Provide IPO valuation model using genetic algorithm and compare the value of the proposed model with Op

Subject Areas : Stock Exchange

samaneh fathalian ¹ (Department of Management, Rasht Branch, Islamic Azad University, Rasht, Iran)
seyed Ali Nabavi Chashmi ² (Department of Financial Management, Babol Branch, Islamic Azad University, Babol, Iran)
Ebrahim Chirani ³ (Department of Management, Rasht Branch, Islamic Azad University, Rasht, Iran)

Received: 2022-02-11 Accepted : 2022-03-05 Published : 2022-12-22

Keywords: Genetic Algorithm, Neural network, valuation, IPO, Op,

Abstract :

Proper Ipo Valuation Companies entering the capital market for the first time are critical to both business owners and investors. But the valuation of these stocks is influenced by many quantitative and qualitative factors. Nonlinear intelligent systems such as neural networks and genetic algorithms are good tools for accurately predicting the initial stock value. Therefore, the purpose of this study is to present the IPO valuation model using genetic algorithm and compare the value of the proposed model with Op. For this purpose, data related to 421 companies were collected that during the years 2009 to 1397 had made an initial public offering of shares on the Tehran Stock Exchange. In order to analyze the data, the methods of regression, neural network and genetic algorithm have been used. The results showed that the Ipo valuation model using genetic algorithm is the optimal IPO valuation model. Also, the projected valuation, while close to the OP, while meeting the relative price increase, can meet the expectations of investors and business owners in a proper IPO valuation.