The Value at Risk of a portfolio differs from the sum of the Values at Risk of the portfolio's components. In this paper, we analyze the problem of how a single economic risk figure for the Value at Risk of a hypothetical portfolio composed of different commercial banks might be obtained for a...

Life insurance companies are affected directly by the impact of the low-interestrate environment. To fulfil promised guarantees they may be forced to tap into their own funds, say if the current income generated is no longer sufficient to cover the policyholders' profit participation share as...

Die Lebensversicherer sind von den Auswirkungen des Niedrigzinsumfelds unmittelbar betroffen. Damit sie die zugesicherten Garantien erfüllen können, müssen sie unter Umständen Eigenmittel aufwenden. Dies ist dann der Fall, wenn die von den Unternehmen festgelegte Überschussbeteiligung oder...

We use a compound option-based structural credit risk model to infer a term structure of banking crisis risk from market data on bank stocks in daily frequency. Considering debt service payments with different maturities this term structure assigns a separate estimator for short- and long-term...

Group-specific estimations can significantly improve the predictive power of accountingbased rating models. This is shown using a binary logistic regression model applied to the Deutsche Bundesbank's USTAN dataset, which contains 300,000 financial statements provided by German companies for the...

In this paper we 'update' the option implied probability of default (option iPoD) approach recently suggested in the literature. First, a numerically more stable objective function for the estimation of the risk neutral density is derived whose integrals can be solved analytically. Second, it is...

The evaluation of multi-step-ahead density forecasts is complicated by the serial correlation of the corresponding probability integral transforms. In the literature, three testing approaches can be found which take this problem into account. However, these approaches can be computationally...

Measuring and displaying uncertainty around path-forecasts, i.e. forecasts made in period T about the expected trajectory of a random variable in periods T+1 to T+H is a key ingredient for decision making under uncertainty. The probabilistic assessment about the set of possible trajectories that...

Density forecasts have become quite important in economics and finance. For example, such forecasts play a central role in modern financial risk management techniques like Value at Risk. This paper suggests a regression based density forecast evaluation framework as a simple alternative to other...

In this paper we will be estimating risk-neutral densities (RND) for the largest euro area stock market (the index of which is the German DAX), reporting their statistical properties, and evaluating their forecasting performance. We have applied an innovative test procedure to a new, rich, and...