An empirical study in risk management: estimation of Value at Risk with GARCH family models
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
In this paper the performance of classical approaches and GARCH family models are evaluated and compared in estimation one-step-ahead VaR. The classical VaR methodology includes historical simulation (HS), RiskMetrics, and unconditional approaches. The classical VaR methods, the four univariate and two multivariate GARCH models with the Student’s t and the normal error distributions have been applied to 5 stock indices and 4 portfolios to determine the best VaR method. We used four evaluation tests to assess the quality of VaR forecasts:
- Violation ratio
- Kupiec’s test
- Christoffersen’s test
- Joint test
The results point out that GARCH-based models produce far more accurate forecasts for both individual and portfolio VaR. RiskMetrics gives reliable VaR predictions but it is still substantially inferior to GARCH models. The choice of an optimal GARCH model depends on the individual asset, and the best model can be different based on different empirical data.
Place, publisher, year, edition, pages
2013. , 62 p.
Value at Risk, univariate and multivariate GARCH models, classical VaR approaches, evaluation tests
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:uu:diva-201397OAI: oai:DiVA.org:uu-201397DiVA: diva2:627075
Subject / course
Master Programme in Statistics
Ågren, Anders, Professor