{"id":"https://openalex.org/W3027733516","doi":"https://doi.org/10.1109/cis-ram47153.2019.9095772","title":"From Technical Analysis to Text Analytics: Stock and Index Prediction with GRU","display_name":"From Technical Analysis to Text Analytics: Stock and Index Prediction with GRU","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3027733516","doi":"https://doi.org/10.1109/cis-ram47153.2019.9095772","mag":"3027733516"},"language":"en","primary_location":{"id":"doi:10.1109/cis-ram47153.2019.9095772","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cis-ram47153.2019.9095772","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM)","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":null,"display_name":"T.-T. Teoh","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"T.-T. Teoh","raw_affiliation_strings":["Nanyang Business School, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Business School, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042844366","display_name":"Wonhyuk Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"W. T. Lim","raw_affiliation_strings":["Nanyang Business School, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Business School, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058843952","display_name":"Kevin Koh","orcid":"https://orcid.org/0000-0001-5042-503X"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"K. W. Koh","raw_affiliation_strings":["Nanyang Business School, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Business School, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044916548","display_name":"Jaehyun Soh","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"J. J. Soh","raw_affiliation_strings":["Nanyang Business School, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Business School, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102855246","display_name":"Teng Tan","orcid":"https://orcid.org/0000-0002-8217-6557"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"T. Tan","raw_affiliation_strings":["Nanyang Business School, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Business School, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113021027","display_name":"S.Y. Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"S.Y. Liu","raw_affiliation_strings":["Nanyang Business School, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Business School, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083267686","display_name":"Yok-Yen Nguwi","orcid":"https://orcid.org/0000-0001-7021-9188"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Y.-Y. Nguwi","raw_affiliation_strings":["Nanyang Business School, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Business School, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.8249,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.78326707,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"496","last_page":"500"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9832000136375427,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9775999784469604,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"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/computer-science","display_name":"Computer science","score":0.7128133773803711},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6340435743331909},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6261765956878662},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.6216079592704773},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5972000360488892},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5683842301368713},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5636652708053589},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5488142371177673},{"id":"https://openalex.org/keywords/closing","display_name":"Closing (real estate)","score":0.5365078449249268},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4932712912559509},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.4758469760417938},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.46801862120628357},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.46662792563438416},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42968153953552246},{"id":"https://openalex.org/keywords/stock-market-index","display_name":"Stock market index","score":0.42046409845352173},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.4027891755104065},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3532434105873108},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10826140642166138},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.10500332713127136}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7128133773803711},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6340435743331909},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6261765956878662},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.6216079592704773},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5972000360488892},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5683842301368713},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5636652708053589},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5488142371177673},{"id":"https://openalex.org/C2778775528","wikidata":"https://www.wikidata.org/wiki/Q5135432","display_name":"Closing (real estate)","level":2,"score":0.5365078449249268},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4932712912559509},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.4758469760417938},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.46801862120628357},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.46662792563438416},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42968153953552246},{"id":"https://openalex.org/C88389905","wikidata":"https://www.wikidata.org/wiki/Q223371","display_name":"Stock market index","level":4,"score":0.42046409845352173},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.4027891755104065},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3532434105873108},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10826140642166138},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.10500332713127136},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cis-ram47153.2019.9095772","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cis-ram47153.2019.9095772","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W633661686","https://openalex.org/W1570209723","https://openalex.org/W1606532857","https://openalex.org/W2049421816","https://openalex.org/W2054592136","https://openalex.org/W2056204285","https://openalex.org/W2092373177","https://openalex.org/W3216539911","https://openalex.org/W4233796571","https://openalex.org/W6600516592","https://openalex.org/W6804807188"],"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/W2516969888"],"abstract_inverted_index":{"Technical":[0],"Analysis":[1],"is":[2],"a":[3,40],"trading":[4],"practice":[5],"to":[6,15,81,101,127,131,175],"identify":[7],"and":[8,59,67,89,163],"observe":[9,128],"the":[10,27,51,83,138,146,150],"changes":[11],"in":[12,31,43,75],"stock":[13,88],"movements":[14],"anticipate":[16],"future":[17],"movement.":[18],"It":[19],"operates":[20],"mainly":[21],"by":[22],"observing":[23],"patterns":[24],"discovered":[25],"among":[26],"historical":[28],"closing":[29],"prices":[30],"numeric":[32],"form.":[33],"Studies":[34],"have":[35],"shown":[36],"that":[37,137],"sentiments":[38,164],"play":[39],"significant":[41],"role":[42],"stocks":[44,58,66],"movement":[45,70],"prediction":[46],"[1]-[3].":[47],"This":[48],"work":[49],"studies":[50],"effect":[52],"of":[53,87,97,161,173],"adding":[54],"text":[55],"data":[56],"into":[57],"index":[60,69],"prediction.":[61,133],"We":[62,77],"studied":[63],"major":[64],"technological":[65],"NASDAQ":[68],"which":[71],"are":[72],"highly":[73],"volatile":[74],"nature.":[76],"set":[78],"up":[79],"experiments":[80],"predict":[82],"10-day":[84],"forward":[85],"momentum":[86],"index.":[90],"In":[91],"this":[92],"work,":[93],"we":[94],"make":[95,132],"use":[96],"machine":[98],"learning":[99,168],"techniques":[100],"establish":[102],"10":[103],"different":[104],"models":[105,141,155],"including":[106],"decision":[107],"tree,":[108],"random":[109],"forest,":[110],"K-nearest":[111],"neighbors,":[112],"support":[113],"vector":[114],"machine,":[115],"recurrent":[116,124],"neural":[117,153],"network,":[118,122],"long-short":[119],"term":[120],"memory":[121],"gated":[123],"unit":[125],"network":[126,140,154],"their":[129],"ability":[130],"The":[134,159],"results":[135],"illustrate":[136],"non-neural":[139],"experience":[142],"over-fitting":[143],"issue":[144],"despite":[145],"good":[147],"accuracy.":[148],"On":[149],"other":[151],"hand,":[152],"require":[156],"more":[157],"data.":[158],"addition":[160],"news":[162],"can":[165],"improve":[166],"deep":[167],"models'":[169],"performance":[170],"from":[171],"accuracy":[172],"50.1%":[174],"78.57%.":[176]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
