{"id":"https://openalex.org/W3194363670","doi":"https://doi.org/10.1145/3469213.3470231","title":"Multi-factor Data Mining Analysis of Stock Index Volatility","display_name":"Multi-factor Data Mining Analysis of Stock Index Volatility","publication_year":2021,"publication_date":"2021-05-28","ids":{"openalex":"https://openalex.org/W3194363670","doi":"https://doi.org/10.1145/3469213.3470231","mag":"3194363670"},"language":"en","primary_location":{"id":"doi:10.1145/3469213.3470231","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469213.3470231","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 2nd International Conference on Artificial Intelligence and Information Systems","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/A5033758211","display_name":"Yichen He","orcid":"https://orcid.org/0000-0003-3464-7526"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yichen He","raw_affiliation_strings":["South China Agricultural University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China Agricultural University, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101701563","display_name":"Yijun Mao","orcid":"https://orcid.org/0000-0001-8123-2564"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yijun Mao","raw_affiliation_strings":["South China Agricultural University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China Agricultural University, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052770637","display_name":"Xianfen Xie","orcid":"https://orcid.org/0000-0002-7204-2555"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianfen Xie","raw_affiliation_strings":["Jinan University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jinan University, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050565052","display_name":"Wanrong Gu","orcid":"https://orcid.org/0000-0002-0551-9245"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanrong Gu","raw_affiliation_strings":["South China University of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080782923","display_name":"Ziye Zhang","orcid":"https://orcid.org/0000-0002-3049-0173"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziye Zhang","raw_affiliation_strings":["South China Agricultural University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China Agricultural University, China","institution_ids":["https://openalex.org/I101479585"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3015,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.75888506,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11059","display_name":"Market Dynamics and Volatility","score":0.9973000288009644,"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"}},"topics":[{"id":"https://openalex.org/T11059","display_name":"Market Dynamics and Volatility","score":0.9973000288009644,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9957000017166138,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9921000003814697,"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/volatility","display_name":"Volatility (finance)","score":0.7523584961891174},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.7329025864601135},{"id":"https://openalex.org/keywords/autoregressive-conditional-heteroskedasticity","display_name":"Autoregressive conditional heteroskedasticity","score":0.6009746193885803},{"id":"https://openalex.org/keywords/composite-index","display_name":"Composite index","score":0.5785741806030273},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.5665998458862305},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5360427498817444},{"id":"https://openalex.org/keywords/forward-volatility","display_name":"Forward volatility","score":0.49207085371017456},{"id":"https://openalex.org/keywords/capitalization-weighted-index","display_name":"Capitalization-weighted index","score":0.44354063272476196},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.4392359256744385},{"id":"https://openalex.org/keywords/stock-market-index","display_name":"Stock market index","score":0.4188649654388428},{"id":"https://openalex.org/keywords/financial-economics","display_name":"Financial economics","score":0.3525482714176178},{"id":"https://openalex.org/keywords/volatility-smile","display_name":"Volatility smile","score":0.2947416305541992},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08641615509986877},{"id":"https://openalex.org/keywords/composite-indicator","display_name":"Composite indicator","score":0.08493447303771973}],"concepts":[{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.7523584961891174},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.7329025864601135},{"id":"https://openalex.org/C23922673","wikidata":"https://www.wikidata.org/wiki/Q180752","display_name":"Autoregressive conditional heteroskedasticity","level":3,"score":0.6009746193885803},{"id":"https://openalex.org/C2778098375","wikidata":"https://www.wikidata.org/wiki/Q19596433","display_name":"Composite index","level":3,"score":0.5785741806030273},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.5665998458862305},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5360427498817444},{"id":"https://openalex.org/C117996083","wikidata":"https://www.wikidata.org/wiki/Q5473296","display_name":"Forward volatility","level":4,"score":0.49207085371017456},{"id":"https://openalex.org/C192737826","wikidata":"https://www.wikidata.org/wiki/Q5035802","display_name":"Capitalization-weighted index","level":5,"score":0.44354063272476196},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.4392359256744385},{"id":"https://openalex.org/C88389905","wikidata":"https://www.wikidata.org/wiki/Q223371","display_name":"Stock market index","level":4,"score":0.4188649654388428},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.3525482714176178},{"id":"https://openalex.org/C13290067","wikidata":"https://www.wikidata.org/wiki/Q915788","display_name":"Volatility smile","level":3,"score":0.2947416305541992},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08641615509986877},{"id":"https://openalex.org/C2992405062","wikidata":"https://www.wikidata.org/wiki/Q18208028","display_name":"Composite indicator","level":2,"score":0.08493447303771973},{"id":"https://openalex.org/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","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/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":1,"locations":[{"id":"doi:10.1145/3469213.3470231","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469213.3470231","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 2nd International Conference on Artificial Intelligence and Information Systems","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":2,"referenced_works":["https://openalex.org/W2000303290","https://openalex.org/W2904701040"],"related_works":["https://openalex.org/W1971081312","https://openalex.org/W2133325433","https://openalex.org/W3123252458","https://openalex.org/W4283826746","https://openalex.org/W2539018841","https://openalex.org/W4386639254","https://openalex.org/W2391550732","https://openalex.org/W3191555699","https://openalex.org/W3186974393","https://openalex.org/W2057927238"],"abstract_inverted_index":{"In":[0,47,84],"the":[1,4,12,18,42,45,63,75,85,93,100,119,123,127],"study":[2,62],"of":[3,30,44,58,65,80,113],"relationship":[5,128],"between":[6,129],"macroeconomy":[7,130],"and":[8,40,54,69,77,92,103,118,131,139],"stock":[9,81,132,150],"price":[10,67,82,137],"volatility,":[11],"traditional":[13],"method":[14,32],"is":[15,33],"to":[16,37,61,108],"unify":[17],"mixed":[19],"data":[20,60,115],"by":[21],"summation":[22],"or":[23],"interpolation":[24],"before":[25],"modelling.":[26],"The":[27,135],"biggest":[28],"disadvantage":[29],"this":[31,48],"that":[34,122],"it":[35],"leads":[36],"inflated":[38],"information":[39],"affects":[41],"validity":[43],"model.":[46],"paper,":[49],"we":[50],"use":[51,57],"GARCH-MIDAS":[52],"model":[53,124],"make":[55],"full":[56],"high-frequency":[59],"impact":[64,147],"consumer":[66,136],"index":[68,138],"industrial":[70,140],"production":[71,141],"growth":[72,142],"rate":[73,112,143],"on":[74,105,148],"long-run":[76,149],"short-run":[78],"components":[79],"volatility.":[83,134,151],"empirical":[86],"study,":[87],"Shanghai":[88],"Securities":[89],"Composite":[90],"Index":[91,96],"Shanghai-Shenzhen":[94],"300":[95],"are":[97],"selected":[98],"as":[99],"research":[101],"objects,":[102],"based":[104],"January":[106],"2010":[107],"February":[109],"2021":[110],"daily":[111],"return":[114],"for":[116],"analysis,":[117],"results":[120],"show":[121],"can":[125],"describe":[126],"market":[133],"have":[144],"a":[145],"positive":[146]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}