Portfolio optimization whitepaper in MATLAB, R and Python

We revised our whitepaper on portfolio optimization.

The whitepaper gives an introduction to portfolio optimization using the MOSEK conic optimizer from MATLAB, R and Python and includes topics such as:

• Conic formulations of standard Markowitz portfolio problems.
• Minimum risk/maximum return formulations.
• Computing the efficient frontier.
• Computing the maximum Sharpe ratio.
• Exploiting low-rank structure in the covariance matrix to reduce solution time, including factor models.
• Transaction costs with market impact, modeled as a conic quadratic problem.
• Transactions costs with a fixed term, modeled as a conic mixed-integer problem. 

Historical data from the S&P500 index is used in all examples.

The Markowitz portfolio optimization whitepaper and data can be downloaded from the MOSEK publications page.

Server licenses are now available

Until now all licenses MOSEK has sold have been floating licenses. For most of our customers this has been a very convenient type of license but not for all. Therefore, as of the 5th March of 2012 a server license is also available. A server license corresponds to having an unlimited number of licenses available on a prespecified computer/server. Please see our price list for details or contact MOSEK sales.

MOSEK version 6.0.0.135

MOSEK version 6.0.0.135 is available for download at the MOSEK website.

The most important new feature in this release is support for conic quadratic optimization (aka. SOCP) in the AMPL interface. Hence, it is now possible to specify conic quadratic constraints directly in AMPL using a MOSEK specific suffix named cone. Please see the AMPL documentation for details.

The other major changes are:

• Fixed a number of bugs in the mixed integer optimizer.
• Fixed some bugs in the AMPL interface. 
• Fixed a bug occurring under special circumstances in the interior-point optimizer when multiple threads are employed.
• Fixed a bug in the dual simplex optimizer.

DrugMatrix now employs MOSEK

DrugMatrix, an on-line tool by the US Department of Health and Human Services, now employs MOSEK  to compute the database of scorable genomic signatures.

Feature update in the R to MOSEK interface

A new version of the Rmosek package is available. The new features are:

• support for separable convex optimization,
• new methods to formulate quadratic programs on conic quadratic form,
• and a simplified installation process.

Furthermore, a change in input format regarding bounds and cones have been made to decrease the time it takes to construct large problems. Please see the NEWS file for details.

MOSEK is leadership sponsor of ISMP 2012

MOSEK is sponsoring the 21st International Symposium on Mathematical Programming that will take place in Berlin, Germany, August 19-24, 2012. MOSEK will also present at the conference. More about that later.

Octave to MOSEK Interface

Octave is a scripting language and interactive environment suited for numerical computations. As part of our efforts to bring powerful optimization tools closer to our customers, MOSEK is pleased to announce an open source Octave to MOSEK interface is now available at Google Code Project Hosting. The interface makes it possible to solve

• linear,
• conic quadratic (aka. second order cone), 
• and mixed-integer 

problems from Octave. As any convex quadratic problem can be reformulated as a conic quadratic problem, the interface can also be employed to solve convex quadratic and quadratically constrained problems. Note that an R to MOSEK interface was released earlier this year.