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Conditional beta pricing models: A nonparametric approach

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  • Ferreira, Eva
  • Gil-Bazo, Javier
  • Orbe, Susan

Abstract

We propose a two-stage procedure to estimate conditional beta pricing models that allows for flexibility in the dynamics of asset betas and market prices of risk (MPR). First, conditional betas are estimated nonparametrically for each asset and period using the time-series of previous data. Then, time-varying MPR are estimated from the cross-section of returns and betas. We prove the consistency and asymptotic normality of the estimators. We also perform Monte Carlo simulations for the conditional version of the three-factor model of Fama and French (1993) and show that nonparametrically estimated betas outperform rolling betas under different specifications of beta dynamics. Using return data on the 25 size and book-to-market sorted portfolios, we find that the nonparametric procedure produces a better fit of the three-factor model to the data, less biased estimates of MPR and lower pricing errors than the Fama–MacBeth procedure with betas estimated under several alternative parametric specifications.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Banking & Finance.

Volume (Year): 35 (2011)
Issue (Month): 12 ()
Pages: 3362-3382

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Handle: RePEc:eee:jbfina:v:35:y:2011:i:12:p:3362-3382

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Web page: http://www.elsevier.com/locate/jbf

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Keywords: Kernel estimation; Conditional beta pricing models; Fama–French three-factor model; Locally stationary processes;

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Cited by:
  1. Zárraga Alonso, Ainhoa & Nieto Domenech, Belén & Orbe Mandaluniz, Susan, 2011. "Time-Varying Beta Estimators in the Mexican Emerging Market," BILTOKI 2011-06, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).

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