Forecasting the weekly time-varying beta of UK firms: comparison between GARCH models vs Kalman filter method

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Description/Abstract

This paper investigates the forecasting ability 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 non-GARCH model
the Kalman method. Forecast errors based on twenty UK company weekly stock return (based on timevary
beta) 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 somewhat more
accurate forecasts than the bivariate GARCH model.