Computational Intelligence for Evolving Trading Rules
This paper describes an adaptive computational intelligence system for learning trading rules. The trading rules are represented using a fuzzy logic rule base, and using an artificial evolutionary process the system learns to form rules that can perform well in dynamic market conditions. A comprehen...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on evolutionary computation 2009-02, Vol.13 (1), p.71-86 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 86 |
|---|---|
| container_issue | 1 |
| container_start_page | 71 |
| container_title | IEEE transactions on evolutionary computation |
| container_volume | 13 |
| creator | Ghandar, A. Michalewicz, Z. Schmidt, M. Thuy-Duong To Zurbrugg, R. |
| description | This paper describes an adaptive computational intelligence system for learning trading rules. The trading rules are represented using a fuzzy logic rule base, and using an artificial evolutionary process the system learns to form rules that can perform well in dynamic market conditions. A comprehensive analysis of the results of applying the system for portfolio construction using portfolio evaluation tools widely accepted by both the financial industry and academia is provided. |
| doi_str_mv | 10.1109/TEVC.2008.915992 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_miscellaneous_34559968</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4769003</ieee_id><sourcerecordid>34559968</sourcerecordid><originalsourceid>FETCH-LOGICAL-c395t-fad2fec01a146f11ef3ca360d1888aa9eb4591f5db0289a0a78eba87c8487c723</originalsourceid><addsrcrecordid>eNp9kMFLwzAUh4MoOKd3wUvxoKfOl6RpkqOUqYOBIFO8haxNRkfXzKQd7L83peLBg5f33uF7j_f7ELrGMMMY5MNq_lHMCICYScykJCdogmWGUwCSn8YZhEw5F5_n6CKELQDOGJYTxAq32_ed7mrX6iZZtJ1pmnpj2tIk1vlkfnDNoW43ycrrauhvfWPCJTqzugnm6qdP0fvTfFW8pMvX50XxuExLKlmXWl0Ra0rAGme5xdhYWmqaQ4WFEFpLs86YxJZVayBCatBcmLUWvBRZLJzQKbof7-69--pN6NSuDmX8ULfG9UEJzoDQmCSSd_-SEYpWchHB2z_g1vU-Zo_XGM-IoBIiBCNUeheCN1btfb3T_qgwqEG3GnSrQbcadceVm3GlNsb84hnPJQCl39mreso</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>857428390</pqid></control><display><type>article</type><title>Computational Intelligence for Evolving Trading Rules</title><source>IEEE Electronic Library (IEL)</source><creator>Ghandar, A. ; Michalewicz, Z. ; Schmidt, M. ; Thuy-Duong To ; Zurbrugg, R.</creator><creatorcontrib>Ghandar, A. ; Michalewicz, Z. ; Schmidt, M. ; Thuy-Duong To ; Zurbrugg, R.</creatorcontrib><description>This paper describes an adaptive computational intelligence system for learning trading rules. The trading rules are represented using a fuzzy logic rule base, and using an artificial evolutionary process the system learns to form rules that can perform well in dynamic market conditions. A comprehensive analysis of the results of applying the system for portfolio construction using portfolio evaluation tools widely accepted by both the financial industry and academia is provided.</description><identifier>ISSN: 1089-778X</identifier><identifier>EISSN: 1941-0026</identifier><identifier>DOI: 10.1109/TEVC.2008.915992</identifier><identifier>CODEN: ITEVF5</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptive systems ; Asset management ; Australia ; Computation ; Computational intelligence ; Computer science ; Construction equipment ; Construction industry ; Dynamical systems ; Dynamics ; Evolutionary computation ; Fuzzy logic ; Fuzzy systems ; Intelligence ; Learning ; Markets ; portfolio management ; Portfolios ; stock market ; trading systems</subject><ispartof>IEEE transactions on evolutionary computation, 2009-02, Vol.13 (1), p.71-86</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2009</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c395t-fad2fec01a146f11ef3ca360d1888aa9eb4591f5db0289a0a78eba87c8487c723</citedby><cites>FETCH-LOGICAL-c395t-fad2fec01a146f11ef3ca360d1888aa9eb4591f5db0289a0a78eba87c8487c723</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4769003$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27922,27923,54756</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4769003$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ghandar, A.</creatorcontrib><creatorcontrib>Michalewicz, Z.</creatorcontrib><creatorcontrib>Schmidt, M.</creatorcontrib><creatorcontrib>Thuy-Duong To</creatorcontrib><creatorcontrib>Zurbrugg, R.</creatorcontrib><title>Computational Intelligence for Evolving Trading Rules</title><title>IEEE transactions on evolutionary computation</title><addtitle>TEVC</addtitle><description>This paper describes an adaptive computational intelligence system for learning trading rules. The trading rules are represented using a fuzzy logic rule base, and using an artificial evolutionary process the system learns to form rules that can perform well in dynamic market conditions. A comprehensive analysis of the results of applying the system for portfolio construction using portfolio evaluation tools widely accepted by both the financial industry and academia is provided.</description><subject>Adaptive systems</subject><subject>Asset management</subject><subject>Australia</subject><subject>Computation</subject><subject>Computational intelligence</subject><subject>Computer science</subject><subject>Construction equipment</subject><subject>Construction industry</subject><subject>Dynamical systems</subject><subject>Dynamics</subject><subject>Evolutionary computation</subject><subject>Fuzzy logic</subject><subject>Fuzzy systems</subject><subject>Intelligence</subject><subject>Learning</subject><subject>Markets</subject><subject>portfolio management</subject><subject>Portfolios</subject><subject>stock market</subject><subject>trading systems</subject><issn>1089-778X</issn><issn>1941-0026</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9kMFLwzAUh4MoOKd3wUvxoKfOl6RpkqOUqYOBIFO8haxNRkfXzKQd7L83peLBg5f33uF7j_f7ELrGMMMY5MNq_lHMCICYScykJCdogmWGUwCSn8YZhEw5F5_n6CKELQDOGJYTxAq32_ed7mrX6iZZtJ1pmnpj2tIk1vlkfnDNoW43ycrrauhvfWPCJTqzugnm6qdP0fvTfFW8pMvX50XxuExLKlmXWl0Ra0rAGme5xdhYWmqaQ4WFEFpLs86YxJZVayBCatBcmLUWvBRZLJzQKbof7-69--pN6NSuDmX8ULfG9UEJzoDQmCSSd_-SEYpWchHB2z_g1vU-Zo_XGM-IoBIiBCNUeheCN1btfb3T_qgwqEG3GnSrQbcadceVm3GlNsb84hnPJQCl39mreso</recordid><startdate>20090201</startdate><enddate>20090201</enddate><creator>Ghandar, A.</creator><creator>Michalewicz, Z.</creator><creator>Schmidt, M.</creator><creator>Thuy-Duong To</creator><creator>Zurbrugg, R.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20090201</creationdate><title>Computational Intelligence for Evolving Trading Rules</title><author>Ghandar, A. ; Michalewicz, Z. ; Schmidt, M. ; Thuy-Duong To ; Zurbrugg, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c395t-fad2fec01a146f11ef3ca360d1888aa9eb4591f5db0289a0a78eba87c8487c723</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Adaptive systems</topic><topic>Asset management</topic><topic>Australia</topic><topic>Computation</topic><topic>Computational intelligence</topic><topic>Computer science</topic><topic>Construction equipment</topic><topic>Construction industry</topic><topic>Dynamical systems</topic><topic>Dynamics</topic><topic>Evolutionary computation</topic><topic>Fuzzy logic</topic><topic>Fuzzy systems</topic><topic>Intelligence</topic><topic>Learning</topic><topic>Markets</topic><topic>portfolio management</topic><topic>Portfolios</topic><topic>stock market</topic><topic>trading systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ghandar, A.</creatorcontrib><creatorcontrib>Michalewicz, Z.</creatorcontrib><creatorcontrib>Schmidt, M.</creatorcontrib><creatorcontrib>Thuy-Duong To</creatorcontrib><creatorcontrib>Zurbrugg, R.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on evolutionary computation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ghandar, A.</au><au>Michalewicz, Z.</au><au>Schmidt, M.</au><au>Thuy-Duong To</au><au>Zurbrugg, R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Computational Intelligence for Evolving Trading Rules</atitle><jtitle>IEEE transactions on evolutionary computation</jtitle><stitle>TEVC</stitle><date>2009-02-01</date><risdate>2009</risdate><volume>13</volume><issue>1</issue><spage>71</spage><epage>86</epage><pages>71-86</pages><issn>1089-778X</issn><eissn>1941-0026</eissn><coden>ITEVF5</coden><abstract>This paper describes an adaptive computational intelligence system for learning trading rules. The trading rules are represented using a fuzzy logic rule base, and using an artificial evolutionary process the system learns to form rules that can perform well in dynamic market conditions. A comprehensive analysis of the results of applying the system for portfolio construction using portfolio evaluation tools widely accepted by both the financial industry and academia is provided.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TEVC.2008.915992</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1089-778X |
| ispartof | IEEE transactions on evolutionary computation, 2009-02, Vol.13 (1), p.71-86 |
| issn | 1089-778X 1941-0026 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_34559968 |
| source | IEEE Electronic Library (IEL) |
| subjects | Adaptive systems Asset management Australia Computation Computational intelligence Computer science Construction equipment Construction industry Dynamical systems Dynamics Evolutionary computation Fuzzy logic Fuzzy systems Intelligence Learning Markets portfolio management Portfolios stock market trading systems |
| title | Computational Intelligence for Evolving Trading Rules |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T14%3A08%3A14IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Computational%20Intelligence%20for%20Evolving%20Trading%20Rules&rft.jtitle=IEEE%20transactions%20on%20evolutionary%20computation&rft.au=Ghandar,%20A.&rft.date=2009-02-01&rft.volume=13&rft.issue=1&rft.spage=71&rft.epage=86&rft.pages=71-86&rft.issn=1089-778X&rft.eissn=1941-0026&rft.coden=ITEVF5&rft_id=info:doi/10.1109/TEVC.2008.915992&rft_dat=%3Cproquest_RIE%3E34559968%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=857428390&rft_id=info:pmid/&rft_ieee_id=4769003&rfr_iscdi=true |