{"id":"https://openalex.org/W2789605973","doi":"https://doi.org/10.1109/access.2018.2806180","title":"An Adaptive SVR for High-Frequency Stock Price Forecasting","display_name":"An Adaptive SVR for High-Frequency Stock Price Forecasting","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2789605973","doi":"https://doi.org/10.1109/access.2018.2806180","mag":"2789605973"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2806180","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2806180","pdf_url":null,"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://doi.org/10.1109/access.2018.2806180","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028142707","display_name":"Yanhui Guo","orcid":"https://orcid.org/0000-0002-5444-3822"},"institutions":[{"id":"https://openalex.org/I4210151294","display_name":"Shandong Women\u2019s University","ror":"https://ror.org/03rp8h078","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151294"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhui Guo","raw_affiliation_strings":["School of Information Technology, Shandong Women\u2019s University, Jinan, China","School of Information Technology, Shandong Women's University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-5444-3822","affiliations":[{"raw_affiliation_string":"School of Information Technology, Shandong Women\u2019s University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]},{"raw_affiliation_string":"School of Information Technology, Shandong Women's University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110840249","display_name":"Siming Han","orcid":"https://orcid.org/0009-0002-3887-3846"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siming Han","raw_affiliation_strings":["School of Computer Science, Shaanxi Normal University, Xi\u2019an, China","School of Computer Science, Shaanxi Normal University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Shaanxi Normal University, Xi\u2019an, China","institution_ids":["https://openalex.org/I88830068"]},{"raw_affiliation_string":"School of Computer Science, Shaanxi Normal University, Xi'an, China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024764291","display_name":"Chuanhe Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151294","display_name":"Shandong Women\u2019s University","ror":"https://ror.org/03rp8h078","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151294"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanhe Shen","raw_affiliation_strings":["School of Information Technology, Shandong Women\u2019s University, Jinan, China","School of Information Technology, Shandong Women's University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Shandong Women\u2019s University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]},{"raw_affiliation_string":"School of Information Technology, Shandong Women's University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100414144","display_name":"Ying Li","orcid":"https://orcid.org/0000-0002-1143-1258"},"institutions":[{"id":"https://openalex.org/I4210151294","display_name":"Shandong Women\u2019s University","ror":"https://ror.org/03rp8h078","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151294"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Li","raw_affiliation_strings":["School of Information Technology, Shandong Women\u2019s University, Jinan, China","School of Information Technology, Shandong Women's University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Shandong Women\u2019s University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]},{"raw_affiliation_string":"School of Information Technology, Shandong Women's University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068516081","display_name":"Xijie Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151294","display_name":"Shandong Women\u2019s University","ror":"https://ror.org/03rp8h078","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151294"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xijie Yin","raw_affiliation_strings":["School of Information Technology, Shandong Women\u2019s University, Jinan, China","School of Information Technology, Shandong Women's University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Shandong Women\u2019s University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]},{"raw_affiliation_string":"School of Information Technology, Shandong Women's University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018409371","display_name":"Yu Bai","orcid":"https://orcid.org/0000-0002-2303-1120"},"institutions":[{"id":"https://openalex.org/I142934699","display_name":"California State University, Fullerton","ror":"https://ror.org/02avqqw26","country_code":"US","type":"education","lineage":["https://openalex.org/I142934699"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Bai","raw_affiliation_strings":["School of Engineering and Computer Science, California State University, Fullerton, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2303-1120","affiliations":[{"raw_affiliation_string":"School of Engineering and Computer Science, California State University, Fullerton, CA, USA","institution_ids":["https://openalex.org/I142934699"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":8.0676,"has_fulltext":false,"cited_by_count":108,"citation_normalized_percentile":{"value":0.97609348,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"11397","last_page":"11404"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9997000098228455,"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":0.9997000098228455,"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":0.995199978351593,"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"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9923999905586243,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.7721339464187622},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7385738492012024},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6564633846282959},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5837904214859009},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5450764298439026},{"id":"https://openalex.org/keywords/normality","display_name":"Normality","score":0.48854193091392517},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.46396103501319885},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4011087715625763},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.354514479637146},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.34676098823547363},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3296625018119812},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30054789781570435},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16446182131767273},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.147219717502594},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07456916570663452}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.7721339464187622},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7385738492012024},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6564633846282959},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5837904214859009},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5450764298439026},{"id":"https://openalex.org/C2776157432","wikidata":"https://www.wikidata.org/wiki/Q1375683","display_name":"Normality","level":2,"score":0.48854193091392517},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.46396103501319885},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4011087715625763},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.354514479637146},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.34676098823547363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3296625018119812},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30054789781570435},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16446182131767273},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.147219717502594},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07456916570663452},{"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.2018.2806180","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2806180","pdf_url":null,"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:0f097ae90dba4a699760b354fdb0c48b","is_oa":true,"landing_page_url":"https://doaj.org/article/0f097ae90dba4a699760b354fdb0c48b","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 6, Pp 11397-11404 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2806180","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2806180","pdf_url":null,"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":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W163346876","https://openalex.org/W1586335931","https://openalex.org/W1815264562","https://openalex.org/W2002644193","https://openalex.org/W2010089783","https://openalex.org/W2016287239","https://openalex.org/W2018351240","https://openalex.org/W2034019416","https://openalex.org/W2039935421","https://openalex.org/W2080265874","https://openalex.org/W2109364787","https://openalex.org/W2119821739","https://openalex.org/W2144246192","https://openalex.org/W2145344497","https://openalex.org/W2169533279","https://openalex.org/W2416924782","https://openalex.org/W2487144183","https://openalex.org/W2489850253","https://openalex.org/W4239510810","https://openalex.org/W4239922572","https://openalex.org/W6606548013","https://openalex.org/W6684976734"],"related_works":["https://openalex.org/W4321650139","https://openalex.org/W2169275958","https://openalex.org/W4239286941","https://openalex.org/W2917687159","https://openalex.org/W2000721663","https://openalex.org/W2088845016","https://openalex.org/W2506314341","https://openalex.org/W2405714784","https://openalex.org/W589102260","https://openalex.org/W4391002904"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,63],"mitigate":[3],"investments,":[4],"stock":[5,81],"price":[6],"forecasting":[7],"has":[8],"attracted":[9],"more":[10],"attention":[11],"in":[12,21,33,39],"recent":[13],"years.":[14],"Aiming":[15],"at":[16,83],"the":[17,37,43,47,66,99],"discreteness,":[18],"non-normality,":[19],"high-noise":[20],"high-frequency":[22],"data,":[23,90,92],"a":[24,114],"support":[25],"vector":[26],"machine":[27],"regression":[28],"(SVR)":[29],"algorithm":[30],"is":[31,61],"introduced":[32],"this":[34,73],"paper.":[35],"However,":[36],"characteristics":[38],"different":[40,51,85],"periods":[41,49],"of":[42,50,105],"same":[44,48],"stock,":[45],"or":[46],"stocks":[52],"are":[53],"significantly":[54],"different.":[55],"So,":[56],"SVR":[57,77,101,121],"with":[58,65,102],"fixed":[59],"parameters":[60,107],"difficult":[62],"satisfy":[64],"constantly":[67],"changing":[68],"data":[69,82],"flow.":[70],"To":[71],"tackle":[72],"problem,":[74],"an":[75],"adaptive":[76],"was":[78],"proposed":[79],"for":[80],"three":[84],"time":[86],"scales,":[87],"including":[88,120],"daily":[89],"30-min":[91],"and":[93,122],"5-min":[94],"data.":[95],"Experiments":[96],"show":[97],"that":[98],"improved":[100],"dynamic":[103],"optimization":[104,111],"learning":[106],"by":[108],"particle":[109],"swarm":[110],"can":[112],"get":[113],"better":[115],"result":[116],"than":[117],"compared":[118],"methods":[119],"back-propagation":[123],"neural":[124],"network.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
