Die Berechnung des VaR führt zur Reduktion der Dimension des Raumes der Risikofaktoren. Die vorzunehmenden Vereinfachungen resultieren aus unterschiedlichen Beweggründen, z.B. technische Effizienz, Sachlogik der Ergebnisse und statistische Adäquanz des Modells. Im Kapitel 2 stellen wir drei...

Die vorliegende Studie untersucht den Realoptionsansatz als Bewertungsverfahren für unentwickelte Immobilien. Im Gegensatz zu klassischen Bewertungsverfahren berücksichtigt das Realoptionsverfahren explizit die Unsicherheit zukünftiger Mieterträge und die daraus folgenden...

Travel arrangements and flight ticket booking via internet is widely used nowadays and follow already certain standards. Although increasing activity for multimedia/web education components can be observed, we are far away from standards in this important area. Statistics can possibly profit the...

The use of electronic spreadsheets as the primary software tool for teaching management science modeling techniques and quantitative methods in economics and finance undoubtedly played a key role in the increasing impact of quantitative lectures given in graduate programs. Researchers suggest...

Modern econometrics requires implementation of highly specialized software. In contrast to mathematical arguments used in implementing new econometric techniques the corresponding software algorithms require specific platforms. The specialization of hardware and software, in fact, seriously...

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given dataset, a statistical test is required. In this paper, we develop such a test based on the linear state space representation. We provide a...

It is common practice to identify the number and sources of shocks that move implied volatilities across space and time by applying Principal Components Analysis (PCA) to pooled covariance matrices of changes in implied volatilities. This approach, however, is likely to result in a loss of...

Most dimension reduction methods based on nonparametric smoothing are highly sensitive to outliers and to data coming from heavy tailed distributions. We show that the recently proposed MAVE and OPG methods by Xia et al. (2002) allow us to make them robust in a relatively straightforward way...

Models are studied where the response Y and covariates X, T are assumed to fulfill E(Y

For over a decade, nonparametric modelling has been successfully applied to study nonlinear structures in financial time series. It is well known that the usual nonparametric models often have less than satisfactory performance when dealing with more than one lag. When the mean has an additive...