{"id":"https://openalex.org/W4415918879","doi":"https://doi.org/10.48550/arxiv.2510.27334","title":"When AI Trading Agents Compete: Adverse Selection of Meta-Orders by Reinforcement Learning-Based Market Making","display_name":"When AI Trading Agents Compete: Adverse Selection of Meta-Orders by Reinforcement Learning-Based Market Making","publication_year":2025,"publication_date":"2025-10-31","ids":{"openalex":"https://openalex.org/W4415918879","doi":"https://doi.org/10.48550/arxiv.2510.27334"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2510.27334","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.27334","pdf_url":"https://arxiv.org/pdf/2510.27334","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":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/2510.27334","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120266767","display_name":"Ali Raza Jafree","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jafree, Ali Raza","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086469887","display_name":"Konark Jain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jain, Konark","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5051759229","display_name":"Nick Firoozye","orcid":"https://orcid.org/0000-0002-6460-0406"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Firoozye, Nick","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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.1168999969959259,"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":0.1168999969959259,"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":0.1006999984383583,"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/T11513","display_name":"stochastic dynamics and bifurcation","score":0.09449999779462814,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7663000226020813},{"id":"https://openalex.org/keywords/replicate","display_name":"Replicate","score":0.6966000199317932},{"id":"https://openalex.org/keywords/adverse-selection","display_name":"Adverse selection","score":0.6194999814033508},{"id":"https://openalex.org/keywords/market-maker","display_name":"Market maker","score":0.4900999963283539},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.4595000147819519},{"id":"https://openalex.org/keywords/algorithmic-trading","display_name":"Algorithmic trading","score":0.43220001459121704},{"id":"https://openalex.org/keywords/agent-based-model","display_name":"Agent-based model","score":0.40139999985694885}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7663000226020813},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.6966000199317932},{"id":"https://openalex.org/C32252159","wikidata":"https://www.wikidata.org/wiki/Q380037","display_name":"Adverse selection","level":2,"score":0.6194999814033508},{"id":"https://openalex.org/C18991353","wikidata":"https://www.wikidata.org/wiki/Q1137319","display_name":"Market maker","level":4,"score":0.4900999963283539},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47850000858306885},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.4595000147819519},{"id":"https://openalex.org/C78508483","wikidata":"https://www.wikidata.org/wiki/Q139445","display_name":"Algorithmic trading","level":2,"score":0.43220001459121704},{"id":"https://openalex.org/C2780873155","wikidata":"https://www.wikidata.org/wiki/Q392811","display_name":"Agent-based model","level":2,"score":0.40139999985694885},{"id":"https://openalex.org/C24683644","wikidata":"https://www.wikidata.org/wiki/Q138372","display_name":"High-frequency trading","level":3,"score":0.3781000077724457},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3765999972820282},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.37599998712539673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35580000281333923},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.33660000562667847},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C2779309563","wikidata":"https://www.wikidata.org/wiki/Q649206","display_name":"Order book","level":3,"score":0.3156000077724457},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.3107999861240387},{"id":"https://openalex.org/C51926234","wikidata":"https://www.wikidata.org/wiki/Q3312426","display_name":"Market microstructure","level":3,"score":0.2842000126838684},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2510.27334","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.27334","pdf_url":"https://arxiv.org/pdf/2510.27334","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2510.27334","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.27334","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.27334","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.27334","pdf_url":"https://arxiv.org/pdf/2510.27334","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":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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,16],"investigate":[1],"the":[2,33,42,50,63,70,74,83,87,107,119,125,144,149,158,163,192,214,225],"mechanisms":[3],"by":[4,12,162,179,196],"which":[5],"medium-frequency":[6,171,197],"trading":[7,128,181,185],"agents":[8],"are":[9,173,199],"adversely":[10],"selected":[11],"opportunistic":[13],"high-frequency":[14,36,88,180,184],"traders.":[15],"use":[17],"reinforcement":[18,96],"learning":[19,97],"(RL)":[20],"within":[21],"a":[22,130,136],"Hawkes":[23,51],"Limit":[24],"Order":[25],"Book":[26],"(LOB)":[27],"model":[28,52],"in":[29,82,106],"order":[30],"to":[31,41,155,176,187,201],"replicate":[32,118],"behaviours":[34],"of":[35,62,73],"market":[37,64,75,89,151,215],"makers.":[38],"In":[39],"contrast":[40],"classical":[43],"models":[44],"with":[45,141],"exogenous":[46],"price":[47,56,159],"impact":[48,57],"assumptions,":[49],"accounts":[53],"for":[54,79,213,224],"endogenous":[55],"and":[58,114,138],"other":[59],"key":[60],"properties":[61],"(Jain":[65,99],"et":[66,100],"al.":[67,101],"2024a).":[68],"Given":[69],"real-world":[71],"impracticalities":[72],"maker":[76],"updating":[77],"strategies":[78],"every":[80],"event":[81],"LOB,":[84],"we":[85,123,206],"formulate":[86],"making":[90,152,216],"agent":[91,127,153,218],"via":[92],"an":[93],"impulse":[94],"control":[95],"framework":[98],"2025).":[102],"The":[103],"RL":[104,126,150,217],"used":[105],"simulation":[108],"utilises":[109],"Proximal":[110],"Policy":[111],"Optimisation":[112],"(PPO)":[113],"self-imitation":[115],"learning.":[116],"To":[117],"adverse":[120,177],"selection":[121,178],"phenomenon,":[122],"test":[124],"against":[129,143],"medium":[131],"frequency":[132],"trader":[133],"(MFT)":[134],"executing":[135],"meta-order":[137,146],"demonstrate":[139],"that,":[140],"training":[142],"MFT":[145,226],"execution":[147],"agent,":[148],"learns":[154],"capitalise":[156],"on":[157],"drift":[160],"induced":[161],"meta-order.":[164],"Recent":[165],"empirical":[166],"studies":[167],"have":[168],"shown":[169],"that":[170,210],"traders":[172,198],"increasingly":[174],"subject":[175],"agents.":[182],"As":[183],"continues":[186],"proliferate":[188],"across":[189],"financial":[190],"markets,":[191],"slippage":[193],"costs":[194],"incurred":[195],"likely":[200],"increase":[202],"over":[203],"time.":[204],"However,":[205],"do":[207],"not":[208],"observe":[209],"increased":[211,222],"profits":[212],"necessarily":[219],"cause":[220],"significantly":[221],"slippages":[223],"agent.":[227]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-11-05T00:00:00"}
