{"id":"https://openalex.org/W4390224352","doi":"https://doi.org/10.1109/access.2023.3347608","title":"Diversified Adaptive Stock Selection Using Continual Graph Learning and Ensemble Approach","display_name":"Diversified Adaptive Stock Selection Using Continual Graph Learning and Ensemble Approach","publication_year":2023,"publication_date":"2023-12-26","ids":{"openalex":"https://openalex.org/W4390224352","doi":"https://doi.org/10.1109/access.2023.3347608"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3347608","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3347608","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10374320.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10374320.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102899682","display_name":"Jae\u2010Seung Kim","orcid":"https://orcid.org/0000-0003-3052-6444"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jae-Seung Kim","raw_affiliation_strings":["School of Computer and Information Engineering, Kwangwoon University, Nowon-gu, Republic of Korea","School of Computer and Information Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Kwangwoon University, Nowon-gu, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]},{"raw_affiliation_string":"School of Computer and Information Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sang-Ho Kim","orcid":"https://orcid.org/0000-0001-8424-0754"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang-Ho Kim","raw_affiliation_strings":["School of Computer and Information Engineering, Kwangwoon University, Nowon-gu, Republic of Korea","School of Computer and Information Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0001-8424-0754","affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Kwangwoon University, Nowon-gu, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]},{"raw_affiliation_string":"School of Computer and Information Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091742813","display_name":"Kihoon Lee","orcid":"https://orcid.org/0000-0003-4661-0982"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ki-Hoon Lee","raw_affiliation_strings":["School of Computer and Information Engineering, Kwangwoon University, Nowon-gu, Republic of Korea","School of Computer and Information Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-4661-0982","affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Kwangwoon University, Nowon-gu, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]},{"raw_affiliation_string":"School of Computer and Information Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102899682"],"corresponding_institution_ids":["https://openalex.org/I161024014"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.8425,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7956516,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"1039","last_page":"1050"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994000196456909,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.668425977230072},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5191994905471802},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.47590431571006775},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44418850541114807},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42842045426368713},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.4173222780227661},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.41304540634155273},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40069395303726196},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3352569341659546},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.33376169204711914},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2502988278865814},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1373128890991211},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.1030350923538208},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.09514108300209045},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08931395411491394}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.668425977230072},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5191994905471802},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.47590431571006775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44418850541114807},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42842045426368713},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.4173222780227661},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.41304540634155273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40069395303726196},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3352569341659546},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.33376169204711914},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2502988278865814},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1373128890991211},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.1030350923538208},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.09514108300209045},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08931395411491394},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3347608","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3347608","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10374320.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4b190ccf8cfd4fe4b7883d33e175d399","is_oa":true,"landing_page_url":"https://doaj.org/article/4b190ccf8cfd4fe4b7883d33e175d399","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 1039-1050 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3347608","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3347608","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10374320.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1283058587","display_name":null,"funder_award_id":"NRF-2022R1F1A1062787","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G6708692081","display_name":null,"funder_award_id":"in 2022","funder_id":"https://openalex.org/F4320321374","funder_display_name":"Kwangwoon University"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321374","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390224352.pdf","grobid_xml":"https://content.openalex.org/works/W4390224352.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W746481651","https://openalex.org/W1522301498","https://openalex.org/W1844261860","https://openalex.org/W1924770834","https://openalex.org/W2008348094","https://openalex.org/W2088252378","https://openalex.org/W2115839797","https://openalex.org/W2116341502","https://openalex.org/W2153580489","https://openalex.org/W2560647685","https://openalex.org/W2592424858","https://openalex.org/W2771333147","https://openalex.org/W2893230400","https://openalex.org/W2898017895","https://openalex.org/W2904929551","https://openalex.org/W2964015378","https://openalex.org/W2969677753","https://openalex.org/W3085990079","https://openalex.org/W3087775916","https://openalex.org/W3098366174","https://openalex.org/W3100777112","https://openalex.org/W3123329971","https://openalex.org/W3160222876","https://openalex.org/W3170261818","https://openalex.org/W3175177406","https://openalex.org/W3179886952","https://openalex.org/W3211452587","https://openalex.org/W4200563083","https://openalex.org/W4206553113","https://openalex.org/W4224996103","https://openalex.org/W4229034430","https://openalex.org/W4244655201","https://openalex.org/W4281645686","https://openalex.org/W4292696884","https://openalex.org/W4295021554","https://openalex.org/W4300511110","https://openalex.org/W4312532098","https://openalex.org/W4320036691","https://openalex.org/W4321485380","https://openalex.org/W4353115071","https://openalex.org/W4361806599","https://openalex.org/W4365420821","https://openalex.org/W4378506766","https://openalex.org/W4378649784","https://openalex.org/W4383751754","https://openalex.org/W4407831847","https://openalex.org/W6631190155","https://openalex.org/W6639024717","https://openalex.org/W6640212811","https://openalex.org/W6704825425","https://openalex.org/W6726873649","https://openalex.org/W6739901393","https://openalex.org/W6745537798","https://openalex.org/W6767528804","https://openalex.org/W6784237645"],"related_works":["https://openalex.org/W2291973775","https://openalex.org/W3201861680","https://openalex.org/W2044090075","https://openalex.org/W2996452312","https://openalex.org/W2172176281","https://openalex.org/W2768197547","https://openalex.org/W2326995271","https://openalex.org/W4286620652","https://openalex.org/W2000491696","https://openalex.org/W2370669686"],"abstract_inverted_index":{"Stock":[0],"selection":[1,15,58,126,225],"is":[2,16,43,218],"essential":[3],"for":[4,136,229],"portfolio":[5],"diversification":[6],"to":[7,19,65,93,104,115,146],"reduce":[8],"risks":[9],"and":[10,118,133,150,182,201,211],"maximize":[11],"profits.":[12],"However,":[13],"stock":[14,24,28,57,125,209,224],"difficult":[17],"owing":[18],"the":[20,48,67,192,233,251],"non-stationary":[21],"nature":[22],"of":[23,37,51,82,170,208,216,222,248],"markets.":[25],"In":[26],"fact,":[27],"markets":[29],"experience":[30],"abrupt":[31,94,117],"or":[32],"gradual":[33,105,119],"concept":[34,95,106,120],"drift":[35,42,107],"because":[36,108],"their":[38],"inherent":[39],"volatility.":[40],"Concept":[41],"a":[44,79,124,243],"phenomenon":[45],"in":[46,232],"which":[47,130,166,176,187],"statistical":[49],"characteristics":[50],"data":[52],"change":[53],"over":[54],"time.":[55],"Recent":[56],"methods":[59,73,90,101],"have":[60],"adopted":[61],"graph":[62,88,99,144,154],"neural":[63],"networks":[64],"capture":[66],"relational":[68,151,174,178,194],"dependencies":[69,169,179,190],"between":[70,180],"stocks.":[71],"These":[72],"perform":[74],"non-continual":[75,132],"learning":[76,145,155],"that":[77,221,240],"uses":[78],"fixed":[80],"set":[81],"stocks":[83,230],"without":[84],"knowledge":[85,111],"retention.":[86,112],"Non-continual":[87],"learning-based":[89,100],"can":[91,102],"adapt":[92,103,114],"drift,":[96],"while":[97],"continual":[98,134],"they":[109],"involve":[110],"To":[113],"both":[116,140,148],"drifts,":[121],"we":[122,142],"propose":[123],"framework":[127],"called":[128],"DASS,":[129],"combines":[131],"models":[135],"diversified":[137],"adaptation.":[138],"For":[139],"models,":[141],"employ":[143],"extract":[147],"temporal":[149,164,168,185,189],"dependencies.":[152,195],"Our":[153],"method":[156,253],"relies":[157],"on":[158,204],"three":[159],"main":[160],"components:":[161],"(1)":[162],"low-level":[163],"modeling,":[165,175,186],"extracts":[167,177,188],"individual":[171],"stocks,":[172,181],"(2)":[173],"(3)":[183],"high-level":[184],"from":[191],"learned":[193],"Furthermore,":[196],"DASS":[197,217,241],"constructs":[198],"simple":[199],"graphs":[200],"hypergraphs":[202],"based":[203],"dynamic":[205],"time":[206],"warping":[207],"prices":[210],"volume":[212],"data.":[213],"The":[214],"performance":[215],"compared":[219],"with":[220],"state-of-the-art":[223],"methods.":[226],"Experimental":[227],"results":[228],"included":[231],"Standard":[234],"&":[235],"Poor\u2019s":[236],"500":[237],"index":[238],"reveal":[239],"achieves":[242],"compounded":[244],"annual":[245],"growth":[246],"rate":[247],"83.2%,":[249],"outperforming":[250],"second-best":[252],"by":[254],"23.0%P.":[255]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
