A Scientometric Analysis of Robust Portfolio Optimization

Iranian Journal of Accounting, Auditing and Finance

مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 28 آبان 1402   

نوع مقاله: Review article

شناسه دیجیتال (DOI): 10.22067/ijaaf.2023.84137.1402

نویسندگان

Amirhossein Eskorouchi¹؛ Hossein Ghanbari¹؛ Emran Mohammadi^{* 2}

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

²IUST

چکیده

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.

کلیدواژه‌ها

Robust optimization؛ Portfolio selection؛ Risk measures؛ Scientometrics