{"id":"https://openalex.org/W4200255832","doi":"https://doi.org/10.1155/2021/2917577","title":"Is It Possible to Earn Abnormal Return in an Inefficient Market? An Approach Based on Machine Learning in Stock Trading","display_name":"Is It Possible to Earn Abnormal Return in an Inefficient Market? An Approach Based on Machine Learning in Stock Trading","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W4200255832","doi":"https://doi.org/10.1155/2021/2917577","pmid":"https://pubmed.ncbi.nlm.nih.gov/34963777"},"language":"en","primary_location":{"id":"doi:10.1155/2021/2917577","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2917577","pdf_url":"https://downloads.hindawi.com/journals/cin/2021/2917577.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/cin/2021/2917577.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088106269","display_name":"B\u00f9i Th\u00e0nh Khoa","orcid":"https://orcid.org/0000-0002-9878-2164"},"institutions":[{"id":"https://openalex.org/I4210096063","display_name":"Ho Chi Minh City Open University","ror":"https://ror.org/00tean533","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210096063"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Bui Thanh Khoa","raw_affiliation_strings":["Finance, Economics, and Management Research Group, Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam"],"affiliations":[{"raw_affiliation_string":"Finance, Economics, and Management Research Group, Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam","institution_ids":["https://openalex.org/I4210096063"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029799094","display_name":"Tr\u1ea7n Tr\u1ecdng Hu\u1ef3nh","orcid":"https://orcid.org/0000-0001-9145-2894"},"institutions":[{"id":"https://openalex.org/I109689652","display_name":"FPT University","ror":"https://ror.org/03esj4g97","country_code":"VN","type":"education","lineage":["https://openalex.org/I109689652"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Tran Trong Huynh","raw_affiliation_strings":["FPT University, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"FPT University, Hanoi, Vietnam","institution_ids":["https://openalex.org/I109689652"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088106269"],"corresponding_institution_ids":["https://openalex.org/I4210096063"],"apc_list":{"value":2100,"currency":"USD","value_usd":2100},"apc_paid":{"value":2100,"currency":"USD","value_usd":2100},"fwci":2.8633,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.9091434,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"2021","issue":"1","first_page":"2917577","last_page":"2917577"},"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":0.9980000257492065,"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":0.9965000152587891,"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/business","display_name":"Business","score":0.5159164667129517},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.5082504153251648},{"id":"https://openalex.org/keywords/trading-strategy","display_name":"Trading strategy","score":0.4928288757801056},{"id":"https://openalex.org/keywords/portfolio","display_name":"Portfolio","score":0.49016889929771423},{"id":"https://openalex.org/keywords/stock-exchange","display_name":"Stock exchange","score":0.4689606726169586},{"id":"https://openalex.org/keywords/financial-economics","display_name":"Financial economics","score":0.45106273889541626},{"id":"https://openalex.org/keywords/stock-market-index","display_name":"Stock market index","score":0.44555357098579407},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.4411618113517761},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.4182211756706238},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.3677116632461548},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3404896855354309},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.2674552798271179},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.25178927183151245},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.19993609189987183},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1323959231376648}],"concepts":[{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.5159164667129517},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.5082504153251648},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.4928288757801056},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.49016889929771423},{"id":"https://openalex.org/C200870193","wikidata":"https://www.wikidata.org/wiki/Q11691","display_name":"Stock exchange","level":2,"score":0.4689606726169586},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.45106273889541626},{"id":"https://openalex.org/C88389905","wikidata":"https://www.wikidata.org/wiki/Q223371","display_name":"Stock market index","level":4,"score":0.44555357098579407},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4411618113517761},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.4182211756706238},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3677116632461548},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3404896855354309},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.2674552798271179},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.25178927183151245},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.19993609189987183},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1323959231376648},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007449","descriptor_name":"Investments","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007449","descriptor_name":"Investments","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007449","descriptor_name":"Investments","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D058873","descriptor_name":"Pandemics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D058873","descriptor_name":"Pandemics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D058873","descriptor_name":"Pandemics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1155/2021/2917577","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2917577","pdf_url":"https://downloads.hindawi.com/journals/cin/2021/2917577.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},{"id":"pmid:34963777","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34963777","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational intelligence and neuroscience","raw_type":null},{"id":"pmh:oai:doaj.org/article:1f2c2260656e47b58ec5dfe278c325a9","is_oa":true,"landing_page_url":"https://doaj.org/article/1f2c2260656e47b58ec5dfe278c325a9","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":"Computational Intelligence and Neuroscience, Vol 2021 (2021)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:8710363","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8710363","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Comput Intell Neurosci","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1155/2021/2917577","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2917577","pdf_url":"https://downloads.hindawi.com/journals/cin/2021/2917577.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4200255832.pdf","grobid_xml":"https://content.openalex.org/works/W4200255832.grobid-xml"},"referenced_works_count":77,"referenced_works":["https://openalex.org/W33891176","https://openalex.org/W234640303","https://openalex.org/W1534292004","https://openalex.org/W1588863263","https://openalex.org/W1836069407","https://openalex.org/W1940590295","https://openalex.org/W1959284290","https://openalex.org/W1978575620","https://openalex.org/W1980836123","https://openalex.org/W1992175460","https://openalex.org/W1996594817","https://openalex.org/W2012079387","https://openalex.org/W2025053102","https://openalex.org/W2032170121","https://openalex.org/W2032367279","https://openalex.org/W2037717024","https://openalex.org/W2039935421","https://openalex.org/W2061859805","https://openalex.org/W2067374063","https://openalex.org/W2068805783","https://openalex.org/W2071036467","https://openalex.org/W2081402090","https://openalex.org/W2084273726","https://openalex.org/W2087963635","https://openalex.org/W2090637028","https://openalex.org/W2094385112","https://openalex.org/W2105904034","https://openalex.org/W2118378381","https://openalex.org/W2138293190","https://openalex.org/W2153580489","https://openalex.org/W2165453772","https://openalex.org/W2172073485","https://openalex.org/W2172137905","https://openalex.org/W2183526542","https://openalex.org/W2200777151","https://openalex.org/W2202875375","https://openalex.org/W2313112061","https://openalex.org/W2395786628","https://openalex.org/W2400770063","https://openalex.org/W2526248091","https://openalex.org/W2535131375","https://openalex.org/W2592858280","https://openalex.org/W2606299602","https://openalex.org/W2746771610","https://openalex.org/W2794904450","https://openalex.org/W2795679926","https://openalex.org/W2809274349","https://openalex.org/W2904656275","https://openalex.org/W2971659559","https://openalex.org/W2977280727","https://openalex.org/W3017193407","https://openalex.org/W3024864927","https://openalex.org/W3045738921","https://openalex.org/W3090534603","https://openalex.org/W3122558997","https://openalex.org/W3123598380","https://openalex.org/W3124084377","https://openalex.org/W3124125434","https://openalex.org/W3126932198","https://openalex.org/W3134206323","https://openalex.org/W3151910759","https://openalex.org/W3208578359","https://openalex.org/W3215843613","https://openalex.org/W4210603519","https://openalex.org/W4230871672","https://openalex.org/W4231546411","https://openalex.org/W4234848434","https://openalex.org/W4239510810","https://openalex.org/W4244218025","https://openalex.org/W4248125267","https://openalex.org/W4249692389","https://openalex.org/W4250886548","https://openalex.org/W4251074844","https://openalex.org/W4251742615","https://openalex.org/W4252771961","https://openalex.org/W6684095520","https://openalex.org/W6804681714"],"related_works":["https://openalex.org/W4293452383","https://openalex.org/W2990652064","https://openalex.org/W3134659362","https://openalex.org/W3123122373","https://openalex.org/W4386639254","https://openalex.org/W2360554747","https://openalex.org/W3208509893","https://openalex.org/W2611464132","https://openalex.org/W2049127694","https://openalex.org/W2363401122"],"abstract_inverted_index":{"Risk":[0],"management":[1],"and":[2,12,87,109,114,139,150,167,180,188,231],"stock":[3,33,142,218],"investment":[4,55,192],"decision-making":[5],"is":[6,30,43,58,66,157,214],"an":[7,49,53,73],"essential":[8],"topic":[9],"for":[10,75,207,221],"investors":[11,46,223,238],"fund":[13],"managers,":[14],"especially":[15],"in":[16,106,175],"the":[17,20,28,41,61,64,83,107,121,127,145,160,172,178,198],"context":[18],"of":[19,60,104,155,164,186],"COVID-19":[21],"pandemic.":[22],"The":[23,153,194],"problem":[24],"becomes":[25],"easier":[26],"if":[27,40],"market":[29,42,86],"efficient,":[31,45],"where":[32],"prices":[34],"fully":[35],"reflect":[36],"potential":[37],"risk.":[38],"Nevertheless,":[39],"not":[44],"may":[47],"have":[48,233],"opportunity":[50,74],"to":[51,81,92,112,125,140,177,190,215,224,242],"find":[52],"effective":[54,235],"method.":[56],"Vietnam":[57],"one":[59],"emerging":[62],"markets;":[63],"efficiency":[65],"still":[67],"weak.":[68],"Thus,":[69],"there":[70],"will":[71],"be":[72],"astute":[76],"investors.":[77],"This":[78,169,210],"study":[79,100,170],"aims":[80],"test":[82,126,138,195],"weak-form":[84,199],"efficient":[85],"provide":[88,216],"a":[89,117,136,217],"modern":[90],"approach":[91,124],"investors'":[93],"decision-making.":[94],"To":[95],"achieve":[96,243],"that":[97],"aim,":[98],"this":[99],"uses":[101],"historical":[102],"data":[103],"stocks":[105,156],"VN-Index":[108,187],"VN30":[110,189],"portfolio":[111],"buy":[113],"sell":[115],"within":[116],"one-day":[118],"period":[119],"under":[120],"rolling":[122],"window":[123],"Ho":[128],"Chi":[129],"Minh":[130],"City":[131],"Stock":[132],"Exchange":[133],"(HoSE)":[134],"through":[135],"runs":[137],"perform":[141],"trading":[143,219,226,236],"using":[144],"support":[146],"vector":[147],"machine":[148],"(SVM)":[149],"logistic":[151,165,229],"regression.":[152],"buying/selling":[154],"guided":[158],"by":[159],"forecasted":[161],"outcomes":[162],"(increase/decrease)":[163],"regression":[166,230],"SVM.":[168],"adjusted":[171],"return":[173],"rate":[174],"proportion":[176],"risks":[179],"compared":[181],"it":[182],"with":[183],"index":[184],"investments":[185],"evaluate":[191],"efficiency.":[193],"results":[196],"dismissed":[197],"efficient-market":[200],"hypothesis,":[201],"which":[202],"opens":[203],"up":[204],"many":[205],"opportunities":[206],"short-term":[208,222],"traders.":[209],"study's":[211],"primary":[212],"contribution":[213],"strategy":[220],"maximize":[225],"profits.":[227],"Because":[228],"SVM":[232],"proven":[234],"methods,":[237],"can":[239],"use":[240],"them":[241],"abnormal":[244],"returns.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":5}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}