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GARCH in VaR - which model is best?
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Economics.
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 is to identify the best volatility model for Value-at-Risk (VaR) estimations. We estimate 1 % and 5 % VaR figures for Nordic indices and stocks by using two symmetrical and two asymmetrical GARCH models under different error distributions. Out-of-sample volatility forecasts are produced using a 500 day rolling window estimation on data covering January 2007 to December 2014. The VaR estimates are thereafter evaluated through Kupiec´s test and Christoffersen´s test in order to find the best model. The results suggest that asymmetrical models perform better than symmetrical models albeit the simple ARCH is often good enough for 1 % VaR estimates.

Place, publisher, year, edition, pages
2015.
Keyword [en]
Value-at-Risk, ARCH/GARCH forecasting, Backtesting, Kupiec test, Christoffersen test
National Category
Economics
Identifiers
URN: urn:nbn:se:uu:diva-243048OAI: oai:DiVA.org:uu-243048DiVA: diva2:785844
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Available from: 2015-02-04 Created: 2015-02-04 Last updated: 2015-02-04Bibliographically approved

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