<?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>0186-1042</journal-id>
<journal-title><![CDATA[Contaduría y administración]]></journal-title>
<abbrev-journal-title><![CDATA[Contad. Adm]]></abbrev-journal-title>
<issn>0186-1042</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Facultad de Contaduría y Administración]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0186-10422020000200008</article-id>
<article-id pub-id-type="doi">10.22201/fca.24488410e.2018.1973</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Los determinantes de las variaciones en el rendimiento del oro]]></article-title>
<article-title xml:lang="en"><![CDATA[Determinants of changes in gold returns]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Díaz-Hernández]]></surname>
<given-names><![CDATA[Adán]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ramírez Sánchez]]></surname>
<given-names><![CDATA[José Carlos]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Salazar Flores]]></surname>
<given-names><![CDATA[Yuri]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Anáhuac México  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Panamericana  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Nacional Autónoma de México  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2020</year>
</pub-date>
<volume>65</volume>
<numero>2</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0186-10422020000200008&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0186-10422020000200008&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0186-10422020000200008&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En este trabajo se caracteriza el comportamiento de los rendimientos logarítmicos del oro entre 1995 y 2017 con base en varios modelos de media y varianza condicionales, que incorporan efectos de asimetría y colas pesadas. Para tal efecto, se lleva a cabo, primero, un análisis basado en vectores autorregresivos con el fin de identificar los principales regresores externos y, luego, una serie de ajustes con distintas especificaciones del tipo AR-GARCH para pronosticar la volatilidad de las fluctuaciones del oro con base en dichos regresores. La conclusión principal es que esas fluctuaciones pueden ser adecuadamente explicadas por el comportamiento de las series de USDEER y SP500 de acuerdo con la especificación AR(1)-GARCH(1,1) que tiene asociada una distribución t de Student. Esto quiere decir que los determinantes de largo plazo de las variaciones del rendimiento del oro están relacionados con las estrategias cambiarias y de protección contra el ciclo del mercado de valores por parte de los inversionistas.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This paper explains the behavior of logarithmic gold returns between 1995 and 2017 by using several conditional mean and variance models that incorporate asymmetry and heavy tails effects. For this purpose, we conduct, first, an analysis based on standard autoregressive vectors in order to identify the main external regressors and, later, a sort of adjustments with different specifications of the AR-GARCH type to forecast the volatility of gold-price fluctuations. The main conclusion is that these fluctuations can be adequately explained by the behavior of the USDEER and SP500 series according to the specification AR(1)-GARCH (1, 1) that has a Student t distribution associated to it. This means that the long-term determinants of gold-return volatilities are related to exchange rate hedging strategies and anti-cyclical protection against stock markets variations by investors.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[C46]]></kwd>
<kwd lng="es"><![CDATA[C51]]></kwd>
<kwd lng="es"><![CDATA[D81]]></kwd>
<kwd lng="es"><![CDATA[Fluctuaciones del precio del oro]]></kwd>
<kwd lng="es"><![CDATA[VAR]]></kwd>
<kwd lng="es"><![CDATA[GARCH]]></kwd>
<kwd lng="es"><![CDATA[Métricas de riesgo]]></kwd>
<kwd lng="es"><![CDATA[Pronósticos de volatilidad]]></kwd>
<kwd lng="en"><![CDATA[C46]]></kwd>
<kwd lng="en"><![CDATA[C51]]></kwd>
<kwd lng="en"><![CDATA[D81]]></kwd>
<kwd lng="en"><![CDATA[Gold price fluctuations]]></kwd>
<kwd lng="en"><![CDATA[VAR]]></kwd>
<kwd lng="en"><![CDATA[GARCH]]></kwd>
<kwd lng="en"><![CDATA[Risk measures]]></kwd>
<kwd lng="en"><![CDATA[Volatility forecasts]]></kwd>
</kwd-group>
</article-meta>
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