{"id":"https://openalex.org/W4416195614","doi":"https://doi.org/10.1145/3768292.3770338","title":"Interpretable Market Simulations via Optimal Transport: Power Law Decomposition and Implications for Market Design","display_name":"Interpretable Market Simulations via Optimal Transport: Power Law Decomposition and Implications for Market Design","publication_year":2025,"publication_date":"2025-11-14","ids":{"openalex":"https://openalex.org/W4416195614","doi":"https://doi.org/10.1145/3768292.3770338"},"language":null,"primary_location":{"id":"doi:10.1145/3768292.3770338","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3768292.3770338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM International Conference on AI in Finance","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/A5110117696","display_name":"Ryuji Hashimoto","orcid":"https://orcid.org/0009-0008-0042-1477"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryuji Hashimoto","raw_affiliation_strings":["Graduate School of Engineering, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0009-0008-0042-1477","affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044205949","display_name":"Kiyoshi Izumi","orcid":"https://orcid.org/0000-0003-0870-7310"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kiyoshi Izumi","raw_affiliation_strings":["Graduate School of Engineering, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-0870-7310","affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39837149,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"35","last_page":"43"},"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":0.9514999985694885,"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":0.9514999985694885,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.018799999728798866,"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/T10047","display_name":"Financial Markets and Investment Strategies","score":0.007899999618530273,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/financial-market","display_name":"Financial market","score":0.5285000205039978},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.4830000102519989},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4036000072956085},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.4016000032424927},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3840000033378601},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.37540000677108765},{"id":"https://openalex.org/keywords/market-power","display_name":"Market power","score":0.3433000147342682},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.33880001306533813}],"concepts":[{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6503999829292297},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.5587999820709229},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.5285000205039978},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.4830000102519989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41370001435279846},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4036000072956085},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4016000032424927},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3840000033378601},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.37540000677108765},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.3621000051498413},{"id":"https://openalex.org/C2775881736","wikidata":"https://www.wikidata.org/wiki/Q1274157","display_name":"Market power","level":3,"score":0.3433000147342682},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.33880001306533813},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3278999924659729},{"id":"https://openalex.org/C114118609","wikidata":"https://www.wikidata.org/wiki/Q3036837","display_name":"Market data","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.29190000891685486},{"id":"https://openalex.org/C2780021719","wikidata":"https://www.wikidata.org/wiki/Q282283","display_name":"Prediction market","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C64112148","wikidata":"https://www.wikidata.org/wiki/Q160151","display_name":"Market price","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2621000111103058}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3768292.3770338","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3768292.3770338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM International Conference on AI in Finance","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1537415400","https://openalex.org/W1642983364","https://openalex.org/W1975140694","https://openalex.org/W2019291268","https://openalex.org/W2019302713","https://openalex.org/W2021537912","https://openalex.org/W2048649579","https://openalex.org/W2050032417","https://openalex.org/W2057116804","https://openalex.org/W2097653633","https://openalex.org/W2100011707","https://openalex.org/W2121681609","https://openalex.org/W2122528211","https://openalex.org/W2125725371","https://openalex.org/W2129894886","https://openalex.org/W2133756959","https://openalex.org/W2153146814","https://openalex.org/W2162599984","https://openalex.org/W2169471158","https://openalex.org/W2273968408","https://openalex.org/W2617197422","https://openalex.org/W2619756347","https://openalex.org/W2621095836","https://openalex.org/W2973078842","https://openalex.org/W2987434780","https://openalex.org/W3122895822","https://openalex.org/W3124460636","https://openalex.org/W4206471589","https://openalex.org/W4255461888","https://openalex.org/W4319150720","https://openalex.org/W4387601546","https://openalex.org/W4388994224","https://openalex.org/W4388994325","https://openalex.org/W4393383830"],"related_works":[],"abstract_inverted_index":{"We":[0],"investigate":[1],"the":[2,5,28,77,80,117,161,174],"mechanisms":[3],"behind":[4],"power-law":[6,147],"distribution":[7],"of":[8,30,72,79,82,139,163,176],"stock":[9],"returns":[10],"using":[11,86,100],"artificial":[12,94],"market":[13,165],"simulations.":[14],"While":[15],"traditional":[16],"financial":[17,74,180],"theory":[18],"assumes":[19],"Gaussian":[20],"price":[21],"fluctuations,":[22],"empirical":[23,128],"studies":[24],"consistently":[25],"show":[26],"that":[27,136,150],"tails":[29],"return":[31],"distributions":[32],"follow":[33],"a":[34,83,105,142,168],"power":[35],"law.":[36],"Previous":[37],"research":[38],"has":[39],"proposed":[40,110],"hypotheses":[41],"for":[42],"this":[43,157],"phenomenon\u2014some":[44],"attributing":[45],"it":[46],"to":[47,51,63,122,155,171],"investor":[48],"behavior,":[49],"others":[50],"institutional":[52],"demand":[53],"imbalances.":[54],"However,":[55],"these":[56],"factors":[57],"have":[58],"rarely":[59],"been":[60],"modeled":[61],"together":[62],"assess":[64],"their":[65],"individual":[66],"and":[67,96,149,178],"joint":[68],"contributions.":[69],"The":[70,133],"complexity":[71],"real":[73],"markets":[75,95],"complicates":[76],"isolation":[78],"contribution":[81],"single":[84],"component":[85],"existing":[87],"data.":[88],"To":[89],"address":[90],"this,":[91],"we":[92],"construct":[93],"conduct":[97],"controlled":[98],"experiments":[99],"optimal":[101],"transport":[102],"(OT)":[103],"as":[104,167],"quantitative":[106],"similarity":[107],"measure.":[108],"Our":[109],"framework":[111],"incrementally":[112],"introduces":[113],"behavioral":[114],"components":[115,152],"into":[116],"agent":[118],"models,":[119],"allowing":[120],"us":[121],"compare":[123],"each":[124],"simulation":[125],"output":[126],"with":[127],"data":[129],"via":[130],"OT":[131],"distances.":[132],"results":[134],"highlight":[135],"informational":[137],"effect":[138],"prices":[140],"plays":[141],"dominant":[143],"role":[144],"in":[145,173],"reproducing":[146],"behavior":[148],"multiple":[151],"interact":[153],"synergistically":[154],"amplify":[156],"effect.":[158],"This":[159],"underscores":[160],"importance":[162],"indirect":[164],"impact":[166],"key":[169],"factor":[170],"consider":[172],"design":[175],"stable":[177],"resilient":[179],"markets.":[181]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-14T00:00:00"}