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.

资产组合优化应该为投资者带来巨大的收益，但是标准均值-方差优化（MVO）在实践中效果不佳，以至于优化常常被放弃。为解决此问题而开发的许多方法都被关于如何，为什么以及是否真正起作用的神秘感所包围。因此，我们试图简化，统一和揭开优化的神秘面纱。我们确定了导致标准MVO出现问题的投资组合，在此提出一种简单的“增强的投资组合优化”方法。将这种方法应用于股票和全球资产类别的行业动量和时间序列动量，我们发现除市场，1 / N投资组合和标准资产定价因素之外的重要alpha值。