R/table.Correlation.R

In R-Finance/PerformanceAnalytics: Econometric tools for performance and risk analysis.

#' calculate correlalations of multicolumn data
#' 
#' This is a wrapper for calculating correlation and significance against each
#' column of the data provided.
#' 
#' 
#' @param Ra a vector of returns to test, e.g., the asset to be examined
#' @param Rb a matrix, data.frame, or timeSeries of benchmark(s) to test the
#' asset against.
#' @param \dots any other passthru parameters to \code{\link{cor.test}}
#' @author Peter Carl
#' @seealso \code{\link{cor.test}}
#' @keywords ts multivariate distribution models
#' @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))
#' 
#' @export
table.Correlation <-
function (Ra, Rb, ...)
{# @author Peter Carl

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

    # Inputs:
    # Assumes that Ra and Rb are sequenced exactly the same.

    # Output:
    # A data table of correlation and corresponding p-value for each column
    # in Rb.

    # FUNCTION:

    Ra = checkData(Ra)
    Rb = checkData(Rb)

    # Get dimensions and labels
    columns.a = ncol(Ra)
    columns.b = ncol(Rb)
    columnnames.a = colnames(Ra)
    columnnames.b = colnames(Rb)

    # Calculate
    for(column.a in 1:columns.a) { # for each asset passed in as R
        for(column.b in 1:columns.b) { # against each asset passed in as Rb
            merged.assets = merge(Ra[,column.a,drop=FALSE], Rb[,column.b,drop=FALSE])
            merged.assets = na.omit(merged.assets) # leaves the overlapping period

            htest = cor.test(merged.assets[,1], merged.assets[,2], ...)
            values = cbind(htest$estimate, htest$p.value,htest$conf.int[1],htest$conf.int[2])

            if(column.a == 1 & column.b == 1) {
                result.df = data.frame(Value = values)
                rownames(result.df) = paste(columnnames.a[column.a], columnnames.b[column.b], sep = " to ")
            }
            else {
                nextrow = data.frame(Value = values)
                rownames(nextrow) = paste(columnnames.a[column.a], columnnames.b[column.b], sep = " to ")
                result.df = rbind(result.df, nextrow)
            }
        }
    }

    colnames(result.df) = c("Correlation","p-value","Lower CI","Upper CI")

    result.df

}

###############################################################################
# R (http://r-project.org/) Econometrics for Performance and Risk Analysis
#
# Copyright (c) 2004-2014 Peter Carl and Brian G. Peterson
#
# This R package is distributed under the terms of the GNU Public License (GPL)
# for full details see the file COPYING
#
# $Id$
#
###############################################################################