Neben der Einleitung ist die Dissertation in zwei Teile aufgeteilt. In Teil I wird die Annahme eines Investors mit μ-σ Präferenz getroffen. Das erste Kapitel stellt ein Multi-Rating ATSM unter Arbitragefreiheit mit dem klaren Fokus auf Zinsstrukturkurvenmodelle für Unternehmensanleihen vor....

Graphical modeling as a form of multivariate analysis has turned out to be a capable tool for the detection and modeling of complex dependency structures. Statistical models are related to graphs, in which variables are represented by points and associations between each two of them as lines....

The aim of detecting outliers in a multivariate sample can be pursued in different ways. We investigate here the performance of several simultaneous multivariate outlier identification rules based on robust estimators of location and scale. It has been shown that the use of estimators with high...

ARMA-GARCH-Modellierung; nicht-Normalität; normal-inverse Gauss-Verteilung (NIG-Verteilung); realisierte Momente; Staatsanleihen; Strom Forwards; stylized facts von Finanzzeitreihen; Value at Risk; Verteilung von Anleiherenditen

In their paper, Davies and Gather (1993) formalized the task of outlier identification, considering also certain performance criteria for outlier identifiers. One of those Criteria, the maximum asymptotic bias, is carried over here to multivariate outlier identifiers. We show how this term...

Sliced Inverse Regression (SIR) is a promising technique for the purpose of dimension reduction. Several properties of this relatively new method have been examined already, but little attention has been paid to robustness aspects. We show that SIR is very sensitive towards outliers in the data....

In this paper, we consider one-step outlier identification rules for multivariate data-generalizing the concept of so-called a - outlier identifiers_ as presented in Davies and Gather (1993) for the case of univariate samples. We investigate how the finite sample breakdown points of estimators...

In investigations on the behaviour of robust estimators, typically their consistency and their asymptotic normality are studied as a necessity. Their rates of convergence, however, are often given less weight. We show here that the rate of convergence of a multivariate robust estimator to its...