Dynamic Analysis of Bitcoin Fluctuations by Means of a Fractal Predictor

Jesús Jaime Moreno Escobar, Oswaldo Morales Matamoros, Ana Lilia Coria Páez, Ricardo Tejeida Padilla

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Using of cryptocurrency has boomed in recent years, such as Bitcoin, Ethereum or Ripple. It is interesting to have a Bitcoin forecasting tool to try to understand the trends at global economic level. A virtual currency that can be used as a means of payment just like physical money. Any cryptocurrency uses peer-to-peer technology and is not controlled by any economic or political entity, such as a bank or government. In 2009, Bitcoin was conceived and was priced at 0.39 USD reaching its all-time high in 2017 with a price of 17,549.67 USD, i.e. 45 thousand times more in less than 10 years. This work focuses on predicting bitcoin-price trending will have in 2020 by using a Self-Affine Fractal Analysis as a tool of artificial intelligence. The results provided by present work in first 6 months agree with 98% with those actually obtained despite training only with data from first days of time series.

Idioma originalInglés
Título de la publicación alojadaIntelligent Systems and Applications - Proceedings of the 2021 Intelligent Systems Conference IntelliSys
EditoresKohei Arai
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas791-804
Número de páginas14
ISBN (versión impresa)9783030821920
DOI
EstadoPublicada - 2022
Evento Intelligent Systems Conference, IntelliSys 2021 - Virtual, Online
Duración: 2 sep 20213 sep 2021

Serie de la publicación

NombreLecture Notes in Networks and Systems
Volumen294
ISSN (versión impresa)2367-3370
ISSN (versión digital)2367-3389

Conferencia

Conferencia Intelligent Systems Conference, IntelliSys 2021
CiudadVirtual, Online
Período2/09/213/09/21

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