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

In: Handbook of Computational and Numerical Methods in Finance

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  • Frank Schlottmann

    (GILLARDON AG Financial Software Research Dept.)

  • Detlef Seese

    (Institut AIFB Universität Karlsruhe (TH))

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.

Suggested Citation

  • Frank Schlottmann & Detlef Seese, 2004. "Modern Heuristics for Finance Problems: A Survey of Selected Methods and Applications," Springer Books, in: Svetlozar T. Rachev (ed.), Handbook of Computational and Numerical Methods in Finance, chapter 9, pages 331-359, Springer.
    • Handle: RePEc:spr:sprchp:978-0-8176-8180-7_9
    DOI: 10.1007/978-0-8176-8180-7_9
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