This paper forecast the weekly time-varying beta of 20 UK firms by means of four
different GARCH models and the Kalman filter method. The four GARCH models
applied are the bivariate GARCH, BEKK GARCH, GARCH-GJR and the GARCH-X
model. The paper also compares the forecasting ability of the GARCH models and the
Kalman method. Forecast errors based on return forecasts are employed to evaluate
out-of-sample forecasting ability of both GARCH models and Kalman method.
Measures of forecast errors overwhelmingly support the Kalman filter approach.
Among the GARCH models both GJR and GARCH-X models appear to provide a bit
more accurate forecasts than the bivariate GARCH model