Issue |
RAIRO-Oper. Res.
Volume 55, 2021
Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
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Page(s) | S2709 - S2726 | |
DOI | https://doi.org/10.1051/ro/2020114 | |
Published online | 02 March 2021 |
Analysis and classification of companies on tehran stock exchange with incomplete information
1
Industrial Engineering And Management, Shahrood University of Technology, Shahrood, Iran
2
Management Sciences, Kharazmi University, Tehran, Iran
3
Kishore Bharati Bhagini Nivedita College, Ramkrishna Sarani, Behala, Kolkata 700060, India
* Corresponding author: shib_sankar@yahoo.com
Received:
5
August
2020
Accepted:
6
October
2020
Due to uncertainty and large number of companies in financial market, it has become difficult to choose the right stock to investments. Identifying and classifying stocks using fundamental criteria help investors to better understand the risks involved in selecting companies and better manage their own capital, thereby rapidly and accurately choose their preferred stock and make more secure profit. The main concern that capital market investors are facing difficulty to choosing the right stock despite the uncertainties in the market. Uncertainties in the market that lead to incomplete information are presented in this article to complete the reciprocal preference relation method. The purpose of this paper is to present a method for completing information to reduce the uncertainties in the market and finally classify companies in each industry based on fundamental criteria. The classification method used is acceptability/reject ability which is based on distance fuzzy analysis yields more accurate results. Finally, a case study on one of the most critical industries in Tehran Stock Exchange is presented to show the effectiveness of the proposed approach.
Mathematics Subject Classification: 90B60 / 90B50
Key words: acceptability / reject ability / stock market / classification
© EDP Sciences, ROADEF, SMAI 2021
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