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Foreign exchange value-at-risk with multiple currency exposure : a multivariate and copula generalized autoregressive conditional heteroskedasticity approach

Author: David W Maybury; Canada. Defence Research and Development Canada.
Publisher: [Ottawa] : Defence Research and Development Canada, 2014.
Series: Scientific report (Defence Research and Development Canada), 2014-R62
Edition/Format:   eBook : Document : National government publication : EnglishView all editions and formats
Database:WorldCat
Summary:
Large DND projects and acquisitions are exposed to more than one foreign currency at the same time which complicates management?s foreign exchange risk assessments. The Centre for Operational Research and Analysis? (CORA) in-house Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models are extended to a full multivariate setting. The extensions involve two models types: multivariate GARCH and  Read more...
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Details

Material Type: Document, Government publication, National government publication, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: David W Maybury; Canada. Defence Research and Development Canada.
OCLC Number: 945110726
Notes: November 2014.
Description: 1 online resource (viii, 42, [2] pages) : figure, graphs, tables.
Series Title: Scientific report (Defence Research and Development Canada), 2014-R62
Responsibility: David W. Maybury.

Abstract:

Large DND projects and acquisitions are exposed to more than one foreign currency at the same time which complicates management?s foreign exchange risk assessments. The Centre for Operational Research and Analysis? (CORA) in-house Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models are extended to a full multivariate setting. The extensions involve two models types: multivariate GARCH and copula-GARCH. It was found that both models give qualitatively similar value-at-risk (VaR) estimates, and that both models provide a much improved risk assessment relative to the current practice? correcting VaR estimates on the order of 25% in cases in which multiple currency exposures are of similar size. Using the USDCAD, the EURCAD, and the GBPCAD, estimation techniques for each model are demonstrated. Finally, the strength of the improved models are shown through a 100-day VaR calculation.

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