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Corrigendum: Bond Risk Premiums with Machine Learning
The Review of Financial Studies ( IF 8.414 ) Pub Date : 2020-11-06 , DOI: 10.1093/rfs/hhaa098 Daniele Bianchi 1 , Matthias Büchner 2 , Tobias Hoogteijling 3 , Andrea Tamoni 4
中文翻译:
更正:机器学习带来的债券风险溢价
更新日期:2020-11-06
The Review of Financial Studies ( IF 8.414 ) Pub Date : 2020-11-06 , DOI: 10.1093/rfs/hhaa098 Daniele Bianchi 1 , Matthias Büchner 2 , Tobias Hoogteijling 3 , Andrea Tamoni 4
Affiliation
Abstract
In this note we revisit the empirical results in Bianchi, Büchner, and Tamoni (2020) after correcting for using information not available at the time the forecast was made. Although we note a decrease in out-of-sample $R^2$, the revised analysis confirms that bond excess return predictability from neural networks remains statistically and economically significant.
中文翻译:
更正:机器学习带来的债券风险溢价
摘要
在本说明中,我们校正了使用预测时不可用的信息后,重新审视了比安奇(Bianchi),比希纳(Büchner)和塔莫尼(Tamoni)(2020)的经验结果。尽管我们注意到样本外的$ R ^ 2 $有所减少,但修订后的分析证实,来自神经网络的债券超额收益的可预测性在统计和经济上仍然很重要。