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Evolutionary Strategies for Building Risk-Optimal Portfolios

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

Summary

This chapter describes an evolutionary approach to portfolio optimization. It rejects some assumptions from classic models, introduces alternative risk measures and proposes three evolutionary algorithms to solve the optimization problem. In order to validate the approach proposed, results of a number of experiments using data from the Paris Stock Exchange are presented.

Keywords

Evolutionary Algorithm Risk Measure Return Rate Portfolio Optimization Downside Risk 
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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References

  1. [1]
    Aftalion F, Poncet P (2003) Les Techniques de Mesure de Performance. EconomicaGoogle Scholar
  2. [2]
    Back T (1995) Evolutionary Algorithms in Theory and Practice. Oxford University Press, New YorkGoogle Scholar
  3. [3]
    Harlow H V (1991) Asset allocation in a downside-risk framework. In: Financial Analysts Journal:30-40.Google Scholar
  4. [4]
    Huang C F, Litzenberger R (1988) Foundations for Financial Economics. North-HollandGoogle Scholar
  5. [5]
    Korczak J, Lipinski P (2004) Evolutionary Building of Stock Trading Experts in a Real-Time System. In: Proceedings of the 2004 Congress on Evolutionary Computation :940-947Google Scholar
  6. [6]
    Korczak J, Lipinski P, Roger P (2002) Evolution Strategy in Portfolio Optimization. In: Collet P (eds) Artificial Evolution. Lecture Notes in Computer Science 2310:156-167Google Scholar
  7. [7]
    Korczak J, Roger P (2002) Stock Timing using Genetic Algorithms. In: Applied Stochastic Models in Business and Industry :121-134Google Scholar
  8. [8]
    Lipinski P, Korczak J (2004) Performance Measures in an Evolutionary Stock Trading Expert System. In: Bubak M, van Albada G, Sloot P, Dongarra J (eds) Proceedings of the International Conference on Computational Science. Lecture Notes in Computer Science 3039:835-842Google Scholar
  9. [9]
    Lipinski P, Winczura K, Wojcik J (2007) Building Risk-Optimal Portfolio Using Evolutionary Strategies. In: Giacobini M (eds) Proceedings of EvoWorkshops 2007. Lecture Notes in Computer Science 4448:208-217Google Scholar
  10. [10]
    Loraschi A, Tettamanzi A (1996) An Evolutionary Algorithm for Portfolio Selection Within a Downside Risk Framework. In: Forecasting Financial Markets. Wiley :275285.Google Scholar
  11. [11]
    Markowitz H (1952) Portfolio Selection. In: Journal of Finance 7:77-91Google Scholar
  12. [12]
    Schwefel H-P (1995) Evolution and Optimum Seeking. John Wiley and SonsGoogle Scholar
  13. [13]
    Schwefel H-P, Rudolph G (1995) Contemporary Evolution Strategies. In: Advances in Artificial Life. Springer :893-907.Google Scholar
  14. [14]
    Tsang E P K, Yung P, Li J (2004) EDDIE-automation, a decision support tool for financial forecasting. In: Journal of Decision Support Systems 37:559-565Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Piotr Lipinski
    • 1
  1. 1.Institute of Computer ScienceUniversity of WroclawPoland

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