My last post provided examples of how to use the LSPM package. Those who experimented with the code have probably found that constrained optimizations with horizons > 6 have long run-times (when calc.max >= horizon).

This post will illustrate how the snow package can increase the speed of the probDrawdown and probRuin functions on computers with multiple cores. This yields nearly linear improvements in run-times relative to the number of cores. (Improvements are nearly linear because there is overhead in setting up the cluster and communication between the nodes.)

The first optimization takes 346 seconds on my 2.2Ghz Centrino, while the second optimization (with snow) takes 193 seconds… nearly a 45% improvement.

# Load the libraries

library(LSPM)

library(snow)

# Create a Leverage Space Portfolio object

trades <- cbind(

c(-150,-45.33,-45.33,rep(13,5),rep(79.67,3),136),

c(253,-1000,rep(-64.43,3),253,253,448,rep(-64.43,3),253),

c(533,220.14,220.14,-500,533,220.14,799,220.14,-325,220.14,533,220.14) )

probs <- c(rep(0.076923077,2),0.153846154,rep(0.076923077,9))

port <- lsp(trades,probs)
# Optimization using one CPU core

system.time({

res1 <- optimalf(port,probDrawdown,0.1,DD=0.2,horizon=5,control=list(NP=30,itermax=100))

})

# Create snow socket cluster for both cores

clust <- makeSOCKcluster(2)
# Optimization using both CPU cores

system.time({

res2 <- optimalf(port,probDrawdown,0.1,DD=0.2,horizon=5,snow=clust,control=list(NP=30,itermax=100))

})

# Stop snow cluster

stopCluster(clust)

*Related*

To

**leave a comment** for the author, please follow the link and comment on their blog:

** FOSS Trading**.

R-bloggers.com offers

**daily e-mail updates** about

R news and

tutorials on topics such as:

Data science,

Big Data, R jobs, visualization (

ggplot2,

Boxplots,

maps,

animation), programming (

RStudio,

Sweave,

LaTeX,

SQL,

Eclipse,

git,

hadoop,

Web Scraping) statistics (

regression,

PCA,

time series,

trading) and more...

If you got this far, why not

__subscribe for updates__ from the site? Choose your flavor:

e-mail,

twitter,

RSS, or

facebook...

**Tags:** Examples, LSPM