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European Conference on the Applications of Evolutionary Computation

EvoApplications 2011: Applications of Evolutionary Computation pp 81–90Cite as

Using Evolutionary Neural Networks to Test the Influence of the Choice of Numeraire on Financial Time Series Modeling

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6625))

Abstract

This work presents an evolutionary solution that aims to test the influence of the choice of numeraire on financial time series modeling. In particular, the method used in such a problem is to apply a very powerful natural computing analysis tool, namely evolutionary neural networks, based on the joint evolution of the topology and the connection weights together with a novel similarity-based crossover, to a couple of very liquid financial time series expressed in their trading currency and several alternative numeraires like gold, silver, and a currency like the euro, which is intended to be stable ‘by design’, and compare the results.

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References

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Author information

Authors and Affiliations

  1. Dipartimento di Tecnologie dell’Informazione, Universita’ degli Studi di Milano, Italy

    Antonia Azzini, Mauro Dragoni & Andrea G. B. Tettamanzi

Authors
  1. Antonia Azzini
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  2. Mauro Dragoni
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  3. Andrea G. B. Tettamanzi
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, University of Strathclyde, 16 Richmond Street, G1 1XQ, Glasgow, UK

    Cecilia Di Chio

  2. School of Business, University College Dublin, 4, Belfield, Dublin, UK

    Anthony Brabazon

  3. Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Galleria 2, 6928, Manno-Lugano, Switzerland

    Gianni A. Di Caro

  4. Institute of Computer Science, University of Bremen, 28359, Bremen, Germany

    Rolf Drechsler

  5. Next Generation Intelligent Networks Research Center (nexGIN RC), National University of Computer & Emerging Sciences (FAST-NU), Islamabad, Pakistan

    Muddassar Farooq

  6. Department of Information Systems, Johannes Gutenberg-Universität, 55099, Mainz, Germany

    Jörn Grahl

  7. Mathematics and Computer Science Depatment, University of Richmond, 23173, Richmond, VA, USA

    Gary Greenfield

  8. ICD - OSI, University of Technology of Troyes, 12, Rue Marie Curie, BP 2060, 10010, Troyes, France

    Christian Prins

  9. Facultad de Informatica, Universidade de A Coruña, 15071, Coruña, CP, Spain

    Juan Romero

  10. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

  11. Consiglio Nazionale delle Ricerche (CNR), Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), Via P. Castellino 111, 80131, Naples, Italy

    Ernesto Tarantino

  12. Dipartimento di Tecnologie dell’Informazione, Università degli Studi di Milano, Via Bramante 65, 26013, Crema (CR), Italy

    Andrea G. B. Tettamanzi

  13. School of Computing, Edinburgh Napier University, 10 Clinton Road, EH10 5DT, Edinburgh, UK

    Neil Urquhart

  14. Computer Engineering Department, Istanbul Technical University, Room Nr. 3302, Maslak, 34469, Istanbul, Turkey

    A. Şima Uyar

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© 2011 Springer-Verlag Berlin Heidelberg

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Azzini, A., Dragoni, M., Tettamanzi, A.G.B. (2011). Using Evolutionary Neural Networks to Test the Influence of the Choice of Numeraire on Financial Time Series Modeling. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2011. Lecture Notes in Computer Science, vol 6625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20520-0_9

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  • DOI: https://doi.org/10.1007/978-3-642-20520-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20519-4

  • Online ISBN: 978-3-642-20520-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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