Previous research has shown that equally weighted portfolios outperform optimized
portfolios, which suggests that optimization adds no value in the absence of
informed inputs. This article argues the opposite. With naive inputs, optimized
portfolios usually outperform equally weighted portfolios. The ostensible
superiority of the 1/N approach arises not from limitations in optimization but,
rather, from reliance on rolling short-term samples for estimating expected
returns. This approach often yields implausible expectations. By relying on
longer-term samples for estimating expected returns or even naively contrived
yet plausible assumptions, optimized portfolios outperform equally weighted
portfolios out of sample.