Abstract:
The main goal of this paper is to propose a new approach for efficiency measurement
and ranking of stocks. Data envelopment analysis (DEA) is one of the popular
and applicable techniques that can be used to reach this goal. However, there
are always concerns about negative data and uncertainty in financial markets.
Since the classical DEA models cannot deal with negative and imprecise values,
in this paper, possibilistic range directional measure (PRDM) model is proposed
to measure the efficiencies of stocks in the presence of negative data and uncertainty
with input/output parameters. Using the data from insurance industry, this
model is also implemented for a real case study of Tehran stock exchange (TSE)
in order to analyse the performance of the proposed method.
Machine summary:
Fuzzy Data Envelopment Analysis Approach for Ranking of Stocks with an Application to Tehran Stock Exchange Pejman Peykania, Emran Mohammadi*,a, Mohsen Rostamy-Malkhalifehb, Farhad Hosseinzadeh Lotfib aFaculty of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran bDepartment of Mathematics, Faculty of Science, Science and Research Branch, Islamic Azad University, Tehran, Iran ARTICLE INFO Article history: Received 24 August 2018 Accepted 29 December 2018 Keywords: Stocks Ranking Fuzzy DEAInsurance Companies ABSTRACT The main goal of this paper is to propose a new approach for efficiency measure- ment and ranking of stocks.
Since the classical DEA models cannot deal with negative and imprecise values, in this paper, possibilistic range directional measure (PRDM) model is proposed to measure the efficiencies of stocks in the presence of negative data and uncer- tainty with input/output parameters.
The FDEA model for dealing with negative data are proposed based on RDM models with envelopment and multiplier forms by applying the pos- sibility approach.
Finally, by applying Equations (8) and (9), an equivalent crisp of fuzzy chance constraint according to one specific confidence level with using of possibility measure is as follows: (View the image of this page) m s å i =1 ((a n +1 ) R3- + (1 - a ) R4 - )v + å r =1 ((a (View the image of this page) Models (12) and (13) are fuzzy RDMs in envelopment and multiplier forms, respectively and they are based on possibility approach.
Then, fuzzy RDM modeling in envelopment and multiplier forms based on possibility approach were proposed.