Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Bitcoin Analysis and Forecasting Through Fuzzy Transform

Version 1 : Received: 30 October 2020 / Approved: 2 November 2020 / Online: 2 November 2020 (15:10:06 CET)

A peer-reviewed article of this Preprint also exists.

Guerra, M.L.; Sorini, L.; Stefanini, L. Bitcoin Analysis and Forecasting through Fuzzy Transform. Axioms 2020, 9, 139. Guerra, M.L.; Sorini, L.; Stefanini, L. Bitcoin Analysis and Forecasting through Fuzzy Transform. Axioms 2020, 9, 139.

Journal reference: Axioms 2020, 9, 139
DOI: 10.3390/axioms9040139

Abstract

Sentiment analysis to characterize properties of Bitcoin prices and their forecasting is here developed thanks to the capability of the Fuzzy transform to capture stylized facts and mutual connections between time series having different nature. Six years of daily Bitcoin Prices and Google Trends are analyzed in order to establish new perspectives in the management of their dynamics.

Subject Areas

F-transform; BITCOIN; Clustering; Sentiment Analysis

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