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Portfolio selection using λ mean and hybrid entropy

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  • Jiuping Xu
  • Xiaoyang Zhou
  • Desheng Wu

Abstract

This paper develops a λ mean-hybrid entropy model to deal with portfolio selection problem with both random uncertainty and fuzzy uncertainty. Solving this model provides the investor a tradeoff frontier between security return and risk. We model the security return as a triangular fuzzy random variable, where the investor’s individual preference is reflected by the pessimistic-optimistic parameter λ. We measure the security risk using the hybrid entropy in this model. Algorithm is developed to solve this bi-objective portfolio selection model. Beside, a numerical example is also presented to illustrate this approach. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • Jiuping Xu & Xiaoyang Zhou & Desheng Wu, 2011. "Portfolio selection using λ mean and hybrid entropy," Annals of Operations Research, Springer, vol. 185(1), pages 213-229, May.
    • Handle: RePEc:spr:annopr:v:185:y:2011:i:1:p:213-229:10.1007/s10479-009-0550-3
    DOI: 10.1007/s10479-009-0550-3
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    References listed on IDEAS

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    1. Soyer, Refik & Tanyeri, Kadir, 2006. "Bayesian portfolio selection with multi-variate random variance models," European Journal of Operational Research, Elsevier, vol. 171(3), pages 977-990, June.
    2. Abdelaziz, Fouad Ben & Aouni, Belaid & Fayedh, Rimeh El, 2007. "Multi-objective stochastic programming for portfolio selection," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1811-1823, March.
    3. Smimou, K. & Bector, C.R. & Jacoby, G., 2007. "A subjective assessment of approximate probabilities with a portfolio application," Research in International Business and Finance, Elsevier, vol. 21(2), pages 134-160, June.
    4. Simonelli, Maria Rosaria, 2005. "Indeterminacy in portfolio selection," European Journal of Operational Research, Elsevier, vol. 163(1), pages 170-176, May.
    5. Wu, Desheng Dash, 2009. "Performance evaluation: An integrated method using data envelopment analysis and fuzzy preference relations," European Journal of Operational Research, Elsevier, vol. 194(1), pages 227-235, April.
    6. Srichander Ramaswamy, 1998. "Portfolio selection using fuzzy decision theory," BIS Working Papers 59, Bank for International Settlements.
    7. Arenas Parra, M. & Bilbao Terol, A. & Rodriguez Uria, M. V., 2001. "A fuzzy goal programming approach to portfolio selection," European Journal of Operational Research, Elsevier, vol. 133(2), pages 287-297, January.
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    Cited by:

    1. Ponta, Linda & Carbone, Anna, 2018. "Information measure for financial time series: Quantifying short-term market heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 132-144.
    2. Tsaur, Ruey-Chyn, 2013. "Fuzzy portfolio model with different investor risk attitudes," European Journal of Operational Research, Elsevier, vol. 227(2), pages 385-390.
    3. Galina Deeva, 2017. "Comparing Entropy and Beta as Measures of Risk in Asset Pricing," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(6), pages 1889-1894.
    4. Vishwas Kukreti & Hirdesh K. Pharasi & Priya Gupta & Sunil Kumar, 2020. "A perspective on correlation-based financial networks and entropy measures," Papers 2004.09448, arXiv.org.

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