Looking at the New Era Challenges in Finance: Forecasting Modeling by Using Artificial Intelligence

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

Deadline for manuscript submissions: 30 April 2024 | Viewed by 257

Special Issue Editors


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Guest Editor
Department of Economics and Political Science, University of Aosta Valley, 11100 Aosta, Italy
Interests: time series; Bayesian econometrics; financial econometrics

E-Mail Website
Guest Editor
Department of Economics and Political Sciences, University of Aosta Valley, 11100 Aosta, Italy
Interests: mathematical economics; stochastic programming; artificial intelligence; dynamic system
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. Department of Law, Economics and Human Sciences, University “Mediterranea” of Reggio Calabria, 89124 Reggio Calabria, Italy
2. The Invernizzi Centre for Research in Innovation, Organization, Strategy and Entrepreneurship (ICRIOS), Bocconi University, Via Sarfatti, 25, 20136 Milano, Italy
Interests: mathematical economics; machine learning and data science; epidemics models; fractional calculus
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid development of machine learning, deep learning, and data science techniques opens new opportunities as well as challenges for financial studies and attracts researchers from different fields, such as mathematics, econometrics, statistics, and informatics. Automatic trading, fraud detection, portfolio management, risk management, the financial implications of climate change, and the role of big data in financial decisions are just some examples of the most recent open fields of research in which these techniques could improve knowledge.

As Guest Editors of this Special Issue of Mathematics, titled “Looking at the New Era Challenges in Finance: Forecasting Modeling by Using Artificial Intelligence”, we would like to invite potential authors to submit papers that investigate new advances in these directions for review and possible publication. Contributions to this Special Issue should be based on quantitative methods based on econometrics, mathematics, and statistical models.

We encourage papers proposing financial theoretical and empirical advances in topics such as (but not limited to) the following: machine learning, deep learning, artificial intelligence for big data, time series forecasting, classification models, portfolio management, risk management, digital finance, climate change modeling and forecasting, stochastic optimization and prediction, automatic trading, and fraud detection.

This Special Issue will bring together contributions from researchers in mathematics, statistics and econometrics, finance, and other affine scientific fields. Papers describing theoretical models as well as experimental advances are expected.

Dr. Consuelo Nava
Dr. Tiziana Ciano
Prof. Dr. Massimiliano Ferrara
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

  • machine learning and deep learning for big data in finance
  • time series forecasting in finance
  • classification models in finance
  • data science for portfolio and risk management
  • climate change modeling and forecasting
  • portfolio and risk management by artificial intelligence
  • digital finance

Published Papers

This special issue is now open for submission.
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