{"id":"https://openalex.org/W4400948363","doi":"https://doi.org/10.1145/3672919.3673005","title":"Stock trading strategy based on reinforcement learning with GRU network","display_name":"Stock trading strategy based on reinforcement learning with GRU network","publication_year":2024,"publication_date":"2024-03-01","ids":{"openalex":"https://openalex.org/W4400948363","doi":"https://doi.org/10.1145/3672919.3673005"},"language":"en","primary_location":{"id":"doi:10.1145/3672919.3673005","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3672919.3673005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd International Conference on Cyber Security, Artificial Intelligence and Digital Economy","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/A5079364852","display_name":"Jipu Yu","orcid":"https://orcid.org/0009-0004-9213-327X"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jipu Yu","raw_affiliation_strings":["School of Information Science and Technology, Donghua University, China"],"raw_orcid":"https://orcid.org/0009-0004-9213-327X","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Donghua University, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090128836","display_name":"Xiaochen Lu","orcid":"https://orcid.org/0000-0003-1745-4992"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaochen Lu","raw_affiliation_strings":["School of Information Science and Technology, Donghua University, China"],"raw_orcid":"https://orcid.org/0000-0003-1745-4992","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Donghua University, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085124830","display_name":"Anqi Pan","orcid":"https://orcid.org/0000-0002-5100-3071"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anqi Pan","raw_affiliation_strings":["School of Information Science and Technology, Donghua University, China"],"raw_orcid":"https://orcid.org/0000-0002-5100-3071","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Donghua University, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063512990","display_name":"J. Y. Shi","orcid":"https://orcid.org/0009-0003-8317-5622"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaji Shi","raw_affiliation_strings":["School of Information Science and Technology, Donghua University, China"],"raw_orcid":"https://orcid.org/0009-0003-8317-5622","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Donghua University, China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079364852"],"corresponding_institution_ids":["https://openalex.org/I181326427"],"apc_list":null,"apc_paid":null,"fwci":0.4693,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66673945,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"480","last_page":"485"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9976000189781189,"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":0.9976000189781189,"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":0.9728999733924866,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9595000147819519,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7912445068359375},{"id":"https://openalex.org/keywords/stock-trading","display_name":"Stock trading","score":0.5798618793487549},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5793955326080322},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5281612277030945},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.42055103182792664},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.360553503036499},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.26648104190826416},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11840429902076721}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7912445068359375},{"id":"https://openalex.org/C2989233474","wikidata":"https://www.wikidata.org/wiki/Q7831917","display_name":"Stock trading","level":4,"score":0.5798618793487549},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5793955326080322},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5281612277030945},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.42055103182792664},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.360553503036499},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.26648104190826416},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11840429902076721},{"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/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"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/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3672919.3673005","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3672919.3673005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd International Conference on Cyber Security, Artificial Intelligence and Digital Economy","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2145339207","https://openalex.org/W2891295326","https://openalex.org/W2919115771","https://openalex.org/W2977590557","https://openalex.org/W3024896014","https://openalex.org/W3046559364","https://openalex.org/W3126577088","https://openalex.org/W3138503612","https://openalex.org/W4386012935","https://openalex.org/W4386401396"],"related_works":["https://openalex.org/W2888254471","https://openalex.org/W4283277338","https://openalex.org/W4287219598","https://openalex.org/W4206714504","https://openalex.org/W4391178413","https://openalex.org/W3130821343","https://openalex.org/W2504342329","https://openalex.org/W1481739708","https://openalex.org/W2093710055","https://openalex.org/W4280526326"],"abstract_inverted_index":{"The":[0,121],"complexity":[1],"and":[2,87,97],"dynamic":[3],"feature":[4],"of":[5,15],"the":[6,13,18,35,84,90,106,115],"stock":[7,39,101,111],"market":[8,30,102],"pose":[9],"significant":[10],"challenges":[11],"for":[12,63],"industry":[14],"finance,":[16],"where":[17],"traditional":[19],"trading":[20,40,65,112],"strategy":[21,41],"often":[22],"struggle":[23],"to":[24,34,58],"achieve":[25],"satisfactory":[26],"performances":[27],"across":[28],"different":[29],"conditions.":[31],"In":[32],"response":[33],"challenges,":[36],"an":[37],"automatic":[38,64],"based":[42],"on":[43,114],"reinforcement":[44,71],"learning":[45,72],"with":[46,117],"Gated":[47],"Recurrent":[48],"Unit":[49],"(GRU)":[50],"network":[51,55],"is":[52,56,68],"proposed.":[53],"GRU":[54],"employed":[57],"extract":[59],"rich":[60],"financial":[61],"features":[62],"decisions.":[66],"DQN":[67],"a":[69],"deep":[70],"method":[73],"that":[74,125],"can":[75,92],"solve":[76],"problems":[77],"in":[78,100],"high-dimensional":[79],"state":[80,86],"spaces.":[81],"Furthermore,":[82],"by":[83],"customized":[85],"reward":[88],"functions,":[89],"model":[91,127],"effectively":[93],"capture":[94],"underlying":[95],"relationships":[96],"potential":[98],"trends":[99],"data.":[103],"To":[104],"evaluate":[105],"proposed":[107],"model,":[108],"we":[109],"conducted":[110],"experiments":[113],"stocks":[116],"distinct":[118],"changing":[119],"trends.":[120],"experimental":[122],"results":[123],"show":[124],"our":[126],"surpasses":[128],"other":[129],"state-of-the-art":[130],"models.":[131]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}