Predicting Individual Corporate Bond Returns

50 Pages Posted: 30 Jun 2021 Last revised: 14 Oct 2022

See all articles by Xin He

Xin He

Hunan University - College of Finance and Statistics; City University of Hong Kong (CityU)

Guanhao Feng

City University of Hong Kong (CityU)

Junbo Wang

Dept. of Economics and Finance, City Univ. of HK

Chunchi Wu

SUNY at Buffalo - School of Management

Date Written: June 19, 2021

Abstract

This paper finds positive evidence of return predictability and investment gains for individual corporate bonds from 1976 to 2020. First, we provide a comprehensive study for multiple predictive models and find random forest is the best. Considering bonds issued by private companies, we find their useful return predictors differ from bonds issued by public companies. The predictability of public bond returns is more sensitive to the T-Bill rate, equity market return and volatility, but private bonds deliver higher investment gains. Second, for 20 macro predictors and 20 bond characteristics considered for return prediction, we find the macro predictors contain additional information. Finally, based on return forecast, market-timing and cross-sectional long-short strategies are profitable and economically significant net of the transaction cost.

Keywords: Bond Characteristics, Individual Corporate Bonds, Macro Predictors, Return Predictability, Private Company Bonds.

JEL Classification: C55, C58, G0, G1, G17.

Suggested Citation

He, Xin and Feng, Guanhao and Wang, Junbo and Wu, Chunchi, Predicting Individual Corporate Bond Returns (June 19, 2021). Available at SSRN: https://ssrn.com/abstract=3870306 or http://dx.doi.org/10.2139/ssrn.3870306

Xin He

Hunan University - College of Finance and Statistics ( email )

109th Shijiachong Road, Yuelu District
Changsha, Hunan 410006
China

HOME PAGE: http://www.xinhesean.com

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Kowloon
Hong Kong

Guanhao Feng (Contact Author)

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Kowloon Tong
Hong Kong

Junbo Wang

Dept. of Economics and Finance, City Univ. of HK ( email )

83 Tat Chee Ave., Kowloon Tong
Kowloon Town
Kowloon, 220
Hong Kong
34429492 (Phone)
852-2788-8806 (Fax)

Chunchi Wu

SUNY at Buffalo - School of Management ( email )

Jacobs Management Center
Buffalo, NY 14222
United States

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