{"id":"https://openalex.org/W4296474190","doi":"https://doi.org/10.1145/3543712.3543722","title":"Split Feature Space Ensemble Method using Deep Reinforcement Learning for Algorithmic Trading","display_name":"Split Feature Space Ensemble Method using Deep Reinforcement Learning for Algorithmic Trading","publication_year":2022,"publication_date":"2022-05-12","ids":{"openalex":"https://openalex.org/W4296474190","doi":"https://doi.org/10.1145/3543712.3543722"},"language":"en","primary_location":{"id":"doi:10.1145/3543712.3543722","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543712.3543722","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 8th International Conference on Computer Technology Applications","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/A5023602473","display_name":"Marcell N\u00e9meth","orcid":null},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":true,"raw_author_name":"Marcell N\u00e9meth","raw_affiliation_strings":["Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Hungary"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Hungary","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076485961","display_name":"G\u00e1bor Sz\u00fccs","orcid":"https://orcid.org/0000-0002-5781-1088"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"G\u00e1bor Sz\u0171cs","raw_affiliation_strings":["Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Hungary"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Hungary","institution_ids":["https://openalex.org/I29770179"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023602473"],"corresponding_institution_ids":["https://openalex.org/I29770179"],"apc_list":null,"apc_paid":null,"fwci":0.4909,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67505121,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"188","last_page":"194"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9993000030517578,"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":0.9993000030517578,"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":0.998199999332428,"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":0.9891999959945679,"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":0.8013441562652588},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7272469997406006},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6739010810852051},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6483280658721924},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6098275780677795},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.6030338406562805},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5938376784324646},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5697280168533325},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5055804252624512},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.4702058434486389},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3302161693572998},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32244372367858887},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17764949798583984}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8013441562652588},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7272469997406006},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6739010810852051},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6483280658721924},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6098275780677795},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.6030338406562805},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5938376784324646},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5697280168533325},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5055804252624512},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.4702058434486389},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3302161693572998},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32244372367858887},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17764949798583984},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3543712.3543722","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543712.3543722","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 8th International Conference on Computer Technology Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2043806097","https://openalex.org/W2076337359","https://openalex.org/W2103359683","https://openalex.org/W2130126738","https://openalex.org/W2145339207","https://openalex.org/W2156737235","https://openalex.org/W2173248099","https://openalex.org/W2260756217","https://openalex.org/W2563720985","https://openalex.org/W2824141369","https://openalex.org/W2914656440","https://openalex.org/W3012223895","https://openalex.org/W3088749011","https://openalex.org/W3089019288","https://openalex.org/W6661362345","https://openalex.org/W6669402789","https://openalex.org/W6683195989","https://openalex.org/W6689723076","https://openalex.org/W6741002519"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W3172436493","https://openalex.org/W4287164812","https://openalex.org/W2957492749","https://openalex.org/W1887135636","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849","https://openalex.org/W4285605394"],"abstract_inverted_index":{"In":[0],"the":[1,22,59,63,73,76,78,103,115,133,137],"financial":[2],"sector,":[3],"machine":[4],"learning":[5,31,69],"is":[6,50,85,92],"a":[7,52,95,110],"promising":[8],"tool,":[9],"which":[10],"can":[11],"be":[12],"utilized":[13],"in":[14,70],"stock":[15,35],"trading":[16,36],"as":[17],"well.":[18],"The":[19,44,128],"aim":[20],"of":[21,47,65,75,98,126],"research":[23],"was":[24],"to":[25,33],"develop":[26],"and":[27,40,62,121],"refine":[28],"deep":[29],"reinforcement":[30],"models":[32],"execute":[34],"that":[37,132],"maximizes":[38],"revenue":[39],"minimizes":[41],"investment":[42],"risk.":[43],"main":[45],"focus":[46],"this":[48],"paper":[49],"on":[51,57,102],"new":[53,111],"ensemble":[54,112,139],"technique":[55],"based":[56],"splitting":[58,106],"feature":[60,104],"space":[61,79,105],"optimization":[64],"decision-making":[66],"by":[67,81,87,94],"agents":[68],"parallel.":[71],"As":[72],"consequence":[74],"splitting,":[77],"formed":[80],"all":[82],"input":[83],"features":[84],"replaced":[86],"subspaces,":[88],"where":[89],"each":[90],"subspace":[91],"covered":[93],"functional":[96],"group":[97],"technical":[99],"indicators.":[100],"Based":[101],"idea,":[107],"we":[108],"proposed":[109,134],"method,":[113],"called":[114],"Split":[116],"Feature":[117],"Space":[118],"Ensemble":[119],"Method,":[120],"developed":[122],"three":[123],"model":[124],"variants":[125],"it.":[127],"experimental":[129],"results":[130],"show":[131],"method":[135],"outperforms":[136],"standard":[138],"approach.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
