{"id":"https://openalex.org/W4387929241","doi":"https://doi.org/10.1145/3604237.3626870","title":"Co-Training Realized Volatility Prediction Model with Neural Distributional Transformation","display_name":"Co-Training Realized Volatility Prediction Model with Neural Distributional Transformation","publication_year":2023,"publication_date":"2023-11-25","ids":{"openalex":"https://openalex.org/W4387929241","doi":"https://doi.org/10.1145/3604237.3626870"},"language":"en","primary_location":{"id":"doi:10.1145/3604237.3626870","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3604237.3626870","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"4th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2310.14536","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101855903","display_name":"Xin Du","orcid":"https://orcid.org/0000-0001-9135-2906"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xin Du","raw_affiliation_strings":["Tanaka-Ishii Laboratory, Waseda University, Japan"],"raw_orcid":"https://orcid.org/0000-0001-9135-2906","affiliations":[{"raw_affiliation_string":"Tanaka-Ishii Laboratory, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072664860","display_name":"K. Moriyama","orcid":"https://orcid.org/0009-0007-0530-2082"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kai Moriyama","raw_affiliation_strings":["Tanaka-Ishii Laboratory, Waseda University, Japan"],"raw_orcid":"https://orcid.org/0009-0007-0530-2082","affiliations":[{"raw_affiliation_string":"Tanaka-Ishii Laboratory, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073822077","display_name":"Kumiko Tanaka\u2010Ishii","orcid":"https://orcid.org/0000-0003-1752-3951"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kumiko Tanaka-Ishii","raw_affiliation_strings":["Tanaka-Ishii Laboratory, Waseda University, Japan"],"raw_orcid":"https://orcid.org/0000-0003-1752-3951","affiliations":[{"raw_affiliation_string":"Tanaka-Ishii Laboratory, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"418","last_page":"426"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9993000030517578,"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":0.9993000030517578,"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/T11059","display_name":"Market Dynamics and Volatility","score":0.9991999864578247,"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":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6994900107383728},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.6355807781219482},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.585471510887146},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5579355955123901},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5033456683158875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5007753372192383},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5007286071777344},{"id":"https://openalex.org/keywords/invertible-matrix","display_name":"Invertible matrix","score":0.49571001529693604},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.48243507742881775},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.41441023349761963},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39262425899505615},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3778374493122101},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37197059392929077},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34296920895576477},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.2830643951892853}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6994900107383728},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.6355807781219482},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.585471510887146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5579355955123901},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5033456683158875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5007753372192383},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5007286071777344},{"id":"https://openalex.org/C96442724","wikidata":"https://www.wikidata.org/wiki/Q242188","display_name":"Invertible matrix","level":2,"score":0.49571001529693604},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.48243507742881775},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.41441023349761963},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39262425899505615},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3778374493122101},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37197059392929077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34296920895576477},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2830643951892853},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3604237.3626870","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3604237.3626870","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"4th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2310.14536","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.14536","pdf_url":"https://arxiv.org/pdf/2310.14536","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:RePEc:arx:papers:2310.14536","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2310.14536","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.14536","pdf_url":"https://arxiv.org/pdf/2310.14536","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2725189110","display_name":null,"funder_award_id":"21H03493, 20K20492","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G3758391561","display_name":null,"funder_award_id":"JP21H03493","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7861004958","display_name":null,"funder_award_id":"JP20K20492","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387929241.pdf","grobid_xml":"https://content.openalex.org/works/W4387929241.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W129305155","https://openalex.org/W1507378142","https://openalex.org/W1522301498","https://openalex.org/W1583912456","https://openalex.org/W1598869432","https://openalex.org/W1788744250","https://openalex.org/W1964233058","https://openalex.org/W1979575715","https://openalex.org/W1985198035","https://openalex.org/W2007321142","https://openalex.org/W2012748001","https://openalex.org/W2019960288","https://openalex.org/W2049633694","https://openalex.org/W2055781590","https://openalex.org/W2070792261","https://openalex.org/W2076209196","https://openalex.org/W2082137964","https://openalex.org/W2083402998","https://openalex.org/W2090637028","https://openalex.org/W2122528211","https://openalex.org/W2134477639","https://openalex.org/W2146134639","https://openalex.org/W2146270957","https://openalex.org/W2157403008","https://openalex.org/W2161125443","https://openalex.org/W2164062516","https://openalex.org/W2169471158","https://openalex.org/W2280053103","https://openalex.org/W2320881454","https://openalex.org/W2440397453","https://openalex.org/W2514394181","https://openalex.org/W2747329762","https://openalex.org/W2963090522","https://openalex.org/W2963755523","https://openalex.org/W2989193306","https://openalex.org/W3007636763","https://openalex.org/W3121857437","https://openalex.org/W3122660707","https://openalex.org/W3124732950","https://openalex.org/W3124749346","https://openalex.org/W3125016575","https://openalex.org/W3125246470","https://openalex.org/W3156436918","https://openalex.org/W4236064375","https://openalex.org/W4250389103","https://openalex.org/W4320930577","https://openalex.org/W4388090621"],"related_works":["https://openalex.org/W4220715471","https://openalex.org/W4295035285","https://openalex.org/W4200022986","https://openalex.org/W2963637926","https://openalex.org/W3130734945","https://openalex.org/W2019890371","https://openalex.org/W2048140462","https://openalex.org/W4388542635","https://openalex.org/W1964286703","https://openalex.org/W2947936036"],"abstract_inverted_index":{"This":[0,68],"paper":[1,69],"shows":[2],"a":[3,14,30,41,51,84,118],"novel":[4],"machine":[5],"learning":[6],"model":[7],"for":[8],"realized":[9],"volatility":[10],"(RV)":[11],"prediction":[12,52,66,78,96],"using":[13,113,129],"normalizing":[15],"flow,":[16],"an":[17,45,114],"invertible":[18],"neural":[19],"network.":[20],"Since":[21],"RV":[22,36,101],"is":[23,58,89,110],"known":[24],"to":[25,71],"be":[26],"skewed":[27],"and":[28,48,60,76],"have":[29],"fat":[31],"tail,":[32],"previous":[33],"methods":[34,128],"transform":[35],"into":[37],"values":[38],"that":[39,56,88,94],"follow":[40],"latent":[42],"distribution":[43],"with":[44],"explicit":[46],"shape":[47,57],"then":[49],"apply":[50],"model.":[53,67,79],"However,":[54],"knowing":[55],"non-trivial,":[59],"the":[61,65,74,77,92,95,99],"transformation":[62,75],"result":[63],"influences":[64],"proposes":[70],"jointly":[72],"train":[73],"The":[80,107],"training":[81],"process":[82],"follows":[83],"maximum-likelihood":[85],"objective":[86,108],"function":[87,109],"derived":[90],"from":[91],"assumption":[93],"residuals":[97],"on":[98],"transformed":[100],"time":[102],"series":[103],"are":[104],"homogeneously":[105],"Gaussian.":[106],"further":[111],"approximated":[112],"expectation\u2013maximum":[115],"algorithm.":[116],"On":[117],"dataset":[119],"of":[120],"100":[121],"stocks,":[122],"our":[123],"method":[124],"significantly":[125],"outperforms":[126],"other":[127],"analytical":[130],"or":[131],"na\u00efve":[132],"neural-network":[133],"transformations.":[134]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}