Managers can improve the performance of the mean–variance approach by using enhanced portfolio optimization (EPO). EPO accounts for the noise in investors’ estimates of risk–return and, as a result, increases risk-adjusted performance.
Portfolio optimization should provide large benefits for investors, but standard mean–variance optimization (MVO) works so poorly in practice that optimization is often abandoned. Many of the approaches developed to address this issue are surrounded by mystique regarding how, why, and whether they really work. So, we sought to simplify, unify, and demystify optimization. We identified the portfolios that cause problems in standard MVO, and we present here a simple “enhanced portfolio optimization” method. Applying this method to industry momentum and time-series momentum across equities and global asset classes, we found significant alpha beyond the market, the 1/N portfolio, and standard asset pricing factors.