Paper Information

Journal:   IRANIAN JOURNAL OF BUSINESS AND ECONOMICS   JUNE 2014 , Volume 1 , Number 2; Page(s) 0 To 0.
 
Paper: 

THE MODELING AND PREDICTION OF STOCK PRICES IN THE MINING INDUSTRY IN TEHRAN STOCK EXCHANGE

 
 
Author(s):  AMANDAD OMID*, SEYFI GHOBADI HOSSEIN, BAHARLOOYI FOROUGH, HOSEINIPOUR RAZA
 
* DEPARTMENT OF ACCOUNTING, FERDOWSI UNIVERSITY OF MASHHAD, MASHHAD, IRAN
 
Abstract: 

Financial and economic issues, especially capital markets is one area that is important in today's forecast. Future trend of prices prediction to adopt appropriate strategies for buying or selling is the main goal in these markets. Various techniques exist to predict future stock prices. Fundamental analysis is one method that considers several variables. In this paper, neural network model (RBF) and econometric panel data are used to increase efficiency, reduce costs and time in fundamental analysis. For this purpose, a sample of 17 companies over a period of 7 years (2005-2012) of listed companies in Tehran Stock Exchange are selected in the coal mining industry, mining and other mining, metal ore mining and other non-metallic mineral products. The results indicate good accuracy in modeling to predict the stock price on the Stock Exchange and subset of industries. Also, comparing the accuracy of econometric panel data pattern with neural networks in forecasting stock price represents the neural network has higher precision.

 
Keyword(s): FUNDAMENTAL ANALYSIS, PRICES STOCK PREDICTION, RBF, PANEL DATA, COAL MINING INDUSTRY
 
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