We deal with the problem of the practical use of Haezendonck risk measures (see Haezendonck and Goovaerts [8], Goovaerts et al. [7], Bellini and Rosazza Gianin [4]) in portfolio optimization.We first analyze the properties of the natural estimators ofHaezendonck riskmeasures by means of numerical simulations and point out a connection with the theory of M-functionals (see Hampel [9], Huber [11], Serfling [19]) that enables us to derive analytic results on the asymptotic distribution of Orlicz premia. We then prove that as in the CVaR case (see Rockafellar and Uryasev [17, 18], Bertsimas et al. [6]) the mean/Haezendonck optimal portfolios can be obtained through the solution of a single minimization, and that the resulting efficient frontiers are convex. We conclude with a real data example in which we compare optimal portfolios generated by a mean/Haezendonck criterion with mean/variance and mean/CVaR optimal portfolios.
Bellini, F., & Rosazza Gianin, E. (2008). Optimal portfolios with Haezendonck risk measures. STATISTICS & DECISIONS, 26(2), 89-108.
Citazione: | Bellini, F., & Rosazza Gianin, E. (2008). Optimal portfolios with Haezendonck risk measures. STATISTICS & DECISIONS, 26(2), 89-108. |
Tipo: | Articolo in rivista - Articolo scientifico |
Carattere della pubblicazione: | Scientifica |
Titolo: | Optimal portfolios with Haezendonck risk measures |
Autori: | Bellini, F; Rosazza Gianin, E |
Autori: | |
Data di pubblicazione: | 2008 |
Lingua: | English |
Rivista: | STATISTICS & DECISIONS |
Sostituisce: | http://hdl.handle.net/10281/3164 |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1524/stnd.2008.0915 |
Appare nelle tipologie: | 01 - Articolo su rivista |