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Forecasting value at risk in the Swedish stock market - an investigation of GARCH volatility models
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Economics.
2015 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The purpose of this thesis was to investigate various conditional volatility models commonly used in forecasting financial risk within the field of Financial Econometrics. The GARCH, the GJR-GARCH and the T-GARCH models were examined. The models ability to forecast the conditional variance was investigated by forecasting the conditional volatility in four of the major Swedish stock indices, the OMXS30, Large Cap, Medium Cap and the Small Cap. The forecasted conditional volatility was then used to compute Value at Risk measurements, a measurement of risk that today is used in the risk management of most financial houses around the globe. The models ability to forecast the Value at Risk was then tested with Kupiecs unconditional coverage test. Support was found for the GJR-GARCH and T-GARCH models with Gaussian distributions producing the most satisfactory Value at Risk measures.

KEYWORDS: ARCH, GARCH, GJR-GARCH, T-GARCH, Conditional Volatility, Value at Risk, Stock Indices.

Place, publisher, year, edition, pages
2015. , 23 p.
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:uu:diva-261004OAI: oai:DiVA.org:uu-261004DiVA: diva2:849270
Subject / course
Economics
Supervisors
Examiners
Available from: 2015-10-13 Created: 2015-08-27 Last updated: 2015-10-13Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association
  • 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