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Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach

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journal contribution
posted on 12.05.2022, 04:13 by Hai LinHai Lin, C Wu, G Zhou
Using a comprehensive return data set and an array of 27 macroeconomic, stock, and bond predictors, we find that corporate bond returns are highly predictable based on an iterated combination model. The large set of predictors outperforms traditional predictors substantially, and predictability generated by the iterated combination is both statistically and economically significant. Stock market and macroeconomic variables play an important role in forming expected bond returns. Return forecasts are closely linked to the evolution of real economy. Corporate bond premia have strong predictive power for business cycle, and the primary source of this predictive power is from the low-grade bond premium.

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Preferred citation

Lin, H., Wu, C. & Zhou, G. (2017). Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach. Management Science, 64(9), 1-21. https://doi.org/10.1287/mnsc.2017.2734

Journal title

Management Science

Volume

64

Issue

9

Publication date

10/05/2017

Pagination

1-21

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Publication status

Published

Contribution type

Article

Online publication date

10/05/2017

ISSN

0025-1909

eISSN

1526-5501

Language

en