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 early active managers may have intuitively identified factor opportunities before the research formalized them.

(0:34:09) Ben discusses whether factor premiums have shrunk after publication and why the evidence is still noisy.

(0:34:59) He describes how the paper helped launch the boom in empirical asset pricing research.

(0:35:35) Ben introduces the "factor zoo" problem and the explosion of published factors.

(0:36:49) He explains the five-factor model and the addition of profitability and investment.

(0:38:21) Dan asks about the intuition behind profitability and investment, especially why profitable firms might have higher expected returns.

(0:39:38) Ben explains profitability through a multi-factor lens and inferred discount rates.

(0:42:15) He argues that combining factors matters because single-factor portfolios can have offsetting exposures.

(0:44:05) Dan points out that layering too many factors naively can just bring you back toward the market portfolio.

(0:44:56) Ben discusses the tradeoff between diversified tilts and concentrated factor bets.

(0:46:29) Dan describes factor tilting as a subtle adjustment around a diversified core portfolio.

(0:46:47) Ben cites Fama's idea that investors need to "talk themselves out of the market portfolio."

(0:47:16) He notes that there is still active debate over which factors and models truly make sense.

(0:48:31) Dan explains why momentum is harder to implement in practice because of turnover, taxes, and trading costs.

(0:49:23) Ben says even simple-sounding factors like value and profitability remain heavily debated in academia.

(0:50:20) He brings the discussion back to practical relevance: how investors can access factor exposure through funds.

(0:51:06) Ben explains Dimensional's roots in academic research and its long history of implementation.

(0:52:48) He introduces Avantis as a newer competitor with similar academic foundations and newly launched Canadian ETFs.

(0:53:42) Ben discloses that PWL uses Dimensional extensively, while noting they are not paid to mention Dimensional or Avantis.

(0:54:09) He summarizes what factor investing means for investors seeking higher expected returns through systematic tilts.

(0:55:47) Dan reflects on how early PWL's adoption of index and factor-based investing was in the Canadian market.

(0:57:07) Ben invites listeners to learn more about how PWL applies this thinking in client portfolios.

(0:57:41) The episode moves to the after show and review section.

(0:58:21) Dan reads a listener review focused on evidence-based investing, planning, and disciplined saving.

(1:00:23) Ben notes that they never actually named the paper during the main episode.

(1:00:32) Dan closes with: the paper is Common Risk Factors in the Returns on Stocks and Bonds.

Links: Patrick Adams – MIT PhD Candidate: https://patrick-adams.com/

Meet with PWL Capital: https://calendly.com/d/3vm-t2j-h3p

Rational Reminder on iTunes — https://itunes.apple.com/ca/podcast/the-rational-reminder-podcast/id1426530582. Rational Reminder on Instagram — https://www.instagram.com/rationalreminder/

Rational Reminder on YouTube — https://www.youtube.com/channel/ Benjamin Felix — https://pwlcapital.com/our-team/

Benjamin on X — https://x.com/benjaminwfelix

Benjamin on LinkedIn — https://www.linkedin.com/in/benjaminwfelix/

Cameron Passmore — https://pwlcapital.com/our-team/

Cameron on X — https://x.com/CameronPassmore

Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com)