Abstract
Over the last 20 years risk management has become one of the more challenging tasks in the financial and insurance industries. With the current uncertainty in the financial institutions and markets, risk management is a major and pressing topic of interest. Risks in insurance and finance are often described by stochastic models such as stochastic differential equations, which describing the evolution of prices of risky assets (i.e., stock shares, interest rates, foreign exchange rates, etc.) or by difference equations for time series. In order for these models to be useful, optimal statistical methods have to be utilized to fit the models to data. This workshop drew together researchers from a myriad of areas related to risk management including statistics, econometrics, applied probability theory, and econometrics. The main objective was to account for the state of the art of statistical and probabilistic modeling in risk management and, in particular, to collect problems which need an urgent theoretical solution.