I am trying to simulate the trajectory of the pension assets of one
person. In C-like syntax, it looks like this:
daily.wage.growth = 1.001 # deterministic
contribution.rate = 0.08 # deterministic 8%
Wage = 10 # initial
Asset = 0 # initial
for (10,000 days) {
Asset += contribution.rate * Wage # accreting contributions
Wage *= daily.wage.growth * Wage # wage growth
Asset *= draw from a normal distribution # Asset returns
}
cat("Terminal asset = ", Asset, "\n")
How can one do this well in R? What I tried so far is to notice that
the wage trajectory is deterministic, it does not change from one run
to the next, and it can be done in one line. The asset returns
trajectory can be obtained using a single call to rnorm(). Both these
can be done nicely using R functions (if you're curious, I can give
you my code). Using these, I efficiently get a vector of contributions
c[] and a vector of returns r[]. But that still leaves the loop:
Asset <- 0
for (t in 1:T) {
Asset <- c[t] + r[t]*Asset
}
How might one do this better?
I find that using this code, it takes roughly 0.3 seconds per
computation of Asset (on my dinky 500 MHz Celeron). I need to do
50,000 of these every now and then, and it's a pain to have to wait 3
hours. It'll be great if there is some neat R way to rewrite the
little loop above.
--
Ajay Shah Consultant
[EMAIL PROTECTED] Department of Economic Affairs
http://www.mayin.org/ajayshah Ministry of Finance, New Delhi
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