Podcast Summary: Grant’s Current Yield – “Growth and Profitability”

Date: November 20, 2024
Host: Jim Grant
Guests: Evan Lorenz (Deputy Editor), Dev Katasaria (Valley Forge Capital Fund)

Episode Overview

In this episode, Jim Grant and Evan Lorenz welcome Dev Katasaria, founder of Valley Forge Capital Fund. With wit and a conversational blend of finance and history, the discussion explores Dev's unconventional career path, his philosophy of concentrated investing in public equities, perspectives on market efficiency, the impact of artificial intelligence on investing and society, and the enduring lessons (and risks) in equity markets. The overarching theme is the search for exceptional businesses that balance growth and predictability, even as technological and social changes loom.

Key Discussion Points & Insights

1. Dev Katasaria’s Background and Investment Philosophy

• Unconventional Path: MIT graduate, Harvard Medical School, but ventured into finance instead of medicine.
  • "My mom still wishes she could go to parties and say, you know, her son’s a cardiothoracic surgeon." (02:00, Dev)
• Valley Forge Capital:
  • Runs a highly concentrated, low-turnover portfolio: typically 8–12 positions, rarely more than 20.
  • Daily work is reading, research, and industry study.
  • "I think about it as Buffett's punch card. You have to make 20 decisions in a lifetime. If you find the right opportunity, make sure it counts." (02:35, Dev)

Investing Discipline

• Focus on “finding the perfect intersection between growth and predictability.”
• Extensive use of historical context to judge company durability—not just current metrics.
• “We need to get to the essence of the business. What will matter for earnings power 10+ years out from now.” (04:18, Dev)

2. Market Efficiency & Finding Edge

• Grant probes Dev on the "strong form efficient markets hypothesis" (03:26).
• Dev agrees that markets are mostly efficient, so their edge comes from rare instances of mispricing or neglect.
  • “Our job is to find a few instances... where there is a disconnect. And our job is to predict the future… interpret [data] better than others.” (03:32, Dev)
• 2/3 of investments are due to “market neglect” rather than crisis or bad headlines.

3. Public Markets vs. Private Markets

Why Public Equity Over Venture Capital?

• Dev spent 18 years in VC; made significant returns, but disliked the lack of reliability and transparency.
• Prefers public equities for their liquidity, meritocracy, and transparency.
  • “I love the fairness of that game. There's a more direct correlation between making good decisions... and outcomes.” (09:19, Dev)
  • “If you do it right, you can have the returns of a private fund, but with all the advantages of... daily liquidity.” (09:19, Dev)

Skepticism of Private Equity's Popularity

• University endowments overexposed to private equity for volatility management, not return maximization.
  • “What private funds… do for endowments is that many of the problems… can be hidden for long periods because there’s no daily pricing.” (11:23, Dev)
  • “Any great portfolio’s foundation has to start with a public equity... and then the other stuff should be window dressing.” (12:29, Dev)

4. Current Portfolio Construction & The "Fishing Pond"

• About 40–50 companies make the quality cut; from thousands screened.
• Looks for dominant franchises with durable moats and pricing power.

Case Study: ASML vs TSMC

• Owns ASML, not TSMC, despite TSMC’s apparent monopoly in chipmaking.
  • “ASML is a monopoly [in] machines about the size of a school bus. Arguably they're 10 to 15 years ahead [technologically]… all the growth in AI… has to flow through ASML.” (07:42, Dev)
  • TSMC’s edge is scale (less durable); ASML’s is technology and industry structure.

5. AI: Transformative & Disruptive Forces

Investment Implications

• Sees AI as both an investment opportunity and a societal threat.
• Predicts rapid commoditization of AI, making it widely available and affordable.
  • “In a few years an off the shelf AI program will… handle 95% of the human tasks that we have today.” (16:21, Dev)
• Cautions that identifying lasting winners in AI is difficult.

Societal Consequences

• “Nothing in human history that… we've experienced like AI. It will put significant numbers of people out of work.” (16:21, Dev)
• Foresees profound changes in the labor market and society—unclear how to absorb mass unemployment.
  • “I don't really know how society will react when you have tens of millions of people sitting at home with nothing to do.” (30:35, Dev)

6. Defense of Key Holdings in Light of AI

Payment Networks (Visa & Mastercard)

• Recognizes consumer volume risk from unemployment/recession.
• Holds that pricing power and secular shifts from cash to electronic payments outweigh these risks.
  • “The best way as an equity investor to protect against risks like inflation or even deflation is to own companies with pricing power.” (17:56, Dev)

Bond Ratings (Moody’s & S&P Global)

• AI may enhance margins by reducing human labor, but network effects protect their oligopoly status.
  • “If we created our own ratings agency today... we still could not undercut Moody's and S&P because... it's viewed as a lower quality offering.” (21:20, Dev)
  • “I don't see any displacement of things like FICO scores, Moody's ratings simply because there's an AI model that says it can calculate... better.” (21:20, Dev)

Memorable Moment:

• Recounted buying S&P Global and Moody’s stock at generational lows during his honeymoon (early 2009)—a definitive moment in his investing career.
  • “I remember sitting in the lobby... in Mexico... it was early 2009, and futures were down, and I was able to buy S&P Global for $17.50.” (24:18, Dev)

7. Assessment of Today’s Market & Opportunities

• Market volatility is up; sees some opportunity but urges caution regarding forward P/E multiples.
  • “If you simply open up your Bloomberg... and start looking at forward multiples... you're really making a lot of mistakes because those forward multiples don't often represent reality.” (26:00, Dev)
• Highlights FICO’s price increases as unaccounted for in consensus forecasts.

On Big Tech

• Avoids major tech names (Meta, Google, Amazon)—historically concerned by capital allocation, dual-class shares, unpredictability, and the high R&D/AI spend.
  • “When Google announces a stock buyback... the stock goes up 10% in aftermarket... always been concerns about the companies using that money rationally...” (28:34, Dev)
  • “If you believe... that AI will be largely commoditized, you know, who's the winner? Who's monetizing, you know, all of those AI investments?” (28:34, Dev)

8. Fees, Humans vs AI, and the Future of Investment Management

• On traditional hedge fund fees (1%/2%): in a world where AI matches or beats average managers, only a “handful” of humans add value.
  • “Most of what exists today in public markets is random noise. Will AI outperform or at least equal... the vast majority of public equity managers today? Absolutely.” (19:25, Dev)
• Still sees a role for top human judgment—at least until AI becomes truly superhuman.
  • “Information is generic and ubiquitous. Judgment is scarce, precious and highly compensated.” (20:03, Jim Grant)
  • “We'll be one of the last to fall.” (20:28, Dev)

Notable Quotes & Memorable Moments

• On keeping an academic mindset in investing:
  "We are students of business of all types... I'm a lover of all business models and what we do..." (02:37, Dev)

• On the durability of network effects:
  "There is a value to those ratings that goes far beyond [accuracy]." (22:51, Dev)

• On risks of extrapolating current market conditions:
  "If you had been born a few generations earlier, you would have assumed that downward and to the right was the default investment position." (14:40, Jim Grant)

• On the future role of AI in investment management:
  "Absolutely [AI will outperform the vast majority of managers]." (19:37, Dev)

• Memorable stock purchase:
  “I remember sitting at my mother's desk... when I bought Moody's at $16.50. Both of those stocks today are around $500.” (24:49, Dev)

• On AI’s impact on society:
  "There’s nothing in human history that... we’ve experienced like AI. It will put significant numbers of people out of work." (16:21, Dev)

Timestamps for Major Segments

• [00:00] – Introduction and Dev’s unusual career path
• [02:35] – Investment philosophy: “Few big decisions; focus on enduring businesses”
• [03:26] – Thoughts on market efficiency and “edge”
• [06:00] – Aiming for (“fishing pond”) 40-50 great global businesses
• [07:42] – Case study: ASML vs TSMC
• [09:19] – Why Dev left venture for public equities
• [11:23] – Skepticism over private equity's popularity (esp. with endowments)
• [13:08] – On holding cash vs being fully invested
• [14:40] – Risks of projecting recent history into the future
• [16:14] – Dev’s views on AI’s rapid commoditization and societal effects
• [17:56] – Payment rails (Visa/Mastercard) and pricing power amid AI-driven unemployment
• [19:25] – Can humans outperform AI in investing?
• [21:20] – Franchise durability: Moody’s, S&P, and the limits of AI disruption
• [24:18] – Memorable stock purchases during 2009 market lows
• [26:00] – Market valuation, forward multiples, FICO example
• [28:34] – On Big Tech’s capital allocation and the lack of predictability
• [30:08] – Dystopian questions: AI, mass unemployment, and capitalism’s future
• [31:21] – Closing

Tone and Takeaways

The episode blends measured skepticism, historical reflection, and forward-looking concern as the guests probe the durability of great companies, the nature of market efficiency, and the profound potential challenges posed by AI. While Dev champions disciplined, research-intensive investing in dominant franchises, he candidly acknowledges how rapid technological change (especially AI) may fatally upend current investing frameworks and even wider elements of society.

For listeners:
This episode offers insight-rich perspective for those interested in long-term investing fundamentals, the allure and pitfalls of public vs private markets, the meaning of business “quality,” and a thoughtful, sometimes sobering, meditation on technology’s role in finance and society.