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The effect of prudence on the optimal allocation in possibilistic and mixed models

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  • Irina Georgescu

Abstract

In this paper two portfolio choice models are studied: a purely possibilistic model, in which the return of a risky asset is a fuzzy number, and a mixed model in which a probabilistic background risk is added. For the two models an approximate formula of the optimal allocation is computed, with respect to the possibilistic moments associated with fuzzy numbers and the indicators of the investor risk preferences (risk aversion, prudence).

Suggested Citation

  • Irina Georgescu, 2018. "The effect of prudence on the optimal allocation in possibilistic and mixed models," Papers 1805.12066, arXiv.org.
  • Handle: RePEc:arx:papers:1805.12066
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    1. Zakamouline, Valeri & Koekebakker, Steen, 2009. "Portfolio performance evaluation with generalized Sharpe ratios: Beyond the mean and variance," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1242-1254, July.
    2. Ñíguez, Trino-Manuel & Paya, Ivan & Peel, David, 2016. "Pure higher-order effects in the portfolio choice model," Finance Research Letters, Elsevier, vol. 19(C), pages 255-260.
    3. Kimball, Miles S, 1990. "Precautionary Saving in the Small and in the Large," Econometrica, Econometric Society, vol. 58(1), pages 53-73, January.
    4. Louis Eeckhoudt & Harris Schlesinger, 2006. "Putting Risk in Its Proper Place," American Economic Review, American Economic Association, vol. 96(1), pages 280-289, March.
    5. L. Eeckhoudt & C. Gollier & H. Schlesinger, 2005. "Economic and financial decisions under risk," Post-Print hal-00325882, HAL.
    6. Christian Gollier, 2004. "The Economics of Risk and Time," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262572249, April.
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    Cited by:

    1. Irina Georgescu & Louis Aimé Fono, 2019. "A Portfolio Choice Problem in the Framework of Expected Utility Operators," Mathematics, MDPI, vol. 7(8), pages 1-16, July.
    2. Georgescu Irina & Kinnunen Jani, 2019. "How the Investor’s Risk Preferences Influence the Optimal Allocation in a Credibilistic Portfolio Problem," Journal of Systems Science and Information, De Gruyter, vol. 7(4), pages 317-329, August.
    3. Farzaneh Pourahmadi & Payman Dehghanian, 2018. "A Game-Theoretic Loss Allocation Approach in Power Distribution Systems with High Penetration of Distributed Generations," Mathematics, MDPI, vol. 6(9), pages 1-14, September.

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