{"id":"https://openalex.org/W4306316902","doi":"https://doi.org/10.1145/3511808.3557412","title":"Optimal Action Space Search","display_name":"Optimal Action Space Search","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306316902","doi":"https://doi.org/10.1145/3511808.3557412"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557412","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557412","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","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/A5040636331","display_name":"Zhongjie Duan","orcid":"https://orcid.org/0000-0002-5973-8240"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongjie Duan","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100622589","display_name":"Cen Chen","orcid":"https://orcid.org/0000-0002-5115-4929"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cen Chen","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069869295","display_name":"Dawei Cheng","orcid":"https://orcid.org/0000-0002-5877-7387"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawei Cheng","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016761088","display_name":"Yuqi Liang","orcid":"https://orcid.org/0000-0002-7481-116X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuqi Liang","raw_affiliation_strings":["Seek Data Group, Emoney Inc., Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Seek Data Group, Emoney Inc., Shanghai, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089931216","display_name":"Weining Qian","orcid":"https://orcid.org/0000-0002-4132-8630"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weining Qian","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5040636331"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":2.0587,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.8821639,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"406","last_page":"415"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9984999895095825,"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":0.9984999895095825,"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/T11674","display_name":"Sports Analytics and Performance","score":0.9940000176429749,"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"}},{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9908000230789185,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7506041526794434},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6913412809371948},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6017270088195801},{"id":"https://openalex.org/keywords/trading-strategy","display_name":"Trading strategy","score":0.5243102312088013},{"id":"https://openalex.org/keywords/dynamic-programming","display_name":"Dynamic programming","score":0.5047639608383179},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4954115152359009},{"id":"https://openalex.org/keywords/financial-market","display_name":"Financial market","score":0.4532703757286072},{"id":"https://openalex.org/keywords/sharpe-ratio","display_name":"Sharpe ratio","score":0.4213179051876068},{"id":"https://openalex.org/keywords/algorithmic-trading","display_name":"Algorithmic trading","score":0.4160591959953308},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.41460394859313965},{"id":"https://openalex.org/keywords/dijkstras-algorithm","display_name":"Dijkstra's algorithm","score":0.4109314978122711},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3818672299385071},{"id":"https://openalex.org/keywords/shortest-path-problem","display_name":"Shortest path problem","score":0.35503119230270386},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.2211706042289734},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21331331133842468},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16499993205070496}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7506041526794434},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6913412809371948},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6017270088195801},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.5243102312088013},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.5047639608383179},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4954115152359009},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.4532703757286072},{"id":"https://openalex.org/C139938925","wikidata":"https://www.wikidata.org/wiki/Q1501898","display_name":"Sharpe ratio","level":3,"score":0.4213179051876068},{"id":"https://openalex.org/C78508483","wikidata":"https://www.wikidata.org/wiki/Q139445","display_name":"Algorithmic trading","level":2,"score":0.4160591959953308},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.41460394859313965},{"id":"https://openalex.org/C173870130","wikidata":"https://www.wikidata.org/wiki/Q8548","display_name":"Dijkstra's algorithm","level":4,"score":0.4109314978122711},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3818672299385071},{"id":"https://openalex.org/C22590252","wikidata":"https://www.wikidata.org/wiki/Q1058754","display_name":"Shortest path problem","level":3,"score":0.35503119230270386},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.2211706042289734},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21331331133842468},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16499993205070496},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557412","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557412","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","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":24,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1988021444","https://openalex.org/W2014417912","https://openalex.org/W2067050450","https://openalex.org/W2117726420","https://openalex.org/W2125838338","https://openalex.org/W2143895421","https://openalex.org/W2145339207","https://openalex.org/W2187089797","https://openalex.org/W2344786740","https://openalex.org/W2490603845","https://openalex.org/W2806777472","https://openalex.org/W2885054548","https://openalex.org/W2891295326","https://openalex.org/W2963467914","https://openalex.org/W2963698230","https://openalex.org/W2982109826","https://openalex.org/W3012223895","https://openalex.org/W3012333258","https://openalex.org/W3012544020","https://openalex.org/W3022746105","https://openalex.org/W3035574064","https://openalex.org/W3097267636","https://openalex.org/W3176553972"],"related_works":["https://openalex.org/W3209137076","https://openalex.org/W4223969905","https://openalex.org/W2374560440","https://openalex.org/W1490490684","https://openalex.org/W1844669668","https://openalex.org/W3122593455","https://openalex.org/W3095472613","https://openalex.org/W2765618043","https://openalex.org/W1965766592","https://openalex.org/W4388796911"],"abstract_inverted_index":{"Algorithmic":[0],"trading":[1,13,29,59,223],"is":[2,184],"a":[3,34,107,130,143,158],"crucial":[4],"yet":[5],"challenging":[6],"task":[7],"in":[8,39,57,176,202],"the":[9,24,40,66,83,103,115,125,152,162,173,233],"financial":[10,42,67],"domain,":[11],"where":[12],"decisions":[14],"are":[15,69],"made":[16],"sequentially":[17],"from":[18],"milliseconds":[19],"to":[20,148,197],"days":[21],"based":[22,48],"on":[23,102,209,237],"historical":[25],"price":[26],"movements":[27],"and":[28,53,78,120,123,171,199,228,240],"frequency.":[30],"To":[31,134],"model":[32,124,139],"such":[33],"sequential":[35],"decision":[36],"making":[37],"process":[38],"dynamic":[41,109,145],"markets,":[43],"Deep":[44],"Reinforcement":[45],"Learning":[46],"(DRL)":[47],"methods":[49,236],"have":[50,206],"been":[51,207],"applied":[52],"demonstrated":[54],"their":[55],"success":[56],"finding":[58],"strategies":[60,224],"that":[61,99,217],"achieve":[62],"profitable":[63],"returns.":[64],"However,":[65],"markets":[68],"complex":[70],"imperfect":[71],"information":[72],"games":[73],"with":[74,186],"high-level":[75],"of":[76,86,156],"noise":[77],"uncertainties":[79],"which":[80,192],"usually":[81],"make":[82],"exploration":[84],"policy":[85],"DRL":[87,97,179,235],"less":[88],"effective.":[89],"In":[90],"this":[91],"paper,":[92],"we":[93,113,141,165],"propose":[94,166],"an":[95,167],"end-to-end":[96],"method":[98,183,195,219],"explores":[100],"solutions":[101,150],"whole":[104,153],"graph":[105,154],"via":[106],"probabilistic":[108,144],"programming":[110,146],"algorithm.":[111],"Specifically,":[112],"separate":[114],"state":[116,119,127],"into":[117],"environment":[118],"position":[121,126],"state,":[122],"transition":[128],"as":[129],"directed":[131],"acyclic":[132],"graph.":[133],"obtain":[135],"reliable":[136],"gradients":[137],"for":[138,225],"training,":[140],"adopt":[142],"algorithm":[147,170],"explore":[149],"over":[151],"instead":[155],"sampling":[157,163],"path.":[159],"By":[160],"avoiding":[161],"procedure,":[164],"efficient":[168],"training":[169],"overcome":[172],"efficiency":[174],"problem":[175],"most":[177,187],"existing":[178],"methods.":[180],"Furthermore,":[181],"our":[182,194,218],"compatible":[185],"recurrent":[188],"neural":[189],"network":[190],"architecture,":[191],"makes":[193],"easy":[196],"implement":[198],"very":[200],"effective":[201],"practice.":[203],"Extensive":[204],"experiments":[205],"conducted":[208],"two":[210],"real-world":[211],"stock":[212],"datasets.":[213],"Experimental":[214],"results":[215],"demonstrate":[216],"can":[220],"generate":[221],"stable":[222],"both":[226],"high-frequency":[227],"low-frequency":[229],"trading,":[230],"significantly":[231],"outperforming":[232],"baseline":[234],"annualized":[238],"return":[239],"Sharpe":[241],"ratio.":[242]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}