{"id":"https://openalex.org/W7214944784","doi":"https://doi.org/10.11591/eei.v15i5.11750","title":"S&P 500 forecasting with financial news sentiment using FinBERT-CNN-LSTM","display_name":"S&P 500 forecasting with financial news sentiment using FinBERT-CNN-LSTM","publication_year":2026,"publication_date":"2026-10-01","ids":{"openalex":"https://openalex.org/W7214944784","doi":"https://doi.org/10.11591/eei.v15i5.11750"},"language":"en","primary_location":{"id":"doi:10.11591/eei.v15i5.11750","doi":"https://doi.org/10.11591/eei.v15i5.11750","is_oa":true,"landing_page_url":"https://doi.org/10.11591/eei.v15i5.11750","pdf_url":"https://beei.org/index.php/EEI/article/download/11750/5025","source":{"id":"https://openalex.org/S2765016208","display_name":"Bulletin of Electrical Engineering and Informatics","issn_l":"2089-3191","issn":["2089-3191","2302-9285"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315009","host_organization_name":"Institute of Advanced Engineering and Science (IAES)","host_organization_lineage":["https://openalex.org/P4310315009"],"host_organization_lineage_names":["Institute of Advanced Engineering and Science (IAES)"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bulletin of Electrical Engineering and Informatics","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://beei.org/index.php/EEI/article/download/11750/5025","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092698672","display_name":"Zakaria Al Bakkari","orcid":"https://orcid.org/0000-0002-8437-0564","observed_orcids":["https://orcid.org/0000-0002-8437-0564"]},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Zakaria Al Bakkari","raw_affiliation_strings":["Ibn Tofail University"],"raw_orcid":"https://orcid.org/0000-0002-8437-0564","affiliations":[{"raw_affiliation_string":"Ibn Tofail University","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047126111","display_name":"Ikram El Azami","orcid":"https://orcid.org/0000-0002-9204-7759","observed_orcids":["https://orcid.org/0000-0002-9204-7759"]},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Ikram El Azami","raw_affiliation_strings":["Ibn Tofail University"],"raw_orcid":"https://orcid.org/0000-0002-9204-7759","affiliations":[{"raw_affiliation_string":"Ibn Tofail University","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060737440","display_name":"Adil El Makrani","orcid":"https://orcid.org/0000-0002-6316-2379","observed_orcids":["https://orcid.org/0000-0002-6316-2379"]},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Adil El Makrani","raw_affiliation_strings":["Ibn Tofail University"],"raw_orcid":"https://orcid.org/0000-0002-6316-2379","affiliations":[{"raw_affiliation_string":"Ibn Tofail University","institution_ids":["https://openalex.org/I3121676899"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3121676899"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.73506683,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":"5","first_page":"4474","last_page":"4486"},"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/T10047","display_name":"Financial Markets and Investment Strategies","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","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"}}],"keywords":[{"id":"https://openalex.org/keywords/stock-market-forecasting","display_name":"stock market prediction","score":0.8840000033378601},{"id":"https://openalex.org/keywords/financial-news-sentiment","display_name":"financial news sentiment","score":0.9760000109672546},{"id":"https://openalex.org/keywords/finbert","display_name":"FinBERT","score":0.9670000076293945},{"id":"https://openalex.org/keywords/hybrid-cnn-lstm-model","display_name":"CNN-LSTM hybrid model","score":0.8740000128746033},{"id":"https://openalex.org/keywords/investor-sentiment","display_name":"investor sentiment","score":0.7289999723434448},{"id":"https://openalex.org/keywords/financial-time-series","display_name":"financial time series","score":0.7620000243186951},{"id":"https://openalex.org/keywords/directional-accuracy","display_name":"directional accuracy","score":0.39899998903274536},{"id":"https://openalex.org/keywords/diebold-mariano-test","display_name":"Diebold-Mariano test","score":0.8080000281333923}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5497000217437744},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.5479000210762024},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5376999974250793},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.5361999869346619},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5299999713897705},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5076000094413757},{"id":"https://openalex.org/C139938925","wikidata":"https://www.wikidata.org/wiki/Q1501898","display_name":"Sharpe ratio","level":3,"score":0.5069000124931335},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.49959999322891235},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4771000146865845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44690001010894775},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C88389905","wikidata":"https://www.wikidata.org/wiki/Q223371","display_name":"Stock market index","level":4,"score":0.43650001287460327},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.40689998865127563},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3878999948501587},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.37529999017715454},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.3723999857902527},{"id":"https://openalex.org/C26021514","wikidata":"https://www.wikidata.org/wiki/Q4669830","display_name":"Absolute return","level":5,"score":0.3610999882221222},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3474000096321106},{"id":"https://openalex.org/C118315980","wikidata":"https://www.wikidata.org/wiki/Q375350","display_name":"Market timing","level":3,"score":0.34279999136924744},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.31360000371932983},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3100000023841858},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C2781410264","wikidata":"https://www.wikidata.org/wiki/Q440364","display_name":"Market sentiment","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C174303752","wikidata":"https://www.wikidata.org/wiki/Q3624438","display_name":"Forecast error","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C29368100","wikidata":"https://www.wikidata.org/wiki/Q724931","display_name":"Efficient-market hypothesis","level":4,"score":0.2994000017642975},{"id":"https://openalex.org/C2776256503","wikidata":"https://www.wikidata.org/wiki/Q7617906","display_name":"Stock market prediction","level":4,"score":0.2985000014305115},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.2939999997615814},{"id":"https://openalex.org/C98014903","wikidata":"https://www.wikidata.org/wiki/Q832161","display_name":"Financial ratio","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.26739999651908875},{"id":"https://openalex.org/C117245426","wikidata":"https://www.wikidata.org/wiki/Q235038","display_name":"Technical analysis","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C2776174256","wikidata":"https://www.wikidata.org/wiki/Q830842","display_name":"BETA (programming language)","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C114118609","wikidata":"https://www.wikidata.org/wiki/Q3036837","display_name":"Market data","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.11591/eei.v15i5.11750","doi":"https://doi.org/10.11591/eei.v15i5.11750","is_oa":true,"landing_page_url":"https://doi.org/10.11591/eei.v15i5.11750","pdf_url":"https://beei.org/index.php/EEI/article/download/11750/5025","source":{"id":"https://openalex.org/S2765016208","display_name":"Bulletin of Electrical Engineering and Informatics","issn_l":"2089-3191","issn":["2089-3191","2302-9285"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315009","host_organization_name":"Institute of Advanced Engineering and Science (IAES)","host_organization_lineage":["https://openalex.org/P4310315009"],"host_organization_lineage_names":["Institute of Advanced Engineering and Science (IAES)"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bulletin of Electrical Engineering and Informatics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.11591/eei.v15i5.11750","doi":"https://doi.org/10.11591/eei.v15i5.11750","is_oa":true,"landing_page_url":"https://doi.org/10.11591/eei.v15i5.11750","pdf_url":"https://beei.org/index.php/EEI/article/download/11750/5025","source":{"id":"https://openalex.org/S2765016208","display_name":"Bulletin of Electrical Engineering and Informatics","issn_l":"2089-3191","issn":["2089-3191","2302-9285"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315009","host_organization_name":"Institute of Advanced Engineering and Science (IAES)","host_organization_lineage":["https://openalex.org/P4310315009"],"host_organization_lineage_names":["Institute of Advanced Engineering and Science (IAES)"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bulletin of Electrical Engineering and Informatics","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7214944784.pdf","grobid_xml":"https://content.openalex.org/works/W7214944784.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7204460235","https://openalex.org/W4404172054","https://openalex.org/W7202391117","https://openalex.org/W7157817279","https://openalex.org/W4417444781","https://openalex.org/W7157823283","https://openalex.org/W7081304087","https://openalex.org/W7201868906","https://openalex.org/W7132909145","https://openalex.org/W4379539262"],"abstract_inverted_index":{"Accurate":[0],"stock":[1,186],"market":[2,20,68,80,187],"forecasting":[3,52],"remains":[4],"challenging":[5],"due":[6],"to":[7],"the":[8,53,97,110,166,170,175],"nonlinear,":[9],"noisy,":[10],"and":[11,27,45,82,93,138,152,160,181],"volatile":[12],"nature":[13],"of":[14,123,129,136,142,150,156,169,177],"financial":[15,25,35,63,103,179],"markets.":[16],"Beyond":[17],"historical":[18,67],"prices,":[19],"movements":[21],"are":[22,77],"influenced":[23],"by":[24,61],"news":[26,64],"investor":[28],"sentiment.":[29],"This":[30],"study":[31],"proposes":[32],"a":[33,85,117,147,153],"hybrid":[34],"bidirectional":[36],"encoder":[37],"representations":[38],"from":[39],"transformers":[40],"with":[41,66,79],"convolutional":[42],"neural":[43],"network":[44],"long":[46],"short-term":[47,94],"memory":[48],"(FinBERT-CNN-LSTM)":[49],"model":[50,112],"for":[51,185],"Standard":[54],"&":[55],"Poor\u2019s":[56],"500":[57],"(S&P":[58],"500)":[59],"index":[60],"integrating":[62],"sentiment":[65,74,180],"data.":[69],"FinBERT":[70],"generates":[71],"daily":[72],"aggregated":[73],"scores,":[75],"which":[76],"combined":[78],"features":[81],"processed":[83],"through":[84],"CNN-LSTM":[86],"architecture.":[87],"The":[88],"CNN":[89],"captures":[90],"local":[91],"patterns":[92],"interactions,":[95],"while":[96],"LSTM":[98],"models":[99],"temporal":[100],"dependencies":[101],"in":[102],"time":[104],"series.":[105],"Experimental":[106],"results":[107],"show":[108],"that":[109],"proposed":[111],"outperforms":[113],"benchmark":[114],"models,":[115],"achieving":[116],"root":[118],"mean":[119,125,131],"square":[120],"error":[121,127,134],"(RMSE)":[122],"0.0119,":[124],"absolute":[126,132],"(MAE)":[128],"0.0091,":[130],"percentage":[133],"(MAPE)":[135],"2.10%,":[137],"directional":[139],"accuracy":[140],"(DA)":[141],"63.4%.":[143],"It":[144],"also":[145],"achieves":[146],"cumulative":[148],"return":[149],"15.8%":[151],"Sharpe":[154],"ratio":[155],"1.35.":[157],"Rolling-window":[158],"validation":[159],"Diebold\u2013Mariano":[161],"(DM)":[162],"testing":[163],"further":[164],"support":[165],"statistical":[167],"significance":[168],"improvements.":[171],"These":[172],"findings":[173],"demonstrate":[174],"effectiveness":[176],"combining":[178],"deep":[182],"learning":[183],"(DL)":[184],"forecasting.":[188]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-10-01T00:00:00"}