Building Diversified Portfolios that Outperform Out of Sample

What it asks

López de Prado traces the instability to a single step: inverting the covariance matrix. His method skips that step entirely. It places the assets into a tree by similarity and distributes risk down that tree from the top. The resulting portfolio is not theoretically optimal, but it holds up better out of sample.