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Computational approaches and data analytics in financial services: A literature review

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  • Dimitris Andriosopoulos
  • Michalis Doumpos
  • Panos M. Pardalos
  • Constantin Zopounidis

Abstract

The level of modeling sophistication in financial services has increased considerably over the years. Nowadays, the complexity of financial problems and the vast amount of data require an engineering approach based on analytical modeling tools for planning, decision making, reporting, and supervisory control. This article provides an overview of the main financial applications of computational and data analytics approaches, focusing on the coverage of the recent developments and trends. The overview covers different methodological tools and their uses in areas, such as portfolio management, credit analysis, banking, and insurance.

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  • Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
  • Handle: RePEc:taf:tjorxx:v:70:y:2019:i:10:p:1581-1599
    DOI: 10.1080/01605682.2019.1595193
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    Cited by:

    1. C. A. Valle & J. E. Beasley, 2019. "A nonlinear optimisation model for constructing minimal drawdown portfolios," Papers 1908.08684, arXiv.org.
    2. Nguyet Nguyen & Dung Nguyen, 2020. "Global Stock Selection with Hidden Markov Model," Risks, MDPI, Open Access Journal, vol. 9(1), pages 1-18, December.

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