Please use this identifier to cite or link to this item:
Title: GHICA - Risk analysis with GH distributions and independent components
Authors: Chen, Y. 
Härdle, W.
Spokoiny, V.
Keywords: Expected shortfall
Generalized hyperbolic distribution
Independent component analysis
Local exponential estimation
Multivariate risk management
Value at risk
Issue Date: Mar-2010
Source: Chen, Y., Härdle, W., Spokoiny, V. (2010-03). GHICA - Risk analysis with GH distributions and independent components. Journal of Empirical Finance 17 (2) : 255-269. ScholarBank@NUS Repository.
Abstract: Over recent years, a study on risk management has been prompted by the Basel committee for regular banking supervisory. There are however limitations of some widely-used risk management methods that either calculate risk measures under the Gaussian distributional assumption or involve numerical difficulty. The primary aim of this paper is to present a realistic and fast method, GHICA, which overcomes the limitations in multivariate risk analysis. The idea is to first retrieve independent components (ICs) out of the observed high-dimensional time series and then individually and adaptively fit the resulting ICs in the generalized hyperbolic (GH) distributional framework. For the volatility estimation of each IC, the local exponential smoothing technique is used to achieve the best possible accuracy of estimation. Finally, the fast Fourier transformation technique is used to approximate the density of the portfolio returns. The proposed GHICA method is applicable to covariance estimation as well. It is compared with the dynamic conditional correlation (DCC) method based on the simulated data with d = 50 GH distributed components. We further implement the GHICA method to calculate risk measures given 20-dimensional German DAX portfolios and a dynamic exchange rate portfolio. Several alternative methods are considered as well to compare the accuracy of calculation with the GHICA one. © 2009 Elsevier B.V. All rights reserved.
Source Title: Journal of Empirical Finance
ISSN: 09275398
DOI: 10.1016/j.jempfin.2009.09.005
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 13, 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.