Paper
Credit Risk Assessment Using Kalman Filtering
- Authors:
- Song Tao; Nie Li-ping
- Abstract
- The credit risk assessment is one of the most important topics in the field of financial risk management. In this paper the credit risk assessment model using Kalman filtering is tested for listed companies of china. The Kalman filtering model sets regression parameters based on the actual dynamic characteristics of the credit risk assessment. Firstly the parameters of the logistic regression are expressed as state space model form, then the parameters of the default model are estimated by Kalman filtering. Finally empirical results show that the Kalman filtering model has a very credible prediction and generalization ability.
- Keywords
- Credit risk assessment; Logistic regression; Kalman filtering; Maximum likelihood estimator
- StartPage
- 1
- EndPage
- 5
- Doi