Prediction of cryptocurrency returns using machine learning

DOI10.1007/s10479-020-03575-yzbMath1465.62171OpenAlexW3015481177MaRDI QIDQ829124

Ahmet Sensoy, Erdinç Akyıldırım, Ahmet Göncü

Publication date: 5 May 2021

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/11693/75677

zbMATH Keywords

logistic regressionartificial neural networksmachine learningrandom forestsupport vector machinecryptocurrency

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Generalized linear models (logistic models) (62J12) Learning and adaptive systems in artificial intelligence (68T05)

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• Random forests

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