Nonparametric estimation of conditional beta pricing models

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dc.contributor.author Ferreira, Eva
dc.contributor.author Gil-Bazo, Javier
dc.contributor.author Orbe, Susan
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Economía de la Empresa
dc.date.accessioned 2008-05-28T10:07:31Z
dc.date.available 2008-05-28T10:07:31Z
dc.date.issued 2008-05
dc.identifier.uri http://hdl.handle.net/10016/2612
dc.description.abstract We propose a new procedure to estimate and test conditional beta pricing models which allows for flexibility in the dynamics of assets' covariances with risk factors and market prices of risk (MPR). The method can be seen as a nonparametric version of the two-pass approach commonly employed in the context of unconditional models. In the first stage, conditional covariances are estimated nonparametrically for each asset and period using the time-series of previous data. In the second stage, time-varying MPR are estimated from the cross-section of returns and covariances, using the entire sample and allowing for heteroscedastic and cross-sectionally correlated errors. We prove the desirable properties of consistency and asymptotic normality of the estimators. Finally, an empirical application to the term structure of interest rates illustrates the method and highlights several drawbacks of existing parametric models.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Business Economics
dc.relation.ispartofseries 08-03
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Kernel estimation
dc.subject.other Locally stationary processes
dc.subject.other Time-varying coefficients
dc.subject.other Conditional asset pricing models
dc.title Nonparametric estimation of conditional beta pricing models
dc.type workingPaper
dc.subject.jel C14
dc.subject.jel G12
dc.subject.eciencia Empresa
dc.rights.accessRights openAccess
dc.identifier.repec wb082403
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