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Prospect Theory Based Portfolio Optimization Problem with Imprecise Forecasts

Author

Listed:
  • Massimiliano Kaucic

    (University of Trieste, Italy)

  • Roberto Daris

    (University of Trieste, Italy)

Abstract

In this paper we propose a novel interval optimization approach for portfolio selection when imprecise forecasts are available. We consider investors acting their choices according to the prospect theory, where scenarios are provided in the form of approximate numbers. The resulting constrained nonlinear interval optimization problem is converted into two nonlinear programming problems using a total order relation between intervals. Static and dynamic analysis of portfolios involving assets from the Croatian market illustrate the potential of the method with respect to the standard procedure.

Suggested Citation

  • Massimiliano Kaucic & Roberto Daris, 2016. "Prospect Theory Based Portfolio Optimization Problem with Imprecise Forecasts," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 14(4 (Winter), pages 359-384.
    • Handle: RePEc:mgt:youmgt:v:14:y:2016:i:4:p:359-384
    as

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    References listed on IDEAS

    as
    1. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. Rubinstein, R. Y., 1982. "Generating random vectors uniformly distributed inside and on the surface of different regions," European Journal of Operational Research, Elsevier, vol. 10(2), pages 205-209, June.
    3. Topaloglou, Nikolas & Vladimirou, Hercules & Zenios, Stavros A., 2002. "CVaR models with selective hedging for international asset allocation," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1535-1561, July.
    4. Radman Peša, Anita & Brajković, Ana, 2015. "Testing The ‘Black Swan Effect’ on Croatian Stock Market Between 2000 and 2013," MPRA Paper 69223, University Library of Munich, Germany, revised 2015.
    5. Enrico Giorgi & Thorsten Hens & János Mayer, 2007. "Computational aspects of prospect theory with asset pricing applications," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 267-281, May.
    6. Holthausen, Duncan M, 1981. "A Risk-Return Model with Risk and Return Measured as Deviations from a Target Return," American Economic Review, American Economic Association, vol. 71(1), pages 182-188, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    prospect theory; random sets; interval orders; interval optimization; Croatian stock market;
    All these keywords.

    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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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