Evaluation of Value-at-Risk Models During Volatility Clustering

Sammanfattning: In the light of the financial crisis of 2008, risk management has become one of the most important topics in the financial world. This study applies five different VaR approaches, normal distribution, student’s t distribution, historical simulation, age weighted historical simulation and volatility weighted historical simulation under three different sample windows. These parametric, non-parametric and semi-parametric approaches were applied on the historical closing prices of five highly diversified stock indices, OMXS 30, S&P 500, NIKKEI 225, DAX 30 and FTSE 100, where the focus has been on the period of 2007-2012. Performance was evaluated by comparing the expected number of VaR breaks to the actual number of VaR breaks, the so called VaR ratio. The study found that most of the models using a larger sample window failed to cope with sudden changes in volatility, while the age weighted historical simulation seemed to cope well with sudden changes in market conditions in all sample windows. The study also found that forecasting volatility using EWMA in extreme market conditions failed to give accurate VaR estimates.