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Evolutionary Stochastic Portfolio Optimization

  • Ronald Hochreiter
Part of the Studies in Computational Intelligence book series (SCI, volume 100)

Summary

In this chapter, the concept of evolutionary stochastic portfolio optimization is discussed. Selected theory from the fields of Stochastic Programming, evolutionary computation, portfolio optimization, as well as financial risk management is used to derive a generalized framework for computing optimal financial portfolios given an uncertain future using a probabilistic risk measure approach. A set of structurally different risk measures - Standard Deviation, Mean-absolute Downside Semi Deviation, Value-at-Risk, and Expected Shortfall - which are commonly used for practical portfolio management purposes have been selected to substantiate the approach with numerical results.

Keywords

Risk Measure Portfolio Optimization Efficient Frontier Loss Distribution Cardinality Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ronald Hochreiter
    • 1
  1. 1.Department of Statistics and Decision Support SystemsUniversity of ViennaViennaAustria

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