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

DOI

10.20347/WIAS.PREPRINT.1063

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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