{"id":"https://openalex.org/W2170850305","doi":"https://doi.org/10.1109/cec.2009.4983238","title":"Constructing portfolio investment strategy based on Time Adapting Genetic Network Programming","display_name":"Constructing portfolio investment strategy based on Time Adapting Genetic Network Programming","publication_year":2009,"publication_date":"2009-05-01","ids":{"openalex":"https://openalex.org/W2170850305","doi":"https://doi.org/10.1109/cec.2009.4983238","mag":"2170850305"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2009.4983238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2009.4983238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Congress on Evolutionary Computation","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/A5050847122","display_name":"Yan Chen","orcid":"https://orcid.org/0000-0003-1287-4525"},"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":true,"raw_author_name":"Yan Chen","raw_affiliation_strings":["School of Information, Production, and Systems, Waseda University, Fukuoka, Japan"],"affiliations":[{"raw_affiliation_string":"School of Information, Production, and Systems, Waseda University, Fukuoka, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037937808","display_name":"Shingo Mabu","orcid":"https://orcid.org/0000-0002-8759-8337"},"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":"Shingo Mabu","raw_affiliation_strings":["School of Information, Production and Systems, Waseda University, Fukuoka, Japan"],"affiliations":[{"raw_affiliation_string":"School of Information, Production and Systems, Waseda University, Fukuoka, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048265074","display_name":"Etsushi Ohkawa","orcid":null},"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":"Etsushi Ohkawa","raw_affiliation_strings":["School of Information, Production and Systems, Waseda University, Fukuoka, Japan"],"affiliations":[{"raw_affiliation_string":"School of Information, Production and Systems, Waseda University, Fukuoka, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013008417","display_name":"Kotaro Hirasawa","orcid":null},"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":"Kotaro Hirasawa","raw_affiliation_strings":["School of Information, Production and Systems, Waseda University, Fukuoka, Japan"],"affiliations":[{"raw_affiliation_string":"School of Information, Production and Systems, Waseda University, Fukuoka, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5050847122"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.22947585,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2379","last_page":"2386"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9932000041007996,"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"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9932000041007996,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/investment-strategy","display_name":"Investment strategy","score":0.6694401502609253},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.6680648326873779},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"Genetic programming","score":0.6047650575637817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5873214602470398},{"id":"https://openalex.org/keywords/portfolio-optimization","display_name":"Portfolio optimization","score":0.5652614831924438},{"id":"https://openalex.org/keywords/technical-analysis","display_name":"Technical analysis","score":0.5352087616920471},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.5229809284210205},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.4929168224334717},{"id":"https://openalex.org/keywords/chart","display_name":"Chart","score":0.4861619174480438},{"id":"https://openalex.org/keywords/investment","display_name":"Investment (military)","score":0.4590972065925598},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4431348741054535},{"id":"https://openalex.org/keywords/investment-portfolio","display_name":"Investment portfolio","score":0.4361081123352051},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.43399202823638916},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4290798604488373},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.381673663854599},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2875825762748718},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.283869206905365},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2530147433280945},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.1787852644920349},{"id":"https://openalex.org/keywords/financial-economics","display_name":"Financial economics","score":0.17571619153022766},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14852860569953918},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1386706531047821},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07304796576499939}],"concepts":[{"id":"https://openalex.org/C103144560","wikidata":"https://www.wikidata.org/wiki/Q2670999","display_name":"Investment strategy","level":3,"score":0.6694401502609253},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.6680648326873779},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.6047650575637817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5873214602470398},{"id":"https://openalex.org/C202655437","wikidata":"https://www.wikidata.org/wiki/Q7231728","display_name":"Portfolio optimization","level":3,"score":0.5652614831924438},{"id":"https://openalex.org/C117245426","wikidata":"https://www.wikidata.org/wiki/Q235038","display_name":"Technical analysis","level":2,"score":0.5352087616920471},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.5229809284210205},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.4929168224334717},{"id":"https://openalex.org/C190812933","wikidata":"https://www.wikidata.org/wiki/Q28923","display_name":"Chart","level":2,"score":0.4861619174480438},{"id":"https://openalex.org/C27548731","wikidata":"https://www.wikidata.org/wiki/Q88272","display_name":"Investment (military)","level":3,"score":0.4590972065925598},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4431348741054535},{"id":"https://openalex.org/C2983001568","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Investment portfolio","level":3,"score":0.4361081123352051},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.43399202823638916},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4290798604488373},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.381673663854599},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2875825762748718},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.283869206905365},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2530147433280945},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.1787852644920349},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.17571619153022766},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14852860569953918},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1386706531047821},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07304796576499939},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C181622380","wikidata":"https://www.wikidata.org/wiki/Q26911","display_name":"Profit (economics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2009.4983238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2009.4983238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Congress on Evolutionary Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1576818901","https://openalex.org/W1639032689","https://openalex.org/W1659842140","https://openalex.org/W1984815740","https://openalex.org/W1995319408","https://openalex.org/W1997069306","https://openalex.org/W2002685209","https://openalex.org/W2015856032","https://openalex.org/W2086600750","https://openalex.org/W2114146953","https://openalex.org/W2130063495","https://openalex.org/W2148836909","https://openalex.org/W2152387530","https://openalex.org/W2207807602","https://openalex.org/W2255344912","https://openalex.org/W2795413297","https://openalex.org/W3123800628","https://openalex.org/W6691676939"],"related_works":["https://openalex.org/W2155008338","https://openalex.org/W3154480698","https://openalex.org/W2375743981","https://openalex.org/W1496057683","https://openalex.org/W4249112627","https://openalex.org/W2979375829","https://openalex.org/W273679374","https://openalex.org/W2365416894","https://openalex.org/W2360745586","https://openalex.org/W4389200325"],"abstract_inverted_index":{"The":[0,53],"classical":[1],"portfolio":[2,27,55,135],"problem":[3,6],"is":[4,124,131],"a":[5,11],"of":[7,13,20,44,58,93,104],"distributing":[8],"capital":[9],"to":[10,17,64,118],"set":[12],"stocks.":[14],"By":[15],"adapting":[16],"the":[18,45,71,77,101,105,109,127,134],"change":[19],"stock":[21,73],"prices,":[22],"this":[23],"study":[24],"proposes":[25],"an":[26,32],"investment":[28,66,79,129],"strategy":[29,80,130],"based":[30,112],"on":[31,70,133],"evolutionary":[33],"method":[34,41,86,117],"named":[35],"ldquoGenetic":[36],"Network":[37],"Programmingrdquo":[38],"(GNP).":[39],"This":[40],"makes":[42],"use":[43],"information":[46],"from":[47],"Technical":[48],"Indices":[49],"and":[50,96,115,122],"Candlestick":[51],"Chart.":[52],"proposed":[54,78,106,128],"model,":[56],"consisting":[57],"technical":[59],"analysis":[60],"rules,":[61],"are":[62],"trained":[63],"generate":[65],"advice.":[67],"Experimental":[68],"results":[69,103],"Japanese":[72],"market":[74],"show":[75],"that":[76,126],"using":[81],"Time":[82],"Adapting":[83],"GNP":[84,111],"(TA-GNP)":[85],"outperforms":[87],"other":[88],"traditional":[89],"models":[90],"in":[91],"terms":[92],"both":[94],"accuracy":[95],"efficiency.":[97],"We":[98],"also":[99],"compared":[100],"experimental":[102],"model":[107],"with":[108],"conventional":[110],"methods,":[113],"GA":[114],"Buy&Hold":[116],"confirm":[119],"its":[120],"effectiveness,":[121],"it":[123],"clarified":[125],"effective":[132],"optimization":[136],"problem.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
