HA270 : Analysis and classification on Tehran Stock Exchange using Intuitive Fuzzy Methods with Incomplete Information
Thesis > Central Library of Shahrood University > Industrial Engineering & Management > MSc > 2019
Authors:
Abstarct: Nowadays due to the development of financial markets and the government's attention to the capital market, classifying the listed companies at the stock exchange market is a valuable way. Classification allows capital market investors to make the right choices in the shortest time and as soon as possible, and chose their desired company, and to minimize market risk as much as possible. Capital market experts consider different criteria for classifying listed companies, most of which are extracted from the company's financial statements and conditions so they can look more closely at the company's profitability and growth trends. They provide a more accurate comparison of the current situation of companies relative to each other. The innovations presented in this study can be applied to the proposed classification method of listed companies at the stock exchange market which can be achieved by the fundamental criteria of the companies and most importantly the opinions of the experts. Also, because the capital market is widespread and the information of some experts about some companies is inadequate, it is possible to create incomplete information but by the method presented in this study, the incomplete information becomes completed. Since it is not possible to compare the financial ratios of two companies from two different industries, therefore, this study classifies the two industries separately. The sugar industry is first classified because of the small number of companies in this industry and because of this small number we could be able to express the proposed method and then one of the most important and sensitive industries of the Iranian stock exchange (chemical industry) is classified and reviewed.
Keywords:
#Classification #Stock Exchange Companies #Financial Ratios #Intuitive Fuzzy #Similarity-baxsed Classification #Uncertainty #Incomplete Information
Keeping place: Central Library of Shahrood University
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Keeping place: Central Library of Shahrood University
Visitor: