We consider a vector-valued multivariate risk measure that depends on the user's profile given by the user's utility. It is constructed on the basis of weighted-mean trimmed regions and represents the solution of an optimization problem. The key feature of this measure is convexity. We apply the...

This paper applies the Alkire and Foster (2011) index of multidimensional poverty to German data. This is done with respect to the politically most important dimensions of poverty mentioned in the German federal government's report on poverty and wealth. Additionally, a modification of the...

This paper applies the Alkire and Foster (2011) index of multidimensional poverty to German data. This is done with respect to the politically most important dimensions of poverty mentioned in the German federal government's report on poverty and wealth. Additionally, a modification of the...

We consider a vector-valued multivariate risk measure that depends on the user's profile given by the user's utility. It is constructed on the basis of weighted-mean trimmed regions and represents the solution of an optimization problem. The key feature of this measure is convexity. We apply the...

We consider a vector-valued multivariate risk measure that depends on the user's profile given by the user's utility. It is constructed on the basis of weighted-mean trimmed regions and represents the solution of an optimization problem. The key feature of this measure is convexity. We apply the...

This article provides a new test for sphericity of the covariance matrix of a d-dimensional multinormal population X ∼ Nd(µ,Σ). This test is applicable if the sample size, n + 1, and d both go to infinity while d/n → y ∈ (0,∞), provided that the limits of tr(Σk)/d, k = 1,...,8, are...

A new procedure, called DD-procedure, is developed to solve the problem of classifying d-dimensional objects into q Ï 2 classes. The procedure is completely nonparametric; it uses q-dimensional depth plots and a very efficient algorithm for discrimination analysis in the depth space [0, 1]q ....

The specification of prior parameters is a common practical problem when implementing Bayesian approaches to portfolio optimization. The precision parameter of the prior on the expected asset returns reflects the confidence of the investor in the prior knowledge. Within the framework of the...

Linear optimization problems are investigated whose parameters are uncertain. We apply coherent distortion risk measures to capture the violation of restrictions. Such a model turns out to be appropriate for many applications and, principally, for the mean-risk portfolio selection problem. Each...

We introduce a measure of diversification for portfolios comprising d risky assets. This measure relates the smallest possible return variance among these d assets to the overall portfolio return variance, yielding the portion of non-diversifiable risk. In the context of normally distributed...