Keywords

capital asset-pricing model, multivariate autoregressive conditional heteroscedasticity, semiparametric efficiency

Abstract

A semiparametric efficient estimation procedure is developed for the parameters of multivariate generalized autoregressive conditional heteroscedasticity-in-mean models when the disturbances have a conditional distribution assumed to be elliptically symmetric but otherwise unrestricted. Under highlevel assumptions, the resulting estimator achieves the asymptotic semiparametric efficiency bound. The elliptical symmetry assumption allows us to avert the curse of dimensionality problem that would otherwise arise in estimating the unknown error distribution. This framework is suitable for the estimation and testing of conditional asset-pricing models, such as the conditional capital asset-pricing model. We apply our procedure in an empirical study of stock prices, with Monte Carlo simulation results also reported.

Original Publication Citation

“Efficient Estimation of Conditional Asset Pricing Models,” (with Douglas Hodgson), 2003, Journal of Business and Economic Statistics, 21, 269-283.

Document Type

Peer-Reviewed Article

Publication Date

2003

Publisher

Journal of Business and Economic Statistics

Language

English

College

Marriott School of Business

Department

Finance

University Standing at Time of Publication

Full Professor

Download

Share

COinS