Management Science Letters (Aug 2012)

Neural networks and forecasting stock price movements-accounting approach: Empirical evidence from Iran

  • Hossein Naderi,
  • Mojtaba Moradpour,
  • Mehdi Zangeneh,
  • Farzad Khani

Journal volume & issue
Vol. 2, no. 4
pp. 1417 – 1424

Abstract

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Stock market prediction is one of the most important interesting areas of research in business. Stock markets prediction is normally assumed as tedious task since there are many factors influencing the market. The primary objective of this paper is to forecast trend closing price movement of Tehran Stock Exchange (TSE) using financial accounting ratios from year 2003 to year 2008. The proposed study of this paper uses two approaches namely Artificial Neural Networks and multi-layer perceptron. Independent variables are accounting ratios and dependent variable of stock price , so the latter was gathered for the industry of Motor Vehicles and Auto Parts. The results of this study show that neural networks models are useful tools in forecasting stock price movements in emerging markets but multi-layer perception provides better results in term of lowering error terms.

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