We propose a model that can capture the typical features of multivariate extreme events observed in financial time series, namely, clustering behaviors in magnitudes and arrival times of multivariate extreme events, and time-varying dependence. The model is developed within the framework of the...

Lévy copulas are the most general concept to capture jump dependence in multivariate Lévy processes. They translate the intuition and many features of the copula concept into a time series setting. A challenge faced by both, distributional and Lévy copulas, is to find flexible but still...

Nonparametric copula models are based on observations whose distributions are generally unknown. Estimation of these copula models is based on pseudo-observations consisting of the ranked data. To determine distributional properties (e.g., the variance) of the models and their estimators,...

Student’s t-distributions are widely used in financial studies as heavy-tailed alternatives to normal distributions. As these distributions are not closed under convolution, there exist no Lévy processes with Student’s t-marginals at all points in time. In this article we show that a...

The investment decision on the placement of wind turbines is, neglecting legal formalities, mainly driven by the aim to maximize the expected annual energy production of single turbines. The result is a concentration of wind farms at locations with high average wind speed. While this strategy...

Measures of association are suggested between two random vectors. The measures are copula-based and therefore invariant with respect to the univariate marginal distributions. The measures are able to capture positive as well as negative association. In case the random vectors are just random...

Chapter 1: A Two-Stage Stochastic Optimisation Model for Urban Same-Day Delivery with Micro-hubs -- Chapter 2: Computational Linear Bilevel Optimization -- Chapter 3: Faster Algorithms for Steiner Tree and Related Problems: From Theory to Practice -- Chapter 4: Prescriptive Analytics for...