完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Cheng, TW | en_US |
dc.contributor.author | Tsai, WC | en_US |
dc.contributor.author | Chen, AP | en_US |
dc.date.accessioned | 2014-12-08T15:25:54Z | - |
dc.date.available | 2014-12-08T15:25:54Z | - |
dc.date.issued | 2004 | en_US |
dc.identifier.isbn | 0-7803-8278-1 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/18355 | - |
dc.description.abstract | Nowadays 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.iso | en_US | en_US |
dc.subject | extended classifier system | en_US |
dc.subject | futures exchange | en_US |
dc.subject | futures extended classifier trading mechanism | en_US |
dc.subject | futures investment | en_US |
dc.title | Strategy of futures trading mechanism using extended classifier system | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | 2004 2ND INTERNATIONAL IEEE CONFERENCE INTELLIGENT SYSTEMS, VOLS 1 AND 2, PROCEEDINGS | en_US |
dc.citation.spage | 503 | en_US |
dc.citation.epage | 507 | en_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.department | Department of Information Management and Finance | en_US |
dc.identifier.wosnumber | WOS:000223848200089 | - |
顯示於類別: | 會議論文 |