The Quantitative Richter Scale | 2026 Multi-Factor Modeling with Steve Cress episode artwork

EPISODE · Jul 24, 2026 · 44 MIN

The Quantitative Richter Scale | 2026 Multi-Factor Modeling with Steve Cress

from Market Misbehavior with David Keller, CMT · host Dave Keller, CMT

In this episode of the Market Misbehavior podcast, Dave is joined by Steve Cress, Head of Quantitative Research at Seeking Alpha. Recorded July 21st 2026.Steve explains how quantitative methodologies eliminate emotional bias and act as an early-warning "Richter scale" for broader market corrections. We dig into why momentum remains the single strongest historical predictive factor, how his team's disciplined multi-factor model has consistently outperformed dynamic hedge funds like Bridgewater, and the staggering data behind buying top-tier "Strong Buy" stocks during a 15% market drawdown. The conversation also explores the launch of the new Quant Growth and Income product, how macro shifts like interest rates naturally bake themselves into consensus EPS revisions, and why generative AI still hasn't managed to beat a purely data-driven, bottom-up quant approach at stock picking.If you enjoyed our episode today, please make sure to check out our Market Misbehaviour collaboration with Seeking Alpha! These links will give you a unique bonus off just for being a podcast viewer.  Seeking Alpha Premium: https://marketmisbehavior.com/seekingalphaAlpha Picks: https://marketmisbehavior.com/alphapicks📈 Topics Covered• How quantitative models act as an early-warning "Richter scale" for sector rotations and market corrections• The historical data on buying the dip: Why buying top quant stocks during a 15% market drawdown creates generational wealth• Breaking down Seeking Alpha's five-factor model: Value, Growth, Profitability, EPS Revisions, and Momentum• Why momentum consistently ranks as the most powerful predictive market factor over the last 250 years• The danger of dynamic factor weighting: Why disciplined, static models often outperform complex hedge fund algorithms• How macro shifts (like rising interest rates or oil prices) are naturally priced into the model via consensus analyst EPS revisions• Assessing AI valuations on a stock-by-stock basis: Why names like Micron and SanDisk outranked Nvidia in the value grade• Launching the "Quant Growth and Income" model to capture non-tech sector rotations (like Financials)• The behavioral advantage of quant investing: Eliminating narrative bias, CEO sales pitches, and emotional panic selling• The intersection of generative AI and quantitative finance (and why AI hasn't beaten the models yet)🎓 Take Dave’s FREE course on behavioral investing: https://www.marketmisbehavior.com/freecourse📘 Check out Dave’s recommended reading list: https://www.marketmisbehavior.com/readinglist👉  Follow Dave on X: https://x.com/DKellerCMT👉  Follow Dave on Bluesky: https://bsky.app/profile/dkellercmt.bsky.social👉  Follow Dave on Facebook: https://www.facebook.com/marketmisbehavior👉  Follow Dave on Instagram: https://www.instagram.com/marketmisbehaviorThe content in this presentation should not be considered as a recommendation to buy or sell any security. All information is intended for educational purposes only and in no way should be considered as investment advice. 

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In this episode of the Market Misbehavior podcast, Dave is joined by Steve Cress, Head of Quantitative Research at Seeking Alpha. Recorded July 21st 2026. Steve explains how quantitative methodologies eliminate emotional bias and act as an early-warning "Richter scale" for broader market corrections. We dig into why momentum remains the single strongest historical predictive factor, how his team's disciplined multi-factor model has consistently outperformed dynamic hedge funds like Bridgewat...

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The Quantitative Richter Scale | 2026 Multi-Factor Modeling with Steve Cress

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