<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2007-9753</journal-id>
<journal-title><![CDATA[RIIIT. Revista internacional de investigación e innovación tecnológica]]></journal-title>
<abbrev-journal-title><![CDATA[RIIIT. Rev. int. investig. innov. tecnol.]]></abbrev-journal-title>
<issn>2007-9753</issn>
<publisher>
<publisher-name><![CDATA[Universidad Autónoma de Coahuila]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-97532024000200001</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Trading de criptomonedas mediante algoritmos de aprendizaje por refuerzo profundo y aprendizaje automático]]></article-title>
<article-title xml:lang="en"><![CDATA[Cryptocurrency trading using deep reinforcement learning and machine learning algorithms]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Valdez-Rivera]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Saucedo-Zendejo]]></surname>
<given-names><![CDATA[F.R.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Navarro-Acosta]]></surname>
<given-names><![CDATA[J.A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Musi-Gutiérrez]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma de Coahuila Centro de Investigación en Matemáticas Aplicadas ]]></institution>
<addr-line><![CDATA[Saltillo Coahuila]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Autónoma de Coahuila Facultad de Sistemas ]]></institution>
<addr-line><![CDATA[Arteaga Coahuila]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2024</year>
</pub-date>
<volume>12</volume>
<numero>67</numero>
<fpage>1</fpage>
<lpage>15</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-97532024000200001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-97532024000200001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-97532024000200001&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El objetivo de este artículo es realizar una comparación del desempeño de algoritmos de aprendizaje automático y de aprendizaje por refuerzo profundo para la compra y venta de criptomonedas basándose en la predicción de precios. Esto se lleva a cabo mediante el entrenamiento y prueba de dichos modelos usando información diaria que abarca el periodo del 2017-11-09 al 2022-05-01 y fue descargada de la página de Yahoo finance en su sección de criptomonedas. Se observa que los algoritmos de aprendizaje automático tienen métricas de precisión altas en sus predicciones y se ejecutan de forma rápida, aunque no resultan en alto retorno de la inversión, ni tampoco sobrepasan al aprendizaje por refuerzo profundo en este sentido.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The aim of this article is to perform a comparison of the performance of machine learning and deep reinforcement learning algorithms for buying and selling cryptocurrencies based on price prediction. This is done by training and testing such models using daily data spanning the period from 2017-11-09 to 2022-05-01 and was downloaded from Yahoo finance page in their cryptocurrency section. It is observed that machine learning algorithms have high accuracy metrics in their predictions and execute quickly, although they do not result in high return on investment, nor do they surpass deep reinforcement learning in this regard.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[aprendizaje automático]]></kwd>
<kwd lng="es"><![CDATA[criptomonedas]]></kwd>
<kwd lng="es"><![CDATA[trading]]></kwd>
<kwd lng="es"><![CDATA[aprendizaje por refuerzo]]></kwd>
<kwd lng="en"><![CDATA[machine learning]]></kwd>
<kwd lng="en"><![CDATA[cryptocurrencies]]></kwd>
<kwd lng="en"><![CDATA[trading]]></kwd>
<kwd lng="en"><![CDATA[reinforcement learning]]></kwd>
</kwd-group>
</article-meta>
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