<?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>1665-5346</journal-id>
<journal-title><![CDATA[Revista mexicana de economía y finanzas]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. mex. econ. finanz]]></abbrev-journal-title>
<issn>1665-5346</issn>
<publisher>
<publisher-name><![CDATA[Instituto Mexicano de Ejecutivos de Finanzas A.C.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1665-53462018000100001</article-id>
<article-id pub-id-type="doi">10.21919/remef.v13i1.257</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Valor en Riesgo mediante un modelo heterocedástico condicional &#945;-estable]]></article-title>
<article-title xml:lang="en"><![CDATA[Value at Risk using an &#945;-Stable Conditional Heterocedastic Model]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Serrano Bautista]]></surname>
<given-names><![CDATA[Ramona]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mata Mata]]></surname>
<given-names><![CDATA[Leovardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Tecnológico de Monterrey  ]]></institution>
<addr-line><![CDATA[Guadalajara Jalisco]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Tecnológico de Monterrey  ]]></institution>
<addr-line><![CDATA[ Estado de México]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2018</year>
</pub-date>
<volume>13</volume>
<numero>1</numero>
<fpage>1</fpage>
<lpage>26</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1665-53462018000100001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1665-53462018000100001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1665-53462018000100001&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: El objetivo de esta investigación es describir y comparar la estimación del Valor en Riesgo (VaR), considerando un modelo GARCH univariado con la innovación de la distribución &#945;-estable. Los resultados estadísticos sugieren que el modelo VaR &#945;-estable proporciona estimaciones del VaR más precisas que el modelo bajo la hipótesis gaussiana, el cual subestima significativamente el VaR en períodos de alta volatilidad. Por el contrario, en el período posterior a la crisis, el VaR al 95% bajo la hipótesis gaussiana muestra resultados aceptables y el obtenido bajo el modelo &#945;-estable se encuentra por debajo del rango admisible. La principal aportación de esta investigación es que propone una distribución condicional alternativa para los rendimientos de los precios de los activos en el mercado financiero mexicano, considerando un modelo GARCH con la innovación de la distribución &#945;-estable. Por último, esta investigación proporciona evidencia de que el modelo VaR &#945;-estable estima satisfactoriamente el VaR para niveles altos de confianza incluso en períodos de alta volatilidad. En contraste, en períodos de relativa tranquilidad para niveles de confianza bajos este modelo sobrestima las pérdidas potenciales.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: The aim of this research is to describe and compare the estimation of Value at Risk (VaR), considering a univariate GARCH model with the innovation of the a-stable distribution. The statistical results suggest that the a-stable VaR model provides more accurate VaR estimations than the traditional Gaussian model, which significantly underestimates VaR in periods of high volatility. In contrast, in the post-crisis period, VaR at 95% under the Gaussian hypothesis shows acceptable results, and that obtained under the a-stable model is below the admissible range. The main contribution of this research is that it proposes an alternative conditional distribution for asset price yields in the Mexican financial market, considering a GARCH model with the innovation of the a-stable distribution. Finally, this research provides evidence that the a-stable VaR model satisfactorily estimates the VaR for high levels of confidence even in periods of high volatility. In contrast, in periods of relative financial tranquility for low confidence levels, this model overestimates potential losses.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Valor en Riesgo (VaR)]]></kwd>
<kwd lng="es"><![CDATA[Distribución estable]]></kwd>
<kwd lng="es"><![CDATA[GARCH]]></kwd>
<kwd lng="es"><![CDATA[Modelo heterocedástico condicional &#945;-estable]]></kwd>
<kwd lng="es"><![CDATA[G17]]></kwd>
<kwd lng="es"><![CDATA[C22]]></kwd>
<kwd lng="es"><![CDATA[C13]]></kwd>
<kwd lng="en"><![CDATA[Value at Risk (VaR)]]></kwd>
<kwd lng="en"><![CDATA[Stable Distribution]]></kwd>
<kwd lng="en"><![CDATA[GARCH]]></kwd>
<kwd lng="en"><![CDATA[&#945;-Stable Conditional]]></kwd>
<kwd lng="en"><![CDATA[Heterocedastic Model]]></kwd>
<kwd lng="en"><![CDATA[G17]]></kwd>
<kwd lng="en"><![CDATA[C22]]></kwd>
<kwd lng="en"><![CDATA[C13]]></kwd>
</kwd-group>
</article-meta>
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