Empirical Study on Stock Return of Shanghai through Arch with DQPSO Algorithm

摘要：

Due to the disadvantages of traditional estimating methods of ARCH model,we estimate the parameters in ARCH model accurately with a new enhanced quantum-behaved particle swarm optimization algorithm with diversity.Then the ARCH model for stock return is established empirically with algorithm and forecast of the return is given.

作者: Halqam Ablat Wenbo Xu

作者单位: School of Mathematics and Information Technology,Xinjiang Education Institute Urumqi,Xinjiang,China School of Information Technology Southern Yangze University,Wuxi,jiangsu,China

会议类型: 国际会议

会议名称: 2008年国际电子商务、工程及科学领域的分布式计算和应用学术研讨会(2008 International Symposium on Distributed Computing and Applications for Business Engineering and Science)

会议地点: 大连

会议语种:英文

页码: 324-329

在线出版日期: 2008-07-27（万方平台首次上网日期，不代表论文的发表时间）