Value investing has produced some of the greatest investors of all time. Whether it be Benjamin Graham's deep value approach or Warren Buffett's quality at a reasonable price strategy, value has a long track record of success. But what if the great value investors of the future won't be human at all? What if machines can be trained to identify the best value stocks?

In this episode, we talk to John Alberg of Euclidean Technologies about applying machine learning to the process of selecting value stocks. We talk about the different types of machine learning and how these techniques can be utilized to select fundamentally sound stocks, We also discuss using machine learning techniques to avoid value traps, whether intuitive factors are more successful, areas where humans can still perform better than machines and much more.

We hope you enjoy the discussion.

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Excess Returns is an investing podcast hosted by Jack Forehand (@practicalquant) and Justin Carbonneau (@jjcarbonneau), partners at Validea. Justin and Jack discuss a wide range of investing topics including factor investing, value investing, momentum investing, multi-factor investing, trend following, market valuation and more with the goal of helping those who watch and listen become better long term investors.

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Applying Machine Learning to Value Investing with Euclidean’s John Alberg

Excess Returns