UWSpace is currently experiencing technical difficulties resulting from its recent migration to a new version of its software. These technical issues are not affecting the submission and browse features of the site. UWaterloo community members may continue submitting items to UWSpace. We apologize for the inconvenience, and are actively working to resolve these technical issues.
 

Conditional Scenario Generation with a GVAR Model

dc.contributor.authorWang, Xinghao
dc.date.accessioned2016-12-15T17:02:00Z
dc.date.available2016-12-15T17:02:00Z
dc.date.issued2016-12-15
dc.date.submitted2016-12-02
dc.description.abstractThe stress-testing method formed an integral part of the practice of risk management. However, the underlying models for scenarios generation have not been much studied so far. In past practice, the users typically did not model risk factors for portfolios of moderate size endogenously due to the presence of "curse of dimensionality" problem. Moreover, it is almost impossible to impose the expert views for a future outcome of macroeconomy on the scenario generator without making ad-hoc adjustments. In this thesis we propose a GVAR-based framework which allows an efficient simulation of risk factors for a complex multi-currency portfolio of various classes of assets conditioning on economic scenarios. Given reasonable sets of economic forecasts, the GVAR model anticipates the trend and codependency of the future path of portfolio risk factors and supports the production of meaningful results from risk analytics.en
dc.identifier.urihttp://hdl.handle.net/10012/11108
dc.language.isoenen
dc.pendingfalse
dc.publisherUniversity of Waterlooen
dc.subjectStress-testingen
dc.subjectConditional Scenario Generationen
dc.subjectHigh-dimensional Dataen
dc.subjectGVARen
dc.titleConditional Scenario Generation with a GVAR Modelen
dc.typeMaster Thesisen
uws-etd.degreeMaster of Mathematicsen
uws-etd.degree.departmentStatistics and Actuarial Scienceen
uws-etd.degree.disciplineActuarial Scienceen
uws-etd.degree.grantorUniversity of Waterlooen
uws.contributor.advisorSaunders, David
uws.contributor.advisorWirjanto, Tony
uws.contributor.affiliation1Faculty of Mathematicsen
uws.peerReviewStatusUnrevieweden
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Wang_Xinghao.pdf
Size:
2.2 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
6.17 KB
Format:
Item-specific license agreed upon to submission
Description: