{"id":"https://openalex.org/W3022367143","doi":"https://doi.org/10.3390/a13050121","title":"Ensemble Deep Learning Models for Forecasting Cryptocurrency Time-Series","display_name":"Ensemble Deep Learning Models for Forecasting Cryptocurrency Time-Series","publication_year":2020,"publication_date":"2020-05-10","ids":{"openalex":"https://openalex.org/W3022367143","doi":"https://doi.org/10.3390/a13050121","mag":"3022367143"},"language":"en","primary_location":{"id":"doi:10.3390/a13050121","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a13050121","pdf_url":"https://www.mdpi.com/1999-4893/13/5/121/pdf","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"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":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/13/5/121/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074255083","display_name":"Ioannis E. Livieris","orcid":"https://orcid.org/0000-0002-3996-3301"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Ioannis E. Livieris","raw_affiliation_strings":["Department of Mathematics, University of Patras, GR 265-00 Patras, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Patras, GR 265-00 Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053208277","display_name":"Emmanuel Pintelas","orcid":null},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Emmanuel Pintelas","raw_affiliation_strings":["Department of Mathematics, University of Patras, GR 265-00 Patras, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Patras, GR 265-00 Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061913836","display_name":"Stavros Stavroyiannis","orcid":"https://orcid.org/0000-0001-8444-9371"},"institutions":[{"id":"https://openalex.org/I158716096","display_name":"University of Peloponnese","ror":"https://ror.org/04d4d3c02","country_code":"GR","type":"education","lineage":["https://openalex.org/I158716096"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Stavros Stavroyiannis","raw_affiliation_strings":["Department of Accounting &amp; Finance, University of the Peloponnese, GR 241-00 Antikalamos, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Accounting &amp; Finance, University of the Peloponnese, GR 241-00 Antikalamos, Greece","institution_ids":["https://openalex.org/I158716096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024258131","display_name":"Panagiotis Pintelas","orcid":"https://orcid.org/0000-0001-8436-2743"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Panagiotis Pintelas","raw_affiliation_strings":["Department of Mathematics, University of Patras, GR 265-00 Patras, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Patras, GR 265-00 Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5074255083"],"corresponding_institution_ids":["https://openalex.org/I174878644"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":14.4895,"has_fulltext":false,"cited_by_count":143,"citation_normalized_percentile":{"value":0.99178357,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"13","issue":"5","first_page":"121","last_page":"121"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994999766349792,"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":0.9994999766349792,"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cryptocurrency","display_name":"Cryptocurrency","score":0.8641458749771118},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7059685587882996},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6657060384750366},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6495645046234131},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.6472113728523254},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.619469940662384},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5625407695770264},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.5193427801132202},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5027658939361572},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.4720236659049988},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.21266332268714905},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.17344814538955688}],"concepts":[{"id":"https://openalex.org/C180706569","wikidata":"https://www.wikidata.org/wiki/Q13479982","display_name":"Cryptocurrency","level":2,"score":0.8641458749771118},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7059685587882996},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6657060384750366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6495645046234131},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.6472113728523254},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.619469940662384},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5625407695770264},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.5193427801132202},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5027658939361572},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.4720236659049988},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.21266332268714905},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.17344814538955688},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/a13050121","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a13050121","pdf_url":"https://www.mdpi.com/1999-4893/13/5/121/pdf","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"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":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:628be04a901b47bb8134157268440b04","is_oa":true,"landing_page_url":"https://doaj.org/article/628be04a901b47bb8134157268440b04","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 13, Iss 5, p 121 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1999-4893/13/5/121/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/a13050121","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":"Algorithms","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/a13050121","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a13050121","pdf_url":"https://www.mdpi.com/1999-4893/13/5/121/pdf","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"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":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3022367143.pdf","grobid_xml":"https://content.openalex.org/works/W3022367143.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W1542270631","https://openalex.org/W1689508274","https://openalex.org/W2058613733","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2131542408","https://openalex.org/W2131774270","https://openalex.org/W2140831914","https://openalex.org/W2143612262","https://openalex.org/W2150277917","https://openalex.org/W2159219354","https://openalex.org/W2402902088","https://openalex.org/W2586112617","https://openalex.org/W2592022686","https://openalex.org/W2618360053","https://openalex.org/W2622826443","https://openalex.org/W2752550544","https://openalex.org/W2766243861","https://openalex.org/W2768428981","https://openalex.org/W2798056406","https://openalex.org/W2810097917","https://openalex.org/W2896916590","https://openalex.org/W2910159406","https://openalex.org/W2913325799","https://openalex.org/W2944741672","https://openalex.org/W2944851425","https://openalex.org/W2946073460","https://openalex.org/W2949117887","https://openalex.org/W2953561386","https://openalex.org/W2963919999","https://openalex.org/W2964035888","https://openalex.org/W2976581604","https://openalex.org/W2999196618","https://openalex.org/W3005141333","https://openalex.org/W3017116930","https://openalex.org/W3028847668","https://openalex.org/W3128828886","https://openalex.org/W4211068006","https://openalex.org/W4232478844","https://openalex.org/W4240516607","https://openalex.org/W4242940620","https://openalex.org/W4245604662","https://openalex.org/W4248302511","https://openalex.org/W4251197426","https://openalex.org/W4251708881","https://openalex.org/W4292081177","https://openalex.org/W4297957988","https://openalex.org/W6631190155","https://openalex.org/W6637177075","https://openalex.org/W6674330103","https://openalex.org/W6679563152"],"related_works":["https://openalex.org/W4394826704","https://openalex.org/W2794896638","https://openalex.org/W2891633941","https://openalex.org/W3202800081","https://openalex.org/W3101614107","https://openalex.org/W1909207154","https://openalex.org/W4390971112","https://openalex.org/W3036530763","https://openalex.org/W3124390867","https://openalex.org/W1514365828"],"abstract_inverted_index":{"Nowadays,":[0],"cryptocurrency":[1,99,140],"has":[2],"infiltrated":[3],"almost":[4],"all":[5],"financial":[6,28],"transactions;":[7],"thus,":[8],"it":[9,38],"is":[10,39,59,74,183],"generally":[11],"recognized":[12],"as":[13,113],"an":[14,55],"alternative":[15],"method":[16],"for":[17,62,96,187,210],"paying":[18],"and":[19,30,44,65,89,128,147,177,200,214],"exchanging":[20],"currency.":[21],"Cryptocurrency":[22],"trade":[23],"constitutes":[24],"a":[25,31],"constantly":[26],"increasing":[27],"market":[29],"promising":[32],"type":[33],"of":[34,47,54,71,77,79,121,138,173,180,189],"profitable":[35],"investment;":[36],"however,":[37],"characterized":[40],"by":[41,119,185],"high":[42],"volatility":[43],"strong":[45],"fluctuations":[46],"prices":[48],"over":[49],"time.":[50],"Therefore,":[51],"the":[52,75,80,139,143,150,153,156,166,171,178,190],"development":[53],"intelligent":[56],"forecasting":[57,97,175,216],"model":[58,176],"considered":[60],"essential":[61],"portfolio":[63],"optimization":[64],"decision":[66],"making.":[67],"The":[68,102,131],"main":[69],"contribution":[70],"this":[72],"research":[73],"combination":[76],"three":[78],"most":[81],"widely":[82],"employed":[83],"ensemble":[84,104,132,198],"learning":[85,94,111,199,202],"strategies:":[86],"ensemble-averaging,":[87],"bagging":[88],"stacking":[90],"with":[91,163],"advanced":[92],"deep":[93,110,201],"models":[95,105,112,133],"major":[98],"hourly":[100],"prices.":[101],"proposed":[103],"were":[106,117,134],"evaluated":[107,135,184],"utilizing":[108],"state-of-the-art":[109],"component":[114],"learners,":[115],"which":[116],"comprised":[118],"combinations":[120],"long":[122],"short-term":[123],"memory":[124],"(LSTM),":[125],"Bi-directional":[126],"LSTM":[127],"convolutional":[129],"layers.":[130],"on":[136,142,149,155],"prediction":[137,151],"price":[141,154,168],"following":[144,157],"hour":[145,158],"(regression)":[146],"also":[148],"if":[152],"will":[159],"increase":[160],"or":[161],"decrease":[162],"respect":[164],"to":[165,207],"current":[167],"(classification).":[169],"Additionally,":[170],"reliability":[172],"each":[174,208],"efficiency":[179],"its":[181],"predictions":[182],"examining":[186],"autocorrelation":[188],"errors.":[191],"Our":[192],"detailed":[193],"experimental":[194],"analysis":[195],"indicates":[196],"that":[197],"can":[203],"be":[204],"efficiently":[205],"beneficial":[206],"other,":[209],"developing":[211],"strong,":[212],"stable,":[213],"reliable":[215],"models.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":30},{"year":2024,"cited_by_count":32},{"year":2023,"cited_by_count":32},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":6}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
