基于机器学习算法的企业债券违约预警模型
A Machine Learning Based Enterprise Bond Default Warning Model
胡传胜 1周志国1
作者信息
- 1. 安徽继远软件有限公司,安徽 合肥 230088
- 折叠
摘要
本研究旨在通过大数据方法构建企业债券违约预警模型,利用逻辑回归、XGboost、支持向量机等机器学习算法,结合企业用电、财务等多维数据,搭建企业违约预警指标体系,训练并预测当期企业债券违约概率,划分企业风险等级,降低投资风险.
Abstract
This study aims to construct a corporate bond default warning model using big data methods,utilizing machine learning algorithms such as logistic regression,XGboost,and support vector machines,combined with multidimensional data such as enterprise electricity and finance,to establish a corporate default warning indicator system,train and predict the default probability of current corporate bonds,classify enterprise risk levels,and reduce investment risks.
关键词
债券违约/投资风险/逻辑回归/XGBoost算法/支持向量机Key words
bond default/investment risk/logistic regression/XGBoost algorithm/Support vec-tor machine引用本文复制引用
出版年
2024
NETL
NSTL
万方数据