This paper provides a coherent method for scenario aggregation addressing model uncertainty. It is based on divergence … the definition of five fundamental criteria that serve as a basis for our method. Standard risk measures, such as value-at-risk …

their fluctuations, called the loss and gain quadratic risk premium (QRP) respectively. The loss QRP interprets as the … premium paid for downside risk hedging, while the gain QRP reads as the premium received for upside risk compensation. Long …-short portfolio strategies based on the loss or gain QRP yield monthly risk-adjusted expected excess returns of up to 2.8%. This cross …

their fluctuations, called the loss and gain quadratic risk premium (QRP) respectively. The loss QRP interprets as the … premium paid for downside risk hedging, while the gain QRP reads as the premium received for upside risk compensation. Long …-short portfolio strategies based on the loss or gain QRP yield monthly risk-adjusted expected excess returns of up to 2.8%. This cross …

We introduce a dynamical model for the time evolution of probability density functions incorporating uncertainty in the … parameters. The uncertainty follows stochastic processes, thereby defining a new class of stochastic processes with values in the … space of probability densities. The purpose is to quantify uncertainty that can be used for probabilistic forecasting …

Despite well-known shortcomings as a risk measure, Value-at-Risk (VaR) is still the industry and regulatory standard … for the calculation of risk capital in banking and insurance. This paper is concerned with the numerical estimation of the … interpreted as a measure of model uncertainty induced by possible dependence scenarios …