A Scientometric Analysis of Robust Portfolio Optimization

Document Type : Review article

Authors

• Amirhossein Eskorouchi ¹
• Hossein Ghanbari ¹
• Emran Mohammadi ²

¹ School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

² IUST

10.22067/ijaaf.2023.84137.1402

Abstract

During the past few years, there have been some turbulent events in the global economy that have significantly impacted the performance of financial markets. Therefore, there is an urgent need for a robust method to deal with the existing uncertainties related to the performance of financial entities. Robust portfolio optimization (RPO) refers to developing an investment strategy that performs well even in the worst-case scenario of the uncertain inputs, e.g., return and covariance. This research paper provides a systematic review of recent developments of this field and its extensions. The authors use bibliometric analysis and visual mapping techniques to examine the evolution and trends of 1085 articles published between 2000 and 2023. The analysis explores the evolution and trends within RPO, while also investigating the interconnectedness among articles, authors, sources, countries, and keywords. The insights gained from our analysis can inform future research directions in this field and help practitioners make better-informed investment decisions.

Keywords

• Robust optimization
• Portfolio selection
• Risk measures
• Scientometrics

Main Subjects

• Finance

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