Wavelet Neural Networks and Support Vector Machine for Financial Distress Prediction Modelling: The Chinese Case

Authors:
Hongshan Yao
Affiliations:
Zhongnan University of Economics and Law, Wuhan, China 430074
Venue:
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Year:
2009

Citing 3
Cited 0

Support Vector Machines

IEEE Intelligent Systems
Kernel Methods for Pattern Analysis

Kernel Methods for Pattern Analysis
Using wavelet network in nonparametric estimation

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.01

Visualization

Abstract

Wavelet neural networks (WNN) and support vector machine (SVM) are two advanced methods which are fit for classification. A comparative analysis of the two methods was conducted based on Chinese firms. The results show WNN has good classification effect. Wavelet decomposition has been demonstrated to be an effective tool for recognizing the firms' feature. Also the study applied SVM to the same estimation sample and test sample. The results show SVM is much superior to WNN for small sample learning.