EFFECT OF THE COMPANY RELATIONSHIP NETWORK ON DEFAULT PREDICTION: EVIDENCE FROM CHINESE LISTED COMPANIES

被引：3

作者：

Chi, Guotai ^{[1
]}

Zhou, Ying ^{[1
]}

Shen, Long ^{[1
]}

Xiong, Jian ^{[1
]}

Yan, Hongjia ^{[1
]}

机构：

[1] Dalian Univ Technol, Sch Econ & Management, 2 Linggong Rd, Dalian 116024, Peoples R China

来源：

INTERNATIONAL JOURNAL OF THEORETICAL AND APPLIED FINANCE | 2022年 / 25卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Relationship network; indicator systems; default prediction; SVM; big data; FINANCIAL DISTRESS PREDICTION; BANKRUPTCY PREDICTION; MARKET BEHAVIOR; RATIOS; RISK; CLASSIFICATION; POLICIES; MACHINE;

D O I：

10.1142/S021902492250025X

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

The default risk of listed companies not only threatens the interests of enterprises and internal staff but also leads the investors to face significant financial losses. Thus, this study attempts to establish an effective default prediction system for better corporate governance. In present times, it is not uncommon for a senior manager to serve in two or more companies. Our contribution has threefold. First, we construct an indicator system of default prediction for Chinese listed companies by considering the company relationship score. Then, we reversely infer the optimal ratios of the default and non-default companies' degrees of influence on their related companies with the maximum area under the curve (AUC). Third, the empirical results show that the default prediction accuracy is improved by using our indicator system that includes the company relationship score.

引用

页数：22

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