Open AccessA novel two-phase robust portfolio selection and optimization approach under uncertainty: A case study of Tehran stock exchange
Author(s) -
Pejman Peykani,
Emran Mohammadi,
Armin Jabbarzadeh,
Mohsen Rostamy-Malkhalifeh,
Mir Saman Pishvaee
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0239810
Subject(s) - portfolio , robustness (evolution) , econometrics , portfolio optimization , stock exchange , robust optimization , market liquidity , computer science , stock (firearms) , data envelopment analysis , mathematical optimization , economics , mathematics , financial economics , finance , engineering , biology , mechanical engineering , biochemistry , gene
Portfolio construction is one of the most critical problems in financial markets. In this paper, a new two-phase robust portfolio selection and optimization approach is proposed to deal with the uncertainty of the data, increasing the robustness of investment process against uncertainty, decreasing computational complexity, and comprehensive assessments of stocks from different financial aspects and criteria are provided. In the first phase of this approach, all candidate stocks’ efficiency is measured using a robust data envelopment analysis (RDEA) method. Then in the second phase, by applying robust mean-semi variance-liquidity (RMSVL) and robust mean-absolute deviation-liquidity (RMADL) models, the amount of investment in each qualified stock is determined. Finally, the proposed approach is implemented in a real case study of the Tehran stock exchange (TSE). Additionally, a sensitivity analysis of all robust models of this study is examined. Illustrative results show that the proposed approach is effective for portfolio selection and optimization in the presence of uncertain data.