{"id":"https://openalex.org/W2077365830","doi":"https://doi.org/10.1007/s10489-006-0001-7","title":"Stock market prediction with multiple classifiers","display_name":"Stock market prediction with multiple classifiers","publication_year":2006,"publication_date":"2006-11-27","ids":{"openalex":"https://openalex.org/W2077365830","doi":"https://doi.org/10.1007/s10489-006-0001-7","mag":"2077365830"},"language":"en","primary_location":{"id":"doi:10.1007/s10489-006-0001-7","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10489-006-0001-7","pdf_url":null,"source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071419774","display_name":"Bo Qian","orcid":"https://orcid.org/0000-0002-6964-220X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bo Qian","raw_affiliation_strings":["Countrywide Financial Corporation, 4500 Park Granada, MS CH-21A, Calabasas, CA, 91302, USA","Countrywide Financial Corporation, Calabasas, USA 91302"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Countrywide Financial Corporation, 4500 Park Granada, MS CH-21A, Calabasas, CA, 91302, USA","institution_ids":[]},{"raw_affiliation_string":"Countrywide Financial Corporation, Calabasas, USA 91302","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035370466","display_name":"Khaled Rasheed","orcid":"https://orcid.org/0000-0003-4646-0937"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Khaled Rasheed","raw_affiliation_strings":["Department of Computer Science, The University of Georgia, Athens, GA, 30602, USA","Department of Computer Science, The University of Georgia, Athens, USA 30602"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Georgia, Athens, GA, 30602, USA","institution_ids":["https://openalex.org/I165733156"]},{"raw_affiliation_string":"Department of Computer Science, The University of Georgia, Athens, USA 30602","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5071419774"],"corresponding_institution_ids":[],"apc_list":{"value":3190,"currency":"USD","value_usd":3190},"apc_paid":null,"fwci":1.2355,"has_fulltext":false,"cited_by_count":237,"citation_normalized_percentile":{"value":0.81432658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"26","issue":"1","first_page":"25","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/predictability","display_name":"Predictability","score":0.8917630910873413},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8029581308364868},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.6212373375892639},{"id":"https://openalex.org/keywords/stock-market-prediction","display_name":"Stock market prediction","score":0.6146603226661682},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6109683513641357},{"id":"https://openalex.org/keywords/hurst-exponent","display_name":"Hurst exponent","score":0.5979328155517578},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.597030520439148},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5935073494911194},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.5673931241035461},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.516939103603363},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.507183313369751},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4901007115840912},{"id":"https://openalex.org/keywords/stock-market-index","display_name":"Stock market index","score":0.48254889249801636},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.4605606496334076},{"id":"https://openalex.org/keywords/sharpe-ratio","display_name":"Sharpe ratio","score":0.43738648295402527},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.41888612508773804},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36577609181404114},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3541754484176636},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.2291625440120697},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18688195943832397},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11155149340629578},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.07038980722427368}],"concepts":[{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.8917630910873413},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8029581308364868},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.6212373375892639},{"id":"https://openalex.org/C2776256503","wikidata":"https://www.wikidata.org/wiki/Q7617906","display_name":"Stock market prediction","level":4,"score":0.6146603226661682},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6109683513641357},{"id":"https://openalex.org/C96835011","wikidata":"https://www.wikidata.org/wiki/Q1638718","display_name":"Hurst exponent","level":2,"score":0.5979328155517578},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.597030520439148},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5935073494911194},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.5673931241035461},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.516939103603363},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.507183313369751},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4901007115840912},{"id":"https://openalex.org/C88389905","wikidata":"https://www.wikidata.org/wiki/Q223371","display_name":"Stock market index","level":4,"score":0.48254889249801636},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.4605606496334076},{"id":"https://openalex.org/C139938925","wikidata":"https://www.wikidata.org/wiki/Q1501898","display_name":"Sharpe ratio","level":3,"score":0.43738648295402527},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.41888612508773804},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36577609181404114},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3541754484176636},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.2291625440120697},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18688195943832397},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11155149340629578},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.07038980722427368},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"score":0.0},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10489-006-0001-7","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10489-006-0001-7","pdf_url":null,"source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W571815222","https://openalex.org/W602851501","https://openalex.org/W1495591997","https://openalex.org/W1496929357","https://openalex.org/W1508618229","https://openalex.org/W1534477342","https://openalex.org/W1553313034","https://openalex.org/W1581560129","https://openalex.org/W1587239851","https://openalex.org/W1594031697","https://openalex.org/W1598847143","https://openalex.org/W1645816215","https://openalex.org/W1782977420","https://openalex.org/W1825077972","https://openalex.org/W1997127946","https://openalex.org/W2010461070","https://openalex.org/W2026712034","https://openalex.org/W2031753087","https://openalex.org/W2036713496","https://openalex.org/W2046712495","https://openalex.org/W2057949709","https://openalex.org/W2078206416","https://openalex.org/W2090637028","https://openalex.org/W2110321237","https://openalex.org/W2112081648","https://openalex.org/W2116988722","https://openalex.org/W2117039450","https://openalex.org/W2134204705","https://openalex.org/W2135293965","https://openalex.org/W2135606128","https://openalex.org/W2137983211","https://openalex.org/W2147169507","https://openalex.org/W2155482699","https://openalex.org/W2160607725","https://openalex.org/W2302243455","https://openalex.org/W2313094413","https://openalex.org/W2341760625","https://openalex.org/W2490896275","https://openalex.org/W2800860906","https://openalex.org/W2912934387","https://openalex.org/W2914859268","https://openalex.org/W3085162807","https://openalex.org/W3100344990","https://openalex.org/W3122127754","https://openalex.org/W3122205006","https://openalex.org/W3146803896","https://openalex.org/W3151666377","https://openalex.org/W3151910759","https://openalex.org/W4231237509","https://openalex.org/W4240307802","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2360437128","https://openalex.org/W3121129682","https://openalex.org/W4280561011","https://openalex.org/W2058358182","https://openalex.org/W2122476482","https://openalex.org/W2776770276","https://openalex.org/W4205225885","https://openalex.org/W2963919538","https://openalex.org/W2217864342","https://openalex.org/W4311328018"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":27},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":14},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":3}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
