Bitcoin Analysis and Forecasting Through Fuzzy Transform

Maria Letizia Guerra; Laerte Sorini; Luciano Stefanini

doi:10.20944/preprints202011.0055.v1

Submitted:

30 October 2020

Posted:

02 November 2020

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This version is not peer-reviewed.

Bitcoin Analysis and Forecasting Through Fuzzy Transform

Maria Letizia Guerra^*

,Laerte Sorini

,Luciano Stefanini

Maria Letizia Guerra^*

,Laerte Sorini

,Luciano Stefanini

A peer-reviewed version of this preprint was published in:

Axioms 2020, 9(4), 139. https://doi.org/10.3390/axioms9040139

Submitted:

30 October 2020

Posted:

02 November 2020

You are already at the latest version

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

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