Article Authors : Mohammad Arabmazar Yazdi , Mahsa Ghasemi

Published by : THE IRANIAN ACCOUNTING AND AUDITING REVIEW

Abstract :

The article set out to create useful predicting tool for pricing initial public offerings through combining neural networks and genetic algorithm. The theoretical framework of this study is information asymmetry theory. Although the literature of pricing initial public offerings introduces variety of possible signals, a few of them have considerable effect on efficiency of predicting. The results show that combining neural networks and genetic algorithm in order to selecting the best variables improves considerably the forecasting power.

Email: m84ghasemi@gmail.com