Rolling Periods Summary: Statistics and Stylized Facts
A table of estimates of rolling period return measures
table.RollingPeriods(
R,
periods = subset(c(12, 36, 60), c(12, 36, 60) < length(as.matrix(R[, 1]))),
FUNCS = c("mean", "sd"),
funcs.names = c("Average", "Std Dev"),
digits = 4,
...
)
table.TrailingPeriodsRel(
R,
Rb,
periods = subset(c(12, 36, 60), c(12, 36, 60) < length(as.matrix(R[, 1]))),
FUNCS = c("cor", "CAPM.beta"),
funcs.names = c("Correlation", "Beta"),
digits = 4,
...
)R |
an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns |
periods |
number of periods to use as rolling window(s), subset of
|
FUNCS |
list of functions to apply the rolling period to |
funcs.names |
vector of function names used for labeling table rows |
digits |
number of digits to round results to |
... |
any other passthru parameters for functions specified in FUNCS |
Rb |
an xts, vector, matrix, data frame, timeSeries or zoo object of index, benchmark, portfolio, or secondary asset returns to compare against |
Peter Carl
data(edhec)
table.TrailingPeriods(edhec[,10:13], periods=c(12,24,36))
result=table.TrailingPeriods(edhec[,10:13], periods=c(12,24,36))
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=15, wrap.colnames=10, mar = c(0,0,3,0)+0.1)
title(main="Trailing Period Statistics")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.