DocumentCode
2667688
Title
Comparison of the prediction effect between the Logistic Regressive model and SVM model
Author
Sijia, Li ; Lan, Tan ; Yu, Zhuang ; Xiuliang, Yu
Author_Institution
City Coll., Zhejiang Univ., Hangzhou, China
fYear
2010
fDate
17-19 Sept. 2010
Firstpage
316
Lastpage
318
Abstract
Financial crises forewarning has important practical significance both for the investors and for the lenders. This paper uses the financial forewarning models, including the Logistic Regressive model and SVM model, to verify the feasibility of the short-term forecast for the financial situation of enterprises. And the paper also gives comparisons between these two models. The results of the study suggest that these two models are both feasible, and the SVM model can achieve better forecasting effects than the Logistic Regressive model.
Keywords
economic cycles; forecasting theory; regression analysis; support vector machines; SVM model; financial crises; financial forewarning models; investors; logistic regressive model; prediction effect; short-term forecast; Biological system modeling; Companies; Estimation; Logistics; Predictive models; Support vector machines; Training; Credit Risk Management; Logistic Regressive Model; SVM (Supporting Vector Machine) Model; financial crisis forewarning; prediction effect;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-6927-7
Type
conf
DOI
10.1109/ICIFE.2010.5609308
Filename
5609308
Link To Document