Philps: Rothko has learned many things; most importantly how return opportunities can be exploited in international equity markets. We believe our performance speaks for itself on this. We have learned many things from Rothko too, such as the importance of the way a company treats its shareholders. This is important to Rothko’s stock selection, especially in Emerging Markets.

One piece of knowledge that particularly concerns us is the indirect impact of the multi trillion dollar shift into factor investing. On closer inspection we believe the factor trades of traditional quants have become dangerously crowded and this risks a repeat of 2007’s “quant quake”. It is important to understand that Rothko does not use factors (after Fama and French) or traditional quant tools.

Hortz: How can applying AI to the investment decision process potentially add high alpha or excess return relative to benchmarks?

Philps: A well-conceived AI approach can, we believe, exceed the limitations of both human driven stock selectors and traditional quants. Firstly, humans are hard wired to think in 3 dimensions, which means there is a cognitive speed limit when weighing up the many dimensions in which a company can succeed or fail. In contrast AI can consider many, many dimensions at the same time.

AI can also be designed to scale across vast and inefficient stock universes, aiming to extract bottom-up driven alpha. Traditional quants tend to drive returns using weightings to traditional factors, after Fama and French. These factors, such as Value, Growth, MinVol, Momentum, can be accessed inexpensively through ETFs these days. For us, AI is about fundamentals and bottom-up driven returns, alpha, which sets an AI approach apart from traditional quants. 

Hortz: How is your fund unique in its application of Artificial Intelligence (AI) to current standards of fundamentally driven value investing across non-U.S. equity markets?

Philps: Actually, our AI methodology has commonalities with a human-driven, active, fundamental approach. However, we believe we do not suffer from classic human behavioral pitfalls, subjective judgments, and inconsistent decision making. Additionally, Rothko’s AI can retain more information about the world to inform decisions. Our strategy can integrate a myriad of perspectives into each investment decision through different rules or models. Each one of these perspectives is used in our AI’s stock selection decisions.

Hortz: Some commentators, such as Research Affiliates, imply that AI is dangerous when applied to investing. Is there any truth in this?

Philps: We firmly believe that naively throwing machine learning — which is a more mechanical subset of AI — at an investment strategy is a recipe for disaster. Investment should always come before technology and, for us, an AI should be founded on investment rationales that a successful human stock selector would believe in.

There have certainly been more thought pieces from traditional quants about the dangers of investments driven by AI but this is notably correlated with the level of disruption AI threatens to old quant businesses and should, in our view, be taken with a large pinch of salt.