Show Notes
What if the way we think about investing—and expected returns—was fundamentally incomplete? In this episode, Ben Felix and Dan Bortolotti take a deep dive into one of the most influential papers in financial economics: Fama and French (1993). With nearly 15,000 citations, this research reshaped how we understand asset pricing by showing that market beta alone isn't enough to explain returns. Instead, multiple factors—specifically size and value—play a critical role. Ben and Dan unpack how this paper challenged the dominance of CAPM, introduced the now-famous Three-Factor Model, and laid the foundation for decades of empirical asset pricing research. They explore how factor investing evolved, why anomalies may not be anomalies at all, and what this means for evaluating portfolios and active managers today. The conversation also connects theory to practice—highlighting how modern fund providers implement factor strategies and what it means for investors trying to improve expected returns without abandoning diversification.
Key Points From This Episode: (0:00:00) Introduction to the episode and why this is a long-awaited deep dive into factor investing. (0:01:12) Overview of Fama and French (1993) and its massive impact on finance and portfolio management. (0:03:55) Origins of factor investing and how it connects to index investing and academic research. (0:04:46) Core premise: multiple factors drive expected returns and asset prices. (0:06:08) He explains why different assets can have different expected returns, and why that matters for investors. (0:07:24) Ben introduces the CAPM as the dominant model that linked expected return to market beta. (0:08:53) Dan reflects on how revolutionary CAPM and portfolio theory were when they were first introduced. (0:10:51) Ben describes today as a "golden age of investing," where theory and implementation tools are widely accessible. (0:11:17) He explains how anomalies emerged that CAPM could not explain. (0:12:10) Ben introduces the joint hypothesis problem: we cannot cleanly separate market efficiency from model accuracy. (0:13:47) He identifies the three big issues with CAPM: size, value, and the weak relationship between beta and returns. (0:15:29) Ben introduces the three-factor model: market, size (SMB), and value (HML). (0:17:37) He explains that these factors are built as long-short portfolios designed to capture systematic return variation. (0:18:02) Dan notes that the model did not really address the low-volatility anomaly. (0:18:36) Ben agrees and explains that later work, including the five-factor model, went further on that front. (0:19:03) Ben describes how Fama and French formed 25 portfolios sorted by size and book-to-market. (0:20:00) He explains their use of time-series regression to test how well the model explained portfolio returns. (0:21:12) Ben walks through factor loadings, alpha, and R-squared, and why those outputs matter. (0:23:31) He highlights the model's strong explanatory power, with average R-squared around 0.93 across test portfolios. (0:25:00) Dan clarifies that unexplained return could reflect skill, luck, or another missing factor. (0:25:27) Ben emphasizes how dramatic the jump was from CAPM's explanatory power to the three-factor model's. (0:26:11) He points to small-cap growth as the major area the model struggled to explain. (0:27:09) Ben explains how the model also absorbed dividend-to-price and earnings-to-price "anomalies." (0:28:01) Dan discusses why dividend strategies may simply act as rough value screens rather than offering something unique. (0:28:52) Ben expands on how later research, especially profitability, sharpened value investing implementation. (0:30:37) He notes the unresolved debate over whether factors are true risk exposures or persistent mispricing. (0:32:16) Ben explains how factor models changed the way investors evaluate active managers and fees. (0:33:16) Dan raises the possibility that some ear
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