table.TrailingPeriods {PerformanceAnalytics} | R Documentation |
A table of estimates of rolling period return measures
table.TrailingPeriods(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 |
Rb |
an xts, vector, matrix, data frame, timeSeries or zoo object of index, benchmark, portfolio, or secondary asset returns to compare against |
periods |
number of periods to use as rolling window(s), subset of c(3, 6, 9, 12, 18, 24, 36, 48) |
funcs.names |
vector of function names used for labeling table rows |
FUNCS |
list of functions to apply the rolling period to |
digits |
number of digits to round results to |
... |
any other passthru parameters for functions specified in FUNCS |
Peter Carl
data(edhec) table.TrailingPeriods(edhec[,10:13], FUNCS=c("SharpeRatio","VaR"), funcs.names = c("Sharpe Ratio", "Modified VaR"), periods=c(12,24,36)) result=table.TrailingPeriods(edhec[,10:13], FUNCS=c("SharpeRatio","VaR"), funcs.names = c("Sharpe Ratio", "Modified VaR"), 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")