Variability Summary: Statistics and Stylized Facts

Table of Mean absolute difference, Monthly standard deviation and annualised standard deviation

table.Variability(R, scale = NA, geometric = TRUE, digits = 4)

Arguments

R	an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
scale	number of periods in a year (daily scale = 252, monthly scale = 12, quarterly scale = 4)
geometric	utilize geometric chaining (TRUE) or simple/arithmetic chaining (FALSE) to aggregate returns, default TRUE
digits	number of digits to round results to

References

Carl Bacon, Practical portfolio performance measurement and attribution, second edition 2008 p.65

See also

StdDev.annualized MeanAbsoluteDeviation

Examples

data(managers)
table.Variability(managers[,1:8])
#>                           HAM1   HAM2   HAM3   HAM4   HAM5   HAM6 EDHEC LS EQ
#> Mean Absolute deviation 0.0182 0.0268 0.0268 0.0410 0.0329 0.0187      0.0159
#> Monthly Std Dev         0.0256 0.0367 0.0365 0.0532 0.0457 0.0238      0.0205
#> Annualized Std Dev      0.0888 0.1272 0.1265 0.1843 0.1584 0.0825      0.0708
#>                         SP500 TR
#> Mean Absolute deviation   0.0333
#> Monthly Std Dev           0.0433
#> Annualized Std Dev        0.1500

require("Hmisc")
#> Loading required package: Hmisc
#> Warning: there is no package called ‘Hmisc’
result = t(table.Variability(managers[,1:8]))

textplot(format.df(result, na.blank=TRUE, numeric.dollar=FALSE, cdec=c(3,3,1)),
rmar = 0.8, cmar = 2,  max.cex=.9, halign = "center", valign = "top",
row.valign="center", wrap.rownames=20, wrap.colnames=10,
col.rownames=c("red", rep("darkgray",5), rep("orange",2)), mar = c(0,0,3,0)+0.1)
#> Error in format.df(result, na.blank = TRUE, numeric.dollar = FALSE, cdec = c(3,     3, 1)): could not find function "format.df"
title(main="Portfolio variability")
#> Error in title(main = "Portfolio variability"): plot.new has not been called yet