Abstract
In this chapter, we examine a simple model of stock market, where artificial neural networks play the role of traders. Each net is assumed to take long/short positions in the market, according to perception of future price fluctuations they have formed during a learning procedure over past data. Final price results from the market mechanism applied to different nets assuming various positions. Experimental results are then compared to real data, testing their consistency under financial and statistical profiles.
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© 2016 Springer International Publishing Switzerland
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Resta, M. (2016). SOM Variants for the Simulation of Market Price Modeling. In: Computational Intelligence Paradigms in Economic and Financial Decision Making. Intelligent Systems Reference Library, vol 99. Springer, Cham. https://doi.org/10.1007/978-3-319-21440-5_4
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DOI: https://doi.org/10.1007/978-3-319-21440-5_4
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-21439-9
Online ISBN: 978-3-319-21440-5
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