article
Diagnostic for Volatility and Local Influence Analysis for the Vasicek Model
by Manuel Galea, Alonso Molina and Isabelle S. Beaudry
J. Risk Financial Manag. 2025, 18(2), 63; https://doi.org/10.3390/jrfm18020063 - 29 Jan 2025
Viewed by 820
Abstract
The Ornstein–Uhlenbeck process is widely used in modeling biological systems and, in financial engineering, is commonly employed to describe the dynamics of interest rates, currency exchange rates, and asset price volatilities. As in any stochastic model, influential observations, such as outliers, can significantly [...] Read more.
The Ornstein–Uhlenbeck process is widely used in modeling biological systems and, in financial engineering, is commonly employed to describe the dynamics of interest rates, currency exchange rates, and asset price volatilities. As in any stochastic model, influential observations, such as outliers, can significantly influence the accuracy of statistical analysis and the conclusions we draw from it. Identifying atypical data is, therefore, an essential step in any statistical analysis. In this work, we explore a set of methods called local influence, which helps us understand how small changes in the data or model can affect an analysis. We focus on deriving local influence methods for models that predict interest or currency exchange rates, specifically the stochastic model called the Vasicek model. We develop and implement local influence diagnostic techniques based on likelihood displacement, assessing the impact of the perturbation of the variance and the response. We also introduce a novel and simple way to test whether the model’s variability stays constant over time based on the Gradient test. The purpose of these methods is to identify potential risks of reaching incorrect conclusions from the model, such as the inaccurate prediction of future interest rates. Finally, we illustrate the methodology using the monthly exchange rate between the US dollar and the Swiss franc over a period exceeding 20 years and assess the performance through a simulation study. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
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27 pages, 404 KiB  
Article
ESG Ratings and Financial Performance in the Global Hospitality Industry
by Kefan Lu, Cagri Berk Onuk, Yifei Xia and Jianing Zhang
J. Risk Financial Manag. 2025, 18(1), 24; https://doi.org/10.3390/jrfm18010024 - 9 Jan 2025
Cited by 1 | Viewed by 2302
Abstract
Existing research critically examines the influence of environmental, social, and governance (ESG) ratings on corporate financial performance (CFP), with outcomes varying considerably. This study employs a dataset of publicly traded firms across 16 countries within the hospitality sector from 2005 to 2022 to [...] Read more.
Existing research critically examines the influence of environmental, social, and governance (ESG) ratings on corporate financial performance (CFP), with outcomes varying considerably. This study employs a dataset of publicly traded firms across 16 countries within the hospitality sector from 2005 to 2022 to examine the ESG-CFP relationship. Fixed effects regression results demonstrate a positive linkage between ESG ratings and CFP, utilizing both comprehensive ESG ratings and discrete pillar ratings. These findings remain robust across various performance measures including return on assets, return on equity, and Tobin’s Q. Heteroscedasticity and endogeneity concerns are mitigated through generalized least squares and two-stage least squares methods, respectively. Moreover, the positive impact of ESG on CFP exhibits greater potency in the United States relative to other countries and was more pronounced during the COVID-19 era. These findings offer valuable insights for business executives, investors, and policymakers in supporting ESG initiatives, guiding investment decisions, and formulating effective policy directives. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
12 pages, 272 KiB  
Article
The Modelling of Auto Insurance Claim-Frequency Counts by the Inverse Trinomial Distribution
by Seng Huat Ong, Shin Zhu Sim and Shuangzhe Liu
J. Risk Financial Manag. 2025, 18(1), 7; https://doi.org/10.3390/jrfm18010007 - 27 Dec 2024
Viewed by 859
Abstract
In the transportation services industry, the proper assessment of insurance claim count distribution is an important step to determine insurance premiums based on policyholders’ risk profiles. Risk factors are identified through regression analysis. In this paper, the inverse trinomial distribution is proposed as [...] Read more.
In the transportation services industry, the proper assessment of insurance claim count distribution is an important step to determine insurance premiums based on policyholders’ risk profiles. Risk factors are identified through regression analysis. In this paper, the inverse trinomial distribution is proposed as a count data model for insurance claims characterised by having long tails and a high index of dispersion. Two regression models are developed to identify associated risk factors. Other popular models, such as the negative binomial and COM-Poisson, are fitted and compared to information criteria. The risk profiles of policyholders are determined based on the selected model. To illustrate the application of the inverse trinomial regression models, the ausprivautolong dataset of automobile claims in Australia has been fitted with identification of risk factors. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
20 pages, 288 KiB  
Article
The Relationship Between Sociodemographic Attributes and Financial Well-Being of Low-Income Urban Families Amid the COVID-19 Pandemic: A Case Study of Malaysia
by Abdullah Sallehhuddin Abdullah Salim, Norzarina Md Yatim and Al Mansor Abu Said
J. Risk Financial Manag. 2024, 17(12), 544; https://doi.org/10.3390/jrfm17120544 - 29 Nov 2024
Viewed by 1733
Abstract
The COVID-19 pandemic and the Movement Control Order (MCO) have had a negative impact on the financial well-being of low-income families in urban areas. This study involved respondents living in the public housing project (PPR) residential areas in Kuala Lumpur—the capital of Malaysia. [...] Read more.
The COVID-19 pandemic and the Movement Control Order (MCO) have had a negative impact on the financial well-being of low-income families in urban areas. This study involved respondents living in the public housing project (PPR) residential areas in Kuala Lumpur—the capital of Malaysia. The key finding is that the financial well-being of low-income urban families was negatively impacted due to the COVID-19 pandemic and the MCO implementation. Furthermore, the impact on the financial well-being of low-income urban families is significantly different in terms of types of families, type and sector of employment, type of home ownership, household monthly income, and education level. Reforms to the financial assistance system and the community empowerment of low-income urban families are necessary to increase the community’s preparedness and resilience in the face of new shocks in the future. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
31 pages, 565 KiB  
Article
Environmental, Social and Governance Awareness and Organisational Risk Perception Amongst Accountants
by Hok-Ko Pong and Chun-Cheong Fong
J. Risk Financial Manag. 2024, 17(11), 480; https://doi.org/10.3390/jrfm17110480 - 24 Oct 2024
Viewed by 1118
Abstract
The relationships between accountants’ environmental, social and governance (ESG) awareness and their perceptions of organisational risk are examined in this study. The emphasis is on the operational, strategic, financial and compliance risks of business organisations. A total of 462 accountants in Hong Kong [...] Read more.
The relationships between accountants’ environmental, social and governance (ESG) awareness and their perceptions of organisational risk are examined in this study. The emphasis is on the operational, strategic, financial and compliance risks of business organisations. A total of 462 accountants in Hong Kong were included via stratified random sampling and snowball sampling to ensure population diversity. A stratified random approach was used to include factors such as age, gender, income and experience, and snowball sampling amongst professional networks was used to ensure representativeness. A significant positive relationship exists between ESG awareness and risk perception, with environmental and governance factors emerging as the strongest predictors. Accountants with deep ESG awareness, especially in the aforementioned areas, can successfully identify and manage nontraditional risks such as regulatory changes and environmental threats. The findings highlight the need for institutionalising ESG-focused education in accounting and corporate governance to improve risk management capabilities. Increased ESG awareness can ensure responsible and sustainable business behaviour. Future research can expand the sample of accountants to executives and use longitudinal designs to capture the dynamic nature of ESG awareness and risk perception. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
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32 pages, 552 KiB  
Article
Bayesian Lower and Upper Estimates for Ether Option Prices with Conditional Heteroscedasticity and Model Uncertainty
by Tak Kuen Siu
J. Risk Financial Manag. 2024, 17(10), 436; https://doi.org/10.3390/jrfm17100436 - 29 Sep 2024
Viewed by 1054
Abstract
This paper aims to leverage Bayesian nonlinear expectations to construct Bayesian lower and upper estimates for prices of Ether options, that is, options written on Ethereum, with conditional heteroscedasticity and model uncertainty. Specifically, a discrete-time generalized conditional autoregressive heteroscedastic (GARCH) model is used [...] Read more.
This paper aims to leverage Bayesian nonlinear expectations to construct Bayesian lower and upper estimates for prices of Ether options, that is, options written on Ethereum, with conditional heteroscedasticity and model uncertainty. Specifically, a discrete-time generalized conditional autoregressive heteroscedastic (GARCH) model is used to incorporate conditional heteroscedasticity in the logarithmic returns of Ethereum, and Bayesian nonlinear expectations are adopted to introduce model uncertainty, or ambiguity, about the conditional mean and volatility of the logarithmic returns of Ethereum. Extended Girsanov’s principle is employed to change probability measures for introducing a family of alternative GARCH models and their risk-neutral counterparts. The Bayesian credible intervals for “uncertain” drift and volatility parameters obtained from conjugate priors and residuals obtained from the estimated GARCH model are used to construct Bayesian superlinear and sublinear expectations giving the Bayesian lower and upper estimates for the price of an Ether option, respectively. Empirical and simulation studies are provided using real data on Ethereum in AUD. Comparisons with a model incorporating conditional heteroscedasticity only and a model capturing ambiguity only are presented. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
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24 pages, 349 KiB  
Article
Extended Least Squares Making Evident Nonlinear Relationships between Variables: Portfolios of Financial Assets
by Pierpaolo Angelini
J. Risk Financial Manag. 2024, 17(8), 336; https://doi.org/10.3390/jrfm17080336 - 2 Aug 2024
Viewed by 2589
Abstract
This research work extends the least squares criterion. The regression models which have been treated so far in the literature do not study multilinear relationships between variables. Such relationships are of a nonlinear nature. They take place whenever two or more than two [...] Read more.
This research work extends the least squares criterion. The regression models which have been treated so far in the literature do not study multilinear relationships between variables. Such relationships are of a nonlinear nature. They take place whenever two or more than two univariate variables are the components of a multiple variable of order 2 or an order greater than 2. A multiple variable of order 2 is not a bivariate variable, and a multiple variable of an order greater than 2 is not a multivariate variable. A multiple variable allows for the construction of a tensor. The α-norm of this tensor gives rise to an aggregate measure of a multilinear nature. In particular, given a multiple variable of order 2, four regression lines can be estimated in the same subset of a two-dimensional linear space over R. How these four regression lines give rise to an aggregate measure of a multilinear nature is shown by this paper. In this research work, such a measure is an estimate concerning the expected return on a portfolio of financial assets. The metric notion of α-product is used to summarize the sampling units which are observed. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
27 pages, 1263 KiB  
Article
On Smoothing and Habit Formation of Variable Life Annuity Benefits
by Mogens Steffensen and Savannah Halling Vikkelsøe
J. Risk Financial Manag. 2024, 17(2), 75; https://doi.org/10.3390/jrfm17020075 - 13 Feb 2024
Cited by 1 | Viewed by 1844
Abstract
This paper studies optimal consumption and investment strategies with lifetime uncertainty to design a smooth pension product. In a simplified Black–Scholes market, we investigate three strategies for consumption and investment: the classical strategy, the habit strategy, and the hybrid strategy. Incorporating additive habit [...] Read more.
This paper studies optimal consumption and investment strategies with lifetime uncertainty to design a smooth pension product. In a simplified Black–Scholes market, we investigate three strategies for consumption and investment: the classical strategy, the habit strategy, and the hybrid strategy. Incorporating additive habit formation in preferences leads to a request for less consumption volatility. Studying the consumption dynamics, it turns out that the hybrid strategy complies with the same preferences as the habit strategy. In our design of a smooth pension product, we are highly inspired by the consumption structure under the hybrid strategy and let consumption be specified as a time-dependent weighted average of last year’s consumption level and a standard market rate life annuity. We give two approaches for the investment portfolio. The numerical examples show that consumption under these approaches is less volatile than consumption under the classical strategy. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
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22 pages, 356 KiB  
Article
The Duality Principle for Multidimensional Optional Semimartingales
by Mahdieh Aminian Shahrokhabadi, Alexander Melnikov and Andrey Pak
J. Risk Financial Manag. 2024, 17(2), 43; https://doi.org/10.3390/jrfm17020043 - 25 Jan 2024
Viewed by 1580
Abstract
In option pricing, we often deal with options whose payoffs depend on multiple factors such as foreign exchange rates, stocks, etc. Usually, this leads to a knowledge of the joint distributions and complicated integration procedures. This paper develops an alternative approach that converts [...] Read more.
In option pricing, we often deal with options whose payoffs depend on multiple factors such as foreign exchange rates, stocks, etc. Usually, this leads to a knowledge of the joint distributions and complicated integration procedures. This paper develops an alternative approach that converts the option pricing problem into a dual one and presents a solution to the problem in the optional semimartingale setting. The paper contains several examples which illustrate its results in terms of the parameters of models and options. Full article
(This article belongs to the Special Issue Featured Papers in Finance and Society Wellbeing—in Honor of Professors Joe Gani and Chris Heyde)
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