Recognizing the Pattern of Beta Based Rough Set- Neural Network System
Beta is calculated by linear analysis between the closing prices of stocks and the security index of stock market.However,many studies have showed there are strong relationships between beta and financial information. Since the traditional statistical techniques have many limitations in disposing deficient and high noisy data, the past studies rested on proving the relationships between financial information and systematic risk. Recently, numerous studies have demonstrated that the hybrid system of rough sets and BP neural-networks has many advantages in disposing the problem of pattern recognizing, in which rough sets were used for accelerating or simplifying the process of using neural network by eliminating the redundant data from database. Therefore, this paper used the hybrid system to recognize the clusters of beta with financial information. At last the effectiveness of our approach was verified by testing the hybrid system with the companies which listed on Shenzhen stock market.
Bate Financial information Rough sets Neural-networks
ZHOU Jianguo WU Zhaoming REN Guoqiao HUN Fengwu
School of Business Administration North China Electric Power University Baoding 071003, China
国际会议
厦门
英文
829-832
2006-07-27（万方平台首次上网日期，不代表论文的发表时间）