Does a Bayesian approach generate robust forecasts? Evidence from applications in portfolio investment decisions

被引:0
|
作者
Chih-Ling Tsai
Hansheng Wang
Ning Zhu
机构
[1] University of California-Davis,Graduate School of Management
[2] Peking University,Department of Business Statistics and Econometrics, Guanghua School of Management
关键词
Model selection; BIC; Model averaging; Model mixing; Stock predictability; Financial markets;
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中图分类号
学科分类号
摘要
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.
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页码:109 / 116
页数:7
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