Dynamic Prediction of Financial Distress Based on Kalman Filtering
The widely used discriminant models currently for financial distress prediction have deficiencies in dynamics. Based on the dynamic nature of corporate financial distress, dynamic prediction models consisting of a process model and a discriminant model, which are used to describe the dynamic process...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2014/370280 |
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| _version_ | 1849396865142882304 |
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| author | Qian Zhuang Lianghua Chen |
| author_facet | Qian Zhuang Lianghua Chen |
| author_sort | Qian Zhuang |
| collection | DOAJ |
| description | The widely used discriminant models currently for financial distress prediction have deficiencies in dynamics. Based on the dynamic nature of corporate financial distress, dynamic prediction models consisting of a process model and a discriminant model, which are used to describe the dynamic process and discriminant rules of financial distress, respectively, is established. The operation of the dynamic prediction is achieved by Kalman filtering algorithm. And a general n-step-ahead prediction algorithm based on Kalman filtering is deduced in order for prospective prediction. An empirical study for China’s manufacturing industry has been conducted and the results have proved the accuracy and advance of predicting financial distress in such case. |
| format | Article |
| id | doaj-art-abfdd392350d403ca07c7a54b0130d25 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-abfdd392350d403ca07c7a54b0130d252025-08-20T03:39:13ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2014-01-01201410.1155/2014/370280370280Dynamic Prediction of Financial Distress Based on Kalman FilteringQian Zhuang0Lianghua Chen1School of Economics and Management, Southeast University, Nanjing, Jiangsu 211189, ChinaSchool of Economics and Management, Southeast University, Nanjing, Jiangsu 211189, ChinaThe widely used discriminant models currently for financial distress prediction have deficiencies in dynamics. Based on the dynamic nature of corporate financial distress, dynamic prediction models consisting of a process model and a discriminant model, which are used to describe the dynamic process and discriminant rules of financial distress, respectively, is established. The operation of the dynamic prediction is achieved by Kalman filtering algorithm. And a general n-step-ahead prediction algorithm based on Kalman filtering is deduced in order for prospective prediction. An empirical study for China’s manufacturing industry has been conducted and the results have proved the accuracy and advance of predicting financial distress in such case.http://dx.doi.org/10.1155/2014/370280 |
| spellingShingle | Qian Zhuang Lianghua Chen Dynamic Prediction of Financial Distress Based on Kalman Filtering Discrete Dynamics in Nature and Society |
| title | Dynamic Prediction of Financial Distress Based on Kalman Filtering |
| title_full | Dynamic Prediction of Financial Distress Based on Kalman Filtering |
| title_fullStr | Dynamic Prediction of Financial Distress Based on Kalman Filtering |
| title_full_unstemmed | Dynamic Prediction of Financial Distress Based on Kalman Filtering |
| title_short | Dynamic Prediction of Financial Distress Based on Kalman Filtering |
| title_sort | dynamic prediction of financial distress based on kalman filtering |
| url | http://dx.doi.org/10.1155/2014/370280 |
| work_keys_str_mv | AT qianzhuang dynamicpredictionoffinancialdistressbasedonkalmanfiltering AT lianghuachen dynamicpredictionoffinancialdistressbasedonkalmanfiltering |