The market model assumes stock returns to be a linear function of the market return. However, there is considerable evidence that the beta stability assumption commonly used when estimating the market model is invalid. In this paper we account for beta instability in German stock returns by allowing the coefficients to vary over time in estimation. For time-varying beta estimation we rely on the Flexible Least Squares approach, the Random Walk Model and Moving Window Least Squares. Due to our results time-varying estimation fits the data considerably better than time-invariant estimation and, hence, increases the efficiency of beta based risk measurement. Copyright Swiss Society for Financial Market Research 2005
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Mª Victoria Esteban González & Fernando Tusell Palmer, 2009.
"Predicting Betas: Two new methods,"
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200901, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
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