One of the main problems in managing multidimensional data for decision making is that it is impossible to define a complete ordering on multidimensional Euclidean spaces. In order to solve this problem the scientific community has devolped more and more sofisticated tecniques belonging to the wide framework of Multivariate Statistics. Recently some authors [DR04] have proposed an ordering procedure in which the "meaningful direction" is the "worst-best". The aim of this paper is to extend this approach considering that, especially in financial applications, variables are quantified in different scales and, as we are going to show, this can lead to undesired results. As a matter of fact, we show that, without an appropriate rescaling, variables with a large range of variation (rv) are "overweighted" with respect to variables with a small one.
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Paper provided by Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia in its series Quaderni DSEMS with number
lg_maf_2006.
Length: Date of creation: Oct 2006 Date of revision: Publication status: Published in Mathematical and Statistical Methods for Insurance and Finance, Perna, Cira; Sibillo, Marilena (Eds.), ISBN: 978-88-470-0703-1, Springer, 2008.. Handle: RePEc:ufg:qdsems:lg_maf_2006
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