{"id":"https://openalex.org/W3203903097","doi":"https://doi.org/10.1145/3471287.3471289","title":"Nepal Stock Market Movement Prediction with Machine Learning","display_name":"Nepal Stock Market Movement Prediction with Machine Learning","publication_year":2021,"publication_date":"2021-05-27","ids":{"openalex":"https://openalex.org/W3203903097","doi":"https://doi.org/10.1145/3471287.3471289","mag":"3203903097"},"language":"en","primary_location":{"id":"doi:10.1145/3471287.3471289","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3471287.3471289","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 the 5th International Conference on Information System and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027757795","display_name":"Shunan Zhao","orcid":"https://orcid.org/0000-0002-4700-9403"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shunan Zhao","raw_affiliation_strings":["Nankai University, China"],"affiliations":[{"raw_affiliation_string":"Nankai University, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5027757795"],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":0.1743,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55059235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9945999979972839,"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"}},{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9886999726295471,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6397191286087036},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5738458633422852},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5377640128135681},{"id":"https://openalex.org/keywords/economic-shortage","display_name":"Economic shortage","score":0.5175870656967163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5174851417541504},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5084778070449829},{"id":"https://openalex.org/keywords/financial-market","display_name":"Financial market","score":0.4919126033782959},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.46368497610092163},{"id":"https://openalex.org/keywords/closing","display_name":"Closing (real estate)","score":0.43851137161254883},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.4269661605358124},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.42534762620925903},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.41936370730400085},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.2779369056224823},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.2585464119911194},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14828887581825256},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13072076439857483}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6397191286087036},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5738458633422852},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5377640128135681},{"id":"https://openalex.org/C194051981","wikidata":"https://www.wikidata.org/wiki/Q1337691","display_name":"Economic shortage","level":3,"score":0.5175870656967163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5174851417541504},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5084778070449829},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.4919126033782959},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.46368497610092163},{"id":"https://openalex.org/C2778775528","wikidata":"https://www.wikidata.org/wiki/Q5135432","display_name":"Closing (real estate)","level":2,"score":0.43851137161254883},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.4269661605358124},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.42534762620925903},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.41936370730400085},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.2779369056224823},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.2585464119911194},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14828887581825256},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13072076439857483},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.0},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3471287.3471289","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3471287.3471289","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 the 5th International Conference on Information System and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W2899619587","https://openalex.org/W2963763250","https://openalex.org/W3006845699","https://openalex.org/W3012362112","https://openalex.org/W3031664953","https://openalex.org/W3080113688","https://openalex.org/W3082523044","https://openalex.org/W3082540584","https://openalex.org/W3084759552","https://openalex.org/W3097382998","https://openalex.org/W3100102918","https://openalex.org/W6600042794","https://openalex.org/W6601630192"],"related_works":["https://openalex.org/W2116422677","https://openalex.org/W2517007886","https://openalex.org/W2383994331","https://openalex.org/W1522019333","https://openalex.org/W278047738","https://openalex.org/W2076369646","https://openalex.org/W2373884197","https://openalex.org/W4244817184","https://openalex.org/W2961923709","https://openalex.org/W2645942849"],"abstract_inverted_index":{"Financial":[0],"market":[1,62],"predicting":[2],"is":[3],"a":[4],"popular":[5],"theme":[6],"of":[7,9,17,55],"lots":[8],"researches":[10],"in":[11,24,44,63,143],"recent":[12],"years.":[13],"However,":[14],"the":[15,91,105,137,144],"majority":[16],"previous":[18],"studies":[19],"are":[20,36,136],"focus":[21],"on":[22,67],"markets":[23],"great":[25],"countries":[26,35],"like":[27],"China":[28],"and":[29,51,99,119,131,135],"United":[30],"States,":[31],"while":[32],"some":[33],"small":[34],"drawn":[37],"less":[38],"attention.":[39],"To":[40],"cover":[41],"this":[42,64],"shortage":[43],"current":[45],"literature,":[46],"we":[47,80,126],"determined":[48],"to":[49,59,89],"use":[50],"compare":[52],"17":[53],"types":[54],"machine":[56],"learning":[57],"models":[58],"foresee":[60],"Nepal":[61],"paper.":[65],"Based":[66],"stock":[68],"prices,":[69],"10":[70],"technical":[71],"indicators":[72],"were":[73],"computed":[74],"as":[75],"input":[76],"features.":[77],"In":[78],"addition,":[79],"also":[81],"added":[82],"emotional":[83],"factors":[84],"extracted":[85],"from":[86],"financial":[87],"news":[88],"improve":[90],"prediction":[92],"performance,":[93],"which":[94],"was":[95],"evaluated":[96],"by":[97],"accuracy":[98],"F1":[100],"score.":[101],"We":[102],"predicted":[103],"whether":[104],"closing":[106],"price":[107],"would":[108],"rise":[109],"or":[110],"descend":[111],"after":[112],"three":[113],"horizons:":[114],"1-day":[115],"movement,":[116],"15-day":[117],"movement":[118],"30-day":[120],"movement.":[121],"From":[122],"our":[123],"experiment":[124],"results,":[125],"found":[127],"that":[128],"linear":[129],"SVM":[130],"XGBoost":[132],"perform":[133],"best":[134,138],"options":[139],"for":[140],"further":[141],"consideration":[142],"trading":[145],"process.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
