一个改进多元马尔可夫链违约预测模型——基于群组专家关于企业之间信用变化影响的判别  

An Improved Multivariate Markov Chain Default Prediction Model——Based on the Judgment of a Group of Experts on Default Correlation among Companies

作　　者：闫达文[1] 迟国泰[2] 张帆 YAN Dawen;CHI Guotai;ZHANG Fan(School of Mathematical Sciences,Dalian University of Technology,Dalian 116024,China;School of Economics and Management,Dalian University of Technology,Dalian 116024,China)

机构地区：[1]大连理工大学数学科学学院,辽宁大连116024 [2]大连理工大学经济管理学院,辽宁大连116024

出　　处：《运筹与管理》2024年第9期126-133,共8页Operations Research and Management Science

基　　金：国家自然科学基金资助项目(72271040,72071026);教育部人文社会科学研究项目(22YJAZH125);2023年度来华留学研究课题重点项目(DUTLHLX202304)。

摘　　要：本研究通过运用群组决策方法为信用状态变化过程中不同企业的影响力排序,进而建立信用转移概率影响系数的不等式约束,提出了一个改进的多元马尔可夫链违约预测模型。本文的创新和特色:一是将专家对企业信用变化相关程度的判断与多元马尔可夫链模型重要参数确定结合起来,解决了多家企业信用状态变化过程中相关性不可观测且难准确度量的问题。二是利用信用转移影响系数反映不同企业对下一时期同一家企业信用状态形成的影响比重,改变了现有研究仅考虑了该参数满足归一性和非负性权重的数理含义、忽略其能差异化地反映不同企业信用影响程度的弊端,提高了模型的可解释性。本文运用改进后的马尔可夫链模型对中国上市金融业企业实施了违约预测。结果显示,改进模型预测表现均高于现有模型,且一家企业未来信用状态不仅与自身当前的信用分布有关,也受到专家认为的关系密切的其他企业信用变化的影响,反映了同行业企业信用状态变化过程中的不对称影响特征。An enterprise’s default behavior may not only cause its bankruptcy,but also lead to the financial distress of other enterprises,and even induce systemic risks.Due to the complex web of links between financial enterprises,such as an extensive use of mutual credit guarantee,large capital borrowing and complex cross-shareholding relations among themselves,financial stresses to one part of the group can spread to others,leading to a system-wide threat to financial stability.The global financial crisis that began in 2008 was triggered by the Lehman Brothers bankruptcy,which led to a comprehensive collapse of US financial system.In fact,non-financial enterprises may also withstand a financial default contagion.A specific instance is the knock-on effects of Evergrande Real Estate default behavior in 2021 that caused the deterioration of financial conditions of many real estate companies.The accurate estimation of default correlation between interested companies is quite important for the subsequent default risk measurement.However,it has always been challenging due to two main reasons.Firstly,the joint credit migration is less likely to be directly observed;and thus,the link needs to be inferred to observable correlations,such as equity returns,which may lead to inaccurate assessment of correlation.Secondly,the degree of mutual influence on default behavior from firm A to firm B and from firm B to A is different and lack of covariance-like symmetry,owing to the big difference among companies in terms of industry dominance and competitiveness.Under the existing framework of the multivariate Markov chain model,this paper utilizes a group decision-making method to adjust the key coefficients associated with the existing approach,proposing an improved multivariate Markov chain model for default prediction.The primary distinction between this model and existing multivariate Markov chain models lies in the estimation of the credit transition influence coefficients.The current study constructs a linear optimization model wit

关 键 词：多元马尔可夫链模型 信用变化相关性 群组决策 违约预测 上市企业 

分 类 号：F224[经济管理—国民经济]