{"id":"https://openalex.org/W7140870794","doi":"https://doi.org/10.1109/access.2026.3678064","title":"An End-to-End Deep Learning Model for Clustering-Based Statistical Arbitrage","display_name":"An End-to-End Deep Learning Model for Clustering-Based Statistical Arbitrage","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7140870794","doi":"https://doi.org/10.1109/access.2026.3678064"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3678064","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3678064","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3678064","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130717822","display_name":"Hyunju Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyunju Lee","raw_affiliation_strings":["Department of Industrial Engineering, Seoul National University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0007-6160-099X","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129788126","display_name":"Woojin Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Woojin Chang","raw_affiliation_strings":["Department of Industrial Engineering, Seoul National University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0001-5164-973X","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5130717822"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59530377,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"47301","last_page":"47318"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.060600001364946365,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.060600001364946365,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.057999998331069946,"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.0551999993622303,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6938999891281128},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4235000014305115},{"id":"https://openalex.org/keywords/statistical-learning","display_name":"Statistical learning","score":0.3953000009059906},{"id":"https://openalex.org/keywords/arbitrage","display_name":"Arbitrage","score":0.3682999908924103},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.34220001101493835}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6938999891281128},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6284999847412109},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6111999750137329},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4235000014305115},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.3953000009059906},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.39320001006126404},{"id":"https://openalex.org/C160623529","wikidata":"https://www.wikidata.org/wiki/Q273088","display_name":"Arbitrage","level":2,"score":0.3682999908924103},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32739999890327454},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.2809000015258789}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3678064","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3678064","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:51e66774cb424e6584b5fc54e261bbd0","is_oa":true,"landing_page_url":"https://doaj.org/article/51e66774cb424e6584b5fc54e261bbd0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 47301-47318 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3678064","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3678064","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W2097880690","https://openalex.org/W2149558700","https://openalex.org/W2276162781","https://openalex.org/W2342352817","https://openalex.org/W2582533304","https://openalex.org/W2809373714","https://openalex.org/W2883143933","https://openalex.org/W2912400541","https://openalex.org/W2914318589","https://openalex.org/W2937024709","https://openalex.org/W2943763361","https://openalex.org/W2988746083","https://openalex.org/W3008413283","https://openalex.org/W3021475001","https://openalex.org/W3030465810","https://openalex.org/W3043476515","https://openalex.org/W3121617283","https://openalex.org/W3122010751","https://openalex.org/W3122035786","https://openalex.org/W3124586629","https://openalex.org/W3177380395","https://openalex.org/W3194738551","https://openalex.org/W3214832881","https://openalex.org/W4205288333","https://openalex.org/W4221041661","https://openalex.org/W4224220755","https://openalex.org/W4256431242","https://openalex.org/W4285327283","https://openalex.org/W4285402398","https://openalex.org/W4293056416","https://openalex.org/W4294691340","https://openalex.org/W4297433024","https://openalex.org/W4300619693","https://openalex.org/W4302362891","https://openalex.org/W4312450127","https://openalex.org/W4321241641","https://openalex.org/W4360610769","https://openalex.org/W4362503992","https://openalex.org/W4384459953","https://openalex.org/W4384518871","https://openalex.org/W4388994545","https://openalex.org/W4389272391","https://openalex.org/W4389678176","https://openalex.org/W4391070735","https://openalex.org/W4410031102"],"related_works":[],"abstract_inverted_index":{"We":[0,56],"propose":[1],"an":[2,140],"end-to-end":[3,194],"deep":[4],"learning":[5],"framework":[6],"for":[7,53,148],"statistical":[8,116,204],"arbitrage":[9,25,65,78,93],"in":[10,201],"the":[11,60,73,111,122,155,183,193,197],"crypto-currency":[12],"futures":[13],"market,":[14,40],"which":[15],"integrates":[16],"clustering":[17,58],"and":[18,47,76,139,196],"trading":[19,66],"within":[20,72],"a":[21,105,134],"unified":[22],"structure.":[23],"Statistical":[24],"seeks":[26],"to":[27,34,62,85,98,170],"exploit":[28],"price":[29],"deviations":[30],"among":[31,45,89],"similar":[32],"assets":[33,46],"generate":[35],"market-neutral":[36,177],"profits.":[37],"The":[38,91],"cryptocurrency":[39,74],"characterized":[41],"by":[42],"structural":[43],"similarities":[44],"market":[48,75,161],"inefficiency,":[49],"offers":[50],"promising":[51],"opportunities":[52],"such":[54,190],"strategies.":[55],"incorporate":[57],"into":[59],"model":[61,86,124,188],"learn":[63],"optimal":[64],"strategies":[67,128],"that":[68,109,121,154],"capture":[69],"dynamic":[70],"relationships":[71],"detect":[77],"opportunities.":[79],"A":[80],"transformer":[81],"encoder":[82],"is":[83,101],"employed":[84],"temporal":[87],"dependencies":[88],"assets.":[90],"entire":[92],"process":[94],"from":[95,168],"portfolio":[96],"selection":[97],"trade":[99],"allocation":[100],"jointly":[102],"optimized":[103],"under":[104],"customized":[106],"objective":[107,199],"function":[108],"reflects":[110],"core":[112],"principles":[113],"of":[114,137,144,186],"traditional":[115],"arbitrage.":[117,205],"Empirical":[118],"results":[119],"demonstrate":[120],"proposed":[123,198],"consistently":[125],"outperforms":[126],"benchmark":[127],"with":[129,163,172],"negative":[130],"Sharpe":[131,142,165],"ratios,":[132],"achieving":[133],"cumulative":[135],"return":[136],"3.310":[138],"annualized":[141,164],"ratio":[143],"2.516":[145],"after":[146],"accounting":[147],"transaction":[149,173],"costs.":[150],"Sub-period":[151],"analysis":[152],"shows":[153],"strategy":[156],"remains":[157],"robust":[158],"across":[159],"varying":[160],"conditions":[162],"ratios":[166],"ranging":[167],"1.168":[169],"2.240":[171],"fees,":[174],"supporting":[175],"its":[176],"characteristics.":[178],"Ablation":[179],"studies":[180],"further":[181],"validate":[182],"crucial":[184],"contribution":[185],"each":[187],"component,":[189],"as":[191],"clustering,":[192],"structure,":[195],"function,":[200],"enabling":[202],"effective":[203]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-03-27T00:00:00"}
