An Empirical Study On The Factors Influencing The Credit Spread Of Real Estate Corporate Bonds

Before 2015,the companies that can issue corporate bounds in China's securities market are only listed companies(including domestic listed companies and overseas listed companies).In 2015,the CSRC published the Measures for the Administration of Corporate Bond Issuance and Trading,which expand the issuers to all corporate ownership.As a result,the scale and number of issuance of corporate bonds exploded.Also,issuing bounds have became one of the most important channels to raise money in capital market.In 2019,a total of 2464 corporate bonds were issued,with an amount of 2.54 trillion,with an increase of 53%,accounting for 17.13%of China's total bond issuance.The rapid expansion of the issuance scale of corporate bonds provides a convenient channel for the company to direct financing,which is benificial for the company to access a large number of funds in the capital market,to make full use of the role of financial leverage,to promote the company's production and operation.As a capital-intensive industry,real estate has a huge demand for money.Recently,with the macro-control policies to the real estate industry,the policy of "house are bulit to live,not to speculate" is the main principle.Under this circumstance,the government has intensively issued a number of policies to regulate the real estate industrial to promote a stable development.As one of the main industries of debt issuance,the real estate industry has its unique characteristics,so it is necessary to research which factors have influence on the bond credit risk of the real estate industry.At the same time,with the increasing concentration of the real estate industry,the enterprises with large capital demand are generally listed enterprises,so it is very meaningful to study the bond credit spread of listed real estate enterprises.This paper research the bonds issued by listed real estate enterprises.It selects some influencing factors from the macro level,the real estate industry level,the corporate level and the bound level.The bond issuance data are obtained from wind and national database.Then I structure a multiple regression analysis on the influencing factors of bond credit spread,and test the regression results,finding that there is a collinearity problem in the selected indicators.Next,the model needs to be improved,which is mainly reflected in the sample dimension reduction and variable selection.The stepwise regression method is used to gradually select significant variables to introduce the model.The principal component analysis method is used to select the main components that have significant influence on the model and regression model is established for the selected main components.The significant variables are selected and regression analysis is carried out through the lesso method.The results show that the later three models are better than the original least square model.In addition,by selecting the data of bond issuance in 2020 for back testing to test the effect of the model and compare the results of different methods,it is found that the prediction error of lesso regression is the smallest.The main innovation of this paper lies in the selection method of risk-free interest rate and the introduction of relevant industry level influencing factors.