分类号密级公开
UDC 编号20223550011
硕士学位论文
（专业学位）
我国房地产公司债务违约风险预警研究
——以“金科股份”为例
申请人姓名付家宝____
导师姓名及职称卢万青，教授___
专业学位类别金融硕士______
专业学位领域金融______
培养单位广东外语外贸大学_
学位授予单位广东外语外贸大学_
2024年5月27日
分类号密级公开
UDC 编号20223550011
广东外语外贸大学硕士学位论文
（专业学位）
我国房地产公司债务违约风险预警研究
——以“金科股份”为例
Research on early warning of debt default risk of real estate
companies in China
——Take "Jinke shares"as an example
申请人姓名____付家宝________
导师姓名及职称____卢万青，教授__
专业学位类别_____金融硕士________
专业学位领域_____金融_____________
论文提交日期_____2024年5月27日_____
论文答辩日期_____2024年5月16日__
答辩委员会__郭文伟教授杨龙___
___杨碧云教授__________
学位授予单位：广东外语外贸大学______
摘要
根据数据显示，2022年债券违约数量为202只，债券违约发生金额
2220.89亿元，债务违约数量和规模都较往年呈大规模上升趋势。其中债券违
约数量最多的行业是房地产行业，违约主体中民营企业违约数量和金额都多于
国有企业，上市公司占比大幅攀升。在信用评级方面，高等级债券违约规模占
比较高。债券由于其本身财务杠杆效应的优势，使得其逐渐成为我国公司融资
的一种重要渠道。因此，研究公司债务违约风险并对其进行提前预警十分重要。
金科股份曾经是一家优质的房地产民营上市企业，但却于近些年来多次发生债
务展期及违约事件。
本文先根据财务指标、非财务指标等多种方面初步选取风险预警指标，通
过相关性分析剔除相关性检验能力较差的指标，再通过熵值法、功效系数法等
多种方法构建风险预警模型，本文选取金科股份作为研究对象，将信用评级模
型、KMV 模型与金科股份代入债务违约风险预警的结果进行对比分析，得出最
终的结论与建议。
通过本文的研究发现:第一，在选取指标方面，若只单一的选取财务指标和
微观指标，而不全面的选取非财务指标等宏观因素指标，会使预警指标无法全
面准确地预测债务违约风险，可通过选取宏观经济、行业状况等多因素来对风
险进行预警。第二，当前的一些研究模型普遍依赖于信用评级和单方面选取指
标来构建预警模型，这样的模型方法明显存在滞后性和片面性，很难达到提前
预警效果，KMV 预警模型结果受上市公司的股票市场数据影响较大，如果上市
公司股票停牌过久很容易导致数据失灵，使最终预警结果不准确。在信用评级
方面，外部信用评级也存在着滞后性和评级不客观等问题，使最终预警结果不
能很好地反映现实状况。第三，企业发生债务违约在外部上主要是由于受到宏
观经济恶化、政策缩紧等多种因素影响，在内部上很大程度上是由于融资问题、
资金使用效率问题、经营战略失误等造成的。这暗示着企业应拓宽融资渠道、
提高资金使用效率、进行正确的前瞻性战略规划，并提高风险管理能力。
关键词：公司债务违约；违约风险；风险预警
I
Abstract
According to the data,the number of bond defaults in 2022is 202,and bond
default amount is 222.089billion yuan,debt number and scale show a large-scale
upward trend compared with previous years.Among them,the real estate industry
accounts for the largest proportion of bond defaults.Among the default subjects,the
number and amount of defaults of private enterprises are more than that of state-
owned enterprises,and the proportion of listed companies has risen significantly.In
terms of credit rating,high-grade bond defaults account for a relatively high scale.
Because of its advantage of financial leverage effect,bond has gradually become an
important financing channel for Chinese companies.Therefore,it is very important to
study the company's debt default risk and give early warning.Jinke Shares used to be
a high-quality private real estate listed enterprise,but in recent years,there have been
many debt extensions and defaults.
In this paper,risk early warning indicators are initially selected according to
various aspects such as financial indicators and non-financial indicators,then
indicators with poor correlation testing ability are eliminated through correlation
analysis,and risk early warning models are constructed through entropy method,
efficacy coefficient method and other methods.In this paper,Jinke shares are selected
as the research object.The results of credit rating model,KMV model and Jinke stock
substitute debt default risk warning are compared and analyzed,and the final
conclusions and suggestions are drawn.
The findings of this paper are as follows:First,only financial and micro
indicators are selected,but non-financial indicators and other macro factors are not
comprehensively selected,the early warning indicators will not be able to predict the
debt default risk comprehensively and accurately.Multiple factors such as
macroeconomic and industry conditions can be selected for early warning.Second,
some current research models generally rely on credit rating and unilateral selection
of indicators to build early warning models,such model methods obviously have lag
and one-sidedness,and it is difficult to achieve early warning effect.The result of
KMV early warning model is greatly influenced by stock market data,and if the stock
trading of listed companies is suspended for too long,it is easy to cause data failure.
The final warning result is not accurate.In terms of credit rating,external credit rating
II
also has some problems,such as lag and non-objective rating,so that the final
warning result can not reflect the reality well.Third,the debt default of enterprises is
mainly caused externally by a variety of factors such as macroeconomic deterioration
and policy tightening,and internally,to a large extent,it is caused by financing
problems,fund use efficiency problems,and business strategy errors.This implies that
enterprises should broaden financing channels,improve the efficiency of capital use,
carry out correct strategic planning and improve risk management capabilities.
Keywords:Corporate default;Default risk;Risk warning
III