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The Mean-CVaR Model for Portfolio Optimization Using a Multi-Objective Approach and the Kalai-Smorodinsky Solution

Rajae Aboulaich, Rachid Ellaia, Samira El Moumen, Abderahmane Habbal and Noureddine Moussaid
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Rajae Aboulaich: LERMA - Laboratoire d'Etudes et Recherche en Mathématiques Appliquées - EMI - Ecole Mohammadia d'Ingénieurs
Rachid Ellaia: LERMA - Laboratoire d'Etudes et Recherche en Mathématiques Appliquées - EMI - Ecole Mohammadia d'Ingénieurs
Samira El Moumen: LERMA - Laboratoire d'Etudes et Recherche en Mathématiques Appliquées - EMI - Ecole Mohammadia d'Ingénieurs
Abderahmane Habbal: ACUMES - Analysis and Control of Unsteady Models for Engineering Sciences - CRISAM - Inria Sophia Antipolis - Méditerranée - Inria - Institut National de Recherche en Informatique et en Automatique
Noureddine Moussaid: LERMA - Laboratoire d'Etudes et Recherche en Mathématiques Appliquées - EMI - Ecole Mohammadia d'Ingénieurs

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Abstract: The purpose of this work is to present a model for portfolio multi-optimization, in which distributions are compared on the basis of tow statistics: the expected value and the Conditional Value-at-Risk (CVaR), to solve such a problem many authors have developed several algorithms, in this work we propose to find the efficient boundary by using the Normal Boundary Intersection approach (NBI) based on our proposed hybrid method SASP, since the considered problem is multi-objective, then we find the Kalai-smorodinsky solution.

Date: 2017
New Economics Papers: this item is included in nep-rmg
Note: View the original document on HAL open archive server: https://inria.hal.science/hal-01575730v1
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Published in MATEC Web of Conferences, 2017, 105, pp.4. ⟨10.1051/matecconf/201710500010⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01575730

DOI: 10.1051/matecconf/201710500010

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