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

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.

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Identifiers

ORCID for Taufiq Choudhry: orcid.org/0000-0002-0463-0662

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