Hot answers tagged robust-optimization
It depends on what you want to optimize with transaction costs: liquidation hedging allocation The two best reference I have in mind are: Gökay, S., Roch, A., Soner, 2011. Liquidity models in continuous and discrete time. In: Di Nunno, G., Øksendal, B. (Eds.), Advanced Mathematical Methods for Finance. Springer Berlin Heidelberg, pp. 333-365. URL ...
In robust optimization, the true return is not known, we just have a prior $\alpha$ and you have to take into account a possible misestimate which can lower the true return. This is done under the assumption that the posterior return will be within the prior return $\alpha$ plus minus the error being in some $\sigma$-interval. Now a try for a more formal ...
The Lyxor white paper Regularization of Portfolio Allocation contains a lot on this topic. The head of quant research there, Thierry Roncalli, also held a talk about this recently.
From a general point of view and to answer directly to your originial question, you should only have to modify the inputs to the MATLAB function you refer to. As a matter of fact, fmincon is an optimizer looking to process a broad variety of problems as explained in the documentation: fmincon attempts to find a constrained minimum of a scalar function of ...
You could refer Dimitris Bertsimas's work on Robust Optimization. One of his notable works that may be relevant include robust optimization formulations of the multiperiod portfolio optimization problem in the presence of transaction costs.
Only top voted, non community-wiki answers of a minimum length are eligible