I have a dataset that includes a date column and the other columns are daily index returns. I would like to receive the rolling standard deviation for all indices but preserve the date in order to plot the results. Data looks as follows:
head(mydata)
Date GL1 GL2 US CN JP DE UK
1 1990-01-03 0.02460 NA -0.25889 NA NA 3.00128 1.20872
2 1990-01-04 0.33681 NA -0.86503 NA NA -1.82327 -0.49234
3 1990-01-05 -0.81943 NA -0.98041 NA -1.13817 -0.86874 -0.29003
4 1990-01-06 NA NA NA NA NA NA NA
5 1990-01-07 NA NA NA NA NA NA NA
When using rollapply function the date however disappears and returns NAs
require(zoo)
Rolling = as.data.frame(rollapply(mydata,30,sd,na.rm=TRUE,align="right"))
head(Rolling)
Date GL1 GL2 US CN JP DE UK
1 NA 0.5527451 NA 1.033204 NA 0.9021960 1.486567 0.8421562
2 NA 0.5675608 NA 1.057156 NA 0.9318496 1.467637 0.7954081
3 NA 0.5681388 NA 1.077253 NA 0.9318496 1.438117 0.8123918
4 NA 0.5663124 NA 1.095049 NA 0.9264034 1.454327 0.8331727
5 NA 0.5623544 NA 1.075118 NA 0.9017324 1.443547 0.8123613
6 NA 0.5523878 NA 1.052310 NA 0.8797660 1.411220 0.8197624
I kept the date in the as.Date format but can not figure out how to continue showing the corresponding dates in the Date column.
The real problem here is using data frames to represent time series. If you use a time series representation then the entire problem goes away.
mydata_z <- read.zoo(mydata)
r <- rollapplyr(mydata_z, 30, sd, na.rm = TRUE, fill = NA)
Now you can use plot.zoo, xyplot.zoo or autoplot.zoo to graph r using classic graphics, lattice graphics or ggplot2 graphics respectively or if you need a data frame then fortify.zoo(r).