{"id":"https://openalex.org/W4206109875","doi":"https://doi.org/10.1109/bigdata52589.2021.9671826","title":"Do Candlestick Patterns Work in Cryptocurrency Trading?","display_name":"Do Candlestick Patterns Work in Cryptocurrency Trading?","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4206109875","doi":"https://doi.org/10.1109/bigdata52589.2021.9671826"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671826","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","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/A5029636211","display_name":"Kin-Hon Ho","orcid":"https://orcid.org/0000-0002-2524-6950"},"institutions":[{"id":"https://openalex.org/I47605537","display_name":"The Hang Seng University of Hong Kong","ror":"https://ror.org/04fa64g55","country_code":"CN","type":"education","lineage":["https://openalex.org/I47605537"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":true,"raw_author_name":"Kin-Hon Ho","raw_affiliation_strings":["Department of Computing, The Hang Seng University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computing, The Hang Seng University of Hong Kong","institution_ids":["https://openalex.org/I47605537","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047023625","display_name":"Tse-Tin Chan","orcid":"https://orcid.org/0000-0001-9235-7813"},"institutions":[{"id":"https://openalex.org/I47605537","display_name":"The Hang Seng University of Hong Kong","ror":"https://ror.org/04fa64g55","country_code":"CN","type":"education","lineage":["https://openalex.org/I47605537"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Tse-Tin Chan","raw_affiliation_strings":["Department of Computing, The Hang Seng University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computing, The Hang Seng University of Hong Kong","institution_ids":["https://openalex.org/I47605537","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076812737","display_name":"Haoyuan Pan","orcid":"https://orcid.org/0000-0003-3651-3417"},"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":"Haoyuan Pan","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027695241","display_name":"Chin Li","orcid":"https://orcid.org/0000-0002-5457-9623"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chin Li","raw_affiliation_strings":["Hong Kong-Shenzhen Finance Research Centre, The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"Hong Kong-Shenzhen Finance Research Centre, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029636211"],"corresponding_institution_ids":["https://openalex.org/I47605537","https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":3.1987,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.94890511,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4566","last_page":"4569"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10047","display_name":"Financial Markets and Investment Strategies","score":0.9991999864578247,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9962999820709229,"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/cryptocurrency","display_name":"Cryptocurrency","score":0.9532724618911743},{"id":"https://openalex.org/keywords/market-capitalization","display_name":"Market capitalization","score":0.7614330053329468},{"id":"https://openalex.org/keywords/technical-analysis","display_name":"Technical analysis","score":0.744789183139801},{"id":"https://openalex.org/keywords/capitalization","display_name":"Capitalization","score":0.5937323570251465},{"id":"https://openalex.org/keywords/trading-strategy","display_name":"Trading strategy","score":0.5891682505607605},{"id":"https://openalex.org/keywords/algorithmic-trading","display_name":"Algorithmic trading","score":0.4727288782596588},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4128551483154297},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.41092410683631897},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.37933775782585144},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.3240400552749634},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.30309829115867615},{"id":"https://openalex.org/keywords/financial-economics","display_name":"Financial economics","score":0.2803831100463867},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.14485979080200195},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.061022400856018066}],"concepts":[{"id":"https://openalex.org/C180706569","wikidata":"https://www.wikidata.org/wiki/Q13479982","display_name":"Cryptocurrency","level":2,"score":0.9532724618911743},{"id":"https://openalex.org/C193445137","wikidata":"https://www.wikidata.org/wiki/Q471719","display_name":"Market capitalization","level":4,"score":0.7614330053329468},{"id":"https://openalex.org/C117245426","wikidata":"https://www.wikidata.org/wiki/Q235038","display_name":"Technical analysis","level":2,"score":0.744789183139801},{"id":"https://openalex.org/C2779137862","wikidata":"https://www.wikidata.org/wiki/Q425951","display_name":"Capitalization","level":2,"score":0.5937323570251465},{"id":"https://openalex.org/C131562839","wikidata":"https://www.wikidata.org/wiki/Q1574928","display_name":"Trading strategy","level":2,"score":0.5891682505607605},{"id":"https://openalex.org/C78508483","wikidata":"https://www.wikidata.org/wiki/Q139445","display_name":"Algorithmic trading","level":2,"score":0.4727288782596588},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4128551483154297},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.41092410683631897},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37933775782585144},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3240400552749634},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.30309829115867615},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.2803831100463867},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.14485979080200195},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.061022400856018066},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671826","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W638987163","https://openalex.org/W1590184280","https://openalex.org/W1740634745","https://openalex.org/W1996897705","https://openalex.org/W2002393636","https://openalex.org/W2004068247","https://openalex.org/W2015166767","https://openalex.org/W2024212714","https://openalex.org/W2058078399","https://openalex.org/W2617856110","https://openalex.org/W2744110108","https://openalex.org/W2899065505","https://openalex.org/W3037715530","https://openalex.org/W3121701788","https://openalex.org/W3138152858","https://openalex.org/W6738714152"],"related_works":["https://openalex.org/W3195793285","https://openalex.org/W1863543693","https://openalex.org/W3165885989","https://openalex.org/W880995879","https://openalex.org/W2994104012","https://openalex.org/W2005233533","https://openalex.org/W4244220816","https://openalex.org/W2155646692","https://openalex.org/W2747966161","https://openalex.org/W3031468904"],"abstract_inverted_index":{"This":[0],"paper":[1,102],"investigates":[2],"the":[3,24,44,56,96,106,112],"effectiveness":[4,113],"of":[5,23,49,98,105,114],"candlestick":[6,36,46,115],"patterns":[7,37,47,61,78,116],"in":[8,52,117],"cryptocurrency":[9,53,118,131],"trading.":[10,54,119],"Our":[11,120],"data":[12],"set":[13],"includes":[14],"historical":[15],"daily":[16],"opening,":[17],"high,":[18],"low,":[19],"and":[20,41,74],"closing":[21],"prices":[22],"top":[25],"23":[26],"cryptocurrencies":[27],"by":[28],"market":[29],"capitalization.":[30],"We":[31],"examine":[32],"68":[33],"commonly":[34],"used":[35],"using":[38],"statistical":[39],"analysis":[40],"find":[42],"that":[43,88],"studied":[45],"are":[48,59],"little":[50],"use":[51],"On":[55],"contrary,":[57],"there":[58],"more":[60],"with":[62,70],"relatively":[63],"low":[64],"accuracy.":[65],"Investors":[66],"should":[67],"be":[68,83],"cautious":[69],"their":[71],"trading":[72,86,132],"strategies":[73],"decisions":[75],"when":[76,129],"these":[77],"appear,":[79],"as":[80,124],"they":[81],"may":[82],"a":[84,125],"false":[85],"signal":[87],"could":[89,122],"cause":[90],"losses":[91],"rather":[92],"than":[93],"gains.":[94],"To":[95],"best":[97],"our":[99],"knowledge,":[100],"this":[101],"is":[103],"one":[104],"first":[107],"research":[108],"studies":[109],"to":[110],"investigate":[111],"findings":[121],"serve":[123],"reference":[126],"for":[127],"investors":[128],"developing":[130],"strategies.":[133]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}