Excess Returns

On the latest Click Beta, Matt Zeigler, Dave Nadig and Cameron Dawson discuss what could happen when SpaceX goes public and why this IPO may be as much a market structure problem as a valuation problem.
They break down the potential impact of a $1.75 trillion IPO, 100 times sales, a small free float, forced index buying, passive fund flows, options trading, bubble dynamics and what advisors should tell clients who want SpaceX exposure.
Subscribe to Click Beta on Spotify⁠
⁠Subscribe to Click Beta on Apple Podcasts
Dave Nadig
https://x.com/davenadig
Cameron Dawson
https://x.com/CameronDawson
Topics Covered:
Why the SpaceX IPO could create a chaotic first 30 days of trading

How 100 times sales, no earnings and a $1.75 trillion valuation change the discussion

Why pre-IPO access, lockups, fees and vehicle structure matter for investors

How Palantir and Tesla frame the debate over extreme growth stock valuations

Why SpaceX could create unusual supply and demand pressure in the public market

How options trading, Nasdaq 100 inclusion and accelerated index rules could affect price discovery

Why free float matters and how a 4 percent float could become a 12 percent index adjustment

How much passive demand might chase SpaceX shares after the IPO

What the bubble triangle says about technology, speculation, money and credit

Why real earnings do not disprove a technology-driven bubble

How liquidity, private credit gates, IPO supply and buybacks could shape the next phase of the market

Why advisors need to help clients think through sizing, exit plans and safe access

Peak season travel, TikTok monoculture, Ocean City, Coheed and Cambria, and the lost art of CDs and mixtapes

Timestamps:
00:00 Why the first 30 days could be chaotic
04:00 Why everyone is talking about the SpaceX IPO
09:23 The market structure problem behind SpaceX
13:00 Options trading, small indexes and forced buying
17:18 How much passive demand could chase SpaceX
21:27 Why real earnings do not disprove a bubble
25:43 Liquidity, IPO supply and why bubbles can keep going
29:13 What advisors tell clients who want SpaceX
33:17 Fake SPVs, scams and safe access
37:39 Ocean City, peak season and Jersey Shore memories
41:39 Coheed and Cambria opening for Shinedown
45:44 Summer concerts, Bikini Kill, Weezer and The Shins
46:25 Cleaning out old cars and rediscovering CDs
50:10 Old iPods, underwater MP3 players and forgotten playlists
53:20 Mixtapes, liner notes and physical music culture
55:08 Where to find Dave Nadig and Cameron Dawson

Jim Paulsen returns to Excess Returns to discuss why he is increasingly concerned about a meaningful stock market pullback, even though he does not expect a bear market. We cover the extreme divide between AI-driven “new era” stocks and the rest of the market, what oil and inflation could mean for the Fed, why tech earnings and market leadership have become so concentrated, and what investors should watch as the economy potentially shifts from inflation fears to growth fears.
Subscribe to the Jim Paulsen Show on Spotify⁠⁠

⁠⁠Subscribe to the Jim Paulsen Show on Apple Podcasts

Jim Paulsen on X
https://x.com/jimwpaulsen
Paulsen Perspectives
https://paulsenperspectives.substack.com/
Topics Covered
Why Jim thinks the economy could weaken into the summer and fall

The risk of a sharp stock market pullback without a full bear market

How inflation, oil prices and geopolitical conflict are affecting the market

Why the Fed may face a difficult decision under Kevin Warsh

The extreme divide between new era tech stocks and old era stocks

Why AI and innovation need to benefit the broader economy to be sustainable

How tech earnings have become concentrated in only two S&P 500 sectors

Why small-cap tech and unprofitable tech leadership may be a warning sign

What past oil price peaks suggest about stock market corrections

Why investor focus may shift from inflation risk to growth risk

How this bull market has been driven by a series of booms in Mag 7, Bitcoin, gold, oil and AI

Timestamps
00:00 Why AI has to benefit more than the tech sector
05:18 Inflation, oil prices and the impact of geopolitical conflict
10:54 New era stocks versus old era stocks
15:43 Corporate cash, AI spending and pressure on tech investment
20:17 Policy tightening and why economic momentum may slow
25:31 Why AI must spread beyond the companies building it
31:42 Why this tech boom is different from the 1990s
36:51 Why market breadth keeps fading back into large-cap growth
42:06 Small-cap tech and unprofitable tech start leading
46:15 Why the damage from oil shocks often comes after oil peaks
50:15 How the market could shift from inflation fear to growth fear
54:40 The bull market of booms in Mag 7, Bitcoin, gold, oil and AI
59:46 Jim’s main takeaway for investors now
Follow the Excess Returns podcasts:
https://excessreturnspod.com/
Contact us:
[email protected]/
No information on this podcast should be construed as investment advice. Securities discussed in the podcast may be holdings of the firms of the hosts or their clients.

Kai Wu of Sparkline Capital joins Excess Returns to break down his latest research on AI disruption, software stocks, value traps, and intangible moats. We discuss why software valuations have collapsed, why traditional value investing can fail during technological disruption, and how investors can separate potential AI winners from companies whose business models may be permanently impaired.
AI Disruption: Moats and Value Traps
https://www.sparklinecapital.com/post/ai-disruption
Kai Wu on X
https://x.com/ckaiwu
Sparkline Capital
https://www.sparklinecapital.com/
Topics Covered:
Why software stocks are trading at a historically unusual discount to the market

How AI disruption can create both real opportunities and dangerous value traps

Why Blockbuster, Borders, RadioShack and newspapers offer lessons for today’s software selloff

How patent data and natural language processing can measure technological disruption

Why disruption has helped explain the poor performance of traditional value investing

Why value investing may still work in sectors insulated from technological change

How intangible assets like brand, human capital, intellectual property and network effects can protect companies

Why Walmart and The New York Times survived disruption while other incumbents did not

How David Teece’s complementary assets framework applies to AI, software and moats

Why AI adoption and intangible value together may help identify software survivors

Why high dispersion in disruption-scare stocks creates a potential opportunity for stock pickers

Timestamps:
00:00 Software stocks now trade at a historic discount
04:26 What makes a cheap stock a value trap
08:25 Measuring disruption using patents, filings and natural language processing
13:23 Is AI the biggest disruptive wave in history?
14:55 Why disruption keeps stacking on retailers
17:10 How technological change disrupted traditional value investing
21:20 Why value investors need to know when not to apply old metrics
25:06 Why more of the market is exposed to innovation than ever before
27:07 What Walmart and The New York Times teach about surviving disruption
32:40 The four intangible moats that can protect companies
35:02 Why intangible value works better in disrupted industries
38:50 Apple, Amazon, Macy’s and the difference between disruptors and value traps
42:58 Applying intangible value to beaten-down software stocks
47:05 Why AI adoption alone is not enough
48:23 How AI could improve margins for surviving software companies
50:09 Which industries are adopting AI fastest
52:14 The software sweet spot: AI adoption plus intangible moats
53:53 Why disruption-scare stocks have extreme return dispersion
57:40 What happens when intangible value is applied to high-disruption stocks
01:01:42 Why “code is not the moat” for many software companies

In this episode of Last Call, we break down one of the most confusing market backdrops in years: AI-driven earnings optimism, rising oil and inflation risk, stretched options positioning, and the market impact of a potential SpaceX IPO. Jack Forehand and Matt Zeigler are joined by Aahan Menon, Ben Hunt, and Brent Kochuba to examine what macro data, political narratives, options flows, and index mechanics are saying about where markets could go next.
Follow Last Call on Spotify⁠⁠⁠⁠⁠
⁠⁠⁠⁠⁠Follow Last Call on Apple Podcasts⁠
Topics Covered:
Why markets are looking through war, oil shocks and valuation concerns

How earnings estimates are driving sector performance in the AI trade

Aahan Menon on growth, inflation, oil prices and macro regime signals

Why demand destruction from higher energy prices can take longer than investors expect

What a rising growth and rising inflation regime can mean for stocks, commodities and bonds

Ben Hunt on World War AI and the collision between AI market optimism and political backlash

Why opposition to AI data centers could become a major market and election issue

Brent Kochuba on call buying, implied volatility and signs of options market froth

Why CORE 1M and skew signals may be warning of a downside spasm

How the SpaceX IPO could affect index flows, active managers and mega-cap stocks

Timestamps:
00:00 Intro: AI, inflation and options risk in one market
05:40 Earnings estimates, AI optimism and why fundamentals still matter
10:31 Aahan Menon on a difficult macro backdrop
15:29 Why energy shocks and demand destruction take time
20:24 Why inflation can persist even if the oil shock eases
24:47 Ben Hunt on World War AI and the AI resource build-out
30:00 AI CapEx as the pillar holding up market optimism
34:00 The political backlash against AI data centers
38:00 Why data center opposition matters for markets
42:09 Why price action can distort the AI narrative
47:48 CORE 1M, stretched call prices and downside spasm risk
52:00 Why Nasdaq options are priced for upside crashes
56:11 Index rules, human judgment and the SpaceX IPO
01:00:34 The free float problem and rebalancing pressure
01:05:22 Space data centers, valuation and the size of the AI opportunity

Adam Parker returns to Excess Returns to explain why the market may be trading more on future fundamentals than investors think, how AI is reshaping stock selection, and why traditional valuation signals may be less useful than they once were.
We discuss AI revenue exposure, software vs. semiconductors, Mag Seven positioning, gross margins, estimate achievability, spinoffs, and Adam’s highest-conviction contrarian sector idea.
Adam Parker on X
https://x.com/Adam_Parker_Tri
Trivariate Research
https://trivariateresearch.com/
Trivector Research
https://www.trivectorresearch.com
Topics covered:
Why “sell in May” and other calendar-based market rules often lack statistical support

Why Adam thinks the stock market leads the economy, not the other way around

How to think about whether today’s AI market is a bubble

Why the market may be trading on 2030 or 2031 fundamentals

When investors may start demanding returns on AI capital spending

Why AI could create new jobs rather than simply destroy existing ones

How large AI-related IPOs like SpaceX could affect index mechanics and portfolio flows

Why gross margin expansion is one of Adam’s most important stock selection factors

Why Adam remains cautious on software and prefers semiconductors over software

How valuation, quality, and other traditional factors may have changed since COVID

Why estimate achievability and incremental margins matter more than simple beats and misses

How to think about the Mag Seven, Nvidia, and market concentration

Why spinoffs may become more important in an AI-driven market

Why healthcare is Adam’s highest-conviction contrarian sector idea

Timestamps:
00:00 Why the market may be trading on future fundamentals
04:37 Is today’s stock market an AI bubble?
08:45 When AI capex needs to show real returns
13:00 How trillion-dollar IPOs could reshape index mechanics
19:00 Why gross margin expansion is such a powerful factor
23:00 Why software companies face AI-driven margin pressure
27:21 Where AI semiconductor exposure goes next
31:54 Why valuation does not work for stock picking
35:03 What has changed in markets since COVID
39:22 Estimate achievability and incremental margins
43:06 How to think about the Mag Seven and Nvidia
47:55 Why healthcare could be the biggest AI opportunity