The extraction of trading rules from stock market data using rough sets

Cited 21 time in webofscience Cited 0 time in scopus
  • Hit : 916
  • Download : 230
DC FieldValueLanguage
dc.contributor.authorKim, KJko
dc.contributor.authorHan, Ingooko
dc.date.accessioned2008-04-07T08:59:50Z-
dc.date.available2008-04-07T08:59:50Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2001-09-
dc.identifier.citationEXPERT SYSTEMS, v.18, no.4, pp.194 - 202-
dc.identifier.issn0266-4720-
dc.identifier.urihttp://hdl.handle.net/10203/3696-
dc.description.abstractWe propose the rough set approach to the extraction of trading rules for discriminating between bullish and bearish patterns in the stock market. Rough set theory is quite valuable for extracting trading rules because it can be used to discover dependences in data while reducing the effect of superfluous factors in noisy data. In addition, it does not generate a signal to trade when the pattern of the market is uncertain because the selection of reducts and the extraction of rules are controlled by the strength of each reduct and rule. The experimental results are encouraging and show the usefulness of the rough set approach for stock market analysis with respect to profitability.-
dc.languageEnglish-
dc.language.isoenen
dc.publisherBLACKWELL PUBL LTD-
dc.subjectBUSINESS FAILURE PREDICTION-
dc.subjectNEURAL-NETWORK-
dc.subjectINDEX FUTURES-
dc.subjectCLASSIFICATION-
dc.subjectSYSTEM-
dc.subjectACQUISITION-
dc.titleThe extraction of trading rules from stock market data using rough sets-
dc.typeArticle-
dc.identifier.wosid000171297100004-
dc.identifier.scopusid2-s2.0-0010533951-
dc.type.rimsART-
dc.citation.volume18-
dc.citation.issue4-
dc.citation.beginningpage194-
dc.citation.endingpage202-
dc.citation.publicationnameEXPERT SYSTEMS-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorHan, Ingoo-
dc.contributor.nonIdAuthorKim, KJ-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorrough sets-
dc.subject.keywordAuthortrading rules-
dc.subject.keywordAuthorstock market timing-
dc.subject.keywordPlusBUSINESS FAILURE PREDICTION-
dc.subject.keywordPlusNEURAL-NETWORK-
dc.subject.keywordPlusINDEX FUTURES-
dc.subject.keywordPlusCLASSIFICATION-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordPlusACQUISITION-
Appears in Collection
MT-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 21 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0