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


Choudhry, Taufiq and Wu, Hao (2007) Forecasting the weekly time-varying beta of UK firms: comparison between GARCH models vs Kalman filter method. Southampton, UK, University of Southampton, 38pp. (Management Working Papers, (M-07-09) ).

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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.

Item Type: Monograph (Working Paper)
ISSNs: 1356-3548 (print)
Keywords: forecasting, kalman filter, garch, volatility
Subjects: H Social Sciences > HG Finance
H Social Sciences > HB Economic Theory
Divisions: University Structure - Pre August 2011 > School of Management
ePrint ID: 51665
Date Deposited: 05 Jun 2008
Last Modified: 27 Mar 2014 18:34
Publisher: University of Southampton
URI: http://eprints.soton.ac.uk/id/eprint/51665

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