Computational Intelligence Algorithms in Economics and Finance

Dear Colleagues,

Computational intelligence, intended as a broad set of techniques that extract information from massive datasets, has gained a prominent role in many fields of applications and Economics and Finance are no exceptions. This is particularly true in contexts where analyses were previously conducted through models validated on small datasets. The wide availability of massive datasets, e.g., on trading operations, has revolutionized the ways of conducting analysis. The applications of CI techniques include short- and long-term forecasting, risk classification, optimal resource allocation, and optimal pricing of assets and services. The tasks called for include classification, regression, and optimization.

For this Special Issue, we welcome innovative contributions and applications of Machine Learning and Computational Intelligence Algorithms in all areas of Economics and Finance, including financial applications that address climate and environmental risk assessment. The primary acceptance criterion for submission will be the high quality and originality of the contribution.

We especially welcome innovative contributions related to, but not limited to, the following main topics:

• Machine learning
• Deep learning
• Neural networks
• Genetic algorithms
• Credit risk
• Market risk
• Liquidity risk
• Climate risk
• Asset and derivative pricing
• Network modelling
• Portfolio optimization
• Systemic risk
• Insurance

Prof. Maurizio Naldi
Dr. Loretta Mastroeni
Guest Editors

Manuscript Submission Information

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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.

• computational intelligence
• machine learning
• deep learning
• data analytics
• business analytics
• risk analysis
• ML applications in economics and finance