table.HigherMoments: Higher Moments Summary: Statistics and Stylized Facts

Description

Summary of the higher moements and Co-Moments of the return distribution. Used to determine diversification potential. Also called "systematic" moments by several papers.

Usage

table.HigherMoments(Ra, Rb, scale = NA, Rf = 0, digits = 4, method = "moment")

Arguments

Ra: an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
Rb: return vector of the benchmark asset
scale: number of periods in a year (daily scale = 252, monthly scale = 12, quarterly scale = 4)
Rf: risk free rate, in same period as your returns
digits: number of digits to round results to
method: method to use when computing kurtosis one of: excess, moment, fisher

Author

Peter Carl

References

Martellini L., Vaissie M., Ziemann V. Investing in Hedge Funds: Adding Value through Active Style Allocation Decisions. October 2005. Edhec Risk and Asset Management Research Centre.

Examples

Run this code


data(managers)
table.HigherMoments(managers[,1:3],managers[,8,drop=FALSE])
result=t(table.HigherMoments(managers[,1:6],managers[,8,drop=FALSE]))
rownames(result)=colnames(managers[,1:6])

 # don't test on CRAN, since it requires Suggested packages

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=5, wrap.colnames=10, mar = c(0,0,3,0)+0.1)
title(main="Higher Co-Moments with SP500 TR")