Credit rating prediction with supply chain information: a machine learning perspective
Author:
Funder
Young Scientists Fund
Publisher
Springer Science and Business Media LLC
Subject
Management Science and Operations Research,General Decision Sciences
Link
https://link.springer.com/content/pdf/10.1007/s10479-023-05662-2.pdf
Reference93 articles.
1. Abellán, J., & Castellano, J. G. (2017). A comparative study on base classifiers in ensemble methods for credit scoring. Expert Systems with Applications, 73, 1–10.
2. Agca, S., Babich, V., Birge, J. R., & Wu, J. (2021). Credit shock propagation along supply chains: Evidence from the cds market. Management Science.
3. Agca, S., Babich, V., Birge, J. R., & Wu, J. (2022). Credit shock propagation along supply chains: Evidence from the CDS market. Management Science, 68(9), 6506–6538.
4. Ali, M., Alam, N., & Rizvi, S. A. R. (2020). Coronavirus (covid-19)—An epidemic or pandemic for financial markets. Journal of Behavioral and Experimental Finance, 27, 100341.
5. Alldredge, D. M., Chen, Y., Liu, S., & Luo, L. (2021). The effect of credit rating downgrades along the supply chain. Review of Accounting and Finance.
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