Hortz: How exactly can AI avoid, as you have mentioned, the shortcomings of factor models?
Philps: Rothko’s AI investment strategy is very different from traditional quant investors that almost universally rely on ‘factors’ as mentioned. The vast majority of traditional quants generally seek to forecast expected returns or tilt exposures towards factors. We believe factor models offer shallow insights, viewing the world through a simplified, linear-constrained lens. We also note that some traditional quants are blurring the lines between their traditional approaches and AI by employing datamining, such as news sentiment scoring. We do not believe in this approach and think it amounts to window dressing.
Again, factor strategies have also witnessed significant growth where we see indications of crowded factor trades. Investors are potentially exposed should there be a reversal factor sentiment. A Quant Quake 2 perhaps? Rothko’s AI maintains a low correlation to factors and a relatively high active share to style-factor indices, drawing similarities to a good, active fundamental approach.
We think an AI successfully applied to investing combines the most appropriate aspects of data-driven modeling techniques with guiding human-like rationales.
Hortz: How do you keep developing your AI technology and its applications? Where is your R&D pointing to next?
Philps: Our research continues to search for deeper inferences, guided by the fundamental rationales of value and income. There are a number of threads to this and one we can discuss is our interest in the cutting edge AI research area called Continual Learning. This is where machines accumulate knowledge over time and then learn how to apply that knowledge to make better decisions in the future. I was invited to present some of our research to the world’s leading AI research conference in December 2018 (NeurIPS).
Hortz: Can you provide some recommendations and share your experience to advisors on how to look at and apply AI in portfolio management and how best to use it in their client portfolios?
Philps: Whether RIAs are applying AI or selecting an AI tool or manager, they need to have two words at the forefront of their minds: expectations and interpretability. These are the two watch words for reviewing an AI approach in our view. Investors should have crystal clear expectations of an AI. In Rothko’s case investors can generally expect value attributes, defensiveness and a material proportion of returns coming from the dividend component.
Interpretability is critical too. An AI approach should be human readable, not a black box. In Rothko’s case every stock we hold we can talk to in terms of that stock’s fundamentals, valuations, levels of shareholder value and more. Equally we can tell you why Rothko does not hold a particular stock in the same terms.
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