Regelmäßige Veröffentlichungen makroökonomischer Kennzahlen, die von den Erwartungen der Marktteilnehmer abweichen, wirken sich in rund zwei Drittel der Fälle sofort auf den deutschen Aktienmarkt aus. Vor allem Daten zu Investitionen, Zahlen über die realwirtschaftlichen Aktivitäten oder...

The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution...

Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors, such as GARCH models, are investigated, to determine...

We introduce a dynamic banking-macro model, which abstains from conventional mean-reversion assumptions and in which - similar to Brunnermeier and Sannikov (2010) - adverse asset-price movements and their impact on risk premia and credit spreads can induce instabilities in the banking sector. To...

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and,...