The Empirical Studies of the Term Structure of Interest Rates Based on BP and RBF Neural Network

摘要：

The term structure of interest rates is a basic problem in financial field. Especially in the process of Chinese marketization of interest rates, research on the term structure of interest rates has very important theoretical and practical significance to the development and improvement of Chinese financial market. In this paper, we take advantage of faster learning speed, stronger capability of adaptability and numerical approximation of neural network characteristics to make the empirical analysis on the 14 group data selected from the Shanghai Security Exchange Market of Government Bonds traded on 12-Feb-2010 by means of BP and RBF neural network respectively. The results show that neural network has higher accuracy in predicting yields of government bonds, and calibration of parameters can affect the accuracy of network to some extent.

关键词： term structure of interest rates BP Neural Network RBF Neural Network parameter analysis

作者: Zhou Rongxi Niu Weining Ma Xin Zheng Qinghua

作者单位: School of Economics and Management, Beijing University of Chemical Technology, Beijing, 100029, China

会议类型: 国际会议

会议名称: 2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)

会议地点: 四川绵阳

会议语种:英文

页码: 3039-3042

在线出版日期: 2011-05-23（万方平台首次上网日期，不代表论文的发表时间）