Academic Journal of Business & Management, 2022, 4(7); doi: 10.25236/AJBM.2022.040715.
Longyifei Ye, Haolong Wu, Xiuwen Duan
City College, Zhejiang University, Hangzhou, Zhejiang, 310000, China
As an important part of the bond market, corporate bonds have the characteristics of high yield and high risk. This work aims to design an index system of influencing factors through the literature research on the current situation of corporate bond defaults, credit risk related theories and credit risk model theories, using corporate bond default data, and integrate machine learning models and KMV optimization models to construct the credit risk early warning model of my country's high-yield corporate bonds. Investors, regulators and other relevant parties can use this early warning model to more effectively pay attention to the potential default risk of corporate bonds, and carry out corresponding credit risk control to ensure the stable development of the bond market.
High-yield bonds, Support vector machine, KMV-Logistic model, Bond default
Longyifei Ye, Haolong Wu, Xiuwen Duan. Research on the Credit of High-Yield Corporate Bonds in My country Under Machine Learning. Academic Journal of Business & Management (2022) Vol. 4, Issue 7: 88-92. https://doi.org/10.25236/AJBM.2022.040715.
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