Examining GARCH forecasts for Value-at-Risk predictions
In this thesis we use the GARCH(1,1) and GJR-GARCH(1,1) models to estimate the conditional variance for five equities from the OMX Nasdaq Stockholm (OMXS) stock exchange. We predict 95% and 99% Value-at-Risk (VaR) using one-day ahead forecasts, under three different error distribution assumptions, t...
| Main Authors: | , |
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| Format: | Others |
| Language: | English |
| Published: |
Uppsala universitet, Statistiska institutionen
2014
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| Subjects: | |
| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-226032 |