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Investment technology for the 21st century.
A new beta and more

There are several new things in the Portfolio Probe world.

Second beta of version 1.04

There is a second beta available of Portfolio Probe version 1.04.  The two main changes are:

  • It works under R 2.14.x (a namespace was added)
  • Specification of trading costs is generalized (by user request)
The trading cost item allows each asset to have different exponents in the formula.  That is, market impact can be asset specific rather than a property of the universe.

More about the beta can be found in the user email:

BurStFin is now on CRAN

The BurStFin R package is (finally) on CRAN.  It is almost the same as the old version, but has a bit of improvement:

  • It works in R 2.14.x (a namespace was added)
  • The variance estimation functions (Ledoit-Wolf shrinkage and statistical factor model) now warn by default if you accidentally give them prices rather than returns
  • There is a new function that creates a three-dimensional array from one or more matrices
The blog post with more detail is

Using Portfolio Probe in C++

The real work of random portfolio generation and trade optimization in Portfolio Probe is done in C.  So it would seem that if you want to use Portfolio Probe in a C++ program that calling that code directly would be the thing to do.  In actuality that is a very hard path to go down.

But there's an alternative.  Thanks to the wonderful R packages Rcpp and RInside it is quite easy to call R code from C++.  This includes Portfolio Probe.

There is now an example of doing this on the Cookbook page on the Portfolio Probe website:

Blog highlights 

The most popular blog posts in January are listed in:

The winner was the post "The top 7 portfolio optimization problems":

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