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Excess Returns

Excess Returns is dedicated to making you a better long-term investor and making complex investing topics understandable. Join Jack Forehand, Justin Carbonneau and Matt Zeigler as they sit down with some of the most interesting names in finance to discuss topics like macroeconomics, value investing, factor investing, and more. Subscribe to learn along with us.

Latest Episodes:

Tech is Selling Off. AI Debt Fears Are Rising. So Why Does a $4B Manager See a Reverse Bubble? Oct 30, 2026

Show notes

Jay Hatfield of Infrastructure Capital Advisors makes the case for an AI "reverse bubble" and explains how earnings growth, interest rates, and valuation shape his market outlook. Rather than treating AI spending as proof of excess, he looks at contracts, financing costs, and the returns companies can earn on their investments.

In this episode of Excess Returns, Jay joins Jack Forehand and Justin Carbonneau to discuss his S&P 500 scenarios, the debate over CoreWeave and AI infrastructure debt, and why he believes some technology stocks offer better value than perceived safe havens. He also challenges the Fed's inflation framework and explains how he combines earnings growth, dividend yield, catalysts, and individual-stock covered calls in his investment process.

Topics covered:

- How Jay Hatfield builds S&P 500 targets from earnings estimates and valuation multiples

- Why Treasury yields matter to discounted cash flow valuations

- CoreWeave, project financing, and the distinction between contracted demand and speculative construction

- What compute prices and long-term contracts could reveal about AI bubble risk

- Jay Hatfield's "reverse bubble" thesis and his comparisons of growth-adjusted stock valuations

- His framework linking the 10-year Treasury yield to expected terminal Fed policy

- Why he challenges the Fed's inflation target, shelter data, and use of PCE

- Evaluating dividend payers with PEGY: price relative to earnings growth plus dividend yield

- How reinvestment, corporate taxes, and returns on capital affect long-term compounding

- Combining stock selection and catalysts with actively managed covered calls

Infrastructure Capital Advisors:

https://www.infracapfunds.com/

Jay Hatfield / InfraCap on X:

https://x.com/JDHatfield_ICAP

InfraCap's CPI-R analysis:

https://www.infracapfunds.com/consumer-price-index-cpi-r

Chapters:

00:00 Jay Hatfield's S&P 500 outlook and market scenarios

06:43 Treasury yields, growth assumptions, and valuation multiples

13:03 Technology stocks, CoreWeave, and project financing

18:38 AI debt, vendor financing, and contracted demand

26:09 The AI "reverse bubble" and growth-adjusted valuations

31:09 Fed expectations and the 10-year Treasury yield

38:14 Jay Hatfield's critique of the Fed and inflation data

43:12 Could the Fed change its inflation target?

47:48 Dividend yield, PEGY, and corporate reinvestment

55:23 Stock selection, catalysts, and individual covered calls

01:00:23 The long-term investing lesson: valuation and compounding

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.

The S&P 500 Is Just 50 Stocks. The Nasdaq Is a 67% AI Bet. Kai Wu on What Else Is Hiding in Your Funds Oct 29, 2026

Show notes

Kai Wu of Sparkline Capital shows how to uncover hidden AI exposure, overlapping ETF holdings, and unintended factor bets in your portfolio. Owning several funds can still leave you dependent on the same companies and the same AI spending cycle.

In this episode of Excess Returns, Kai joins Matt Zeigler and Justin Carbonneau for a walkthrough of Sparkline Analytics. Using examples from the S&P 500, Nasdaq, emerging markets, and active funds, they examine what investors actually own beneath the fund labels.

Kai explains his distinction between AI infrastructure, early adopters, and laggards, then demonstrates how factor analysis, intangible asset data, and a portfolio builder can help investors ask better questions about diversification and manager performance.

Explore Sparkline Analytics:
https://app.sparklinecapital.com/

Topics covered:

How AI infrastructure exposure can overlap across the S&P 500, Nasdaq, and thematic AI funds
Why Kai Wu distinguishes AI early adopters from infrastructure builders and laggards
How rising capital expenditures can change the economics of formerly asset-light businesses
Why a fund's number of holdings can overstate its diversification
How semiconductor exposure can connect emerging markets to the same AI trade
The trade-off between reducing AI infrastructure exposure and increasing exposure to laggards
What ARKK illustrates about separating stock selection from factor headwinds
Why dividend, value, and low-volatility funds can have similar underlying exposures
How patents, R&D, and human capital reveal assets traditional value metrics can miss
Using fund comparisons and portfolio look-through tools to identify overlapping positions

Chapters:

00:00 Sparkline Analytics and hidden AI exposure in the S&P 500
08:05 AI adopters, laggards, and multinational businesses
12:47 How index exposure changes as the AI cycle evolves
20:41 Does adding an AI fund diversify your portfolio?
25:44 Capital spending and effective portfolio concentration
30:14 Capital intensity and AI exposure beyond Big Tech
35:44 Diversifying without retreating into AI laggards
40:48 Screening funds and looking inside ARKK
46:11 Separating stock-picking alpha from factor exposure
52:35 Dividend, value, and low-volatility fund overlap
57:52 Intangible value and a fund-diligence checklist
01:05:39 Building a portfolio and looking through its holdings
01:10:39 Where to find Sparkline Analytics

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.

Dr. Daniel Crosby on Behaviorally Optimal Portfolios, Risk Composure and the Casino Myth Oct 27, 2026

Show notes

Daniel Crosby explains why investors can lose money in winning funds and how to build a portfolio they can actually hold. Picking the right investment is only part of the challenge; staying with it through discomfort is where behavior can overwhelm the plan.

In this episode of Excess Returns, psychologist and Orion Chief Behavioral Officer Daniel Crosby joins Matt Zeigler to discuss the new paperback edition of The Behavioral Investor. Daniel shares the story of a fund that returned over 18% annually for a decade while its average investor lost money, then explains how safety, stability, and success portfolios can help align investment decisions with human psychology. They also explore gambling apps, the limits of risk questionnaires, social media feedback loops, and the human side of financial advice in an AI-driven world.

Topics covered:

- Why a fund's returns can look very different from the returns its investors earn

- Building safety, stability, and success buckets around different financial needs

- The differences between risk tolerance, risk capacity, and risk composure

- Why knowing what to do does not guarantee doing it during a drawdown

- Daniel Crosby's case for rules, diversification, and meaningful benchmark differences

- How sports betting and prediction markets blur the distinction between investing and gambling

- Why recent market experience can create unrealistic expectations about future returns

- Education, environment, and encouragement as tools for changing investor behavior

- How algorithms reinforce market biases and why excitement can signal a blind spot

- Where AI can free financial advisors to spend more time on human relationships

The Behavioral Investor - paperback edition:https://link.amazon/B00hgkHGG

Daniel Crosby on X:

https://x.com/danielcrosby

Orion Behavioral Finance:

https://orion.com/behavioral-finance

Research discussed:

The heat of the moment: the effect of sexual arousal on sexual decision making

https://onlinelibrary.wiley.com/doi/abs/10.1002/bdm.501

Chapters:

00:00 Daniel Crosby and The Behavioral Investor

04:51 Why winning funds can have losing investors

11:46 Risk tolerance, capacity, and composure

17:38 Stability portfolios and rules-based stock selection

23:06 Investing, gambling, and prediction markets

27:27 Recency bias and unrealistic return expectations

31:30 Addictive apps and changing investor behavior

35:48 Investor distractions and the media diet

40:51 Investment excitement, humility, and AI

45:00 What music reveals about consistency and experimentation

49:29 Where to find Daniel Crosby and the book

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.

Baird's Tech Strategist Says This Isn't 2000. So Why Is He Warning Against Buying the Dip? Oct 24, 2026

Show notes

Ted Mortonson of Baird explains why conviction in the AI boom doesn't mean buying every dip in tech stocks.

He joins Jack Forehand and Justin Carbonneau to explain what experienced technology investors watch before putting money back to work—and why he still sees AI as the most powerful technology cycle of his career.

The discussion moves from lessons of the dot-com bust to the companies Ted believes can capture AI's profits. They explore the importance of free cash flow, the financing demands of the data center buildout, and how large IPOs could force portfolio managers to sell existing holdings. Ted also shares his views on Apple, Meta, Nvidia, Tesla, and SpaceX, before closing with lessons from his service as a naval aviator.

Topics covered:

- Why Ted Mortonson's institutional clients aren't rushing to buy the semiconductor dip

- What past tech cycles teach about taking profits, preserving capital, and waiting for selling to settle

- Why Ted Mortonson sees a stronger long-term AI opportunity than the dot-com cycle

- How geopolitics, energy costs, regulation, and investor sentiment shape technology investing

- Why free cash flow, engineering resources, and manufacturing scale matter for AI beneficiaries

- Financing the infrastructure buildout before enterprise adoption delivers returns

- How large IPOs and circular financing can create risks for existing shareholders

- Ted Mortonson's concerns about Apple and his outlook for Meta, Tesla, and SpaceX

- Optical networking, advanced chip architectures, and high-bandwidth memory

- Navy lessons on decisions under uncertainty, teamwork, and integrity

Chapters:

00:00 Ted Mortonson on the risks facing tech investors

05:42 Market sentiment and why his clients aren't buying yet

12:00 Dot-com lessons and the danger of buying every dip

16:17 Why Ted sees a different AI cycle

23:06 Which companies could capture AI's profits?

27:38 Regulation and financing the AI buildout

35:10 Can the market absorb massive AI IPOs?

39:30 Circular financing and the Tesla-SpaceX thesis

46:06 Apple, Meta, and competing AI strategies

54:19 SpaceX, advanced chips, and memory technology

58:26 Lessons from serving as a naval aviator

01:03:35 Closing thoughts

Ted Mortonson at Baird:

https://www.rwbaird.com/corporations-and-institutions/institutional-equities-research/team/ted-mortonson/

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.

He Asked 25 Finance Pros How They Invest Their Own Money: Brian Portnoy on What the Models Get Wrong Oct 23, 2026

Show notes

Brian Portnoy of Shaping Wealth explores why experienced investors build very different portfolios—and what that means for your own money.

In How I Invest My Money Volume Two, 25 new contributors explain how they invest their personal wealth. Brian joins Matt Zeigler to discuss what those stories reveal about the gap between an optimal portfolio on paper and one you can actually live with.

From large cash reserves and paid-off mortgages to investments in their own businesses, their choices reflect family needs, career risk, and priorities that a model can struggle to capture.

The conversation also explores why low-cost index funds don't settle every investing question, how financial professionals think about bonds and alternatives, and what it means to compound relationships, knowledge, and opportunities alongside money.

How I Invest My Money Volume Two:
https://link.amazon/B0aVpNlfS

Topics covered:

Why knowing how markets work doesn't produce one right portfolio for everyone
What Ben Hunt and other contributors reveal about investing beyond a brokerage account
Connecting personal goals to asset allocation and risk tolerance
Why business ownership and household needs change the role of stocks and bonds
Why financial professionals may deliberately hold substantial cash reserves
The difference between spreadsheet optimization and a portfolio you can stick with
Paying off a mortgage, feeling secure, and accepting the opportunity cost
The complexity and illiquidity that can come with alternative investments
Matt Zeigler's approach to compounding human, intellectual, social, and financial capital
Brian Portnoy's experience editing the book with his son Zach and sharing opportunities across generations

Chapters:

00:00 How finance professionals invest their own money
05:35 Why investing extends beyond index funds
12:20 Connecting financial goals to portfolio choices
18:32 Why investors choose different stock and bond allocations
25:05 Cash reserves, career risk, and peace of mind
34:55 Paying off a mortgage: security versus opportunity cost
40:11 Alternatives, complexity, and the investment industry
44:40 Matt Zeigler on investing in more than money
52:22 Brian Portnoy on family, opportunity, and working with his son

Shaping Wealth:
https://www.shapingwealth.com

Follow Brian Portnoy on X:
https://x.com/bportnoy_

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.

Rob Arnott on the Hidden Costs of Passive Investing and the Real Winners From AI Oct 21, 2026

Show notes

Rob Arnott, founder of Research Affiliates and chairman of Syzygy Asset Management, examines S&P 500 concentration and who could benefit most from AI. Owning today’s market leaders is not necessarily the same as owning tomorrow’s biggest investment winners.

Subscribe on Spotify⁠⁠⁠⁠

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In this episode of The Intangible Economy, Rob joins Kai Wu to explore how index construction shapes what investors own, why index additions can create hidden costs, and why he would consider buying a richly valued IPO before index funds have to buy it. The conversation also covers AI’s shift toward capital-intensive business models, GPU depreciation, intangible assets, and the importance of testing investment ideas rather than chasing impressive backtests.

Topics covered:

Why Rob Arnott sees a real AI revolution alongside risks in the prices of its leading stocks
How AI customers could capture value beyond the infrastructure builders
Valuation changes versus fundamental growth in large and smaller companies
Tesla, SpaceX, and the price pressures surrounding index inclusion
Hidden implementation costs that do not appear in an index fund’s expense ratio
Selecting index members by business size rather than market value
AI financing, customer economics, and the risk of rapid hardware obsolescence
R&D, intangible assets, and what conventional book value can miss
Competitive moats, leadership, and creating value for customers
Using AI in research while resisting overfitting and performance chasing

Research discussed:

⁠The Active Side of Indexing⁠

⁠Fundamental Growth⁠

Learn more about ⁠Syzygy Asset Management⁠.

Timestamps:

00:00 Rob Arnott on index concentration and AI’s future winners

12:13 What S&P 500 investors own and pay for

20:35 Why Rob Arnott would buy before index inclusion

25:41 Hidden index costs and fundamental membership rules30:37 Passive investing’s embedded decisions

36:40 Big Tech’s shift from asset light to capital intensive

42:41 GPU depreciation and economic obsolescence

47:03 R&D, intangible assets, and value investing

51:04 How durable are competitive moats?

59:01 Using AI in business and investment research

01:05:11 Performance chasing and the backtest trap

Learn more about the Excess Returns podcast network:⁠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.

The S&P 500 Is Only 50 Stocks. 70% of the Index Is in a Correction. Did the Sell-Off Already Happen? Oct 18, 2026

Show notes

Paisley Nardini of Tema ETFs explores AI investing, S&P 500 concentration, and how to build a portfolio around changing market risks. How can investors participate in powerful growth trends without making every holding a bet on the same outcome?

In this episode of Excess Returns, Paisley joins Jack Forehand and Justin Carbonneau to discuss the risks beneath a resilient stock market, why tomorrow’s AI winners may differ from today’s leaders, and where she sees opportunities in power and infrastructure. They also explore private-company exposure inside ETFs, the role of thematic funds alongside a passive core, and why knowing what you own matters more than the number of holdings in your portfolio.

Topics covered:

What weak market breadth reveals beneath the headline indexes
Interest rates, midterm elections, and the limits of historical market patterns
Prediction markets as a source of information for investors
AI earnings expectations, debt financing, and the risk of slowing growth
Why bonds can provide income without reliably offsetting equity risk
Small-cap profitability and the importance of quality screens
AI bottlenecks, photonics, power demand, and infrastructure investment
Private-company exposure in ETFs: liquidity, fees, and investment rationale
Using thematic strategies as satellite positions around a passive core
Portfolio concentration, investment humility, and staying flexible

Learn more about Tema ETFs.

Follow Paisley Nardini on X.

Timestamps:

00:00 Introduction and the risks beneath the market
04:37 Higher rates and the midterm election outlook
09:17 What investors can learn from prediction markets
13:36 AI growth expectations and changing market leadership
19:50 Portfolio risk, bonds, and faster market drawdowns
26:09 The AI bubble debate and small-cap quality
33:45 Who benefits from AI beyond the hyperscalers?
39:29 Energy infrastructure and putting AI to work
45:54 Private-company exposure inside ETFs
52:01 Where thematic investing fits in a portfolio
58:32 Commodities, S&P 500 concentration, and humility

Learn more about the Excess Returns podcast network:
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.

We Asked T. Rowe Price's $17B International Manager Why Value is Winning Again — and What the S&P 500 Leaves Out Oct 17, 2026

Show notes

Colin McQueen of T. Rowe Price explains what is changing for international value stocks and how he separates cheap businesses from opportunities that can improve. Higher interest rates, industrial investment, and corporate reform are reshaping the opportunity set, but his process still starts with free cash flow and the price investors pay for it.

Colin joins Justin Carbonneau and Jack Forehand to discuss his evolution from deep value investing to a broader approach that includes quality businesses and restructuring opportunities. We explore why value struggled in the 2010s, what has changed outside the US, and how he uses valuation signals and diversification to manage risk.

The conversation also covers AI suppliers and disruption, governance changes in Japan and Korea, opportunities and risks in China, and the case for financial stocks. Colin shares examples involving Samsung, Hitachi, and Rolls-Royce, along with his experiments using AI to challenge investment theses and recognize when conviction has become stubbornness.

Topics covered:

The lessons Colin McQueen learned from deep value, quality investing, and a difficult decade for value
How higher rates and spending on infrastructure, defense, and power can change the opportunity set
AI supply-chain opportunities and the uncertainty around future winners and losers
Valuing tangible and intangible businesses through normalized free cash flow
Using AI as an alternative voice when deciding whether an investment thesis is broken
The US-international valuation gap, earnings growth, and diversification beyond tech
Japan's corporate reforms, Korea's value-up effort, and the importance of what is already priced in
China's contrarian appeal and the governance risks that accompany it
How restructuring, management changes, and better capital allocation can unlock value
Building a diversified portfolio and looking beyond quarterly earnings and market narratives

T. Rowe Price International Value Fund

https://www.troweprice.com/financial-intermediary/us/en/investments/mutual-funds/us-products/international-value-equity-fund/advisor-class.htmlTimestamps:

00:00 Colin McQueen's evolution as a value investor
07:04 Why deep value struggled in the 2010s
11:20 Higher rates and a more balanced opportunity set
16:20 International value, financials, and AI suppliers
21:20 AI versus the dot-com era and managing valuation risk
25:27 Free cash flow, restructuring, and AI-assisted research
29:56 Comparing US and international valuations
35:39 The risk dashboard and changing European markets
40:00 Corporate reform and opportunities in Japan and Korea
44:57 China, Asia ex Japan, and financial stocks
49:31 Global connections and why a stock market isn't an economy
54:55 Diversification and researching corporate turnarounds
59:57 Looking beyond quarterly earnings and extreme narratives

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.

Tech Is Rolling Over. Yields Are Falling. Why Jim Paulsen is Watching the Walmart Recession Signal Oct 16, 2026

Show notes

Jim Paulsen sees a risk of a stock market correction as financial conditions tighten and investors grow comfortable with tech's long run of leadership. But his warning does not require a recession or the end of the bull market.

In this month's Jim Paulsen Show, Jim joins Justin Carbonneau and Jack Forehand to walk through the charts behind his cautious outlook. He explains how rising yields, oil prices, and a firmer dollar can affect the economy with a lag, why favorable seasonality may offer less support than investors expect, and how a slowdown in technology spending could challenge market leadership.

We also explore the signals Jim sees in retail, housing, employment, and Walmart's relative performance. He closes with a possible path through a correction: slowing growth, lower inflation and yields, and a recovery that could give the bull market another run. His seven lagging sectors, the "Modest Seven," are central to that case.

Topics covered:

Why Jim Paulsen is cautious without making a recession or full bear-market call
His financial-conditions gauge and the risks of tightening into an already pressured economy
How restrictive conditions can weaken the November-to-April seasonal advantage
The delayed effects of bond yields, oil prices, and the dollar on economic surprises
Technology spending relative to GDP and why slower growth could matter for tech stocks
AI adoption, pricing, and the challenge of turning investment into profits
How two decades of tech leadership may encourage complacency and crowded positioning
The divide between AI, inflation-assisted sectors, and the "Modest Seven"
What sector performance, bond yields, and the Walmart Recession Signal suggest about growth
Why rate cuts may initially accompany falling stocks, and how a correction could set up another advance

Follow Jim Paulsen:

Paulsen Perspectives
Jim Paulsen on X

Timestamps:

00:00 Jim Paulsen's outlook: correction risk without a bear-market call
07:41 Restrictive conditions and the seasonal buying period
14:12 Why the Fed and investors interpret conditions differently
20:28 Oil, yields, the dollar, and their lagged effects
26:00 Technology spending relative to the economy
30:18 Can AI break the historical pattern?
35:00 Tech's long leadership cycle and investor complacency
42:00 AI, inflation-assisted sectors, and the Modest Seven
47:06 Market signals ahead of economic reports and bond pressure
53:00 Bond competition and the Walmart Recession Signal
58:11 How a correction could lead to another bull-market run

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.

AI Productivity Is Real. 83% of Stocks Are 10% Off Highs. Why Does Barry Ritholtz Like Bonds Again? Oct 14, 2026

Show notes

Barry Ritholtz, Dave Nadig and Matt Zeigler explore why AI's real productivity gains don't automatically translate into an investing edge. From stock picking and market concentration to the financing behind the AI buildout, they separate enthusiasm for the technology from the economics of owning it.

Subscribe to Click Beta on Spotify⁠⁠⁠

⁠⁠⁠Subscribe to Click Beta on Apple Podcasts

In this episode of Click Beta, Barry Ritholtz and Dave Nadig join Matt Zeigler for a conversation about where AI is already changing their work and where investors should ask harder questions. Barry shares how his team uses AI to analyze portfolio drift and identify clients who may need a rebalance. The discussion also covers client relationships, consumer pricing, creative side projects, and why Barry is increasingly enthusiastic about bonds without calling an end to the equity bull market.

Topics covered:

Why widely available AI tools may improve research without creating a lasting stock-picking advantage
Market breadth, mega-cap concentration, and the potential impact of large tech IPOs
Data center financing, credit quality, and the risk of rapid technological change
Barry Ritholtz's use of AI to analyze allocation drift, taxes, and household circumstances
How better meeting records can strengthen the human side of financial advice
Learning to collaborate with AI and asking better questions
The debate over dynamic pricing, consumer data, and whose interests AI agents serve
Baseball tools, astronomy dashboards, music discovery, and the joy of experimenting
Deciding which tasks to automate and which activities are worth doing yourself
Barry Ritholtz's case for bonds, municipal income, and avoiding the reach for yield

Find our guests:

Barry Ritholtz — The Big Picture - https://ritholtz.com
Ritholtz Wealth Management - https://www.ritholtzwealth.com
Barry Ritholtz on X - https://x.com/Ritholtz
Dave Nadig's work at etf.com - https://www.etf.com
Dave Nadig on X - https://x.com/DaveNadig

Timestamps:

00:00 Meet Click Beta: AI and the stock-picking question
05:14 AI concentration and market breadth
10:08 Tech IPO valuations and data center financing
15:22 Barry Ritholtz: AI and portfolio rebalancing analysis
20:58 Can AI improve the human side of financial advice?
25:49 Better client questions and better prompts
30:13 The AI imagination gap: collaboration versus search
36:48 Dynamic pricing and the consumer-retailer arms race
41:26 Consumer data and the incentives behind AI agents
45:54 Astronomy, music, and testing your assumptions
51:18 Automating busywork to make room for curiosity
55:39 Creative experiments and choosing what to automate
01:00:11 Why Barry Ritholtz is excited about bonds
01:04:37 Bonds versus equity income and closing thoughts

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.

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