<?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>S1665-53462022000200002</article-id>
<article-id pub-id-type="doi">10.21919/remef.v17i2.531</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Estimación bayesiana del modelo de difusión con saltos de Merton]]></article-title>
<article-title xml:lang="en"><![CDATA[On the Bayesian Estimation of Merton's Jump Diffusion Model]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Alba Suarez]]></surname>
<given-names><![CDATA[Miguel Antonio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Alba Acosta]]></surname>
<given-names><![CDATA[Miguel Ángel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Alba Acosta]]></surname>
<given-names><![CDATA[David Camilo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Santo Tomás  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universität Potsdam  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Germany</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2022</year>
</pub-date>
<volume>17</volume>
<numero>2</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1665-53462022000200002&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1665-53462022000200002&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1665-53462022000200002&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En la literatura existen diferentes aportes en la forma como se puede identificar la evolución de los derivados financieros vía precios de los activos subyacentes. El Modelo de Difusión con Saltos de Merton (MDSM) es una de las referencias más importantes para modelar la dinámica estocástica de los rendimientos de los activos en comparación con el modelo de Black y Scholes (B&amp;S). El objetivo principal de este trabajo es realizar un análisis comparativo entre el MDSM y el B&amp;S desde un enfoque bayesiano utilizando métodos Markov-Chain-Monte-Carlo (MCMC). Las simulaciones aplicadas al registro diario de algunas de las principales acciones que conforman el índice NASDAQ evidenciaron la superioridad en ajuste del MDSM sobre los rendimientos financieros vía MCMC. Algunas recomendaciones y limitaciones de esta investigación surgen en la propuesta adecuada para los valores usados como parámetros para las distribuciones a priori previas a la estimación de las distribuciones posterior para cada parámetro de cada modelo. El mayor aporte dentro del marco estadístico de esta investigación es ilustrar la efectividad los métodos MCMC para MDSM en yuxtaposición a B&amp;S.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract In the literature there are different contributions on how to identify the evolution of financial derivatives via underlying asset prices. The Jump-difussion-Merton&#8217;s model (JDMM) is one of the most important references to model the stochastic dynamics of asset returns in comparison with the Black and Scholes (B&amp;S) model. The main objective of this paper is to perform a comparative analysis between the JDMM and the B&amp;S from a Bayesian approach using Markov-Chain-Monte-Carlo (MCMC) methods. Simulations applied to the daily log of some of the main stocks that make up the NASDAQ index evidenced the superiority in goodness of fit of the JDMM over financial returns via MCMC. Some recommendations and limitations of this research arise in the appropriate proposal for the values used as parameters for the prior distributions used before estimating the posterior distributions for each parameter of each model. The major contribution within the statistical framework of this research is illustrating the effectiveness of the MCMC methods for the JDMM in juxtaposition to B&amp;S.]]></p></abstract>
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<kwd lng="es"><![CDATA[Modelo de Difusión con saltos de Merton (MDSM)]]></kwd>
<kwd lng="es"><![CDATA[estadística bayesiana]]></kwd>
<kwd lng="es"><![CDATA[MCMC]]></kwd>
<kwd lng="es"><![CDATA[Modelo de Black &amp; Scholes (B&amp;S)]]></kwd>
<kwd lng="es"><![CDATA[procesos estocásticos]]></kwd>
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<kwd lng="en"><![CDATA[Merton's jump diffusion model (JDMM)]]></kwd>
<kwd lng="en"><![CDATA[Bayesian statistics]]></kwd>
<kwd lng="en"><![CDATA[MCMC]]></kwd>
<kwd lng="en"><![CDATA[Black &amp; Scholes (B&amp;S) model]]></kwd>
<kwd lng="en"><![CDATA[stochastic processes]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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