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Time-Varying Beta Estimators in the Mexican Emerging Market

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  • Zárraga Alonso, Ainhoa
  • Nieto Domenech, Belén
  • Orbe Mandaluniz, Susan

Abstract

This paper compares the performance of three different time-varying betas that have never previously been compared: the rolling OLS estimator, a nonparametric estimator and an estimator based on GARCH models. The study is conducted using returns from the Mexican stock market grouped into six portfolios for the period 2003-2009. The comparison, based on asset pricing perspective and mean-variance space returns, concludes that GARCH based beta estimators outperform the others when the comparison is in terms of time series while the nonparametric estimator is more appropriate in the cross-sectional context.

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Bibliographic Info

Paper provided by Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística) in its series BILTOKI with number 2011-06.

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Date of creation: 2011
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Handle: RePEc:ehu:biltok:5283

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Postal: Dpto. de Econometría y Estadística, Facultad de CC. Económicas y Empresariales, Universidad del País Vasco, Avda. Lehendakari Aguirre 83, 48015 Bilbao, Spain
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Keywords: time-varying beta; nonparametric estimator; GARCH based beta estimator;

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  1. Rodríguez Poo, Juan M. & Ferreira García, María Eva & Orbe Mandaluniz, Susan, 2001. "Nonparametric estimation of time varying parameters under shape restrictions," BILTOKI 2001-02, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
  2. Haerdle,Wolfgang & Hall,Peter & Marron,J., 1986. "How far are automatically chosen regression smoothing parametres from their optimum?," Discussion Paper Serie A 74, University of Bonn, Germany.
  3. Andrew Ang & Dennis Kristensen, 2011. "Testing Conditional Factor Models," NBER Working Papers 17561, National Bureau of Economic Research, Inc.
  4. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
  5. Maria Victoria Esteban & Susan Orbe-Mandaluniz, 2010. "A nonparametric approach for estimating betas: the smoothed rolling estimator," Applied Economics, Taylor & Francis Journals, vol. 42(10), pages 1269-1279.
  6. Sascha Mergner & Jan Bulla, 2008. "Time-varying beta risk of Pan-European industry portfolios: A comparison of alternative modeling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 771-802.
  7. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
  8. Li, Yan & Yang, Liyan, 2011. "Testing conditional factor models: A nonparametric approach," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 972-992.
  9. Lewellen, Jonathan & Nagel, Stefan, 2006. "The conditional CAPM does not explain asset-pricing anomalies," Journal of Financial Economics, Elsevier, vol. 82(2), pages 289-314, November.
  10. Shanken, Jay, 1990. "Intertemporal asset pricing : An Empirical Investigation," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 99-120.
  11. Ferreira, Eva & Gil-Bazo, Javier & Orbe, Susan, 2011. "Conditional beta pricing models: A nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3362-3382.
  12. Lewellen, Jonathan & Nagel, Stefan & Shanken, Jay, 2010. "A skeptical appraisal of asset pricing tests," Journal of Financial Economics, Elsevier, vol. 96(2), pages 175-194, May.
  13. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
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