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Application of Optimistic and Pessimistic OWA and DEA Methods in Stock Selection
Author(s) -
Amin Gholam R.,
Hajjami Mohaddeseh
Publication year - 2016
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21824
Subject(s) - pessimism , data envelopment analysis , computer science , stock (firearms) , econometrics , selection (genetic algorithm) , operations research , mathematical optimization , economics , mathematics , artificial intelligence , engineering , mechanical engineering , philosophy , epistemology
One of the main objectives of fund managers in financial service industry is to select superior stocks by analyzing financial ratios. This paper proposes a novel methodology for stock selection by integrating optimistic and pessimistic ordered weighted averaging (OWA) and data envelopment analysis (DEA) methods. The paper first reveals the drawback of using the standard DEA models for stocks evaluation and then proposes a new method by using the OWA operator. Unlike the classical DEA, the proposed method in this paper does not involve the specification of inputs and outputs. The paper incorporates optimistic and pessimistic scenarios and generates interval OWA scores for all stocks. This is followed by using appropriate interval DEA models for selecting superior stocks. The proposed method in this paper is applied to identify high financial performance stocks in the Tehran stock market.