{"id":"https://openalex.org/W4403582610","doi":"https://doi.org/10.1145/3627673.3679544","title":"Explainable Stock Price Movement Prediction using Contrastive Learning","display_name":"Explainable Stock Price Movement Prediction using Contrastive Learning","publication_year":2024,"publication_date":"2024-10-20","ids":{"openalex":"https://openalex.org/W4403582610","doi":"https://doi.org/10.1145/3627673.3679544"},"language":"en","primary_location":{"id":"doi:10.1145/3627673.3679544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679544","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3627673.3679544","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103108962","display_name":"Kelvin Du","orcid":"https://orcid.org/0000-0002-7856-3140"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Kelvin Du","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062187850","display_name":"Rui Mao","orcid":"https://orcid.org/0000-0002-1082-8755"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Rui Mao","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024877482","display_name":"Frank Xing","orcid":"https://orcid.org/0000-0002-5751-3937"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Frank Xing","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100752356","display_name":"Erik Cambria","orcid":"https://orcid.org/0000-0002-3030-1280"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Erik Cambria","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103108962"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":5.6195,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.96122092,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"529","last_page":"537"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9635000228881836,"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9611999988555908,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7211722731590271},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.5475351810455322},{"id":"https://openalex.org/keywords/stock-price","display_name":"Stock price","score":0.5031480193138123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4789296090602875},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.4532131552696228},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3750881850719452},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12199467420578003},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08987846970558167},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.07790574431419373}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7211722731590271},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.5475351810455322},{"id":"https://openalex.org/C2988984586","wikidata":"https://www.wikidata.org/wiki/Q1020013","display_name":"Stock price","level":3,"score":0.5031480193138123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4789296090602875},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.4532131552696228},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3750881850719452},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12199467420578003},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08987846970558167},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.07790574431419373},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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":1,"locations":[{"id":"doi:10.1145/3627673.3679544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679544","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3627673.3679544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679544","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.4699999988079071,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1588690085","https://openalex.org/W2095847349","https://openalex.org/W2096733369","https://openalex.org/W2613328025","https://openalex.org/W2766718178","https://openalex.org/W2774559076","https://openalex.org/W2798413829","https://openalex.org/W2896309423","https://openalex.org/W2896421350","https://openalex.org/W2902534617","https://openalex.org/W2964413206","https://openalex.org/W2970641574","https://openalex.org/W3099645789","https://openalex.org/W3115467802","https://openalex.org/W3170487013","https://openalex.org/W3202576141","https://openalex.org/W3210936843","https://openalex.org/W4234552385","https://openalex.org/W4308512597","https://openalex.org/W4318148071","https://openalex.org/W4318477615","https://openalex.org/W4385572047","https://openalex.org/W4385574410","https://openalex.org/W4387068131","https://openalex.org/W4389166221","https://openalex.org/W4389473931","https://openalex.org/W4391549756","https://openalex.org/W4392168447","https://openalex.org/W4402352733"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Predicting":[0],"stock":[1,43,163],"price":[2],"movements":[3],"is":[4,20,72,111,154],"a":[5,31,75,93],"high-stakes":[6],"task":[7],"that":[8,96],"demands":[9],"explainability":[10,41],"for":[11,35],"human":[12],"decision-makers.":[13],"A":[14],"key":[15],"shortcoming":[16],"in":[17,105],"current":[18],"methods":[19],"treating":[21],"sub-predictions":[22],"independently,":[23],"without":[24],"learning":[25,37],"from":[26],"accumulated":[27],"experiences.":[28],"We":[29,56],"propose":[30],"novel":[32],"triplet":[33],"network":[34],"contrastive":[36],"to":[38,58],"enhance":[39],"the":[40,59,66,88,106,114,119,130,133,142,145],"of":[42,49,116],"movement":[44],"prediction":[45,164],"by":[46,79],"considering":[47],"instances":[48,135,147],"\"integrated":[50],"textual":[51],"information":[52],"and":[53,92,126,136,139,148],"quantitative":[54],"indicators\".":[55],"refer":[57],"target":[60],"past-l-day":[61],"tweet-price":[62],"time":[63],"series":[64],"as":[65],"\"anchor":[67],"instance\".":[68],"Each":[69],"anchor":[70,134,146],"instance":[71],"paired":[73],"with":[74,102,113],"\"positive":[76],"instance\"":[77,95],"characterized":[78],"highly":[80],"correlated":[81],"return":[82,99],"trends":[83,100],"yet":[84],"significant":[85],"differences":[86],"across":[87],"entire":[89],"feature":[90,107],"space,":[91],"\"negative":[94],"exhibits":[97],"similar":[98],"along":[101],"high":[103],"proximity":[104],"space.":[108],"The":[109],"model":[110],"designed":[112],"objective":[115],"(1)":[117],"minimizing":[118,129],"cross":[120],"entropy":[121],"loss":[122],"between":[123,132,144],"input":[124],"logits":[125],"target,":[127],"(2)":[128],"distance":[131,143],"positive":[137],"instances,":[138],"(3)":[140],"maximizing":[141],"negative":[149],"instances.":[150],"Our":[151],"framework's":[152],"effectiveness":[153],"demonstrated":[155],"through":[156],"extensive":[157],"testing,":[158],"showing":[159],"superior":[160],"performance":[161],"on":[162],"benchmarks.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
