Please use this identifier to cite or link to this item:
Title: Nonparametric risk management with generalized hyperbolic distributions
Authors: Chen, Y. 
Härdle, W.
Jeong, S.-O.
Keywords: Adaptive volatility estimation
Generalized hyperbolic distribution
Risk management
Value at risk
Issue Date: Sep-2008
Source: Chen, Y., Härdle, W., Jeong, S.-O. (2008-09). Nonparametric risk management with generalized hyperbolic distributions. Journal of the American Statistical Association 103 (483) : 910-923. ScholarBank@NUS Repository.
Abstract: In this article we propose the generalized hyperbolic adaptive volatility (GHADA) risk management model based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared with the normal distribution, the GH distribution has semiheavy 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 the German mark/U.S. dollar 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. © 2008 American Statistical Association.
Source Title: Journal of the American Statistical Association
ISSN: 01621459
DOI: 10.1198/016214507000001003
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Mar 8, 2018


checked on Feb 7, 2018

Page view(s)

checked on Mar 12, 2018

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.