Please use this identifier to cite or link to this item: https://doi.org/10.1198/016214507000001003
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
Citation: 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. https://doi.org/10.1198/016214507000001003
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
URI: http://scholarbank.nus.edu.sg/handle/10635/105243
ISSN: 01621459
DOI: 10.1198/016214507000001003
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