{"id":724,"date":"2020-07-27T09:41:10","date_gmt":"2020-07-27T09:41:10","guid":{"rendered":"https:\/\/ricovictor.com\/?p=724"},"modified":"2020-07-27T09:41:15","modified_gmt":"2020-07-27T09:41:15","slug":"vectores-autorregresivos-en-r","status":"publish","type":"post","link":"https:\/\/ricovictor.com\/index.php\/2020\/07\/27\/vectores-autorregresivos-en-r\/","title":{"rendered":"Vectores Autorregresivos en R"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"724\" class=\"elementor elementor-724\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-8101e32 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8101e32\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f2e4dec\" data-id=\"f2e4dec\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-be86119 elementor-widget elementor-widget-text-editor\" data-id=\"be86119\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>EL modelo con <strong>Vectores Autorregresivos (VAR)<\/strong> es uno de los m\u00e1s exitosos, flexibles y f\u00e1ciles de usar para el an\u00e1lisis de series de tiempo <strong>multivariadas<\/strong>. Es una extensi\u00f3n natural del modelo autorregresivo univariante de series temporales multivariadas din\u00e1micas. El modelo VAR ha demostrado ser especialmente \u00fatil para describir el <strong>comportamiento din\u00e1mico<\/strong> de series temporales econ\u00f3micas y financieras, as\u00ed como para sus pron\u00f3sticos. A menudo proporciona mejores pron\u00f3sticos \u00a0 que otros modelos econom\u00e9tricos. Los pron\u00f3sticos de los modelos VAR son bastante flexibles porque pueden ser condicionado a las posibles rutas futuras de variables especificadas en el modelo.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-43be57f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"43be57f\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-75545f3\" data-id=\"75545f3\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f1c8e13 elementor-widget elementor-widget-text-editor\" data-id=\"f1c8e13\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Adem\u00e1s de la descripci\u00f3n y pron\u00f3stico de datos, el modelo VAR tambi\u00e9n es utilizado para <strong>inferencia estructural<\/strong> y an\u00e1lisis de pol\u00edticas. En el an\u00e1lisis estructural, se consideran ciertos supuestos sobre la estructura causal de los datos con los que se est\u00e1 trabajando. Los<strong> impactos causales<\/strong> son usualmente resumidos a trav\u00e9s de las <strong>funciones de impulso respuesta<\/strong> y la descomposici\u00f3n de la varianza.<\/p><p>.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-656a4f9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"656a4f9\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-7425602\" data-id=\"7425602\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-84e18a9 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"84e18a9\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eb54042 elementor-widget elementor-widget-text-editor\" data-id=\"eb54042\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Es este tutorial se explican las bases para trabajar con modelos VAR en Rstudio, as\u00ed como la <strong>causalidad de Granger<\/strong> para finalmente exponer el procedimiento para estimar y graficar el impulso respuesta.\u00a0<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4f88b66 elementor-view-default elementor-widget elementor-widget-icon\" data-id=\"4f88b66\" data-element_type=\"widget\" data-widget_type=\"icon.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-icon-wrapper\">\n\t\t\t<div class=\"elementor-icon elementor-animation-pulse\">\n\t\t\t<i aria-hidden=\"true\" class=\"fas fa-video\"><\/i>\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-0233dc2\" data-id=\"0233dc2\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0518fdb elementor-widget elementor-widget-video\" data-id=\"0518fdb\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/www.youtube.com\\\/watch?v=AhSENS5Ka1U&amp;t=41s&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-093b8e2 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"093b8e2\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-86e866e\" data-id=\"86e866e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1689333 elementor-widget elementor-widget-spacer\" data-id=\"1689333\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d53f66b elementor-widget elementor-widget-text-editor\" data-id=\"d53f66b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4><strong>Si te interesa aprender a usar los modelos econom\u00e9tricos aplicados a finanzas aqu\u00ed tienes un curso de introducci\u00f3n que he creado basado en el Arbitraje Estad\u00edstico.Pincha en le bot\u00f3n de abajo\u00a0 \ud83d\udc47\ud83d\udc47<\/strong><\/h4>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ac228a5 elementor-button-info elementor-align-center elementor-widget elementor-widget-button\" data-id=\"ac228a5\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-lg\" href=\"https:\/\/ricovictor.com\/index.php\/iniciacion-al-arbitraje-estadistico\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Curso Introducci\u00f3n al Arbitraje Estad\u00edstico<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>EL modelo con Vectores Autorregresivos (VAR) es uno de los m\u00e1s exitosos, flexibles y f\u00e1ciles de usar para el an\u00e1lisis de series de tiempo multivariadas. Es una extensi\u00f3n natural del modelo autorregresivo univariante de series temporales multivariadas din\u00e1micas. El modelo VAR ha demostrado ser especialmente \u00fatil para describir el comportamiento din\u00e1mico de series temporales econ\u00f3micas &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/ricovictor.com\/index.php\/2020\/07\/27\/vectores-autorregresivos-en-r\/\"> <span class=\"screen-reader-text\">Vectores Autorregresivos en R<\/span> Leer m\u00e1s &raquo;<\/a><\/p>\n","protected":false},"author":3,"featured_media":730,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"footnotes":""},"categories":[2,13],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Vectores Autorregresivos en R - V\u00edctor A. Rico \u2014 Econometr\u00eda y Finanzas Cuantitativas<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ricovictor.com\/index.php\/2020\/07\/27\/vectores-autorregresivos-en-r\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Vectores Autorregresivos en R - V\u00edctor A. Rico \u2014 Econometr\u00eda y Finanzas Cuantitativas\" \/>\n<meta property=\"og:description\" content=\"EL modelo con Vectores Autorregresivos (VAR) es uno de los m\u00e1s exitosos, flexibles y f\u00e1ciles de usar para el an\u00e1lisis de series de tiempo multivariadas. Es una extensi\u00f3n natural del modelo autorregresivo univariante de series temporales multivariadas din\u00e1micas. El modelo VAR ha demostrado ser especialmente \u00fatil para describir el comportamiento din\u00e1mico de series temporales econ\u00f3micas &hellip; Vectores Autorregresivos en R Leer m\u00e1s &raquo;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/ricovictor.com\/index.php\/2020\/07\/27\/vectores-autorregresivos-en-r\/\" \/>\n<meta property=\"og:site_name\" content=\"V\u00edctor A. 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Rico \u2014 Econometr\u00eda y Finanzas Cuantitativas","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/ricovictor.com\/index.php\/2020\/07\/27\/vectores-autorregresivos-en-r\/","og_locale":"es_ES","og_type":"article","og_title":"Vectores Autorregresivos en R - V\u00edctor A. Rico \u2014 Econometr\u00eda y Finanzas Cuantitativas","og_description":"EL modelo con Vectores Autorregresivos (VAR) es uno de los m\u00e1s exitosos, flexibles y f\u00e1ciles de usar para el an\u00e1lisis de series de tiempo multivariadas. Es una extensi\u00f3n natural del modelo autorregresivo univariante de series temporales multivariadas din\u00e1micas. El modelo VAR ha demostrado ser especialmente \u00fatil para describir el comportamiento din\u00e1mico de series temporales econ\u00f3micas &hellip; Vectores Autorregresivos en R Leer m\u00e1s &raquo;","og_url":"https:\/\/ricovictor.com\/index.php\/2020\/07\/27\/vectores-autorregresivos-en-r\/","og_site_name":"V\u00edctor A. 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