{"id":"https://openalex.org/W4313066707","doi":"https://doi.org/10.1109/indin51773.2022.9976077","title":"Self-FTS: A Self-Supervised Learning Method for Financial Time Series Representation in Stock Intraday Trading","display_name":"Self-FTS: A Self-Supervised Learning Method for Financial Time Series Representation in Stock Intraday Trading","publication_year":2022,"publication_date":"2022-07-25","ids":{"openalex":"https://openalex.org/W4313066707","doi":"https://doi.org/10.1109/indin51773.2022.9976077"},"language":"en","primary_location":{"id":"doi:10.1109/indin51773.2022.9976077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin51773.2022.9976077","pdf_url":null,"source":{"id":"https://openalex.org/S4363608444","display_name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-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/A5102106544","display_name":"Jifeng Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jifeng Sun","raw_affiliation_strings":["Tsinghua University,Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School,Shenzhen,China","Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021017214","display_name":"Yinghe Qing","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinghe Qing","raw_affiliation_strings":["Tsinghua University,Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School,Shenzhen,China","Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353141","display_name":"Chang Liu","orcid":"https://orcid.org/0000-0001-5560-7203"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang Liu","raw_affiliation_strings":["Tsinghua University,Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School,Shenzhen,China","Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua-Berkeley Shenzhen Institute Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019425648","display_name":"Jianwu Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwu Lin","raw_affiliation_strings":["Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,China","Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102106544"],"corresponding_institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.5487,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.84285714,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"501","last_page":"506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998999834060669,"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":0.9998999834060669,"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/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9911999702453613,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9905999898910522,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6061037182807922},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5875477194786072},{"id":"https://openalex.org/keywords/self-representation","display_name":"Self representation","score":0.5803362727165222},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5761987566947937},{"id":"https://openalex.org/keywords/stock-trading","display_name":"Stock trading","score":0.574669599533081},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5572780966758728},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5481694936752319},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44349780678749084},{"id":"https://openalex.org/keywords/stock-exchange","display_name":"Stock exchange","score":0.4333694577217102},{"id":"https://openalex.org/keywords/trading-strategy","display_name":"Trading strategy","score":0.4138178825378418},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3453846573829651},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.34145021438598633},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.3309658169746399},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.2638006806373596},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.20026028156280518},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08787938952445984},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.07786396145820618}],"concepts":[{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6061037182807922},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5875477194786072},{"id":"https://openalex.org/C2988612419","wikidata":"https://www.wikidata.org/wiki/Q7448312","display_name":"Self representation","level":2,"score":0.5803362727165222},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5761987566947937},{"id":"https://openalex.org/C2989233474","wikidata":"https://www.wikidata.org/wiki/Q7831917","display_name":"Stock trading","level":4,"score":0.574669599533081},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5572780966758728},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5481694936752319},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44349780678749084},{"id":"https://openalex.org/C200870193","wikidata":"https://www.wikidata.org/wiki/Q11691","display_name":"Stock exchange","level":2,"score":0.4333694577217102},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.4138178825378418},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3453846573829651},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34145021438598633},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3309658169746399},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.2638006806373596},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.20026028156280518},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08787938952445984},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.07786396145820618},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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/C15708023","wikidata":"https://www.wikidata.org/wiki/Q80083","display_name":"Humanities","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/indin51773.2022.9976077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin51773.2022.9976077","pdf_url":null,"source":{"id":"https://openalex.org/S4363608444","display_name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W343636949","https://openalex.org/W1995834279","https://openalex.org/W2187089797","https://openalex.org/W2613328025","https://openalex.org/W2785325870","https://openalex.org/W2792764867","https://openalex.org/W2949736877","https://openalex.org/W2964413206","https://openalex.org/W2975308768","https://openalex.org/W2996552856","https://openalex.org/W3009650506","https://openalex.org/W3046296398","https://openalex.org/W3109603638","https://openalex.org/W3124360968","https://openalex.org/W3162049936","https://openalex.org/W3162807103","https://openalex.org/W3172781652","https://openalex.org/W3173151551","https://openalex.org/W3177318507","https://openalex.org/W3200019757","https://openalex.org/W4301372783","https://openalex.org/W6611801654","https://openalex.org/W6747899497","https://openalex.org/W6749825310","https://openalex.org/W6755591634","https://openalex.org/W6763309814","https://openalex.org/W6776111384","https://openalex.org/W6783990618","https://openalex.org/W6787312032","https://openalex.org/W6797132756"],"related_works":["https://openalex.org/W4311922785","https://openalex.org/W4313491999","https://openalex.org/W4286702726","https://openalex.org/W2045187328","https://openalex.org/W1510124424","https://openalex.org/W78115955","https://openalex.org/W3175255688","https://openalex.org/W1564421840","https://openalex.org/W3176836227","https://openalex.org/W4214771350"],"abstract_inverted_index":{"The":[0,17],"stock":[1,15,45,70,118,159,172,182],"price\u2019s":[2],"highly":[3],"unstable":[4],"fluctuation":[5],"pattern":[6],"makes":[7],"learning":[8,20,55,78,84],"efficient":[9],"representation":[10,66,85],"challenging":[11],"to":[12,42,62,95,109,134,161,194],"model":[13],"the":[14,33,37,44,64,74,97,116,136,141,146,151,170,181,187,195],"movement.":[16],"common":[18],"deep":[19],"often":[21],"overfits":[22],"after":[23],"a":[24,53,80,124,131],"few":[25],"epochs":[26],"of":[27],"training":[28],"and":[29,67,122,186],"performs":[30],"poorly":[31],"in":[32,69],"validation":[34],"set":[35],"because":[36],"optimization":[38],"objective":[39],"is":[40,79],"insufficient":[41],"characterize":[43],"adequately.":[46],"In":[47],"this":[48],"paper,":[49],"we":[50,104],"propose":[51],"Self-FTS,":[52],"self-supervised":[54,77],"framework":[56],"for":[57,83,86],"financial":[58,93],"time":[59],"series":[60],"representation,":[61],"learn":[63,135],"underlying":[65],"use":[68],"trading,":[71],"affected":[72],"by":[73,100,153],"fact":[75],"that":[76,176],"promising":[81],"technique":[82],"extracting":[87],"high":[88],"dimensional":[89],"features":[90],"from":[91,115,150],"unlabeled":[92],"data":[94,120,155,174],"overcome":[96],"bias":[98],"caused":[99],"handcrafted":[101],"features.":[102],"Specifically,":[103],"design":[105],"several":[106],"auxiliary":[107],"tasks":[108],"generate":[110],"samples":[111],"with":[112,130,158],"pseudo":[113,137],"labels":[114,138],"A-share":[117],"price":[119],"sets":[121,156],"build":[123,162],"weight-sharing":[125],"feature":[126],"extraction":[127],"backbone":[128,152],"combined":[129],"classification":[132],"head":[133],"based":[139],"on":[140,169],"samples.":[142],"Finally,":[143],"We":[144],"evaluate":[145],"learned":[147],"representations":[148],"extracted":[149],"fine-tuning":[154],"labelled":[157],"returns":[160],"an":[163],"investment":[164,189],"portfolio.":[165],"Experimental":[166],"analysis":[167],"results":[168],"Chinese":[171],"market":[173],"show":[175],"our":[177,202],"method":[178],"significantly":[179],"improves":[180],"trend":[183],"forecasting":[184],"performances":[185],"actual":[188],"income":[190],"through":[191],"backtesting":[192],"compared":[193],"current":[196],"SOTA":[197],"method,":[198],"which":[199],"strongly":[200],"demonstrates":[201],"effective":[203],"approach.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
