The work at hand tries to identify factors that explain accidents on German Autobahn connectors. To find these factors the empirical study makes use of count data models. The findings are based on a set of 197 ramps, which we classified into three distinct types of ramps. For these ramps...

In credit default prediction models, the need to deal with time-varying covariates often arises. For instance, in the context of corporate default prediction a typical approach is to estimate a hazard model by regressing the hazard rate on time-varying covariates like balance sheet or stock...

While modern portfolio theory grounds on the trade-off between portfolio return and portfolio variance to determine the optimal investment decision, postmodern portfolio theory uses downside risk measures instead of the variance. Prominent examples are given by the risk measures Value-at-Risk...

In small samples and especially in the case of small true default probabilities, standard approaches to credit default probability estimation have certain drawbacks. Most importantly, standard estimators tend to underestimate the true default probability which is of course an undesirable...

We elaborate economic explanations for the time-varying risk of month, quarter and year base load electricity forward contracts traded on the Nord Pool Energy Exchange from January 2006 to March 2010. Daily risk quantities are generated by decomposing realized volatility in its continuous and...

In the present work I derive the risk functions of 5 standard estimators for expected asset returns which are frequently advocated in the literature, viz the sample mean vector, the James-Stein and Bayes-Stein estimator, the minimum-variance estimator, and the CAPM estimator. I resolve the...

Credit ratings are ordinal predictions for the default risk of an obligor. To evaluate the accuracy of such predictions commonly used measures are the Accuracy Ratio or, equivalently, the Area under the ROC curve. The disadvantage of these measures is that they treat default as a binary variable...

Trimmed regions are a powerful tool of multivariate data analysis. They describe a probability distribution in Euclidean d-space regarding location, dispersion, and shape, and they order multivariate data with respect to their centrality. Dyckerhoff and Mosler (201x) have introduced the class of...

This paper investigates a selection of methods disentangling contributions from price jumps to realized variance. Flat prices (consecutively sampled prices in calendar time with the same value) and no trading (no price observation at sampling points), both frequently occurring stylized facts in...

It is well known that the correlation between financial series varies over time. Here, the forecasting performance of different time-varying correlation models is compared for cross-country correlations of weekly G5 and daily European stock market indices. In contrast to previous studies only...