Application of artificial neural network models and principal component analysis method in predicting stock prices on Tehran Stock Exchange

Javad Zahedi and Mohammad Mahdi Rounaghi

Physica A: Statistical Mechanics and its Applications, 2015, vol. 438, issue C, 178-187

Abstract: Stock price changes are receiving the increasing attention of investors, especially those who have long-term aims. The present study intends to assess the predictability of prices on Tehran Stock Exchange through the application of artificial neural network models and principal component analysis method and using 20 accounting variables. Finally, goodness of fit for principal component analysis has been determined through real values, and the effective factors in Tehran Stock Exchange prices have been accurately predicted and modeled in the form of a new pattern consisting of all variables.

Keywords: Artificial neural networks; Prediction stock price; Principal component analysis (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:438:y:2015:i:c:p:178-187

DOI: 10.1016/j.physa.2015.06.033

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