{"id":"https://openalex.org/W4404577276","doi":"https://doi.org/10.1109/icmlca63499.2024.10753702","title":"Predicting Liquidity Coverage Ratio with Gated Recurrent Units: A Deep Learning Model for Risk Management","display_name":"Predicting Liquidity Coverage Ratio with Gated Recurrent Units: A Deep Learning Model for Risk Management","publication_year":2024,"publication_date":"2024-10-18","ids":{"openalex":"https://openalex.org/W4404577276","doi":"https://doi.org/10.1109/icmlca63499.2024.10753702"},"language":"en","primary_location":{"id":"doi:10.1109/icmlca63499.2024.10753702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlca63499.2024.10753702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Machine Learning and Computer Application (ICMLCA)","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/A5112109734","display_name":"Zhen Xu","orcid":"https://orcid.org/0009-0001-0603-9825"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhen Xu","raw_affiliation_strings":["Independent Researcher,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Independent Researcher,Shanghai,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jingming Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingming Pan","raw_affiliation_strings":["University of Pennsylvania,Philadelphia,USA"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania,Philadelphia,USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007507062","display_name":"Suji Han","orcid":"https://orcid.org/0000-0002-5460-7786"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siyuan Han","raw_affiliation_strings":["Columbia University,New York,USA"],"affiliations":[{"raw_affiliation_string":"Columbia University,New York,USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hongju Ouyang","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongju Ouyang","raw_affiliation_strings":["Columbia University,New York,USA"],"affiliations":[{"raw_affiliation_string":"Columbia University,New York,USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100400883","display_name":"Yuan Chen","orcid":"https://orcid.org/0000-0001-8799-7664"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuan Chen","raw_affiliation_strings":["Rice University,Houston,USA"],"affiliations":[{"raw_affiliation_string":"Rice University,Houston,USA","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"last","author":{"id":null,"display_name":"Mohan Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohan Jiang","raw_affiliation_strings":["New York University,New York,USA"],"affiliations":[{"raw_affiliation_string":"New York University,New York,USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5112109734"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.7472,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.98699432,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"108","last_page":"112"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.7174000144004822,"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"}},"topics":[{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.7174000144004822,"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":0.5753785371780396},{"id":"https://openalex.org/keywords/risk-management","display_name":"Risk management","score":0.5446920990943909},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5130494832992554},{"id":"https://openalex.org/keywords/market-liquidity","display_name":"Market liquidity","score":0.4971299469470978},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4279877841472626},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.33017414808273315},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.18662795424461365}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5753785371780396},{"id":"https://openalex.org/C32896092","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Risk management","level":2,"score":0.5446920990943909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5130494832992554},{"id":"https://openalex.org/C183582576","wikidata":"https://www.wikidata.org/wiki/Q184783","display_name":"Market liquidity","level":2,"score":0.4971299469470978},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4279877841472626},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.33017414808273315},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.18662795424461365}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlca63499.2024.10753702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlca63499.2024.10753702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Machine Learning and Computer Application (ICMLCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"With":[0],"the":[1,6,33,51,58,78,89,141,144],"global":[2],"economic":[3],"integration":[4],"and":[5,68,108,134],"high":[7],"interconnection":[8],"of":[9,75,143],"financial":[10,12,41,114,146],"markets,":[11],"institutions":[13,42,115],"are":[14],"facing":[15],"unprecedented":[16],"challenges,":[17],"especially":[18],"liquidity":[19,25,45,120],"risk.":[20],"This":[21,110],"paper":[22],"proposes":[23],"a":[24,73,117],"coverage":[26],"ratio":[27],"(LCR)":[28],"prediction":[29],"model":[30,59,91],"based":[31],"on":[32],"gated":[34],"recurrent":[35],"unit":[36],"(GRU)":[37],"network":[38,53],"to":[39,130,139],"help":[40],"manage":[43],"their":[44],"risk":[46,121],"more":[47,118,132],"effectively.":[48],"By":[49],"utilizing":[50],"GRU":[52,90],"in":[54,77,93,99],"deep":[55],"learning":[56],"technology,":[57],"can":[60],"automatically":[61],"learn":[62],"complex":[63],"patterns":[64],"from":[65],"historical":[66],"data":[67],"accurately":[69],"predict":[70],"LCR":[71],"for":[72,128],"period":[74],"time":[76],"future.":[79],"The":[80],"experimental":[81],"results":[82],"show":[83],"that":[84],"compared":[85],"with":[86,116],"traditional":[87],"methods,":[88],"proposed":[92],"this":[94],"study":[95],"shows":[96],"significant":[97],"advantages":[98],"mean":[100],"absolute":[101],"error":[102],"(MAE),":[103],"proving":[104],"its":[105],"higher":[106],"accuracy":[107],"robustness.":[109],"not":[111],"only":[112],"provides":[113,126],"reliable":[119],"management":[122],"tool":[123],"but":[124],"also":[125],"support":[127],"regulators":[129],"formulate":[131],"scientific":[133],"reasonable":[135],"policies,":[136],"which":[137],"helps":[138],"improve":[140],"stability":[142],"entire":[145],"system.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}