{"id":"https://openalex.org/W7148255196","doi":"https://doi.org/10.48550/arxiv.2604.00195","title":"L\u00e9vy-Flow Models: Heavy-Tail-Aware Normalizing Flows for Financial Risk Management","display_name":"L\u00e9vy-Flow Models: Heavy-Tail-Aware Normalizing Flows for Financial Risk Management","publication_year":2026,"publication_date":"2026-03-31","ids":{"openalex":"https://openalex.org/W7148255196","doi":"https://doi.org/10.48550/arxiv.2604.00195"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.00195","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00195","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.00195","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061208871","display_name":"Rachid Drissi","orcid":"https://orcid.org/0000-0003-0564-0181"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Drissi, Rachid","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5061208871"],"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/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.32330000400543213,"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/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.32330000400543213,"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/T11720","display_name":"Probability and Risk Models","score":0.23829999566078186,"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/T10067","display_name":"Stochastic processes and financial applications","score":0.11010000109672546,"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/gaussian","display_name":"Gaussian","score":0.5113000273704529},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4440000057220459},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4375999867916107},{"id":"https://openalex.org/keywords/variance-gamma-distribution","display_name":"Variance-gamma distribution","score":0.43369999527931213},{"id":"https://openalex.org/keywords/risk-management","display_name":"Risk management","score":0.39100000262260437},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.3880999982357025},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.36570000648498535},{"id":"https://openalex.org/keywords/l\u00e9vy-process","display_name":"L\u00e9vy process","score":0.353300005197525},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.3447999954223633}],"concepts":[{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5823000073432922},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.567300021648407},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5113000273704529},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4440000057220459},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4375999867916107},{"id":"https://openalex.org/C30084815","wikidata":"https://www.wikidata.org/wiki/Q4390268","display_name":"Variance-gamma distribution","level":4,"score":0.43369999527931213},{"id":"https://openalex.org/C32896092","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Risk management","level":2,"score":0.39100000262260437},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.3880999982357025},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3878999948501587},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.36570000648498535},{"id":"https://openalex.org/C88757350","wikidata":"https://www.wikidata.org/wiki/Q1557613","display_name":"L\u00e9vy process","level":2,"score":0.353300005197525},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C76073288","wikidata":"https://www.wikidata.org/wiki/Q1337875","display_name":"Financial risk","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C102094743","wikidata":"https://www.wikidata.org/wiki/Q133871","display_name":"Normal distribution","level":2,"score":0.3125},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.31040000915527344},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3073999881744385},{"id":"https://openalex.org/C5496284","wikidata":"https://www.wikidata.org/wiki/Q5420856","display_name":"Expected shortfall","level":3,"score":0.305400013923645},{"id":"https://openalex.org/C132878287","wikidata":"https://www.wikidata.org/wiki/Q1671727","display_name":"Inverse Gaussian distribution","level":3,"score":0.30469998717308044},{"id":"https://openalex.org/C149717495","wikidata":"https://www.wikidata.org/wiki/Q117806","display_name":"Gamma distribution","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C94128290","wikidata":"https://www.wikidata.org/wiki/Q963287","display_name":"Value at risk","level":3,"score":0.2921000123023987},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C10390562","wikidata":"https://www.wikidata.org/wiki/Q581809","display_name":"Spline (mechanical)","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C165216359","wikidata":"https://www.wikidata.org/wiki/Q670653","display_name":"Marginal distribution","level":3,"score":0.26010000705718994},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.00195","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00195","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.00195","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00195","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":false,"raw_source_name":null,"raw_type":"article"},"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":[0,43],"introduce":[1],"L\u00e9vy-Flows,":[2],"a":[3],"class":[4],"of":[5],"normalizing":[6,141],"flow":[7,64],"models":[8],"that":[9,51,67,135],"replace":[10],"the":[11,56,74,81,126],"standard":[12],"Gaussian":[13,26,114],"base":[14,75],"distribution":[15],"with":[16,150],"L\u00e9vy":[17,137],"process-based":[18],"distributions,":[19],"specifically":[20],"Variance":[21],"Gamma":[22],"(VG)":[23],"and":[24,39,66,92,101,116],"Normal-Inverse":[25],"(NIG).":[27],"These":[28,132],"distributions":[29],"naturally":[30],"capture":[31],"heavy-tailed":[32,148],"behavior":[33],"while":[34,122],"preserving":[35],"exact":[36,118],"likelihood":[37],"evaluation":[38],"efficient":[40],"reparameterized":[41],"sampling.":[42],"establish":[44],"theoretical":[45],"guarantees":[46],"on":[47,87],"tail":[48,57,77],"behavior,":[49],"showing":[50],"for":[52],"regularly":[53],"varying":[54],"bases":[55],"index":[58],"is":[59],"preserved":[60],"under":[61],"asymptotically":[62],"linear":[63],"transformations,":[65],"identity-tail":[68],"Neural":[69],"Spline":[70],"Flow":[71],"architectures":[72],"preserve":[73],"distribution's":[76],"shape":[78],"exactly":[79],"outside":[80],"transformation":[82],"region.":[83],"Empirically,":[84],"we":[85],"evaluate":[86],"S&amp;P":[88],"500":[89],"daily":[90],"returns":[91],"additional":[93],"assets,":[94],"demonstrating":[95],"substantial":[96],"improvements":[97],"in":[98,146],"density":[99],"estimation":[100],"risk":[102,154],"calibration.":[103],"VG-based":[104],"flows":[105,115,124,142],"reduce":[106],"test":[107],"negative":[108],"log-likelihood":[109],"by":[110],"69%":[111],"relative":[112],"to":[113,152],"achieve":[117],"95%":[119],"VaR":[120],"calibration,":[121],"NIG-based":[123],"provide":[125],"most":[127],"accurate":[128],"Expected":[129],"Shortfall":[130],"estimates.":[131],"results":[133],"show":[134],"incorporating":[136],"process":[138],"structure":[139],"into":[140],"yields":[143],"significant":[144],"gains":[145],"modeling":[147],"data,":[149],"applications":[151],"financial":[153],"management.":[155]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-04-03T00:00:00"}
