{"id":"https://openalex.org/W4390936972","doi":"https://doi.org/10.1155/2024/1124822","title":"A Multilevel Wavelet Decomposition Network Hybrid Model Utilizing Cyclic Patterns for Stock Price Prediction","display_name":"A Multilevel Wavelet Decomposition Network Hybrid Model Utilizing Cyclic Patterns for Stock Price Prediction","publication_year":2024,"publication_date":"2024-01-17","ids":{"openalex":"https://openalex.org/W4390936972","doi":"https://doi.org/10.1155/2024/1124822"},"language":"en","primary_location":{"id":"doi:10.1155/2024/1124822","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2024/1124822","pdf_url":"https://downloads.hindawi.com/journals/complexity/2024/1124822.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/complexity/2024/1124822.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078289245","display_name":"He\u2010Rui Wen","orcid":"https://orcid.org/0000-0002-6497-2955"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"H. R. Wen","raw_affiliation_strings":["Shenzhen Technology University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Technology University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033725594","display_name":"Mingchuan Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingchuan Yuan","raw_affiliation_strings":["Shenzhen Technology University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Technology University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005695172","display_name":"Shuxin Wang","orcid":"https://orcid.org/0000-0002-3609-9423"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuxin Wang","raw_affiliation_strings":["Shenzhen Technology University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-3609-9423","affiliations":[{"raw_affiliation_string":"Shenzhen Technology University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045205941","display_name":"Lixin Liang","orcid":"https://orcid.org/0000-0002-5995-8024"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Liang","raw_affiliation_strings":["Shenzhen Technology University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Technology University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037794437","display_name":"Xianghua Fu","orcid":"https://orcid.org/0000-0003-4431-3386"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianghua Fu","raw_affiliation_strings":["Shenzhen Technology University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Technology University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5005695172"],"corresponding_institution_ids":["https://openalex.org/I4210152380"],"apc_list":{"value":2300,"currency":"USD","value_usd":2300},"apc_paid":{"value":2300,"currency":"USD","value_usd":2300},"fwci":0.9386,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74284328,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"2024","issue":null,"first_page":"1","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9969000220298767,"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"}},{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9952999949455261,"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":0.6513052582740784},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.6329659223556519},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5413683652877808},{"id":"https://openalex.org/keywords/stock-price","display_name":"Stock price","score":0.5109288096427917},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5086787343025208},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.47360658645629883},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39068061113357544},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3689046800136566},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.262859046459198},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.21791771054267883}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6513052582740784},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.6329659223556519},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5413683652877808},{"id":"https://openalex.org/C2988984586","wikidata":"https://www.wikidata.org/wiki/Q1020013","display_name":"Stock price","level":3,"score":0.5109288096427917},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5086787343025208},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.47360658645629883},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39068061113357544},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3689046800136566},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.262859046459198},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.21791771054267883},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1155/2024/1124822","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2024/1124822","pdf_url":"https://downloads.hindawi.com/journals/complexity/2024/1124822.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:hin:complx:1124822","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/complexity/2024/1124822.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:bfef2270bc204e3ba70673b2cc6df20f","is_oa":true,"landing_page_url":"https://doaj.org/article/bfef2270bc204e3ba70673b2cc6df20f","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complexity, Vol 2024 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2024/1124822","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2024/1124822","pdf_url":"https://downloads.hindawi.com/journals/complexity/2024/1124822.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320319297","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390936972.pdf"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1522237958","https://openalex.org/W1586335931","https://openalex.org/W1969396493","https://openalex.org/W1983971157","https://openalex.org/W2000287117","https://openalex.org/W2025291942","https://openalex.org/W2053615983","https://openalex.org/W2064675550","https://openalex.org/W2070471559","https://openalex.org/W2306394264","https://openalex.org/W2363005808","https://openalex.org/W2602977295","https://openalex.org/W2774513877","https://openalex.org/W2808955427","https://openalex.org/W2907706982","https://openalex.org/W2910401125","https://openalex.org/W2911645277","https://openalex.org/W2946975908","https://openalex.org/W2981097085","https://openalex.org/W3013063141","https://openalex.org/W3096794928","https://openalex.org/W3110420963","https://openalex.org/W3130456109","https://openalex.org/W3152556944","https://openalex.org/W3155820657","https://openalex.org/W3158198533","https://openalex.org/W3164783494","https://openalex.org/W3186883985","https://openalex.org/W3195699963","https://openalex.org/W4220793756","https://openalex.org/W4224220755","https://openalex.org/W4251742615","https://openalex.org/W4293143812","https://openalex.org/W6809705806","https://openalex.org/W7024667298"],"related_works":["https://openalex.org/W2370669686","https://openalex.org/W247222457","https://openalex.org/W2887069341","https://openalex.org/W3124131549","https://openalex.org/W3008476150","https://openalex.org/W2152348935","https://openalex.org/W2554106722","https://openalex.org/W1797892342","https://openalex.org/W2344827208","https://openalex.org/W2601854245"],"abstract_inverted_index":{"Stock":[0,15],"price":[1,107,150],"prediction":[2],"is":[3],"an":[4],"important":[5],"and":[6,12,25,41,113,140],"complex":[7],"time-series":[8],"problem":[9],"in":[10,148],"academia":[11],"financial":[13],"industries.":[14],"market":[16,43],"prices":[17],"are":[18,26,50],"voted":[19],"by":[20,28,85],"all":[21],"kinds":[22],"of":[23,53,144],"investors":[24],"influenced":[27],"various":[29],"factors.":[30],"According":[31,117],"to":[32,104,118],"the":[33,47,54,71,86,100,110,119,129,136,142],"literature":[34],"studies,":[35],"such":[36,132],"as":[37,133],"Elliott\u2019s":[38],"wave":[39],"theory":[40],"Howard\u2019s":[42],"cycle":[44],"investment":[45],"theory,":[46],"cyclic":[48,64,101,146],"patterns":[49,65,147],"significant":[51],"characteristics":[52],"stock":[55,106,149],"market.":[56],"However,":[57],"even":[58],"several":[59],"studies":[60],"that":[61],"do":[62],"consider":[63],"(or":[66],"similar":[67],"concepts)":[68],"suffered":[69],"from":[70],"data":[72,111],"leakage":[73,112],"or":[74],"boundary":[75,115],"problems,":[76],"which":[77,97],"could":[78],"be":[79],"impractical":[80],"for":[81],"real":[82],"applications.":[83],"Inspired":[84],"abovementioned,":[87],"we":[88],"propose":[89],"a":[90],"hybrid":[91],"deep":[92],"learning":[93],"model":[94,126],"called":[95],"mWDN-LSTM,":[96],"correctly":[98],"utilizes":[99],"patterns\u2019":[102],"information":[103],"predict":[105],"while":[108],"avoiding":[109],"alleviating":[114],"problems.":[116],"experiments":[120],"on":[121,135],"two":[122],"different":[123],"datasets,":[124],"our":[125],"mWDN-LSTM":[127],"outperforms":[128],"well-known":[130],"benchmarks":[131],"CNN-LSTM":[134],"same":[137],"experimental":[138],"setup":[139],"demonstrates":[141],"effectiveness":[143],"utilizing":[145],"prediction.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}