{"id":"https://openalex.org/W2001847190","doi":"https://doi.org/10.1109/bmei.2012.6513138","title":"Discrete portfolio optimisation for large scale systematic trading applications","display_name":"Discrete portfolio optimisation for large scale systematic trading applications","publication_year":2012,"publication_date":"2012-10-01","ids":{"openalex":"https://openalex.org/W2001847190","doi":"https://doi.org/10.1109/bmei.2012.6513138","mag":"2001847190"},"language":"en","primary_location":{"id":"doi:10.1109/bmei.2012.6513138","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmei.2012.6513138","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 5th International Conference on BioMedical Engineering and Informatics","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/A5049557351","display_name":"Aistis Raudys","orcid":"https://orcid.org/0000-0002-0139-6014"},"institutions":[{"id":"https://openalex.org/I173212132","display_name":"Vilnius University","ror":"https://ror.org/03nadee84","country_code":"LT","type":"education","lineage":["https://openalex.org/I173212132"]}],"countries":["LT"],"is_corresponding":true,"raw_author_name":"Aistis Raudys","raw_affiliation_strings":["Faculty of Mathematics and Informatics, Vilnius University, Vilnius, Lithuania","Fac. of Math. & Inf., Vilnius Univ., Vilnius, Lithuania"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Informatics, Vilnius University, Vilnius, Lithuania","institution_ids":["https://openalex.org/I173212132"]},{"raw_affiliation_string":"Fac. of Math. & Inf., Vilnius Univ., Vilnius, Lithuania","institution_ids":["https://openalex.org/I173212132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000833244","display_name":"\u017didrina Pabar\u0161kait\u0117","orcid":null},"institutions":[{"id":"https://openalex.org/I173212132","display_name":"Vilnius University","ror":"https://ror.org/03nadee84","country_code":"LT","type":"education","lineage":["https://openalex.org/I173212132"]}],"countries":["LT"],"is_corresponding":false,"raw_author_name":"Zidrina Pabarskaite","raw_affiliation_strings":["Faculty of Mathematics and Informatics, Vilnius University, Vilnius, Lithuania","Fac. of Math. & Inf., Vilnius Univ., Vilnius, Lithuania"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Informatics, Vilnius University, Vilnius, Lithuania","institution_ids":["https://openalex.org/I173212132"]},{"raw_affiliation_string":"Fac. of Math. & Inf., Vilnius Univ., Vilnius, Lithuania","institution_ids":["https://openalex.org/I173212132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049557351"],"corresponding_institution_ids":["https://openalex.org/I173212132"],"apc_list":null,"apc_paid":null,"fwci":0.32852539,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.69390355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"10","issue":null,"first_page":"1566","last_page":"1570"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9983999729156494,"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/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9983999729156494,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9961000084877014,"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/T11413","display_name":"Risk and Portfolio Optimization","score":0.9922999739646912,"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/sharpe-ratio","display_name":"Sharpe ratio","score":0.6451801657676697},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.6341813802719116},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5948190689086914},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5109161734580994},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5095425248146057},{"id":"https://openalex.org/keywords/portfolio-optimization","display_name":"Portfolio optimization","score":0.49744871258735657},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.494795024394989},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.4348589777946472},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.35144931077957153},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24865031242370605},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21083614230155945},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.15838512778282166},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15699338912963867},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.12518984079360962}],"concepts":[{"id":"https://openalex.org/C139938925","wikidata":"https://www.wikidata.org/wiki/Q1501898","display_name":"Sharpe ratio","level":3,"score":0.6451801657676697},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.6341813802719116},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5948190689086914},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5109161734580994},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5095425248146057},{"id":"https://openalex.org/C202655437","wikidata":"https://www.wikidata.org/wiki/Q7231728","display_name":"Portfolio optimization","level":3,"score":0.49744871258735657},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.494795024394989},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.4348589777946472},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.35144931077957153},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24865031242370605},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21083614230155945},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.15838512778282166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15699338912963867},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.12518984079360962},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bmei.2012.6513138","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmei.2012.6513138","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 5th International Conference on BioMedical Engineering and Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W642509312","https://openalex.org/W1912679334","https://openalex.org/W1912911237","https://openalex.org/W1984862813","https://openalex.org/W1996834329","https://openalex.org/W1998409204","https://openalex.org/W2040956360","https://openalex.org/W2094181350","https://openalex.org/W2108618176","https://openalex.org/W2167168110","https://openalex.org/W2294342001","https://openalex.org/W2389292054","https://openalex.org/W2480664052","https://openalex.org/W2991769409","https://openalex.org/W4214757140","https://openalex.org/W4235536281","https://openalex.org/W4236670843","https://openalex.org/W4241584625","https://openalex.org/W4285719527","https://openalex.org/W6697284956","https://openalex.org/W6770697022"],"related_works":["https://openalex.org/W2094358534","https://openalex.org/W3121398551","https://openalex.org/W2767021466","https://openalex.org/W4225637079","https://openalex.org/W2241184227","https://openalex.org/W3173433198","https://openalex.org/W4386641461","https://openalex.org/W4387737582","https://openalex.org/W2165226765","https://openalex.org/W3124976413"],"abstract_inverted_index":{"Markowitz's":[0],"mean-variance":[1],"portfolio":[2],"optimisation":[3,19],"is":[4,23,63,92,173],"not":[5,93],"suitable":[6],"for":[7],"a":[8,41,80,101,125,148,161],"large":[9],"number":[10,170],"of":[11,32,100,109,135,140,171],"assets":[12,172],"due":[13],"to":[14,73],"the":[15,51,55,68,83,89,107,136,141,153,157],"unacceptably":[16],"slow":[17],"quadratic":[18,52],"procedure":[20,85],"involved.":[21],"This":[22],"particularly":[24],"important":[25],"in":[26,54,133],"systematic/algorithmic/automated":[27],"trading":[28,35,121],"applications":[29],"where":[30],"instead":[31],"assets,":[33],"automated":[34],"systems":[36],"are":[37],"used.":[38],"We":[39,123],"propose":[40],"much":[42],"faster":[43,164,168],"heuristic":[44],"approach":[45,70,112,146],"that":[46,132],"scales":[47],"linearly":[48],"rather":[49],"than":[50,67,152],"scaling":[53],"Markowitz":[56,69,84,154],"method.":[57],"Moreover,":[58],"our":[59],"proposed":[60],"approach,":[61,155],"Comgen,":[62],"on":[64],"average":[65],"better":[66,149],"when":[71],"applied":[72],"unseen":[74],"data.":[75],"Additionally,":[76],"Comgen":[77],"always":[78,94],"finds":[79],"solution,":[81],"whereas":[82],"occasionally":[86],"fails":[87],"as":[88],"covariance":[90],"matrix":[91],"positive-semidefinite.":[95],"In":[96],"an":[97],"empirical":[98],"study":[99],"~2000":[102],"day":[103],"history,":[104],"we":[105],"demonstrate":[106],"benefits":[108],"this":[110,144],"novel":[111,145],"by":[113,119],"using":[114],"~3200":[115],"time":[116,159],"series":[117],"produced":[118],"automatic":[120],"systems.":[122],"perform":[124],"3":[126],"year":[127],"walk-forward":[128],"analysis":[129],"and":[130],"show":[131],"most":[134],"12\u03013=36":[137],"months":[138],"out":[139],"sample":[142],"periods,":[143],"produces":[147],"Sharpe":[150],"ratio":[151],"at":[156],"same":[158],"being":[160],"thousand":[162],"times":[163,167],"(and":[165],"2400":[166],"if":[169],"4000).":[174]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
