table.Correlation {PerformanceAnalytics} | R Documentation |
This is a wrapper for calculating correlation and significance against each column of the data provided.
table.Correlation(Ra, Rb, trim = TRUE, na.rm = FALSE, ...)
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 |
A dataframe with correlation and significance against each column of the data provided as Rb
.
Peter Carl
# 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))