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2010 Asia-Pacific Conference on Information Theory (APCIT 2010 E-BOOK)

Xi'an,China,10.1-10.2,2010

ISBN: 978-1-935068-47-1 Scientific Research Publishing, USA

E-Book 506pp Pub. Date: November 2010

Category: Computer Science & Communications

Price: $80

Title: Intelligent Classification System of Clients’ Risk for Futures Company
Source: 2010 Asia-Pacific Conference on Information Theory (APCIT 2010 E-BOOK) (pp 153-156)
Author(s): Zhongxing Ye, Department of Mathematics, Jiao Tong University, Shanghai 200240
Zhangyi He, Department of Mathematics, Jiao Tong University, Shanghai 200240
Xinlu Tang, Department of Mathematics, Jiao Tong University, Shanghai 200240
Abstract: The level of clients′ trading risk management directly influences the existence and develop- ment of a futures company. Therefore, to identify, classify and control clients′ credit risk seems crucially important for futures companies. At present, futures companies in China classify clients merely based on sales account managers′ experience and their subjective judgment. Therefore futures companies require a client classification and identification system (CCIS) based on clients′ historical transaction data immi- nently. In this paper, a CCIS is established on the basis of unsupervised cluster analysis. A sufficiently large number of clients and their historical transaction data are used from the database of the futures company. Three different clustering algorithms, such as Two Step algorithm, self organization mapping algorithm and CLIQUE algorithm are sued to cluster the data, and then Intersection-based Clustering Combination algorithm is applied to get kernels of different classes and the standard of classification. Finally, random sub-sampling and bootstrap methods are used to test the system.
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