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: Qian Zhuang, Lianghua Chen
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2014/370280
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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.
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institution Kabale University
issn 1026-0226
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language English
publishDate 2014-01-01
publisher Wiley
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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