Portfolio Optimization Using Forward-Looking Information

In this paper we develop the rst estimator of the covariance matrix that relies solely onforward-looking information. This estimator only uses price information from a cross-sectionof plain-vanilla options. In an out-of-sample study for US blue-chip stocks we show that aminimum-variance strategy based on this fully implied estimator consistently outperforms awide range of benchmark strategies, including strategies based on historical estimates, indexinvesting, and investing according to the 1/N rule. The outperformance is strong in periodsof high information asymmetry, whereas in quiet periods all strategies lead to similar results.The outperformance can only be reached using a fully implied approach; partially impliedapproaches that combine implied moments with historical ones might even perform worsethan purely historical approaches.