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Effect Of The Company Relationship Network On Default Prediction: Evidence From Chinese Listed Companies

Author

Listed:
  • GUOTAI CHI

    (School of Economics and Management, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian City 116024, P. R. China)

  • YING ZHOU

    (School of Economics and Management, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian City 116024, P. R. China)

  • LONG SHEN

    (School of Economics and Management, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian City 116024, P. R. China)

  • JIAN XIONG

    (School of Economics and Management, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian City 116024, P. R. China)

  • HONGJIA YAN

    (School of Economics and Management, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian City 116024, P. R. China)

Abstract

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 nondefault 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.

Suggested Citation

  • Guotai Chi & Ying Zhou & Long Shen & Jian Xiong & Hongjia Yan, 2022. "Effect Of The Company Relationship Network On Default Prediction: Evidence From Chinese Listed Companies," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 25(06), pages 1-22, September.
    • Handle: RePEc:wsi:ijtafx:v:25:y:2022:i:06:n:s021902492250025x
    DOI: 10.1142/S021902492250025X
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    Cited by:

    1. Wen Chen & Yufeng Zhu & Chenyu Wang, 2023. "Executives' overseas background and corporate green innovation," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(1), pages 165-179, January.

    More about this item

    Keywords

    Relationship network; indicator systems; default prediction; SVM; big data;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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