Analysis of Default Recovery Rate for Chinese Credit Bonds
Xiangzhen Li;Shida Liu;Hao Wang;
Abstract:
This article uses default data from 2014 to 2021 to study the recovery rate of credit bonds in China. The average recovery rate one year after bond default(as of the end of 2021) is 8%(11%), with an asymmetric bipolar distribution, concentrated on both sides of 0% and 100%. With different horizon, the gold recovery horizon for defaulting bonds is one year. The proportion of Existing bonds in assets is an important factor affecting the recovery rate. Besides, with or without guarantor, issued in the inter-bank market or not, state owned enterprise or not, publicly listed or not, short-term treasury rate and spread over long and short treasury rate significantly affect the default recovery rate. In terms of recovery rate prediction, machine learning models are significantly superior to linear regression models. Among them, the prediction of ensemble learning model is the best.
Key Words:
Foundation: 清华自主科研基金的资助(项目号2023THZWJC20)的资助
Authors: Xiangzhen Li;Shida Liu;Hao Wang;
References:
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- ① 见王浩和刘士达(2022)。 ② 见林青和郝帅(2017)和刘逸凡等(2020)。 (1)在分布假设上,OLS线性模型会隐含正态分布的假设,其对回收率的解释力度实则较低;而机器学习模型多为非线性模型,对回收率的解释力度要明显高于OLS。在算法机制上,Strobl et al.(2007)指出,排序重要性更倾向于筛选连续变量和分类较多的离散变量,对0/1变量存在“歧视”,这也使得机器学习模型不易把债券特征(有无担保人、是否在银行间市场发行)和企业特征(是否为国企、是否为上市公司)变量作为有解释力度的重要变量。 (2)523支违约债券中有52只存在违约后的交易记录,占比仅为9.94%;另一方面,存在交易价格的债券中,26支债券交易记录小于2笔,占比50%。
- Xiangzhen Li
- Shida Liu
- Hao Wang
- School of Economics and Management
- Tsinghua University
- National Council for Social Security Fund
- Xiangzhen Li
- Shida Liu
- Hao Wang
- School of Economics and Management
- Tsinghua University
- National Council for Social Security Fund