About this document
Stock Return Predictability and Uncertainty by Blunders is a document available to read on EtoBox.
This document summarizes a journal article that uses Bayesian model averaging to analyze stock return predictability in the presence of model uncertainty. The key findings are: 1) Bayesian model averaging reveals both in-sample and out-of-sample return predictability, unlike model selection criteria which fail to show out-of-sample predictability. 2) Term premium and market premium are robust predictors of future returns, while dividend yield and book-to-market have weaker predictive power when accountin
- Author
- Blunders
- Language
- EN