table.RollingPeriods: Rolling Periods Summary: Statistics and Stylized Facts

In braverock/PerformanceAnalytics: Econometric Tools for Performance and Risk Analysis

Rolling Periods Summary: Statistics and Stylized Facts

Description

A table of estimates of rolling period return measures

Usage

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,
  ...
)

Arguments

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 c(3, 6, 9, 12, 18, 24, 36, 48)
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

Author(s)

Peter Carl

See Also

rollapply

Examples

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")

braverock/PerformanceAnalytics documentation built on Feb. 16, 2024, 5:37 a.m.