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A New Framework for Assets Selection Based on Dimensions Reduction Techniques

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Book cover Knowlege-Based and Intelligent Information and Engineering Systems (KES 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6882))

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Abstract

We introduce a model called Asset Drivers Framework (ADF), which combines Dimensions Reduction Techniques (DRT) with a ranking procedure to find out assets to be inserted into a financial portfolio. The basic idea is that market securities can be described by a wider number of determinants, but only a few number of them can effectively characterize the assets to form well–balanced portfolios. The ADF manages this as a dimensions reduction problem, and extrapolates for each asset a reduced number of determinants as natural drivers of theirs. The procedure ends by assigning a score to the assets projected in such dimensionally reduced space, with a method of punishment/reward of the way the securities cluster into it. The beauty of the ADF scheme relies on a number of points: (i) it provides a platform to test various dimensions reduction techniques; (ii) looking at the performance, ADF makes possible to build portfolios whose returns are aligned to those of the traditional approach, but with lower variance, and hence lower risk.

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Author information

Authors and Affiliations

  1. DIEM, sezione di Matematica Finanziaria, Via Vivaldi 2, 16126, Genova, Italy

    Marina Resta

Authors
  1. Marina Resta
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Editor information

Editors and Affiliations

  1. Institute of Integrated Sensor Systems, University of Kaiserslautern, Erwin-Schroedinger-str. 12, 67663, Kaiserslautern, Germany

    Andreas König

  2. Knowledge-Based Systems Group, Department of Computer Science, University of Kaiserslautern, P.O. Box 3049, 67653, Kaiserslautern, Germany

    Andreas Dengel

  3. School of Business, University of Applied Sciences Northwestern Switzerland, Riggenbachstr. 16, 4600, Olten, Switzerland

    Knut Hinkelmann

  4. Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, 599-8531, Sakai,, Osaka, Japan

    Koichi Kise

  5. KES International, P.O. Box 2115, BN43 9AF, Shoreham-by-sea, UK

    Robert J. Howlett

  6. University of South Australia, Adelaide, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2011 Springer-Verlag Berlin Heidelberg

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Resta, M. (2011). A New Framework for Assets Selection Based on Dimensions Reduction Techniques. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowlege-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23863-5_38

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  • DOI: https://doi.org/10.1007/978-3-642-23863-5_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23862-8

  • Online ISBN: 978-3-642-23863-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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