{"id":"https://openalex.org/W4410887149","doi":"https://doi.org/10.1109/iscbi64586.2025.11015406","title":"End-to-End Robust Portfolio Optimization with Neural Network","display_name":"End-to-End Robust Portfolio Optimization with Neural Network","publication_year":2025,"publication_date":"2025-02-14","ids":{"openalex":"https://openalex.org/W4410887149","doi":"https://doi.org/10.1109/iscbi64586.2025.11015406"},"language":"en","primary_location":{"id":"doi:10.1109/iscbi64586.2025.11015406","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscbi64586.2025.11015406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 7th International Symposium on Computational and Business Intelligence (ISCBI)","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/A5039897396","display_name":"Hongbo Sun","orcid":"https://orcid.org/0009-0008-7272-7205"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongbo Sun","raw_affiliation_strings":["University of Chinese Academy of Sciences China,School of Mathematical Sciences"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences China,School of Mathematical Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055992274","display_name":"Cuicui Luo","orcid":"https://orcid.org/0000-0002-4570-5990"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cuicui Luo","raw_affiliation_strings":["University of Chinese Academy of Sciences,International College,China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,International College,China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051840580","display_name":"Hamid R. Arian","orcid":"https://orcid.org/0000-0002-4624-9421"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hamid Arian","raw_affiliation_strings":["York University,School of Administrative Studies,Canada"],"affiliations":[{"raw_affiliation_string":"York University,School of Administrative Studies,Canada","institution_ids":["https://openalex.org/I192455969"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5039897396"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18095063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"46","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11801","display_name":"Reservoir Engineering and Simulation Methods","score":0.9765999913215637,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11801","display_name":"Reservoir Engineering and Simulation Methods","score":0.9765999913215637,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10067","display_name":"Stochastic processes and financial applications","score":0.9449999928474426,"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/T11413","display_name":"Risk and Portfolio Optimization","score":0.9243999719619751,"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/end-to-end-principle","display_name":"End-to-end principle","score":0.6414368152618408},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5628592371940613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5576493144035339},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.4630454182624817},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2703869044780731},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.19361117482185364},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.05984950065612793}],"concepts":[{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.6414368152618408},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5628592371940613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5576493144035339},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.4630454182624817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2703869044780731},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.19361117482185364},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.05984950065612793}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscbi64586.2025.11015406","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscbi64586.2025.11015406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 7th International Symposium on Computational and Business Intelligence (ISCBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1990275757","https://openalex.org/W2003777645","https://openalex.org/W2084575717","https://openalex.org/W2087009359","https://openalex.org/W2089105401","https://openalex.org/W2134919172","https://openalex.org/W2140496876","https://openalex.org/W2602299999","https://openalex.org/W2891638642","https://openalex.org/W2952116272","https://openalex.org/W3019535201","https://openalex.org/W3021248164","https://openalex.org/W3122167207","https://openalex.org/W3127037042","https://openalex.org/W3169684165","https://openalex.org/W4389062772","https://openalex.org/W4406101730","https://openalex.org/W6743460405","https://openalex.org/W6803788118"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2151749779","https://openalex.org/W3179968364","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109"],"abstract_inverted_index":{"Traditional":[0],"Mean-Variance":[1],"(MV)":[2],"portfolio":[3],"optimization":[4],"methods":[5],"face":[6],"challenges":[7],"due":[8],"to":[9,21,43,57,65,118],"the":[10,52,59,67,71,86,91,95,103,107,122,125,136,139],"separation":[11],"of":[12,94,109,114,138],"prediction":[13,60],"and":[14,24,61,83,101,120,129],"decision-making":[15,62],"processes,":[16],"rendering":[17],"decisions":[18],"highly":[19],"sensitive":[20],"uncertain":[22],"predictions":[23],"resulting":[25],"in":[26,46,144],"suboptimal":[27],"performance.":[28],"In":[29],"this":[30,145],"paper":[31],"we":[32,50,74,84,142],"propose":[33],"an":[34],"end-to-end":[35],"(E2E)":[36],"framework":[37],"that":[38,78],"integrates":[39],"Robust":[40],"Optimization":[41],"(RO)":[42],"address":[44],"uncertainties":[45],"expected":[47],"returns.":[48],"Firstly,":[49],"use":[51,85],"LSTM":[53],"neural":[54,72,96],"network":[55],"approach":[56],"unify":[58],"stages.":[63],"Secondly,":[64],"integrate":[66],"RO":[68,88],"method":[69,89,128],"into":[70],"network,":[73],"transform":[75],"it":[76,79],"so":[77],"could":[80],"remain":[81],"differentiable":[82],"transformed":[87],"as":[90],"loss":[92],"function":[93],"network.":[97],"We":[98],"then":[99],"train":[100],"solve":[102],"model":[104,141],"based":[105],"on":[106],"returns":[108],"more":[110],"than":[111],"1,000":[112],"stocks":[113],"NASDAQ":[115],"from":[116],"2015":[117],"2020,":[119],"compare":[121],"results":[123,134],"with":[124],"traditional":[126],"MV":[127],"other":[130],"existing":[131],"methods.":[132],"The":[133],"show":[135],"superiority":[137],"new":[140],"proposed":[143],"paper.":[146]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}