Il giorno venerdì 24 aprile alle ore 14.00 presso la aula seminari del Dipartimento di Statistica e Metodi Quantitativi della Università di Milano-Bicocca (edificio U7, IV piano), la dott.ssa Valeria Bignozzi della Università di Firenze terrà un seminario su:
Reducing model risk using positive and negative dependence assumptions
Abstract
We give analytical bounds on the Value-at-Risk and on convex risk measures for a portfolio of random variables with fixed marginal distributions under an additional positive dependence structure. We show that assuming positive dependence information in our model leads to reduced dependence uncertainty spreads compared to the case where only marginals information is known. In more detail, we show that in our model the assumption of a positive dependence structure improves the best-possible lower estimate of a risk measure, while leaving unchanged its worst-possible upper risk bounds. In a similar way, we derive for convex risk measures that the assumption of a negative dependence structure leads to improved upper bounds for the risk while it does not help to increase the lower risk bounds in an essential way. As a result we find that additional assumptions on the dependence structure may result in essentially improved risk bounds (joint work with G. Puccetti and L. Ruschendorf).
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Prof. Fabio Bellini Department of Statistics and Quantitative Methods University of Milano-Bicocca Via Bicocca degli Arcimboldi 8, 20126 Milano 0039-2-64483119 http://www.economia.unimib.it/bellini http://scholar.google.it/citations?user=P61L8P4AAAAJ&hl=it