The Catalyst for Machine Learning

In this episode I speak with Adam Butler, co-founder and CIO of ReSolve Asset Management.  For full disclosure, at the time of recording I am personally an investor in one of ReSolve’s private funds.

Adam last joined the show in Season 1, where we discussed his background and philosophy of diversification.  This episode begins with a discussion of how Adam’s thinking and process has evolved over the last four-plus years, much of which is centered around the idea of experimental design.  Adam discusses the adoption of machine learning techniques, the spectrum of complexity between zero- and strong-prior signals, and how proper experiment design allows for greater process diversification.

The back half of the conversation dances across a few subjects.  We discuss topics such as seasonality, carry, the operational burdens of introducing a full-stack machine learning process, and the difficulties allocators face in introducing multi-strategy alternatives into their portfolios.

I hope you enjoy this episode with Adam Butler.