{"id":"https://openalex.org/W2036871488","doi":"https://doi.org/10.1109/fskd.2013.6816204","title":"A portfolio selection model with interval-valued return rates","display_name":"A portfolio selection model with interval-valued return rates","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2036871488","doi":"https://doi.org/10.1109/fskd.2013.6816204","mag":"2036871488"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2013.6816204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2013.6816204","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","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/A5057613154","display_name":"Weijie Pang","orcid":"https://orcid.org/0000-0002-7666-8248"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weijie Pang","raw_affiliation_strings":["College of Applied Science, Beijing University of Technology, Beijing, China","College of Applied Science, Beijing University of Technology, China 100124"],"affiliations":[{"raw_affiliation_string":"College of Applied Science, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]},{"raw_affiliation_string":"College of Applied Science, Beijing University of Technology, China 100124","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060571396","display_name":"Shoumei Li","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shoumei Li","raw_affiliation_strings":["College of Applied Science, Beijing University of Technology, Beijing, China","College of Applied Science, Beijing University of Technology, China 100124"],"affiliations":[{"raw_affiliation_string":"College of Applied Science, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]},{"raw_affiliation_string":"College of Applied Science, Beijing University of Technology, China 100124","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057613154"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.1061306,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"262","last_page":"267"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12135","display_name":"Fuzzy Systems and Optimization","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12135","display_name":"Fuzzy Systems and Optimization","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11413","display_name":"Risk and Portfolio Optimization","score":0.9980999827384949,"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.995199978351593,"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/portfolio","display_name":"Portfolio","score":0.7853817343711853},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.6183947324752808},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5810829997062683},{"id":"https://openalex.org/keywords/rate-of-return-on-a-portfolio","display_name":"Rate of return on a portfolio","score":0.5720787644386292},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.47644689679145813},{"id":"https://openalex.org/keywords/portfolio-optimization","display_name":"Portfolio optimization","score":0.47419315576553345},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.46391525864601135},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.4610964059829712},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4465298354625702},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43976449966430664},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.43456512689590454},{"id":"https://openalex.org/keywords/modern-portfolio-theory","display_name":"Modern portfolio theory","score":0.4125368595123291},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3803432881832123},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3474084734916687},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.18395507335662842},{"id":"https://openalex.org/keywords/financial-economics","display_name":"Financial economics","score":0.17631012201309204},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.14112666249275208}],"concepts":[{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.7853817343711853},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6183947324752808},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5810829997062683},{"id":"https://openalex.org/C104946779","wikidata":"https://www.wikidata.org/wiki/Q7295542","display_name":"Rate of return on a portfolio","level":4,"score":0.5720787644386292},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.47644689679145813},{"id":"https://openalex.org/C202655437","wikidata":"https://www.wikidata.org/wiki/Q7231728","display_name":"Portfolio optimization","level":3,"score":0.47419315576553345},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.46391525864601135},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.4610964059829712},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4465298354625702},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43976449966430664},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.43456512689590454},{"id":"https://openalex.org/C9725762","wikidata":"https://www.wikidata.org/wiki/Q1072885","display_name":"Modern portfolio theory","level":3,"score":0.4125368595123291},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3803432881832123},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3474084734916687},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.18395507335662842},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.17631012201309204},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.14112666249275208},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2013.6816204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2013.6816204","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","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":10,"referenced_works":["https://openalex.org/W1564759251","https://openalex.org/W1967438308","https://openalex.org/W2001133140","https://openalex.org/W2021244475","https://openalex.org/W2089191214","https://openalex.org/W2130409740","https://openalex.org/W2170914403","https://openalex.org/W2313727555","https://openalex.org/W3122117224","https://openalex.org/W4236670843"],"related_works":["https://openalex.org/W2221832056","https://openalex.org/W3114011295","https://openalex.org/W2131638049","https://openalex.org/W2367990330","https://openalex.org/W2342245948","https://openalex.org/W4387811153","https://openalex.org/W2151303070","https://openalex.org/W3198789915","https://openalex.org/W3122820618","https://openalex.org/W4243169348"],"abstract_inverted_index":{"This":[0],"paper":[1],"mainly":[2],"proposes":[3],"a":[4,11],"new":[5,72],"model":[6,14,75],"for":[7,44],"stock":[8,96,100],"markets,":[9],"namely":[10],"portfolio":[12,73],"selection":[13,74],"with":[15,80],"interval-valued":[16,58,77],"return":[17,78],"rates.":[18],"To":[19],"do":[20,89],"it,":[21],"we":[22,38,47,69,88],"review":[23],"some":[24,63],"concepts":[25],"of":[26,33,57,76,85],"interval":[27],"numbers":[28],"and":[29,54,61],"the":[30,52,55,67],"acceptability":[31],"function":[32],"rankings":[34],"at":[35],"first.":[36],"And":[37],"present":[39],"an":[40,90],"improved":[41],"ranking":[42],"method":[43],"intervals.":[45],"Then,":[46],"introduce":[48,70],"set-valued":[49],"random":[50,59],"variables,":[51],"semi-variance":[53],"semi-covariance":[56],"variables":[60],"prove":[62],"related":[64],"properties.":[65],"After":[66],"preparation,":[68],"our":[71,104],"rates":[79],"semi-variances":[81],"as":[82],"risk":[83],"measurements":[84],"stocks.":[86],"Finally,":[87],"empirical":[91],"analysis":[92],"by":[93],"using":[94],"real":[95],"data":[97],"in":[98],"NASDAQ":[99],"market":[101],"to":[102],"illustrate":[103],"model.":[105]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}