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.
Arab Mazar, M. and Ghasemi, M. (2010). Pricing Initial Public Offerings: combining Artificial Neural Networks and Genetic Algorithm. Accounting and Auditing Review, 16(4), -.
MLA
Arab Mazar, M. , and Ghasemi, M. . "Pricing Initial Public Offerings: combining Artificial Neural Networks and Genetic Algorithm", Accounting and Auditing Review, 16, 4, 2010, -.
HARVARD
Arab Mazar, M., Ghasemi, M. (2010). 'Pricing Initial Public Offerings: combining Artificial Neural Networks and Genetic Algorithm', Accounting and Auditing Review, 16(4), pp. -.
CHICAGO
M. Arab Mazar and M. Ghasemi, "Pricing Initial Public Offerings: combining Artificial Neural Networks and Genetic Algorithm," Accounting and Auditing Review, 16 4 (2010): -,
VANCOUVER
Arab Mazar, M., Ghasemi, M. Pricing Initial Public Offerings: combining Artificial Neural Networks and Genetic Algorithm. Accounting and Auditing Review, 2010; 16(4): -.
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