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Forecasting of earnings per share for accepted firms in Tehran's stock exchange by utilizing the genetic algorithm of artificial neural network

Tourism & management studies, 2013 (3 (Proceedings TMS Int. Conference 2012: Financial Management), p.863-869 [Peer Reviewed Journal]

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  • Title:
    Forecasting of earnings per share for accepted firms in Tehran's stock exchange by utilizing the genetic algorithm of artificial neural network
  • Author: Nekouei, Mohammad Hossein ; Sarchami, Mohammad
  • Subjects: Artificial Neural Network ; Earnings per Share ; Genetic Algorithm
  • Is Part Of: Tourism & management studies, 2013 (3 (Proceedings TMS Int. Conference 2012: Financial Management), p.863-869
  • Description: Forecasting the Earnings per Share for Investments is Particularly Important because it is considered an Important Factor in Share assessment methods and a Fundamental Factor in making Investment decisions. In Order to Forecast earnings per share using an Artificial Neural Network, 61 Firms were selected in eight Financial Years From the Beginning of 2000 to the End of 2007 along With 9 Variables (8 Input Variables and 1 Output Variable), yielding 4392 (9 x 8 x 61) data points. The Research Hypothesis is that a Neural Network with a genetic algorithm can forecast earnings per share. In order to Test the Hypothesis, MATLAB Software was used to determine the Mean Square Error and Mean Absolute Error. The researchers' hypothesis is supported.
  • Language: English
  • Identifier: ISSN: 2182-8458
    ISSN: 2182-8466
    EISSN: 2182-8466
  • Source: Dialnet
    DOAJ Directory of Open Access Journals
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