Title :
Credit assessment for listed companies based on GA-BP model
Author_Institution :
Sch. of Int. Finance, Nanjing Univ. of Inf. Sci.&Technol., Nanjing, China
Abstract :
This paper first constructed a financial index system for credit assessment of listed companies, then analyzed the defects of BP neural network model and found out it is easy to fall into the defect of local optical solution. By introducing the revised connection weight value of genetic algorithms, constructed GA-BP neural network model, and selected 80 companies listed from 2004 to 2007 as training samples, another 80 listed companies as test samples, to evaluate after screening indicators. The result shows high accuracy on assessment by using this model.
Keywords :
backpropagation; credit transactions; financial data processing; genetic algorithms; neural nets; GA-BP neural network model; backpropagation; credit assessment; financial index system; genetic algorithm; listed companies; Companies; Ecosystems; Electronic mail; Finance; Genetic algorithms; Information analysis; Information science; Neural networks; Profitability; Risk management; BP neural network; credit assessment; genetic algorithm; listed company;
Conference_Titel :
E-Health Networking, Digital Ecosystems and Technologies (EDT), 2010 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-5514-0
DOI :
10.1109/EDT.2010.5496521