Robust Active Portfolio Management
COLUMBIA UNIV NEW YORK DEPT OF INDUSTRIAL ENGINEERING AND OPERATIONS RESEARCH
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In this paper we construct robust models for active portfolio management in a market with transaction costs. The goal of these robust models is to control the impact of estimation errors in the values of the market parameters on the performance of the portfolio strategy. Our models can handle a large class of piecewise convex transaction cost functions and allow one to impose additional side constraints such as bounds on the portfolio holdings, constraints on the portfolio beta, and limits on cash and industry exposure. We show that the optimal portfolios can be computed by solving second-order cone programs -- a class of optimization problems with a worst case complexity i.e., cost that is comparable to that for solving convex quadratic programs e.g. the Markowitz portfolio selection problem. We tested our robust strategies on simulated data and on real market data from 2000-2003 imposing realistic transaction costs. In these tests, the proposed robust active portfolio management strategies significantly outperformed the SP 500 index without a significant increase in volatility.
- Economics and Cost Analysis
- Statistics and Probability
- Operations Research