1 Modelling and Forecasting Dynamic VaR Thresholds for Risk Management and Regulation*

The paper presents methods of estimating Value-at-Risk (VaR) thresholds utilising two calibrated models and three conditional volatility or GARCH models. These are used to estimate and forecast the VaR thresholds of an equally-weighted portfolio, comprising: the S&P500, CAC40, FTSE100 a Swiss market index (SMI). On the basis of the number of (non-)violations of the Basel Accord thresholds, the best performing model is PS-GARCH, followed by VARMA-AGARCH, then Portfolio-GARCH and the RiskmetricsTM –EWMA models, both of which would attract a penalty of 0.5. The worst forecasts are obtained from the standard normal method based on historical variances