Integration of artificial intelligence techniques to Model to predict stock prices

Subject Areas :

مهدی Moradzadeh ¹ (استادیار، گروه آموزشی حسابداری، واحد کرج ، دانشگاه آزاد اسلامی، کرج، ایران)
رویا Darabi ² (استادیار، گروه آموزشی حسابداری، واحد تهران جنوب ، دانشگاه آزاد اسلامی، تهران، ایران)
رامین Shahalizadeh ³ (کارشناس ارشد حسابداری)

Received: 2015-05-06 Accepted : 2015-05-06 Published : 2014-12-22

Keywords:

Abstract :

Stock exchange is a secure way to gain public trust for investment in different securities with varying risks. In this way small and scattered capitals which cannot be utilized alone can be accumulated and a huge investment can be made of them for economic development and progress. In stock exchange, there are a lot of sensitivities to price formation course. This has caused that changes related to such phenomenon to be systematically analyzed. In recent years, a variety of models have been employed by specialists for prediction of share price. Since Artificial Intelligence Techniques which include Neural Networks, Genetic Algorithm and Fuzzy Logic have achieved successful results in complex problems, they are used more for this purpose. Present study intends to answer the question whether using a combination of Artificial Intelligence Technique, a model can be set up which compared to other linear and non-linear methods predicts share price with less error. In this research, to predict stock price (Tehran stock exchange - Iran Khodro CO), a combination of Artificial Intelligence Methods including Neural Networks, Fuzzy Logic and Genetic Algorithm are used and this combined model is compared with Neural Network Methods, the title for one of the other Artificial Intelligence Models, and ARIMA linear model, given R2, MAE, MAPE, MSE. The results of this research shows that the superiority of Hybrid model compared to other models are examined.