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Machine Learning in Finance, Insurance and Risk Management

Special Issue Information

Dear Colleagues,

In recent years, machine learning has seen tremendous successes in many areas. In insurance and finance, additional difficulties due to the inherently dynamic and complex environment, small data, and the need for a precise understanding of the risks of applied algorithms pose enormous challenges to research and practice.

This Special Issue collects some of the latest developments with a focus on applications and their possible risks. Code for the used algorithms will be made available.

Prof. Dr. Thorsten Schmidt
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. Risks 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 1800 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

  • deep neural networks
  • machine learning
  • finance
  • insurance
  • calibration
  • hedging
  • risk estimation
  • risk management
  • big and small data
  • time series forecasting
  • premium calculation
  • risks of ML

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Risks - ISSN 2227-9091
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