{"id":"https://openalex.org/W7163034806","doi":"https://doi.org/10.48550/arxiv.2605.30363","title":"Enhancing Regime Shift Detection Using Unstructured Data: A Study on the Treasury Market","display_name":"Enhancing Regime Shift Detection Using Unstructured Data: A Study on the Treasury Market","publication_year":2026,"publication_date":"2026-05-17","ids":{"openalex":"https://openalex.org/W7163034806","doi":"https://doi.org/10.48550/arxiv.2605.30363"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30363","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30363","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.2605.30363","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137585825","display_name":"Mingxuan Yi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi, Mingxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137592511","display_name":"Vidal Mehra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mehra, Vidal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137534447","display_name":"Jing Chen","orcid":"https://orcid.org/0000-0002-2453-765X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125755561","display_name":"John Cartlidge","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cartlidge, John","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/T11326","display_name":"Stock Market Forecasting Methods","score":0.3849000036716461,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.3849000036716461,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.06430000066757202,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T13702","display_name":"Machine Learning in Healthcare","score":0.06040000170469284,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6021999716758728},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5698999762535095},{"id":"https://openalex.org/keywords/treasury","display_name":"Treasury","score":0.5178999900817871},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.4595000147819519},{"id":"https://openalex.org/keywords/financial-market","display_name":"Financial market","score":0.37549999356269836},{"id":"https://openalex.org/keywords/regime-shift","display_name":"Regime shift","score":0.3573000133037567},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.3395000100135803},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.32989999651908875},{"id":"https://openalex.org/keywords/vector-autoregression","display_name":"Vector autoregression","score":0.32600000500679016}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6021999716758728},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5734000205993652},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5698999762535095},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5461999773979187},{"id":"https://openalex.org/C2780889827","wikidata":"https://www.wikidata.org/wiki/Q10756188","display_name":"Treasury","level":2,"score":0.5178999900817871},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.4595000147819519},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.4424999952316284},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.37549999356269836},{"id":"https://openalex.org/C2780893879","wikidata":"https://www.wikidata.org/wiki/Q7308372","display_name":"Regime shift","level":3,"score":0.3573000133037567},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.32989999651908875},{"id":"https://openalex.org/C133029050","wikidata":"https://www.wikidata.org/wiki/Q385593","display_name":"Vector autoregression","level":2,"score":0.32600000500679016},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3206000030040741},{"id":"https://openalex.org/C126285488","wikidata":"https://www.wikidata.org/wiki/Q178476","display_name":"Monetary policy","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.31439998745918274},{"id":"https://openalex.org/C166955791","wikidata":"https://www.wikidata.org/wiki/Q629579","display_name":"Macro","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C139819358","wikidata":"https://www.wikidata.org/wiki/Q462748","display_name":"Asset allocation","level":3,"score":0.31049999594688416},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C183582576","wikidata":"https://www.wikidata.org/wiki/Q184783","display_name":"Market liquidity","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C2780093650","wikidata":"https://www.wikidata.org/wiki/Q1673271","display_name":"Regime change","level":4,"score":0.28130000829696655},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C76178495","wikidata":"https://www.wikidata.org/wiki/Q4808784","display_name":"Asset (computer security)","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C43540301","wikidata":"https://www.wikidata.org/wiki/Q689971","display_name":"Paradigm shift","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30363","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30363","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.2605.30363","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30363","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":{"Regime":[0],"shifts":[1,65],"in":[2,69,203],"financial":[3,95,204],"markets":[4],"reorganise":[5],"the":[6,27,36,133,195],"joint":[7],"dynamics":[8],"of":[9,165,199],"asset":[10],"prices":[11],"and":[12,32,55,145,174,197],"macro":[13],"variables,":[14],"breaking":[15],"any":[16],"single-regime":[17],"calibration.":[18],"They":[19],"are":[20,104,123],"nonetheless":[21],"difficult":[22],"to":[23],"detect":[24],"reliably":[25],"because":[26],"data":[28,54],"signal":[29,64],"is":[30,42,100],"noisy":[31],"heavily":[33],"multicollinear,":[34],"while":[35,116],"contemporaneous":[37],"text":[38,129,189],"that":[39,80,185],"announces":[40],"them":[41],"unstructured.":[43],"Standard":[44],"regime":[45,76,121,167,200],"shift":[46,77,201],"detection":[47,78,172,193],"methods":[48],"rely":[49],"solely":[50],"on":[51,93,111,135],"structured":[52],"time-series":[53],"ignore":[56],"policy":[57,188],"communications,":[58],"even":[59],"though":[60],"these":[61],"texts":[62],"often":[63],"before":[66],"they":[67],"materialise":[68],"observed":[70],"prices.":[71],"We":[72,131],"propose":[73],"a":[74,107,112,126,141,161],"text-enhanced":[75],"pipeline":[79,155],"combines":[81],"large":[82],"language":[83],"model":[84],"(LLM)":[85],"reasoning":[86],"over":[87],"central-bank":[88],"communications":[89],"with":[90,140,169,190],"statistical":[91,191],"validation":[92],"multivariate":[94],"time":[96],"series.":[97],"The":[98,153,182],"framework":[99,134],"detector-agnostic:":[101],"text-proposed":[102],"candidates":[103,118],"validated":[105],"using":[106,148],"bootstrap":[108],"likelihood-ratio":[109],"test":[110],"vector":[113],"autoregression":[114],"(VAR),":[115],"data-driven":[117,151,180],"from":[119],"arbitrary":[120],"detectors":[122],"ratified":[124],"through":[125],"lenient":[127],"LLM":[128],"check.":[130],"evaluate":[132],"2010-2024":[136],"FOMC":[137],"minutes":[138],"paired":[139],"14-variable":[142],"U.S.":[143],"Treasury":[144],"macroeconomic":[146],"panel,":[147],"four":[149],"interchangeable":[150],"detectors.":[152],"proposed":[154],"achieves":[156],"F1":[157],"=":[158],"0.82":[159],"against":[160],"verified":[162],"anchor":[163],"list":[164],"monetary-policy":[166],"shifts,":[168],"same-day":[170],"modal":[171],"latency":[173],"consistently":[175],"stronger":[176],"performance":[177],"than":[178],"pure":[179],"baselines.":[181],"results":[183],"demonstrate":[184],"combining":[186],"unstructured":[187],"structural-break":[192],"improves":[194],"robustness":[196],"interpretability":[198],"identification":[202],"markets.":[205]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-02T00:00:00"}