{"id":"https://openalex.org/W2037079276","doi":"https://doi.org/10.1109/ijcnn.2014.6889651","title":"Stock volatility prediction using multi-kernel learning based extreme learning machine","display_name":"Stock volatility prediction using multi-kernel learning based extreme learning machine","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2037079276","doi":"https://doi.org/10.1109/ijcnn.2014.6889651","mag":"2037079276"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2014.6889651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889651","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","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/A5100431362","display_name":"Feng Wang","orcid":"https://orcid.org/0000-0003-1427-5964"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feng Wang","raw_affiliation_strings":["Wuhan University, Wuhan, Hubei, CN","Computer School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, Hubei, CN","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"Computer School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103047803","display_name":"Zhiyong Zhao","orcid":"https://orcid.org/0000-0002-1439-1298"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Zhao","raw_affiliation_strings":["State Key Laboratory of Software Engineering, Wuhan University, Wuhan, China","Computer School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"Computer School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100369719","display_name":"Xiaodong Li","orcid":"https://orcid.org/0000-0003-0346-1526"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaodong Li","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Hong Kong","Department of Computer Science,City University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Department of Computer Science,City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100420016","display_name":"F. Richard Yu","orcid":"https://orcid.org/0000-0003-1006-7594"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Yu","raw_affiliation_strings":["State Key Laboratory of Software Engineering, Wuhan University, Wuhan, China","Computer School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"Computer School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100396799","display_name":"Hao Zhang","orcid":"https://orcid.org/0000-0001-7089-8344"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["State Key Laboratory of Software Engineering, Wuhan University, Wuhan, China","Computer School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"Computer School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100431362"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.409,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.73773289,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"3078","last_page":"3085"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9977999925613403,"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/T10320","display_name":"Neural Networks and Applications","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.8531619310379028},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6995733976364136},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6960208415985107},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6609941124916077},{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.6469648480415344},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6279358267784119},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48321568965911865},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.43349403142929077},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.13743063807487488},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1359817385673523},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.11799466609954834}],"concepts":[{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.8531619310379028},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6995733976364136},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6960208415985107},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6609941124916077},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.6469648480415344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6279358267784119},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48321568965911865},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.43349403142929077},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.13743063807487488},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1359817385673523},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.11799466609954834}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2014.6889651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889651","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W62322198","https://openalex.org/W1563088657","https://openalex.org/W1963824809","https://openalex.org/W2015174807","https://openalex.org/W2031823405","https://openalex.org/W2053615983","https://openalex.org/W2094304287","https://openalex.org/W2095657833","https://openalex.org/W2096987757","https://openalex.org/W2106503792","https://openalex.org/W2111072639","https://openalex.org/W2122040390","https://openalex.org/W2135349957","https://openalex.org/W2140308831","https://openalex.org/W2154630456","https://openalex.org/W2156969234","https://openalex.org/W2164727351","https://openalex.org/W2171468534","https://openalex.org/W2172073485","https://openalex.org/W2627025399","https://openalex.org/W6682657502"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2968645206","https://openalex.org/W2061467332","https://openalex.org/W1997850864","https://openalex.org/W2922477536","https://openalex.org/W3134054957"],"abstract_inverted_index":{"Stock":[0],"price":[1,149],"volatility":[2],"prediction":[3,28,32,62,68,84,124,127,186,200,211],"is":[4,87],"regarded":[5],"as":[6,64],"one":[7],"of":[8,42,53,109,122,133],"the":[9,27,31,35,40,51,83,107,120,131,134,151],"most":[10,36,205],"attractive":[11],"and":[12,30,70,92,114,126,150,173,182,190,195,218],"meaningful":[13],"research":[14,99],"issues":[15],"in":[16,39,97,156,204,213],"financial":[17],"market.":[18],"Some":[19],"existing":[20],"researches":[21],"have":[22],"pointed":[23],"out":[24],"that":[25],"both":[26,110,123],"accuracy":[29,63,125,187,212],"speed":[33,66,201],"are":[34,154],"important":[37],"facts":[38],"process":[41],"stock":[43,143],"prediction.":[44],"In":[45],"this":[46,104],"paper,":[47],"we":[48,137],"focus":[49],"on":[50,102,140],"problem":[52],"how":[54],"to":[55,81],"design":[56],"a":[57,72,88],"methodology":[58],"which":[59,116],"can":[60,117,197],"improve":[61],"well":[65,118],"up":[67],"process,":[69],"propose":[71],"multi-kernel":[73],"learning":[74,77,90,113],"based":[75],"extreme":[76],"machine":[78],"(MKL-ELM)":[79],"model":[80,91],"enhance":[82],"performance.":[85],"ELM":[86,172],"fast":[89],"has":[93,106,209],"been":[94],"successfully":[95],"applied":[96],"many":[98],"fields.":[100],"Based":[101],"ELM,":[103,115],"MKL-ELM":[105,163,194,208],"benefits":[108],"multiple":[111],"kernel":[112],"balanced":[119],"requirements":[121],"speed.":[128],"To":[129],"validate":[130],"performance":[132],"proposed":[135,162],"MKL-ELM,":[136,180],"take":[138],"experiments":[139],"HKEx":[141],"2001":[142],"market":[144,147,152],"datasets.":[145],"The":[146],"historical":[148],"news":[153],"implemented":[155],"our":[157,161],"MKL-ELM.":[158],"We":[159],"Compare":[160],"with":[164],"Back-Propagation":[165],"Neural":[166],"Network(BP-NN),":[167],"Support":[168],"Vector":[169],"Machine(SVM),":[170],"Basic":[171],"K-ELM.":[174],"Experimental":[175],"results":[176],"show":[177],"that,":[178],"1)":[179],"K-ELM":[181,196,217],"SVM":[183,203],"get":[184],"higher":[185,210],"than":[188,202,216],"BP-NN":[189],"B-ELM;":[191],"2)":[192],"Both":[193],"achieve":[198],"faster":[199],"cases;":[206],"3)":[207],"some":[214],"cases":[215],"SVM.":[219]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}