Please use this identifier to cite or link to this item: http://hdl.handle.net/11422/9270
Type: Relatório
Title: Robust Statistical modeling portfolios
Author(s)/Inventor(s): Mendes, Beatriz Vaz de Melo
Leal, Ricardo Pereira Câmara
Abstract: Indisponível.
Abstract: The bottom line in many statistical analysis in finance is the basic issue of modeling a set of multivariate data. Financial data are characterized by their fat tails containing some proportion of extreme observations. We propose a simple model able to capture these main characteristics, and to provide a good fit for the bulk of the data as well as for the atypical observations. Basically, we use a robust covariance estimator to define the center and orientations of the data, and the classical sample covariance to estimate how inflated could tins distribution be by the effect of extreme observations. Estimation of the model is done either empirically or by maximum likelihood based on elliptical distributions. Simulation experiments verified the adequacy of the model to real data. We provide illustrations of the usefulness of the proposed procedure, in particular when constructing efficient frontiers. We show that robust portfolios may yield higher cumulative returns and have more stable weights compositions.
Keywords: Finanças
Working paper
Subject CNPq: CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO
Department : Instituto COPPEAD de Administração
Publisher: Universidade Federal do Rio de Janeiro
In: Relatórios COPPEAD
Issue: 355
Issue Date: 2002
Publisher country: Brasil
Language: eng
Right access: Acesso Aberto
ISBN: 8575080369
ISSN: 1518-3335
Citation: MENDES, Beatriz Vaz de Melo; LEAL, Ricardo Pereira Câmara. Robust Statistical modeling portfolios. Rio de Janeiro: UFRJ, 2002. 30 p. (Relatórios COPPEAD, 355).
Appears in Collections:Relatórios Técnicos e de Pesquisa

Files in This Item:
File Description SizeFormat 
RC_355-Comp..pdf682,4 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.