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A Comparative Study of a Financial Agent Based Simulator Across Learning Scenarios

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Agents and Data Mining Interaction (ADMI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7103))

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Abstract

Integrating agent based modeling with learning results in a promising methodology to model the behavior of financial markets. We discuss here how partial and full knowledge learning setups can be combined with agent based modeling to approximate the behavior of financial time series. Partial knowledge learners operate with limited knowledge of the domain, usually only the initial conditions are used. While full knowledge learners use any domain data any time it is made available to adjust their predictions.

We report in this paper an experimental study of our learning system L-FABS, introduced in previous works, in order to show how it can discover models for approximating time series working in partial knowledge and full knowledge learning scenarios.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, University of Naples, 80100, Naples, Italy

    Filippo Neri

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  1. Filippo Neri
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Editor information

Editors and Affiliations

  1. Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, PO Box 123, 2007, Sydney, NSW, Australia

    Longbing Cao

  2. Instituto de Informática, Universidade Federal do Rio Grande do Sul (UFRGS), Caixa Postal 15064, 91.501-970, Porto Alegre, RS, Brazil

    Ana L. C. Bazzan

  3. Electrical and Computer Engineering Department, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece

    Andreas L. Symeonidis

  4. St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, 39, 14th Liniya, 199178, St. Petersburg, Russia

    Vladimir I. Gorodetsky

  5. Department of Knowledge Engineering, Maastricht University, P.O. Box 616, 6200, Maastricht, MD, The Netherlands

    Gerhard Weiss

  6. Department of Computer Science, University of Illinois at Chicago, 851 S. Morgan Street, Room 1138 SEO, 60607, Chicago, IL, USA

    Philip S. Yu

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Neri, F. (2012). A Comparative Study of a Financial Agent Based Simulator Across Learning Scenarios. In: Cao, L., Bazzan, A.L.C., Symeonidis, A.L., Gorodetsky, V.I., Weiss, G., Yu, P.S. (eds) Agents and Data Mining Interaction. ADMI 2011. Lecture Notes in Computer Science(), vol 7103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27609-5_7

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  • DOI: https://doi.org/10.1007/978-3-642-27609-5_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27608-8

  • Online ISBN: 978-3-642-27609-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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