Volume 15, Issue 2 (7-2018)                   2018, 15(2): 89-107 | Back to browse issues page

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Shahbandarzadeh H, Omrani N, Sheikhiani A. Financial Performance Evaluation of Companies Stock of Tehran Stock Exchange by Using Integrated Fuzzy Logarithmic Preference Programming (Case Study: Multiple Fields Industry). Journal of Operational Research and Its Applications. 2018; 15 (2) :89-107
URL: http://jamlu.liau.ac.ir/article-1-782-en.html
Associate Professor, Department of Industrial Management, Persian Gulf University, Boushehr
Abstract:   (2358 Views)
The most important issue for investors in stock exchange is how to select appropriate stock in order to achieve most yields. So, financial performance evaluation of companies can help investors in investment appropriate decision making .One of the performance evaluation methods is ranking companies stock according to different financial criteria.
This research uses Integrated Fuzzy Logarithmic Preference Programming method in order to rank companies stock of «multiple fields industry». Mentioned method is a two-step nonlinear programming model that extracts relative importance degree of the companies stock and performance evaluation criteria from fuzzy paired comparison matrix.
Findings of the research shows that the stock of Tosey-e-Melli group investment company has had the best performance and the stock of Omid investment company has had the worst performance during the performance evaluation period (year 1395). Moreover, according to the views of analysts and experts of the capital market, the criteria «Earning Per Share» and «P/E» have the most effect on performance evaluation of the companies stocks.
According to the achieved results, it’s recommended that this method should be used in order to investment portfolio construction at a greater level. Moreover, it’s necessary that different investors for companies stock analysis consider more about the criteria «Earning Per Share» and «P/E».
 
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Type of Study: Applicable | Subject: Special
Received: 2016/05/14 | Accepted: 2016/11/30 | Published: 2018/07/15

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