Cross-Sectional Predictability of Corporate Bond Returns

83 Pages Posted: 21 Nov 2016 Last revised: 13 Mar 2019

See all articles by Hai Lin

Hai Lin

Victoria University of Wellington - School of Economics & Finance

Chunchi Wu

SUNY at Buffalo - School of Management

Guofu Zhou

Washington University in St. Louis - John M. Olin Business School; China Academy of Financial Research (CAFR)

Date Written: March 12, 2019

Abstract

While there are hundreds of cross-sectional predictors in the equity market, whether corporate bonds are predictable in the cross-section is an open question. This paper proposes to use trend signals in returns, which exploit short-, intermediate- and long-term trends simultaneously, to predict future bond returns. We provide new evidence that there is statistically significant and economically important predictability in the cross-section of corporate bond returns. This predictability is robust to various controls and stronger for lower-rated bonds. The pronounced bond market anomaly uncovered in this study joins a host of equity anomalies that challenges existing rational pricing models.

Keywords: trend signals; moving averages; cross-sectional predictability; corporate bond returns

JEL Classification: G12; G14

Suggested Citation

Lin, Hai and Wu, Chunchi and Zhou, Guofu, Cross-Sectional Predictability of Corporate Bond Returns (March 12, 2019). Available at SSRN: https://ssrn.com/abstract=2872382 or http://dx.doi.org/10.2139/ssrn.2872382

Hai Lin (Contact Author)

Victoria University of Wellington - School of Economics & Finance ( email )

P.O. Box 600
Wellington 6001
New Zealand

Chunchi Wu

SUNY at Buffalo - School of Management ( email )

Jacobs Management Center
Buffalo, NY 14222
United States

Guofu Zhou

Washington University in St. Louis - John M. Olin Business School ( email )

Washington University
Campus Box 1133
St. Louis, MO 63130-4899
United States
314-935-6384 (Phone)
314-658-6359 (Fax)

HOME PAGE: http://apps.olin.wustl.edu/faculty/zhou/

China Academy of Financial Research (CAFR)

Shanghai Advanced Institute of Finance
Shanghai P.R.China, 200030
China

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