The Rational Reminder Podcast Podcast Por Benjamin Felix Cameron Passmore and Dan Bortolotti arte de portada

The Rational Reminder Podcast

The Rational Reminder Podcast

De: Benjamin Felix Cameron Passmore and Dan Bortolotti
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A weekly reality check on sensible investing and financial decision-making, from three Canadians. Hosted by Benjamin Felix, Cameron Passmore, and Dan Bortolotti, Portfolio Managers at PWL Capital.2025 copyright - PWL Capital, all rights reserved Economía Finanzas Personales
Episodios
  • Episode 405: Timothy Edwards - Inside S&P DJ Indices

    Episode 405: Timothy Edwards - Inside S&P DJ Indices
    Apr 16 2026
    What if the decades-long debate between active and passive investing wasn't really a debate—but a data problem? In this episode, Ben Felix and Cameron Passmore are joined by Tim Edwards, Managing Director and Global Head of Index Investment Strategy at S&P Dow Jones Indices, for a deep dive into the SPIVA Scorecard—the industry's most enduring and data-driven comparison of active versus passive investing. Tim explains how SPIVA has evolved over 25 years, why survivorship bias matters more than most investors realize, and what the data consistently shows across markets: most active funds underperform their benchmarks—especially over longer time horizons. The conversation goes beyond the headline results, exploring persistence (or lack thereof) in manager performance, why bond funds don't escape the same fate, and whether combining active funds improves outcomes (spoiler: not really). They also tackle common critiques of indexing, including index rebalancing costs, IPO inclusion concerns, and the role of index funds in market concentration. Key Points From This Episode: (0:00:17) Introduction to the SPIVA report and its long-standing role in the indexing vs. active debate (0:01:18) Overview of the episode: SPIVA, index behavior, IPOs, and market concentration (0:03:30) What SPIVA is and how it measures active fund performance versus benchmarks (0:04:14) Why SPIVA was created: to inform—not settle—the active vs. passive debate (0:05:20) How SPIVA has evolved across regions, asset classes, and research dimensions (0:06:59) Controlling for survivorship bias and why it materially affects results (0:08:57) Real-world survivorship rates: ~50–60% of funds survive over 10 years (0:10:12) Core finding: most active funds underperform, especially over longer horizons (0:10:57) Comparison of equity vs. bond funds: slightly better outcomes in bonds, but still mostly underperformance (0:13:44) Structural differences in equity vs. bond markets (e.g., skewness, dispersion) (0:15:06) Typical survivorship rates across markets and how crises affect fund closures (0:16:02) Persistence analysis: past winners rarely remain winners (0:18:16) Global variation: some markets (e.g., international small caps) show slightly better active results (0:20:41) "Better" doesn't mean good: even in stronger categories, most funds still underperform (0:21:31) Do active funds perform better in down markets? Not consistently (0:23:37) Multi-asset portfolios of active funds: 97% underperform over 10 years (0:25:10) Selecting top-quartile funds improves outcomes slightly—but not meaningfully (0:26:46) Surprising findings in SPIVA and how market dynamics shape results (0:27:45) Impact of SPIVA on industry behavior and investor education (0:29:03) Ben shares how SPIVA influenced his own career path toward indexing (0:30:08) The "index effect" and whether index rebalancing creates performance drag (0:31:30) Why the index effect has largely diminished due to market competition and liquidity (0:34:05) Research on IPO inclusion and whether index rules create systematic return drag (0:36:57) How S&P handles IPO inclusion (e.g., 12-month seasoning rule for S&P 500) (0:39:58) Whether index methodology could evolve due to larger modern IPOs (0:42:36) Addressing concerns about large IPOs entering index funds (0:43:52) Historical perspective on market concentration and today's top-heavy indices (0:45:29) What happened to past top-10 companies: many declined, but markets still thrived (0:47:10) Creative destruction: why markets can succeed even when leaders fail (0:49:15) Weak relationship between market concentration and future returns (0:50:55) None of today's top companies were top companies in the 1960s (0:52:16) Key takeaway: markets evolve, and cap-weighted indices adapt automatically (0:53:58) Concerns about index fund growth and its impact on market function (0:54:30) Benefits of indexing: lower fees and often better investor outcomes (0:56:15) Timing the market: why waiting for a bigger drop tends to hurt returns (0:58:52) "Time in the market" vs. "timing the market" (0:59:09) Tim's favorite index: the DSPX dispersion index (1:00:53) Defining success: why happiness is the ultimate metric Links: 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)
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  • Episode 404: The Finance Paper that Changed Everything

    Episode 404: The Finance Paper that Changed Everything
    Apr 9 2026
    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 ...
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  • Episode 403: Patrick Adams - When Stock Crashes Matter for Long-Term Investors

    Episode 403: Patrick Adams - When Stock Crashes Matter for Long-Term Investors
    Apr 2 2026
    What if your biggest investment risk isn't the stock market—but your own income? In this episode, we are joined by Patrick Adams, a PhD candidate at MIT, for a fascinating deep dive into how income risk, spending commitments, and liquidity constraints reshape what "optimal" investing actually looks like. Drawing on large-scale administrative tax data, Patrick challenges the conventional wisdom that young investors should be heavily—or even fully—invested in equities. We explore why stocks appear safe over long horizons but become risky when real-world constraints force investors to sell at the worst possible times. Patrick explains how high-income households behave during market downturns, why their income risk is closely tied to stock market performance, and how consumption commitments like mortgages and childcare create hidden financial leverage. The conversation also introduces a new life-cycle model that incorporates these frictions—leading to surprisingly conservative optimal equity allocations for working-age investors. This episode reframes asset allocation as a problem of liquidity and risk management, not just return maximization. Key Points From This Episode: (0:00:00) Introduction to the podcast and overview of the episode's focus on asset allocation and new research. (0:01:18) Patrick Adams' background, MIT PhD research, and how the paper was discovered. (0:07:08) Why stocks are considered safe for long-term investors based on historical returns. (0:08:37) When the "stocks for the long run" logic breaks down—forced selling during downturns. (0:10:35) Evidence: High-income households sell stocks during crashes instead of buying. (0:12:24) Data source: Administrative U.S. tax return data and its advantages/limitations. (0:14:23) Investors shift into fixed income during crashes rather than staying invested. (0:16:52) Financial reality: High wealth, but low liquid assets relative to income. (0:18:00) Human capital: Income is risky and correlated with stock market downturns. (0:20:15) Typical allocation: About 25% of liquid wealth in stocks for working-age households. (0:22:36) Higher-income households have more volatile flows and greater exposure to stock risk. (0:23:42) Income shocks drive stock selling—not just panic or behavioral mistakes. (0:25:29) Why households draw down assets instead of cutting spending sharply. (0:27:26) Consumption commitments (mortgages, childcare) act like hidden leverage. (0:27:57) Key risk factors: Income volatility, low liquidity, and inflexible expenses. (0:31:31) Traditional models vs reality: People don't cut spending—they use savings. (0:35:25) New model incorporates income risk, market crashes, and spending frictions. (0:38:33) Core finding: Optimal equity allocation for working-age investors is only 10–40%. (0:40:55) Practical takeaway: Asset allocation is fundamentally about emergency funds. (0:42:35) Higher fixed expenses require larger safe asset buffers. (0:43:49) Counterintuitive result: Retirees may optimally hold more equities than workers. (0:46:56) Scenario analysis: Selling during downturns destroys long-term returns. (0:49:12) Key drivers of results: Income-stock correlation and spending rigidity. (0:51:11) Why this model differs from others suggesting 100% equity portfolios. (0:53:20) When 100% equity could make sense: low risk, high wealth, high risk tolerance. (0:56:28) Personal impact: Patrick rethinks his own savings, risk, and spending commitments. (0:57:34) Advice for listeners: Focus on liquidity, income risk, and fixed expenses. (0:59:58) Defining success: Impactful research, teaching, and meaningful personal relationships. 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)
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