Predictive information in corporate bond yields

Xu Guo; Hai Lin; Chunchi Wu; Guofu Zhou

doi:10.1016/j.finmar.2021.100687

Predictive information in corporate bond yields

Xu Guo
, Hai Lin
, Chunchi Wu
, Guofu Zhou

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

We document strong evidence of the cross-sectional predictability of corporate bond returns based on a set of yield predictors that capture the information in the yields of past 1, 3, 6, 12, 24, 36, and 48 months. Return predictability is economically and statistically significant, and is robust to various controls. The uncovered predictability presents the most pronounced anomaly in the corporate bond literature that challenges rational pricing models.

Original language	English
Article number	100687
Journal	Journal of Financial Markets
Volume	59
DOIs	https://doi.org/10.1016/j.finmar.2021.100687
State	Published - Jun 2022

Keywords

Corporate bond returns
Cross-sectional predictability
Moving averages
Yield signals

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10.1016/j.finmar.2021.100687

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title = "Predictive information in corporate bond yields",

abstract = "We document strong evidence of the cross-sectional predictability of corporate bond returns based on a set of yield predictors that capture the information in the yields of past 1, 3, 6, 12, 24, 36, and 48 months. Return predictability is economically and statistically significant, and is robust to various controls. The uncovered predictability presents the most pronounced anomaly in the corporate bond literature that challenges rational pricing models.",

keywords = "Corporate bond returns, Cross-sectional predictability, Moving averages, Yield signals",

author = "Xu Guo and Hai Lin and Chunchi Wu and Guofu Zhou",

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year = "2022",

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doi = "10.1016/j.finmar.2021.100687",

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AU - Guo, Xu

AU - Lin, Hai

AU - Wu, Chunchi

AU - Zhou, Guofu

PY - 2022/6

Y1 - 2022/6

N2 - We document strong evidence of the cross-sectional predictability of corporate bond returns based on a set of yield predictors that capture the information in the yields of past 1, 3, 6, 12, 24, 36, and 48 months. Return predictability is economically and statistically significant, and is robust to various controls. The uncovered predictability presents the most pronounced anomaly in the corporate bond literature that challenges rational pricing models.

AB - We document strong evidence of the cross-sectional predictability of corporate bond returns based on a set of yield predictors that capture the information in the yields of past 1, 3, 6, 12, 24, 36, and 48 months. Return predictability is economically and statistically significant, and is robust to various controls. The uncovered predictability presents the most pronounced anomaly in the corporate bond literature that challenges rational pricing models.

KW - Corporate bond returns

KW - Cross-sectional predictability

KW - Moving averages

KW - Yield signals

UR - https://www.scopus.com/pages/publications/85119196920

U2 - 10.1016/j.finmar.2021.100687

DO - 10.1016/j.finmar.2021.100687

M3 - Article

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SN - 1386-4181

VL - 59

JO - Journal of Financial Markets

JF - Journal of Financial Markets

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ER -

Predictive information in corporate bond yields

Abstract

Keywords

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