Time-Varying Market Beta: does the estimation methodology matter?

• Autores: Belén Nieto Domenech, Susan Orbe Mandaluniz, Ainhoa Zarraga Alonso
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 38, Nº. 1, 2014, págs. 13-42
• Idioma: inglés
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• Resumen

  • 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 be- tween 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.