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Research On Constructing Predictive Model Of Corporate Bond Default Based On Operating And Corporate Governance Characteristics

Posted on:2020-08-14Degree:MasterType:Thesis
Country:ChinaCandidate:Z H ZhangFull Text:PDF
GTID:2439330572488601Subject:Accounting
Abstract/Summary:PDF Full Text Request
Since the “11 Super Day Debt” defaulted in 2014,“rigid redemption” has been broken in Chinese bond market and bond defaults have occurred from time to time,which has greatly hurt the confidence of investors who want to obtain stable return through bond investment,credit spreads have increased and put a huge burden on enterprises,it also make a profound impact on the credit process of Chinese bond market.Under this background,how to effectively identify the operating and governance characteristics of bond default companies and construct a bond default predictive model has theoretical and practical significance for preventing bond default risk.Based on credit risk management and principal-agent theory,combined with the institutional background of Chinese bond market and the situation of corporate bonds default,this paper first put forward the relevant assumptions of the company’s operating and governance characteristics which affect the bond default.Made company which defaulted on bonds from January 2014 to June 2018 in Chinese bond market as a sample and selected the control sample.The statistical variables and factor analysis method are used to screen out the difference variables between the bond default company and the non-default company and they are summarized by dimension reduction to identify the default company’s operating and governance characteristics.Then,based on the data of Chinese bond default companies from January 2014 to June 2018,considering the operating and governance characteristics,the logistic regression model was used to test the hypothesis and construct a corporate bond default predictive model.Finally,the bond default predictive model was tested based on the data of Chinese bond default companies which defaulted from July 2018 to December 2018,the results showed that the prediction accuracy rate is 72.7% and the model is reliable.Based on the research conclusions,this paper puts forward relevant policy recommendations to prevent bond default risk from the perspectives of bond regulators,bond intermediaries,bond issuers and bond investors.The research in this paper promotes the development of risk management research theory;it has positive significance for improving the bond issuance supervision system and exploring the bond default risk evaluation mechanism.
Keywords/Search Tags:Corporate bond, Bond default, Feature recognition, Predictive model
PDF Full Text Request
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