{"id":"https://openalex.org/W4391022567","doi":"https://doi.org/10.1080/09540091.2023.2286188","title":"A multi-feature stock price prediction model based on multi-feature calculation, LASSO feature selection, and Ca-LSTM network","display_name":"A multi-feature stock price prediction model based on multi-feature calculation, LASSO feature selection, and Ca-LSTM network","publication_year":2024,"publication_date":"2024-01-19","ids":{"openalex":"https://openalex.org/W4391022567","doi":"https://doi.org/10.1080/09540091.2023.2286188"},"language":"en","primary_location":{"id":"doi:10.1080/09540091.2023.2286188","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2023.2286188","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2286188?download=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2286188?download=true","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100373698","display_name":"Xiao Dong Chen","orcid":"https://orcid.org/0000-0002-0150-0491"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Chen","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049926126","display_name":"Lei Cao","orcid":"https://orcid.org/0000-0001-9909-8607"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lei Cao","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049500649","display_name":"Zhi Cao","orcid":"https://orcid.org/0000-0002-3232-5200"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Cao","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China"],"raw_orcid":"https://orcid.org/0000-0002-3232-5200","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100397259","display_name":"Hongwei Zhang","orcid":"https://orcid.org/0000-0002-8711-3870"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"HongWei Zhang","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai, People's Republic of China","institution_ids":["https://openalex.org/I96733725"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5049926126"],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":{"value":1270,"currency":"USD","value_usd":1270},"apc_paid":{"value":1270,"currency":"USD","value_usd":1270},"fwci":5.5319,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.95675964,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"36","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":1.0,"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":1.0,"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":0.9952999949455261,"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/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9948999881744385,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7584384679794312},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6681572794914246},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5525151491165161},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.5297594666481018},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5108027458190918},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.5092579126358032},{"id":"https://openalex.org/keywords/stock-price","display_name":"Stock price","score":0.4819238483905792},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.45921561121940613},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.41005176305770874},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.1667795181274414},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.14431247115135193}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7584384679794312},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6681572794914246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5525151491165161},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.5297594666481018},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5108027458190918},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.5092579126358032},{"id":"https://openalex.org/C2988984586","wikidata":"https://www.wikidata.org/wiki/Q1020013","display_name":"Stock price","level":3,"score":0.4819238483905792},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.45921561121940613},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.41005176305770874},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.1667795181274414},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.14431247115135193},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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},{"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/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"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":2,"locations":[{"id":"doi:10.1080/09540091.2023.2286188","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2023.2286188","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2286188?download=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ca1ae3c7b0a24afeb7c9cdd678db0f3d","is_oa":false,"landing_page_url":"https://doaj.org/article/ca1ae3c7b0a24afeb7c9cdd678db0f3d","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Connection Science, Vol 36, Iss 1 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/09540091.2023.2286188","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2023.2286188","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2286188?download=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391022567.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1547333707","https://openalex.org/W1967647846","https://openalex.org/W1999996900","https://openalex.org/W2005424446","https://openalex.org/W2021938316","https://openalex.org/W2046346480","https://openalex.org/W2064675550","https://openalex.org/W2084439920","https://openalex.org/W2121702267","https://openalex.org/W2135046866","https://openalex.org/W2303916163","https://openalex.org/W2897733922","https://openalex.org/W2905193157","https://openalex.org/W2958060654","https://openalex.org/W2990597424","https://openalex.org/W2990966567","https://openalex.org/W2997421965","https://openalex.org/W3000568686","https://openalex.org/W3001790167","https://openalex.org/W3005069536","https://openalex.org/W3038102750","https://openalex.org/W3043008751","https://openalex.org/W3083701701","https://openalex.org/W3105339524","https://openalex.org/W3124947604","https://openalex.org/W3152560920","https://openalex.org/W3157171516","https://openalex.org/W3167977819","https://openalex.org/W3171038109","https://openalex.org/W3173074502","https://openalex.org/W3175821757","https://openalex.org/W3183739234","https://openalex.org/W3197486829","https://openalex.org/W3202315245","https://openalex.org/W4200197568","https://openalex.org/W4205171949","https://openalex.org/W4205505376","https://openalex.org/W4228998808","https://openalex.org/W4229446061","https://openalex.org/W4247496182","https://openalex.org/W4283740490","https://openalex.org/W4293226241","https://openalex.org/W4307440667","https://openalex.org/W4310894515","https://openalex.org/W4311089293","https://openalex.org/W4311954044"],"related_works":["https://openalex.org/W2380784125","https://openalex.org/W2810025138","https://openalex.org/W1997711767","https://openalex.org/W4386543887","https://openalex.org/W4387885766","https://openalex.org/W2765894738","https://openalex.org/W2370669686","https://openalex.org/W247222457","https://openalex.org/W2887069341","https://openalex.org/W3124131549"],"abstract_inverted_index":{"This":[0,150],"paper":[1],"addresses":[2],"the":[3,79,86,99,119,122,142,168],"crucial":[4],"realm":[5],"of":[6,28,81,121],"stock":[7,29,75,158],"price":[8,76,159],"prediction,":[9,160],"highly":[10],"coveted":[11],"by":[12,115],"individual":[13,110],"investors":[14,166],"and":[15,25,42,131],"institutions":[16],"for":[17,40,74],"its":[18],"substantial":[19],"economic":[20,72],"implications.":[21],"The":[22],"inherent":[23],"non-stationary":[24],"intricate":[26],"nature":[27],"market":[30],"fluctuations,":[31],"coupled":[32],"with":[33,141],"real-time":[34],"transactions,":[35],"poses":[36],"a":[37,58],"formidable":[38],"challenge":[39],"accurate":[41],"swift":[43],"prediction.":[44,77],"Unlike":[45],"prevailing":[46],"research":[47],"that":[48],"predominantly":[49],"focuses":[50],"on":[51,61],"forecasting":[52,148],"methods,":[53],"our":[54,96,138],"novel":[55],"approach":[56],"places":[57],"paramount":[59],"emphasis":[60],"processing":[62],"original":[63],"data,":[64],"introducing":[65],"57":[66],"technical":[67],"indicators":[68],"to":[69,89,156,165],"better":[70],"represent":[71],"aspects":[73],"Signifying":[78],"importance":[80],"each":[82],"feature,":[83],"we":[84],"employ":[85],"LASSO":[87],"algorithm":[88],"derive":[90],"an":[91],"optimal":[92],"feature":[93],"combination.":[94],"Additionally,":[95],"methodology":[97],"utilizes":[98],"Ca-LSTM":[100,123],"(cascade":[101],"long":[102,133],"short-term":[103,134],"memory)":[104],"technique,":[105],"enhancing":[106],"information":[107],"extraction":[108],"from":[109],"features.":[111],"Experimental":[112],"results,":[113],"gauged":[114],"mean":[116],"error,":[117],"underscore":[118],"superiority":[120],"model":[124,145],"over":[125],"other":[126],"time":[127],"series":[128],"prediction":[129],"models":[130],"conventional":[132],"memory":[135],"approaches.":[136],"Notably,":[137],"model's":[139],"integration":[140],"accumulation-based":[143],"VMD-LSTM":[144],"demonstrates":[146],"enhanced":[147],"accuracy.":[149],"proposed":[151],"method":[152],"holds":[153],"considerable":[154],"potential":[155],"refine":[157],"thereby":[161],"delivering":[162],"heightened":[163],"value":[164],"in":[167],"dynamic":[169],"financial":[170],"landscape.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
