信用债违约:潜在水平与时空分布  

Credit Debt Default:Potential Level and the Distribution of Time and Space

作　　者：郭琪[1] 郑蕾[1] 代斌[2] Guo Qi;Zheng Lei;Dai Bin(PBC Jinan Branch,Shandong Jinan 250021;PBC Dezhou Sub-branch,Shandong Dezhou 253012)

机构地区：[1]中国人民银行济南分行,山东济南250021 [2]中国人民银行德州市中心支行,山东德州253012

出　　处：《金融发展研究》2019年第8期26-33,共8页Journal Of Financial Development Research

摘　　要：2018年债券市场风险案件频发,违约触发机制与以往有所不同,体现为由外部现金流收缩而非内部现金流恶化引发。从中债国债指数和经济数据的周期叠加看,流动性风险是当前信用债违约风险的集中表现。通过Fisher判别得出流动资产周转率、速动比率、总资产周转率、现金债务比和总资产报酬率等5个指标是影响信用债风险的核心指标,并由此筛选出当前信用债市场532家潜在风险企业。基于KMV模型对潜在风险企业违约距离及违约概率进行测算,存在3个高风险区间,进一步筛选出136家高风险企业。这些企业从行业看集中于制造业及批发零售业,从地域分布看集中于东部省份,从企业性质看集中于民企及地方国有企业,风险引爆时间集中于2018年四季度及2019年。Bond market risks were frequent in 2018 and the trigger mechanism was different from the past,which was caused by the contraction of external cash flow rather than the deterioration of internal cash flow.From the periodic superposition of Government Bond Index and economic data,liquidity risk is the concentrated performance of current credit bond default risk.Five core indicators including current asset turnover rate,quick ratio,total asset turnover ra- tio,cash debt ratio and return on total assets are those which can affect the credit debt risk by Fisher.Thus,532 enter- prises with potential risk in the current credit bond market are screened out.Based on the KMV model, the default dis- tance and default probability of potentially risky enterprises were calculated,and there were 3 high-risk intervals and we further filtrated 136 high-risk ones.From the perspective of industry,these enterprises are mainly manufacturing and wholesale and retail industries;from the perspective of geographical distribution,they concentrate in east China;from the perspective of enterprise nature,they concentrate in private enterprises and local state-owned enterprises.And the risk initiation fastens in the fourth quarter of 2018 and 2019.

关 键 词：信用债 违约KMV 风险识别 

分 类 号：F830[经济管理—金融学]