I am working on some computations for large datasets of market data and I was wondering is there is a simple way to apply the following logic without using heavy looping. I will simplify the problem:

Say that I have a time series

data = 1 4 9 3.12 6.07 2 20.19 18.34 7.1 7.34 8.23 9.34 5.011

where each number represents a certain market value at each consecutive day (going from day 1 to day 13). I want to calculate a rolling standard deviation starting from day 9, that is, a new time series, where the first value is the standard deviation from values day 1 - day 9 in the data vector, second value is the standard deviation of day 2 - day 10 in the data vector ... until the standard deviation of day 5 - day 13 in the data vector and store these values in a new vector of length 5.

What is the easiest way to do this for large datasets? I have done some research and the package 'zoo' might be useful maybe? How to extend the above analysis when working with percentiles instead of standard deviations?



1 Answer 1


Functio rollapply in package zoo will let you apply a function (given as argument FUN) to a moving section of your time series. I think this is what you are after.


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