Desarrollo de un Algoritmo Predictivo de la Tendencia del Bitcoin Bajo la Metodología de Machine Learning.
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Date
2022-05-18
Authors
Montes Mendoza, Marcos Andrés
Pabón Martínez, Héctor Alexander
Advisors
Chaparro Prieto, Adriana Yeicy
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
Corporación Universitaria Minuto de Dios
Type
Thesis
Rights
Atribución-NoComercial-SinDerivadas 2.5 Colombia
Abstract
Desarrolló un algoritmo predictivo de la tendencia del bitcoin, con visualización de resultados en una aplicación web con información basada en análisis históricos del bitcoin, esto con el fin de dar solución a una problemática al momento de comerciar con el bitcoin, dicha problemática consiste en que las personas que comercian con esta criptomoneda toman decisiones por emoción, dando como resultado perdidas al momento de comerciar con el bitcoin.
In this work, a predictive algorithm of the Bitcoin trend was developed, with visualization of results in a web application with information based on historical analysis of Bitcoin, this to solve a problem when trading with Bitcoin, this problem is that people who trade with this cryptocurrency make decisions by emotion, resulting in losses when trading with Bitcoin. The research methodology used was quantitative since it was used to make a predictive technical analysis of Bitcoin historical data with a Machine Learning model developed in the Python programming language. The development methodology used for the realization of the project was the XP methodology (Extreme Programming), since it offered us tools that allowed us to give continuous improvement to the software, giving the possibility of teamwork between two or more developers to make the software code universal. Also, to have within the scheme defined roles such as: testers, tracker, coach, and programmers which allow us to give an agile response to the operation of the software. We seek to have a predictive model with a high percentage of assertiveness in the prediction of how likely it is that the value of Bitcoin will go down or up in real time in the market of the cryptocurrency trading platform coinbase.com, to show the results in a free web application for the public.
In this work, a predictive algorithm of the Bitcoin trend was developed, with visualization of results in a web application with information based on historical analysis of Bitcoin, this to solve a problem when trading with Bitcoin, this problem is that people who trade with this cryptocurrency make decisions by emotion, resulting in losses when trading with Bitcoin. The research methodology used was quantitative since it was used to make a predictive technical analysis of Bitcoin historical data with a Machine Learning model developed in the Python programming language. The development methodology used for the realization of the project was the XP methodology (Extreme Programming), since it offered us tools that allowed us to give continuous improvement to the software, giving the possibility of teamwork between two or more developers to make the software code universal. Also, to have within the scheme defined roles such as: testers, tracker, coach, and programmers which allow us to give an agile response to the operation of the software. We seek to have a predictive model with a high percentage of assertiveness in the prediction of how likely it is that the value of Bitcoin will go down or up in real time in the market of the cryptocurrency trading platform coinbase.com, to show the results in a free web application for the public.
Description
Desarrollo de un algoritmo predictivo de la tendencia del Bitcoin con visualización en una aplicación web que permita brindar información, para una adecuada toma de decisiones en el comercio del bitcoin.
Keywords
Tendencia, Bitcoin, Aplicación web, Análisis de datos, Machine Learning, Trend, Bitcoin, Web application