{"id":"https://openalex.org/W4306962791","doi":"https://doi.org/10.1145/3533271.3561687","title":"Denoised Labels for Financial Time Series Data via Self-Supervised Learning","display_name":"Denoised Labels for Financial Time Series Data via Self-Supervised Learning","publication_year":2022,"publication_date":"2022-10-20","ids":{"openalex":"https://openalex.org/W4306962791","doi":"https://doi.org/10.1145/3533271.3561687"},"language":"en","primary_location":{"id":"doi:10.1145/3533271.3561687","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3533271.3561687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third ACM International Conference on AI in Finance","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/A5065357239","display_name":"Yan-Qing Ma","orcid":"https://orcid.org/0000-0001-5795-3791"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Yanqing Ma","raw_affiliation_strings":["King's College London, UK"],"affiliations":[{"raw_affiliation_string":"King's College London, UK","institution_ids":["https://openalex.org/I183935753"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001328914","display_name":"Carmine Ventre","orcid":"https://orcid.org/0000-0003-1464-1215"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Carmine Ventre","raw_affiliation_strings":["King's College London, UK"],"affiliations":[{"raw_affiliation_string":"King's College London, UK","institution_ids":["https://openalex.org/I183935753"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065622718","display_name":"Maria Polukarov","orcid":"https://orcid.org/0000-0002-7421-3012"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Maria Polukarov","raw_affiliation_strings":["King's College London, UK"],"affiliations":[{"raw_affiliation_string":"King's College London, UK","institution_ids":["https://openalex.org/I183935753"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5065357239"],"corresponding_institution_ids":["https://openalex.org/I183935753"],"apc_list":null,"apc_paid":null,"fwci":1.1887,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.78054947,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"471","last_page":"479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.993399977684021,"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":0.9861000180244446,"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/computer-science","display_name":"Computer science","score":0.7011816501617432},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6578935384750366},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5926194190979004},{"id":"https://openalex.org/keywords/financial-market","display_name":"Financial market","score":0.5328842401504517},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5239529609680176},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.5236194729804993},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5224505662918091},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5132498741149902},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.4990994930267334},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.47517648339271545},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.3655869662761688},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.344103068113327},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.14206534624099731},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.0879298746585846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7011816501617432},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6578935384750366},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5926194190979004},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.5328842401504517},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5239529609680176},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.5236194729804993},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5224505662918091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5132498741149902},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.4990994930267334},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.47517648339271545},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3655869662761688},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.344103068113327},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.14206534624099731},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0879298746585846},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3533271.3561687","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3533271.3561687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third ACM International Conference on AI in Finance","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":17,"referenced_works":["https://openalex.org/W1583837637","https://openalex.org/W1969306056","https://openalex.org/W2174424190","https://openalex.org/W2555077524","https://openalex.org/W2587997492","https://openalex.org/W2734777338","https://openalex.org/W2766355270","https://openalex.org/W2790822776","https://openalex.org/W2936774411","https://openalex.org/W2963751193","https://openalex.org/W2963866024","https://openalex.org/W2999546058","https://openalex.org/W3121241692","https://openalex.org/W3150130320","https://openalex.org/W3174031548","https://openalex.org/W4255461888","https://openalex.org/W4299365791"],"related_works":["https://openalex.org/W1919101720","https://openalex.org/W4390822878","https://openalex.org/W96888382","https://openalex.org/W2041308758","https://openalex.org/W4386126592","https://openalex.org/W2951907088","https://openalex.org/W2622688551","https://openalex.org/W2119012848","https://openalex.org/W1990205660","https://openalex.org/W1550175370"],"abstract_inverted_index":{"The":[0,107],"introduction":[1],"of":[2,10,28,40,52,68,102],"electronic":[3],"trading":[4,13],"platforms":[5],"effectively":[6],"changed":[7],"the":[8,38,45,50,61,66,97,115],"organisation":[9],"traditional":[11],"systemic":[12],"from":[14],"quote-driven":[15],"markets":[16],"into":[17],"order-driven":[18],"markets.":[19],"Its":[20],"convenience":[21],"led":[22],"to":[23,35,44,64,81],"an":[24],"exponentially":[25],"increasing":[26],"amount":[27],"financial":[29,53,85],"data,":[30],"which":[31],"is":[32,63,87],"however":[33,88],"hard":[34],"use":[36],"for":[37],"prediction":[39],"future":[41,69],"prices,":[42],"due":[43],"low":[46],"signal-to-noise":[47],"ratio":[48],"and":[49],"non-stationarity":[51],"time":[54],"series.":[55],"Simpler":[56],"classification":[57],"tasks":[58],"\u2014":[59,76],"where":[60],"goal":[62],"predict":[65],"directions":[67],"price":[70,98],"movement":[71],"via":[72],"supervised":[73],"learning":[74,124],"algorithms":[75],"need":[77],"sufficiently":[78],"reliable":[79],"labels":[80],"generalise":[82],"well.":[83],"Labelling":[84],"data":[86],"less":[89],"well":[90,118],"defined":[91],"than":[92],"in":[93,122],"other":[94],"domains:":[95],"did":[96],"go":[99],"up":[100],"because":[101],"noise":[103],"or":[104],"a":[105],"signal?":[106],"existing":[108],"labelling":[109],"methods":[110],"have":[111],"limited":[112,120],"countermeasures":[113],"against":[114],"noise,":[116],"as":[117,119],"effects":[121],"improving":[123],"algorithms.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
