{"id":"https://openalex.org/W4399971860","doi":"https://doi.org/10.1080/08839514.2024.2371706","title":"Exploring Different Dynamics of Recurrent Neural Network Methods for Stock Market Prediction - A Comparative Study","display_name":"Exploring Different Dynamics of Recurrent Neural Network Methods for Stock Market Prediction - A Comparative Study","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4399971860","doi":"https://doi.org/10.1080/08839514.2024.2371706"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2024.2371706","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2024.2371706","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2371706?needAccess=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2371706?needAccess=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5099435591","display_name":"Ajit Mohan Pattanayak","orcid":null},"institutions":[{"id":"https://openalex.org/I67357951","display_name":"KIIT University","ror":"https://ror.org/00k8zt527","country_code":"IN","type":"education","lineage":["https://openalex.org/I67357951"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ajit Mohan Pattanayak","raw_affiliation_strings":["School of Computer Engineering, KIIT deemed to be University, Bhubaneswar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, KIIT deemed to be University, Bhubaneswar, India","institution_ids":["https://openalex.org/I67357951"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068965698","display_name":"Aleena Swetapadma","orcid":null},"institutions":[{"id":"https://openalex.org/I67357951","display_name":"KIIT University","ror":"https://ror.org/00k8zt527","country_code":"IN","type":"education","lineage":["https://openalex.org/I67357951"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Aleena Swetapadma","raw_affiliation_strings":["School of Computer Engineering, KIIT deemed to be University, Bhubaneswar, India"],"raw_orcid":"https://orcid.org/0000-0001-8270-2927","affiliations":[{"raw_affiliation_string":"School of Computer Engineering, KIIT deemed to be University, Bhubaneswar, India","institution_ids":["https://openalex.org/I67357951"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081211580","display_name":"Biswajit Sahoo","orcid":"https://orcid.org/0000-0003-3292-3574"},"institutions":[{"id":"https://openalex.org/I67357951","display_name":"KIIT University","ror":"https://ror.org/00k8zt527","country_code":"IN","type":"education","lineage":["https://openalex.org/I67357951"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Biswajit Sahoo","raw_affiliation_strings":["School of Computer Engineering, KIIT deemed to be University, Bhubaneswar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, KIIT deemed to be University, Bhubaneswar, India","institution_ids":["https://openalex.org/I67357951"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5068965698"],"corresponding_institution_ids":["https://openalex.org/I67357951"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":5.1622,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.95504609,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"38","issue":"1","first_page":null,"last_page":null},"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9926000237464905,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8624028563499451},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5530557632446289},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.540560781955719},{"id":"https://openalex.org/keywords/stock-market-prediction","display_name":"Stock market prediction","score":0.523140549659729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4816912114620209},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44951677322387695},{"id":"https://openalex.org/keywords/dynamics","display_name":"Dynamics (music)","score":0.4465487003326416},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4152581989765167},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34862762689590454},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.32020115852355957}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8624028563499451},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5530557632446289},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.540560781955719},{"id":"https://openalex.org/C2776256503","wikidata":"https://www.wikidata.org/wiki/Q7617906","display_name":"Stock market prediction","level":4,"score":0.523140549659729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4816912114620209},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44951677322387695},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.4465487003326416},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4152581989765167},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34862762689590454},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32020115852355957},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2024.2371706","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2024.2371706","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2371706?needAccess=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b2183a026e5a4bf6bdf9cabaf7258e1c","is_oa":true,"landing_page_url":"https://doaj.org/article/b2183a026e5a4bf6bdf9cabaf7258e1c","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 38, Iss 1 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/08839514.2024.2371706","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2024.2371706","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2371706?needAccess=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399971860.pdf"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1995382443","https://openalex.org/W2025053102","https://openalex.org/W2053615983","https://openalex.org/W2400770063","https://openalex.org/W2794904450","https://openalex.org/W2806777472","https://openalex.org/W2912614123","https://openalex.org/W3017229010","https://openalex.org/W3081799531","https://openalex.org/W3110378470","https://openalex.org/W3126479554","https://openalex.org/W3134206323","https://openalex.org/W3149859316","https://openalex.org/W3197594655","https://openalex.org/W4212907713","https://openalex.org/W4296209180","https://openalex.org/W4311764669","https://openalex.org/W4380048054","https://openalex.org/W4386646203","https://openalex.org/W4388575137","https://openalex.org/W4388751946","https://openalex.org/W4389219081","https://openalex.org/W4391093719","https://openalex.org/W4392232034","https://openalex.org/W4404049250","https://openalex.org/W6873698495"],"related_works":["https://openalex.org/W2586556113","https://openalex.org/W3135178882","https://openalex.org/W2542516223","https://openalex.org/W2624043242","https://openalex.org/W3209908847","https://openalex.org/W108833508","https://openalex.org/W2110351804","https://openalex.org/W3023530306","https://openalex.org/W2086993069","https://openalex.org/W1980850818"],"abstract_inverted_index":{"The":[0,62,116],"intricate":[1],"and":[2,19,33,79,112,131,140,186],"unpredictable":[3],"nature":[4],"of":[5,11,17,44,52,64,183],"stock":[6,39,81,105],"markets":[7],"underscores":[8],"the":[9,42,50,77,152,159,162,181,191],"importance":[10],"precise":[12,71],"forecasting":[13],"for":[14,75,169],"timely":[15],"detection":[16],"downturns":[18],"subsequent":[20],"rebounds.":[21],"Various":[22],"factors,":[23],"including":[24],"news,":[25],"rumors":[26],"surrounding":[27],"events":[28],"or":[29,179],"companies,":[30],"market":[31,127],"sentiments,":[32],"governmental":[34],"policies,":[35],"can":[36],"significantly":[37],"impact":[38],"prices.":[40],"Nevertheless,":[41],"precision":[43],"current":[45],"methods":[46],"remained":[47],"insufficient":[48],"until":[49],"adoption":[51],"artificial":[53],"neural":[54],"network":[55],"architectures":[56],"like":[57],"long":[58],"short-term":[59],"memory":[60],"(LSTM).":[61],"aim":[63],"this":[65],"study":[66],"is":[67,85,164],"to":[68,87,119,124,146,154,165,189,193],"create":[69],"a":[70,148],"AI-driven":[72],"platform":[73,84],"tailored":[74],"both":[76],"Indian":[78],"international":[80],"markets.":[82],"This":[83],"designed":[86],"assist":[88],"retail":[89,156],"investors":[90,171],"in":[91,158,177],"navigating":[92],"digital":[93],"environments":[94],"by":[95],"employing":[96],"various":[97],"LSTM":[98,122,144],"algorithms.":[99],"Its":[100],"primary":[101],"goals":[102],"include":[103],"predicting":[104],"price":[106,139],"fluctuations,":[107],"pinpointing":[108],"potential":[109],"investment":[110],"prospects,":[111],"refining":[113],"trading":[114],"strategies.":[115],"application":[117,168],"aims":[118],"leverage":[120,190],"advanced":[121],"algorithms":[123,145],"analyze":[125],"historical":[126],"data,":[128],"recognize":[129],"patterns,":[130],"provide":[132],"real-time":[133],"insights.":[134],"It":[135],"will":[136],"take":[137,147],"past":[138],"process":[141],"it":[142],"through":[143],"logical":[149],"decision.":[150],"In":[151],"quest":[153],"broaden":[155],"participation":[157],"capital":[160],"markets,":[161],"effort":[163],"develop":[166],"an":[167],"novice":[170],"who":[172],"either":[173],"have":[174],"no":[175],"time":[176],"research":[178],"are":[180],"victims":[182],"financial":[184],"mis-selling":[185],"enable":[187],"them":[188],"technology":[192],"their":[194],"advantage.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}