R help - Oct 2010 - Calculating confidence intervals on subset of bootstrap sample statistics

I have a vector of monthly log asset price returns. I would like use the boot
package to sample one-year returns, and then calculate confidence intervals on
the loss distribution only. More concretely, I would like to say something like
"99% of LOSSES (not RETURNS) are above cutoff X."

If the variable "x" contains my returns and I was interested in
confidence intervals for the entire distribution of returns, I might do
something like this:

results <- boot(x, statistic=function(d, indx) sum(d[indx[1:12]]), R=100000)
boot.ci(results, conf=.98)

In this case I establish a cutoff for the bottom 1% of the return distribution,
but this is not the same thing as the bottom 1% for the losses only. It seems
one thing to do would be to just extract the sample returns from the results
object, filter them, and then calculate confidence intervals manually. However,
I was curious if there was a simple way to subset the results object so that it
could be fed directly into boot.ci()

Thanks.

Abiel
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