Nothing

```
#
# LSPM: The Leverage Space Portfolio Modeler
#
# Copyright (C) 2009-2010 Soren Macbeth, Joshua Ulrich, and Ralph Vince
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
probProfit <-
function(lsp, target, horizon, error=0.001, sigma=3, snow=NULL) {
if(!missing(target)) {
lsp$z[3] <- target
}
NR <- NROW(lsp$probs)
nsamp <- ( (sigma/error) ^ 2 ) * 0.25
nperm <- NR ^ horizon
sample <- 0 # sampling off by default
if(nperm > nsamp) {
# this turns sampling on and tells the function to sample
# permutations from 1:nperm
sample <- nperm
# this lowers the number of permutations to be calculated
# to nsamp
nperm <- nsamp
}
if(is.null(snow)) {
# calculate all the permutations on the local machine
res <- .probProfit(c(1,nperm), lsp, horizon, sample)
failProb <- res[1]
sumProb <- res[2]
} else {
# number of cores in snow cluster
ncores <- length(snow)
# divide all the needed calculations evenly among all the cores.
ij <- c(seq(1, nperm, nperm/ncores),
seq(nperm/ncores, nperm, nperm/ncores))
ij <- sort(ij)
ind <- list()
for(i in 1:ncores) ind <- c(ind, list(ij[(i-1)*2+(1:2)]))
# clusterSetupRNG, if rlecuyer or rsprng installed
# send the function to the cluster
ca <- clusterApply(snow, ind, fun=.probProfit, lsp=lsp,
horizon=horizon, sample)
# sum the fail and total probabilities from all the cores
seqlen <- 1:length(ca)
failProb <- sum( sapply(seqlen, function(i) ca[[i]][1]) )
sumProb <- sum( sapply(seqlen, function(i) ca[[i]][2]) )
}
out <- failProb / sumProb
return(out)
}
.probProfit <- function(range, lsp, horizon, sample) {
# This is a simple function that can be sent to the cluster
beg <- range[1]
end <- range[2]
res <- .Call('prob_profit', beg, end, lsp, horizon,
sample, PACKAGE="LSPM")
return(res)
}
```

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