Title :
The Financial Early-Warning Model of Listed Companies
Author_Institution :
Sch. of Manage. Sci. & Eng., Dongbei Univ. of Finance & Econ., Dalian, China
Abstract :
This paper use Microsoft SQL Server 2005 data mining tools and three methods of neural networks, decision trees and logistic regression to establish the financial crisis early-warning model of listed companies. The conclusion is that the three kinds of methods have good results and the prediction accuracy rate are 80% or more. The accuracy of the decision tree algorithm model is higher than others.
Keywords :
data mining; decision trees; financial management; neural nets; regression analysis; Microsoft SQL Server 2005 data mining tool; decision trees; financial crisis early-warning model; listed companies; logistic regression; neural network; prediction accuracy; Analytical models; Artificial neural networks; Biological system modeling; Companies; Data models; Predictive models; Profitability;
Conference_Titel :
Management and Service Science (MASS), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5325-2
Electronic_ISBN :
978-1-4244-5326-9
DOI :
10.1109/ICMSS.2010.5576555
