The cross-section of Chinese corporate bond returns

IF 3.9 Q1 Mathematics Journal of Finance and Data Science Pub Date : 2023-06-20 DOI:10.1016/j.jfds.2023.100100
Xiaoyan Zhang, Zijian Zhang
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引用次数: 1

Abstract

We study the relation between bond characteristics and corporate bond returns in China's two distinct and segmented bond markets—the interbank market and the exchange market—with a large cross-sectional dataset of 8318 corporate bonds from January 2010 to December 2022. Corporate bonds with large sizes, long maturities, old ages, poor credit ratings and large Amihud illiquidity earn high monthly returns in the interbank market. The return predictive patterns of bond size, time to maturity, and credit rating are similar in the exchange market, but bond age and Amihud illiquidity predict returns in the opposite direction, implying market segmentation. We construct two factors based on credit rating and Amihud illiquidity to represent the common risk of corporate bonds—credit risk and liquidity risk—and use the Hansen-Jagannathan distance to evaluate the performances of factors in explaining the returns of corporate bond portfolios. We find that the two characteristic-based factors help reduce the model specification errors of the five factors in Fama and French (1993).

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中国公司债券收益率的横截面
我们利用2010年1月至2022年12月的8318只公司债券的大型横截面数据,研究了中国两个截然不同且细分的债券市场——银行间市场和交易所市场——的债券特征与公司债券回报之间的关系。规模大、期限长、期限长、信用评级差、Amihud流动性差的公司债券在银行间市场获得了较高的月度回报。债券规模、到期日和信用评级的收益预测模式在交易所市场上相似,但债券年限和Amihud非流动性预测收益方向相反,暗示市场细分。我们基于信用评级和Amihud非流动性构建了两个因子来表示公司债券的共同风险——信用风险和流动性风险,并使用Hansen-Jagannathan距离来评价因子在解释公司债券投资组合收益方面的表现。我们发现这两个基于特征的因素有助于减少Fama和French(1993)的五个因素的模型规范误差。
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来源期刊
Journal of Finance and Data Science
Journal of Finance and Data Science Mathematics-Statistics and Probability
CiteScore
3.90
自引率
0.00%
发文量
15
审稿时长
30 days
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