In this episode of the Investor Insight Skull Session, Maj Soueidan sits down with Yuval Taylor of Fieldsong Investments, a quantitative investor who turned a late start in the markets into a remarkable second career.
Yuval shares how his path into investing began after 30 years in publishing, when a sabbatical in Bolivia left him with extra savings and a growing obsession with the markets. After losing money on the typical novice mistakes, he found his footing through algorithmic investing and ranking systems, eventually compounding at roughly 40% annually for a decade, retiring early, and launching his own hedge fund in 2024.
The conversation explores the mechanics of Yuval's process, including how he combines around 200 factors across value, growth, quality, and stability, why middling values can beat extreme ones, and how he screens for earnings manipulation using his revised version of the Beneish M-Score, a lesson learned the hard way after being burned by the Tingo fraud. Yuval also explains why he holds more money in Canadian stocks than U.S. ones, the overlooked opportunity in OTC and low-priced shares, and the "factor inversion" phenomenon punishing quality stocks in the U.S. market. Examples discussed include Conrad Industries, Power Solutions International, Hammond Power Solutions, D-BOX Technologies, and CareCloud.
The two also dig into hedging with put options, position sizing and turnover, the limits of AI in financial analysis, and whether qualitative judgment can ever truly be quantified. Beyond investing, Yuval opens up about his writing life, from his book on Zora Neale Hurston and Langston Hughes to his current project on Lindsey Buckingham and Stevie Nicks.
This episode offers a candid look at how a self-taught quant built a rigorous, repeatable process and the discipline required to stay systematic in volatile markets.
Disclaimer: This podcast is for informational purposes only and should not be considered financial or investment advice. All investments involve risk, and past performance is not indicative of future results.