table.Correlation: calculate correlalations of multicolumn data

In braverock/PerformanceAnalytics: Econometric Tools for Performance and Risk Analysis

calculate correlalations of multicolumn data

Description

This is a wrapper for calculating correlation and significance against each column of the data provided.

Usage

table.Correlation(Ra, Rb, ...)

Arguments

Ra	a vector of returns to test, e.g., the asset to be examined
Rb	a matrix, data.frame, or timeSeries of benchmark(s) to test the asset against.
...	any other passthru parameters to cor.test

Author(s)

Peter Carl

See Also

cor.test

Examples

# First we load the data
data(managers)
table.Correlation(managers[,1:6],managers[,7:8])

result=table.Correlation(managers[,1:6],managers[,8])
rownames(result)=colnames(managers[,1:6])
require("Hmisc")
textplot(format.df(result, na.blank=TRUE, numeric.dollar=FALSE, 
         cdec=rep(3,dim(result)[2])), rmar = 0.8, cmar = 1.5,  
         max.cex=.9, halign = "center", valign = "top", row.valign="center"
         , wrap.rownames=20, wrap.colnames=10, mar = c(0,0,3,0)+0.1)
title(main="Correlations to SP500 TR")

ctable = table.Correlation(managers[,1:6],managers[,8,drop=FALSE], conf.level=.99)
dotchart(ctable[,1],labels=rownames(ctable),xlim=c(-1,1))

braverock/PerformanceAnalytics documentation built on Feb. 16, 2024, 5:37 a.m.