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Modern Heuristics for Finance Problems: A Survey of Selected Methods and Applications

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Handbook of Computational and Numerical Methods in Finance

Abstract

The high computational complexity of many problems in financial decision-making has prevented the development of time-efficient deterministic solution algorithms so far. At least for some of these problems, e.g., constrained portfolio selection or non-linear time series prediction problems, the results from complexity theory indicate that there is no way to avoid this problem. Due to the practical importance of these problems, we require algorithms for finding optimal or near-optimal solutions within reasonable computing time. Hence, heuristic approaches are an interesting alternative to classical approximation algorithms for such problems. Over the last years many interesting ideas for heuristic approaches were developed and tested for financial decision-making. We present an overview of the relevant methodology, and, some applications that show interesting results for selected problems in finance.

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Authors and Affiliations

  1. GILLARDON AG Financial Software Research Dept., Alte Wilhelmstr. 4, D-75015, Bretten, Germany

    Frank Schlottmann

  2. Institut AIFB Universität Karlsruhe (TH), Postfach 6980, D-76128, Karlsruhe, Germany

    Detlef Seese

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  1. Frank Schlottmann
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  1. Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, 93106, USA

    Svetlozar T. Rachev

  2. Department of Economics and Business Engineering, Universität Karlsruhe, D-76128, Karlsruhe, Germany

    Svetlozar T. Rachev

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Schlottmann, F., Seese, D. (2004). Modern Heuristics for Finance Problems: A Survey of Selected Methods and Applications. In: Rachev, S.T. (eds) Handbook of Computational and Numerical Methods in Finance. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-0-8176-8180-7_9

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  • DOI: https://doi.org/10.1007/978-0-8176-8180-7_9

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