{"id":"https://openalex.org/W2323521202","doi":"https://doi.org/10.1109/tkde.2016.2545660","title":"Stock Selection with a Novel Sigmoid-Based Mixed Discrete-Continuous Differential Evolution Algorithm","display_name":"Stock Selection with a Novel Sigmoid-Based Mixed Discrete-Continuous Differential Evolution Algorithm","publication_year":2016,"publication_date":"2016-03-23","ids":{"openalex":"https://openalex.org/W2323521202","doi":"https://doi.org/10.1109/tkde.2016.2545660","mag":"2323521202"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2016.2545660","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2016.2545660","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","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/A5058109866","display_name":"Lean Yu","orcid":"https://orcid.org/0000-0002-8035-4938"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lean Yu","raw_affiliation_strings":["School of Economics and Management, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103635769","display_name":"Lunchao Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210120485","display_name":"Academy of Mathematics and Systems Science","ror":"https://ror.org/02jkmyk67","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210120485"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lunchao Hu","raw_affiliation_strings":["Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210120485","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084708538","display_name":"Ling Tang","orcid":"https://orcid.org/0000-0002-2522-9675"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Tang","raw_affiliation_strings":["School of Economics and Management, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5058109866"],"corresponding_institution_ids":["https://openalex.org/I75390827"],"apc_list":null,"apc_paid":null,"fwci":5.157,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.9493453,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"28","issue":"7","first_page":"1891","last_page":"1904"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9983999729156494,"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":0.9983999729156494,"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":0.9980999827384949,"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":0.9959999918937683,"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/sigmoid-function","display_name":"Sigmoid function","score":0.7342140674591064},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6206651329994202},{"id":"https://openalex.org/keywords/differential-evolution","display_name":"Differential evolution","score":0.5974847078323364},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.5607466697692871},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5242564678192139},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4755932092666626},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.46560508012771606},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.44499388337135315},{"id":"https://openalex.org/keywords/continuous-modelling","display_name":"Continuous modelling","score":0.4406243860721588},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28543639183044434},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19095778465270996},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.155666321516037},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.13625425100326538}],"concepts":[{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.7342140674591064},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6206651329994202},{"id":"https://openalex.org/C74750220","wikidata":"https://www.wikidata.org/wiki/Q2662197","display_name":"Differential evolution","level":2,"score":0.5974847078323364},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.5607466697692871},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5242564678192139},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4755932092666626},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.46560508012771606},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.44499388337135315},{"id":"https://openalex.org/C10184394","wikidata":"https://www.wikidata.org/wiki/Q5165491","display_name":"Continuous modelling","level":2,"score":0.4406243860721588},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28543639183044434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19095778465270996},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.155666321516037},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.13625425100326538},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2016.2545660","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2016.2545660","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2115449191","display_name":null,"funder_award_id":"71301006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6960563880","display_name":null,"funder_award_id":"71025005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G798293579","display_name":null,"funder_award_id":"71433001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336125","display_name":"National Science Fund for Distinguished Young Scholars","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W30773325","https://openalex.org/W44449266","https://openalex.org/W137575789","https://openalex.org/W619088304","https://openalex.org/W1202823825","https://openalex.org/W1498895452","https://openalex.org/W1573340282","https://openalex.org/W1596914020","https://openalex.org/W1598223338","https://openalex.org/W1599836326","https://openalex.org/W1612277053","https://openalex.org/W1659842140","https://openalex.org/W1713078372","https://openalex.org/W1879678483","https://openalex.org/W1966573329","https://openalex.org/W1988078783","https://openalex.org/W1995808291","https://openalex.org/W1995834279","https://openalex.org/W2001709855","https://openalex.org/W2001823102","https://openalex.org/W2009957539","https://openalex.org/W2010681793","https://openalex.org/W2010824638","https://openalex.org/W2013704165","https://openalex.org/W2022679019","https://openalex.org/W2028915215","https://openalex.org/W2029056003","https://openalex.org/W2029846254","https://openalex.org/W2051408140","https://openalex.org/W2064568104","https://openalex.org/W2066795664","https://openalex.org/W2075363999","https://openalex.org/W2082468510","https://openalex.org/W2093119036","https://openalex.org/W2101381319","https://openalex.org/W2102831150","https://openalex.org/W2110940238","https://openalex.org/W2117420405","https://openalex.org/W2120176508","https://openalex.org/W2125213524","https://openalex.org/W2138810473","https://openalex.org/W2144006959","https://openalex.org/W2152195021","https://openalex.org/W2154258145","https://openalex.org/W2156194072","https://openalex.org/W2156758690","https://openalex.org/W2160548572","https://openalex.org/W2164657862","https://openalex.org/W2236966765","https://openalex.org/W2241752804","https://openalex.org/W2248644291","https://openalex.org/W2333436712","https://openalex.org/W2383883410","https://openalex.org/W2527156766","https://openalex.org/W2534269851","https://openalex.org/W2947067951","https://openalex.org/W2998216295","https://openalex.org/W3098834468","https://openalex.org/W3100535899","https://openalex.org/W4206316875","https://openalex.org/W4211105675","https://openalex.org/W4230661391","https://openalex.org/W4236670843","https://openalex.org/W4285719527","https://openalex.org/W6650727744","https://openalex.org/W6702929843","https://openalex.org/W6727906416","https://openalex.org/W7052783474","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W4385957115","https://openalex.org/W2061372042","https://openalex.org/W3047779762","https://openalex.org/W1520030019","https://openalex.org/W2071654592","https://openalex.org/W3104477175","https://openalex.org/W2088157920","https://openalex.org/W4283785902","https://openalex.org/W4313324256","https://openalex.org/W2019022049"],"abstract_inverted_index":{"A":[0,138],"stock":[1,32,118,133,154],"selection":[2,119,155],"model":[3,27,63,120,156,169,186],"with":[4],"both":[5,182],"discrete":[6,114],"and":[7,46,49,84,162,171,185],"continuous":[8,98],"decision":[9],"variables":[10],"is":[11,23,35,100],"proposed,":[12],"in":[13,77,175,179],"which":[14],"a":[15,31,103,159],"novel":[16,104,153],"sigmoid-based":[17,110],"mixed":[18,105],"discrete-continuous":[19,106],"differential":[20,92,129],"evolution":[21,93,130],"algorithm":[22,94,131],"especially":[24],"developed":[25],"for":[26,112],"optimization.":[28],"In":[29],"particular,":[30],"scoring":[33],"mechanism":[34],"first":[36],"designed":[37],"to":[38,55,72,102,132],"evaluate":[39],"candidate":[40],"stocks":[41,52],"based":[42,108],"on":[43,97,109],"their":[44],"fundamental":[45],"technical":[47],"features,":[48],"the":[50,61,74,85,90,113,117,123,126,136,144,147,152,176],"top-ranked":[51],"are":[53],"selected":[54],"formulate":[56],"an":[57],"equal-weighted":[58],"portfolio.":[59],"Generally,":[60],"proposed":[62],"makes":[64],"literature":[65],"contributions":[66],"from":[67],"two":[68],"main":[69],"perspectives.":[70],"First,":[71],"determine":[73],"optimal":[75],"solution":[76],"terms":[78,180],"of":[79,125,128,141,181],"feature":[80],"selections":[81],"(discrete":[82],"variables)":[83],"corresponding":[86],"weights":[87],"(continuous":[88],"variables),":[89],"original":[91],"focusing":[95],"only":[96],"problems":[99],"extended":[101],"variant":[107],"conversion":[111],"part.":[115],"Second,":[116],"also":[121],"resolves":[122],"gap":[124],"application":[127],"selection.":[134],"Using":[135],"Shanghai":[137],"share":[139],"market":[140],"China":[142],"as":[143],"study":[145],"sample,":[146],"empirical":[148],"results":[149],"show":[150],"that":[151],"can":[157],"make":[158],"profitable":[160],"portfolio":[161],"significantly":[163],"outperform":[164],"its":[165],"benchmarks":[166],"(with":[167],"other":[168],"designs":[170],"optimization":[172],"algorithms":[173],"used":[174],"existing":[177],"studies)":[178],"investment":[183],"return":[184],"robustness.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
