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Univariate GARCH models with realized variance
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This essay investigates how realized variance affects the GARCH-models (GARCH, EGARCH, GJRGARCH) when added as an external regressor. The GARCH models are estimated with three different distributions; Normal-, Student’s t- and Normal inverse gaussian distribution. The results are ambiguous - the models with realized variance improves the model fit, but when applied to forecasting, the models with realized variance are performing similar Value at Risk predictions compared to the models without realized variance.

Place, publisher, year, edition, pages
2019. , p. 40
Keywords [en]
GARCH, EGARCH, GJRGARCH, external regressor, realized variance, volatility, Value at Risk, nig, Normal inverse gaussian, std, Student’s t distribution, norm, Normal distribution, rugarch, rolling forecast
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-386073OAI: oai:DiVA.org:uu-386073DiVA, id: diva2:1326886
Supervisors
Available from: 2019-06-24 Created: 2019-06-18 Last updated: 2019-06-24Bibliographically approved

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Univariate GARCH models with realized variance,(3606 kB)63 downloads
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Department of Statistics
Probability Theory and Statistics

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