NDLI: Research in financial risk prediction on biochemical industry of China listed companies

Content Provider	IEEE Xplore Digital Library
Author	Li Qi-zhi Shi Wen-chao
Copyright Year	2012
Description	Author affiliation: School of Business Administration, University of Science and Technology Liaoning, China, 114051 (Li Qi-zhi; Shi Wen-chao)
Abstract	Since the Shanghai and Shenzhen stock exchange established for thirty years, our capital market has been booming and provides strong support to the listed company. However, because of the competition environment of market economy becoming more and more fiercely, more and more listed companies are faced with serious financial risk. This situation not only affects the normal development of the capital market, also give all the stakeholder, such as investors, creditors, etc, brought huge economic losses. The listed companies referred to biochemical industry are classified, and fifteen typical financial indexes are selected in this paper. The factor analysis is applied to analysis of sample in this paper firstly, and then scores of five principal components are calculated .In the end, factor scores are analyzed by method of logistic regression. Model of logistic regression is constructed to analyze financial crisis predication. The precision of this model is about seventy four point three percentage, which shows that this model could be used to analyze financial crisis of this industry.
Starting Page	1517
Ending Page	1521
File Size	283781
Page Count	5
File Format	PDF
ISBN	9781467330152
ISSN	21551855
e-ISBN	9781467330145
DOI	10.1109/ICMSE.2012.6414374
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Industries Analytical models biochemical industry Companies Predictive models Indexes logistic regression financial crisis prediction principal component analysis Logistics
Content Type	Text
Resource Type	Article

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