{"id":"https://openalex.org/W2344786740","doi":"https://doi.org/10.1109/tnnls.2016.2522401","title":"Deep Direct Reinforcement Learning for Financial Signal Representation and Trading","display_name":"Deep Direct Reinforcement Learning for Financial Signal Representation and Trading","publication_year":2016,"publication_date":"2016-02-15","ids":{"openalex":"https://openalex.org/W2344786740","doi":"https://doi.org/10.1109/tnnls.2016.2522401","mag":"2344786740","pmid":"https://pubmed.ncbi.nlm.nih.gov/26890927"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2016.2522401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2016.2522401","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5082404485","display_name":"Yue Deng","orcid":"https://orcid.org/0000-0003-2871-8922"},"institutions":[{"id":"https://openalex.org/I180670191","display_name":"University of California, San Francisco","ror":"https://ror.org/043mz5j54","country_code":"US","type":"education","lineage":["https://openalex.org/I180670191"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Yue Deng","raw_affiliation_strings":["Automation Department, Tsinghua University, Beijing, China","School of Pharmacy, University of California at San Francisco, San Francisco, CA, USA"],"affiliations":[{"raw_affiliation_string":"Automation Department, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"School of Pharmacy, University of California at San Francisco, San Francisco, CA, USA","institution_ids":["https://openalex.org/I180670191"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022735755","display_name":"Feng Bao","orcid":"https://orcid.org/0000-0002-5721-9551"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Bao","raw_affiliation_strings":["Automation Department, Tsinghua University, Beijing, China","[Automation Department, Tsinghua University, Beijing, China]"],"affiliations":[{"raw_affiliation_string":"Automation Department, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"[Automation Department, Tsinghua University, Beijing, China]","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008751186","display_name":"Youyong Kong","orcid":"https://orcid.org/0000-0003-2095-8470"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youyong Kong","raw_affiliation_strings":["School of Computer Science and Engineering, Southeast University, Nanjing, China","[School of Computer Science and Engineering, Southeast University Nanjing, China]"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"[School of Computer Science and Engineering, Southeast University Nanjing, China]","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082017037","display_name":"Zhiquan Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiquan Ren","raw_affiliation_strings":["Automation Department, Tsinghua University, Beijing, China","[Automation Department, Tsinghua University, Beijing, China]"],"affiliations":[{"raw_affiliation_string":"Automation Department, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"[Automation Department, Tsinghua University, Beijing, China]","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080722708","display_name":"Qionghai Dai","orcid":"https://orcid.org/0000-0001-7043-3061"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qionghai Dai","raw_affiliation_strings":["Automation Department, Tsinghua University, Beijing, China","[Automation Department, Tsinghua University, Beijing, China]"],"affiliations":[{"raw_affiliation_string":"Automation Department, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"[Automation Department, Tsinghua University, Beijing, China]","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5082404485"],"corresponding_institution_ids":["https://openalex.org/I180670191","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":49.6948,"has_fulltext":false,"cited_by_count":765,"citation_normalized_percentile":{"value":0.99921228,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"28","issue":"3","first_page":"653","last_page":"664"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9936000108718872,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9916999936103821,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8670384883880615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7024977803230286},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7006150484085083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6903144717216492},{"id":"https://openalex.org/keywords/algorithmic-trading","display_name":"Algorithmic trading","score":0.5802528858184814},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5690020322799683},{"id":"https://openalex.org/keywords/financial-market","display_name":"Financial market","score":0.5653420686721802},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5550103783607483},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.4990501403808594},{"id":"https://openalex.org/keywords/trading-strategy","display_name":"Trading strategy","score":0.4967115521430969},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49569904804229736},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4700426459312439},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4472426772117615},{"id":"https://openalex.org/keywords/learning-classifier-system","display_name":"Learning classifier system","score":0.438446581363678},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4242994785308838},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.28174981474876404},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.10815709829330444}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8670384883880615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7024977803230286},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7006150484085083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6903144717216492},{"id":"https://openalex.org/C78508483","wikidata":"https://www.wikidata.org/wiki/Q139445","display_name":"Algorithmic trading","level":2,"score":0.5802528858184814},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5690020322799683},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.5653420686721802},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5550103783607483},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.4990501403808594},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.4967115521430969},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49569904804229736},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4700426459312439},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4472426772117615},{"id":"https://openalex.org/C199190896","wikidata":"https://www.wikidata.org/wiki/Q3509276","display_name":"Learning classifier system","level":3,"score":0.438446581363678},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4242994785308838},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.28174981474876404},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.10815709829330444},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"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/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2016.2522401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2016.2522401","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:26890927","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26890927","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":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G1792797213","display_name":null,"funder_award_id":"61120106003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6217526815","display_name":null,"funder_award_id":"BK20150650","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G8883308132","display_name":null,"funder_award_id":"61327902","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1515851193","https://openalex.org/W1570082825","https://openalex.org/W1761828760","https://openalex.org/W1898724844","https://openalex.org/W1977051850","https://openalex.org/W1996342763","https://openalex.org/W2006092805","https://openalex.org/W2041367235","https://openalex.org/W2052688942","https://openalex.org/W2059278667","https://openalex.org/W2072128103","https://openalex.org/W2072182757","https://openalex.org/W2092348774","https://openalex.org/W2097018403","https://openalex.org/W2098432798","https://openalex.org/W2107878631","https://openalex.org/W2108734173","https://openalex.org/W2111204393","https://openalex.org/W2111499159","https://openalex.org/W2114966857","https://openalex.org/W2117726420","https://openalex.org/W2119567691","https://openalex.org/W2119777970","https://openalex.org/W2121863487","https://openalex.org/W2124940450","https://openalex.org/W2126357802","https://openalex.org/W2130325614","https://openalex.org/W2136848157","https://openalex.org/W2143612262","https://openalex.org/W2145094598","https://openalex.org/W2145339207","https://openalex.org/W2147768505","https://openalex.org/W2150355110","https://openalex.org/W2152516042","https://openalex.org/W2153580489","https://openalex.org/W2156060469","https://openalex.org/W2158663270","https://openalex.org/W2161944915","https://openalex.org/W2169015875","https://openalex.org/W2169990839","https://openalex.org/W2997574889","https://openalex.org/W3097267636","https://openalex.org/W3121251852","https://openalex.org/W3121764760","https://openalex.org/W3121900378","https://openalex.org/W4214717370","https://openalex.org/W4231109964","https://openalex.org/W4232730838","https://openalex.org/W4248510338","https://openalex.org/W4253239620","https://openalex.org/W4298023569","https://openalex.org/W6674642818","https://openalex.org/W6676172287","https://openalex.org/W6681096077"],"related_works":["https://openalex.org/W4313491999","https://openalex.org/W3195402399","https://openalex.org/W2523594540","https://openalex.org/W4206190611","https://openalex.org/W4399587225","https://openalex.org/W4231485458","https://openalex.org/W4386992034","https://openalex.org/W4311038708","https://openalex.org/W4313641676","https://openalex.org/W4387142800"],"abstract_inverted_index":{"Can":[0],"we":[1,16,109],"train":[2],"the":[3,55,57,62,71,84,103,120,130,137,140],"computer":[4],"to":[5,18,82,117],"beat":[6],"experienced":[7],"traders":[8],"for":[9,30,66],"financial":[10,32],"assert":[11],"trading?":[12],"In":[13,54],"this":[14,20],"paper,":[15],"try":[17],"address":[19],"challenge":[21],"by":[22,41],"introducing":[23],"a":[24,97,111],"recurrent":[25,106],"deep":[26,47,76,104,125],"neural":[27,131],"network":[28],"(NN)":[29],"real-time":[31],"signal":[33],"representation":[34],"and":[35,50,78,105,139],"trading.":[36],"Our":[37],"model":[38],"is":[39,94,133],"inspired":[40],"two":[42],"biological-related":[43],"learning":[44,48,52,92],"concepts":[45],"of":[46,129],"(DL)":[49],"reinforcement":[51],"(RL).":[53],"framework,":[56],"DL":[58],"part":[59],"automatically":[60],"senses":[61],"dynamic":[63],"market":[64],"condition":[65],"informative":[67],"feature":[68],"learning.":[69],"Then,":[70],"RL":[72],"module":[73],"interacts":[74],"with":[75,119],"representations":[77],"makes":[79],"trading":[80],"decisions":[81],"accumulate":[83],"ultimate":[85],"rewards":[86],"in":[87,96,124],"an":[88],"unknown":[89],"environment.":[90],"The":[91,127],"system":[93,132],"implemented":[95],"complex":[98],"NN":[99],"that":[100],"exhibits":[101],"both":[102,136],"structures.":[107],"Hence,":[108],"propose":[110],"task-aware":[112],"backpropagation":[113],"through":[114],"time":[115],"method":[116],"cope":[118],"gradient":[121],"vanishing":[122],"issue":[123],"training.":[126],"robustness":[128],"verified":[134],"on":[135],"stock":[138],"commodity":[141],"future":[142],"markets":[143],"under":[144],"broad":[145],"testing":[146],"conditions.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":22},{"year":2025,"cited_by_count":87},{"year":2024,"cited_by_count":96},{"year":2023,"cited_by_count":111},{"year":2022,"cited_by_count":110},{"year":2021,"cited_by_count":106},{"year":2020,"cited_by_count":99},{"year":2019,"cited_by_count":80},{"year":2018,"cited_by_count":40},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":3}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}