<?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>2683-2690</journal-id>
<journal-title><![CDATA[The Anáhuac journal]]></journal-title>
<abbrev-journal-title><![CDATA[The Anáhuac j.]]></abbrev-journal-title>
<issn>2683-2690</issn>
<publisher>
<publisher-name><![CDATA[Universidad Anáhuac del Sur S.C., Facultad de Economía y Negocios]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2683-26902024000100160</article-id>
<article-id pub-id-type="doi">10.36105/theanahuacjour.2024v24n1.06</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Comparing the Performance of Long Short-Term Memory Architectures (LSTM) in Equity Price Forecasting: A Research on the Mexican Stock Market]]></article-title>
<article-title xml:lang="es"><![CDATA[Comparación del desempeño de arquitecturas de memoria a corto y largo plazo (LSTM) en el pronóstico de precios de acciones: una investigación sobre el mercado bursátil mexicano]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[García]]></surname>
<given-names><![CDATA[Samuel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Instituto Tecnológico y de Estudios Superiores de Monterrey EGADE Business School ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2024</year>
</pub-date>
<volume>24</volume>
<numero>1</numero>
<fpage>160</fpage>
<lpage>179</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2683-26902024000100160&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2683-26902024000100160&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2683-26902024000100160&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This study compares the performance of univariate and multivariate Long Short-Term Memory (LSTM) to predict next-day closing prices on four stocks in the consumer retail sector of the Mexican Stock Exchange. Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Median Absolute Percentage Error (MdAPE), and Root Mean Squared Error (RMSE) are used to test the networks&#8217; performance. Results show a better performance on multivariate price forecasts when using 20-day and 15-day length sequences, generating consistent results for the sample, including illiquid and liquid stocks. On the other hand, univariate LSTM discloses lower forecast performance when predicting the price of illiquid stocks.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Este trabajo compara el desempeño de la memoria de corto y largo plazo (LSTM, por sus siglas en inglés) univariada y multivariada en la predicción de los precios de cierre del día siguiente de cuatro acciones del sector de consumo minorista en la Bolsa Mexicana de Valores. El error absoluto medio (MAE, por sus siglas en inglés), el error porcentual absoluto medio (MAPE, por sus siglas en inglés), la mediana del error porcentual absoluto (MdAPE, por sus siglas en inglés) y la raíz del error cuadrático medio (RMSE, por sus siglas en inglés) se utilizan para probar el desempeño de las redes. Por un lado, los resultados muestran un mejor desempeño en el pro nóstico multivariado de precios cuando se utilizan secuencias de 20 y 15 días de duración, generando resultados coherentes para la muestra, incluidas las acciones líquidas e ilíquidas. Por otro lado, la LSTM univariada revela un desempeño de pronóstico menor para la predicción del precio de acciones ilíquidas.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[forecast]]></kwd>
<kwd lng="en"><![CDATA[stocks]]></kwd>
<kwd lng="en"><![CDATA[univariate]]></kwd>
<kwd lng="en"><![CDATA[multivariate]]></kwd>
<kwd lng="en"><![CDATA[LSTM]]></kwd>
<kwd lng="es"><![CDATA[predicción]]></kwd>
<kwd lng="es"><![CDATA[acciones]]></kwd>
<kwd lng="es"><![CDATA[univariada]]></kwd>
<kwd lng="es"><![CDATA[multivariada]]></kwd>
<kwd lng="es"><![CDATA[LSTM]]></kwd>
</kwd-group>
</article-meta>
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