{"id":"https://openalex.org/W4313892575","doi":"https://doi.org/10.1109/icsai57119.2022.10005355","title":"Application Research of the XGBoost-SVM Combination Model in Quantitative Investment Strategy","display_name":"Application Research of the XGBoost-SVM Combination Model in Quantitative Investment Strategy","publication_year":2022,"publication_date":"2022-12-10","ids":{"openalex":"https://openalex.org/W4313892575","doi":"https://doi.org/10.1109/icsai57119.2022.10005355"},"language":"en","primary_location":{"id":"doi:10.1109/icsai57119.2022.10005355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai57119.2022.10005355","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 Systems and Informatics (ICSAI)","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/A5112976734","display_name":"Hongxin Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongxin Zhu","raw_affiliation_strings":["Shenzhen University,College of Computer and Software,Shenzhen,China","College of Computer and Software, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University,College of Computer and Software,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"College of Computer and Software, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101964822","display_name":"Anmin Zhu","orcid":"https://orcid.org/0000-0001-8654-7100"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anmin Zhu","raw_affiliation_strings":["Shenzhen University,College of Computer and Software,Shenzhen,China","College of Computer and Software, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University,College of Computer and Software,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"College of Computer and Software, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5112976734"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.8182,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7600497,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9916999936103821,"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/T11059","display_name":"Market Dynamics and Volatility","score":0.9743000268936157,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8569233417510986},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6387078762054443},{"id":"https://openalex.org/keywords/futures-contract","display_name":"Futures contract","score":0.6090941429138184},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6058598160743713},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5920485258102417},{"id":"https://openalex.org/keywords/stock-index-futures","display_name":"Stock index futures","score":0.5584323406219482},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.549297571182251},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.49115774035453796},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.469835489988327},{"id":"https://openalex.org/keywords/stock-market-index","display_name":"Stock market index","score":0.45532986521720886},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.44749802350997925},{"id":"https://openalex.org/keywords/investment-strategy","display_name":"Investment strategy","score":0.44351285696029663},{"id":"https://openalex.org/keywords/investment","display_name":"Investment (military)","score":0.43941420316696167},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.34111636877059937},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3224799633026123},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.24527403712272644},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.22999730706214905},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.17170369625091553},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1424083709716797}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8569233417510986},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6387078762054443},{"id":"https://openalex.org/C106306483","wikidata":"https://www.wikidata.org/wiki/Q183984","display_name":"Futures contract","level":2,"score":0.6090941429138184},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6058598160743713},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5920485258102417},{"id":"https://openalex.org/C2993390347","wikidata":"https://www.wikidata.org/wiki/Q905615","display_name":"Stock index futures","level":5,"score":0.5584323406219482},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.549297571182251},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.49115774035453796},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.469835489988327},{"id":"https://openalex.org/C88389905","wikidata":"https://www.wikidata.org/wiki/Q223371","display_name":"Stock market index","level":4,"score":0.45532986521720886},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.44749802350997925},{"id":"https://openalex.org/C103144560","wikidata":"https://www.wikidata.org/wiki/Q2670999","display_name":"Investment strategy","level":3,"score":0.44351285696029663},{"id":"https://openalex.org/C27548731","wikidata":"https://www.wikidata.org/wiki/Q88272","display_name":"Investment (military)","level":3,"score":0.43941420316696167},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34111636877059937},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3224799633026123},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.24527403712272644},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.22999730706214905},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.17170369625091553},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1424083709716797},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C183582576","wikidata":"https://www.wikidata.org/wiki/Q184783","display_name":"Market liquidity","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsai57119.2022.10005355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai57119.2022.10005355","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 Systems and Informatics (ICSAI)","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":5,"referenced_works":["https://openalex.org/W2295598076","https://openalex.org/W2940136728","https://openalex.org/W3080657584","https://openalex.org/W3134942033","https://openalex.org/W4280587748"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856","https://openalex.org/W3094138326"],"abstract_inverted_index":{"Financia1":[0],"data":[1,14],"are":[2],"non-stationary":[3],"and":[4,51,63,70,84],"nonlinear.":[5],"Machine":[6],"learning":[7,29],"makes":[8],"it":[9,78],"easier":[10],"to":[11,58,90,97],"classify":[12],"financial":[13],"than":[15,136],"traditional":[16],"models.":[17],"With":[18],"the":[19,25,45,52,60,80,99,102,112,118,123,127,137],"development":[20],"of":[21,27,65,101,126],"machine":[22,28],"learning,":[23],"improving":[24],"accuracy":[26],"models":[30,103],"for":[31],"stock":[32,73,92],"price":[33],"prediction":[34],"has":[35],"gradually":[36],"become":[37],"a":[38,86],"hot":[39],"research":[40,98,109],"topic.":[41],"This":[42],"paper":[43],"uses":[44],"XGBoost":[46],"(eXtreme":[47],"gradient":[48],"boosting)":[49],"model":[50,57,83,133],"SVM":[53],"(support":[54],"vector":[55],"machine)":[56],"predict":[59],"rising,":[61],"falling":[62],"fluctuating":[64],"CSI":[66,71],"300,":[67],"SSE":[68],"50":[69],"500":[72],"index":[74,93],"futures":[75,94],"respectively.":[76],"Then":[77],"constructs":[79],"XGBoost-SVM":[81,132],"combination":[82],"designs":[85],"quantitative":[87,105],"investment":[88,106,124],"strategy":[89],"trade":[91],"in":[95,104],"order":[96],"effectiveness":[100],"strategies.":[107],"The":[108,130],"shows":[110],"that":[111],"proposed":[113],"method":[114],"can":[115],"stably":[116],"outperform":[117],"benchmark":[119],"returns":[120],"by":[121],"combining":[122],"strategies":[125],"three-price-trend":[128],"classifications.":[129],"constructed":[131],"performs":[134],"better":[135],"original":[138],"model.":[139],"It":[140],"gets":[141],"higher":[142],"returns.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}