Performance Analytics table.AnnualizedReturns

Hi Nick, 

I don't think there's any table for that specific need. However, here's how
I would do it: 

library(PerformanceAnalytics)
data(managers)
R <- managers[, 2]
years <- as.character(unique(lubridate:::year(index(R))))
# Return a list whose elements are years and contain table
ll <- plyr:::llply(years, function(x) {
    ret <- table.AnnualizedReturns(R[x])
    colnames(ret) <- x
    ret
})
# Return a table
df <- unlist(ll)
dim(df) <- c(3, length(years))
colnames(df) <- years
rownames(df) <- c("Annualized Return", "Annualized Volatility", "Sharpe
Ratio")

Cheers! 

Markus D.



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A much simpler solution is to use period.apply.  Note that
table.AnnualizedReturns returns a multi-row data.frame.  period.apply
works best if the function returns a vector, so make a helper function
to do that and everything works.

# A function that wraps table.AnnualizedReturns
# and returns a vector. You might want something
# more elaborate if 'x' has multiple columns and/or
# if you want better column names.
t.table.AnnRet <- function(x)  # one 'x' column
  drop(t(table.AnnualizedReturns(x)))
#t.table.AnnRet <- function(x)  # multiple 'x' columns
#  unlist(table.AnnualizedReturns(x))

# call period.apply via apply.monthly
apply.yearly(managers[,2], t.table.AnnRet)

Best,
--
Joshua Ulrich  |  about.me/joshuaulrich
FOSS Trading  |  www.fosstrading.com

Hi Nick,

I don't think there's any table for that specific need. However, here's how
I would do it:

library(PerformanceAnalytics)
data(managers)
R <- managers[, 2]
years <- as.character(unique(lubridate:::year(index(R))))
# Return a list whose elements are years and contain table
ll <- plyr:::llply(years, function(x) {
    ret <- table.AnnualizedReturns(R[x])
    colnames(ret) <- x
    ret
})
# Return a table
df <- unlist(ll)
dim(df) <- c(3, length(years))
colnames(df) <- years
rownames(df) <- c("Annualized Return", "Annualized Volatility", "Sharpe
Ratio")

Cheers!

Markus D.



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