Optimal R&D investment is defined by deep uncertainty that can only partially be addressed through historical data. Thus, expert judgments expressed as subjective probability distributions are seen as an alternative way of assessing the potential of new technologies. In this paper we propose a...

This paper rationalizes the LASSO algorithm based on uncertain fat-tail priors and max-min robust optimization. Our rationalization excludes heuristic learning or restrictive prior assumptions in the original interpretation of LASSO (Tibshirani (1996)). In our setting, economic agents...

Model risk as part of the operational risk is a serious problem for financial institutions. As the pricing of derivatives as well as the computation of the market or credit risk of an institution depend on statistical models the application of a wrong model can lead to a serious over- or...