Uncertain Portfolio Optimization Problems: Systematic Review

  • Khalid Belabbes Department of Mathematics, Mohamed V University in Rabat
  • Mostafa elhachloufi
  • Zine El Abidine Guennoun
  • Abderrahim El attar
DOI: https://doi.org/10.19139/soic-2310-5070-2179
Keywords: Uncertainty theory, Statistical risk measure, Portfolio optimization, Risk measure, Real features

Abstract

This paper presents a literature review and analysis of Uncertain Portfolio Optimization Problems (UPOP), where security returns are described by uncertain variables due to a lack of historical data. To identify the major gaps in literature and offer perspectives for future research to address these limitations, this paper reviews more than 80 works that have shaped the field among foundational works and recent advancements in UPOP until 2024. We have presented the definitions and some comparisons between various mathematical risk measures to allow the decision-maker to choose which one is appropriate for their situation. In addition, some real features that marked literature are introduced. This has provided a number of enhancements that have been suggested as, artificial intelligence utilization, considering environmental constraints and, using other techniques to model asset returns as the uncertain random variables and employing dynamic and multi-period optimization methods.
Published
2024-11-26
How to Cite
Belabbes, K., Mostafa elhachloufi, Zine El Abidine Guennoun, & Abderrahim El attar. (2024). Uncertain Portfolio Optimization Problems: Systematic Review. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-2179
Issue
Online First
Section
Research Articles
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