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Preserved in Portico This version is not peer-reviewed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.
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.
Keywords
F-transform; BITCOIN; Clustering; Sentiment Analysis
Subject
Computer Science and Mathematics, Algebra and Number Theory
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment