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We show that simple trading strategies assisted by state\u2010of\u2010the\u2010art machine learning algorithms outperform standard benchmarks. Our results show that nontrivial, but ultimately simple, algorithmic mechanisms can help anticipate the short\u2010term evolution of the cryptocurrency market.<\/jats:p>","DOI":"10.1155\/2018\/8983590","type":"journal-article","created":{"date-parts":[[2018,11,4]],"date-time":"2018-11-04T18:31:47Z","timestamp":1541356307000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":174,"title":["Anticipating Cryptocurrency Prices Using Machine Learning"],"prefix":"10.1155","volume":"2018","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6003-1165","authenticated-orcid":false,"given":"Laura","family":"Alessandretti","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4717-891X","authenticated-orcid":false,"given":"Abeer","family":"ElBahrawy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0654-2527","authenticated-orcid":false,"given":"Luca Maria","family":"Aiello","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0255-0829","authenticated-orcid":false,"given":"Andrea","family":"Baronchelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2018,11,4]]},"reference":[{"key":"e_1_2_8_1_2","doi-asserted-by":"publisher","DOI":"10.1098\/rsos.170623"},{"key":"e_1_2_8_2_2","article-title":"Global Cryptocurrency Benchmarking Study","author":"Hileman G.","year":"2017","journal-title":"Cambridge Centre for Alternative Finance"},{"key":"e_1_2_8_3_2","unstructured":"Binance.com. 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