WIAS Preprint No. 1063, (2005)

Nonparametric risk management with generalized hyperbolic distributions



Authors

  • Chen, Ying
  • Härdle, Wolfgang
  • Jeong, Seok-Oh

2010 Mathematics Subject Classification

  • 62H12 62G05 62G07 62G08

Keywords

  • adaptive volatility estimation, generalized hyperbolic distribution, value at risk, risk management

Abstract

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.

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