Excess Returns

Cameron Dawson and Dave Nadig join Matt Zeigler to examine what could break the market's resilience, from AI earnings expectations to the wealth effect supporting consumer spending. A healthy economy and continued data center investment may not be enough to keep stock prices rising if profit margins and investor expectations reset.

In this episode of Click Beta, Matt, Cameron and Dave debate what the two-year Treasury yield is signaling, how the AI buildout is changing demand for capital, and why semiconductor stocks can look cheap just as earnings approach a peak. They also discuss the possibility of a prolonged sideways market, practical approaches to rebalancing, and separating near-term cash needs from long-term investments. Then the surprise topics take a Halloween turn, with homemade costumes, strange family heirlooms, horror movies, and a very specific Creed halftime-show tribute.

Topics covered:
- Cameron Dawson's question: what would have to break for the Fed to deliver fewer hikes than markets expect?
- The wealth effect, consumer spending, and the divide between the top and bottom of the K-shaped economy
- Dave Nadig's concerns about AI financing, IPO supply, and who will absorb new stock issuance
- Why a low semiconductor P/E ratio can reflect concerns about peak earnings
- Micron, margin normalization, and the risk of extrapolating unusually strong profitability
- How a resilient economy could coexist with falling technology stocks or a sideways index
- Market rotation, defensive leadership, and the challenge of countertrend rallies
- Rebalancing rules, timing luck, and planning for cash needs over the next 12 months
- Distinguishing long-term legacy assets from money needed soon
- Halloween costumes, family traditions, Rocky Horror, and cult-film recommendations
Chapters:
00:00 Welcome to Click Beta: Limp Bizkit meets the Fed
05:30 What would have to break for the Fed to change course?
11:18 The K-shaped consumer and AI's demand for capital
16:44 More expensive capital and semiconductor earnings risk
22:30 Can chip margins stay this high?
26:56 Market rotation and the risk of going sideways
32:51 Diversification, rebalancing, and near-term cash needs
37:40 Halloween costumes and family stories
42:02 Holiday heirlooms and a Creed costume deep cut
46:32 Halloween movies, music, and where to find the panel

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.

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.

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.

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.

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.