{"id":"https://openalex.org/W3212614390","doi":"https://doi.org/10.1145/3490354.3494366","title":"FinRL","display_name":"FinRL","publication_year":2021,"publication_date":"2021-11-03","ids":{"openalex":"https://openalex.org/W3212614390","doi":"https://doi.org/10.1145/3490354.3494366","mag":"3212614390"},"language":"en","primary_location":{"id":"doi:10.1145/3490354.3494366","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3490354.3494366","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3490354.3494366","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3490354.3494366","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100405233","display_name":"Xiao-Yang Liu","orcid":"https://orcid.org/0000-0002-9532-1709"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiao-Yang Liu","raw_affiliation_strings":["Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061855742","display_name":"Hongyang Yang","orcid":"https://orcid.org/0009-0000-8168-5264"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongyang Yang","raw_affiliation_strings":["Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012051562","display_name":"Jiechao Gao","orcid":"https://orcid.org/0000-0003-0628-1416"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiechao Gao","raw_affiliation_strings":["University of Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018062245","display_name":"Christina Dan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christina Dan Wang","raw_affiliation_strings":["New York University Shanghai"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University Shanghai","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100405233"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":5.9121,"has_fulltext":true,"cited_by_count":69,"citation_normalized_percentile":{"value":0.96468205,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9983999729156494,"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":0.9983999729156494,"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":0.9965999722480774,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9864000082015991,"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":0.7368433475494385},{"id":"https://openalex.org/keywords/debugging","display_name":"Debugging","score":0.660361647605896},{"id":"https://openalex.org/keywords/algorithmic-trading","display_name":"Algorithmic trading","score":0.536617636680603},{"id":"https://openalex.org/keywords/cryptocurrency","display_name":"Cryptocurrency","score":0.41069120168685913},{"id":"https://openalex.org/keywords/financial-economics","display_name":"Financial economics","score":0.1805868148803711},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.15208733081817627},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.12000203132629395},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.11499398946762085}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7368433475494385},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.660361647605896},{"id":"https://openalex.org/C78508483","wikidata":"https://www.wikidata.org/wiki/Q139445","display_name":"Algorithmic trading","level":2,"score":0.536617636680603},{"id":"https://openalex.org/C180706569","wikidata":"https://www.wikidata.org/wiki/Q13479982","display_name":"Cryptocurrency","level":2,"score":0.41069120168685913},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.1805868148803711},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.15208733081817627},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.12000203132629395},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.11499398946762085}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3490354.3494366","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3490354.3494366","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3490354.3494366","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second ACM International Conference on AI in Finance","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2111.09395","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.09395","pdf_url":"https://arxiv.org/pdf/2111.09395","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3490354.3494366","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3490354.3494366","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3490354.3494366","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W157402190","https://openalex.org/W398859631","https://openalex.org/W1977051850","https://openalex.org/W1990986169","https://openalex.org/W1997231007","https://openalex.org/W2169015875","https://openalex.org/W2344786740","https://openalex.org/W2398342468","https://openalex.org/W2626914210","https://openalex.org/W2999905431","https://openalex.org/W3008231236","https://openalex.org/W3012223895","https://openalex.org/W3121646140","https://openalex.org/W3124184879","https://openalex.org/W3133248211","https://openalex.org/W3203680104","https://openalex.org/W3213740880","https://openalex.org/W4247451115","https://openalex.org/W4248510338","https://openalex.org/W4251523875","https://openalex.org/W4285333950","https://openalex.org/W4288079541","https://openalex.org/W4299967799"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W4366411693","https://openalex.org/W3211641817","https://openalex.org/W3164717803","https://openalex.org/W4389915954","https://openalex.org/W3123387860","https://openalex.org/W4291291739","https://openalex.org/W2915579847","https://openalex.org/W3110645133"],"abstract_inverted_index":{"Deep":[0],"reinforcement":[1],"learning":[2,78],"(DRL)":[3],"has":[4],"been":[5],"envisioned":[6],"to":[7,25,32,41,50,71],"have":[8],"a":[9,18,68,101,131,160],"competitive":[10],"edge":[11],"in":[12,34],"quantitative":[13,23,73],"finance.":[14],"However,":[15],"there":[16],"is":[17,81],"steep":[19,77],"development":[20],"curve":[21],"for":[22],"traders":[24,74],"obtain":[26],"an":[27],"agent":[28],"that":[29],"automatically":[30],"positions":[31],"win":[33],"the":[35,51,62,76,89,119,127],"market,":[36],"namely":[37],"\\textit{to":[38],"decide":[39],"where":[40],"trade,":[42],"at":[43,130],"what":[44],"price}":[45],"and":[46,54,86,96,113,151,165,175],"\\textit{what":[47],"quantity},":[48],"due":[49],"error-prone":[52],"programming":[53],"arduous":[55],"debugging.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60,123],"present":[61],"first":[63],"open-source":[64],"framework":[65],"\\textit{FinRL}":[66],"as":[67,100,145,170,180,189],"full":[69],"pipeline":[70,126],"help":[72,124],"overcome":[75],"curve.":[79],"FinRL":[80,107,141,158],"featured":[82],"with":[83,104],"simplicity,":[84],"applicability":[85],"extensibility":[87],"under":[88],"key":[90],"principles,":[91],"\\textit{full-stack":[92],"framework,":[93],"customization,":[94],"reproducibility}":[95],"\\textit{hands-on":[97],"tutoring}.":[98],"Embodied":[99],"three-layer":[102],"architecture":[103],"modular":[105],"structures,":[106],"implements":[108],"fine-tuned":[109],"state-of-the-art":[110],"DRL":[111],"algorithms":[112],"common":[114],"reward":[115],"functions,":[116],"while":[117],"alleviating":[118],"debugging":[120],"workloads.":[121],"Thus,":[122],"users":[125],"strategy":[128],"design":[129],"high":[132],"turnover":[133],"rate.":[134],"At":[135],"multiple":[136],"levels":[137],"of":[138,162],"time":[139],"granularity,":[140],"simulates":[142],"various":[143],"markets":[144],"training":[146],"environments":[147],"using":[148],"historical":[149],"data":[150],"live":[152],"trading":[153,167,185],"APIs.":[154],"Being":[155],"highly":[156],"extensible,":[157],"reserves":[159],"set":[161],"user-import":[163],"interfaces":[164],"incorporates":[166],"constraints":[168],"such":[169],"market":[171,173],"friction,":[172],"liquidity":[174],"investor's":[176],"risk-aversion.":[177],"Moreover,":[178],"serving":[179],"practitioners'":[181],"stepping":[182],"stones,":[183],"typical":[184],"tasks":[186],"are":[187],"provided":[188],"step-by-step":[190],"tutorials,":[191],"e.g.,":[192],"stock":[193],"trading,":[194,198],"portfolio":[195],"allocation,":[196],"cryptocurrency":[197],"etc.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":31},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":7}],"updated_date":"2026-05-27T09:02:27.158192","created_date":"2021-11-22T00:00:00"}