Predicting Price of Target of Acquisitions Based on RBF Neural Network

摘要：

In order to predict price of candidates in acquisition,in this paper,we design a new model of price prediction of target based on radial basis function neural network. The model is trained by the financial data of acquisition market deals which were made in the past. The result of simulation and test indicates that average error of price prediction is percent 12. It is a suggestive reference of evaluating the feasibility of acquisitions. The result also advises more nonfanance index and training samples should be increased to improve the model.

关键词： acquisition radial basis function neural network predicting price of target

作者: Hongjiu Liu Weimin Ma Hongjiu Liu Yanrong Hu

作者单位: School of Economics and Management Tongji University Shanghai City,China Department of Management Engineering Changshu Institute of Technology,CIT Changshu City,China

会议类型: 国际会议

会议名称: The Third International Conference on Business Intelligence and Financial Engineering(第三届商务智能与金融工程国际会议 BIFE 2010)

会议地点: 香港

会议语种:英文

页码: 35-39

在线出版日期: 2010-08-17（万方平台首次上网日期，不代表论文的发表时间）