{"id":"https://openalex.org/W4411551139","doi":"https://doi.org/10.1109/cscwd64889.2025.11033372","title":"FD-RLPO: Feature Domain-based Reinforcement Learning Framework for Portfolio Optimization","display_name":"FD-RLPO: Feature Domain-based Reinforcement Learning Framework for Portfolio Optimization","publication_year":2025,"publication_date":"2025-05-05","ids":{"openalex":"https://openalex.org/W4411551139","doi":"https://doi.org/10.1109/cscwd64889.2025.11033372"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd64889.2025.11033372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd64889.2025.11033372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","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/A5073679933","display_name":"Jingyuan Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingyuan Feng","raw_affiliation_strings":["Institute of Artificial Intelligence, Xiamen University,Xiamen,China"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence, Xiamen University,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101279170","display_name":"Qiyue Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiyue Wu","raw_affiliation_strings":["Institute of Artificial Intelligence, Xiamen University,Xiamen,China"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence, Xiamen University,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038729392","display_name":"Fan Lin","orcid":"https://orcid.org/0000-0003-2530-859X"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Lin","raw_affiliation_strings":["School of Informatics, Xiamen University,Xiamen,China"],"affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5073679933"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19761846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1190","last_page":"1195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9442999958992004,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9442999958992004,"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":0.8542336821556091},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7351628541946411},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5704439878463745},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5605571269989014},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5062512755393982},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.4581943452358246},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4201841354370117},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3440064489841461},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1294117569923401}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8542336821556091},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7351628541946411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5704439878463745},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5605571269989014},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5062512755393982},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.4581943452358246},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4201841354370117},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3440064489841461},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1294117569923401},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd64889.2025.11033372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd64889.2025.11033372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","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":13,"referenced_works":["https://openalex.org/W1907464529","https://openalex.org/W2092281935","https://openalex.org/W2286419477","https://openalex.org/W2344786740","https://openalex.org/W3034345631","https://openalex.org/W3110378470","https://openalex.org/W3171397019","https://openalex.org/W3177318507","https://openalex.org/W4283804236","https://openalex.org/W4385767800","https://openalex.org/W4393160226","https://openalex.org/W4400490517","https://openalex.org/W4405521288"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W3084456289","https://openalex.org/W2024136090","https://openalex.org/W4391331176","https://openalex.org/W2031695474","https://openalex.org/W2586732548","https://openalex.org/W2964765435"],"abstract_inverted_index":{"Portfolio":[0,68],"optimization":[1],"is":[2],"a":[3,61,95,111,135],"critical":[4],"issue":[5],"in":[6,17,40,51,103,197],"finance.":[7],"In":[8,85],"the":[9,43,87,107,121,131,139,145,148,153,175,185,201,216],"past":[10],"decade,":[11],"reinforcement":[12],"learning":[13,79],"has":[14],"advanced":[15],"con-siderably":[16],"this":[18,56],"area":[19],"owing":[20],"to":[21,25,98,114,156,171,174],"its":[22],"outstanding":[23],"ability":[24],"solve":[26],"complex":[27],"sequential":[28,101],"decision-making":[29],"problems.":[30],"Nevertheless,":[31],"ex-isting":[32],"methods":[33,196],"still":[34],"have":[35],"great":[36],"room":[37],"for":[38,67,81],"improvement":[39],"fully":[41],"considering":[42],"dynamic":[44],"fluctuations":[45,102],"of":[46,123,138,147,163,177,204,218],"intra-domain":[47,104,165],"and":[48,73,151,166,180,187,207],"inter-domain":[49,116,167],"features":[50,168],"financial":[52,178],"markets.":[53],"To":[54],"address":[55],"issue,":[57],"we":[58],"propose":[59],"FD-RLPO,":[60],"Feature":[62],"Domain-based":[63],"Reinforcement":[64],"Learning":[65],"Framework":[66],"Optimization,":[69],"which":[70],"inte-grates":[71],"Prediction":[72,88],"Relation":[74,108],"Modules":[75],"while":[76],"leveraging":[77,152],"rein-forcement":[78],"agents":[80],"adaptive":[82],"strategy":[83],"adjustment.":[84],"particular,":[86],"Module":[89,109,133],"utilizes":[90],"an":[91],"inversion":[92],"mechanism":[93],"within":[94],"Transformer":[96],"architecture":[97],"effectively":[99],"extract":[100],"features.":[105],"Meanwhile,":[106],"employs":[110],"self-supervised":[112],"approach":[113],"capture":[115],"relational":[117],"distribution":[118],"patterns,":[119],"mitigating":[120],"impact":[122],"data":[124],"noise":[125],"on":[126,184],"reconstructed":[127],"asset":[128],"relationships.":[129],"Ultimately,":[130],"Decision":[132],"constructs":[134],"comprehensive":[136],"representation":[137],"market":[140],"feature":[141],"domain":[142],"by":[143],"synthesizing":[144],"outputs":[146],"preceding":[149],"modules":[150],"Actor-Critic":[154],"Network":[155],"achieve":[157],"portfolio":[158],"optimization.":[159],"The":[160],"simultaneous":[161],"perception":[162],"both":[164],"enables":[169],"FD-RLPO":[170,192],"dynamically":[172],"adjust":[173],"volatility":[176],"markets":[179],"increase":[181],"returns.":[182],"Experiments":[183],"CSI-300":[186],"NASDAQ-lOO":[188],"datasets":[189],"demonstrate":[190],"that":[191],"outperforms":[193],"previous":[194],"state-of-the-art":[195],"key":[198],"metrics,":[199],"including":[200],"Annualized":[202,208],"Rate":[203],"Return":[205],"(ARR)":[206],"Sharpe":[209],"Ratio":[210],"(ASR).":[211],"Ablation":[212],"studies":[213],"further":[214],"validate":[215],"effectiveness":[217],"each":[219],"component.":[220]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
