Título:
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Time-varying market beta : does the estimation methodology matter?
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Autor/a:
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Nieto, Belén; Orbe, Susan; Zarraga, Ainhoa
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Abstract:
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This paper compares the performance of nine time-varying beta estimates taken from three different methodologies never previously compared: least-square estimators including nonparametric weights, GARCH-based estimators and Kalman filter estimators. The analysis is applied to the Mexican stock market (2003-2009) because of the high dispersion in betas. The comparison between estimators relies on their financial applications: asset pricing and portfolio management. Results show that Kalman filter estimators with random coefficients outperform the others in capturing both the time series of market risk and their cross-sectional relation with mean returns, while more volatile estimators are better for diversification purposes. |
Materia(s):
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-Time-varying beta -Nonparametric estimator -GARCH-based beta estimator -Kalman filter |
Derechos:
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open access
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https://creativecommons.org/licenses/by-nc-nd/3.0/ |
Tipo de documento:
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Article |
Editor:
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Compartir:
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Uri:
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https://ddd.uab.cat/record/118907
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