Excess Returns

Wes Gray joins us to explain how factor investors should think about high market valuations, S&P 500 concentration, value investing, small caps, artificial intelligence and the behavioral challenge of staying invested for the long term. He also breaks down Section 351 ETF exchanges, including how appreciated portfolios can move into an ETF without an immediate taxable sale, why direct-indexing portfolios are a major use case and how the ETF wrapper is reshaping asset management.
Wes Gray on X
https://x.com/alphaarchitect
Alpha Architect
https://alphaarchitect.com
ETF Architect
https://etfarchitect.com
Long-Only Value Investing: Does Size Matter?
https://alphaarchitect.com/wp-content/uploads/2022/11/AA-JBISFactorInvesting22LongOnlyValueInvesting.pdf
Even God Would Get Fired as an Active Investor
https://alphaarchitect.com/wp-content/uploads/2021/08/Even_God_Would_Get_Fired_as_an_Active_Investor.pdf
Topics covered
Why high valuations may lower long-term expected returns without providing a reliable market-timing signal

How S&P 500 concentration creates a major large-cap, quality and growth factor bet

Why earnings and operating income may be better value metrics than book-to-market in an intangible economy

Why valuation may matter more than company size for long-only value investors

How unprofitable companies and low-quality stocks can distort small-cap value indexes

Whether AI has changed the historical relationship between growth and value investing

How AI may eliminate short-term trading edges while leaving long-horizon opportunities intact

Why even an investor with perfect foresight could suffer severe drawdowns and get fired

How passive investing flows may affect market prices and factor returns

How Section 351 exchanges can solve problems created by appreciated SMAs, tax-loss harvesting and direct indexing

The 25/50 diversification rules, cost-basis transfer and tax-deferral mechanics of ETF conversions

Why assets continue moving from mutual funds, hedge funds and separate accounts into ETFs

Why enduring underperformance may be necessary to earn higher long-term returns

Timestamps
00:00 Alpha Architect, ETF Architect and building an ETF platform
04:00 Can factor investors time a market bubble?
08:03 Intangible assets and the problems with book-to-market
13:42 The quality problem inside small-cap value indexes
18:18 Has technology changed the growth-versus-value equation?
23:25 Can AI create lasting investment alpha?
27:42 Are investors behaving better today?
34:39 How Section 351 ETF exchanges work
39:48 The diversification rules for tax-deferred ETF conversions
44:34 How cost basis and deferred taxes carry into the ETF
49:07 Mutual fund, hedge fund and SMA conversions
54:13 Why investors should embrace underperformance
Learn more about the Excess Returns podcast network:
https://excessreturns.co
No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.

Aahan Menon, founder of Prometheus Research, joins Jack Forehand to explain what systematic macro data says about economic growth, inflation, Federal Reserve policy, oil prices, AI investment and the outlook for stocks and bonds. They examine why nominal GDP remains stable, why traditional recession indicators have failed, how consumer dissaving is boosting corporate profits, and why today's unusually balanced regime probabilities make this a difficult time for large macro bets.
Aahan Menon on X
https://x.com/AahanPrometheus
Prometheus Research
https://www.prometheus-macro.com
Topics covered
Why geopolitical volatility and disrupted market trends make concentrated macro bets unusually difficult

What Prometheus Research's daily GDP nowcast says about stable nominal growth

Why AI capital spending matters but consumer spending still drives the US economy

How household dissaving and the wealth effect are supporting corporate profits

Why the economy and Federal Reserve policy may be increasingly sensitive to stock prices

How oil prices are driving inflation volatility and changing expectations for interest rates

Why demand-driven inflation is more persistent than supply-driven inflation

How technology investment has weakened traditional recession and business-cycle indicators

The value and limitations of timing Federal Reserve policy with systematic macro data

What macro regime probabilities, valuations and expected returns suggest for stocks, bonds and diversification

Timestamps
00:02 Why this is a difficult time for big macro bets
05:02 A daily GDP nowcast shows stable nominal growth
09:21 Consumer dissaving and the future economic risk
13:23 The wealth effect linking stocks, spending and profits
17:52 Oil prices and extreme inflation volatility
22:23 Separating persistent demand inflation from supply shocks
27:27 Why traditional recession indicators stopped working
32:55 How technology is changing the business cycle
37:42 Why timing Federal Reserve cycles matters for bond returns
42:28 The limitations of alternative data and short histories
47:33 Macro regime forecasts and expected returns
51:54 Why the macro backdrop still supports equities
56:19 Why investors can finally get paid to diversify
Learn more about the Excess Returns podcast network:
https://excessreturns.co
No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.

Azeem Azhar joins Kai Wu to break down the real economics of the AI boom, including the $110 billion demand base, where profits may accrue across chips, hosting, foundation models and applications, and whether spending can translate into enterprise productivity. They discuss AI infrastructure bottlenecks, open-source competition, vertical integration, organizational redesign, software moats, human judgment and the signals investors can use to identify companies turning AI adoption into durable competitive advantage.
The State of the AI Economy
https://intelligence.exponentialview.co/assets/ev-state-of-ai-economy-2026.pdf
Why AI Isn't Showing Up on Your Bottom Line
https://www.exponentialview.co/p/why-ai-isnt-showing-up-on-your-bottom-line
Azeem Azhar on X
https://x.com/azeem
Exponential View
https://www.exponentialview.co/
Topics Covered
The size and growth rate of real generative AI demand

How the AI stack divides between chips, hosting, foundation models and applications

Why memory and energized data centers may be the key AI infrastructure bottlenecks

Open-source models, proprietary pricing and enterprise assurance

Vertical integration and foundation model labs moving into applications

How AI value could flow to consumers rather than infrastructure providers

Why AI productivity requires workflow and organizational redesign

What investors can learn from earnings calls, hiring and enterprise spending

Forward-deployed engineers, consulting firms and vendor lock-in

Which intangible business moats strengthen or weaken as intelligence becomes abundant

Timestamps
00:00 The economics and sustainability of the AI boom
06:34 Mapping the four layers of the AI stack
10:43 Vertical integration and cross-stack competition
15:31 Why memory is becoming an AI infrastructure bottleneck
20:01 Open-source models versus proprietary AI
24:36 Why foundation model labs are moving up and down the stack
28:51 Could AI profits become consumer surplus?
33:00 Why more copilots cannot create an AI-native company
37:17 Job postings and the intangible investments behind AI adoption
44:16 Can forward-deployed engineers transform legacy companies?
49:15 Which business moats strengthen or weaken in the AI economy?
54:20 Do foundation models really have network effects?
59:00 Why judgment, verification and human provenance become more valuable
01:04:56 The exponential gap in data centers and education
01:10:06 How Azeem uses AI to deepen research and generate ideas
Learn more about the Excess Returns podcast network:
https://excessreturns.co
No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.

On the Latest First Principles, Andy Constan explains what the options market is signaling about the AI and semiconductor boom, why he believes earnings expectations have outrun the size of the economy, and where the next risks may emerge. We discuss speculative call buying, single-stock volatility, AI capital spending, consumer dissaving, the Fed put, Kevin Warsh's monetary policy framework, and the looming reset of US tariffs.Topics covered:
* Why parabolic moves in AI infrastructure and semiconductor stocks may reflect a speculative bubble
* What rising single-stock volatility and unusually low market correlations reveal beneath a calm index
* Why out-of-the-money calls became more expensive than puts and what that says about investor positioning
* How investors can hedge concentrated stock gains by selling calls and buying protective puts
* Why the AI bubble may be hiding in earnings expectations rather than traditional valuation multiples
* Andy's economic pie framework and why projected corporate profits may exceed the GDP available to support them
* How AI competition, open-source models, job displacement and subsidized token usage affect the return on AI investment
* Why capital spending and consumer dissaving are supporting economic growth, and where those drivers could weaken
* Whether the Federal Reserve could eventually buy equity ETFs and the inflationary consequences of a permanent Fed put
* How lower short-term rates and a smaller Fed balance sheet could rebalance Main Street and Wall Street
* Why expiring Section 122 tariffs could create a near-term shift in inflation, growth and the federal deficit

Timestamps:

00:02 Why the options market is flashing a warning on AI stocks
04:02 Extreme stock dispersion beneath a calm market
08:49 The signals of a speculative call-buying frenzy
13:00 How to hedge a stock position without calling the top
18:36 Why earnings expectations may be the real AI bubble
23:00 The economic pie cannot support every company's forecasts
27:00 AI job displacement and the widening gap between winners and losers
31:59 How capital spending and consumer dissaving are sustaining growth
36:00 When the return on AI investment starts to matter
40:26 Could the Fed buy stocks in the next financial crisis?
44:53 How Kevin Warsh might respond when markets and employment collapse
48:58 Lower rates, a smaller balance sheet and wealth inequality
52:59 The tariff deadline investors may be overlooking

Learn more about the Excess Returns podcast network:
https://excessreturns.co

No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.

Jack Schwager joins Excess Returns to discuss Market Wizards: The Next Generation and the extraordinary young traders profiled in the newest installment of the Market Wizards series.
He explains how traders turned small accounts into fortunes, survived devastating losses, built exceptional risk-adjusted records and adapted from day trading to longer-term strategies, while revealing the psychology, risk management and commitment behind elite trading performance.
Jack Schwager on X
https://x.com/jackschwager
Market Wizards: The Next Generation
https://amzn.to/4psEOmH
Topics covered
How video games, prop trading firms and modern technology shaped a new generation of traders

How Jack Schwager finds candidates and verifies extraordinary trading track records

Why return-to-risk measures can reveal more than the Sharpe ratio

Lukas Froelich's astonishing 2020 performance and the limits of compounding and scalability

Simon Rousseau's journey from a $40,000 borrowed account to nearly $500 million

How breaking risk rules led to massive losses even after extraordinary success

Kristjan Kullamägi's path from security guard to more than $100 million after repeated account blowups

Phil Goedeker's success with short selling, option selling and unusually strong risk control

Rick Bandazian Jr.'s merger arbitrage edge and more than a decade without a losing month

Why financial markets may remain uniquely difficult for artificial intelligence to solve

Lance Breitstein's apprenticeship, deliberate practice and shift from day trading to longer-term positions

What traders and long-term investors can learn about talent, discipline, persistence and human nature

Timestamps
00:00 Intro to Market Wizards: The Next Generation
04:33 How Jack finds exceptional traders and how the trading ecosystem changed
09:15 Auditing Lukas Froelich's extraordinary 2020 returns
14:03 Simon Rousseau: turning $40,000 into nearly $500 million
18:42 The $50 million Carvana loss and the danger of breaking trading rules
22:54 Kristjan Kullamägi: from security guard to more than $100 million
28:36 Phil Goedeker and the risk of negative asymmetry strategies
32:41 Hedging option risk during the Liberation Day market selloff
37:34 Trading personality and Rick Bandazian Jr.'s no-loss record
41:36 Can artificial intelligence ever become a Market Wizard?
45:42 Lance Breitstein: choosing mentorship over a higher salary
49:42 What long-term investors can learn from elite traders
53:52 Innate talent, human nature and all-consuming commitment
57:58 What the next generation of trading may look like
Learn more about the Excess Returns podcast network:
https://excessreturns.co
No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.