Title :
The Combination Forecasting Model for Financial Distress Prediction of Listed Corporations Based on Support Vector Machines
Author :
Sun, Wei ; Yan, Xingxing ; Li, Yanhong
Author_Institution :
Sch. of Bus. Adm., North China Electr. Power Univ., Baoding
Abstract :
This paper establish a new model of financial distress prediction---the combination forecasting model based on support vector machines (CFSVM), with Chinese listed corporations as samples. After rectifying the model, it gets higher predicting precision. Comparing to other warning models, the CFSVM model for listed corporations in financial distress prediction really has bigger application foreground because of its better characters such as higher accuracy rate.
Keywords :
financial management; forecasting theory; support vector machines; combination forecasting model; financial distress prediction; support vector machines; Computer science; Economic forecasting; Financial management; Investments; Logistics; Neural networks; Predictive models; Software engineering; Support vector machine classification; Support vector machines; BP; Logistic model; SVM; combination forecast;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.1002
