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Mean-Risk Analysis with Enhanced Behavioral Content

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  • Alessandra Cillo
  • Philippe Delquié

Abstract

We study a Mean-Risk model derived from a behavioral theory of Disappointment with multiple reference points. One distinguishing feature of the risk measure is that it is based on mutual deviations of outcomes, not deviations from a specific target. We prove necessary and sufficient conditions for strict first and second order stochastic dominance, and show that the model is, in addition, a Convex Risk Measure. The model allows for richer, and behaviorally more plausible, risk preference patterns than competing models with equal degrees of freedom, including Expected Utility (EU), Mean-Variance (MV), Mean-Gini (MG), and models based on non-additive probability weighting, such a Dual Theory (DT). For example, in asset allocation, the decision-maker can abstain from diversifying in a risky asset unless it meets a threshold performance, and gradually invest beyond this threshold, which appears more acceptable than the extreme solutions provided by either EU and MV (always diversify) or DT and MG (always plunge). In asset trading, the model allows no-trade intervals, like DT and MG, in some, but not all, situations. An illustrative application to portfolio selection is presented. The model can provide an improved criterion for Mean-Risk analysis by injecting a new level of behavioral realism and flexibility, while maintaining key normative properties. Key words: Risk analysis; Uncertainty modeling; Utility theory; Stochastic dominance; Convex risk measures

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  • Alessandra Cillo & Philippe Delquié, 2013. "Mean-Risk Analysis with Enhanced Behavioral Content," Working Papers 498, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  • Handle: RePEc:igi:igierp:498
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    2. Bi, Junna & Jin, Hanqing & Meng, Qingbin, 2018. "Behavioral mean-variance portfolio selection," European Journal of Operational Research, Elsevier, vol. 271(2), pages 644-663.
    3. Pinelis, Iosif, 2013. "An optimal three-way stable and monotonic spectrum of bounds on quantiles: a spectrum of coherent measures of financial risk and economic inequality," MPRA Paper 51361, University Library of Munich, Germany.
    4. Alessandra Cillo & Marco Bonetti & Giovanni Burro & Clelia Di Serio & Roberta De Filippis & Riccardo Maria Martoni, 2019. "Neurocognitive assessment in obsessive compulsive disorder patients: Adherence to behavioral decision models," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-16, February.
    5. Alfred Müller & Marco Scarsini & Ilia Tsetlin & Robert L. Winkler, 2017. "Between First- and Second-Order Stochastic Dominance," Management Science, INFORMS, vol. 63(9), pages 2933-2947, September.
    6. Wang, Xianhe & Ouyang, Yuliang & Li, You & Liu, Shu & Teng, Long & Wang, Bo, 2023. "Multi-objective portfolio selection considering expected and total utility," Finance Research Letters, Elsevier, vol. 58(PD).
    7. Pavlo Blavatskyy, 2018. "A second-generation disappointment aversion theory of decision making under risk," Theory and Decision, Springer, vol. 84(1), pages 29-60, January.
    8. Iosif Pinelis, 2013. "An optimal three-way stable and monotonic spectrum of bounds on quantiles: a spectrum of coherent measures of financial risk and economic inequality," Papers 1310.6025, arXiv.org.
    9. Fulga, Cristinca, 2016. "Portfolio optimization with disutility-based risk measure," European Journal of Operational Research, Elsevier, vol. 251(2), pages 541-553.

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