Does a Bayesian Approach Generate Robust Forecasts? Evidence from Applications in Portfolio Investment Decisions
8 Pages Posted: 17 Dec 2008
Date Written: December 15, 2008
We employ a statistical criterion (out-of-sample hit rate) and a financial market measure (portfolio performance) to compare the forecasting accuracy of three model selection approaches: Bayesian information criterion (BIC), model averaging, and model mixing. While the more recent approaches of model averaging and model mixing surpass the Bayesian information criterion in their out-of-sample hit rates, the predicted portfolios from these new approaches do not significantly outperform the portfolio obtained via the BIC subset selection method.
Keywords: model selection, BIC, model averaging, model mixing, stock predictability, financial markets
JEL Classification: E44, C11
Suggested Citation: Suggested Citation