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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).

Record type: Monograph (Working Paper)

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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More information

Published date: 2007
Keywords: forecasting, kalman filter, garch, volatility

Identifiers

Local EPrints ID: 51665
URI: http://eprints.soton.ac.uk/id/eprint/51665
ISSN: 1356-3548
PURE UUID: 9836b283-5526-4e41-ac6a-b00a8f743239

Catalogue record

Date deposited: 05 Jun 2008
Last modified: 17 Jul 2017 14:48

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Contributors

Author: Taufiq Choudhry
Author: Hao Wu

University divisions

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