NDLI: A new method for estimating value-at-risk of Brady bond portfolios

Content Provider	IEEE Xplore Digital Library
Author	D'Vari, R. Sosa, J.C.
Copyright Year	1999
Abstract	Value-at-risk (VAR) statistics are often calculated by a variance-covariance matrix methodology. However, such an approach ignores the well known fact that high frequency financial data tend to substantially deviate from the Gaussian distribution. This feature is particularly pronounced in country spread data (over treasuries) for emerging markets. This study addresses the problem of estimating VAR statistics for Brady bond portfolios by using a modified GARCH(1,1) model with a superimposed 'jump' innovation which affects not only instantaneous spreads but subsequent volatilities. This approach incorporates the stochastic volatility feature of ARCH models, while allowing for occasional large shocks to country spreads that persist over time. This methodology is evaluated by estimating one-day, one-week and one-month VAR measures on a daily basis for several risk tolerance levels for spread driven returns of sample portfolios. The introduction of a persistent 'jump' component improves upon the risk 'confidence intervals' estimated by both standard GARCH(1,1) and rolling variance-covariance methods. However, this result is not homogeneous across countries. Our methodology deals with multiple country portfolios without the computationally problematic large number of parameters of standard multivariate ARCH models. Instead of parametrically estimating cross-country correlations, we extract them from each country's individual 'non-jump' standardized innovations on a rolling basis. Our results also show that by allowing the jump frequencies to depend on variables such as contagion effects, the accuracy of VAR estimates may be improved. All model parameters are re-estimated daily using prior historical data. Therefore our testing is performed out-of-sample.
Starting Page	1
Ending Page	5
File Size	294918
Page Count	5
File Format	PDF
ISBN	0780356632
DOI	10.1109/CIFER.1999.771102
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-04-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bonding Portfolios Reactive power Statistical distributions Technological innovation Frequency estimation Gaussian distribution Stochastic processes Electric shock Data mining
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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