Stock Return Predictability and Model Uncertainty

43 Pages Posted: 19 Feb 2001

See all articles by Doron Avramov

Doron Avramov

Reichman University - Interdisciplinary Center (IDC) Herzliyah

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Date Written: April 17, 2001

Abstract

We use Bayesian model averaging to analyze the sample evidence on return predictability in the presence of uncertainty about the return forecasting model. The analysis reveals in-sample and out-of-sample predictability, and shows that the out-of-sample performance of the Bayesian approach is superior to that of model selection criteria. Our exercises find that term premium and market risk premium are relatively robust predictors. Moreover, small-cap value stocks appear more predictable than large-cap growth stocks. We also investigate the implications of model uncertainty from investment management perspectives. The analysis shows that model uncertainty is more important than estimation risk. Finally, asset allocations in the presence of estimation risk exhibit sensitivity to whether model uncertainty is incorporated or ignored.

Keywords: Stock return predictability, model uncertainty, parameter uncertainty, Bayesian model averaging, portfolio selection, Bayesian weighted predictive distribution

Suggested Citation

Avramov, Doron, Stock Return Predictability and Model Uncertainty (April 17, 2001). Available at SSRN: https://ssrn.com/abstract=260591 or http://dx.doi.org/10.2139/ssrn.260591

Doron Avramov (Contact Author)

Reichman University - Interdisciplinary Center (IDC) Herzliyah ( email )

P.O. Box 167
Herzliya, 4610101
Israel

HOME PAGE: http://faculty.idc.ac.il/davramov/

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