Proceedings of the 8th International Conference on Financial Innovation and Economic Development (ICFIED 2023)

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Credit Default Prediction Based on Multivariate Regression

Authors
Yingzi Sun1, Lirui Yang2, Ruonan Zhao3, *
1University of Arizona, Tucson, USA
2Guangzhou Foreign Language School ISA Wenhua IB Programme, Guangzhou, China
3Pearl River College, Tianjin University of Finance and Economics, Tianjin, China
*Corresponding author. Email: 18404191@masu.edu.cn
Corresponding Author
Ruonan Zhao
Available Online 15 May 2023.
DOI
10.2991/978-94-6463-142-5_3How to use a DOI?
Keywords
Credit Default; risk; logistic regression
Abstract

Credit default is a wide-spread credit derivative instrument. As it becomes more and more popular, an appropriate supervision system has to be established. In this paper, a multiple factor regression models are constructed in order to investigate the feasibility for credit default prediction based on R program. Since risks are unavoidable, some measures should be taken to predict them in order to help the banks that sell credit default swaps to minimize their risks. According to the analysis, a model is successfully created. These results shed light on guiding further exploration focusing on credit default prediction.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 8th International Conference on Financial Innovation and Economic Development (ICFIED 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
15 May 2023
ISBN
10.2991/978-94-6463-142-5_3
ISSN
2352-5428
DOI
10.2991/978-94-6463-142-5_3How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yingzi Sun
AU  - Lirui Yang
AU  - Ruonan Zhao
PY  - 2023
DA  - 2023/05/15
TI  - Credit Default Prediction Based on Multivariate Regression
BT  - Proceedings of the 8th International Conference on Financial Innovation and Economic Development (ICFIED 2023)
PB  - Atlantis Press
SP  - 16
EP  - 23
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-142-5_3
DO  - 10.2991/978-94-6463-142-5_3
ID  - Sun2023
ER  -