{"id":"https://openalex.org/W3043001028","doi":"https://doi.org/10.1007/s40745-020-00305-w","title":"Comparing Artificial Neural Network Architectures for Brazilian Stock Market Prediction","display_name":"Comparing Artificial Neural Network Architectures for Brazilian Stock Market Prediction","publication_year":2020,"publication_date":"2020-07-13","ids":{"openalex":"https://openalex.org/W3043001028","doi":"https://doi.org/10.1007/s40745-020-00305-w","mag":"3043001028","pmid":"https://pubmed.ncbi.nlm.nih.gov/38624383","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/7355518"},"language":"en","primary_location":{"id":"doi:10.1007/s40745-020-00305-w","doi":"https://doi.org/10.1007/s40745-020-00305-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40745-020-00305-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40745-020-00305-w.pdf","source":{"id":"https://openalex.org/S2765063436","display_name":"Annals of Data Science","issn_l":"2198-5804","issn":["2198-5804","2198-5812"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","poland-20","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annals of Data Science","raw_type":"journal-article"},"volume":null,"type":"review","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://link.springer.com/content/pdf/10.1007/s40745-020-00305-w.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034243115","display_name":"Suellen Teixeira Zavadzki de Pauli","orcid":"https://orcid.org/0000-0002-9122-6974","observed_orcids":["https://orcid.org/0000-0002-9122-6974"]},"institutions":[{"id":"https://openalex.org/I52418104","display_name":"Universidade Federal do Paran\u00e1","ror":"https://ror.org/05syd6y78","country_code":"BR","type":"education","lineage":["https://openalex.org/I52418104"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Suellen Teixeira Zavadzki de Pauli","raw_affiliation_strings":["Federal University of Paran\u00e1 (UFPR), Cel. Francisco H. dos Santos Avenue, 210, Curitiba, PR, 81530-000, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-9122-6974","affiliations":[{"raw_affiliation_string":"Federal University of Paran\u00e1 (UFPR), Cel. Francisco H. dos Santos Avenue, 210, Curitiba, PR, 81530-000, Brazil","institution_ids":["https://openalex.org/I52418104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061792055","display_name":"Mariana Kleina","orcid":"https://orcid.org/0000-0001-8108-8793","observed_orcids":["https://orcid.org/0000-0001-8108-8793"]},"institutions":[{"id":"https://openalex.org/I52418104","display_name":"Universidade Federal do Paran\u00e1","ror":"https://ror.org/05syd6y78","country_code":"BR","type":"education","lineage":["https://openalex.org/I52418104"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Mariana Kleina","raw_affiliation_strings":["Federal University of Paran\u00e1 (UFPR), Cel. Francisco H. dos Santos Avenue, 210, Curitiba, PR, 81530-000, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Paran\u00e1 (UFPR), Cel. Francisco H. dos Santos Avenue, 210, Curitiba, PR, 81530-000, Brazil","institution_ids":["https://openalex.org/I52418104"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082508212","display_name":"Wagner Hugo Bonat","orcid":"https://orcid.org/0000-0002-0349-7054","observed_orcids":["https://orcid.org/0000-0002-0349-7054"]},"institutions":[{"id":"https://openalex.org/I52418104","display_name":"Universidade Federal do Paran\u00e1","ror":"https://ror.org/05syd6y78","country_code":"BR","type":"education","lineage":["https://openalex.org/I52418104"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Wagner Hugo Bonat","raw_affiliation_strings":["Federal University of Paran\u00e1 (UFPR), Cel. Francisco H. dos Santos Avenue, 210, Curitiba, PR, 81530-000, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Paran\u00e1 (UFPR), Cel. Francisco H. dos Santos Avenue, 210, Curitiba, PR, 81530-000, Brazil","institution_ids":["https://openalex.org/I52418104"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5034243115"],"corresponding_institution_ids":["https://openalex.org/I52418104"],"apc_list":{"value":2750,"currency":"USD","value_usd":2750},"apc_paid":null,"fwci":1.3713,"has_fulltext":true,"cited_by_count":49,"citation_normalized_percentile":{"value":0.79227053,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":"7","issue":"4","first_page":"613","last_page":"628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":1.0,"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":1.0,"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/T10320","display_name":"Neural Networks and Applications","score":0.0,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.0,"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/stock-market-forecasting","display_name":"stock market prediction","score":0.8489999771118164},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.8029999732971191},{"id":"https://openalex.org/keywords/brazilian-stock-exchange","display_name":"Brazilian stock exchange","score":0.6320000290870667},{"id":"https://openalex.org/keywords/b3","display_name":"B3","score":0.625},{"id":"https://openalex.org/keywords/closing-price-prediction","display_name":"closing price forecasting","score":0.8040000200271606},{"id":"https://openalex.org/keywords/elman-neural-network","display_name":"Elman neural network","score":0.6510000228881836},{"id":"https://openalex.org/keywords/jordan-network","display_name":"Jordan network","score":0.9869999885559082},{"id":"https://openalex.org/keywords/radial-basis-function-neural-network","display_name":"radial basis function neural network","score":0.9539999961853027},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"multilayer perceptron","score":1.0},{"id":"https://openalex.org/keywords/multiple-linear-regression","display_name":"multiple linear regression","score":0.8830000162124634},{"id":"https://openalex.org/keywords/bootstrap-prediction-intervals","display_name":"bootstrap prediction intervals","score":0.574999988079071},{"id":"https://openalex.org/keywords/forecast-uncertainty","display_name":"forecast uncertainty","score":0.8370000123977661},{"id":"https://openalex.org/keywords/covid-19-impact-on-stock-markets","display_name":"COVID-19 impact on stock markets","score":0.8809999823570251},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"hyperparameter optimization","score":0.5580000281333923}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.638941764831543},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5327361226081848},{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.5323802828788757},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5279756188392639},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5157885551452637},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5156994462013245},{"id":"https://openalex.org/C200870193","wikidata":"https://www.wikidata.org/wiki/Q11691","display_name":"Stock exchange","level":2,"score":0.49045106768608093},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.474097341299057},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.42481112480163574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.404910683631897},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3778982162475586},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3447299003601074},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2988271713256836},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.1557042896747589},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.1107344925403595}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s40745-020-00305-w","doi":"https://doi.org/10.1007/s40745-020-00305-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40745-020-00305-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40745-020-00305-w.pdf","source":{"id":"https://openalex.org/S2765063436","display_name":"Annals of Data Science","issn_l":"2198-5804","issn":["2198-5804","2198-5812"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","poland-20","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annals of Data Science","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:7355518","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7355518","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,"listed_in":[],"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":"Ann. Data. Sci.","raw_type":"Text"},{"id":"pmid:38624383","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38624383","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,"listed_in":[],"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":"Annals of data science","raw_type":"Journal Article"},{"id":"pmh:oai:RePEc:spr:aodasc:v:7:y:2020:i:4:d:10.1007_s40745-020-00305-w","doi":null,"is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s40745-020-00305-w","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s40745-020-00305-w","doi":"https://doi.org/10.1007/s40745-020-00305-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40745-020-00305-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40745-020-00305-w.pdf","source":{"id":"https://openalex.org/S2765063436","display_name":"Annals of Data Science","issn_l":"2198-5804","issn":["2198-5804","2198-5812"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","poland-20","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annals of Data Science","raw_type":"journal-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3043001028.pdf","grobid_xml":"https://content.openalex.org/works/W3043001028.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W94523489","https://openalex.org/W562319516","https://openalex.org/W1490229695","https://openalex.org/W1567281254","https://openalex.org/W1598796236","https://openalex.org/W1608292140","https://openalex.org/W1817040532","https://openalex.org/W1840208138","https://openalex.org/W1979156432","https://openalex.org/W1980685279","https://openalex.org/W1983771093","https://openalex.org/W2079775355","https://openalex.org/W2110485445","https://openalex.org/W2123513648","https://openalex.org/W2219598583","https://openalex.org/W2291900318","https://openalex.org/W2515077010","https://openalex.org/W2560171758","https://openalex.org/W2582743722","https://openalex.org/W2729912483","https://openalex.org/W2790137849","https://openalex.org/W2969912626","https://openalex.org/W3005570960","https://openalex.org/W3016759771","https://openalex.org/W3195126080","https://openalex.org/W4388322985"],"related_works":["https://openalex.org/W2911914407","https://openalex.org/W2602648596","https://openalex.org/W7045407819","https://openalex.org/W4295135879","https://openalex.org/W2138754556","https://openalex.org/W2805301523","https://openalex.org/W2164955860","https://openalex.org/W4399726810","https://openalex.org/W7055356890","https://openalex.org/W2183616920"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":1}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2020-07-23T00:00:00"}
