Capital allocation for dynamic risk measures
Freitag, 3.6.16, 12:00-13:00, Raum 125, Eckerstr. 1
apital allocations have been studied in conjunction with static risk measures in various\npapers. The dynamic case has been studied only in a discrete-time setting. We address the\nproblem of allocating risk capital to subportfolios in a continuous-time dynamic context.\nFor this purpose we introduce a classical differentiability result for backward stochastic\nVolterra integral equations and apply this result to derive continuous-time dynamic capital\nallocations. Moreover, we study a dynamic capital allocation principle that is based on\nbackward stochastic differential equations and derive the dynamic gradient allocation for\nthe dynamic entropic risk measure. As a consequence we finally provide a representation result for\ndynamic risk measures that is based on the full allocation property of the Aumann-Shapley\nallocation, which is also new in the static case.\n
New Concepts for Reliable Assessment of Statistical Methods
Freitag, 10.6.16, 12:00-13:00, Raum 404, Eckerstr. 1
In Bioinformatics and Systems Biology, a huge variety of computational tools and statistical approaches have been developed. However, many computational methods are not well-tested in application settings and their applicability is often seriously delimited. Therefore, selecting an optimal analysis strategy of often difficult in applications and missing guidelines hamper the transfer of theoretical approaches to experimental research.\nIn this talk, new concepts for assessing statistical algorithms will be introduced and illustrated. The suggested methodology enables less biased, more reliable and valid comparisons of competing approaches than currently performed in the literature. The presented concepts can be applied to establish optimized analysis pipelines and for developing general decision guidelines for the selection of appropriate analysis methods. Thereby, the presented methodology constitutes a promising perspective for transferring computational approaches to basic research in academia and to industrial applications like drug development.
A short trip through the tree of life: from Ebola over Diphtheria and Tuberculosis to Penguins
Freitag, 24.6.16, 12:00-13:00, Raum 404, Eckerstr. 1
Genetic sequencing data contain a fingerprint of past evolutionary and population dynamic processes. Phylogenetic methods infer evolutionary relationships — the phylogenetic tree — between individuals based on their genetic sequences. Phylodynamics aims to understand the population dynamic processes — such as epidemiological or macroevolutionary processes — giving rise to the phylogenetic tree. I will present the mathematical and computational aspects of our recently developed phylodynamic tools. Then I will discuss epidemiological applications, focussing on the recent Ebola outbreak in West Africa and a potential emergence of Diphtheria in African refugee camps. Second, I will focus on a macroevolutionary application, shedding light on the radiation of penguins.\n\n