Title of article
Stock Evaluation under Mixed Uncertainties Using Robust DEA Model
Author/Authors
Peykani, Pejman Faculty of Industrial Engineering - Iran University of Science & Technology, Tehran, Iran , Mohammadi, Emran Faculty of Industrial Engineering - Iran University of Science & Technology, Tehran, Iran , Seyed Esmaeili, Fatemeh Sadat Faculty of Mathematics - Science and Research Branch, Islamic Azad University, Tehran, Iran
Pages
12
From page
73
To page
84
Abstract
Data Envelopment Analysis (DEA) is one of the popular and applicable techniques for assessing
and ranking the stocks or other financial assets. It should be noted that in the financial markets, most of the
times, the inputs and outputs of DEA models are accompanied by uncertainty. Accordingly, in this paper, a
novel Robust Data Envelopment Analysis (RDEA) model, which is capable to be used in the presence of
discrete and continuous uncertainties, is presented. The proposed novel RDEA model in the paper was
implemented in a real case study of Tehran Stock Exchange (TSE). The results showed that the proposed new
RDEA model was effective in the assessment and ranking of the stocks under different scenarios with interval
values.
Keywords
Scenario based robust optimization , Convex uncertainty set , Stock performance measurement , Robust data envelopment analysis
Journal title
Astroparticle Physics
Serial Year
2019
Record number
2469092
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