
An investor explains how organizing market data like a medical taxonomy reveals cheap, profitable stocks others miss. His Core Earnings Leaders Index returned 27% last year versus the S&P 500's 18%, showing the approach works.
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You need to be able to focus on a slice of the world where you can be sure that the data's reliable and that it's actually organized in the right way too. That's why I like the medical student example. You know, to train someone to be a doctor, there's a whole bunch of material that has been organized into taxonomies, like different types of diseases, different body parts, and then put into an ontology, which is to heal. What are the steps to heal? Yes. So we've organized financial data into a lot of different categories. And then we put it into an ontology that's focused on how to generate alpha. And that's really also related to how to find the stocks that are the most profitable and the cheapest. And we can do that in a way that adds incremental value because the market is looking at so much wrong stuff that our stuff is different enough to generate significant alpha. For example, the Core Earnings Leaders Index was up 27% last year while the S&P was just up 18%. So our earnings numbers are good enough to make a difference. Right.
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