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A comparison of multivariate GARCH models with respect to Value at Risk
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Since the introduction univariate GARCH models number of available models have grown rapidly and has been extended to the multivariate area. This paper compares three different multivariate GARCH models and they are evaluated using out of sample Value at Risk of dif- ferent portfolios. Sector portfolios are used with different market capitalization. The models compared are the DCC,CCC and the GO-Garch model. The forecast horizon is 1-day, 5-day and 10-day ahead forecast of the estimated VaR limit. The DCC performs best with regards to both conditional anc unconditional violations of the VaR estimates.

Place, publisher, year, edition, pages
2019.
Keywords [en]
multivariate GARCH, Value at Risk, forecasting, conditional correlation
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-385521OAI: oai:DiVA.org:uu-385521DiVA, id: diva2:1324825
Educational program
Master Programme in Statistics
Supervisors
Examiners
Available from: 2019-06-18 Created: 2019-06-14 Last updated: 2019-06-18Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf