The author's particular interest in the area of risk measures is to
combine this theory with the analysis of dependence properties. The
present volume gives an introduction of basic concepts and methods in
mathematical risk analysis, in particular of those parts of risk theory
that are of special relevance to finance and insurance. Describing the
influence of dependence in multivariate stochastic models on risk
vectors is the main focus of the text that presents main ideas and
methods as well as their relevance to practical applications. The first
part introduces basic probabilistic tools and methods of distributional
analysis, and describes their use to the modeling of dependence and to
the derivation of risk bounds in these models. In the second, part risk
measures with a particular focus on those in the financial and insurance
context are presented. The final parts are then devoted to applications
relevant to optimal risk allocation, optimal portfolio problems as well
as to the optimization of insurance contracts. Good knowledge of basic
probability and statistics as well as of basic general mathematics is a
prerequisite for comfortably reading and working with the present
volume, which is intended for graduate students, practitioners and
researchers and can serve as a reference resource for the main concepts
and techniques.