Investment Management in the Age of Artificial Intelligence and Machine Learning – We do that!

By DeFred G Folts III via Iris.xyz

Artificial Intelligence and machine learning are everywhere. In the words of Tad Friend at The New Yorker magazine, “AI has grown so ubiquitous — owing to advances in chip design, processing power and big-data hosting that we rarely notice it.” Creating AI tools to solve problems goes back to the work of the mathematical genius Alan Turing in the 1940’s. Turing was the character featured in the movie “The Imitation Game,” in which he and fellow mathematicians attempt to break the Nazi’s Enigma code during World War II.   Today, there are many different flavors of AI including; ANI—artificial narrow intelligence, AGI—artificial general intelligence, and the current holy grail, AI–deep learning.

AI and machine learning are also hot topics in the investment management industry with constant references in the financial press to man vs. machine, human vs. digital, and how AI and machine learning are about to transform the way that we invest. There is little doubt that the investment industry will be transformed by this technology. However, at 3EDGE Asset Management, we believe that the argument over human vs. machine is a false choice, and that the best way forward is human plus machine. We view the relationship between human and machine intelligence as one of cooperation rather than competition.

As the man in the TV commercial says, at 3EDGE, “we know a thing or two, because we’ve seen a thing or two,” about applying Artificial Intelligence and machine learning to investment management. In fact, it is in many ways foundational to our investment approach. However, we also believe that when applying AI and machine learning tools to investment management, it is critical to understand that these tools can be very good at certain tasks, while they may not be so good at others. In particular, AI and machine learning tools are quite good at analyzing massive amounts of data and detecting patterns. However, they are often not yet good at being able to differentiate between correlation and causation, and in investment management that can be particularly problematic.

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