This paper considers robust optimization to cope with uncertainty about the stock return process in one period portfolio selection problems involving options. The ro- bust approach relates portfolio choice to uncertainty, making more cautious portfolios when uncertainty is high. We represent uncertainty by a set of plausible expected returns of the underlyings and show that for this set the robust problem is a second order cone program that can be solved eciently. We illustrate the approach for a benchmark tracking problem and discuss the added value of adopting the robust approach in a stochastic programming framework.
Technical Report, University of Maastricht, 11/2002