Explaining the Optimal Model of Appraisal and Pricing of the Initial Pablic Offering using Fuzzy Multi-Criteria Decision Making Techniques, Multivariate Regression, Neural Network and Genetic Algorithm
Subject Areas : Financial engineeringsamaneh fathalian 1 , sayyed Ali Nabavi Chashmi 2 , Ebrahim Chirani 3
1 - Department of Financial Management, Rasht Branch, Islamic Azad University, Rasht, Iran.
2 - Department of Finance, Babol Branch, Islamic Azad University, Babol, Iran.
3 - Department of management, Faculty of Humanities, Rasht Branch, Islamic Azad University, Rasht, Iran
Keywords: Genetic Algorithm, Neural network, Pricing, stepwise regression, IPO,
Abstract :
Valuation and pricing of securities the process of estimating the value of securities is one of the initial shares of companies. Because, on the one hand, investors need to know in a conscious investment that knows the true value of the stock they are interested in investing in and on the other hand, the owners of companies that are going to sell their securities have to evaluate and value their assets in a proper manner. Therefore, the purpose of this study is to explain the optimal model of evaluation and pricing of the initial public supply of shares of companies accepted in Tehran Stock Exchange using fuzzy multi-criteria decision-making techniques, stepwise regression, neural network and genetic algorithm. To this end, data on 421 companies were collected that during the years 2006 to 2018 launched a public offering of shares on the Tehran Stock Exchange. Fuzzy AHP method, forward regression, neural network and genetic algorithm are also used to analyze the data. The results of the research showed that the genetic algorithm model is the optimal pricing model and initial stock valuation.
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