<?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>0121-4772</journal-id>
<journal-title><![CDATA[Cuadernos de Economía]]></journal-title>
<abbrev-journal-title><![CDATA[Cuad. Econ.]]></abbrev-journal-title>
<issn>0121-4772</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0121-47722019000100023</article-id>
<article-id pub-id-type="doi">10.15446/cuad.econ.v37n76.57654</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[REGRESIÓN CUANTÍLICA DINÁMICA PARA LA MEDICIÓN DEL VALOR EN RIESGO: UNA APLICACIÓN A DATOS COLOMBIANOS]]></article-title>
<article-title xml:lang="en"><![CDATA[Dynamic quantile regression for the measurement of a value at risk: An application to Colombian data]]></article-title>
<article-title xml:lang="fr"><![CDATA[Régression quantile dynamique pour la mesure de la valeur en risque: une application aux données colombiennes]]></article-title>
<article-title xml:lang="pt"><![CDATA[Regressão quantílica dinâmica para a medição do valor em risco: uma aplicação a dados colombianos]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mariño Ustacara]]></surname>
<given-names><![CDATA[Daniel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Melo Velandia]]></surname>
<given-names><![CDATA[Luis Fernando]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional de Colombia  ]]></institution>
<addr-line><![CDATA[Bogotá ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Banco de la República  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2019</year>
</pub-date>
<volume>38</volume>
<numero>76</numero>
<fpage>23</fpage>
<lpage>49</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0121-47722019000100023&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0121-47722019000100023&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0121-47722019000100023&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En este documento se estima el valor en riesgo (VaR) utilizando métodos semiparamétricos basados en regresión cuantílica lineal y no lineal. En particular, se usan varias especificaciones de la familia de modelos CAViaR (conditional autoregressive value at risk). Estos modelos permiten capturar hechos estilizados de las series financieras y evitan imponer supuestos relacionados con la distribución de los activos financieros. Además, estas metodologías son comparadas con técnicas de VaR tradicionales para la tasa de cambio representativa del mercado, un índice de precios de bonos de deuda pública y el índice de la bolsa de valores de Colombia, durante el período comprendido entre diciembre de 2007 y noviembre de 2015. En general, se encontró que las medidas de riesgo de mercado bajo estas metodologías tienen un mejor desempeño respecto a las tradicionales. JEL: C32, C52, G10.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This document contains the results for the estimation of Value at Risk (VaR) based on linear and non-linear quantile regression techniques. In particular, several CAViaR (conditional autoregressive value at risk) models are implemented for this purpose. These models can replicate the empirical properties of asset returns without requiring distributional assumptions. In addition, these methods are compared with traditional VaR techniques for the Colombian peso exchange rate, a public debt market price index and the Colombian stock price index during the periods of December 2007 and November 2015. In general, the quantile regression-based techniques show a good performance with respect to the traditional models. JEL: C32, C52, G10.]]></p></abstract>
<abstract abstract-type="short" xml:lang="fr"><p><![CDATA[Résumé Dans ce document, on évalue la valeur en risque (VaR) en utilisant des méthodes semiparamétriques basées sur la régression quantile linéaire et non linéaire. En particulier, on utilise plusieurs caractérisations de la famille de modèles CAViaR (conditional autoregressive value at risk). Ces modèles permettent de saisir des faits stylisés des séries financières et évitent d&#8217;imposer des hypothèses en rapport avec la distribution des actifs financiers. En outre, ces méthodologies sont comparées avec des techniques de VaR traditionnelles pour le taux de change représentatif du marché, un indice de prix de bons de dette publique et l&#8217;indice de la bourse de valeurs de Colombie, pour la période comprise entre décembre 2007 et novembre 2015. En général, on trouve que les mesures de risque de marché selon ces méthodologies donnent un meilleur résultat que les traditionnelles. JEL: C32, C52, G10.]]></p></abstract>
<abstract abstract-type="short" xml:lang="pt"><p><![CDATA[Resumo Neste documento estima-se o valor em risco (VaR) utilizando métodos semi-paramétricos baseados em regressão quantílica linear e não linear. Particularmente, usam-se várias especificações da família de modelos CAViaR (conditional autoregressive value at risk). Estes modelos permitem capturar fatos estilizados das séries financeiras e evitam impor supostos relacionados com a distribuição dos ativos financeiros. Além do mais, estas metodologias são comparadas às técnicas de VaR tradicionais para a taxa de câmbio representativa do mercado, um índice de preços de bônus de dívida pública e o índice da bolsa de valores da Colômbia, durante o período compreendido entre dezembro de 2007 e novembro de 2015. De modo geral, constatou-se que as medidas de risco de mercado sob estas metodologias têm um melhor desempenho com relação às tradicionais. JEL: C32, C52, G10.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[valor en riesgo]]></kwd>
<kwd lng="es"><![CDATA[regresión cuantílica]]></kwd>
<kwd lng="es"><![CDATA[regresión cuantílica no lineal]]></kwd>
<kwd lng="es"><![CDATA[procesos CAViaR.]]></kwd>
<kwd lng="en"><![CDATA[Value at Risk]]></kwd>
<kwd lng="en"><![CDATA[quantile regression]]></kwd>
<kwd lng="en"><![CDATA[non-linear quantile regression]]></kwd>
<kwd lng="en"><![CDATA[CAViAR model.]]></kwd>
<kwd lng="fr"><![CDATA[valeur en risque]]></kwd>
<kwd lng="fr"><![CDATA[régression quantile]]></kwd>
<kwd lng="fr"><![CDATA[régression quantile non linéaire]]></kwd>
<kwd lng="fr"><![CDATA[processus CAViaR.]]></kwd>
<kwd lng="pt"><![CDATA[valor em risco]]></kwd>
<kwd lng="pt"><![CDATA[regressão quantílica]]></kwd>
<kwd lng="pt"><![CDATA[regressão quantílica não linear]]></kwd>
<kwd lng="pt"><![CDATA[processos CAViaR.]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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