{"id":"https://openalex.org/W1982700162","doi":"https://doi.org/10.1145/1961189.1961192","title":"A learning-based contrarian trading strategy via a dual-classifier model","display_name":"A learning-based contrarian trading strategy via a dual-classifier model","publication_year":2011,"publication_date":"2011-04-01","ids":{"openalex":"https://openalex.org/W1982700162","doi":"https://doi.org/10.1145/1961189.1961192","mag":"1982700162"},"language":"en","primary_location":{"id":"doi:10.1145/1961189.1961192","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1961189.1961192","pdf_url":null,"source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","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/A5074539320","display_name":"Szu-Hao Huang","orcid":"https://orcid.org/0000-0002-4073-0652"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Szu-Hao Huang","raw_affiliation_strings":["National Tsing Hua University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073849580","display_name":"Shang\u2010Hong Lai","orcid":"https://orcid.org/0000-0002-5092-993X"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shang-Hong Lai","raw_affiliation_strings":["National Tsing Hua University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111485481","display_name":"Shih-Hsien Tai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210129488","display_name":"Cathay General Hospital","ror":"https://ror.org/03c8c9n80","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I4210129488"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shih-Hsien Tai","raw_affiliation_strings":["Cathay United Bank, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cathay United Bank, Taipei, Taiwan","institution_ids":["https://openalex.org/I4210129488"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8467,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.79219226,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2","issue":"3","first_page":"1","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998000264167786,"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/T11059","display_name":"Market Dynamics and Volatility","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7708100080490112},{"id":"https://openalex.org/keywords/contrarian","display_name":"Contrarian","score":0.759498119354248},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.666742205619812},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6030706167221069},{"id":"https://openalex.org/keywords/trading-strategy","display_name":"Trading strategy","score":0.5174096822738647},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.4837512969970703},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4712434411048889},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.45325523614883423},{"id":"https://openalex.org/keywords/algorithmic-trading","display_name":"Algorithmic trading","score":0.42119908332824707},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.41451552510261536},{"id":"https://openalex.org/keywords/financial-market","display_name":"Financial market","score":0.4101717472076416},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.30971652269363403},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.1627790331840515},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.1499905288219452}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7708100080490112},{"id":"https://openalex.org/C2779652781","wikidata":"https://www.wikidata.org/wiki/Q5165738","display_name":"Contrarian","level":2,"score":0.759498119354248},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.666742205619812},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6030706167221069},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.5174096822738647},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.4837512969970703},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4712434411048889},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.45325523614883423},{"id":"https://openalex.org/C78508483","wikidata":"https://www.wikidata.org/wiki/Q139445","display_name":"Algorithmic trading","level":2,"score":0.42119908332824707},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.41451552510261536},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.4101717472076416},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.30971652269363403},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.1627790331840515},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.1499905288219452},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1961189.1961192","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1961189.1961192","pdf_url":null,"source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W35721360","https://openalex.org/W1589922412","https://openalex.org/W1608462934","https://openalex.org/W1981439605","https://openalex.org/W1988790447","https://openalex.org/W1992825118","https://openalex.org/W1994496890","https://openalex.org/W2023826935","https://openalex.org/W2032730137","https://openalex.org/W2068878359","https://openalex.org/W2081649978","https://openalex.org/W2097583462","https://openalex.org/W2100526182","https://openalex.org/W2103359683","https://openalex.org/W2106798814","https://openalex.org/W2111204393","https://openalex.org/W2112880279","https://openalex.org/W2112884743","https://openalex.org/W2113305199","https://openalex.org/W2118067958","https://openalex.org/W2119821739","https://openalex.org/W2125520394","https://openalex.org/W2128846462","https://openalex.org/W2131773668","https://openalex.org/W2133469585","https://openalex.org/W2137822226","https://openalex.org/W2144487825","https://openalex.org/W2148999633","https://openalex.org/W2153635508","https://openalex.org/W2161877343","https://openalex.org/W2164598857","https://openalex.org/W2166215547","https://openalex.org/W2170857480","https://openalex.org/W2171140863","https://openalex.org/W2172073485","https://openalex.org/W2506419783","https://openalex.org/W2606362422","https://openalex.org/W3011865677","https://openalex.org/W3121465794","https://openalex.org/W3122961947","https://openalex.org/W3123921709","https://openalex.org/W4231546411","https://openalex.org/W4236965008","https://openalex.org/W4246390368","https://openalex.org/W4301409532","https://openalex.org/W6601488608","https://openalex.org/W6738852829","https://openalex.org/W7048964705"],"related_works":["https://openalex.org/W2205156420","https://openalex.org/W3122015922","https://openalex.org/W2800391519","https://openalex.org/W2023826935","https://openalex.org/W2021295431","https://openalex.org/W4313491999","https://openalex.org/W2178783770","https://openalex.org/W3195402399","https://openalex.org/W3009410046","https://openalex.org/W97930096"],"abstract_inverted_index":{"Behavioral":[0],"finance":[1,104],"is":[2,84,98],"a":[3,92,111,157],"relatively":[4],"new":[5],"and":[6,14,23,41,60,69,94,105,145,174],"developing":[7],"research":[8],"field":[9,33],"which":[10,97],"adopts":[11],"cognitive":[12],"psychology":[13],"emotional":[15],"bias":[16],"to":[17,36,64,85,115,151,194,208,230],"explain":[18],"the":[19,29,38,52,67,71,75,87,120,130,166,177,182,187,211,224,236,241],"inefficient":[20],"market":[21],"phenomenon":[22],"some":[24],"irrational":[25],"trading":[26,77,126,214,233],"decisions.":[27],"Unlike":[28],"experts":[30],"in":[31,45,156,235],"this":[32,82],"who":[34],"tried":[35],"reason":[37],"price":[39],"anomaly":[40],"applied":[42],"empirical":[43],"evidence":[44],"many":[46],"different":[47,135,171],"financial":[48,88,159],"markets,":[49],"we":[50,164],"employ":[51],"advanced":[53],"binary":[54],"classification":[55],"algorithms,":[56],"such":[57,185],"as":[58,186],"AdaBoost":[59],"support":[61],"vector":[62],"machines,":[63],"precisely":[65],"model":[66,96],"overreaction":[68],"strengthen":[70],"portfolio":[72,202],"compositions":[73],"of":[74,81,103,123,240,245],"contrarian":[76,125,213],"strategies.":[78],"The":[79,196],"novelty":[80],"article":[83],"discover":[86],"time-series":[89,160],"patterns":[90],"through":[91],"high-dimensional":[93],"nonlinear":[95],"constructed":[99],"by":[100],"integrated":[101],"knowledge":[102],"machine":[106],"learning":[107,113,132,154,172],"techniques.":[108],"We":[109],"propose":[110],"dual-classifier":[112],"framework":[114],"select":[116],"candidate":[117],"stocks":[118],"from":[119,192,206],"past":[121],"results":[122],"original":[124,212],"strategies":[127],"based":[128],"on":[129],"defined":[131],"targets.":[133],"Three":[134],"feature":[136,161],"extraction":[137],"methods,":[138],"including":[139],"wavelet":[140],"transformation,":[141],"historical":[142,237],"return":[143,189],"distribution,":[144],"various":[146],"technical":[147],"indicators,":[148],"are":[149],"employed":[150],"represent":[152],"these":[153,220],"samples":[155],"381-dimensional":[158],"space.":[162],"Finally,":[163],"construct":[165],"classifier":[167],"models":[168],"with":[169],"four":[170],"kernels":[173],"prove":[175],"that":[176,190,223],"proposed":[178,225],"methods":[179],"could":[180,227],"improve":[181],"returns":[183],"dramatically,":[184],"3-year":[188],"improved":[191,205],"26.79%":[193],"53.75%.":[195],"experiments":[197,221],"also":[198],"demonstrate":[199],"significantly":[200],"higher":[201],"selection":[203],"accuracy,":[204],"57.47%":[207],"66.41%,":[209],"than":[210],"strategy.":[215],"To":[216],"sum":[217],"up,":[218],"all":[219],"show":[222],"method":[226],"be":[228],"extended":[229],"an":[231],"effective":[232],"system":[234],"stock":[238],"prices":[239],"leading":[242],"U.S.":[243],"companies":[244],"S&P":[246],"100":[247],"index.":[248]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}