3month rolling correlation keeping date column in R - r

Question

This is my data. Daily return data for different sectors.
I would like to compute the 3 month rolling correlation between sectors but keep the date field and have it line up.
> head(data)
Date Communication Services Consumer Discretionary Consumer Staples Energy Financials - AREITs Financials - ex AREITs Health Care
1 2003-01-02 -0.0004 0.0016 0.0033 0.0007 0.0073 0.0006 0.0370
2 2003-01-03 -0.0126 -0.0008 0.0057 -0.0019 0.0016 0.0062 0.0166
3 2003-01-06 0.0076 0.0058 -0.0051 0.0044 0.0063 0.0037 -0.0082
4 2003-01-07 -0.0152 0.0052 -0.0024 -0.0042 -0.0037 -0.0014 0.0027
5 2003-01-08 0.0107 0.0017 0.0047 -0.0057 0.0013 -0.0008 -0.0003
6 2003-01-09 -0.0157 0.0019 -0.0020 0.0009 -0.0016 -0.0012 0.0055
`
My data type is this
$ Date : Date[1:5241], format: "2003-01-02" "2003-01-03" "2003-01-06" "2003-01-07" ...
$ Communication Services : num [1:5241] -0.0004 -0.0126 0.0076 -0.0152 0.0107 -0.0157 0.0057 -0.0131 0.0044 0.0103 ...
$ Consumer Discretionary : num [1:5241] 0.0016 -0.0008 0.0058 0.0052 0.0017 0.0019 -0.0022 0.0057 -0.0028 0.0039 ...
$ Consumer Staples : num [1:5241] 0.0033 0.0057 -0.0051 -0.0024 0.0047 -0.002 0.0043 -0.0005 0.0163 0.004 ...
$ Energy : num [1:5241] 0.0007 -0.0019 0.0044 -0.0042 -0.0057 0.0009 0.0058 0.0167 -0.0026 -0.0043 ...
$ Financials - AREITs : num [1:5241] 0.0073 0.0016 0.0063 -0.0037 0.0013 -0.0016 0 0.0025 -0.0051 0.0026 ...`
Currently what I am doing is this:
rollingcor <- rollapply(data, width=60, function(x) cor(x[,2],x[,3]),by=60, by.column=FALSE)
This works fine and works out the rolling 60 day correlation and shifts the window by 60 days. However it doesnt keep the date column and I find it hard to match the dates.
The end goal here is to produce a df in which the the date is every 3 months and the other columns are the correlations between all the sectors in my data.

Answer 1

Please read the information at the top of the r tag and, in particular provide the input in an easily reproducible manner using dput. In the absence of that we will use data shown below based on the 6x2 BOD data frame that comes with R and use a width of 4. The names on the correlation columns are the row:column numbers in the correlation matrix. For example, compare the 4th row of the output below with cor(data[1:4, -1]) .
fill=NA causes it to output the same number of rows as the input by filling with NA's.
library(zoo)
# test data
data <- cbind(Date = as.Date("2023-02-01") + 0:5, BOD, X = 1:6)
# given data frame x return lower triangular part of cor matrix
# Last 2 lines add row:column names.
Cor <- function(x) {
k <- cor(x)
lo <- lower.tri(k)
k.lo <- k[lo]
m <- which(lo, arr.ind = TRUE) # rows & cols of lower tri
setNames(k.lo, paste(m[, 1], m[, 2], sep = ":"))
}
cbind(data, rollapplyr(data[-1], 4, Cor, by.column = FALSE, fill = NA))
giving:
Date Time demand X 2:1 3:1 3:2
1 2023-02-01 1 8.3 1 NA NA NA
2 2023-02-02 2 10.3 2 NA NA NA
3 2023-02-03 3 19.0 3 NA NA NA
4 2023-02-04 4 16.0 4 0.8280576 1.0000000 0.8280576
5 2023-02-05 5 15.6 5 0.4604354 1.0000000 0.4604354
6 2023-02-06 7 19.8 6 0.2959666 0.9827076 0.1223522