{"id":"https://openalex.org/W4410636618","doi":"https://doi.org/10.1145/3701716.3715254","title":"Ploutos: Towards Explainable Stock Movement Prediction with Financial Large Language Model","display_name":"Ploutos: Towards Explainable Stock Movement Prediction with Financial Large Language Model","publication_year":2025,"publication_date":"2025-05-08","ids":{"openalex":"https://openalex.org/W4410636618","doi":"https://doi.org/10.1145/3701716.3715254"},"language":"en","primary_location":{"id":"doi:10.1145/3701716.3715254","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3715254","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715254","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715254","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016525196","display_name":"Hanshuang Tong","orcid":"https://orcid.org/0000-0002-7443-128X"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hanshuang Tong","raw_affiliation_strings":["Microsoft Corporation, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073186959","display_name":"Jun Li","orcid":"https://orcid.org/0009-0004-8938-9055"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["Microsoft Corporation, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101396372","display_name":"Ning Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Wu","raw_affiliation_strings":["Microsoft Corporation, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101640051","display_name":"Ming Gong","orcid":"https://orcid.org/0000-0001-6140-7187"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Gong","raw_affiliation_strings":["Microsoft Corporation, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100331488","display_name":"Dongmei Zhang","orcid":"https://orcid.org/0000-0002-9230-2799"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongmei Zhang","raw_affiliation_strings":["Microsoft Corporation, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022403899","display_name":"Qi Zhang","orcid":"https://orcid.org/0009-0009-7438-7248"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["Microsoft Corporation, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5016525196"],"corresponding_institution_ids":["https://openalex.org/I4210113369"],"apc_list":null,"apc_paid":null,"fwci":2.1106,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.8650745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"490","last_page":"499"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9908000230789185,"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":0.9904000163078308,"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/stock","display_name":"Stock (firearms)","score":0.6032082438468933},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5003697872161865},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.49870848655700684},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.43909475207328796},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.3670234680175781},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30563703179359436},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.2872159481048584},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.08759576082229614}],"concepts":[{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.6032082438468933},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5003697872161865},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.49870848655700684},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.43909475207328796},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3670234680175781},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30563703179359436},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.2872159481048584},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.08759576082229614},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3701716.3715254","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3715254","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715254","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3701716.3715254","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3715254","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715254","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410636618.pdf","grobid_xml":"https://content.openalex.org/works/W4410636618.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2005877787","https://openalex.org/W2011293681","https://openalex.org/W2115839797","https://openalex.org/W2250886571","https://openalex.org/W2251101833","https://openalex.org/W2774513877","https://openalex.org/W2798413829","https://openalex.org/W2798658104","https://openalex.org/W2896421350","https://openalex.org/W2911971986","https://openalex.org/W2969674357","https://openalex.org/W2997379489","https://openalex.org/W3099645789","https://openalex.org/W4283804236","https://openalex.org/W4382239610","https://openalex.org/W4385767800","https://openalex.org/W4389518784","https://openalex.org/W4396843952","https://openalex.org/W4412230201","https://openalex.org/W6854636774"],"related_works":["https://openalex.org/W2184114188","https://openalex.org/W2348328675","https://openalex.org/W4404323120","https://openalex.org/W4234486410","https://openalex.org/W2353407213","https://openalex.org/W3130582205","https://openalex.org/W2479613937","https://openalex.org/W2738039334","https://openalex.org/W2135699798","https://openalex.org/W4402851963"],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2,20,64,164],"large":[3],"language":[4],"models":[5],"(LLMs)":[6],"have":[7],"opened":[8],"new":[9],"pathways":[10],"for":[11,31,36,49,69],"many":[12],"domains.":[13],"However,":[14],"the":[15,67,75,133,172],"full":[16],"potential":[17],"of":[18,88,136],"LLMs":[19],"financial":[21,83],"investments":[22],"remains":[23],"largely":[24],"untapped.":[25],"There":[26],"are":[27],"two":[28],"main":[29],"challenges":[30],"typical":[32],"deep":[33],"learning-based":[34],"methods":[35,55,174],"quantitative":[37,111],"finance.":[38],"First,":[39],"they":[40],"struggle":[41],"to":[42,143,146,155],"fuse":[43],"textual":[44],"and":[45,58,90,107,109,121,123,130,149,160,179],"numerical":[46],"information":[47],"flexibly":[48],"stock":[50],"movement":[51],"prediction.":[52],"Second,":[53],"traditional":[54],"lack":[56],"clarity":[57],"explainability,":[59],"which":[60],"impedes":[61],"their":[62,119],"application":[63],"scenarios":[65],"where":[66],"justification":[68],"predictions":[70,122],"is":[71],"essential.":[72],"To":[73,127],"solve":[74],"above":[76],"challenges,":[77],"we":[78],"propose":[79],"Ploutos,":[80],"a":[81,139,150],"novel":[82],"LLM":[84,157],"framework":[85,170],"that":[86,98],"consists":[87],"PloutosGen":[89,93],"PloutosGPT.":[91],"The":[92],"contains":[94],"multiple":[95],"primary":[96],"experts":[97],"can":[99],"analyze":[100],"different":[101,114],"modal":[102],"data,":[103],"such":[104],"as":[105],"text":[106],"numbers,":[108],"provide":[110],"strategies":[112],"from":[113],"perspectives.":[115],"Then":[116],"PloutosGPT":[117,137],"combines":[118],"insights":[120],"generates":[124],"explainable":[125],"rationales.":[126,165],"generate":[128,147],"accurate":[129],"faithful":[131],"rationales,":[132],"training":[134],"strategy":[135],"leverages":[138],"rearview-mirror":[140],"prompting":[141],"mechanism":[142,154],"guide":[144],"GPT-4":[145],"rationales":[148],"dynamic":[151],"token":[152],"weighting":[153],"finetune":[156],"by":[158],"detecting":[159],"emphasizing":[161],"key":[162],"tokens":[163],"Extensive":[166],"experiments":[167],"show":[168],"our":[169],"outperforms":[171],"state-of-the-art":[173],"on":[175],"both":[176],"prediction":[177],"accuracy":[178],"explainability.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
