{"id":"https://openalex.org/W4404741392","doi":"https://doi.org/10.1109/icbase63199.2024.10762392","title":"Research on the Dynamic Hedging Trading Strategy for Portfolios Based on Deep Reinforcement Learning","display_name":"Research on the Dynamic Hedging Trading Strategy for Portfolios Based on Deep Reinforcement Learning","publication_year":2024,"publication_date":"2024-09-20","ids":{"openalex":"https://openalex.org/W4404741392","doi":"https://doi.org/10.1109/icbase63199.2024.10762392"},"language":"en","primary_location":{"id":"doi:10.1109/icbase63199.2024.10762392","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbase63199.2024.10762392","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE)","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/A5005913248","display_name":"Fei Song","orcid":"https://orcid.org/0000-0003-1289-5502"},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fangji Song","raw_affiliation_strings":["China JiLiang University,Department of Economics and Management,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"China JiLiang University,Department of Economics and Management,Hangzhou,China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chunyu Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyu Liu","raw_affiliation_strings":["China JiLiang University,Department of Economics and Management,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"China JiLiang University,Department of Economics and Management,Hangzhou,China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083156097","display_name":"Jiapeng Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I1315279114","display_name":"Zhejiang Wanli University","ror":"https://ror.org/00rjdhd62","country_code":"CN","type":"education","lineage":["https://openalex.org/I1315279114"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiapeng Liu","raw_affiliation_strings":["Zhejiang Wanli University,Department of Business,Ningbo,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Wanli University,Department of Business,Ningbo,China","institution_ids":["https://openalex.org/I1315279114"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5005913248"],"corresponding_institution_ids":["https://openalex.org/I55538621"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2568696,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"780","last_page":"784"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.5221999883651733,"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":0.5221999883651733,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8704143762588501},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6190305352210999},{"id":"https://openalex.org/keywords/trading-strategy","display_name":"Trading strategy","score":0.5798179507255554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48893871903419495},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.43677571415901184},{"id":"https://openalex.org/keywords/financial-economics","display_name":"Financial economics","score":0.24526327848434448},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.17582106590270996},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11179959774017334}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8704143762588501},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6190305352210999},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.5798179507255554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48893871903419495},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.43677571415901184},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.24526327848434448},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.17582106590270996},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11179959774017334},{"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:10.1109/icbase63199.2024.10762392","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbase63199.2024.10762392","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2344786740","https://openalex.org/W4282933415","https://openalex.org/W4294691400","https://openalex.org/W4312622410","https://openalex.org/W4328007708","https://openalex.org/W4366728016","https://openalex.org/W4377236630","https://openalex.org/W6741238899","https://openalex.org/W6840935075"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4310083477","https://openalex.org/W2328553770","https://openalex.org/W2920061524","https://openalex.org/W1977959518","https://openalex.org/W2038908348","https://openalex.org/W2107890255","https://openalex.org/W2106552856"],"abstract_inverted_index":{"For":[0],"the":[1,5,9,22,27,56,83,93,100,103,106,111,118,126,132,141,148,160,168,177,190,195],"current":[2],"stage":[3],"of":[4,71,102,198],"portfolio":[6,28,178],"strategy":[7,29,130,181],"for":[8],"overall":[10,191],"market":[11,44],"downside":[12,149],"risk":[13,17,150],"that":[14,125,176],"is,":[15],"systemic":[16],"perception":[18],"is":[19],"not":[20],"obvious,":[21],"investment":[23,60,192],"process":[24],"using":[25,92],"only":[26],"will":[30],"be":[31],"exposed":[32],"to":[33,40,43,74,98,115,167],"too":[34],"much":[35],"risk.":[36],"Meanwhile,":[37],"in":[38],"order":[39],"flexibly":[41],"respond":[42],"changes,":[45],"this":[46],"paper":[47],"establishes":[48,67],"a":[49,137,203],"dynamic":[50,127],"hedging":[51,57,72,78,128],"trading":[52,129,180],"strategy,":[53],"dynamically":[54,75],"calculates":[55],"ratio":[58,143],"and":[59,66,91,110,158,201],"weight":[61],"through":[62,80],"different":[63],"adjustment":[64,206],"cycles,":[65],"an":[68],"alternative":[69],"pool":[70],"assets":[73,79],"select":[76],"suitable":[77],"volatility.":[81],"Using":[82],"Actor-Critic":[84],"algorithm":[85,187],"based":[86,182],"on":[87,131,183],"deep":[88,184],"reinforcement":[89,185],"learning;":[90],"Long":[94],"Short-Term":[95],"Memory":[96],"network":[97],"predict":[99],"probability":[101],"action;":[104],"adopting":[105],"experience":[107],"replay":[108],"technology":[109],"online":[112],"learning":[113,186],"method":[114],"randomly":[116],"sample":[117],"past":[119],"experience;":[120],"The":[121,172],"experimental":[122,173],"results":[123,174],"show":[124,175],"testing":[133],"set":[134],"adjusted":[135],"with":[136],"30-day":[138],"period":[139],"improves":[140],"Sortino":[142],"by":[144,151,163],"$692.94":[145],"\\%$,":[146],"reduces":[147,159],"${8":[152],"7":[153],".":[154],"9":[155,156],"\\%}$,":[157],"maximum":[161],"retracement":[162],"$1.11":[164],"\\%$":[165],"compared":[166],"traditional":[169],"fixed":[170],"strategy.":[171],"hedged":[179],"can":[188],"reduce":[189],"risk,":[193],"ensure":[194],"stable":[196],"growth":[197],"cumulative":[199],"return,":[200],"determine":[202],"relatively":[204],"good":[205],"cycle.":[207]},"counts_by_year":[],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}