In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution possesses semi-heavy tails and represents the financial risk factors more appropriately. Nonparametric adaptive methodology has the desirable property of being able to estimate homogeneous volatility over a short time interval and reflects a sudden change in the volatility process. For DEM/USD exchange rate and German bank portfolio data, the proposed GHADA model provides more accurate Value at Risk calculations than the models with assumptions of the normal and t distributions. All calculations and simulations are done with XploRe.

Preprint: Weierstraß-Institut für Angewandte Analysis und Stochastik, vol. 1063