{"id":"https://openalex.org/W4415250062","doi":"https://doi.org/10.48550/arxiv.2509.16206","title":"Deep Reinforcement Learning in Factor Investment","display_name":"Deep Reinforcement Learning in Factor Investment","publication_year":2025,"publication_date":"2025-07-30","ids":{"openalex":"https://openalex.org/W4415250062","doi":"https://doi.org/10.48550/arxiv.2509.16206"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2509.16206","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.16206","pdf_url":"https://arxiv.org/pdf/2509.16206","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2509.16206","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070375205","display_name":"Junlin Liu","orcid":"https://orcid.org/0000-0002-4981-1010"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liu, Junlin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5070375205"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.5605999827384949,"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":0.5605999827384949,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6238999962806702},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.6057000160217285},{"id":"https://openalex.org/keywords/sharpe-ratio","display_name":"Sharpe ratio","score":0.5274999737739563},{"id":"https://openalex.org/keywords/factor-analysis","display_name":"Factor analysis","score":0.476500004529953},{"id":"https://openalex.org/keywords/investment","display_name":"Investment (military)","score":0.46070000529289246},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.4544999897480011},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.438400000333786},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.42739999294281006}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6238999962806702},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.6057000160217285},{"id":"https://openalex.org/C139938925","wikidata":"https://www.wikidata.org/wiki/Q1501898","display_name":"Sharpe ratio","level":3,"score":0.5274999737739563},{"id":"https://openalex.org/C10879293","wikidata":"https://www.wikidata.org/wiki/Q726474","display_name":"Factor analysis","level":2,"score":0.476500004529953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47530001401901245},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4747999906539917},{"id":"https://openalex.org/C27548731","wikidata":"https://www.wikidata.org/wiki/Q88272","display_name":"Investment (military)","level":3,"score":0.46070000529289246},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.4544999897480011},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.438400000333786},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.42739999294281006},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41929998993873596},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41440001130104065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4083999991416931},{"id":"https://openalex.org/C199728807","wikidata":"https://www.wikidata.org/wiki/Q2578557","display_name":"Equity (law)","level":2,"score":0.4056999981403351},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4007999897003174},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.37380000948905945},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.3425999879837036},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34130001068115234},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.33320000767707825},{"id":"https://openalex.org/C103144560","wikidata":"https://www.wikidata.org/wiki/Q2670999","display_name":"Investment strategy","level":3,"score":0.3208000063896179},{"id":"https://openalex.org/C202655437","wikidata":"https://www.wikidata.org/wiki/Q7231728","display_name":"Portfolio optimization","level":3,"score":0.3181000053882599},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26089999079704285},{"id":"https://openalex.org/C9725762","wikidata":"https://www.wikidata.org/wiki/Q1072885","display_name":"Modern portfolio theory","level":3,"score":0.2597000002861023},{"id":"https://openalex.org/C26584437","wikidata":"https://www.wikidata.org/wiki/Q6060874","display_name":"Investment performance","level":4,"score":0.2567000091075897},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2509.16206","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.16206","pdf_url":"https://arxiv.org/pdf/2509.16206","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2509.16206","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.16206","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2509.16206","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.16206","pdf_url":"https://arxiv.org/pdf/2509.16206","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"reinforcement":[1],"learning":[2,125],"has":[3],"shown":[4],"promise":[5],"in":[6,12],"trade":[7],"execution,":[8],"yet":[9],"its":[10],"use":[11],"low-frequency":[13],"factor":[14,117],"portfolio":[15,133],"construction":[16],"remains":[17],"under-explored.":[18],"A":[19],"key":[20],"obstacle":[21],"is":[22],"the":[23,35],"high-dimensional,":[24],"unbalanced":[25],"state":[26],"space":[27],"created":[28],"by":[29],"stocks":[30],"that":[31,122],"enter":[32],"and":[33,72,94,102],"exit":[34],"investable":[36],"universe.":[37],"We":[38],"introduce":[39],"Conditional":[40],"Auto-encoded":[41],"Factor-based":[42],"Portfolio":[43],"Optimisation":[44],"(CAFPO),":[45],"which":[46],"compresses":[47],"stock-level":[48],"returns":[49],"into":[50],"a":[51,65,98,103],"small":[52],"set":[53],"of":[54,82,106,109],"latent":[55],"factors":[56,63],"conditioned":[57],"on":[58],"94":[59],"firm-specific":[60],"characteristics.":[61],"The":[62],"feed":[64],"DRL":[66,128],"agent":[67],"implemented":[68],"with":[69],"both":[70],"PPO":[71],"DDPG":[73],"to":[74],"generate":[75],"continuous":[76],"long-short":[77],"weights.":[78],"On":[79],"20":[80],"years":[81],"U.S.":[83],"equity":[84],"data":[85],"(2000--2020),":[86],"CAFPO":[87],"outperforms":[88],"equal-weight,":[89],"value-weight,":[90],"Markowitz,":[91],"vanilla":[92],"DRL,":[93,96],"Fama--French-driven":[95],"delivering":[97],"24.6\\%":[99],"compound":[100],"return":[101],"Sharpe":[104],"ratio":[105],"0.94":[107],"out":[108],"sample.":[110],"SHAP":[111],"analysis":[112],"further":[113],"reveals":[114],"economically":[115],"intuitive":[116],"attributions.":[118],"Our":[119],"results":[120],"demonstrate":[121],"factor-aware":[123],"representation":[124],"can":[126],"make":[127],"practical":[129],"for":[130],"institutional,":[131],"low-turnover":[132],"management.":[134]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-16T00:00:00"}