Wednesday, March 14, 2012

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.