A study of credit risk of Chinese listed companies: ZPP versus KMV. Issue 29 (20th June 2016)

• Record Type: Journal Article
• Authors: Li, Lili; Yang, Jun; Zou, Xin
• Is Part Of: Applied economics. Volume 48:Issue 29(2016)
• Page Start: 2697
• Page End: 2710
• Publication Date: 2016-06-20
• Subjects: Zero-price probability (ZPP) model -- credit risk -- Monte Carlo simulation -- expected default frequency; G30 -- G33; Economics -- Periodicals; 330
• DOI: 10.1080/00036846.2015.1128077
• Languages: English
• ISSNs: 0003-6846

Abstract

ABSTRACT: The Zero-Price Probability (ZPP) model is applied to evaluate the credit risk of listed companies in China and its performance is compared to that of the Kealhofer-McQuown-Vasicek (KMV) model. The sample includes 34 financially distressed companies and a comparison group of 34 financially healthy companies. The performances of ZPP and KMV models are compared using various descriptive statistics and statistical tests. The empirical analyses show that the ZPP model is superior to the KMV model in terms of discriminatory power. Compared to the KMV model, the ZPP model performs much better in distinguishing between financially challenged and healthy firms. Among different specifications of the ZPP model, the naïve constant variance zero-price probability model outperforms those with generalized autoregressive conditional heteroskedasticity specifications. This article is among the very first studies that provide evidence on the performance of the ZPP model.