Advanced Research in Mathematical Economics and Financial Modelling, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E5: Financial Mathematics".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 278

Special Issue Editors


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Finance Department, Faculty of Economics and Business Administration, West University of Timisoara, 300223 Timișoara, Romania
Interests: public economics; uncertainty analysis; invest; statistics
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Guest Editor
School of Economics, Qingdao University, Qingdao 266071, China
Interests: energy economics; international finance; applied econometrics; mathematics
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Special Issue Information

Dear Colleagues,

We are pleased to announce the call for papers for the Special Issue on “Advanced Research in Mathematical Economics and Financial Modelling, 2nd Edition”. Building on the success of the first edition, this Special Issue continues to focus on the intersection of mathematics, economics, and finance, emphasizing the importance of mathematical tools and techniques in advancing our understanding of economic systems and financial markets.

Mathematical economics and financial modelling are rapidly evolving interdisciplinary fields that leverage advanced mathematical methods to analyze and solve complex problems in finance and economics. This Special Issue aims to expand the body of knowledge on these topics and provide practical insights for both academics and industry professionals.

With recent global challenges such as pandemics, shifting monetary policies, and geopolitical conflicts, the financial landscape has seen significant volatility. In this context, mathematical economics plays a crucial role in the following:

  • Modeling the volatility of asset prices and forecasting their future trends;
  • Developing pricing models and optimal asset allocation strategies to manage financial risks effectively;
  • Using advanced econometric and statistical tools to understand economic phenomena and predict market behaviour.

We encourage contributions that explore the applications of mathematical models in various economic and financial contexts, with an emphasis on both theoretical advancements and practical applications.

We welcome papers on a broad range of topics related to mathematical economics and financial modelling, including, but not limited to, the following:

  • Financial engineering challenges and solutions;
  • Statistical and computational methods in finance and economics;
  • Pricing theory and the application of securities, derivatives, and portfolios;
  • Machine learning and AI techniques for asset price prediction;
  • Stochastic optimization and dynamic control in financial models;
  • Mathematical exploration of economic behaviour and phenomena;
  • Advanced econometric models for macro and microeconomics;
  • Other innovative topics in mathematical economics and financial modelling.

We invite researchers, practitioners, and innovators to submit their cutting-edge research for this Special Issue, as we continue to explore new mathematical approaches for understanding and solving the complex problems of modern economics and finance.

Prof. Dr. Oana-Ramona Lobonț
Prof. Dr. Chi-Wei Su
Prof. Dr. Noja Grațiela Georgiana
Dr. Weike Zhang
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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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

  • mathematical economics
  • financial modelling
  • financial engineering
  • structural equation modelling
  • spatial statistics and econometrics
  • stochastic optimization
  • measurement, network analysis and sampling techniques

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Published Papers (1 paper)

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Research

13 pages, 771 KiB  
Article
Valuation of Euro-Convertible Bonds in a Markov-Modulated, Cox–Ingersoll–Ross Economy
by Yu-Min Lian, Jun-Home Chen and Szu-Lang Liao
Mathematics 2025, 13(13), 2075; https://doi.org/10.3390/math13132075 - 23 Jun 2025
Viewed by 112
Abstract
This study investigates the valuation of Euro-convertible bonds (ECBs) using a novel Markov-modulated cojump-diffusion (MMCJD) model, which effectively captures the dynamics of stochastic volatility and simultaneous jumps (cojumps) in both the underlying stock prices and foreign exchange (FX) rates. Furthermore, we introduce a [...] Read more.
This study investigates the valuation of Euro-convertible bonds (ECBs) using a novel Markov-modulated cojump-diffusion (MMCJD) model, which effectively captures the dynamics of stochastic volatility and simultaneous jumps (cojumps) in both the underlying stock prices and foreign exchange (FX) rates. Furthermore, we introduce a Markov-modulated Cox–Ingersoll–Ross (MMCIR) framework to accurately model domestic and foreign instantaneous interest rates within a regime-switching environment. To manage computational complexity, the least-squares Monte Carlo (LSMC) approach is employed for estimating ECB values. Numerical analyses demonstrate that explicitly incorporating stochastic volatilities and cojumps significantly enhances the realism of ECB pricing, underscoring the novelty and contribution of our integrated modeling approach. Full article
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