Innovative Approaches to Financial Modeling and Decision-Making

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: 28 February 2026 | Viewed by 1167

Special Issue Editors


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Guest Editor
Finance Area, College of Business and Interdisciplinary Neuroscience Program, University of Rhode Island, 7 Lippitt Road, Kingston, RI 02881, USA
Interests: computational finance; behavioral portfolio optimization; AI/ML optimization; explainable AI (XAI); operational research; translational neuroscience

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Guest Editor
1. Department of Computer Science and Statistics, College of Arts and Sciences, University of Rhode Island, 9 Greenhouse Road, Kingston, RI 02881, USA
2. The NKD-Group, Inc., 777 Smith Street, Providence, RI 02908, USA
Interests: computational finance; explainable AI (XAI); machine learning modeling; neural networks; predictive analytics; statistical machine learning; operational research

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Guest Editor Assistant
Department of Business Management, School of Business, SUNY Farmingdale, 2350 Broadhollow Road, Farmingdale, NY 11735, USA
Interests: game theory; supply chain management; green finance; simulation theory

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Guest Editor Assistant
1. School of Accounting, Economics and Finance, University of KwaZulu-Natal, 238 Mazisi Kunene Road, Glenwood, Durban 4041, South Africa
2. Sigma International, Office 14, West Riding Office Park, 50 W Riding Row, Sherwood, Durban 4091, South Africa
Interests: SME finance; climate change; enterprise diagnostics; data analytics; AI/ML modeling

Special Issue Information

Dear Colleagues,

Over the past decade, growing environmental complexity has driven financial decision making to explore innovative quantitative modeling approaches capable of addressing decision-making ambiguities. As financial modeling expands its scope with unprecedented precision, this pursuit has spurred advancements in machine learning, network theory, fuzzy logic, and other state-of-the-art techniques. Collectively, these innovations have propelled groundbreaking research in asset pricing, behavioral portfolio management, fixed income valuation, energy finance, healthcare financial management, tourism finance, biodiversity finance, and SME finance—fields that now require cutting-edge solutions more than ever. Undoubtedly, pioneering financial research will continue to shape global economic stability and improve the well-being of present and future generations.

To promote research on issues that bear on innovation in financial decision making, we invite the submission of empirical, theoretical, and experimental papers that study innovative advances in modeling and decision-making in finance. This Special Issue aims to deepen the understanding of how firms, different types of investors, government entities, households, and other market participants might use innovative approaches to financial decision making. This volume will explore the broader societal and regulatory implications of emerging and potentially disruptive innovations in financial decision making. To be considered for inclusion, papers must examine how innovative financial modeling shapes these outcomes.

Researchers who wish to use the WinORS-AI system for neural network simulations or multiobjective optimization can request access by emailing nina@nkd-group.com. WinORS-AI is a product of NKD Group, Inc.

Prof. Dr. Gordon H. Dash
Dr. Nina Kajiji
Guest Editors

Dr. Bruno Kamdem
Dr. Helper Zhou
Guest Editor Assistants

Manuscript Submission Information

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Keywords

  • asset pricing
  • behavioral portfolio management
  • biodiversity financing
  • credit risk valuation
  • energy finance
  • financial decision-making
  • financial derivatives
  • healthcare financing
  • innovation
  • machine learning
  • post hoc AI model performance
  • SDG financing
  • small medium enterprise finance
  • tourism finance

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Published Papers (1 paper)

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Research

10 pages, 269 KB  
Article
External Habit Persistence and Individual Portfolio Choice
by Timothy K. Chue
J. Risk Financial Manag. 2025, 18(10), 577; https://doi.org/10.3390/jrfm18100577 - 11 Oct 2025
Viewed by 466
Abstract
This paper shows that a common form of external habit persistence, despite having much success in asset pricing, implies an extreme degree of conformity in investors’ portfolio choice. If an investor with this utility function uses US aggregate consumption as her external habit [...] Read more.
This paper shows that a common form of external habit persistence, despite having much success in asset pricing, implies an extreme degree of conformity in investors’ portfolio choice. If an investor with this utility function uses US aggregate consumption as her external habit benchmark, she has to hold all non-redundant securities contained in the US aggregate wealth portfolio. Even for an investor who uses the average consumption of a more narrowly-defined community as her benchmark, she is still required to hold non-zero positions in all (non-redundant) individual stocks held by any other member of the community. If markets are incomplete, even if an individual investor holds a financial portfolio that conforms perfectly with that associated with the external habit benchmark, it is still impossible for the investor to ensure that consumption exceeds habit in all states of the world. Because of this implication, this form of external habit is unlikely to describe the preferences of individual investors—notwithstanding its success as a model for the representative agent in asset pricing. Full article
(This article belongs to the Special Issue Innovative Approaches to Financial Modeling and Decision-Making)
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