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A Data-Driven Optimization Heuristic for Downside Risk Minimization

Author

Listed:
  • M. Gilli

    () (Dept. of Econometrics University of Geneva)

  • E. Kellezi

    (Mirabaud and Cie, Geneva)

  • H. Hysi

    (Dept. of Econometrics University of Geneva)

Abstract

In practical portfolio choice models risk is often defined as VaR, expected shortfall, maximum loss, Omega function, etc. and is computed from simulated future scenarios of the portfolio value. It is well known that the minimization of these functions can not, in general, be performed with standard methods. We present a multi-purpose data-driven optimization heuristic capable to deal efficiently with a variety of risk functions and practical constraints on the positions in the portfolio. The efficiency and robustness of the heuristic is illustrated by solving a collection of real world portfolio optimization problems using different risk functions such as VaR, expected shortfall, maximum loss and Omega function with the same algorithm

Suggested Citation

  • M. Gilli & E. Kellezi & H. Hysi, 2006. "A Data-Driven Optimization Heuristic for Downside Risk Minimization," Computing in Economics and Finance 2006 355, Society for Computational Economics.
  • Handle: RePEc:sce:scecfa:355
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    Citations

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    Cited by:

    1. Jin Zhang & Dietmar Maringer, 2010. "Asset Pair-Copula Selection with Downside Risk Minimization," Working Papers 037, COMISEF.
    2. Konstantinos Anagnostopoulos & Georgios Mamanis, 2011. "Multiobjective evolutionary algorithms for complex portfolio optimization problems," Computational Management Science, Springer, vol. 8(3), pages 259-279, August.
    3. Jin Zhang & Dietmar Maringer, 2016. "Using a Genetic Algorithm to Improve Recurrent Reinforcement Learning for Equity Trading," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 551-567, April.
    4. Travkin, A., 2015. "Estimating Pair-Copula Constructions Using Empirical Tail Dependence Functions: an Application to Russian Stock Market," Journal of the New Economic Association, New Economic Association, vol. 25(1), pages 39-55.
    5. Thiemo Krink & Sandra Paterlini, 2011. "Multiobjective optimization using differential evolution for real-world portfolio optimization," Computational Management Science, Springer, vol. 8(1), pages 157-179, April.
    6. Cyril Caillault, Dominique Guégan, 2009. "Forecasting VaR and Expected Shortfall Using Dynamical Systems: A Risk Management Strategy," Frontiers in Finance and Economics, SKEMA Business School, vol. 6(1), pages 26-50, April.
    7. repec:spr:annopr:v:237:y:2016:i:1:d:10.1007_s10479-015-1822-8 is not listed on IDEAS
    8. Manfred Gilli & Enrico Schumann, 2009. "Robust regression with optimisation heuristics," Working Papers 011, COMISEF.
    9. Harris, Richard D.F. & Mazibas, Murat, 2013. "Dynamic hedge fund portfolio construction: A semi-parametric approach," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 139-149.
    10. Thiemo Krink & Sandra Paterlini, 2008. "Differential Evolution for Multiobjective Portfolio Optimization," Center for Economic Research (RECent) 021, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    11. Iwona Konarzewska, 2008. "On measuring the sensitivity of the optimal portfolio allocation," Operations Research and Decisions, Wroclaw University of Technology, Institute of Organization and Management, vol. 2, pages 55-73.
    12. Manfred Gilli & Enrico Schumann, 2009. "Optimal enough?," Working Papers 010, COMISEF.
    13. Thapar, Rishi & Minsky, Bernard & Obradovic, M & Tang, Qi, 2009. "Applying a global optimisation algorithm to Fund of Hedge Funds portfolio optimisation," MPRA Paper 17099, University Library of Munich, Germany.
    14. Yuichi Takano & Jun-ya Gotoh, 2010. "α-Conservative approximation for probabilistically constrained convex programs," Computational Optimization and Applications, Springer, vol. 46(1), pages 113-133, May.
    15. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
    16. Zhu, Min, 2013. "Return distribution predictability and its implications for portfolio selection," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 209-223.
    17. Ludovic Gaudard & Jeannette Gabbi & Andreas Bauder & Franco Romerio, 2016. "Long-term Uncertainty of Hydropower Revenue Due to Climate Change and Electricity Prices," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1325-1343, March.
    18. repec:eee:ejores:v:266:y:2018:i:1:p:304-315 is not listed on IDEAS
    19. Lwin, Khin T. & Qu, Rong & MacCarthy, Bart L., 2017. "Mean-VaR portfolio optimization: A nonparametric approach," European Journal of Operational Research, Elsevier, vol. 260(2), pages 751-766.
    20. repec:hal:journl:halshs-00375765 is not listed on IDEAS

    More about this item

    Keywords

    Portfolio optimization; Heuristic optimization; Threshold accepting; Downside risk;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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