Revistes Publicacions URV: SORT - Statistics and Operations Research Transactions> 2014

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

  • Datos identificativos

    Identificador: RP:2406
    Handle: http://hdl.handle.net/20.500.11797/RP2406
  • Autores:

    Zarraga, Ainoha
    Orbe, Susan
    Nieto, Belén
  • Otros:

    Autor/es de la URV: Zarraga, Ainoha Orbe, Susan Nieto, Belén
    Palabras clave: Time-varying beta, nonparametric estimator, GARCH-based beta estimator, Kalman filter
    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.
    Año de publicación de la revista: 2014
    Tipo de publicación: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article
  • Palabras clave:

    Time-varying beta, nonparametric estimator, GARCH-based beta estimator, Kalman filter
  • Documentos:

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