How Best Investors Blend Fundamental and Quantitative Approaches

Quant

95% of quants on the Wall Street still mostly toil in the areas of process automation, reporting, portfolio construction and risk management. Very, very few quants work on the forward-looking investment ideas.

That is understandable – truly blending fundamental and quant inputs is extraordinary hard. Yet, as Paul Tudor Jones said, that “No man is better than a machine (computer), and no machine is better than a man with a machine“.

Fidelity provides a shining example of that emerging trend. For starters, they take Data seriously: Fidelity spends $2.5B on technology annually, employing over 12,000 developers, including dozens of AI scientists. According to Ram Subramaniam, Fidelity President, “Fidelity likes to think of themselves as a technology company that happens to be in financial services”.

More importantly, in applying the brute force of computers and Data, Fidelity goes way beyond traditional domains of automation or reporting. At Fidelity, Portfolio Managers systematically seek to enhance their investment process with data-driven approaches. Many PMs there are paired with quants, who seek to sharpen their performance with Data Tools. Jeff Feingold, who runs their historically flagship Magellan fund, works closely with his wingman – Kwazi Dadzie-Yeboah. It is a powerful combination! Jeff cuts his teeth in doing traditional fundamental research, looking at companies and their strategies individually, while Kwazi helps him to identify stocks with better odds of outperforming. When the fundamentals and quant signals align, the pair gets an additional boost of confidence to enter their positions. They know all too well, that there is a big difference between a good company and a good stock, and timing matters, even for long-term investors.

The pair resembles a Top Gun setup from the famous movie with Tom Cruise and Val Kilmer

Do you know any other successful examples of blending Fundamental and Quant approaches?

 

How Best Investors Blend Fundamental and Quantitative Approaches

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