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Proceedings of the 2nd International Symposium on Web Information Systems and Applications (WISA 2009)

Nanchang, China, May 22-24, 2009

Editors: Fei Yu, Jiexian Zeng, and Guangxue Yue

AP Catalog Number: AP-PROC-CS-09CN001

ISBN: 978-952-5726-00-8 (Print), 978-952-5726-01-5 (CD-ROM)

Page(s): 56-59

Choosing Credit Risk Index for Listed Companies Based on Grey Clustering Method

           Lei Hua, Zhigang Song, Ying Li

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Abstract

The credit standing of listed companies is a key index that investors usually place high importance on, and thus many methods are developed for analyzing it. However, no matter what method is used, we have to face the problem of choosing proper indexes before analyzing and forecasting. This article adopts grey clustering method for index selection, then uses neural network for forecasting, and finally it compares the forecasting effects, which show that the forecasting ability of neural network after using grey clustering improves noticeably.

Index Terms

credit, grey clustering, factor analysis, neural network

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