Excess Returns

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 compounding

Timestamps:

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

Subscribe to Click Beta on Spotify⁠

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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

Subscribe to the Jim Paulsen Show on Spotify⁠⁠

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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:
excessreturnspod@gmail.com/

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.

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

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 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

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

Cliff Asness on X
https://x.com/CliffordAsness

AQR 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-Bull

Rubble Logic: What Did We Learn From the Great Stock Market Bubble?
https://www.aqr.com/Insights/Research/Journal-Article/Rubble-Logic

My Top 10 Peeves
https://www.aqr.com/-/media/AQR/Documents/Insights/Journal-Article/My-Top-10-Peeves.pdf

Volatility Laundering
https://www.aqr.com/Insights/Perspectives/Volatility-Laundering

I 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-Days

International Diversification Works (Eventually)
https://www.aqr.com/Insights/Research/Journal-Article/International-Diversification-Works-Eventually

International Diversification - Still Not Crazy after All These Years
https://www.aqr.com/Insights/Research/Journal-Article/International-Diversification-Still-Not-Crazy-after-All-These-Years

Perhaps the Most Important Essay I Will Ever Co Author
https://www.aqr.com/Insights/Perspectives/Perhaps-the-Most-Important-Essay-I-Will-Ever-Co-Author

Main 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's Book
https://amzn.to/4dFHsQz

Ben Carlson on X
https://x.com/awealthofcs

Ben'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

Gene Munster on X
https://x.com/munster_gene

Doug Clinton on X
https://x.com/dougclinton

Deepwater 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 themes

Timestamps:

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

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 on X
https://x.com/MarcRuby

Net 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

Andy Constan on X
https://x.com/dampedspring

Damped 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

Subscribe on Spotify⁠

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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 on X
https://x.com/spotgamma

SpotGamma
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

Bridgeway Capital Management
https://bridgeway.com/

I Know What You Did Last Summer
https://bridgeway.com/perspectives/i-know-what-you-did-last-summer/

How Many Stocks Are Effectively in the S&P 500?
https://bridgeway.com/perspectives/how-many-stocks-are-effectively-in-the-sp500/

Topics Covered

• Why quantitative investing still needs human judgment and skepticism

• The difference between smart beta and true multi-factor portfolio construction

• How Bridgeway combines value, quality, sentiment and risk controls

• Why the size premium may depend on how small-cap stocks are defined

• Why recently fallen large caps and IPOs can distort small-cap research

• How the small-cap universe has changed as companies stay private longer

• How intangible assets affect traditional value and quality metrics

• Why value can work in bursts and why timing factor rotations is so difficult

• How concentrated the S&P 500 has become using the HHI framework

• Why passive investing may create opportunities for active small-cap managers

• How market neutral strategies can help investors manage equity market volatility

• How AI can help with data, text analysis and trading without replacing investment judgment

Timestamps

00:00 Why fewer than 50 stocks are driving S&P 500 returns
01:04 Bridgeway’s evidence-based investing approach
02:59 Why quantitative models need human judgment
07:52 Smart beta vs multi-factor investing
11:32 How Bridgeway builds multi-factor portfolios
16:08 Rethinking the size premium
20:31 Has the small-cap universe gotten worse?
23:49 How intangibles change value investing
28:05 Does value still work?
30:09 Why value returns can be episodic
33:11 Why factor investors need patience
35:22 How concentrated is the S&P 500?
40:29 Factor strategies as portfolio diversifiers
41:41 Passive investing and market structure
44:27 Managing volatility with market neutral strategies
49:40 How systematic managers update their models
55:02 How Bridgeway is using AI
01:00:03 Elena’s biggest lesson for investors

Subscribe to the 100 Year Thinkers on Spotify⁠⁠

⁠⁠Subscribe to the 100 Year Thinkers on Apple

Topics Covered

• Why being present with management teams may still be an investor edge in the age of AI

• How microcap investing differs from small-cap, mid-cap and large-cap investing

• Why talking to management can build conviction but also create bias

• How Chris Mayer thinks about vertical market software, mission-critical systems and AI disruption

• Why AI may become table stakes rather than a durable competitive advantage

• How small companies can use AI to improve workflows, sales, inventory and productivity

• Why many microcaps have short shelf lives and rarely become true long-term compounders

• The role of intelligent fanatics, owner-operators and repeat winners in great investments

• Why management transitions can create powerful microcap opportunities

• The difference between being a great analyst and being a great investor

• Why execution, position sizing, selling losers and holding winners matter more than hit rate

• How Matt and Bogumil apply the lessons to AI, business quality and the limits of small business scalability

Timestamps

00:49 Introducing Chris Mayer, Ian Cassel and 100 Year Thinkers

04:59 Ian Cassel’s first management meeting and XM Satellite Radio

09:00 Why management meetings deepen understanding but can also mislead

14:32 Chris Mayer on the real edge in long-term investing

18:40 Mission-critical software, systems of record and AI disruption

22:45 How microcap companies are using AI in real businesses

27:02 AI as table stakes and when disruption creates opportunity

31:29 Why most microcaps have short shelf lives35:51 Finding Tom Brady before the market knows he is Tom Brady

40:53 Why owner-operators and intelligent fanatics matter

45:03 Second-in-command leaders, repeat winners and chips on shoulders

49:27 Analyst vs investor and the missing skills of stock picking

54:00 Using data to identify investor strengths, weaknesses and decision errors

58:14 Position sizing and letting small positions earn the right to grow

01:03:00 Peter Lynch, stocks as businesses and learning to think like an owner

01:07:00 AI, human judgment and the limits of automation

01:11:00 Why not every small business can become the next Facebook

01:15:00 Where to follow Bogumil and the 100 Year Thinkers series

Subscribe on Spotify

Subscribe on Apple

Topics Covered

• Why letting winners run can be so powerful, but so hard for professional investors

• Chris Davis on how his mother outperformed by never selling great companies

• The tradeoff between concentration, diversification and real-world portfolio risk

• Why Rich Bernstein thinks today may look more like the 1960s than the 1970s

• How oil prices affect consumer behavior when measured against wages

• Chris Davis on why perceived risk can be very different from actual risk

• What cars, insurance and investor behavior reveal about market complacency

• Why the Fed’s 2% inflation target may not reflect the world investors are living in

• The relationship between valuation, durability and software stocks

• Why higher inflation could increase demand for dividends and near-term cash flow

• Chris Davis on why exceptional people and management teams matter in investing

• Why AI may be a great economic story but not necessarily a great investment story

Timestamps

00:00 Letting winners run, 1960s inflation and investor risk perception
02:18 Chris Davis on how his mother outperformed by never selling
08:32 Reinvestment risk and the limits of active management
12:45 Why oil shocks may matter less when gasoline is low relative to wages
20:25 Chris Davis on why feeling safe can make investors take more risk
29:20 Rich Bernstein on whether the Fed’s 2% inflation target is outdated
34:08 Chris Davis on durability, valuation and software stocks
39:39 Why cash flow gives durable companies room to adapt
43:16 Rich Bernstein on dividends, inflation and the need for cash today
51:55 Chris Davis on why people matter more than investors think
56:07 The risk and value of investing with exceptional leaders
1:01:30 Rich Bernstein on AI as an economic story vs. an investment story
1:05:13 Why AI productivity may not translate into obvious stock market winners

Follow Last Call on Spotify⁠⁠⁠⁠

⁠⁠⁠⁠Follow Last Call on Apple Podcasts⁠

Topics Covered

• Why markets are ignoring war, oil shocks, and geopolitical risk

• The “supernova” risk in private credit and why it hasn’t hit markets yet

• How supply-driven inflation differs from 1970s-style demand inflation

• Why pessimistic sentiment may actually be supporting markets

• The role of earnings growth and valuation resets in fueling the rally

• Bull vs bear case for markets based on macro, earnings, and positioning

• Why free cash flow trends may be more concerning than earnings

• How options flows and dealer positioning are suppressing volatility

• The AI capex boom and its impact on market leadership and breadth

• The growing divide between Mag 7 earnings and the rest of the market

Timestamps

00:00 Intro and market overview
01:37 Why markets are not falling despite negative news
03:00 Buy-the-dip behavior and earnings resilience
06:11 Ben Hunt on “supernova” risks in private credit
08:00 Hidden credit crunch in middle market companies
10:24 Why private credit matters for economic growth
14:10 Oil supply shocks and global growth risks
17:00 Why markets can ignore risks before they appear
18:48 Jim Paulsen on market resilience and sentiment
20:00 Why pessimism may reduce downside risk
22:24 Inflation vs labor force growth framework
24:00 Why current inflation is supply-driven, not demand-driven
26:00 Potential shift from inflation focus to growth focus
29:11 Kevin Muir on bull vs bear market setup
31:00 War impact on rates, oil, and positioning
33:00 Fed reaction and shifting rate expectations
35:00 Why earnings remain the dominant market driver
37:00 Why geopolitics often doesn’t move markets
40:00 Bear case: weak free cash flow and employment risk
44:26 Brent Kochuba on options flows and positioning
47:00 Why markets ignore rising rates and oil
49:00 Call buying, dispersion, and tech leadership
51:00 Energy as both hedge and AI-driven opportunity
54:00 Correlation, volatility, and market structure
56:00 Dealer positioning and suppressed volatility
58:00 Earnings strength and narrow market leadership
01:01:00 Free cash flow vs earnings debate
01:01:55 AI capex and long-term market implications

Follow Rich on Twitter:
https://twitter.com/RBAdvisors

Company Website:
https://www.rbadvisors.com

• Why investors in S&P 500 index funds may face disappointing long-term returns

• The shift from exporting disinflation to importing inflation through global trade

• How war and geopolitical conflict are influencing inflation expectations and markets

• Why today’s environment resembles the 1960s “guns and butter” period more than the 1970s

• The case for structurally higher inflation and a potential shift in Fed targets

• Why shorter-duration assets, dividends, and cash flow matter more in inflationary regimes

• The risks of overconcentration in AI and mega-cap growth stocks

• How capital flows and valuation distortions create opportunities outside the Mag 7

• The case for international equities and why investors are significantly underweight

• Where Bernstein sees the most compelling long-term opportunities across sectors and regions

00:00 Intro and why index investors could be disappointed
00:01:13 War, inflation, and the impact of rising gasoline prices
00:02:40 Importing inflation and the role of global trade dynamics
00:03:33 1970s oil shock vs 1960s guns and butter comparison
00:05:00 Why today’s inflation environment may be less severe than the 1970s
00:06:30 Defense spending, tax cuts, and inflation expectations
00:08:54 Why Bernstein is taking the “over” on inflation and deficits
00:10:00 The case for a higher long-term inflation target
00:11:00 Why the Fed may resist changing its 2% inflation target
00:12:00 Deglobalization and the rise of global conflict
00:14:00 Global inflation dynamics and divergence across countries
00:15:21 Why cash and short-duration assets may outperform
00:17:00 Asset-liability mismatches and the endowment model stress
00:18:23 Market concentration and parallels to the dot-com bubble
00:20:00 AI as an economic story vs an investment story
00:21:00 Capital flows, valuation excess, and future return expectations
00:22:39 Why market broadening opportunities may emerge
00:24:19 Passive flows, ETFs, and market distortions
00:25:40 Where Bernstein sees sector opportunities today
00:27:34 The case for dividends in an inflationary environment
00:31:00 Why near-term cash flow matters more than long-term growth
00:33:07 Corporate behavior, capital allocation, and rising hurdle rates
00:36:02 Profit cycle strength and why the market should broaden
00:41:36 Evaluating IPOs and speculative investments
00:47:09 The risk of a lost decade for index investors
00:50:21 Gold, commodities, and portfolio diversification
00:53:48 Most attractive overlooked opportunities today
00:58:06 Biggest long-term risks and what keeps Bernstein up at night

Davis Advisors
https://www.davisadvisors.com

Topics Covered

• Why high valuations signal complacency even in an uncertain macro environment

• The three major forces reshaping markets: higher cost of capital, deglobalization, and AI

• How to identify durable and resilient businesses in a fragile world

• Why growth and value are not opposites and how expectations drive opportunity

• Lessons from past bubbles and why today may resemble 1999 in market structure

• The hidden risks in passive investing and index concentration

• Chris Davis’ five-part framework for investing in AI (winners, enablers, users, protected, disrupted)

• Why most investors lose money by overpaying for growth and underestimating competition

• The importance of management quality and “great people” in long-term investing success

• Why the biggest investing mistakes are often the great companies you sell too early

Timestamps

00:00 Intro and key investing paradox on risk perception
02:45 Why today’s market reflects complacency despite uncertainty
05:20 Valuations, concentration, and optimism in current markets
08:52 Lessons from 1999 and how value investing can outperform in downturns
12:00 Durability, resilience, and why balance sheets matter more now
15:21 Kodak, disruption, and risks of passive investing
18:00 Perception vs reality of risk and behavioral mistakes
21:51 Market structure, moral hazard, and the “buy the dip” mindset
26:34 How investors should think about AI as a long-term technology shift
29:30 Why picking early AI winners is dangerous
33:00 The role of enablers like semiconductors, energy, and infrastructure
36:00 AI users and which companies benefit most from adoption
38:00 Businesses protected from disruption vs “walking dead” companies
42:00 The biggest investing mistake: selling great companies too early
46:00 Portfolio concentration and lessons from real-world experience
50:00 Berkshire Hathaway, long-term culture, and durable business models
54:00 Learning from mistakes: Costco case study
57:00 The importance of management and why people matter more than investors think

Risks Hiding in Plain Sight
https://www.informedmomentum.com/risks-hiding-in-plain-sight-how-the-dominance-of-passive-investing-is-reshaping-market-risk/

Is Quality Broken?
https://www.informedmomentum.com/is-quality-broken-ai-driven-disruption-is-testing-standard-definitions-of-quality/

Buy High, Sell Higher
https://www.informedmomentum.com/buy-high-sell-higher/

Topics Covered:

• The hidden divergence beneath index performance and why the market isn’t as stable as it looks
• Why value and momentum are working together—and what that signals about market broadening
• How AI and deglobalization are driving a major regime shift in markets
• Why momentum investors ignore narratives and focus purely on what’s working
• The structural risks created by the rise of passive investing and index concentration
• How tracking error replaced real risk—and why that may be dangerous
• Why quality stocks (especially software) are under pressure in the AI era
• The key insight behind 52-week highs as a powerful momentum signal
• Why buying stocks near highs works despite investor intuition
• How momentum strategies adapt to changing leadership and market regimes
• The importance of combining factors like value, momentum, and quality for long-term success

Timestamps:

00:00 Intro and major market shifts
01:32 Market divergence beneath the surface
03:00 Factor performance and broadening market trends
05:13 Why market concentration hurts factor investing
06:48 AI and deglobalization as structural drivers
08:14 Does this environment change how you invest?
11:02 Has the market sped up? Momentum implications
14:00 Passive investing and hidden structural risks
17:00 Tracking error vs real risk in portfolios
19:00 AI as a potential change agent for markets
21:09 How passive flows impact factor investing
24:00 What defines “quality” in factor investing
27:04 Why software and quality are under pressure
29:13 AI disruption and changing expectations
32:20 How to evaluate factor underperformance
34:35 Comparing today’s market to the 1990s
37:38 Buy high, sell higher: 52-week highs
41:00 52-week highs vs traditional momentum
43:20 Combining signals for better outcomes
46:00 Why 52-week highs improve downside protection
48:17 What momentum is picking up today
50:21 Misconceptions about momentum and growth
52:12 Timing and implementation of momentum
54:18 Momentum reversals and market behavior
57:17 Future research and improving momentum signals

Semper Augustus Investments
https://www.semperaugustus.com

Topics covered:

• Why extreme market concentration in the Mag 7 may create long-term risks

• The concept of a “secular plateau” vs a market peak

• How AI capex could become a classic capital cycle with poor returns

• Why hyperscaler spending may not translate into shareholder profits

• The hidden risks of leverage both on and off balance sheets

• Why buy-and-hold investing is harder than it seems in practice

• How valuation discipline drives long-term investment outcomes

• Berkshire Hathaway’s cash position and what it signals about opportunity

• Why capital allocation matters more than growth narratives

• Lessons from past bubbles including railroads, fiber, and the Nifty Fifty

• The fragility of life and how it shapes investing priorities

• The importance of independent thinking in the age of AI

Timestamps:
00:00 Intro
05:12 The “Both Sides Now” framework and AI theme
09:03 Secular peak vs secular plateau in markets
13:08 Leverage risks and balance sheet quality
17:42 Why passive investors are more concentrated than they think
21:12 The limits of long-term compounding and disruption risk
25:06 Why valuation matters more than “forever stocks”
29:10 Portfolio construction and return on capital differences
33:18 AI capex boom and capital cycle parallels
37:05 Why hyperscaler spending may not generate adequate returns
41:12 The math problem behind AI investment returns
45:10 Competition, redundancy, and pricing pressure in AI
49:02 Is AI an existential risk for big tech?
52:06 Berkshire Hathaway’s cash and Apple sales
56:08 Capital allocation lessons from Coca-Cola vs Apple
59:20 What Berkshire’s cash signals about future opportunities
01:02:10 The fragility of life and investing priorities
01:05:28 Final lessons for investors: reading, skepticism, and independent thinking

Rosenberg Research
https://www.rosenbergresearch.com

Topics Covered

• Why markets may be a “bubble in behavior,” not technology

• The equity risk premium at zero and what that implies for future returns

• CAPE valuations and why long-term returns could be flat to negative

• The shift from economy driving markets to markets driving the economy

• The “silent contraction” beneath strong GDP headlines

• AI-driven productivity vs weakening labor markets

• The K-shaped economy across consumers, jobs, and capital spending

• Why the savings rate is the most important overlooked economic variable

• Inflation outlook: why this shock may be disinflationary, not persistent

• Portfolio construction in a low-return, high-uncertainty environment

Timestamps
00:00 Intro
04:42 Cycle thinking vs “perma bear” label
09:58 Learning probabilistic thinking and Plan B
15:52 The “sixth mega bubble” and investor behavior
20:36 Why valuations imply poor forward returns
25:08 The “silent contraction” beneath headline data
29:14 The savings rate and equity wealth effect
33:12 Fiscal deficits and artificial economic support
38:28 2027 outlook and shifting probabilities
43:02 Why expectations matter more than recession calls
45:40 Inflation shock vs wage-driven inflation
49:22 Productivity boom and disinflation forces
53:10 Why inflation may fall faster than expected
55:04 Portfolio positioning and diversification strategy
01:00:12 Tactical vs thematic investing framework
01:03:10 Final thoughts on risk, probabilities, and markets

Spectra Markets
https://www.spectramarkets.com

Topics covered:

• Why stocks need a steady stream of bad news to go down and what drives rallies

• The impact of constant policy shocks on volatility, positioning, and mean reversion

• How to distinguish structural trends from short-term trading opportunities

• The “wall of worry” and why markets can ignore negative headlines

• The importance of Mag 7 earnings and concentration in today’s market

• How traders use reassessment triggers like the 200-day moving average

• The complexity of central bank reactions to oil shocks and inflation

• Why bonds still matter as a recession hedge despite recent correlation breakdowns

• How positioning—not fundamentals—drives moves in the U.S. dollar

• Gold, silver, and Bitcoin through the lens of flows, retail behavior, and debasement

• The role of overconfidence and risk management in trading success

• Brent’s journaling process and how writing clarifies thinking

• How to identify asymmetric trades using potential headline scenarios

• Why edges in markets are temporary and require constant adaptation

Timestamps:
00:00 Intro
02:05 Government policy shocks and market impact
05:10 Volatility, shocks, and trading frameworks
09:05 Why the economy remains resilient despite rate hikes
13:05 Market concentration and the importance of big tech earnings
16:05 The “steady stream of bad news” framework for stocks
18:30 Using the 200-day moving average and pattern recognition
22:10 Central banks, oil shocks, and inflation dynamics
24:35 Stocks vs bonds and the 60/40 portfolio outlook
26:05 Why dollar moves depend on positioning, not narratives
30:55 Gold, silver, and the retail-driven momentum cycle
34:05 The debasement trade and long-term gold thesis
38:10 Rationality vs overconfidence in trading
41:05 Risk management, journaling, and avoiding blowups
46:00 Thinking in probabilities, positioning, and market expectations
50:55 Journaling as a tool for clarity and discipline
55:00 Why traders lose discipline when over-earning
59:10 Brent’s new book and evolving trading frameworks
01:03:30 Where to find Brent and closing thoughts

Follow Liz Ann on Twitter
https://twitter.com/LizAnnSonders

Liz Ann's Research and Commentaryhttps://www.schwab.com/learn/author/liz-ann-sondersTopics Covered

• How war and oil shocks are impacting markets, inflation, and Fed policy

• Why the US being a “net energy exporter” doesn’t protect investors

• The hidden bear market beneath index-level resilience

• Rotation vs. correction and what it means for portfolios

• The rise of retail traders and the shift away from “dumb money”

• Why better or worse data matters more than good or bad data

• The K-shaped economy and its impact on consumption and markets

• AI’s three phases and its real impact on jobs and productivity

• Why this earnings season may be more important than usual

• The shifting role of the Mag 7 and broader market participation

• Why the bond market may be the true driver of equities

• Risks in credit markets and what investors should watch

• Labor market dynamics and challenges for younger workers

• How investors and young professionals should think about AI

Timestamps
00:00 Intro and current market environment
04:05 Why the US isn’t immune to oil price shocks
05:35 Lessons from past oil shocks and inflation
07:22 Why markets seem resilient despite macro risks
08:00 The hidden drawdowns beneath the index surface
10:13 Rolling recessions and sector-level weakness
10:37 Are investors conditioned to buy every dip
12:58 What happens when the dip doesn’t get bought
14:36 Valuations, corrections, and market structure
15:12 Sentiment analysis in a new market regime
18:50 Retail investors outperforming institutions
20:08 Better or worse vs good or bad economic data
23:00 How markets anticipate economic turning points
25:22 Understanding the K-shaped economy
28:00 Wealth effects and risks from equity declines
29:09 AI as a transformative force vs macro risks
30:00 The three phases of AI development
33:04 Why this earnings season matters more
34:00 Earnings revisions and sector concentration
36:00 The future of Mag 7 leadership vs the rest of the market
38:00 Contribution vs performance in index returns
40:00 Sector sensitivity to inflation and supply chains
42:00 Fundamentals vs speculation in small caps
44:21 The Fed’s dilemma in an oil shock environment
48:00 Why the bond market is driving equities
50:05 Credit markets and systemic risk signals
53:26 Lessons from past bond market dislocations
54:19 Labor market challenges and younger workers
57:00 Career advice in the age of AI
59:26 How Liz Ann uses AI in her research process
01:01:00 Closing thoughts and where to follow Liz Ann

Grant’s Interest Rate Observer
https://www.grantspub.com/

Topics Covered:

• Why war is inherently inflationary and how it strains the productive economy

• The difference between measured economic stability and underlying systemic risks

• How inflation shifted from a wartime phenomenon to a permanent feature of modern monetary policy

• The Fed’s 2% inflation target as a structural form of currency debasement

• Lessons from the 1970s inflation and oil shocks vs. today’s environment

• Why inflation is a ratchet that erodes purchasing power over time

• The importance of trust in credit markets and growing risks in private credit structures

• Public debt, Treasury market dynamics, and early signs of strain in government financing

• Historical parallels between AI investment and past technological booms like the internet

• The role of gold as a hedge against (and investment in) monetary instability

• The durability of the US dollar despite long-term structural concerns

• Why investing is always difficult in the present—even when it looks obvious in hindsight

Timestamps:
00:00 Intro and Jim Grant on the true causes of inflation
04:04 Why war drives sustained inflation and current geopolitical risks
08:00 Historical perspective on inflation before the 1970s
12:00 Oil shocks, Volcker, and lessons from past inflation cycles
16:00 Why inflation never reverses and purchasing power declines
20:00 Trust in markets and the foundation of credit systems
24:00 Private credit risks and the modern credit cycle
28:00 Public debt, Treasury markets, and fiscal sustainability concerns
32:00 Treasury auctions, yields, and early warning signs in bonds
35:25 AI capex boom and lessons from past technological bubbles
38:17 Air conditioning, internet bubbles, and delayed economic payoffs
40:00 The Fed, Treasury, and hidden financial interdependence
44:14 Asset allocation, gold, and monetary disruption
48:44 The dollar’s strength and global dominance
53:41 Why investing is always difficult in real time
59:00 Advice on markets, newsletters, and enduring uncertainty

Subscribe to the OPEX Effect on Spotify⁠⁠

⁠⁠Subscribe to the OPEX Effect on Apple Podcasts

This episode of The Opex Effect breaks down why markets have remained surprisingly resilient despite geopolitical chaos, an oil shock, and extreme headline risk. Brent Kochuba joins Jack Forehand to analyze what’s really driving the market beneath the surface—from options flows and gamma positioning to the collapse in volatility and what it signals for the next move.

They explore how the options market is shaping price action in ways most investors miss, why the VIX collapsed despite elevated risk, and what positioning tells us about the path forward as we head into earnings and the next major options expiration.

Topics covered:

• Why markets have stayed near highs despite war, oil spikes, and macro uncertainty

• The “taco trade” and why investors expect bad news to reverse quickly

• How options flows and dealer hedging are influencing stock prices

• Why call options are historically cheap heading into earnings

• The mechanics of gamma, delta hedging, and market maker positioning

• Why options expiration (OpEx) can act as a turning point for markets

• The divergence between oil prices and equity volatility

• What the collapse in the VIX reveals about investor positioning

• The role of zero-DTE options in reinforcing short-term market ranges

• Key resistance levels forming from call selling and what they mean for upside

Timestamps:

00:00 Why markets aren’t reacting to geopolitical chaos
04:18 The “taco trade” and shifting market expectations
07:30 How options flows influence stock market movements
11:10 Why OpEx can drive market turning points
13:05 Volatility compression and the gamma-volatility relationship
15:30 How large options positioning shapes market behavior
18:05 Why positioning has shifted toward calls
20:00 Why this OpEx may be less impactful than prior ones
22:00 Market positioning into earnings and key drivers ahead
24:10 Using gamma maps to identify support and resistance
27:00 Revisiting the JP Morgan collar trade and March lows
30:00 Correlation spikes and the oil-volatility relationship
33:00 Why oil has stopped driving equity volatility
34:30 The breakdown between oil and VIX correlation
36:00 Why volatility may reprice higher after OpEx
37:05 The oil curve and expectations for a short-term shock
39:40 One of the largest VIX collapses ever
41:00 How options positioning drove the volatility unwind
43:00 Why selling volatility has become a dominant strategy
45:00 The feedback loop between rising markets and falling volatility

For more information on SpotGamma and Brent’s work:
https://spotgamma.com

Follow Brent on Twitter:
https://twitter.com/spotgamma

Subscribe to the Jim Paulsen Show on Spotify⁠

⁠Subscribe to the Jim Paulsen Show on Apple Podcasts

Jim walks through a wide range of charts and frameworks, from the Walmart vs. luxury retail signal to private credit stress, productivity trends, and policy uncertainty, offering a data-driven perspective on where markets and the economy may be headed next.

Paulsen Perspectives Substack
https://paulsenperspectives.substack.com

Topics Covered

• Why the recent oil spike hasn’t impacted inflation and interest rates as expected

• Slowing economic growth vs. recession risk and what the Fed might do next

• The Walmart vs luxury retail indicator and what it signals about the economy

• Private credit risks and how they differ from traditional credit crises

• Why many indicators point to a new bull market rather than a bear

• The role of sentiment, volatility, and uncertainty in driving market returns

• Market rotation from mega-cap “new era” stocks to broader market leadership

• Corporate profits divergence and the opportunity in the rest of the economy

• Liquidity, cash levels, and positioning as potential fuel for markets

• Productivity trends and whether AI-driven gains are real or overstated

Timestamps
00:00 Intro and current macro backdrop
01:05 Oil spike and limited impact on yields and inflation
04:45 Growth outlook and why recession may still be avoided
07:10 Fed policy and the stagflation question
10:15 Walmart vs luxury retail indicator explained
13:40 Private credit stress vs traditional credit cycles
17:00 Why this isn’t 2008 and how balance sheets differ
19:50 Private credit risks and market spillover effects
22:15 Bear market fears vs signs of a new bull
23:45 Consumer confidence and its impact on returns
25:05 Oil spikes historically as buy signals
26:15 VIX, volatility, and market bottoms
27:05 Yield curve steepening and market implications
28:05 Sentiment indicators and what they really reflect
30:00 Market rotation and broadening beyond mega caps
32:45 Passing the baton from tech to broader markets
35:15 Corporate profits divergence and future potential
37:00 Policy uncertainty and why it can be bullish
42:05 Liquidity, cash levels, and risk allocation
43:20 Options positioning and put-call signals
44:05 Gold vs commodities and risk appetite
45:10 Consumer credit contraction and market signals
46:20 Polymarket recession probabilities as sentiment
47:30 Economic sentiment collapse and contrarian signals
48:10 Interest rate expectations and positioning
49:05 Unemployment trends and historical market bottoms
50:25 Productivity trends and AI impact on the economy

T. Rowe Price Science and Technology Fund
https://www.troweprice.com/financial-intermediary/us/en/investments/mutual-funds/us-products/science-and-technology-fund.htmlTopics Covered

• What it means to invest in “inevitabilities” and separating signal from noise in markets

• Why AI and compute demand represent a structural shift similar to past tech waves

• The rise of agentic AI and how it could transform software and productivity

• Whether AI is underappreciated or already priced into markets

• The “multiple moons” idea and why AI may not be a winner-take-all market

• How AI could reshape the labor market, productivity, and economic growth

• The AI CapEx debate and why this cycle may differ from the dot-com buildout

• Where we are in the AI cycle: training vs inferencing and deployment phase

• The impact of AI on software companies and the innovator’s dilemma

• How semiconductors, memory, and infrastructure remain key bottlenecks

• The changing nature of the Mag 7 and capital intensity in AI

• Tony’s portfolio construction framework across compounders, emerging tech, and value

• How he generates ideas using S-curve adoption and economic bottlenecks

• Position sizing, risk management, and balancing growth with drawdown control

• Sell discipline: valuation, fundamentals, and market signals

Timestamps
00:00 Introduction and Tony Wang overview
01:05 Investing in inevitabilities and long-term thinking
03:00 Differentiating inevitability from hype and consensus
04:45 AI inevitability and the rise of agentic systems
07:00 Cost of intelligence and productivity implications
08:00 Real-world examples of AI adoption (customer service, agents)
09:00 Is AI underappreciated by markets?
11:15 AI as a “space race with multiple moons”
13:30 AI as the dominant driver of markets today
15:00 AI’s impact on jobs, productivity, and the economy
18:30 Creativity, judgment, and the future of work
20:45 Physical AI and robotics opportunity set
22:30 AI CapEx debate vs the dot-com era
25:30 Semiconductors vs software in the AI stack
28:15 AI disruption risk for software companies
31:00 Cyclicality in semiconductors and how AI changes it
33:30 The evolving role of the Mag 7 in AI
36:30 Competition, startups, and AI democratization
38:00 Where we are in the AI cycle today
40:00 Idea generation and S-curve adoption framework
42:30 Case study: memory and AI bottlenecks
44:45 Example position: optical networking and infrastructure
46:40 Portfolio construction and position sizing
49:00 Sell discipline and managing valuation risk

https://www.fairleadstrategies.com/

Topics Covered:

• Why a new monthly MACD sell signal may signal a longer, choppier market phase

• The difference between fast corrections and slow grind bear phases

• Key S&P 500 support levels and what a breakdown could mean for downside risk

• How technical indicators help filter noise in headline-driven markets

• The breakout in crude oil and what it signals about a potential new cycle

• Whether sharp price moves are sustainable or likely to reverse

• Understanding overbought and oversold conditions across different timeframes

• Why mega-cap weakness is critical to overall market direction

• The shift from growth to value and what it means for investors

• Sector rotation trends and where leadership is emerging in 2025

• What gold’s recent run and emerging weakness signal for safe haven assets

• How a systematic, technical approach can help manage drawdowns and re-entry timing

Timestamps:
00:00 Intro
04:18 S&P 500 momentum deterioration and MACD sell signal
08:09 Key support levels and downside scenarios for equities
12:53 Crude oil breakout and implications for a new cycle
16:01 What overbought and oversold really mean in practice
20:04 Mega-cap weakness and shifting market leadership
24:41 Concentration risk in investor portfolios
27:52 Value vs growth rotation and cycle dynamics
32:13 Market breadth and confirmation signals
36:19 Moving averages, death cross, and trend interpretation
39:56 Inside the TAC ETF and sector rotation strategy
44:04 Gold trends and why consolidation may be next
47:00 Key signals to watch going forward

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The conversation moves from base rates and AI growth expectations to competitive dynamics, capital cycles, and the fundamental shift toward intangible-driven business models that are changing how we think about valuation, moats, and market structure.

Papers and Resources Discussed:

Bayes and Base Rates: How History Can Guide Our Assessment of the Future
https://www.morganstanley.com/im/en-us/institutional-investor/insights/consilient-observer/bayes-and-base-rates.html

The Impact of Intangibles on Base Rates
https://www.morganstanley.com/im/publication/insights/articles/article_theimpactofintangiblesonbaserates.pdf

Measuring the Moat: Assessing the Magnitude and Sustainability of Value Creation
https://www.morganstanley.com/im/publication/insights/articles/article_measuringthemoat.pdf

One Job: Expectations and the Role of Intangible Investments
https://www.morganstanley.com/im/publication/insights/articles/article_onejob.pdf

Capitalism Without Capital: The Rise of the Intangible Economy
https://books.google.com/books/about/Capitalism_without_Capital.html?id=J3SYDwAAQBAJ

A Better Estimate of Internally Generated Intangible Capital
https://pubsonline.informs.org/doi/10.1287/mnsc.2022.01703

Underestimating the Red Queen: Measuring Growth and Maintenance Investments
https://www.morganstanley.com/im/publication/insights/articles/article_underestimatingtheredqueen.pdf

Explaining the Recent Failure of Value Investing
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3442539

Guest Links:

Michael Mauboussin Twitter

Topics Covered:

• Why OpenAI’s projected growth would be unprecedented in market history

• How base rates provide a reality check on AI expectations

• The role of diffusion models and adoption curves in forecasting technology

• Why massive capital investment in AI may follow past boom-bust cycles

• Lessons from large-scale infrastructure projects and why timelines break

• How intangible assets change the distribution of business outcomes

• The rise of “fat tails” and why more companies now massively win or fail

• Who captures value in AI across the stack from chips to applications

• Why competition may drive AI profits toward consumers, not producers

• How accounting distorts intangible investment and misleads investors

Timestamps:

00:00 Intro and OpenAI growth expectations vs historical base rates
04:32 Why no company has ever achieved 100%+ sustained growth at scale
08:47 Lessons from megaprojects and AI infrastructure buildouts
13:18 Intangible assets and why outcomes now have fatter tails
18:36 Why big tech is growing faster than historical precedents
23:52 Where value accrues in AI and why consumers may benefit most
28:21 Barriers to entry in AI including capital, talent, and scale
32:47 The risk of overinvestment and historical parallels to past bubbles
37:26 Game theory and competitive signaling in AI capital spending
41:58 Why investment returns—not “asset light” narratives—drive value
46:12 How accounting fails to capture intangible investment properly
50:44 Breaking down SG&A into maintenance vs investment spending
55:03 Why understanding reinvestment and ROI is the core investing skill
59:18 Final thoughts on uncertainty, expectations, and base rates in AI

Prometheus Research
https://www.prometheus-research.com

Aahan Menon Twitter
https://x.com/@AahanPrometheus

• Why the current inflation shock may be one of the most significant in recent history

• How oil prices and geopolitical conflict are reshaping macro expectations

• The growing risk of a stagflationary environment and what it means for portfolios

• Why traditional 60/40 portfolios may struggle in sustained inflation regimes

• How expected returns differ across equities, bonds, commodities, and FX

• Why commodities and energy markets offer the most attractive opportunities today

• The role of backwardation and supply shocks in driving commodity returns

• Why consensus earnings expectations may be too optimistic relative to macro reality

• How inflation flows through the economy from energy to consumer demand

• The Fed’s dilemma between inflation control and economic slowdown

• A simple rule for when to own treasuries based on inflation trends

• Why correlations across asset classes are breaking down in crisis environments

• How systematic investors manage risk when markets are driven by news and geopolitics

• The case for trend following as a core portfolio strategy

• How Aahan’s free trend system works across stocks, bonds, gold, and Bitcoin

• The behavioral advantages of systematic investing during volatile markets

• Risks of trend following including whipsaws and false signals

• How portfolio construction is evolving to include crisis protection and energy overlays

00:00 Inflation shock and why equities and bonds may struggle
01:03 Setting up the macro backdrop before the oil shock
03:12 Labor market slowdown vs strong GDP divergence
04:45 Consumer spending driven by de-saving
05:35 Oil-driven inflation shock as a recession catalyst
07:32 Preparing for stagflation vs disinflationary growth
09:18 Why commodities outperform in inflation regimes
10:45 Expected returns framework across asset classes
12:05 Why commodities and FX offer the best opportunities
14:05 How commodity carry and backwardation work
16:42 Trend following and commodities as pro-cyclical exposures
17:43 Ranking expected returns: energy, FX, bonds, equities
18:51 Challenges of systematic investing in news-driven markets
20:15 Extreme correlations and oil dominating asset pricing
23:47 Earnings expectations vs macro reality gap
28:30 Why the Fed faces an impossible policy tradeoff
30:00 Real-time CPI estimates and inflation pressure
32:00 A rule for when to own treasuries based on CPI
37:30 Stock-bond correlation regime shifts
39:34 How the trend following system works
45:10 Benefits and limitations of trend strategies

Harris Kupperman Twitter
https://twitter.com/HedgeyeKuppy

Praetorian Capital Website
https://praetorian-capital.com

Timestamps
00:00 Why the U.S. stock market is structurally overvalued
01:14 What “inflection investing” means
02:54 Top-down vs bottom-up investing framework
04:31 Using politics to identify winning trades
05:00 Argentina trade setup and execution
06:20 Why the Argentine stock exchange is the best play
08:00 Earnings inflection and multiple expansion potential
10:37 Time horizon and holding period strategy
13:00 When to exit positions and recycle capital
18:41 How and when to raise cash
19:41 De-grossing the portfolio during crises
23:14 Real-time decision making during war scenarios
27:00 Building a shopping list during dislocations
29:32 ETF vs individual stock decision process
33:22 Why the U.S. is less attractive than global markets
38:17 The problem with AI-driven “growth”
43:31 Monitoring vs acting across global opportunities
48:14 The psychology of long-term investing and edge

Follow Last Call on Spotify⁠⁠⁠

⁠⁠⁠Follow Last Call on Apple Podcasts⁠

Jack and Matt bring together Andy Constan, Ben Hunt, Brent Kochuba, and Eric Pachman to analyze the ripple effects of higher oil prices, the “common knowledge” shift in markets, the role of options flows in driving short-term moves, and why traditional economic indicators like unemployment may be telling a misleading story.

Andy Constan Twitter
https://x.com/dampedspring

Ben Hunt Twitter
https://x.com/EpsilonTheory

Brent Kochuba Twitter
https://x.com/spotgamma

Eric Pachman Twitter
https://x.com/epachman

Topics covered:

• How oil supply shocks impact GDP, inflation, and consumer spending

• Why higher oil prices act as a tax on the economy and shift growth dynamics

• The difference between supply shocks and demand shocks in energy markets

• Why central banks may be unable to respond to an oil-driven slowdown

• The “common knowledge” framework and how narratives reshape markets

• Why the Strait of Hormuz has become the key global economic bottleneck

• Oil exporters vs importers and how that divide is driving asset performance

• Why energy equities may outperform in a prolonged geopolitical conflict

• How volatility is being driven by oil prices and geopolitical risk

• The relationship between VIX and oil during crisis periods

• Why $100 oil could trigger a major volatility spike and equity selloff

• The JP Morgan collar trade and how options positioning can pin markets

• How dealer hedging flows influence short-term price action

• Why markets may appear disconnected from negative news

• The limits of predicting what is “priced in” during uncertain environments

• Why diversification matters more when macro visibility is low

• How unemployment data can mislead by excluding people leaving the workforce

• The difference between unemployment rate and labor force participation

• Structural decline in rural economies and the migration to urban centers

• How labor force trends explain the divergence in economic experiences across the US

Timestamps:
00:00 Oil shock as a GDP tax on consumers
00:16 Strait of Hormuz as global economic chokepoint
00:29 Why $100 oil could send VIX to 50
00:39 Why unemployment rate may be misleading
01:07 What Last Call is and how the episode is structured
02:28 Macro, narrative, and flows framework for markets
03:44 How oil supply shocks impact growth and inflation
06:00 Why higher oil prices reduce discretionary spending
07:00 Oil’s impact on inflation and central bank policy
09:39 Scenario analysis for oil prices and market outcomes
12:28 Is the oil shock priced into markets?
16:00 Why oil vs assets may be mispriced
20:00 Ben Hunt on the “common knowledge” market shift
25:00 Why the Strait of Hormuz changes everything
29:00 Portfolio implications: long energy vs global equities
33:00 Brent Kochuba on oil, VIX, and market volatility linkage
36:00 Why $100 oil is the key risk threshold for equities
40:00 JP Morgan collar trade and market pinning dynamics
44:00 Why options flows can override macro narratives short term
52:00 Eric Pachman on unemployment vs labor force reality
59:00 Structural decline in labor force across US counties

Larry Swedroe Twitter
https://twitter.com/larryswedroe

Larry Swedroe Substack
https://larryswedroe.substack.com

Topics covered

• What private credit is and how it evolved after the 2008 financial crisis

• Why private credit is not a single asset class and how risk varies across structures

• The three key risks in private credit: credit risk, liquidity risk, and concentration risk

• How illiquidity premiums work and why they can be a major source of return

• Differences between private credit funds, BDCs, and open architecture platforms

• Why diversification is critical and how concentration risk can be hidden

• How rising interest rates are impacting defaults and underwriting standards

• Media misconceptions around defaults, losses, and valuation marks in private credit

• The real systemic risk of private credit vs the banking system

• How liquidity actually works in interval funds and stress scenarios

• What happens in a recession and how private credit compares to equities and high yield bonds

• The role of software lending and how AI disruption could impact credit portfolios

• How to evaluate private credit managers including scale, underwriting, and leverage

• The importance of credit culture and avoiding “reach for yield” behavior

• Whether private credit should be accessible to retail investors and the risks involved

• The concept of earning “beta” in private credit vs trying to pick winning managers

• AI’s growing role in investment research and the risks of overfitting and false signals

Timestamps
00:00 Why private credit is less risky than banks for systemic stability
01:12 Introduction and episode overview
03:00 What private credit is and how it grew after 2008
05:21 Who provides capital to private credit funds
07:11 Why private credit is not a monolithic asset class
08:00 The three key risks in private credit
09:00 Illiquidity premium and why it can be a “near free lunch”
12:00 Credit risk and importance of senior secured lending
16:00 Concentration risk and why diversification matters
18:11 Are defaults rising and what the data actually shows
21:00 Media narratives vs actual credit losses
23:50 Could private credit cause a financial crisis
25:50 How to analyze portfolios and why most investors can’t
28:44 Should investors think about indexing private credit
30:12 Can private credit work for retail investors
32:26 Mass redemption risk and liquidity stress scenarios
36:00 Sources of liquidity inside private credit funds
41:37 Software lending and AI disruption risk
47:00 Private equity valuations and spillover into credit risk
49:43 Key checklist for evaluating private credit investments
56:30 How AI is changing financial research and investing

Bob Elliott on Twitter
https://twitter.com/BobEUnlimited

Unlimited Funds website
https://www.unlimitedfunds.com

Topics covered

• The shift from an income-driven economy to a savings-driven economy and why it creates fragility

• Why an oil shock acts as both an inflation driver and a tax on real consumer spending

• How higher gas prices mechanically reduce discretionary spending and economic growth

• Why markets may be underpricing the economic impact of the current oil shock

• The link between oil prices, inflation expectations, and real demand destruction

• How global markets respond to shocks through deleveraging and volatility spikes

• Why gold and other winning trades can fall during risk-off environments

• The sequencing of inflation first and growth slowdown later in shock-driven cycles

• How central banks are likely to respond to a stagflationary shock

• Lessons from 2022 and 2008 for understanding today’s macro environment

• Why stocks and bonds may both be mispriced in the current regime

• The difference between consumer surplus and true productivity gains from AI

• Why AI-driven job losses and economic growth cannot coexist without major dissaving

• The most likely path for AI as a productivity enhancer rather than a job destroyer

• How to think about measuring productivity in a technology-driven economy

• The role of second- and third-order effects in macro investing

• How global macro strategies identify mispricings across asset classes

• The concept of using the “wisdom of the crowd” from hedge fund positioning

• Why macro strategies can perform in both rising and falling markets

• How macro fits into a portfolio as a diversifier versus long-only assets

• Why the future investment environment may require broader strategy diversification

Timestamps

00:00 Oil shock meets a savings-driven economy
01:00 Framing the macro environment: oil, inflation, and growth
02:12 What a savings-driven economy means for market fragility
04:46 Why household income vs spending divergence matters
07:00 First principles of an oil shock and demand inelasticity
08:00 How oil price spikes flow through to inflation
13:00 Global market reactions and emerging market dynamics
14:00 Deleveraging and volatility driving asset price reversals
15:44 Why gold declines during macro stress events
17:17 Institutional positioning and ETF flows in gold
17:34 Inflation first, growth slowdown later: sequencing the impact
19:24 Is the economic damage already done
22:00 How macro investors operate in low-conviction environments
29:19 What the Fed should do versus what it will do
31:00 Comparing today’s environment to 2022 inflation dynamics
33:00 Why markets are pricing in almost nothing
34:00 AI and the link between labor, income, and spending
37:11 Productivity vs consumer surplus in AI adoption
40:00 Why better tools don’t necessarily mean higher productivity
s
46:00 How global macro strategies are constructed
48:00 Using hedge fund positioning as a signal
56:00 Why the opportunity set for macro may be expanding

Subscribe to the 100 Year Thinkers of Spotify⁠

⁠Subscribe to the 100 Year Thinkers of Apple

In this episode of our new show, 100 Year Thinkers, Robert Hagstrom and Chris Mayer explore how investors should think about base rates, extreme outcomes, and the realities of long-term wealth creation in markets. Applying the work of Michael Mauboussin, the conversation challenges conventional ideas like mean reversion and highlights why a small number of companies drive most stock market returns—and what that means for portfolio construction.

This episode brings together Robert Hagstrom and Chris Mayer to explore how investors should think about base rates, extreme outcomes, and the realities of long-term wealth creation in markets. The conversation challenges conventional ideas like mean reversion and highlights why a small number of companies drive most stock market returns—and what that means for portfolio construction.

Topics covered
• Why markets are driven by extreme outcomes and power laws, not averages
• The Best & Bessembinder research showing a handful of stocks create most wealth
• Base rates vs outliers and when to trust historical probabilities
• Why the 100 bagger framework focuses on studying winners, not predicting them
• Portfolio construction as a way to capture asymmetric upside
• Buffett’s approach to consistency, durability, and long-term operating history
• Inside view vs outside view and how narratives distort investing decisions
• Why AI may be breaking traditional base rate assumptions in software and tech
• The limits of mean reversion and why it can lead investors astray
• Return on invested capital and how competition erodes excess returns over time
• Identifying durable moats and why most advantages eventually get attacked
• Winner-take-all dynamics and how they shape long-term investing outcomes
• The twin engines of returns: earnings growth and multiple expansion
• Return on incremental capital as a key driver of long-term compounding
• Intangible assets and why accounting understates true business value
• Amazon as a case study in misunderstood profitability and reinvestment
• AI CapEx cycle and why current spending may not be sustainable long term
• Why great businesses matter more than great management in long-term investing

Timestamps
00:00 Why extreme outcomes drive stock market returns
01:00 Base rates vs studying 100 baggers
03:00 Power laws and why markets are a game of outliers
05:00 Just 46 companies created half of all market wealth
07:00 Buffett on consistency and long-term operating history
10:00 How to think about base rates in AI, energy, and macro cycles
12:00 Does AI invalidate historical base rates?
15:00 Inside view vs outside view in investment decision making
19:00 Buffett’s “certainty at a discount” framework
23:00 How often investors should evaluate businesses vs prices
29:00 Mean reversion myths and where it breaks down
33:00 Return on invested capital and competitive pressure
36:00 Moats, winner-take-all markets, and long-term dominance
41:00 Twin engines of compounding: growth plus multiple expansion
43:00 Return on incremental capital and forecasting future returns
47:00 Intangibles and why accounting distorts real business value
50:00 Amazon, CapEx cycles, and hidden profitability
53:00 AI infrastructure buildout and the future of returns

Subscribe to the OPEX Effect on Spotify⁠

⁠Subscribe to the OPEX Effect on Apple Podcasts

This episode breaks down the growing tension beneath the surface of today’s markets, where volatility signals, options positioning, and macro risks like war and inflation are increasingly misaligned. Brent Kochuba and Jack Forehand explain why markets appear calm despite heavy hedging, and what that disconnect could mean for a potential volatility spike and downside move ahead.

Brent Kochuba on Twitter
https://twitter.com/SpotGamma

SpotGamma Website
https://spotgamma.com

Topics covered in this episode

• Why volatility looks elevated beneath the surface even as markets remain relatively calm
• The growing gap between implied volatility VIX and realized volatility and what it signals
• How options expiration OPEX can create turning points in both price and volatility
• Why current positioning is unusually put-heavy and what that means for downside risk
• The role of market makers and hedging flows in driving market moves
• How geopolitical risks like the Iran conflict are changing options behavior and hedging demand
• Why correlation is spiking and what it says about investors moving from stock picking to asset allocation
• The breakdown of traditional diversification including the 60/40 portfolio
• How credit markets and liquidity risks could amplify equity volatility
• The impact of zero DTE options and why traders are shifting to longer-duration hedges
• The significance of the JP Morgan collar trade and key levels to watch into month-end
• Why volatility spikes often follow periods of suppressed market movement
• The potential for a sharp upside rally if geopolitical risks suddenly resolve
• How options positioning can help both traders and long-term investors with timing decisions

Timestamps

00:00 Volatility premium vs low market movement disconnect
01:00 Why markets feel calm despite rising risks
05:20 Explosion in options volume and impact of Monday Wednesday Friday expirations
07:00 How market maker hedging flows drive price movements
08:40 Dynamic hedging and why options impact evolves over time
09:20 Why OPEX can trigger market turning points
10:30 VIX expiration effects and short-term volatility suppression
13:00 Negative gamma and how it amplifies market volatility
14:10 Why hedging demand remains high despite OPEX clearing
16:00 Jump risk scenario and potential VIX spike to 40
17:10 Shift from zero DTE trading to longer-term hedging
18:00 Put-heavy positioning across equities and indices
20:40 Size and significance of the current OPEX event
22:20 VIX spike dynamics around expiration
23:40 JP Morgan collar trade and key SPX levels
25:00 Why OPEX often marks short-term market lows or highs
28:30 Review of prior OPEX signals and market setup
30:00 Rising correlation and shift to asset allocation mindset
32:00 Dispersion breakdown and implications for equities
34:00 Software sector volatility and AI disruption narrative
36:30 Using options signals for better timing decisions
39:00 Correlation spike and risk-off behavior across markets
41:30 Why investors are avoiding calls and piling into puts
44:30 Cross-asset correlation breakdown and bond hedge failure
48:00 Credit market risks and spillover into equities
49:00 Extreme VIX vs realized volatility spread
50:50 Why realized volatility remains unusually low
52:30 Oil, inflation, and macro feedback loops

Jared Dillian Twitter
https://twitter.com/DailyDirtNap

Daily Dirt Nap
https://www.dailydirtnap.com

Topics Covered

• Why markets fail to price low-frequency, high-impact events like war and geopolitical shocks

• The concept of regime change and why investors struggle to adapt to new market environments

• The breakdown of the 60/40 portfolio and stock-bond correlation in an inflationary regime

• Commodities bull market dynamics and why energy, agriculture, and hard assets may outperform

• The role of options and “long gamma” positioning in uncertain macro environments

• Bitcoin as a liquidity trade vs. store of value and how sentiment drives crypto cycles

• Fed policy, oil prices, and why central banks follow the “path of least embarrassment”

• Inflation psychology, consumer behavior, and risks of 1970s-style market conditions

• Political bias in investing and how ideology shapes portfolio decisions

• Risks in private equity and private credit, including valuation marks and liquidity issues

• The Awesome Portfolio framework and why diversification across asset classes reduces drawdowns

• AI, productivity shifts, and how technological change impacts markets and labor trends

Timestamps

00:00 Why markets misprice geopolitical risk and regime change
02:00 Ukraine, Iran, and delayed market reactions to obvious risks
05:00 Overreaction cycles and the Peloton example
06:00 What it means to be long gamma in investing
09:00 Oil volatility and asymmetric risk opportunities
10:00 Regime change explained through stock-bond correlation breakdown
12:00 Non-stationarity and why investing rules constantly change
14:00 Why most investors fail to adapt to new regimes
17:00 Position sizing, risk management, and staying “small”
19:00 Commodities bull market and broad participation across assets
20:30 Bitcoin as a liquidity sponge and sentiment-driven asset
22:00 Fed policy, inflation, and the path of least embarrassment
25:00 Oil-driven inflation vs demand destruction dynamics
27:00 Inflation psychology and real-time indicators
29:00 Are we entering a 1970s-style macro regime
31:00 How political views shape investment strategies
35:00 Learning from past mistakes and adapting to new trends
37:00 Private equity and private credit valuation risks
40:00 Liquidity cycles and refinancing risk in credit markets
43:00 The Awesome Portfolio explained
46:00 Behavior, drawdowns, and why diversification works
49:00 Real estate allocation and portfolio construction
51:00 Labor trends, productivity, and changing work dynamics
54:00 AI productivity boom vs social media drag
57:00 The dangers of consensus thinking and unpopular views

D.A. Wallach – Twitter
https://x.com/DAWallach

Topics covered include

• Why biotech may be one of the last areas where specialist investors can generate persistent alpha
• The “bag of options” framework for valuing development-stage biotech companies
• How probabilities of drug success and clinical base rates drive biotech valuations
• Why rising interest rates hit biotech stocks harder than many other sectors
• How capital flows and investor narratives create boom-and-bust cycles in biotech
• What happened to biotech during the pandemic surge and the post-COVID downturn
• Why AI and tech narratives compete with biotech for investor attention
• The role of specialist biotech hedge funds in the public markets
• How large pharmaceutical companies drive returns through biotech acquisitions
• Differences between biotech venture capital and traditional tech venture investing
• How venture investors evaluate drug development programs and scientific evidence
• Portfolio construction and diversification when investing in highly uncertain biotech companies
• The emerging role of China in clinical trials and global drug development
• Whether AI can improve drug discovery, clinical trials, and pharmaceutical R&D productivity
• Why investors should avoid rigid value vs growth ideologies and stay adaptable

Timestamps

00:00 Why biotech investing requires specialized knowledge
01:40 Is biotech one of the last places for persistent active alpha?
02:45 The “bag of options” model for valuing biotech companies
05:00 Drug development phases and probabilities of success
07:00 Using base rates to estimate clinical trial success
09:20 Estimating total addressable markets for new drugs
11:10 Why rising interest rates hurt biotech valuations
13:00 Capital flows and why biotech underperformed in recent years
15:30 The biotech boom and bust around the COVID pandemic
18:00 How AI and tech compete with biotech for investor capital
22:20 The role of specialist biotech hedge funds
24:00 How pharmaceutical acquisitions drive biotech returns
25:20 How biotech venture capital differs from tech VC
30:50 Why biotech investors must evaluate complex scientific data
34:20 Where AI may improve drug discovery and R&D productivity
42:00 Portfolio construction and diversification in biotech venture investing
44:30 Volatility, valuation marks, and private market pricing
48:00 Managing risk across different drug technologies and disease areas
49:30 Why China is becoming important for clinical trials
53:00 Why biotech investing must be viewed as a global industry
54:30 The importance of flexibility between value and growth investing
58:50 Will investing become more systematic and quantitative over time

Follow Two Quants and a Financial Planner on Spotify⁠

⁠Follow Two Quants and a Financial Planner on Apple

In this episode, we break down the most important insights from the week on Excess Returns,, with insights from Vitaliy Katsenelson, Jim Paulsen, and Joseph Shaposhnik. Markets today are being shaped by powerful crosscurrents including AI disruption, defense spending, macro policy shifts, and historically high valuations. In this episode, we highlight the biggest ideas from our conversations and explore what they mean for investors trying to navigate an uncertain world. Topics include the importance of humility in investing, the potential disruption of software by AI, the growing divergence within the economy, and why long-term structural trends like defense spending may create new opportunities.
Topics Covered

• Why humility may be the most important trait for investors in a rapidly changing world
• How uncertainty around AI, geopolitics, and macro policy is widening the range of possible market outcomes
• Why some investors are reducing exposure to software businesses amid AI disruption
• The importance of management teams that can adapt and evolve in periods of technological change
• Jim Paulsen’s framework for understanding the “new era” economy versus the rest of the economy
• Why a small portion of the economy may now be driving overall GDP growth
• The idea that successful investing may be about being “least wrong” rather than perfectly right
• How long-term structural trends like defense spending could create a multi-year investment tailwind
• Why experienced investors focus on analyzing businesses rather than reacting to headlines
• The potential deflationary impact of AI and how lower prices could shift spending across the economy
• Why high market valuations may act as a headwind for future returns
• The importance of deep research and preparation when unexpected events hit markets
• Jim Paulsen’s concept of “policy juice” and how fiscal and monetary policy drive bull markets
• Whether a new wave of policy support could broaden the current market rally beyond mega-cap tech

Timestamps

00:00 Introduction
02:00 Why humility matters more than ever in investing
08:50 AI disruption and the future of software businesses
18:07 The growing gap between the “new era” economy and the rest of the economy
25:00 Surviving first and being the least wrong as an investor
31:43 The potential defense spending supercycle
37:44 AI’s deflationary impact and how innovation reshapes economies
44:42 Why valuations act as a long-term headwind for stocks
50:56 How investors should respond to geopolitical events
56:49 Jim Paulsen on policy juice and the future of the bull market

Follow Two Quants and a Financial Planner on Spotify

Follow Two Quants and a Financial Planner on Apple

In this new weekly Excess Returns recap, Jack Forehand and Matt Zeigler highlight the most important investing insights from recent conversations across the Excess Returns podcast network. Drawing on discussions with Andy Constan, Rob Arnott, Kai Wu, Ben Hunt, Rupert Mitchell, Meb Faber and others, the episode connects ideas across macro, markets, AI, credit cycles and valuation. The conversation focuses on timeless investing principles investors can apply today, including how to evaluate expert opinions, how AI may reshape markets and jobs, what defines a true market bubble, why international stocks may be benefiting from global fiscal spending, and why the best opportunities in markets often come after long periods of underperformance.

Topics covered in this episode

• How to evaluate expert opinions during major market events and filter signal from noise

• Andy Constan’s framework for judging credibility based on experience and confidence

• Why charts showing markets rising after wars are often misleading data mining

• The difference between believing in AI technology and believing AI stocks are good investments

• How AI could both replace and augment human work through the task based structure of jobs

• Rob Arnott’s definition of a market bubble using implausible growth assumptions

• Why many technology leaders ultimately fail to justify the expectations priced into their stocks

• The difference between software companies whose moat is code and those with durable intangible advantages

• How brand, switching costs, distribution and network effects protect enterprise software companies

• Why AI may be one of the most disruptive technologies in history and what that means for markets

• Meb Faber on the myth that the easy money has already been made in international and value stocks

• The behavioral challenge of holding unpopular strategies through long periods of underperformance

• Rob Arnott on why small cap value could outperform large cap growth over the next decade

• Ben Hunt on the point in every credit cycle when lenders say no more

• How rising costs of capital can trigger boom bust credit cycles

• Rupert Mitchell on why global equity markets often follow government fiscal spending

• The growing role of international fiscal policy and capital flows in global market leadership

Timestamps

00:00 Introduction and the idea behind the weekly Excess Returns recap show
03:00 Andy Constan on how to evaluate experts and filter market commentary
11:40 Why charts showing markets rising after wars can be misleading
17:00 Kai Wu on AI technology versus AI investments and the future of work
25:37 Rob Arnott on how to define a market bubble using valuation assumptions
29:35 Kai Wu on software moats, intangible assets and enterprise software durability
35:31 Rob Arnott on how disruptive AI could be for the global economy
39:54 Meb Faber on why the easy money has never been made in markets
43:57 Rob Arnott on small cap value versus large cap growth opportunities
48:39 Ben Hunt on credit cycles and the moment lenders pull back
55:56 Rupert Mitchell on fiscal spending and global equity market performance

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In this episode of the Jim Paulsen Show, Jim joins Jack Forehand and Justin Carbonneau to break down the macro forces shaping today’s markets and economy. Jim explains why the economy may be far weaker than headline GDP numbers suggest, how technology and AI investment are masking weakness in the broader economy, and why leadership in the stock market may be shifting. The conversation also explores the market implications of geopolitical conflict, the relationship between policy and market leadership, and how investors should think about AI’s long-term economic impact.

Topics covered in this episode

• How geopolitical events like the Iran conflict affect markets, volatility, oil prices, and investor sentiment

• Why market reactions to geopolitical shocks often fade once the situation is “vetted” by investors

• The relationship between oil prices, the US dollar, and global financial markets

• Why Paulsen remains constructive on international stocks and emerging markets despite recent volatility

• Why energy and food now represent a much smaller share of consumer spending than in past inflation cycles

• The argument that inflation fears may be overstated given structural disinflationary forces in the economy

• How AI and technological innovation can destroy some jobs while simultaneously creating new economic demand

• Why technological progress often lowers costs and expands markets rather than simply eliminating work

• The concept that the “new economy” driven by technology investment is now large enough to influence overall GDP growth

• Paulsen’s analysis showing that roughly 11 percent of the economy tied to new-era investment is growing rapidly while the remaining 89 percent is barely growing

• Why the broader economy may resemble a recession even while headline GDP remains positive

• How the dominance of large technology companies in indexes like the S&P 500 may be masking weakness in the broader market

• The historical “toggle” between technology leadership and broader market leadership in equity markets

• Why policy conditions like the yield curve and monetary easing often drive leadership shifts toward value, small caps, and cyclical stocks

• Whether the Federal Reserve could begin easing policy without a traditional recession

• Why policy support may eventually broaden the bull market beyond technology stocks

Timestamps

0:00 Jim Paulsen on geopolitical volatility, oil prices, and market reactions
2:50 How investors should think about the Iran conflict and market implications
10:50 The relationship between oil prices, the US dollar, and safe-haven flows
12:20 Why Paulsen likes international and emerging market stocks
14:30 Why higher oil prices may not lead to sustained inflation
18:40 AI disruption and the economic debate around jobs and productivity
23:00 How innovation historically creates new demand and economic growth
29:40 Technology is the tail wagging the economic dog
33:30 Why the “new economy” is growing far faster than the rest of the economy
37:00 Evidence that most of the economy may already resemble a recession
41:00 Profit growth disparity between technology and the rest of the economy
45:40 Why the stock market can mask weakness in the broader economy
46:30 The historical leadership toggle between tech and the broader market
49:00 Valuation differences between technology and other sectors
50:30 How policy conditions influence market leadership
55:00 Signs that leadership may already be shifting beyond tech
57:00 Could the Fed ease without a traditional recession
59:00 What a policy shift could mean for the next phase of the bull market