{"id":"https://openalex.org/W4409173181","doi":"https://doi.org/10.1007/s42979-025-03848-y","title":"A Quest for Context-Specific Stock Price Prediction: A Comparison Between Time Series, Machine Learning and Deep Learning Models","display_name":"A Quest for Context-Specific Stock Price Prediction: A Comparison Between Time Series, Machine Learning and Deep Learning Models","publication_year":2025,"publication_date":"2025-04-02","ids":{"openalex":"https://openalex.org/W4409173181","doi":"https://doi.org/10.1007/s42979-025-03848-y"},"language":"en","primary_location":{"id":"doi:10.1007/s42979-025-03848-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-025-03848-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-03848-y.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-03848-y.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005698696","display_name":"Mugdha Shailendra Kulkarni","orcid":"https://orcid.org/0000-0001-5443-0725"},"institutions":[{"id":"https://openalex.org/I244572783","display_name":"Symbiosis International University","ror":"https://ror.org/005r2ww51","country_code":"IN","type":"education","lineage":["https://openalex.org/I244572783"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Mugdha Shailendra Kulkarni","raw_affiliation_strings":["Symbiosis Centre for Information Technology, Symbiosis International (Deemed University), Pune, India"],"affiliations":[{"raw_affiliation_string":"Symbiosis Centre for Information Technology, Symbiosis International (Deemed University), Pune, India","institution_ids":["https://openalex.org/I244572783"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011333269","display_name":"S. Vijayakumar Bharathi","orcid":"https://orcid.org/0000-0002-9667-6181"},"institutions":[{"id":"https://openalex.org/I244572783","display_name":"Symbiosis International University","ror":"https://ror.org/005r2ww51","country_code":"IN","type":"education","lineage":["https://openalex.org/I244572783"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"S. Vijayakumar Bharathi","raw_affiliation_strings":["Symbiosis Centre for Information Technology, Symbiosis International (Deemed University), Pune, India"],"affiliations":[{"raw_affiliation_string":"Symbiosis Centre for Information Technology, Symbiosis International (Deemed University), Pune, India","institution_ids":["https://openalex.org/I244572783"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009564606","display_name":"Arif Perdana","orcid":null},"institutions":[{"id":"https://openalex.org/I4210121067","display_name":"Monash Health","ror":"https://ror.org/02t1bej08","country_code":"AU","type":"healthcare","lineage":["https://openalex.org/I4210121067"]},{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Arif Perdana","raw_affiliation_strings":["Monash University, Monash, Indonesia"],"affiliations":[{"raw_affiliation_string":"Monash University, Monash, Indonesia","institution_ids":["https://openalex.org/I56590836","https://openalex.org/I4210121067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5092105111","display_name":"Divisha Kilari","orcid":null},"institutions":[{"id":"https://openalex.org/I244572783","display_name":"Symbiosis International University","ror":"https://ror.org/005r2ww51","country_code":"IN","type":"education","lineage":["https://openalex.org/I244572783"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Divisha Kilari","raw_affiliation_strings":["Symbiosis Centre for Information Technology, Symbiosis International (Deemed University), Pune, India"],"affiliations":[{"raw_affiliation_string":"Symbiosis Centre for Information Technology, Symbiosis International (Deemed University), Pune, India","institution_ids":["https://openalex.org/I244572783"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5005698696"],"corresponding_institution_ids":["https://openalex.org/I244572783"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":12.6638,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.98423333,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"6","issue":"4","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":0.9998999834060669,"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":0.9998999834060669,"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":0.9962999820709229,"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":0.995199978351593,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.5858096480369568},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5834376811981201},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5365560054779053},{"id":"https://openalex.org/keywords/stock-price","display_name":"Stock price","score":0.5293194651603699},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5119305849075317},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47978144884109497},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4793837070465088},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.47176769375801086},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.40275174379348755},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10729870200157166},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06507590413093567},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.059927672147750854}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5858096480369568},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5834376811981201},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5365560054779053},{"id":"https://openalex.org/C2988984586","wikidata":"https://www.wikidata.org/wiki/Q1020013","display_name":"Stock price","level":3,"score":0.5293194651603699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5119305849075317},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47978144884109497},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4793837070465088},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.47176769375801086},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.40275174379348755},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10729870200157166},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06507590413093567},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.059927672147750854},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s42979-025-03848-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-025-03848-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-03848-y.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:monash.edu:publications/62d0bd17-5155-4b1f-91c5-8054a967c918","is_oa":true,"landing_page_url":"https://research.monash.edu/en/publications/62d0bd17-5155-4b1f-91c5-8054a967c918","pdf_url":null,"source":{"id":"https://openalex.org/S4306402625","display_name":"Monash University Research Portal (Monash University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56590836","host_organization_name":"Monash University","host_organization_lineage":["https://openalex.org/I56590836"],"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":"Kulkarni, M S, Vijayakumar Bharathi, S, Perdana, A & Kilari, D 2025, 'A Quest for Context-Specific Stock Price Prediction : A Comparison Between Time Series, Machine Learning and Deep Learning Models', SN Computer Science, vol. 6, no. 4, 335. https://doi.org/10.1007/s42979-025-03848-y","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s42979-025-03848-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-025-03848-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-03848-y.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320971","display_name":"Monash University","ror":"https://ror.org/02bfwt286"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409173181.pdf","grobid_xml":"https://content.openalex.org/works/W4409173181.grobid-xml"},"referenced_works_count":94,"referenced_works":["https://openalex.org/W197787652","https://openalex.org/W333233685","https://openalex.org/W1489293997","https://openalex.org/W1969852690","https://openalex.org/W1980836123","https://openalex.org/W1981531537","https://openalex.org/W1986078433","https://openalex.org/W2004463884","https://openalex.org/W2039935421","https://openalex.org/W2066456070","https://openalex.org/W2081700482","https://openalex.org/W2084029682","https://openalex.org/W2102148524","https://openalex.org/W2132050943","https://openalex.org/W2136738732","https://openalex.org/W2171315676","https://openalex.org/W2236744271","https://openalex.org/W2319203258","https://openalex.org/W2331820705","https://openalex.org/W2501208968","https://openalex.org/W2588718483","https://openalex.org/W2607162077","https://openalex.org/W2607717215","https://openalex.org/W2618452680","https://openalex.org/W2624385633","https://openalex.org/W2756737320","https://openalex.org/W2765776117","https://openalex.org/W2773057751","https://openalex.org/W2783385646","https://openalex.org/W2790130885","https://openalex.org/W2799635155","https://openalex.org/W2799827709","https://openalex.org/W2804153171","https://openalex.org/W2808626748","https://openalex.org/W2833425706","https://openalex.org/W2900329809","https://openalex.org/W2900880305","https://openalex.org/W2911964244","https://openalex.org/W2914419771","https://openalex.org/W2917600866","https://openalex.org/W2921052252","https://openalex.org/W2938903045","https://openalex.org/W2946975908","https://openalex.org/W2949202718","https://openalex.org/W2958168524","https://openalex.org/W2969886070","https://openalex.org/W3002756429","https://openalex.org/W3005880472","https://openalex.org/W3007066689","https://openalex.org/W3009457452","https://openalex.org/W3014278717","https://openalex.org/W3015228848","https://openalex.org/W3085968515","https://openalex.org/W3093310271","https://openalex.org/W3097382998","https://openalex.org/W3107642158","https://openalex.org/W3125589452","https://openalex.org/W3155588839","https://openalex.org/W3156409915","https://openalex.org/W3162969943","https://openalex.org/W3164870412","https://openalex.org/W3172498855","https://openalex.org/W3175646119","https://openalex.org/W3175934715","https://openalex.org/W3200451784","https://openalex.org/W3208685123","https://openalex.org/W3216663761","https://openalex.org/W3217626109","https://openalex.org/W4210342290","https://openalex.org/W4212791338","https://openalex.org/W4212883601","https://openalex.org/W4213276360","https://openalex.org/W4226142228","https://openalex.org/W4226160099","https://openalex.org/W4226366386","https://openalex.org/W4241115065","https://openalex.org/W4243030942","https://openalex.org/W4281848794","https://openalex.org/W4300511110","https://openalex.org/W4306664945","https://openalex.org/W4308433757","https://openalex.org/W4313343713","https://openalex.org/W4313830571","https://openalex.org/W4319160636","https://openalex.org/W4381569929","https://openalex.org/W4382173466","https://openalex.org/W4385386345","https://openalex.org/W4390541186","https://openalex.org/W4390858905","https://openalex.org/W4391554440","https://openalex.org/W4391751939","https://openalex.org/W4392886283","https://openalex.org/W4396787053","https://openalex.org/W4400478149"],"related_works":["https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660","https://openalex.org/W247222457","https://openalex.org/W1488120909","https://openalex.org/W3124131549","https://openalex.org/W2152348935","https://openalex.org/W2887069341","https://openalex.org/W2554106722"],"abstract_inverted_index":{"Abstract":[0],"Understanding":[1,151],"the":[2,58,94,100],"complexities":[3],"of":[4,57],"buying,":[5],"selling,":[6],"and":[7,14,51,74,85,117,160,163,169],"holding":[8],"stocks":[9],"is":[10,35,156],"crucial":[11,157],"for":[12,104,141,158],"institutional":[13,159],"individual":[15,161],"investors":[16,25,41,162],"to":[17,98,144,165],"make":[18],"informed":[19],"decisions.":[20,45],"Despite":[21],"their":[22,142,167],"significance,":[23],"many":[24],"face":[26],"challenges":[27],"in":[28,42],"this":[29],"area.":[30],"Accurate":[31],"stock":[32,49,63,89,105,125,147],"price":[33,90,106],"forecasting":[34],"a":[36],"vital":[37],"tool":[38],"that":[39,111],"aids":[40],"making":[43],"profitable":[44],"This":[46,77],"study":[47],"evaluates":[48],"trends":[50],"patterns":[52],"with":[53,84],"an":[54],"in-depth":[55],"analysis":[56],"Bombay":[59],"Stock":[60],"Exchange":[61],"(BSE)":[62],"data.":[64,91],"We":[65],"utilized":[66],"various":[67],"techniques,":[68],"including":[69],"time-series":[70],"analysis,":[71],"machine":[72,128],"learning,":[73],"deep-learning":[75],"models.":[76],"investigation":[78],"spanned":[79],"two":[80],"distinct":[81],"datasets:":[82],"one":[83,86],"without":[87],"COVID-19":[88],"By":[92],"comparing":[93],"outcomes,":[95],"we":[96],"seek":[97],"identify":[99],"most":[101],"effective":[102],"model":[103,113],"prediction.":[107],"Our":[108],"findings":[109],"indicate":[110],"each":[112,152],"has":[114],"its":[115],"strengths":[116],"limitations.":[118],"Time":[119],"series":[120],"models":[121,130],"accurately":[122],"forecast":[123],"short-term":[124],"prices,":[126],"whereas":[127],"learning":[129,136],"demonstrate":[131],"superior":[132],"generalization":[133],"capabilities.":[134],"Deep":[135],"models,":[137],"however,":[138],"stand":[139],"out":[140],"ability":[143],"predict":[145],"long-term":[146],"prices":[148],"more":[149],"accurately.":[150],"model's":[153],"performance":[154],"nuances":[155],"regulators":[164],"optimize":[166],"strategies":[168],"decision-making":[170],"processes.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
