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Comparing Neural Networks and ARMA Models in Artificial Stock Market

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  • Jiri Krtek

    ()

  • Miloslav Vošvrda

    ()

Abstract

Neural networks - feed-forward neural networks and Elman's simple recurrent neural networks - are compared with vector ARMA models - VAR and VARMA - in this paper. They are compared in an artificial stock market. One risk free and one risky asset are traded in the market. There are only trend followers in this model, which use the mentioned models for forecasting change of a price of the risky asset and the dividend.

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File URL: http://ces.utia.cas.cz/bulletin/index.php/bulletin/article/view/174
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Bibliographic Info

Article provided by The Czech Econometric Society in its journal Bulletin of the Czech Econometric Society.

Volume (Year): 18 (2011)
Issue (Month): 28 ()
Pages:

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Handle: RePEc:czx:journl:v:18:y:2011:i:28:id:174

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Keywords: neural networks; vector ARMA; artificial market;

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