Dynamic Prediction of Corporate Financial Crisis Based on N-Step Ahead Kalman Filter-Reference-Cited by-同舟云学术

Dynamic Prediction of Corporate Financial Crisis Based on N-Step Ahead Kalman Filter

Published:2023-08-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 7th International Conference on Cloud and Big Data Computing
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Author:

Mao Zengli¹^ORCID,Wu Chong¹^ORCID

Affiliation:

1. School of Management, Harbin Institute of Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3616131.3616134

Reference15 articles.

1. Dynamic forecasting of financial distress: the hybrid use of incremental bagging and genetic algorithm—empirical study of Chinese listed corporations

2. Zhang C. , Zhong H.G. , Hu A.P. ( 2022 ) “ Research on Early Warning of Financial Crisis of Listed Companies Based on Random Forest and Time Series .” Mobile Information Systems , Vol. 2022 . Zhang C., Zhong H.G., Hu A.P. (2022) “Research on Early Warning of Financial Crisis of Listed Companies Based on Random Forest and Time Series.” Mobile Information Systems, Vol. 2022.

3. Du Qingyu ( 2021 ) “ Financial Crisis Early Warning Based on Panel Data and Dynamic Dual Choice Model .” Complexity , Vol. 2021 . Du Qingyu (2021) “Financial Crisis Early Warning Based on Panel Data and Dynamic Dual Choice Model.” Complexity, Vol. 2021.

4. Data mining method for listed companies’ financial distress prediction

5. Jan C. ( 2021 ) “ Financial Information Asymmetry: Using Deep Learning Algorithms to Predict Financial Distress .” Symmetry , Vol. 13 , No. 443. Jan C. (2021) “Financial Information Asymmetry: Using Deep Learning Algorithms to Predict Financial Distress.” Symmetry, Vol. 13, No. 443.