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Mathematical Modelling in Economics and Finance
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Mathematical Modelling in Economics and Finance

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: 31 December 2026 | Viewed by 1363

Special Issue Editor

Dr. Heni Boubaker

E-Mail Website
Guest Editor
1. Department of Quantitative Methods, Institute of High Commercial Studies (IHEC) of Sousse, LaREMFiQ, B.P. 40, Sousse 4054, Tunisia
2. Department of Finance, IPAG Business School, IPAG LAB, 184 Boulevard Saint-Germain, 75006 Paris, France
Interests: econometric theory; financial econometrics; time series and panel data econometrics; applied mathematics; artificial intelligence methods; signal processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Mathematical modelling in economics and finance still remains an essential tool allowing the explanation of several phenomena appearing on different financial markets. The development of mathematical and probabilistic models for finance and economics has made it possible to progress in the field of forecasting under turbulent and uncertain conditions. Indeed, research on stochastic processes and probability models has provided a natural set of applications for the vast array of tools and results developed in business and economics theory. Nevertheless, mathematical finance has also been a source of new research questions and challenges in recent years that have generated new motivations and momentum for research on stochastic processes. The main objective of this Special Issue is to approve new approaches to stochastic modelling and estimate density function that deepen our insights into modelling and predicting techniques. This Special Issue aims at collecting original contributions containing new theoretical and/or empirical results in the context of economic and finance modelling, estimating and forecasting using mathematical, statistical, and econometric implements. However, effective alternative approaches are also encouraged.

Dr. Heni Boubaker
Guest Editor

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 process
  • density estimation
  • mathematical finance
  • modelling methods
  • forecasting approach

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Published Papers (1 paper)

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Research

30 pages, 3231 KiB  
Article
The End of Mean-Variance? Tsallis Entropy Revolutionises Portfolio Optimisation in Cryptocurrencies
by Sana Gaied Chortane and Kamel Naoui
J. Risk Financial Manag. 2025, 18(2), 77; https://doi.org/10.3390/jrfm18020077 - 3 Feb 2025
Viewed by 1087
Abstract
Has the mean-variance framework become obsolete? In this paper, we replace traditional variance–covariance methods of portfolio optimisation with relative Tsallis entropy and mutual information measures. Its goal is to enhance risk management and diversification in complicated finance ecosystems. We utilize the S&P 500 [...] Read more.
Has the mean-variance framework become obsolete? In this paper, we replace traditional variance–covariance methods of portfolio optimisation with relative Tsallis entropy and mutual information measures. Its goal is to enhance risk management and diversification in complicated finance ecosystems. We utilize the S&P 500 and Bitwise 10 cryptocurrency indices’ daily returns (2019–2024 data) and conduct our analysis to the year 2020 under extreme shocks. Many models were trained with different configurations, like mean-variance (MV), mean-entropy (ME), and mean-mutual information (MI) traders and their corresponding variants, using Sharpe’s ratio, Jensen’s alpha, and entropy value of risk (EVAR). The findings indicate that entropic models outperform conventional models in terms of diversification and, especially, extreme risk management. Because the appropriate normalization conditions often fail to be satisfied, we can informally see that after a recalibration of the effective frontier, we obtain from EVAR an accumulated resilience aspect to these rare events while also observing the great potential of entropy-based models to replicate non-linear dependencies between assets. The results show that models combining entropy and mutual information optimise the gain–loss ratio (GLR), providing stable diversification and improved risk management, while maximising returns in complex and volatile market environments. Full article
(This article belongs to the Special Issue Mathematical Modelling in Economics and Finance)
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