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- W2136300989 abstract "Article history: Received December 1, 2011 Received in Revised form February, 14, 2011 Accepted 24 March 2012 Available online March 25 2012 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. © 2012 Growing Science Ltd. All rights reserved." @default.
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- W2136300989 date "2012-07-01" @default.
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- W2136300989 title "Neural networks and forecasting stock price movements-accounting approach: Empirical evidence from Iran , Pages 1417-1424" @default.
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- W2136300989 doi "https://doi.org/10.5267/j.msl.2012.03.019" @default.
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