{"id":"https://openalex.org/W7172010647","doi":"https://doi.org/10.48550/arxiv.2607.28410","title":"Can Large Language Models Execute Parent Orders?","display_name":"Can Large Language Models Execute Parent Orders?","publication_year":2026,"publication_date":"2026-07-30","ids":{"openalex":"https://openalex.org/W7172010647","doi":"https://doi.org/10.48550/arxiv.2607.28410"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.28410","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.28410","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.2607.28410","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5144111680","display_name":"Zane Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Zane","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144133147","display_name":"Xinli Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Xinli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144173501","display_name":"Guangyi Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Guangyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144136045","display_name":"Jialong Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jialong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122304934","display_name":"Jinsong Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Jinsong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144159347","display_name":"Cong Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Cong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144113229","display_name":"Guibao Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Guibao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123889199","display_name":"Dongyu Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Dongyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144160070","display_name":"Luozhou Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Luozhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5144160886","display_name":"Zhen Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zhen","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/T10047","display_name":"Financial Markets and Investment Strategies","score":0.42320001125335693,"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"}},"topics":[{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.42320001125335693,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.37389999628067017,"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/T11674","display_name":"Sports Analytics and Performance","score":0.031199999153614044,"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/pace","display_name":"Pace","score":0.8212000131607056},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.5404999852180481},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.5177000164985657},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.48350000381469727},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.48330000042915344},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4733999967575073}],"concepts":[{"id":"https://openalex.org/C2777526511","wikidata":"https://www.wikidata.org/wiki/Q691543","display_name":"Pace","level":2,"score":0.8212000131607056},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6496999859809875},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.5404999852180481},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.5177000164985657},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.48350000381469727},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.48330000042915344},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4733999967575073},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3790999948978424},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.36500000953674316},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31349998712539673},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29660001397132874},{"id":"https://openalex.org/C109574028","wikidata":"https://www.wikidata.org/wiki/Q647525","display_name":"Behavioral economics","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.28410","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.28410","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.2607.28410","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.28410","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Parent-order":[0],"execution":[1,23,95,139,176],"is":[2,12],"a":[3,15,89],"core":[4],"problem":[5],"in":[6,37,73,175],"algorithmic":[7],"trading,":[8],"where":[9],"the":[10,55,69,127,156,164],"goal":[11],"to":[13,46,77,79,81],"split":[14],"large":[16,60],"order":[17],"into":[18,96],"smaller":[19],"orders":[20],"while":[21],"reducing":[22],"costs.":[24],"Existing":[25],"approaches":[26],"either":[27],"rely":[28],"on":[29,111],"pre-specified":[30],"market":[31,105],"assumptions":[32,106],"that":[33,43,92,118,136,169],"may":[34],"not":[35],"hold":[36],"practice,":[38],"or":[39],"require":[40],"task-specific":[41,108],"training":[42],"limits":[44],"adaptability":[45],"new":[47],"settings.":[48],"To":[49],"overcome":[50],"these":[51],"limitations,":[52],"we":[53],"present":[54],"first":[56],"systematic":[57],"study":[58],"of":[59,71],"language":[61],"models":[62],"(LLMs)":[63],"for":[64],"parent-order":[65,94],"execution.":[66],"This":[67],"extends":[68],"use":[70],"LLMs":[72,137,170],"finance":[74],"from":[75,142],"what":[76],"trade":[78],"how":[80],"execute.":[82],"We":[83],"propose":[84],"PACE":[85,119],"(Plan-Ahead":[86],"Controlled":[87],"Execution),":[88],"hierarchical":[90],"framework":[91],"decomposes":[93],"long-horizon":[97],"planning":[98],"and":[99,123,155],"short-horizon":[100],"execution,":[101],"requiring":[102],"neither":[103],"explicit":[104],"nor":[107],"training.":[109],"Experiments":[110],"Shenzhen":[112],"Stock":[113],"Exchange":[114],"Level-1":[115],"data":[116],"show":[117],"outperforms":[120],"TWAP,":[121],"Almgren-Chriss,":[122],"learning-based":[124],"baselines,":[125],"exceeding":[126],"strongest":[128],"baseline":[129],"by":[130],"0.65":[131],"bps.":[132],"Behavioral":[133],"analysis":[134],"reveals":[135],"make":[138],"decisions":[140],"differently":[141],"human":[143,173],"investors:":[144],"higher":[145],"model":[146,157],"confidence":[147],"predicts":[148],"better":[149],"performance":[150],"rather":[151,160],"than":[152,161],"worse":[153],"returns,":[154],"trades":[158],"earlier":[159],"procrastinating":[162],"toward":[163],"deadline.":[165],"These":[166],"findings":[167],"suggest":[168],"can":[171],"complement":[172],"traders":[174],"decisions.":[177]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2026-08-01T00:00:00"}
