{"id":808,"date":"2020-09-01T11:55:20","date_gmt":"2020-09-01T11:55:20","guid":{"rendered":"https:\/\/ricovictor.com\/?p=808"},"modified":"2026-01-29T22:07:13","modified_gmt":"2026-01-29T22:07:13","slug":"correlacion-y-covarianza-con-ventana-de-tiempo","status":"publish","type":"post","link":"https:\/\/ricovictor.com\/index.php\/2020\/09\/01\/correlacion-y-covarianza-con-ventana-de-tiempo\/","title":{"rendered":"Correlaci\u00f3n y Covarianza con Ventana de Tiempo"},"content":{"rendered":"\t\t
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Las ventanas de tiempo o muestrales<\/strong> son muy \u00fatiles en el an\u00e1lisis de datos ya que nos permiten crear una serie de tiempo y ver como se ha comportado en el pasado<\/strong> la variable o estad\u00edstico que estamos estudiando\u00a0<\/p>

La idea es crear una serie siempre con la misma cantidad de periodos de manera que veamos su evoluci\u00f3n en el tiempo<\/strong>.<\/p>

Es \u00fatil<\/strong> y muchas veces es casi imprescindible crearla.<\/p>

Por ejemplo nos sirve como una de las formas m\u00e1s simples para medir la variabilidad y la correlaci\u00f3n<\/strong> que ha tenido un activo financiero o cualquier otra variable. Por supuesto no es el concepto m\u00e1s avanzado en este tema, pero es una aproximaci\u00f3n, y siempre hay que tener en cuenta que el n\u00famero de datos<\/strong> que usemos influir\u00e1 mucho en los resultados.<\/p>

En el siguiente v\u00eddeo tienes un tutorial completo haciendo ejemplos con la correlaci\u00f3n y la covarianza<\/strong> entre pares de divisas.<\/p>

Tambi\u00e9n abajo puedes copiar el c\u00f3digo<\/strong> usado en el v\u00eddeo.<\/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

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\u00a0<\/p>

Codigo R<\/h2>

##3 siempre mismos datos<\/p>

## VIDEO VENTANA DE TIEMPO<\/p>

#### #######<\/p>

#install.packages(\u00abquantmod\u00bb)
library(quantmod)
#install.packages(\u00abtseries\u00bb)
library(tseries)
#install.packages(\u00abfImport\u00bb)
library(fImport)<\/p>

# DESCARGA DE DATOS
# UTILIZAMOS 2 DIVISAS<\/p>

#getFX(\u00abEUR\/USD\u00bb)
#getFX(\u00abGBP\/USD\u00bb)
#getFX(\u00abUSD\/CHF\u00bb)
#getFX(\u00abAUD\/USD\u00bb)<\/p>

#DATOS FRED<\/p>

GBPUSD<-fredSeries(\u00abDEXUSUK\u00bb,from=\u00bb2010-01-01″,to=\u00bb2019-10-23″)
USDCHF<-fredSeries(\u00abDEXSZUS\u00bb,from=\u00bb2010-01-01″,to=\u00bb2019-10-23″)
EURUSD<-fredSeries(\u00abDEXUSEU\u00bb,from=\u00bb2010-01-01″,to=\u00bb2019-10-23″)<\/p>

## Nuestro estudio ser\u00e1 de la correlaci\u00f3n y covarianza<\/p>

### Miramos el n\u00famero de datos que tenemos
## determinamos la ventana m\u00f3vil_ QUe luego podremos variar
## creamos un vector,o matriz vac\u00eda
# creamos el c\u00f3digo con la formula en funci\u00f3n de lo anterior<\/p>

## Correlaci\u00f3n EURUSD Y GBPUSD<\/p>

length(EURUSD)
length(GBPUSD)<\/p>

cor(EURUSD,GBPUSD)<\/p>

#dir\u00edamos que eso es una correlaci\u00f3n de largo plazo con todos nuestros
# datos<\/p>

#nosotros queremos saber algo m\u00e1s,queremos saber como se ha movido en
#en el tiempo<\/p>

#\u255a2456<\/p>

vent<- 120 #cada 120 dias correlacion 1:120- 2:121 – 3:122 — 2337:2456
vent2<- vent-1<\/p>

cor(EURUSD,GBPUSD)<\/p>

cor(EURUSD[1:120],GBPUSD[1:120])
cor(EURUSD[2:121],GBPUSD[2:121])
#.
#.
#.
cor(EURUSD[2337:2456],GBPUSD[2337:2456])<\/p>

victor<-c()
victor<\/p>

##3 corelacion<\/p>

cor(EURUSD[1:120],GBPUSD[1:120])<\/p>

COR=c()
for(i in vent:2456)
{correlacion=cor(EURUSD[(i-vent2):i],GBPUSD[(i-vent2):i])
COR[i]=correlacion} #3 meter las cantidad
COR
plot(COR,type=\u00bbl\u00bb,main=\u00bbCORRELACION_EURUSD\/GBPUSD\u00bb,xlab=\u00bbVENTANA TIEMPO\u00bb)<\/p>

m<-EURUSD
nm<-GBPUSD<\/p>

COV=c()
for(i in vent:length(m))
{covarianza=cov(m[(i-vent2):i],nm[(i-vent2):i])
COV[i]=covarianza}
plot(COV,type=\u00bbl\u00bb)<\/p>

#### modelo video beta<\/p>

beta=c()
for(i in vent:length(m))
{f=lm(m[(i-vent2):i]~nm[(i-vent2):i]-1)
beta[i]=coef(f)}
plot(beta,type=\u00bbl\u00bb)<\/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

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\n\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\tAprende 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
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\n\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\tCurso GRATIS Multicointegraci\u00f3n en FOREX<\/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":"

Las ventanas de tiempo o muestrales son muy \u00fatiles en el an\u00e1lisis de datos ya que nos permiten crear una serie de tiempo y ver como se ha comportado en el pasado la variable o estad\u00edstico que estamos estudiando\u00a0 La idea es crear una serie siempre con la misma cantidad de periodos de manera que …<\/p>\n

Correlaci\u00f3n y Covarianza con Ventana de Tiempo<\/span> Leer m\u00e1s »<\/a><\/p>\n","protected":false},"author":1,"featured_media":809,"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],"tags":[],"yoast_head":"\nCorrelaci\u00f3n y Covarianza con Ventana de Tiempo - V\u00edctor A. 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