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Sustainability 2018, 10(5), 1457; https://doi.org/10.3390/su10051457

Assessing the Credit Risk of Corporate Bonds Based on Factor Analysis and Logistic Regress Analysis Techniques: Evidence from New Energy Enterprises in China

1
School of Economics and Management, North China Electric Power University, Beijing 102206, China
2
Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Changping, Beijing 102206, China
*
Author to whom correspondence should be addressed.
Received: 28 March 2018 / Revised: 30 April 2018 / Accepted: 30 April 2018 / Published: 7 May 2018
(This article belongs to the Section Energy Sustainability)
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Abstract

In recent years, new energy sources have ushered in tremendous opportunities for development. The difficulties to finance new energy enterprises (NEEs) can be estimated through issuing corporate bonds. However, there are few scientific and reasonable methods to assess the credit risk of NEE bonds, which is not conducive to the healthy development of NEEs. Based on this, this paper analyzes the advantages and risks of NEEs issuing bonds and the main factors affecting the credit risk of NEE bonds, constructs a hybrid model for assessing the credit risk of NEE bonds based on factor analysis and logistic regress analysis techniques, and verifies the applicability and effectiveness of the model employing relevant data from 46 Chinese NEEs. The results show that the main factors affecting the credit risk of NEE bonds are internal factors involving the company’s profitability, solvency, operational ability, growth potential, asset structure and viability, and external factors including macroeconomic environment and energy policy support. Based on the empirical results and the exact situation of China’s NEE bonds, this article finally puts forward several targeted recommendations. View Full-Text
Keywords: credit risk assessment; corporate bonds; Chinese new energy enterprise; factor analysis; logistic regress model credit risk assessment; corporate bonds; Chinese new energy enterprise; factor analysis; logistic regress model
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Liu, Y.; Li, F.; Yu, X.; Yuan, J.; Zhou, D. Assessing the Credit Risk of Corporate Bonds Based on Factor Analysis and Logistic Regress Analysis Techniques: Evidence from New Energy Enterprises in China. Sustainability 2018, 10, 1457.

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