DocumentCode
2654042
Title
Financial Distress Prediction Models of China´s Listed Companies
Author
Guo-ming, Qian ; Yuan, Feng ; Ling, Zhou
Author_Institution
Harbin Inst. of Technol., Harbin
fYear
2007
fDate
20-22 Aug. 2007
Firstpage
1824
Lastpage
1829
Abstract
Research of financial distress prediction models has just started in China, and there are some differences between the study abroad and that in China both from the methods and the perspective of research, which are mainly due to the difference of the degree of maturity of the capital market and the imperfections of research methods. Using listed manufacturing industry as its research object and whether the listed company has been special transaction because "the financial conditions are unusual" as a sign of financial distress, this paper adopts the canonical discriminant analysis method of the multivariate discriminant analysis, applies several variables which can cover every aspect of a listed company\´s financial position, utilize the financial data from the audited financial statements and search the variables and prediction models that can predict the financial distress of listed companies as accurately as possible.
Keywords
financial management; investment; manufacturing industries; statistical analysis; China listed companies; audited financial statements; canonical discriminant analysis; capital market; financial distress prediction models; listed manufacturing industry; multivariate discriminant analysis; Artificial neural networks; Conference management; Engineering management; Financial management; Forward contracts; Information technology; Logistics; Predictive models; Regression analysis; Technology management; financial distress; listed company; prediction models; the multivariate discriminant analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Management Science and Engineering, 2007. ICMSE 2007. International Conference on
Conference_Location
Harbin
Print_ISBN
978-7-88358-080-5
Electronic_ISBN
978-7-88358-080-5
Type
conf
DOI
10.1109/ICMSE.2007.4422105
Filename
4422105
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