{"id":"https://openalex.org/W3000125554","doi":"https://doi.org/10.3390/e22010083","title":"The Decomposition and Forecasting of Mutual Investment Funds Using Singular Spectrum Analysis","display_name":"The Decomposition and Forecasting of Mutual Investment Funds Using Singular Spectrum Analysis","publication_year":2020,"publication_date":"2020-01-09","ids":{"openalex":"https://openalex.org/W3000125554","doi":"https://doi.org/10.3390/e22010083","mag":"3000125554","pmid":"https://pubmed.ncbi.nlm.nih.gov/33285858"},"language":"en","primary_location":{"id":"doi:10.3390/e22010083","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e22010083","pdf_url":"https://www.mdpi.com/1099-4300/22/1/83/pdf?version=1579418765","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/22/1/83/pdf?version=1579418765","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024974930","display_name":"Paulo Canas Rodrigues","orcid":"https://orcid.org/0000-0002-1248-9910"},"institutions":[{"id":"https://openalex.org/I126158947","display_name":"Universidade Federal da Bahia","ror":"https://ror.org/03k3p7647","country_code":"BR","type":"education","lineage":["https://openalex.org/I126158947"]},{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["BR","FI"],"is_corresponding":true,"raw_author_name":"Paulo Canas Rodrigues","raw_affiliation_strings":["CAST, Faculty of Information Technology and Communication Sciences, Tampere University, FI-33014 Tampere, Finland","Department of Statistics, Federal University of Bahia, 40170-110 Salvador, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-1248-9910","affiliations":[{"raw_affiliation_string":"CAST, Faculty of Information Technology and Communication Sciences, Tampere University, FI-33014 Tampere, Finland","institution_ids":["https://openalex.org/I166825849"]},{"raw_affiliation_string":"Department of Statistics, Federal University of Bahia, 40170-110 Salvador, Brazil","institution_ids":["https://openalex.org/I126158947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057612931","display_name":"Jonatha Sousa Pimentel","orcid":"https://orcid.org/0000-0003-2982-5383"},"institutions":[{"id":"https://openalex.org/I126158947","display_name":"Universidade Federal da Bahia","ror":"https://ror.org/03k3p7647","country_code":"BR","type":"education","lineage":["https://openalex.org/I126158947"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jonatha Pimentel","raw_affiliation_strings":["Department of Statistics, Federal University of Bahia, 40170-110 Salvador, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Federal University of Bahia, 40170-110 Salvador, Brazil","institution_ids":["https://openalex.org/I126158947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045105630","display_name":"Patrick Messala","orcid":null},"institutions":[{"id":"https://openalex.org/I126158947","display_name":"Universidade Federal da Bahia","ror":"https://ror.org/03k3p7647","country_code":"BR","type":"education","lineage":["https://openalex.org/I126158947"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Patrick Messala","raw_affiliation_strings":["Department of Statistics, Federal University of Bahia, 40170-110 Salvador, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Federal University of Bahia, 40170-110 Salvador, Brazil","institution_ids":["https://openalex.org/I126158947"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020825259","display_name":"Mohammad Kazemi","orcid":"https://orcid.org/0000-0002-9042-6552"},"institutions":[{"id":"https://openalex.org/I176861719","display_name":"University of Shahrood","ror":"https://ror.org/00yqvtm78","country_code":"IR","type":"education","lineage":["https://openalex.org/I176861719"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammad Kazemi","raw_affiliation_strings":["Department of Statistics, Faculty of Mathematical Sciences, Shahrood University of Technology, P.O. Box 3619995161 Shahroud, Iran"],"raw_orcid":"https://orcid.org/0000-0002-9042-6552","affiliations":[{"raw_affiliation_string":"Department of Statistics, Faculty of Mathematical Sciences, Shahrood University of Technology, P.O. Box 3619995161 Shahroud, Iran","institution_ids":["https://openalex.org/I176861719"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024974930"],"corresponding_institution_ids":["https://openalex.org/I126158947","https://openalex.org/I166825849"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":4.392,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.95150522,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"22","issue":"1","first_page":"83","last_page":"83"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13487","display_name":"Statistical and numerical algorithms","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"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/T13487","display_name":"Statistical and numerical algorithms","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"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/T14369","display_name":"Diverse Interdisciplinary Research Innovations","score":0.9383000135421753,"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/singular-spectrum-analysis","display_name":"Singular spectrum analysis","score":0.8755234479904175},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.8690793514251709},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.8183692097663879},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6508487462997437},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6357713937759399},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6020864844322205},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5865839123725891},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5666546821594238},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48812398314476013},{"id":"https://openalex.org/keywords/moving-average","display_name":"Moving average","score":0.4784312844276428},{"id":"https://openalex.org/keywords/autoregressive\u2013moving-average-model","display_name":"Autoregressive\u2013moving-average model","score":0.46966278553009033},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.4651758372783661},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4592329263687134},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35381078720092773},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.3505963683128357},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31666016578674316},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2794437110424042},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18968522548675537}],"concepts":[{"id":"https://openalex.org/C136272165","wikidata":"https://www.wikidata.org/wiki/Q4048889","display_name":"Singular spectrum analysis","level":3,"score":0.8755234479904175},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.8690793514251709},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8183692097663879},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6508487462997437},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6357713937759399},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6020864844322205},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5865839123725891},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5666546821594238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48812398314476013},{"id":"https://openalex.org/C175706884","wikidata":"https://www.wikidata.org/wiki/Q1130194","display_name":"Moving average","level":2,"score":0.4784312844276428},{"id":"https://openalex.org/C74883015","wikidata":"https://www.wikidata.org/wiki/Q290467","display_name":"Autoregressive\u2013moving-average model","level":3,"score":0.46966278553009033},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.4651758372783661},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4592329263687134},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35381078720092773},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.3505963683128357},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31666016578674316},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2794437110424042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18968522548675537},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.3390/e22010083","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e22010083","pdf_url":"https://www.mdpi.com/1099-4300/22/1/83/pdf?version=1579418765","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:33285858","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33285858","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:e205e0e3dbbb4273850e7f3e41a7eb8e","is_oa":true,"landing_page_url":"https://doaj.org/article/e205e0e3dbbb4273850e7f3e41a7eb8e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 22, Iss 1, p 83 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/22/1/83/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/e22010083","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7516519","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7516519","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:trepo.tuni.fi:10024/122971","is_oa":true,"landing_page_url":"https://trepo.tuni.fi/handle/10024/122971","pdf_url":null,"source":{"id":"https://openalex.org/S4306401860","display_name":"Tampere University Institutional Repository (Tampere University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I150589677","host_organization_name":"Tampere University of Applied Sciences","host_organization_lineage":["https://openalex.org/I150589677"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"publishedVersion"}],"best_oa_location":{"id":"doi:10.3390/e22010083","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e22010083","pdf_url":"https://www.mdpi.com/1099-4300/22/1/83/pdf?version=1579418765","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.5299999713897705,"display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3000125554.pdf"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W1563281071","https://openalex.org/W1661709734","https://openalex.org/W1964337655","https://openalex.org/W1964759801","https://openalex.org/W1975964493","https://openalex.org/W2006049051","https://openalex.org/W2046033161","https://openalex.org/W2054044693","https://openalex.org/W2116512828","https://openalex.org/W2119186597","https://openalex.org/W2144717556","https://openalex.org/W2151246315","https://openalex.org/W2152844015","https://openalex.org/W2165148854","https://openalex.org/W2166361350","https://openalex.org/W2319314596","https://openalex.org/W2342484963","https://openalex.org/W2434886108","https://openalex.org/W2503308866","https://openalex.org/W2562456291","https://openalex.org/W2612119906","https://openalex.org/W2738796499","https://openalex.org/W2748099595","https://openalex.org/W2756380349","https://openalex.org/W2761731804","https://openalex.org/W2766801343","https://openalex.org/W2798056406","https://openalex.org/W2800634330","https://openalex.org/W2809072323","https://openalex.org/W2945680505","https://openalex.org/W2964938828","https://openalex.org/W2974237113","https://openalex.org/W2975425963","https://openalex.org/W2981694440","https://openalex.org/W2982483977","https://openalex.org/W3010845685","https://openalex.org/W3014329169","https://openalex.org/W3045916252","https://openalex.org/W3102703560","https://openalex.org/W3103431687","https://openalex.org/W3122820950","https://openalex.org/W4205806204","https://openalex.org/W4232129301","https://openalex.org/W4285719527","https://openalex.org/W4293223245","https://openalex.org/W4297709905","https://openalex.org/W4391919351","https://openalex.org/W6682448929","https://openalex.org/W6770152201","https://openalex.org/W6775324095","https://openalex.org/W6789047656","https://openalex.org/W6862051589"],"related_works":["https://openalex.org/W2073847544","https://openalex.org/W2036994430","https://openalex.org/W2567143433","https://openalex.org/W2620501840","https://openalex.org/W2085237988","https://openalex.org/W3190289737","https://openalex.org/W3032070712","https://openalex.org/W4387300193","https://openalex.org/W3115491726","https://openalex.org/W3201477101"],"abstract_inverted_index":{"Singular":[0],"spectrum":[1],"analysis":[2],"(SSA)":[3],"is":[4],"a":[5,11,15,161],"non-parametric":[6,96],"method":[7],"that":[8,19,40,189],"breaks":[9],"down":[10],"time":[12,44,48,74,82,151,165],"series":[13,49,75,83,166],"into":[14],"set":[16],"of":[17,33,71,88,116,149,173],"components":[18,36,60],"can":[20,50],"be":[21,51,66,107],"interpreted":[22],"and":[23,28,37,76,91,95,103,124,137,152,157,164,171,198],"grouped":[24],"as":[25],"trend,":[26],"periodicity,":[27],"noise,":[29],"emphasizing":[30],"the":[31,34,59,63,69,72,81,86,114,133,138,169,183,185,190,195],"separability":[32],"underlying":[35],"separate":[38],"periodicities":[39],"occur":[41],"at":[42],"different":[43],"scales.":[45],"The":[46,129],"original":[47],"recovered":[52],"by":[53],"summing":[54],"all":[55],"components.":[56],"However,":[57],"only":[58],"associated":[61],"to":[62,77],"signal":[64],"should":[65,106],"considered":[67],"for":[68,121,126,154],"reconstruction":[70],"noise-free":[73],"conduct":[78],"forecasts.":[79],"When":[80,178],"data":[84,167],"has":[85],"presence":[87],"outliers,":[89],"SSA":[90,119,131,135,192,199],"other":[92],"classic":[93,130],"parametric":[94],"methods":[97],"might":[98],"result":[99],"in":[100,147,182],"misleading":[101],"conclusions":[102],"robust":[104,118,134,191],"methodologies":[105],"used.":[108],"In":[109],"this":[110],"paper":[111],"we":[112],"consider":[113],"use":[115],"two":[117],"algorithms":[120,193],"model":[122,127,144,155,158],"fit":[123,156],"one":[125],"forecasting.":[128],"model,":[132],"alternatives,":[136],"autoregressive":[139],"integrated":[140],"moving":[141],"average":[142],"(ARIMA)":[143],"are":[145,180],"compared":[146],"terms":[148],"computational":[150],"accuracy":[153],"forecast,":[159],"using":[160],"simulation":[162,186],"example":[163],"from":[168],"quotas":[170],"returns":[172],"six":[174],"mutual":[175],"investment":[176],"funds.":[177],"outliers":[179],"present":[181],"data,":[184],"study":[187],"shows":[188],"outperform":[194],"classical":[196],"ARIMA":[197],"models.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}