Stock Return Predictability and Model Uncertainty
43 Pages Posted: 19 Feb 2001
There are 2 versions of this paper
Stock Return Predictability and Model Uncertainty
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
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