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Tobias Carlisle joins Excess Returns to discuss why today’s market may be setting up a major opportunity in value stocks, small caps and micro caps. We cover stretched market valuations, AI capex, SpaceX and other massive IPOs, the risk of speculative growth assumptions, and how Tobias builds systematic deep value portfolios in ZIG and DEEP.
Tobias Carlisle on X
https://x.com/GreenbackdAcquirers Funds
https://acquirersfunds.com/Topics covered:
Why elevated market valuations point to lower forward returns, not necessarily an immediate exit from stocks
The case for small value, micro-cap value and mid-cap value after a long large-cap growth cycle
Why equal-weight indexes and small caps may be signaling a market leadership shift
Whether AI capex will create lasting profits or mostly benefit consumers
The parallels and differences between AI, the dot-com boom, railroads and fiber optic buildouts
How AI spending is being financed and why the stock market may be demanding more compute investment
What the SpaceX IPO, OpenAI and Anthropic could mean for market supply and investor psychology
Why base rates are being challenged by the growth of major technology platforms
How disruption can create value traps and why traditional valuation metrics can struggle in disrupted industries
The energy demand implications of AI data centers and why nuclear and natural gas could matter
How Tobias combines valuation, quality, financial statements and portfolio construction in ZIG and DEEP
Why quarterly rebalancing may be a practical balance between timing luck, momentum and trading costs
Timestamps:
00:00 Why AI value may accrue to consumers
04:00 What extreme market valuations say about future returns
08:22 Small caps, equal weight and the Mag Seven reversal
14:15 AI capex and lessons from past technology booms
19:47 Who gets the profits from AI?
23:00 Cash flow, debt and the AI spending race
28:06 SpaceX, giant IPOs and market supply
31:00 OpenAI, Anthropic and Mauboussin’s base rates
35:17 Is buying the S&P 500 more speculative than investors realize?
36:57 Value investing during disruptive technology cycles
41:07 War, energy prices and the broadening trade
45:32 Semiconductor valuations and aggressive growth assumptions
47:30 How Tobias builds the ZIG and DEEP portfolios
54:17 ETF rebalancing, timing luck and systematic value investing -
Professor Aswath Damodaran joins Kai Wu on The Intangible Economy to break down how to value SpaceX, AI companies, intangible assets, and the future of value investing.
We discuss why big markets do not automatically create big value, how AI CapEx is changing the character of major technology companies, and why the best investment stories still have to connect to the numbers.
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Topics covered:
Valuing SpaceX after its IPO and why price matters even for great companies
How Starlink, space launch, and xAI fit into SpaceX’s valuation story
Why total addressable market can mislead investors in AI and other disruptive industries
The problem with AI unit economics, data centers, power, water, and reinvestment needs
Why growth can destroy value when margins and returns on capital are weak
How intangible assets, R&D, future growth, and narratives should show up in valuation
The Big Market Delusion and how overconfidence drives boom and bust cycles
Why AI CapEx is different from the dot-com boom and could create broader risks
How AI is changing the character of the Magnificent Seven and semiconductor companies
Why value investing became rigid, ritualistic, and righteous, and how it can evolve
Timestamps:
00:00 Why great companies can still be bad investments
01:03 Introducing Aswath Damodaran and The Intangible Economy
01:49 SpaceX IPO, Starlink, xAI, and the challenge of valuing uncertainty
05:31 Why Starlink became the core of SpaceX’s current revenue
10:31 How Damodaran valued SpaceX across launch, connectivity, and AI
14:07 Why AI’s huge market may still have difficult unit economics
17:10 The tension between SpaceX competing in AI and renting data centers to competitors
20:00 Why valuation should use distributions instead of false precision
22:39 How stories and numbers work together in valuation
26:45 Why investors confuse promises, potential, and businesses
30:49 The Big Market Delusion and overconfidence in AI investing
33:02 Why the AI CapEx boom is different from the dot-com bubble
35:17 How AI infrastructure is changing the Magnificent Seven
38:36 Nvidia, Micron, semiconductors, and the risk of peak cycle earnings
41:00 Why the biggest AI market stories could be scary for society
43:37 AI disruption, labor markets, and the speed of technological change
46:30 Measuring which jobs and companies are most exposed to AI automation
49:00 Why AI cost structure may look more like Spotify than software
51:13 The unresolved business model questions for LLMs and AI agents
52:29 Why traditional value investing lost its edge
56:03 Passive investing, book value, and the blame game in value investing
58:13 Why rigid value investing is vulnerable to AI disruption
01:00:58 How value investing can adapt to intangible assets and uncertainty
01:02:21 Why any company can be a good investment at the right price
01:04:57 Why investing mistakes and track records are harder to judge than they look
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Saknas det avsnitt?
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In the third episode of First Principles with Andy Constan, Andy breaks down the changing structure of markets as the IPO window reopens, AI CapEx accelerates, and corporate buybacks shift toward new equity supply. We discuss what the SpaceX IPO says about capital markets, whether AI spending can create disinflationary growth, why the consumer is still holding up, and what could challenge the current market bubble.
Follow First Principles on Spotify
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Topics covered:
Why IPOs are central to the purpose of public markets
How Andy evaluates whether the SpaceX IPO worked
Why issuers may want IPOs to trade higher after pricing
The shift from stock buybacks to new equity issuance
Why AI CapEx is changing the supply and demand for shares
How hyperscaler spending is being funded through cash, bonds, and stock
The economic test for whether AI investment pays off
Disinflationary productivity growth versus labor displacement
Why the current economy is still supported by consumption
The role of wealth effects and consumer dissaving
Why falling oil prices may not eliminate inflation pressure
What Andy is watching in Fed policy, tariffs, AI CapEx, and equity issuance
How Kevin Warsh could approach rates, QT, and the Fed balance sheet
Timestamps:
00:00 Intro and key themes
04:18 How Andy reads the SpaceX IPO
08:27 Why underwriters and regulators want IPOs to work
13:00 Why issuers may want IPOs to trade higher
17:05 From stock buybacks to new equity supply
21:06 The 600 to 700 billion dollar shift in share supply
26:42 The economic test for AI tokens
32:09 Can AI create disinflationary productivity growth?
38:10 Is AI CapEx holding up the economy?
41:00 Wealth effects, dissaving, and the consumer
45:52 Oil prices, war, and inflation
49:07 Jalen Brunson, incentives, and long-term value
52:00 Fed policy, tariffs, and what matters this summer
55:36 Kevin Warsh, QT, and the Fed balance sheet
58:42 Closing thoughtsNo 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.
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In this episode of The OPEX Effect, Jack Forehand and Brent Kochuba break down the market structure impact of the SpaceX IPO, options expiration, dealer gamma, volatility, and the next major setup for the S&P 500 and Nasdaq. They discuss why SpaceX may trade more on flows than fundamentals, how call buying could create a gamma squeeze, and why June OPEX, VIX expiration, FOMC, oil, Iran headlines, and index inclusion could all collide at once.
Subscribe to the OPEX Effect on Spotify
Subscribe to the OPEX Effect on Apple Podcasts
Topics covered:
Why SpaceX is a flows game at the start of trading
How the SpaceX IPO could affect liquidity across mega cap tech stocks
Why fundamentals may not matter when index flows and forced buying dominate
The role of Nasdaq, Russell, and S&P 500 index decisions in SpaceX trading
How options could create a gamma squeeze in SpaceX
Why dealer hedging flows can push stocks higher or lower
What June options expiration could mean for the S&P 500
Why VIX expiration and FOMC create a key market window
How Core1M signaled the recent volatility spasm
Why expensive calls, not put buying, drove the recent market stress
The key S&P 500 levels Brent is watching into OPEX
How oil, rates, inflation, and Fed policy could affect market volatility
Why Nasdaq options pricing is diverging from the S&P 500
How SpaceX index inclusion could widen the gap between Nasdaq and the S&P
What would make Brent add protection or look for another short-term market correction
Timestamps:
00:00 Opening clips and the SpaceX flow setup
05:27 Elon Musk net worth after the SpaceX IPO
07:13 SpaceX, liquidity, Mag Seven selling, and index demand
12:48 Why SpaceX may trade on flows before fundamentals
17:59 What options trading could change for SpaceX
22:05 How call buying can create a gamma squeeze
28:24 Why June OPEX matters more than a normal expiration
33:55 VIX expiration, FOMC, and market path dependency
37:20 The Core1M signal and the recent volatility spasm
41:22 The S&P 500 gamma map and key risk levels
46:25 Why expensive calls drove the market stress
50:14 Oil, rates, inflation, and the Fed setup
57:03 The JPMorgan collar and the 6900 to 7000 support zone
58:32 Nasdaq versus S&P 500 after the SpaceX IPO
01:03:14 Brent’s summary, SpaceX gamma squeeze risk, and the next market setup -
Mike Green joins Excess Returns to explain why passive investing, index construction, SpaceX, AI IPOs and mega-cap concentration may be changing how the stock market actually works. We discuss how passive flows can affect prices, why AI earnings may be more circular than investors think, what could break the current market narrative, and why the economy feels much weaker for many households than the headline data suggests.
Michael Green Twitter
https://x.com/profplum99Simplify Asset Management
https://www.simplify.us/Topics covered:
Why the SpaceX IPO has turned passive investing into a mainstream market structure debate
How index committees and passive flows can influence individual stocks
Why low float, Nasdaq demand and passive buying could create unusual IPO dynamics
How new AI-related equity issuance could change the supply-demand balance in the stock market
The research behind passive flows, market impact and cap-weight concentration
Why Mike thinks passive buying explains more of mega-cap outperformance than AI fundamentals
The circular financing risk in AI, including Nvidia, CoreWeave, Google and Anthropic
Why buy-the-dip flows, ETFs, CTAs and vol control funds matter for market direction
How headline economic data can miss household stress, second jobs and lost purchasing power
What Mike is watching to see whether the AI trade and market narrative are starting to break
Why AI may be hugely valuable to consumers before it creates major business productivity gains
How companies may eventually redesign business models around AI rather than simply automate tasks
Why SpaceX wealth creation could seed the next generation of competitors
How inflation, gasoline prices, low savings and a K-shaped economy are affecting consumers
Timestamps:
00:00 Passive indices, AI profits and why this market feels different
04:07 Why SpaceX changed the passive investing debate
08:01 The research behind passive flows and market impact
12:16 Why Mike thinks passive flows explain mega-cap strength
16:18 ETF flows, buy-the-dip behavior and bubble dynamics
20:28 Why economic data can miss household stress
25:13 Bubble warnings, CAPE and what investors may be ignoring
29:17 AI as a consumer advice engine versus a productivity revolution
33:29 How businesses may redesign themselves around AI
37:51 Why IPO wealth may create the next generation of competitors
42:06 Mike Green’s upcoming book on passive investing and market structure -
AI could become the next general purpose technology, reshaping economic growth, inflation, interest rates and portfolio construction. Vanguard Global Chief Economist Joe Davis joins Excess Returns to explain why AI, demographics, fiscal deficits and globalization may define the next decade for investors, and why the biggest market winners may eventually come from outside the technology sector.
Coming into View: How AI and Other Megatrends Will Shape Your Investmentshttps://amzn.to/4v8L7OfVanguard Megatrends Research Hubhttps://explore.vanguard.com/megatrends.html
Topics Covered:
AI as a potential general purpose technology
Why long-term megatrends can affect short-term market returns
The four forces shaping the next decade: technology, demographics, deficits and globalization
Why Vanguard believes AI could lift U.S. growth above consensus
How AI could offset aging demographics and rising debt
Why great technology cycles often include major stock market drawdowns
The difference between AI automation, augmentation and new industry creation
Why the next AI winners may be in healthcare, financial services and other service industries
The risk that AI disappoints and fiscal deficits dominate the outlook
How tariffs, oil prices and AI investment interact in the macro outlook
What AI could mean for 60/40 portfolios, value stocks, fixed income and international markets
Joe Davis’ lesson for average investors: the power of compoundingTimestamps:
00:00 Why every great technology eventually faces a market drawdown
04:28 The four megatrends shaping the economy
08:56 How megatrends explain short-term S&P 500 moves
13:22 Why AI may be in the 1996 or 1997 stage
18:29 Where the next AI winners could emerge
21:44 AI, fiscal deficits and the danger of kicking the can
26:17 Why 2% growth and 2% inflation may be unlikely
30:31 How to tell if AI augmentation is really working
33:19 AI, globalization and which countries could benefit
38:14 Why investors need a multi-factor macro scorecard
41:23 What AI means for the 60/40 portfolio
44:12 Joe Davis on investing, compounding and Vanguard’s megatrends research -
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/davenadigCameron Dawson
https://x.com/CameronDawsonTopics 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
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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
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Jim Paulsen on X
https://x.com/jimwpaulsenPaulsen 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 nowFollow 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.
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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-disruptionKai Wu on X
https://x.com/ckaiwuSparkline 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_TriTrivariate Research
https://trivariateresearch.com/Trivector Research
https://www.trivectorresearch.comTopics 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 -
Eric Crittenden joins Matt Zeigler and Jason Buck for a deep dive into trend following and managed futures.
They discuss why systematic macro trend investing works, how risk transfer creates a return premium, and how trend can fit inside a diversified all-weather portfolio.
Standpoint Funds
https://www.standpointfunds.com/
Topics covered:
Why trend following can struggle during fast reversals and thrive after regime shifts
How systematic investors manage whipsaws, drawdowns, and emotional pressure
The trade-offs between short-term, medium-term, and long-term trend signals
Why Eric prefers simple, durable systems over complex models and constant tinkering
When it makes sense to remove a futures market from a systematic portfolio
Why trend following may earn a risk transfer premium from hedgers and commercial users
How copper producers, options markets, and insurance help explain trend following returns
Why rising interest rates and short bond positions can benefit managed futures
How trend following can pair with global equities in an all-weather portfolio
Why smoothing a trend strategy can reduce its value when investors need convexity most
The behavioral challenge of holding diversifiers that look wrong at the wrong time
Why investors and advisors often want alternatives but struggle to stick with them
Timestamps:
00:00 Why trend following opportunities appear under pressure
04:39 Pro-growth positioning before the whipsaw
09:32 Short-term vs long-term trend signals
13:46 The danger of tinkering with systematic strategies
18:43 What actually changes in a durable process
23:27 Rising rates, short bonds, and collateral yield
28:00 Copper hedging and why trend followers buy rising prices
32:00 Options, insurance, and risk transfer through time
36:28 Regime shifts and supply-demand imbalances
41:00 What investors choose when asset classes are anonymized
45:11 Building a portfolio for 30-year terminal wealth
50:06 Why portfolio construction is different than judging individual strategies
56:15 Why trend following and value investing require faith
01:00:42 Reducing errors vs chasing highlight-reel winners
01:05:36 Where to follow Eric and Standpoint
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Cliff Asness returns to Excess Returns for a greatest hits tour through some of his most important and entertaining investing ideas.
We discuss bubble logic, today’s AI market comparisons, why volatility still matters as a risk measure, private equity “volatility laundering,” international diversification, market timing myths, pulling the goalie, and how machine learning is changing quantitative investing.
Cliff Asness on X
https://x.com/CliffordAsnessAQR Capital Management
https://www.aqr.com/Papers Discussed
Bubble Logic: Or, How to Learn to Stop Worrying and Love the Bull
https://www.aqr.com/Insights/Research/Working-Paper/Bubble-Logic-Or-How-to-Learn-to-Stop-Worrying-and-Love-the-BullRubble Logic: What Did We Learn From the Great Stock Market Bubble?
https://www.aqr.com/Insights/Research/Journal-Article/Rubble-LogicMy Top 10 Peeves
https://www.aqr.com/-/media/AQR/Documents/Insights/Journal-Article/My-Top-10-Peeves.pdfVolatility Laundering
https://www.aqr.com/Insights/Perspectives/Volatility-LaunderingI Did Not Predict What Is Going on in Privates
https://www.aqr.com/Insights/Perspectives/I-Did-Not-Predict-What-is-Going-on-in-Privates(So) What If You Miss the Market's N Best Days?
https://www.aqr.com/Insights/Perspectives/So-What-If-You-Miss-the-Markets-N-Best-DaysInternational Diversification Works (Eventually)
https://www.aqr.com/Insights/Research/Journal-Article/International-Diversification-Works-EventuallyInternational Diversification - Still Not Crazy after All These Years
https://www.aqr.com/Insights/Research/Journal-Article/International-Diversification-Still-Not-Crazy-after-All-These-YearsPerhaps the Most Important Essay I Will Ever Co Author
https://www.aqr.com/Insights/Perspectives/Perhaps-the-Most-Important-Essay-I-Will-Ever-Co-AuthorMain topics covered:
How the dot-com bubble created its own internal logic
Why Dow 36,000 and Cisco message boards captured bubble thinking
What investors learned, and failed to learn, from the tech bubble
How today’s AI market compares with the dot-com era
Why long periods of underperformance make even good strategies hard to stick with
Why Cliff still defends volatility as a useful risk measure
Why “cash on the sidelines” is a misleading market narrative
How private equity smoothing can make risk look lower than it really is
Why the private markets debate is not a short-term prediction
Why the “missing the best 10 days” argument against market timing is incomplete
Why international diversification can still matter after decades of US outperformance
What pulling the goalie can teach investors about risk, incentives and career risk
How machine learning changes quant investing without eliminating economic intuition
Timestamps:
00:00 Why certainty is dangerous in investing
04:58 Why Bubble Logic never became a book
10:18 Cisco, Yahoo message boards and bubble psychology
14:16 Rubble Logic and the lessons investors failed to learn
18:04 What today’s AI market has in common with the dot-com bubble
22:23 Why the long run can lie to investors
26:02 Volatility, permanent loss of capital and real risk control
30:19 Why there is no cash on the sidelines
34:00 Private equity, smoothing and volatility laundering
39:47 Why Cliff did not call the private markets downturn
43:19 The flaw in the missing the best 10 days argument
49:00 Why international diversification still works eventually
53:35 Why crashes are global but lost decades are local
57:30 Pulling the goalie and asymmetric risk
01:01:00 Why coaches and investors avoid optimal decisions
01:07:36 Machine learning, overfitting and economic intuition
01:10:50 Leverage, short selling and derivatives in quant portfolios
01:16:26 Where to follow Cliff Asness -
Ben Carlson joins Excess Returns to discuss his new book Risk and Reward and the biggest lessons investors can learn from market history. We cover how to think about risk, inflation, market timing, bear markets, lost decades, diversification, compounding and why surviving volatility is the key to building long-term wealth.
Ben's Book
https://amzn.to/4dFHsQzBen Carlson on X
https://x.com/awealthofcsBen's Blog
https://awealthofcommonsense.com/Main topics covered:
Why risk is hard to define and always involves trade-offs
How vivid risks like sharks and headlines distort investor decision-making
Why doing nothing can be one of the hardest parts of investing
How inflation should be viewed through personal finance, human capital and long-term investing
Why stocks can be an inflation hedge even if they struggle during inflation spikes
Why waiting for the market coast to clear often fails
What the world’s worst market timer teaches about saving and staying invested
How loss aversion shapes investor behavior
What the Great Depression, bear markets and 30-year returns teach about long-term investing
Why there is no perfect portfolio and the best strategy is one you can actually stick with
Timestamps:
00:00 Ben Carlson on why risk and reward are attached
06:35 Doing nothing, action bias and better investing behavior
11:51 Inflation psychology and lessons from the 1970s
16:55 Why stocks can hedge inflation over the long run
21:07 Why waiting for the coast to clear is a market timing trap
26:30 Time horizons, loss aversion and portfolio behavior
31:49 Government rescue, left-tail risk and unintended consequences
35:54 Recessionary vs non-recessionary bear markets
42:09 Why the stock market and economy can diverge
47:24 Why compounding is about holding, not trading
51:37 Starting valuations, lost decades and future returns
55:40 Risk, reward and the biggest lesson for investors
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AI is moving from hype to real enterprise adoption, and Gene Munster and Doug Clinton join Excess Returns to explain what that means for investors, technology stocks, energy demand, jobs and the next phase of the AI trade. We discuss why AI may still be early in its bubble cycle, how frontier models like GPT, Claude, Gemini and Grok compare, why AI-powered investing is becoming more practical, and where the biggest second-order opportunities may emerge.
Gene Munster on X
https://x.com/munster_geneDoug Clinton on X
https://x.com/dougclintonDeepwater Asset Management
https://www.deepwatermgmt.com/Intelligent Alpha
https://www.intelligentalpha.co/Main topics covered:
• Why Doug Clinton still thinks AI could become a bigger bubble than dot-com
• How Claude Code, Codex and frontier AI models are changing enterprise productivity
• The job disruption risk for knowledge workers and why AI adoption may become a survival skill
• Why the AI model race may not be winner-take-all
• How Intelligent Alpha uses large language models to evaluate stocks and earnings expectations
• Why GPT, Claude and DeepSeek perform differently across investing tasks
• The AI infrastructure boom and why energy may be one of the most underappreciated bottlenecks
• Hyperscaler CapEx, data centers and the investment case for continued AI spending
• How major AI IPOs like SpaceX, Anthropic and OpenAI could affect public markets
• Why space, orbital data centers and zero-gravity manufacturing could become real investment themesTimestamps:
00:00 AI, electricity and intelligence
04:33 Why new AI models changed the semiconductor trade
09:14 What AI means for knowledge worker jobs
14:03 Codex, Claude Code and Google’s AI challenge
18:50 OpenAI, Apple and the model capacity race
23:03 How many frontier AI models can survive?
27:18 Intelligent Alpha’s AI earnings benchmark
31:34 Why AI investors avoid emotional bias
35:33 Where to invest in the AI stack
39:00 Why AI energy demand is still underappreciated
43:43 How markets are judging hyperscaler AI spending
48:00 The investment opportunity in space
52:20 Final thoughts and closing -
Jeremy Grantham joins Excess Returns to discuss The Making of a Permabear, mean reversion, market bubbles, AI, the Magnificent 7, and the long-term lessons investors can take from his career at GMO. We cover why he rejects the simple “permabear” label, how he thinks about valuation and bubbles, why AI may be both transformative and dangerous for investors, and why long-term thinking is so hard but so essential.
The Making of a Permabear: The Perils of Long-term Investing in a Short-term World
https://groveatlantic.com/book/the-making-of-a-permabear/GMO
https://www.gmo.com/americas/Grantham Foundation
https://granthamfoundation.org/Topics covered:
Why Jeremy Grantham thinks the “permabear” label misses the point
The difference between being generally bearish and making a true “abandon ship” call
Mean reversion, valuation cycles, and why history still matters for investors
Why monopoly power helped reshape U.S. profit margins and market concentration
How AI could turn today’s monopoly winners into brutal competitors
Why new technology often becomes a cost of doing business rather than a permanent profit boost
How Grantham defines bubbles using two-sigma market events
Lessons from Japan, the dot-com bubble, the housing bubble, and the 2021 speculative peak
Why institutional investors struggle to stick with value strategies during bubbles
The role of purpose, climate risk, toxicity, and long-term thinking in Grantham’s later career
The one lesson Grantham would teach ordinary investors about pessimism, realism, and time horizons
Timestamps:
00:00 Jeremy Grantham on unpleasant news and long-term investing
04:18 Reinvesting when terrified in 2009
08:43 Why Grantham told investors to abandon ship in 2008
10:28 Mean reversion and why history matters
14:00 Monopoly power, the Mag 7, and rising market concentration
17:14 Why AI is important but impossible to forecast
20:21 AI as a cost of doing business
21:24 From monopoly profits to brutal AI competition
24:05 How investors should think about valuation mean reversion
27:00 Why high returns on capital should eventually attract competition
29:47 How Grantham defines a market bubble
33:00 Japan’s extreme bubble and GMO’s zero weight decision
34:19 The dot-com bubble and the pain of being early
38:00 Grantham’s bubble warning signal in 2021
41:35 Whether today’s market is showing classic bubble behavior
43:00 QuantumScape, meme stocks, and speculative excess
46:35 How ChatGPT interrupted the 2022 bear market
49:12 Investor behavior and the cost of underperforming in a bubble
55:00 Purpose, philanthropy, climate risk, and useful work
01:01:03 The one lesson Grantham would teach average investors -
Marc Rubinstein joins Excess Returns to explain what private credit, bank earnings, insurance balance sheets, fintech growth, and arbitrage firms reveal about the modern financial system. The conversation covers why private credit risks may not be systemic in the traditional banking-crisis sense, but still matter for investors because of redemption gates, hidden leverage, opaque structures, incentive conflicts, and correlations that can spike when markets are under stress.
Marc Rubinstein on X
https://x.com/MarcRubyNet Interest
https://www.netinterest.co/In this episode, we discuss:
Why the Fed says private credit redemption risks are limited and manageable
What Blue Owl’s redemption gates reveal about private credit liquidity
How post-2008 bank regulation pushed risk into private credit, hedge funds, trading firms, and exchanges
Why banks and private credit firms are both competitors and collaborators
The “layer cake” of leverage connecting banks, private credit, and borrowers
How HSBC’s loss tied to Atlas and MFS highlights hidden credit risks
Why insurance companies have become increasingly tied to private credit
Why rapid growth can be dangerous in financial businesses
What bank earnings show about the gap between weak consumer confidence and resilient spending
Why post-mortem reports from SVB, Credit Suisse, and other failures reveal what investors could not see in real time
How Revolut became one of the most interesting fintech stories in global banking
Why Marc calls this a potential golden age of arbitrage
What Jane Street, public BDC discounts, private asset valuations, and geopolitical fragmentation tell us about market structure
Why investors may still be too anchored to the 2008 banking playbook
Where Marc sees risk and opportunity in financials, banks, Europe, and non-bank financial institutions
Timestamps:
00:00 Private credit, hidden risks, and correlation spikes
05:03 Why Blue Owl became a private credit warning sign
10:20 How private credit grew after the 2008 financial crisis
15:30 Banks and private credit as financial “frenemies”
19:44 HSBC, Atlas, MFS, and the layer cake of leverage
24:11 Apollo, Athene, insurance assets, and private credit incentives
29:20 Why higher rates have not broken more of the financial system
33:40 Bank earnings, consumer confidence, and resilient spending
37:20 Why “I don’t know” can be a powerful signal from bank CEOs
41:46 Revolut and the ambition to build a truly global bank
47:38 Why growth can be dangerous in finance
52:19 Private assets, public BDC discounts, and arbitrage opportunities
56:34 What investors misunderstand about banks today
59:31 How Marc would think about financials as a long-short investor -
First Principles with Andy Constan launches with a deep dive into market bubbles, AI, semiconductor stocks, and the financial conditions that can turn powerful technological change into a dangerous investment regime. Andy explains how bubbles form, why they are almost impossible to time, how today’s AI boom compares to past episodes like 1987, the dot-com bubble, housing, and the bond bubble, and what investors should watch as expectations, financing, and FOMO build.
Andy Constan on X
https://x.com/dampedspringDamped Spring Advisors
https://dampedspring.com/Topics covered:
Why bubbles are easy to identify in hindsight but nearly impossible to define in real time
The difference between an expensive market and a true bubble regime
How new technologies, easy money, regulation, and exogenous shocks can create bubble conditions
Why AI may rhyme with the internet boom without being an exact repeat
The role of ChatGPT, Microsoft’s OpenAI investment, and semiconductor earnings expectations
What the 1987 crash, Japan, housing, bonds, and dot-com bubble can teach investors today
Why human nature, FOMO, and “keeping up with the Joneses” make bubbles so powerful
How the late-1990s Fed response to Long-Term Capital Management helped fuel the final phase of the tech bubble
Why tech’s current size in the economy and market may limit how far the AI boom can grow
How AI capex, hyperscaler spending, buybacks, debt issuance, and IPO supply could determine what happens next
Timestamps:
00:00 Intro and the challenge of identifying bubbles
04:32 Expensive markets vs true bubble regimes
09:57 The five bubble episodes Andy compares to today
14:35 Root conditions, escalation events, and the peaking phase
19:20 Why the 1987 crash may also have been a bubble
24:25 The late-1990s setup and the Netscape Navigator moment
28:00 Crisis analogs, easy financial conditions, and today’s AI parallels
32:20 Long-Term Capital Management and rocket fuel for the tech bubble
36:11 Why tech’s market share matters more today than in the 1990s
43:18 Policy mistakes, subsidies, and how governments feed bubbles
47:42 Semiconductor earnings expectations and valuation risk
53:45 The AI capex chain and where the money has to come from
58:42 IPOs, corporate debt, and the financing risk behind the AI boom
01:02:27 What investors should do differently in a bubble regime -
Edward Chancellor joins Kai Wu on the latest episode of the Intangible Economy to discuss what financial history and capital cycle theory can teach investors about today’s AI boom. They explore why transformative technologies can still produce terrible investor returns, how overinvestment develops, where anti-bubbles may be forming, and what past episodes like the railway mania, the dot-com bubble, China’s investment boom and the post-2008 interest rate regime suggest about the risks and opportunities today.
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Topics covered:
How capital cycle theory applies to the AI data center boom
Why railway mania, autos, aircraft and the dot-com bubble offer lessons for today
Why markets often fund major technology transitions but fail to identify the winners
The prisoner’s dilemma driving hyperscaler AI spending
Whether AI demand can justify the supply being built
How GPU depreciation and AI capital spending may affect reported earnings
Why hallucinations and reliability may limit the total addressable market for large language models
The case for looking at AI anti-bubbles instead of shorting the bubble directly
Why China shows that strong GDP growth does not guarantee strong shareholder returns
How intangible capital, SaaS valuations and human capital fit into capital cycle analysis
Whether bubbles can be good for society while still being bad for investors
Why the long-term interest rate cycle may have changed
The role of gold in a world of expensive stocks, rising debt and vulnerable bonds
Timestamps:
00:00 Edward Chancellor on capital cycles, bubbles and AI
04:42 Why the railway mania became a classic overinvestment cycle
09:00 Why markets fund technology booms but often miss the winners
13:19 The prisoner’s dilemma behind AI spending
17:30 Will AI demand justify the supply being built
20:00 How capital spending can inflate profits before the bust
25:08 The AI Hindenburg moment and the limits of large language models
30:55 Why AI hype may exceed the proven technology
35:55 Why the anti-bubble may matter more than shorting AI
40:00 The energy transition bubble and the opportunity in overlooked assets
45:08 China’s lesson on GDP growth and shareholder returns
49:27 Big Booze, GLP-1s and the Lindy effect
54:23 Can intangible capital have its own capital cycle
59:54 SaaS valuations and the index creation warning signal
01:04:10 Why bubbles can help society but hurt investors
01:09:09 Why long-term rates may be in a new multi-decade cycle
01:14:07 Why Edward Chancellor still sees a role for gold -
Brent Kochuba of SpotGamma joins Jack Forehand for the May 2026 OPEX Effect to break down what options positioning is saying after a massive AI and semiconductor-led market rally. They discuss SPX call volume, zero DTE options, dealer gamma, VIX expiration, NVIDIA earnings, oil risk, AI CapEx, and why options flows may help explain both the market’s recent melt-up and the potential for a volatility shift after OPEX.
Guest Links
Brent Kochuba on X
https://x.com/spotgammaSpotGamma
https://spotgamma.com/Topics Covered
Why the market has ignored oil shocks and geopolitical risk while AI earnings dominate investor attention
How AI CapEx, semiconductors and mega-cap tech have driven a powerful melt-up in stocks
Why options volume and zero DTE trading are increasingly important for all investors
How dealer hedging, delta and gamma can affect stock market moves
Why options expiration can create short-term turning points in markets and volatility
What the May OPEX setup says about call-heavy positioning in the S&P 500
Why single-stock options activity in NVIDIA, Tesla, Apple, Amazon and AI-related names matters
How record SPX call volume is being driven by short-dated options flows
Why Brent is watching VIX expiration, NVIDIA earnings and May 19 to May 20 for volatility expansion
What oil, VIX, correlation and dispersion are signaling about market risk
Timestamps
00:00 Intro: SPX call volume, call-heavy positioning and transient options flows
00:57 Are we in melt-up mode?
05:29 AI, UFOs and how fast market narratives are changing
09:00 Why options flows matter more for everyday investors
13:39 Could SpaceX become the next huge options market?
16:00 How dealer hedging, delta and gamma move through the market
20:44 Why OPEX can become a turning point for stocks and volatility
23:22 Why May OPEX is so call heavy
28:07 The market rally into May expiration
33:00 AI rebranding, meme behavior and downside headline risk
36:07 Reviewing last month’s oil and volatility setup
40:17 How the war flipped market leadership back to tech
44:13 Dealer gamma support in the S&P 500
49:19 Single-stock gamma in NVIDIA, Tesla, Apple and Amazon
51:06 Record SPX call volume and the role of zero DTE
54:55 Semiconductor, AI and memory call volume
57:50 From bearish positioning to peak-bull dispersion
59:22 Oil, the S&P 500 and changing correlations
01:03:06 COR1M, dispersion risk and when Brent considers hedging
01:04:57 Brent’s key takeaways for May OPEX and volatility expansion - Visa fler
