完整後設資料紀錄
DC 欄位語言
dc.contributor.authorCheng, TWen_US
dc.contributor.authorTsai, WCen_US
dc.contributor.authorChen, APen_US
dc.date.accessioned2014-12-08T15:25:54Z-
dc.date.available2014-12-08T15:25:54Z-
dc.date.issued2004en_US
dc.identifier.isbn0-7803-8278-1en_US
dc.identifier.urihttp://hdl.handle.net/11536/18355-
dc.description.abstractNowadays many artificial intelligent trading models divided the process in three separate subprocesses: trading, validation and application, but these models cannot meet the request of today's trading environment. A new online learning algorithm, extended classifier system (XCS) is used in futures extended classifier trading mechanism (FXCTM) to satisfy traders' requirement. This paper verifies that FXCTM provides a very good forecast ability in futures market trading performance. Also, this paper discusses about how the population set of XCS affects the result of the model. Finally, the simulation results show that this model could get an obvious profit from futures market.en_US
dc.language.isoen_USen_US
dc.subjectextended classifier systemen_US
dc.subjectfutures exchangeen_US
dc.subjectfutures extended classifier trading mechanismen_US
dc.subjectfutures investmenten_US
dc.titleStrategy of futures trading mechanism using extended classifier systemen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2004 2ND INTERNATIONAL IEEE CONFERENCE INTELLIGENT SYSTEMS, VOLS 1 AND 2, PROCEEDINGSen_US
dc.citation.spage503en_US
dc.citation.epage507en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000223848200089-
顯示於類別:會議論文