Title :
A Study of Corporate Financial Crisis Prediction System: Based on BP Artificial Neural Network
Author_Institution :
Sch. of Manage., Zhejiang Univ., Hangzhou
Abstract :
Financial crisis is fatal to all companies. So, it is very important to establish a financial crisis prediction system for each company to resolve latent problems before they emerge. However, artificial neural network (ANN) offers an approach to computation that is different from conventional analytic methods. In this text, we construct a BP neural network model to predict the financial crisis of companies with the samples from Shanghai stock exchange and Shenzhen stock exchange. And it is proved that the model is appropriate.
Keywords :
backpropagation; corporate modelling; financial management; neural nets; stock markets; BP artificial neural network; Shanghai stock exchange; Shenzhen stock exchange; corporate financial crisis prediction system; Artificial neural networks; Biological neural networks; Costs; Hopfield neural networks; Humans; Nervous system; Neural networks; Neurons; Recurrent neural networks; Stock markets;
Conference_Titel :
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3505-0
DOI :
10.1109/IITA.Workshops.2008.229