The Value of Using Predictive Information Optimally

Abstract

For mean-variance investors, using predictive information unconditionally optimally produces better portfolios than using predictive information conditionally optimally. The latter is more usually done in practice. Empirically, the unconditionally optimal portfolios have higher Sharpe ratios and certainty equivalents than the conditionally optimal portfolios. They also have lower turnover, leverage, losses and draw-downs. Moreover, measures of the whole distribution tend to prefer the unconditionally optimal portfolios, especially once transaction costs are accounted for. With transaction costs, the unconditionally optimal portfolios often second-order stochastically dominate the conditionally optimal portfolios. The unconditionally optimal portfolios are also preferred in terms of Sharpe ratio, certainty equivalent, costs, losses, draw-downs and stochastic dominance to mean-variance optimal portfolios that do not use predictive information. However, whether unconditionally optimal portfolios are preferred to minimum variance or 1/N portfolios depends on the asset universe.