{"id":"https://openalex.org/W7165687783","doi":"https://doi.org/10.48550/arxiv.2606.22385","title":"MetaPS: Adaptive Programmatic Strategy Selection for Market Agents","display_name":"MetaPS: Adaptive Programmatic Strategy Selection for Market Agents","publication_year":2026,"publication_date":"2026-06-21","ids":{"openalex":"https://openalex.org/W7165687783","doi":"https://doi.org/10.48550/arxiv.2606.22385"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.22385","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22385","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.22385","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064450687","display_name":"Jiaxiang Chen","orcid":"https://orcid.org/0000-0001-6793-4025"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jiaxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124967269","display_name":"Aotian Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Aotian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069321324","display_name":"Zhouyi Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Zhouyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121555477","display_name":"Weiyi Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Weiyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139143830","display_name":"Chi Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Chi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5073136550","display_name":"Zhewei Xu","orcid":"https://orcid.org/0000-0003-4718-6175"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Zenglin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.18790000677108765,"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"}},"topics":[{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.18790000677108765,"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/T11182","display_name":"Auction Theory and Applications","score":0.18289999663829803,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.14560000598430634,"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/executable","display_name":"Executable","score":0.9114999771118164},{"id":"https://openalex.org/keywords/sandbox","display_name":"Sandbox (software development)","score":0.7221999764442444},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6079000234603882},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.421999990940094},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4180000126361847},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.41280001401901245},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.3422999978065491}],"concepts":[{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.9114999771118164},{"id":"https://openalex.org/C167981075","wikidata":"https://www.wikidata.org/wiki/Q2667186","display_name":"Sandbox (software development)","level":2,"score":0.7221999764442444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6442000269889832},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6079000234603882},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4180000126361847},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.41280001401901245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3653999865055084},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3476000130176544},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C167393769","wikidata":"https://www.wikidata.org/wiki/Q4680768","display_name":"Adaptive strategies","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2953999936580658},{"id":"https://openalex.org/C27564746","wikidata":"https://www.wikidata.org/wiki/Q913709","display_name":"Market research","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.2793999910354614},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C2777093003","wikidata":"https://www.wikidata.org/wiki/Q6508345","display_name":"Lead (geology)","level":2,"score":0.25360000133514404},{"id":"https://openalex.org/C2780873155","wikidata":"https://www.wikidata.org/wiki/Q392811","display_name":"Agent-based model","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.22385","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22385","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.22385","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22385","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.689613401889801}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"No":[0],"single":[1],"market":[2,19,30,54,110,178],"strategy":[3,66,114,119,192],"always":[4],"wins:":[5],"momentum,":[6],"mean":[7],"reversion,":[8],"risk":[9],"control,and":[10],"event-driven":[11],"rules":[12],"can":[13,180],"each":[14,47],"succeed":[15],"or":[16,75],"fail":[17],"as":[18,49],"conditions":[20],"change.Rather":[21],"than":[22],"asking":[23],"large":[24],"language":[25],"models":[26,168],"to":[27,56,84,148],"directly":[28],"generate":[29],"actions,we":[31],"study":[32],"an":[33,38],"executable":[34,191],"decision":[35],"paradigm":[36],"where":[37,80],"agent":[39],"selects":[40,116],"from":[41,146],"a":[42,50,60,117,134],"library":[43],"of":[44],"programmatic":[45,65],"strategies,":[46],"implemented":[48],"code":[51],"module":[52],"mapping":[53],"observations":[55],"actions.We":[57],"propose":[58],"\\textbf{MetaPS},":[59],"simulation-guided":[61],"framework":[62],"for":[63,186],"adaptive":[64],"selection.":[67,193],"MetaPS":[68,105,140],"rolls":[69],"out":[70],"candidate":[71,113],"strategies":[72,82],"in":[73,163],"simulated":[74],"backtested":[76],"markets,":[77],"identifies":[78],"states":[79],"particular":[81],"lead":[83],"better":[85],"future":[86],"outcomes,":[87],"and":[88,112,121,133,158,183,190],"converts":[89],"these":[90],"state--strategy":[91],"pairs":[92],"into":[93],"supervised":[94],"fine-tuning":[95],"data.":[96],"During":[97],"inference,":[98],"the":[99,108,122,126],"simulator":[100],"is":[101],"no":[102],"longer":[103],"queried:":[104],"observes":[106],"only":[107],"current":[109],"state":[111],"context,":[115],"suitable":[118],"program,":[120],"selected":[123],"program":[124],"produces":[125],"final":[127],"action.":[128],"Experiments":[129],"on":[130],"multi-stock":[131],"trading":[132],"controlled":[135],"goods-exchange":[136],"sandbox":[137],"show":[138],"that":[139,177],"consistently":[141],"improves":[142],"across":[143],"model":[144],"scales":[145],"0.8B":[147],"9B":[149],"parameters.":[150],"It":[151],"outperforms":[152],"fixed-strategy":[153],"baselines,":[154],"direct":[155],"decision-making":[156],"agents,":[157],"prompted":[159],"API-based":[160],"LLM":[161],"agents;":[162],"several":[164],"settings,":[165],"compact":[166],"fine-tuned":[167],"even":[169],"surpass":[170],"stronger":[171],"API":[172],"models.":[173],"These":[174],"results":[175],"demonstrate":[176],"simulations":[179],"provide":[181],"scalable":[182],"targeted":[184],"supervision":[185],"learning":[187],"adaptive,":[188],"interpretable,":[189]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-24T00:00:00"}