Machine learning cryptocurrency

machine learning cryptocurrency

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Machine learning cryptocurrency The annual return is the compound return per year given by the accumulated discrete daily returns considering all days in the test sample, including zero-return days when the strategies prescribe not being in the market. The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative cryptocurrencies. The trading strategy is used to devise a position in the market at the next day, and its returns are computed and averaged for the overall validation period. Ann Econ Finance 16 2 � Sci Rep. Competing interests The authors declare that they have no competing interests. Lo, A.
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open.ilcattolicoonline.org (FET) open.ilcattolicoonline.org is an AI and machine learning platform based on the blockchain. open.ilcattolicoonline.org is all about automating business tasks such as. The aim of this thesis is to compare the machine learning algorithms for the price prediction of Bitcoin while using technical indicators as inputs. The. Both machine learning and blockchain technology are a great match when it comes to efficient collaboration and automated decentralization.
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Success factors of initial coin offerings. Multivariate cryptocurrency prediction: comparative analysis of three recurrent neural networks approaches. Big Data. Natale S.