{"id":"https://openalex.org/W2786348607","doi":"https://doi.org/10.1109/iscid.2017.210","title":"A Multi-objective Deep Reinforcement Learning Approach for Stock Index Future\u2019s Intraday Trading","display_name":"A Multi-objective Deep Reinforcement Learning Approach for Stock Index Future\u2019s Intraday Trading","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2786348607","doi":"https://doi.org/10.1109/iscid.2017.210","mag":"2786348607"},"language":"en","primary_location":{"id":"doi:10.1109/iscid.2017.210","doi":"https://doi.org/10.1109/iscid.2017.210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscid.2017.210","pdf_url":null,"source":{"id":"https://openalex.org/S4306420108","display_name":"International Symposium on Computational Intelligence and Design","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Symposium on Computational Intelligence and Design (ISCID)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5020387228","display_name":"Weiyu Si","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiyu Si","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100685738","display_name":"Jinke Li","orcid":"https://orcid.org/0000-0001-9454-4612","observed_orcids":["https://orcid.org/0000-0001-9454-4612"]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinke Li","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034937387","display_name":"Peng Ding","orcid":"https://orcid.org/0000-0001-7814-6606","observed_orcids":["https://orcid.org/0000-0001-7814-6606"]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Ding","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077732345","display_name":"Ruonan Rao","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruonan Rao","raw_affiliation_strings":["China Quantitative Investment Association, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Quantitative Investment Association, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.4176,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.95765306,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2017","issue":null,"first_page":"431","last_page":"436"},"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/T10047","display_name":"Financial Markets and Investment Strategies","score":9.999999747378752e-05,"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/T12123","display_name":"Financial Analysis and Corporate Governance","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/intraday-trading","display_name":"intraday trading","score":0.8669999837875366},{"id":"https://openalex.org/keywords/stock-index-futures","display_name":"stock index futures","score":0.9929999709129333},{"id":"https://openalex.org/keywords/multi-objective-reinforcement-learning","display_name":"multi-objective reinforcement learning","score":0.8080000281333923},{"id":"https://openalex.org/keywords/algorithmic-trading","display_name":"algorithmic trading","score":0.781000018119812},{"id":"https://openalex.org/keywords/transaction-costs","display_name":"transaction costs","score":0.6970000267028809}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8061928749084473},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7051625847816467},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.6706188321113586},{"id":"https://openalex.org/C78508483","wikidata":"https://www.wikidata.org/wiki/Q139445","display_name":"Algorithmic trading","level":2,"score":0.626966118812561},{"id":"https://openalex.org/C106306483","wikidata":"https://www.wikidata.org/wiki/Q183984","display_name":"Futures contract","level":2,"score":0.6038622260093689},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.572026252746582},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.5251756906509399},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49674469232559204},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.48625385761260986},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48026490211486816},{"id":"https://openalex.org/C181622380","wikidata":"https://www.wikidata.org/wiki/Q26911","display_name":"Profit (economics)","level":2,"score":0.4800490140914917},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.472459077835083},{"id":"https://openalex.org/C158876240","wikidata":"https://www.wikidata.org/wiki/Q17105131","display_name":"Pairs trade","level":4,"score":0.47096115350723267},{"id":"https://openalex.org/C24683644","wikidata":"https://www.wikidata.org/wiki/Q138372","display_name":"High-frequency trading","level":3,"score":0.46708035469055176},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.43784838914871216},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3784274756908417},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.2690909206867218},{"id":"https://openalex.org/C172428447","wikidata":"https://www.wikidata.org/wiki/Q438711","display_name":"Alternative trading system","level":3,"score":0.24613618850708008},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.14412763714790344},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.14324867725372314},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10907146334648132},{"id":"https://openalex.org/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iscid.2017.210","doi":"https://doi.org/10.1109/iscid.2017.210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscid.2017.210","pdf_url":null,"source":{"id":"https://openalex.org/S4306420108","display_name":"International Symposium on Computational Intelligence and Design","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Symposium on Computational Intelligence and Design (ISCID)","raw_type":"proceedings-article"},{"id":"mag:3127303210","doi":null,"is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201802211351860214","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W16011919","https://openalex.org/W1522301498","https://openalex.org/W1894533438","https://openalex.org/W1977051850","https://openalex.org/W1996342763","https://openalex.org/W2006092805","https://openalex.org/W2064675550","https://openalex.org/W2072128103","https://openalex.org/W2098063401","https://openalex.org/W2103359683","https://openalex.org/W2119567691","https://openalex.org/W2121863487","https://openalex.org/W2126909264","https://openalex.org/W2130325614","https://openalex.org/W2133564696","https://openalex.org/W2143612262","https://openalex.org/W2145339207","https://openalex.org/W2150339816","https://openalex.org/W2158663270","https://openalex.org/W2169015875","https://openalex.org/W2184761052","https://openalex.org/W2257979135","https://openalex.org/W2344786740","https://openalex.org/W2586702902","https://openalex.org/W2962887844","https://openalex.org/W2963167310","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W4214717370","https://openalex.org/W4231109964","https://openalex.org/W4242461611","https://openalex.org/W4298023569"],"related_works":["https://openalex.org/W3134096209","https://openalex.org/W4226140927","https://openalex.org/W2344786740","https://openalex.org/W2966021938","https://openalex.org/W4391437365","https://openalex.org/W3208869239","https://openalex.org/W4287124599","https://openalex.org/W4399459083","https://openalex.org/W4214771350","https://openalex.org/W4388664093"],"abstract_inverted_index":{"Modern":[0],"artificial":[1],"intelligence":[2],"has":[3],"been":[4],"widely":[5],"discussed":[6],"to":[7,23,75,99,154],"practice":[8],"in":[9],"automated":[10,165],"financial":[11,64,142,166],"asserts":[12],"trading.":[13,68,167],"Automated":[14],"intraday":[15,63],"trading":[16,102],"means":[17],"that":[18],"the":[19,24,31,35,48,71,78,108],"agent":[20],"can":[21],"react":[22],"market":[25,80,143],"conditions":[26],"automatically,":[27],"while":[28],"simultaneously":[29],"make":[30,100,155],"right":[32],"decisions.":[33,103],"Besides,":[34],"profits":[36],"will":[37],"be":[38],"made":[39],"within":[40],"a":[41,56,83,89,114,149],"day":[42],"considering":[43],"transaction":[44],"cost":[45],"charged":[46],"by":[47,88],"brokerage":[49],"company.":[50],"In":[51,104],"this":[52],"paper,":[53],"we":[54,112],"introduce":[55],"multiobjective":[57],"deep":[58,72],"reinforcement":[59,84],"learning":[60,85],"approach":[61],"for":[62],"signal":[65],"representation":[66],"and":[67,110,132,135,151],"We":[69,124],"design":[70],"neural":[73,94],"networks":[74],"automatically":[76],"discover":[77],"dynamic":[79],"features,":[81],"then":[82],"method":[86,153],"implemented":[87],"special":[90],"kind":[91],"of":[92,106],"recurrent":[93],"network":[95],"(LSTM)":[96],"is":[97],"applied":[98],"continuous":[101],"terms":[105],"balancing":[107],"profit":[109],"risk,":[111],"implement":[113],"multi-objective":[115],"structure":[116],"which":[117,157],"includes":[118],"two":[119],"objectives":[120],"with":[121],"different":[122],"weights.":[123],"conduct":[125],"experiments":[126,136],"on":[127,160,164],"stock":[128],"index":[129],"futures":[130],"data,":[131],"our":[133],"analysis":[134],"not":[137],"only":[138],"offer":[139],"insights":[140],"into":[141],"features":[144],"mining,":[145],"but":[146],"also":[147],"provide":[148],"straightforward":[150],"reliable":[152],"profits,":[156],"sheds":[158],"light":[159],"its":[161],"wide":[162],"application":[163]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2018-02-23T00:00:00"}