Conditional beta pricing models: A nonparametric approach
- Autores: Eva Ferreira García, Javier Gil Bazo, Susan Orbe Mandaluniz
- Localización: Documentos de Trabajo BILTOKI, ISSN-e 1134-8984, Nº. 10, 2010
- Idioma: inglés
- Enlaces
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Resumen
We propose a two-stage procedure to estimate conditional beta pricing models that allow for flexibility in the dynamics of assets� covariances with risk factors and market prices of risk (MPR).
First, conditional covariances 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 covariances using the entire sample. We prove the consistency and asymptotic normality of the estimators. Results from a Monte Carlo simulation for the three-factor model of Fama and French (1993) suggest that nonparametrically estimated betas outperform rolling betas under different specifications of beta dynamics. Using return data on the 25 size and book-tomarket sorted portfolios, we find that MPR associated with the three Fama-French factors exhibit substantial variation through time. Finally, the flexible version of the three-factor model beats alternative parametric specifications in terms of forecasting future returns.
