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- W3121594576 abstract "This article proposes semi-parametric least squares estimation of parametric risk-return relationships, i.e. parametric restrictions between the conditional mean and the conditional variance of excess returns given a set of unobservable parametric factors. A distinctive feature of our estimator is that it does not require a parametric model for the conditional mean and variance. We establish consistency and asymptotic normality of the estimates. The theory is non-standard due to the presence of estimated factors. We provide simple sufficient conditions for the estimated factors not to have an impact in the asymptotic standard error of estimators. A simulation study investigates the nite sample performance of the estimates. Finally, an application to the CRSP value-weighted excess returns highlights the merits of our approach. In contrast to most previous studies using non-parametric estimates, we find a positive and significant price of risk in our semi-parametric setting." @default.
- W3121594576 created "2021-02-01" @default.
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- W3121594576 date "2013-08-01" @default.
- W3121594576 modified "2023-09-27" @default.
- W3121594576 title "SEMI PARAMETRIC ESTIMATION OF RISK-RETURN RELATIONSHIPS" @default.
- W3121594576 hasPublicationYear "2013" @default.
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