Abstract

When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's "nite-sample properties, derived here, can depart substantially from the standard regression setting. Bayesian posterior distributions for the regression parameters are obtained under speci"cations that di!er with respect to (i) prior beliefs about the autocorrelation of the regressor and (ii) whether the initial observation of the regressor is speci"ed as "xed or stochastic. The posteriors di!er across such speci"cations, and asset allocations in the presence of estimation risk exhibit sensitivity to those di!erences. ( 1999 Elsevier Science S.A. All rights reserved. JEL classixcation: C32; C11; G11

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Cite this paper

@inproceedings{Avramov1999PredictiveR, title={Predictive regressions}, author={Doron Avramov and John Y . Campbell and L̆ubos̆ P{\'a}stor and Robert F. Stambaugh}, year={1999} }