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Gestion des actifs financiers : de l’approche Classique à la modélisation non paramétrique en estimation du DownSide Risk pour la constitution d’un portefeuille efficient

Abstract : The DownSide Risk (DSR) model for portfolio optimization allows to overcome the drawbacks of the classical Mean-Variance model concerning the asymmetry of returns and the risk perception of investors. This optimization model deals with a positive definite matrix that is endogenous with respect to the portfolio weights and hence leads to a non standard optimization problem. To bypass this hurdle, we developed a new recursive minimization procedure that ensures the convergence to the solution and gives a smooth portfolio efficient frontier. Our method consists in replacing all the returns by their nonparametric estimators counterpart using kernel mean or median regressions. This technique provides an effect similar to the case where an infinite number of observations is available. We also develop a new portfolio optimization model where the risks are measured through conditional variance or semivariance. This strategy allows us to take advantage from returns prediction which are obtained by nonparametric univariate methods. The prediction step uses kernel estimation of the conditional mean. Data from different markets are used to test and validate the proposed approaches, and results indicate better overall performance
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Hanene Ben Salah. Gestion des actifs financiers : de l’approche Classique à la modélisation non paramétrique en estimation du DownSide Risk pour la constitution d’un portefeuille efficient. Gestion et management. Université Claude Bernard - Lyon I, 2015. Français. ⟨NNT : 2015LYO10249⟩. ⟨tel-01242267⟩

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