This Sponsored Insight features Daniel Mahr, Head of MDT, the $26 billion quantitative equity investing group at Federated Hermes that oversees a suite of actively managed mutual funds, ETFs, collective investment trusts, and separately managed accounts. Dan joined the firm in 2002 as a junior analyst and took over leadership of the team six years later, guiding its evolution through vast changes in data, computing power, and investment methodology. Our conversation traces Dan's path from flipping IPOs as a college student to running machine learning models across global equity markets. We discuss the development of MDT's decision tree framework — a "glass box" approach to stock selection that blends transparency with sophistication — and how the team balances analytical rigor with human judgment. Dan explains lessons from two decades of modeling markets, including the challenges of overfitting and underfitting data, and MDT's steadfast focus on analytical edge, rather than informational edge.
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Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com)
