<?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>S1665-53462019000300447</article-id>
<article-id pub-id-type="doi">10.21919/remef.v14i3.409</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Estimación de la distribución multivariada de los rendimientos de los tipos de cambio contra el dólar de las criptomonedas Bitcoin, Ripple y Ether]]></article-title>
<article-title xml:lang="en"><![CDATA[Estimation of the multivariate distribution of exchange rate yields against the dollar of the Cryptocurrencies Bitcoin, Ripple and Ether]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mota Aragón]]></surname>
<given-names><![CDATA[Beatriz]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Núñez]]></surname>
<given-names><![CDATA[José Antonio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma Metropolitana  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Instituto Tecnológico y de Estudios Superiores de Monterrey  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>09</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>09</month>
<year>2019</year>
</pub-date>
<volume>14</volume>
<numero>3</numero>
<fpage>447</fpage>
<lpage>457</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1665-53462019000300447&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1665-53462019000300447&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1665-53462019000300447&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En este artículo se estima la distribución multivariada para analizar la dependencia del Bitcoin (BTC), Ripple (XRP) y Ether (ETH). Se utiliza la familia Hiperbólica Generalizada de distribuciones (GH) y en particular la distribución Varianza Gamma. El procedimiento para la estimación de los parámetros de la GH es a través del algoritmo EM (Expectation-Maximization). Los resultados muestran que existe una dependencia positiva entre los tres tipos de cambio respecto del dólar americano y seestima una distribución Varianza-Gamma de dimensión tres. Esta distribución es muy flexible para el ajuste de series de los rendimientos con leptocurtosis y sesgo. Esta información se considera importante para los inversionistas que conforman sus portafolios de una manera eficiente.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract In this paper we estimated the multivariate distribution among Bitcoin (BTC), Ripple (XRP) and Ether (ETH) to analyze the dependence. We used the Hyperbolic Generalized (GH) family of distributions and in particular the Variance-Gamma distribution.The procedure for the estimation of the parameters of the GH distribution is through the EM (Expectation-Maximization) algorithm. The results show that there exists a positive dependence among the three exchange rates with respect to the American dollar and a Variance-Gamma distribution of dimension three is estimated. This distribution is very flexible for the adjustment of returns with leptokurtosis and skewness. This distribution is very flexible for the adjustment of the returns with leptokurtosis and skewness. The information is important for the investors who construct their portfolios in an efficient way.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[leptokurtosis]]></kwd>
<kwd lng="es"><![CDATA[asimetría]]></kwd>
<kwd lng="es"><![CDATA[varianza gamma]]></kwd>
<kwd lng="es"><![CDATA[multivariante]]></kwd>
<kwd lng="es"><![CDATA[C11]]></kwd>
<kwd lng="es"><![CDATA[C46]]></kwd>
<kwd lng="en"><![CDATA[leptokurtosis]]></kwd>
<kwd lng="en"><![CDATA[skewness]]></kwd>
<kwd lng="en"><![CDATA[Variance-Gamma]]></kwd>
<kwd lng="en"><![CDATA[Multivariate]]></kwd>
<kwd lng="en"><![CDATA[C11]]></kwd>
<kwd lng="en"><![CDATA[C46]]></kwd>
</kwd-group>
</article-meta>
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