Mathematical and Quantitative Methods in Finance and Forecasting

Dear Colleagues,

We are pleased to announce the call for papers for the Special Issue, titled “Mathematical and Quantitative Methods in Finance and Forecasting.” This Special Issue focuses on the intersection of mathematics, financial modeling, and predictive analytics, emphasizing the essential role of rigorous mathematical tools in advancing our understanding of financial markets and improving forecasting accuracy across diverse asset classes.

With the rapid development of data-rich financial environments, mathematical finance and forecasting methodologies have become increasingly important interdisciplinary fields. This Special Issue aims to expand current knowledge by showcasing innovative theoretical frameworks, quantitative models, and data-driven methods that address practical challenges faced by researchers and industry practitioners.

Recent global developments—such as policy uncertainty, climate-related risks, and structural changes in commodity and energy markets—have led to heightened volatility and forecasting complexity. In this context, mathematical and quantitative approaches play a fundamental role in

• Modeling the dynamics of asset prices and forecasting their future movements;
• Designing advanced pricing, hedging, and portfolio allocation strategies;
• Applying econometric, statistical, and machine learning techniques to understand financial mechanisms and predict market behavior.

We encourage contributions that apply mathematical and quantitative models to a wide range of financial forecasting problems, with a balance between theoretical innovation and empirical relevance.

Topics of interest include, but are not limited to, the following:

• Mathematical modeling and numerical methods in finance;
• Econometric and statistical techniques for financial forecasting;
• Pricing and risk management of derivatives and structured products;
• Machine learning, deep learning, and AI-based models for asset return prediction;
• Stochastic processes, optimization, and control in financial decision-making;
• Time-series forecasting methods, including MIDAS, transformers, and hybrid frameworks;
• Quantitative models for commodities, carbon markets, and energy finance;
• Other innovative approaches related to mathematical finance and predictive modeling.

We invite researchers, practitioners, and innovators to submit their high-quality research to this Special Issue as we continue to explore new mathematical and quantitative approaches for understanding and forecasting the complex behavior of modern financial markets.

Dr. Meng Han
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 250 words) can be sent to the Editorial Office for assessment.

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.