SO WHAT? WHY ML?

ML is already a part of sophisticated quants’ investing toolkit. It offers valuable modeling flexibility and has application throughout the investment process. We view the integration of ML into investing as an evolution rather than a revolution. The techniques aren’t qualitatively distinct from traditional methods, and we expect that the quantitative investment process will remain recognizable in the foreseeable future, even as the research tools that inform its components evolve. Markets make for an especially challenging environment in which to apply ML, and beneficial ML-based research calls for process discipline and finance domain knowledge. For asset owners, more flexible but more opaque analytical tools will exacerbate challenges in distinguishing strategies that add value from data artifact. Working knowledge of ML approaches and ML research best practices offer a valuable defense.