PerformanceAnalytics (version 0.9.5)

table.Correlation: 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, trim = TRUE, na.rm = FALSE, ...)

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.

trim

TRUE/FALSE, whether to keep alignment caused by NA's

na.rm

TRUE/FALSE Remove NA's from the returns?

...

any other passthru parameters

Value

• A dataframe with correlation and significance against each column of the data provided as Rb.

Examples

# First we load the data
data(edhec)
edhec.length = dim(edhec)[1]
start = rownames(edhec[1,])
start
end = rownames(edhec[edhec.length,])
edhec.zoo = zoo(edhec, order.by = rownames(edhec))
rf.zoo = download.RiskFree(start = start, end = end)
sp500.zoo = download.SP500PriceReturns(start = "1996-12-31", end = end)

# Now we have to align it as "monthly" data
time(edhec.zoo) = as.yearmon(time(edhec.zoo))
time(sp500.zoo) = as.yearmon(time(sp500.zoo))
time(rf.zoo) = as.yearmon(time(rf.zoo))
data.zoo = merge(edhec.zoo,sp500.zoo)
time(data.zoo) = as.Date(time(data.zoo),format="%b %Y")
time(rf.zoo) = as.Date(time(rf.zoo),format="%b %Y")

table.Correlation(data.zoo[,14,drop=FALSE],data.zoo[,1:13])
ctable = table.Correlation(data.zoo[,14,drop=FALSE],data.zoo[,1:13], conf.level=.99)
dotchart(ctable[,1],labels=rownames(ctable),xlim=c(-1,1))