Excess Returns

Edward Chancellor joins Kai Wu on the latest episode of the Intangible Economy to discuss what financial history and capital cycle theory can teach investors about today’s AI boom. They explore why transformative technologies can still produce terrible investor returns, how overinvestment develops, where anti-bubbles may be forming, and what past episodes like the railway mania, the dot-com bubble, China’s investment boom and the post-2008 interest rate regime suggest about the risks and opportunities today.Subscribe on Spotify⁠⁠Subscribe on AppleTopics covered:How capital cycle theory applies to the AI data center boomWhy railway mania, autos, aircraft and the dot-com bubble offer lessons for todayWhy markets often fund major technology transitions but fail to identify the winnersThe prisoner’s dilemma driving hyperscaler AI spendingWhether AI demand can justify the supply being builtHow GPU depreciation and AI capital spending may affect reported earningsWhy hallucinations and reliability may limit the total addressable market for large language modelsThe case for looking at AI anti-bubbles instead of shorting the bubble directlyWhy China shows that strong GDP growth does not guarantee strong shareholder returnsHow intangible capital, SaaS valuations and human capital fit into capital cycle analysisWhether bubbles can be good for society while still being bad for investorsWhy the long-term interest rate cycle may have changedThe role of gold in a world of expensive stocks, rising debt and vulnerable bondsTimestamps:00:00 Edward Chancellor on capital cycles, bubbles and AI04:42 Why the railway mania became a classic overinvestment cycle09:00 Why markets fund technology booms but often miss the winners13:19 The prisoner’s dilemma behind AI spending17:30 Will AI demand justify the supply being built20:00 How capital spending can inflate profits before the bust25:08 The AI Hindenburg moment and the limits of large language models30:55 Why AI hype may exceed the proven technology35:55 Why the anti-bubble may matter more than shorting AI40:00 The energy transition bubble and the opportunity in overlooked assets45:08 China’s lesson on GDP growth and shareholder returns49:27 Big Booze, GLP-1s and the Lindy effect54:23 Can intangible capital have its own capital cycle59:54 SaaS valuations and the index creation warning signal01:04:10 Why bubbles can help society but hurt investors01:09:09 Why long-term rates may be in a new multi-decade cycle01:14:07 Why Edward Chancellor still sees a role for gold

Brent Kochuba of SpotGamma joins Jack Forehand for the May 2026 OPEX Effect to break down what options positioning is saying after a massive AI and semiconductor-led market rally. They discuss SPX call volume, zero DTE options, dealer gamma, VIX expiration, NVIDIA earnings, oil risk, AI CapEx, and why options flows may help explain both the market’s recent melt-up and the potential for a volatility shift after OPEX.Guest LinksBrent Kochuba on Xhttps://x.com/spotgammaSpotGammahttps://spotgamma.com/Topics CoveredWhy the market has ignored oil shocks and geopolitical risk while AI earnings dominate investor attentionHow AI CapEx, semiconductors and mega-cap tech have driven a powerful melt-up in stocksWhy options volume and zero DTE trading are increasingly important for all investorsHow dealer hedging, delta and gamma can affect stock market movesWhy options expiration can create short-term turning points in markets and volatilityWhat the May OPEX setup says about call-heavy positioning in the S&P 500Why single-stock options activity in NVIDIA, Tesla, Apple, Amazon and AI-related names mattersHow record SPX call volume is being driven by short-dated options flowsWhy Brent is watching VIX expiration, NVIDIA earnings and May 19 to May 20 for volatility expansionWhat oil, VIX, correlation and dispersion are signaling about market riskTimestamps00:00 Intro: SPX call volume, call-heavy positioning and transient options flows00:57 Are we in melt-up mode?05:29 AI, UFOs and how fast market narratives are changing09:00 Why options flows matter more for everyday investors13:39 Could SpaceX become the next huge options market?16:00 How dealer hedging, delta and gamma move through the market20:44 Why OPEX can become a turning point for stocks and volatility23:22 Why May OPEX is so call heavy28:07 The market rally into May expiration33:00 AI rebranding, meme behavior and downside headline risk36:07 Reviewing last month’s oil and volatility setup40:17 How the war flipped market leadership back to tech44:13 Dealer gamma support in the S&P 50049:19 Single-stock gamma in NVIDIA, Tesla, Apple and Amazon51:06 Record SPX call volume and the role of zero DTE54:55 Semiconductor, AI and memory call volume57:50 From bearish positioning to peak-bull dispersion59:22 Oil, the S&P 500 and changing correlations01:03:06 COR1M, dispersion risk and when Brent considers hedging01:04:57 Brent’s key takeaways for May OPEX and volatility expansion

Elena Khoziaeva, Co-Chief Investment Officer and Portfolio Manager at Bridgeway Capital Management, joins Excess Returns to discuss factor investing, small caps, value investing, market concentration, intangibles, passive investing, market neutral strategies, and the role of AI in quantitative investment research.We cover how Bridgeway combines disciplined quantitative models with human judgment, why the S&P 500 may be less diversified than investors think, and how investors can think about diversification when mega-cap growth stocks dominate market returns.Bridgeway Capital Managementhttps://bridgeway.com/I Know What You Did Last Summerhttps://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 CoveredWhy quantitative investing still needs human judgment and skepticismThe difference between smart beta and true multi-factor portfolio constructionHow Bridgeway combines value, quality, sentiment and risk controlsWhy the size premium may depend on how small-cap stocks are definedWhy recently fallen large caps and IPOs can distort small-cap researchHow the small-cap universe has changed as companies stay private longerHow intangible assets affect traditional value and quality metricsWhy value can work in bursts and why timing factor rotations is so difficultHow concentrated the S&P 500 has become using the HHI frameworkWhy passive investing may create opportunities for active small-cap managersHow market neutral strategies can help investors manage equity market volatilityHow AI can help with data, text analysis and trading without replacing investment judgmentTimestamps00:00 Why fewer than 50 stocks are driving S&P 500 returns01:04 Bridgeway’s evidence-based investing approach02:59 Why quantitative models need human judgment07:52 Smart beta vs multi-factor investing11:32 How Bridgeway builds multi-factor portfolios16:08 Rethinking the size premium20:31 Has the small-cap universe gotten worse?23:49 How intangibles change value investing28:05 Does value still work?30:09 Why value returns can be episodic33:11 Why factor investors need patience35:22 How concentrated is the S&P 500?40:29 Factor strategies as portfolio diversifiers41:41 Passive investing and market structure44:27 Managing volatility with market neutral strategies49:40 How systematic managers update their models55:02 How Bridgeway is using AI01:00:03 Elena’s biggest lesson for investors

This episode of our new showThe 100 Year Thinkers brings together Chris Mayer and Ian Cassel for a deep discussion on long-term stock picking, microcap investing, business quality, AI disruption, management teams, and the behavioral skills that separate great investors from great analysts.They explore why the edge in investing may increasingly come from judgment, presence, relationships, patience, and the ability to hold the right businesses through uncertainty.Subscribe to the 100 Year Thinkers on Spotify⁠⁠⁠⁠Subscribe to the 100 Year Thinkers on AppleTopics CoveredWhy being present with management teams may still be an investor edge in the age of AIHow microcap investing differs from small-cap, mid-cap and large-cap investingWhy talking to management can build conviction but also create biasHow Chris Mayer thinks about vertical market software, mission-critical systems and AI disruptionWhy AI may become table stakes rather than a durable competitive advantageHow small companies can use AI to improve workflows, sales, inventory and productivityWhy many microcaps have short shelf lives and rarely become true long-term compoundersThe role of intelligent fanatics, owner-operators and repeat winners in great investmentsWhy management transitions can create powerful microcap opportunitiesThe difference between being a great analyst and being a great investorWhy execution, position sizing, selling losers and holding winners matter more than hit rateHow Matt and Bogumil apply the lessons to AI, business quality and the limits of small business scalabilityTimestamps00:49 Introducing Chris Mayer, Ian Cassel and 100 Year Thinkers04:59 Ian Cassel’s first management meeting and XM Satellite Radio09:00 Why management meetings deepen understanding but can also mislead14:32 Chris Mayer on the real edge in long-term investing18:40 Mission-critical software, systems of record and AI disruption22:45 How microcap companies are using AI in real businesses27:02 AI as table stakes and when disruption creates opportunity31:29 Why most microcaps have short shelf lives35:51 Finding Tom Brady before the market knows he is Tom Brady40:53 Why owner-operators and intelligent fanatics matter45:03 Second-in-command leaders, repeat winners and chips on shoulders49:27 Analyst vs investor and the missing skills of stock picking54:00 Using data to identify investor strengths, weaknesses and decision errors58:14 Position sizing and letting small positions earn the right to grow01:03:00 Peter Lynch, stocks as businesses and learning to think like an owner01:07:00 AI, human judgment and the limits of automation01:11:00 Why not every small business can become the next Facebook01:15:00 Where to follow Bogumil and the 100 Year Thinkers series

This week’s Excess Returns Weekly Wrap examines what Chris Davis and Rich Bernstein can teach investors about letting winners run, inflation risk, market concentration, dividends, AI, and the difference between economic stories and investment returns. Jack Forehand and Matt Zeigler break down clips on portfolio concentration, the 1960s vs. the 1970s, investor complacency, the Fed’s inflation target, durable businesses, and where the next market opportunity may be hiding.Subscribe on SpotifySubscribe on AppleTopics CoveredWhy letting winners run can be so powerful, but so hard for professional investorsChris Davis on how his mother outperformed by never selling great companiesThe tradeoff between concentration, diversification and real-world portfolio riskWhy Rich Bernstein thinks today may look more like the 1960s than the 1970sHow oil prices affect consumer behavior when measured against wagesChris Davis on why perceived risk can be very different from actual riskWhat cars, insurance and investor behavior reveal about market complacencyWhy the Fed’s 2% inflation target may not reflect the world investors are living inThe relationship between valuation, durability and software stocksWhy higher inflation could increase demand for dividends and near-term cash flowChris Davis on why exceptional people and management teams matter in investingWhy AI may be a great economic story but not necessarily a great investment storyTimestamps00:00 Letting winners run, 1960s inflation and investor risk perception02:18 Chris Davis on how his mother outperformed by never selling08:32 Reinvestment risk and the limits of active management12:45 Why oil shocks may matter less when gasoline is low relative to wages20:25 Chris Davis on why feeling safe can make investors take more risk29:20 Rich Bernstein on whether the Fed’s 2% inflation target is outdated34:08 Chris Davis on durability, valuation and software stocks39:39 Why cash flow gives durable companies room to adapt43:16 Rich Bernstein on dividends, inflation and the need for cash today51:55 Chris Davis on why people matter more than investors think56:07 The risk and value of investing with exceptional leaders1:01:30 Rich Bernstein on AI as an economic story vs. an investment story1:05:13 Why AI productivity may not translate into obvious stock market winners

This episode of Last Call breaks down one of the most confusing market environments in recent memory: why stocks continue to rise despite war, oil shocks, and growing macro risks. Through conversations with Jim Paulsen, Ben Hunt, Kevin Muir, and Brent Kochuba, we explore the tension between strong earnings, hidden risks in private credit and global growth, and the powerful role of flows and positioning in driving markets higher.Follow Last Call on Spotify⁠⁠⁠⁠⁠⁠⁠⁠Follow Last Call on Apple Podcasts⁠Topics CoveredWhy markets are ignoring war, oil shocks, and geopolitical riskThe “supernova” risk in private credit and why it hasn’t hit markets yetHow supply-driven inflation differs from 1970s-style demand inflationWhy pessimistic sentiment may actually be supporting marketsThe role of earnings growth and valuation resets in fueling the rallyBull vs bear case for markets based on macro, earnings, and positioningWhy free cash flow trends may be more concerning than earningsHow options flows and dealer positioning are suppressing volatilityThe AI capex boom and its impact on market leadership and breadthThe growing divide between Mag 7 earnings and the rest of the marketTimestamps00:00 Intro and market overview01:37 Why markets are not falling despite negative news03:00 Buy-the-dip behavior and earnings resilience06:11 Ben Hunt on “supernova” risks in private credit08:00 Hidden credit crunch in middle market companies10:24 Why private credit matters for economic growth14:10 Oil supply shocks and global growth risks17:00 Why markets can ignore risks before they appear18:48 Jim Paulsen on market resilience and sentiment20:00 Why pessimism may reduce downside risk22:24 Inflation vs labor force growth framework24:00 Why current inflation is supply-driven, not demand-driven26:00 Potential shift from inflation focus to growth focus29:11 Kevin Muir on bull vs bear market setup31:00 War impact on rates, oil, and positioning33:00 Fed reaction and shifting rate expectations35:00 Why earnings remain the dominant market driver37:00 Why geopolitics often doesn’t move markets40:00 Bear case: weak free cash flow and employment risk44:26 Brent Kochuba on options flows and positioning47:00 Why markets ignore rising rates and oil49:00 Call buying, dispersion, and tech leadership51:00 Energy as both hedge and AI-driven opportunity54:00 Correlation, volatility, and market structure56:00 Dealer positioning and suppressed volatility58:00 Earnings strength and narrow market leadership01:01:00 Free cash flow vs earnings debate01:01:55 AI capex and long-term market implications

This episode explores one of the most important debates in markets today: whether investors are underestimating the risk of higher inflation and overconcentrating in a narrow group of growth stocks.Richard Bernstein of Janus Henderson Investors joins Excess Returns to explain why today’s environment may look more like the inflationary 1960s than the 1970s, what that means for portfolios, and why many investors may be disappointed with passive index returns over the next decade.Richard walks through the implications of rising import prices, global conflict, and deglobalization, and how these forces could drive a structural shift toward higher inflation and shorter-duration investing. He also explains why market concentration, AI enthusiasm, and capital flows may be setting up a broadening opportunity across overlooked areas of the market.Follow Rich on Twitter:https://twitter.com/RBAdvisorsCompany Website:https://www.rbadvisors.comWhy investors in S&P 500 index funds may face disappointing long-term returnsThe shift from exporting disinflation to importing inflation through global tradeHow war and geopolitical conflict are influencing inflation expectations and marketsWhy today’s environment resembles the 1960s “guns and butter” period more than the 1970sThe case for structurally higher inflation and a potential shift in Fed targetsWhy shorter-duration assets, dividends, and cash flow matter more in inflationary regimesThe risks of overconcentration in AI and mega-cap growth stocksHow capital flows and valuation distortions create opportunities outside the Mag 7The case for international equities and why investors are significantly underweightWhere Bernstein sees the most compelling long-term opportunities across sectors and regions00:00 Intro and why index investors could be disappointed00:01:13 War, inflation, and the impact of rising gasoline prices00:02:40 Importing inflation and the role of global trade dynamics00:03:33 1970s oil shock vs 1960s guns and butter comparison00:05:00 Why today’s inflation environment may be less severe than the 1970s00:06:30 Defense spending, tax cuts, and inflation expectations00:08:54 Why Bernstein is taking the “over” on inflation and deficits00:10:00 The case for a higher long-term inflation target00:11:00 Why the Fed may resist changing its 2% inflation target00:12:00 Deglobalization and the rise of global conflict00:14:00 Global inflation dynamics and divergence across countries00:15:21 Why cash and short-duration assets may outperform00:17:00 Asset-liability mismatches and the endowment model stress00:18:23 Market concentration and parallels to the dot-com bubble00:20:00 AI as an economic story vs an investment story00:21:00 Capital flows, valuation excess, and future return expectations00:22:39 Why market broadening opportunities may emerge00:24:19 Passive flows, ETFs, and market distortions00:25:40 Where Bernstein sees sector opportunities today00:27:34 The case for dividends in an inflationary environment00:31:00 Why near-term cash flow matters more than long-term growth00:33:07 Corporate behavior, capital allocation, and rising hurdle rates00:36:02 Profit cycle strength and why the market should broaden00:41:36 Evaluating IPOs and speculative investments00:47:09 The risk of a lost decade for index investors00:50:21 Gold, commodities, and portfolio diversification00:53:48 Most attractive overlooked opportunities today00:58:06 Biggest long-term risks and what keeps Bernstein up at night

This episode with Chris Davis of Davis Advisors explores how investors should think about risk, valuation, and opportunity in a market defined by high valuations, technological disruption, and major macro shifts. Davis lays out a framework for navigating uncertainty, explains why durability matters more than ever, and shares hard-earned lessons on selling great companies too early.Davis Advisorshttps://www.davisadvisors.comTopics CoveredWhy high valuations signal complacency even in an uncertain macro environmentThe three major forces reshaping markets: higher cost of capital, deglobalization, and AIHow to identify durable and resilient businesses in a fragile worldWhy growth and value are not opposites and how expectations drive opportunityLessons from past bubbles and why today may resemble 1999 in market structureThe hidden risks in passive investing and index concentrationChris Davis’ five-part framework for investing in AI (winners, enablers, users, protected, disrupted)Why most investors lose money by overpaying for growth and underestimating competitionThe importance of management quality and “great people” in long-term investing successWhy the biggest investing mistakes are often the great companies you sell too earlyTimestamps00:00 Intro and key investing paradox on risk perception02:45 Why today’s market reflects complacency despite uncertainty05:20 Valuations, concentration, and optimism in current markets08:52 Lessons from 1999 and how value investing can outperform in downturns12:00 Durability, resilience, and why balance sheets matter more now15:21 Kodak, disruption, and risks of passive investing18:00 Perception vs reality of risk and behavioral mistakes21:51 Market structure, moral hazard, and the “buy the dip” mindset26:34 How investors should think about AI as a long-term technology shift29:30 Why picking early AI winners is dangerous33:00 The role of enablers like semiconductors, energy, and infrastructure36:00 AI users and which companies benefit most from adoption38:00 Businesses protected from disruption vs “walking dead” companies42:00 The biggest investing mistake: selling great companies too early46:00 Portfolio concentration and lessons from real-world experience50:00 Berkshire Hathaway, long-term culture, and durable business models54:00 Learning from mistakes: Costco case study57:00 The importance of management and why people matter more than investors think

This episode explores how massive structural shifts—AI, deglobalization, and the rise of passive investing—are reshaping markets and what that means for investors. Informed Momentum Company CIO Travis Prentice breaks down why 52 week highs don't mean what you think, the extreme dispersion beneath the surface of the market, why traditional definitions of risk may be flawed, and how investors should think about momentum, quality, and diversification in a rapidly changing environment.Papers and Resources Discussed:Risks Hiding in Plain Sighthttps://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 Higherhttps://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 looksWhy value and momentum are working together—and what that signals about market broadeningHow AI and deglobalization are driving a major regime shift in marketsWhy momentum investors ignore narratives and focus purely on what’s workingThe structural risks created by the rise of passive investing and index concentrationHow tracking error replaced real risk—and why that may be dangerousWhy quality stocks (especially software) are under pressure in the AI eraThe key insight behind 52-week highs as a powerful momentum signalWhy buying stocks near highs works despite investor intuitionHow momentum strategies adapt to changing leadership and market regimesThe importance of combining factors like value, momentum, and quality for long-term successTimestamps:00:00 Intro and major market shifts01:32 Market divergence beneath the surface03:00 Factor performance and broadening market trends05:13 Why market concentration hurts factor investing06:48 AI and deglobalization as structural drivers08:14 Does this environment change how you invest?11:02 Has the market sped up? Momentum implications14:00 Passive investing and hidden structural risks17:00 Tracking error vs real risk in portfolios19:00 AI as a potential change agent for markets21:09 How passive flows impact factor investing24:00 What defines “quality” in factor investing27:04 Why software and quality are under pressure29:13 AI disruption and changing expectations32:20 How to evaluate factor underperformance34:35 Comparing today’s market to the 1990s37:38 Buy high, sell higher: 52-week highs41:00 52-week highs vs traditional momentum43:20 Combining signals for better outcomes46:00 Why 52-week highs improve downside protection48:17 What momentum is picking up today50:21 Misconceptions about momentum and growth52:12 Timing and implementation of momentum54:18 Momentum reversals and market behavior57:17 Future research and improving momentum signals

This episode features Chris Bloomstran of Semper Augustus discussing market concentration, AI capital spending, Berkshire Hathaway, and the risks facing today’s equity investors. The conversation explores whether we are at a secular valuation plateau, how AI investment may reshape returns, and why passive investors may face more risk than they realize.Semper Augustus Investmentshttps://www.semperaugustus.comTopics covered:Why extreme market concentration in the Mag 7 may create long-term risksThe concept of a “secular plateau” vs a market peakHow AI capex could become a classic capital cycle with poor returnsWhy hyperscaler spending may not translate into shareholder profitsThe hidden risks of leverage both on and off balance sheetsWhy buy-and-hold investing is harder than it seems in practiceHow valuation discipline drives long-term investment outcomesBerkshire Hathaway’s cash position and what it signals about opportunityWhy capital allocation matters more than growth narrativesLessons from past bubbles including railroads, fiber, and the Nifty FiftyThe fragility of life and how it shapes investing prioritiesThe importance of independent thinking in the age of AITimestamps:00:00 Intro05:12 The “Both Sides Now” framework and AI theme09:03 Secular peak vs secular plateau in markets13:08 Leverage risks and balance sheet quality17:42 Why passive investors are more concentrated than they think21:12 The limits of long-term compounding and disruption risk25:06 Why valuation matters more than “forever stocks”29:10 Portfolio construction and return on capital differences33:18 AI capex boom and capital cycle parallels37:05 Why hyperscaler spending may not generate adequate returns41:12 The math problem behind AI investment returns45:10 Competition, redundancy, and pricing pressure in AI49:02 Is AI an existential risk for big tech?52:06 Berkshire Hathaway’s cash and Apple sales56:08 Capital allocation lessons from Coca-Cola vs Apple59:20 What Berkshire’s cash signals about future opportunities01:02:10 The fragility of life and investing priorities01:05:28 Final lessons for investors: reading, skepticism, and independent thinking

This episode features David Rosenberg, founder of Rosenberg Research, breaking down why today’s market may be driven more by valuation excess and investor behavior than fundamentals. He explains why the biggest risks right now are not obvious in headline data, and why the probability distribution for markets may be far more fragile than investors assume.Rosenberg walks through his framework for thinking in probabilities, how AI-driven productivity is distorting economic signals, why the equity market is now driving the economy, and what a “silent contraction” beneath the surface could mean for growth, inflation, and returns. He also outlines how he is positioning portfolios in response to these risks.Rosenberg Researchhttps://www.rosenbergresearch.comTopics CoveredWhy markets may be a “bubble in behavior,” not technologyThe equity risk premium at zero and what that implies for future returnsCAPE valuations and why long-term returns could be flat to negativeThe shift from economy driving markets to markets driving the economyThe “silent contraction” beneath strong GDP headlinesAI-driven productivity vs weakening labor marketsThe K-shaped economy across consumers, jobs, and capital spendingWhy the savings rate is the most important overlooked economic variableInflation outlook: why this shock may be disinflationary, not persistentPortfolio construction in a low-return, high-uncertainty environmentTimestamps00:00 Intro04:42 Cycle thinking vs “perma bear” label09:58 Learning probabilistic thinking and Plan B15:52 The “sixth mega bubble” and investor behavior20:36 Why valuations imply poor forward returns25:08 The “silent contraction” beneath headline data29:14 The savings rate and equity wealth effect33:12 Fiscal deficits and artificial economic support38:28 2027 outlook and shifting probabilities43:02 Why expectations matter more than recession calls45:40 Inflation shock vs wage-driven inflation49:22 Productivity boom and disinflation forces53:10 Why inflation may fall faster than expected55:04 Portfolio positioning and diversification strategy01:00:12 Tactical vs thematic investing framework01:03:10 Final thoughts on risk, probabilities, and markets

Brent Donnelly returns to Excess Returns to break down one of the most confusing market environments in years, where policy shocks, volatility, and positioning matter more than traditional fundamentals. He explains why markets can keep rising despite constant bad news, how traders should think about regime shifts, and what actually drives moves across equities, bonds, FX, and gold today.Brent also shares practical insights from his trading process, including risk management, journaling, and how to think about positioning and asymmetric opportunities. The conversation spans macro frameworks, behavioral pitfalls, and the evolving nature of market edges, offering a detailed look at how a professional trader navigates uncertainty.Spectra Marketshttps://www.spectramarkets.comTopics covered:Why stocks need a steady stream of bad news to go down and what drives ralliesThe impact of constant policy shocks on volatility, positioning, and mean reversionHow to distinguish structural trends from short-term trading opportunitiesThe “wall of worry” and why markets can ignore negative headlinesThe importance of Mag 7 earnings and concentration in today’s marketHow traders use reassessment triggers like the 200-day moving averageThe complexity of central bank reactions to oil shocks and inflationWhy bonds still matter as a recession hedge despite recent correlation breakdownsHow positioning—not fundamentals—drives moves in the U.S. dollarGold, silver, and Bitcoin through the lens of flows, retail behavior, and debasementThe role of overconfidence and risk management in trading successBrent’s journaling process and how writing clarifies thinkingHow to identify asymmetric trades using potential headline scenariosWhy edges in markets are temporary and require constant adaptationTimestamps:00:00 Intro02:05 Government policy shocks and market impact05:10 Volatility, shocks, and trading frameworks09:05 Why the economy remains resilient despite rate hikes13:05 Market concentration and the importance of big tech earnings16:05 The “steady stream of bad news” framework for stocks18:30 Using the 200-day moving average and pattern recognition22:10 Central banks, oil shocks, and inflation dynamics24:35 Stocks vs bonds and the 60/40 portfolio outlook26:05 Why dollar moves depend on positioning, not narratives30:55 Gold, silver, and the retail-driven momentum cycle34:05 The debasement trade and long-term gold thesis38:10 Rationality vs overconfidence in trading41:05 Risk management, journaling, and avoiding blowups46:00 Thinking in probabilities, positioning, and market expectations50:55 Journaling as a tool for clarity and discipline55:00 Why traders lose discipline when over-earning59:10 Brent’s new book and evolving trading frameworks01:03:30 Where to find Brent and closing thoughts

Liz Ann Sonders of Schwab joins Excess Returns to break down how war, an oil shock, and shifting market dynamics are reshaping the investing landscape. She explains why the surface-level strength in markets is misleading, what’s really happening beneath the index, and how investors should think about inflation, the Fed, AI, and the evolving role of retail traders.Follow Liz Ann on Twitterhttps://twitter.com/LizAnnSondersLiz Ann's Research and Commentaryhttps://www.schwab.com/learn/author/liz-ann-sondersTopics CoveredHow war and oil shocks are impacting markets, inflation, and Fed policyWhy the US being a “net energy exporter” doesn’t protect investorsThe hidden bear market beneath index-level resilienceRotation vs. correction and what it means for portfoliosThe rise of retail traders and the shift away from “dumb money”Why better or worse data matters more than good or bad dataThe K-shaped economy and its impact on consumption and marketsAI’s three phases and its real impact on jobs and productivityWhy this earnings season may be more important than usualThe shifting role of the Mag 7 and broader market participationWhy the bond market may be the true driver of equitiesRisks in credit markets and what investors should watchLabor market dynamics and challenges for younger workersHow investors and young professionals should think about AITimestamps00:00 Intro and current market environment04:05 Why the US isn’t immune to oil price shocks05:35 Lessons from past oil shocks and inflation07:22 Why markets seem resilient despite macro risks08:00 The hidden drawdowns beneath the index surface10:13 Rolling recessions and sector-level weakness10:37 Are investors conditioned to buy every dip12:58 What happens when the dip doesn’t get bought14:36 Valuations, corrections, and market structure15:12 Sentiment analysis in a new market regime18:50 Retail investors outperforming institutions20:08 Better or worse vs good or bad economic data23:00 How markets anticipate economic turning points25:22 Understanding the K-shaped economy28:00 Wealth effects and risks from equity declines29:09 AI as a transformative force vs macro risks30:00 The three phases of AI development33:04 Why this earnings season matters more34:00 Earnings revisions and sector concentration36:00 The future of Mag 7 leadership vs the rest of the market38:00 Contribution vs performance in index returns40:00 Sector sensitivity to inflation and supply chains42:00 Fundamentals vs speculation in small caps44:21 The Fed’s dilemma in an oil shock environment48:00 Why the bond market is driving equities50:05 Credit markets and systemic risk signals53:26 Lessons from past bond market dislocations54:19 Labor market challenges and younger workers57:00 Career advice in the age of AI59:26 How Liz Ann uses AI in her research process01:01:00 Closing thoughts and where to follow Liz Ann

This episode features Jim Grant of Grant’s Interest Rate Observer on inflation, war, monetary policy, and the long arc of credit cycles. Grant explains why inflation is ultimately driven by monetary debasement and why war, fiscal policy, and central bank actions may be setting the stage for a more persistent inflationary regime than markets expect.We explore how today’s environment compares to past inflationary periods, the hidden risks in credit markets and public debt, and what history teaches us about AI investment booms, oil shocks, and monetary disruption. Grant also discusses trust in financial systems, the role of gold, and why markets are always harder in real time than they appear in hindsight.Grant’s Interest Rate Observerhttps://www.grantspub.com/Topics Covered:Why war is inherently inflationary and how it strains the productive economyThe difference between measured economic stability and underlying systemic risksHow inflation shifted from a wartime phenomenon to a permanent feature of modern monetary policyThe Fed’s 2% inflation target as a structural form of currency debasementLessons from the 1970s inflation and oil shocks vs. today’s environmentWhy inflation is a ratchet that erodes purchasing power over timeThe importance of trust in credit markets and growing risks in private credit structuresPublic debt, Treasury market dynamics, and early signs of strain in government financingHistorical parallels between AI investment and past technological booms like the internetThe role of gold as a hedge against (and investment in) monetary instabilityThe durability of the US dollar despite long-term structural concernsWhy investing is always difficult in the present—even when it looks obvious in hindsightTimestamps:00:00 Intro and Jim Grant on the true causes of inflation04:04 Why war drives sustained inflation and current geopolitical risks08:00 Historical perspective on inflation before the 1970s12:00 Oil shocks, Volcker, and lessons from past inflation cycles16:00 Why inflation never reverses and purchasing power declines20:00 Trust in markets and the foundation of credit systems24:00 Private credit risks and the modern credit cycle28:00 Public debt, Treasury markets, and fiscal sustainability concerns32:00 Treasury auctions, yields, and early warning signs in bonds35:25 AI capex boom and lessons from past technological bubbles38:17 Air conditioning, internet bubbles, and delayed economic payoffs40:00 The Fed, Treasury, and hidden financial interdependence44:14 Asset allocation, gold, and monetary disruption48:44 The dollar’s strength and global dominance53:41 Why investing is always difficult in real time59:00 Advice on markets, newsletters, and enduring uncertainty

Subscribe to the OPEX Effect on Spotify⁠⁠⁠⁠Subscribe to the OPEX Effect on Apple PodcastsThis 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 uncertaintyThe “taco trade” and why investors expect bad news to reverse quicklyHow options flows and dealer hedging are influencing stock pricesWhy call options are historically cheap heading into earningsThe mechanics of gamma, delta hedging, and market maker positioningWhy options expiration (OpEx) can act as a turning point for marketsThe divergence between oil prices and equity volatilityWhat the collapse in the VIX reveals about investor positioningThe role of zero-DTE options in reinforcing short-term market rangesKey resistance levels forming from call selling and what they mean for upsideTimestamps:00:00 Why markets aren’t reacting to geopolitical chaos04:18 The “taco trade” and shifting market expectations07:30 How options flows influence stock market movements11:10 Why OpEx can drive market turning points13:05 Volatility compression and the gamma-volatility relationship15:30 How large options positioning shapes market behavior18:05 Why positioning has shifted toward calls20:00 Why this OpEx may be less impactful than prior ones22:00 Market positioning into earnings and key drivers ahead24:10 Using gamma maps to identify support and resistance27:00 Revisiting the JP Morgan collar trade and March lows30:00 Correlation spikes and the oil-volatility relationship33:00 Why oil has stopped driving equity volatility34:30 The breakdown between oil and VIX correlation36:00 Why volatility may reprice higher after OpEx37:05 The oil curve and expectations for a short-term shock39:40 One of the largest VIX collapses ever41:00 How options positioning drove the volatility unwind43:00 Why selling volatility has become a dominant strategy45:00 The feedback loop between rising markets and falling volatilityFor more information on SpotGamma and Brent’s work:https://spotgamma.comFollow Brent on Twitter:https://twitter.com/spotgamma

This episode of Excess Returns features GMO’s Tom Hancock on how to think about AI as an investment opportunity and what truly defines “quality” in today’s market. The conversation breaks down the AI value chain, challenges common assumptions about where value will accrue, and ties it all back to building durable portfolios in a rapidly changing technological landscape.Tom walks through his “Hype vs High Conviction” framework, explaining why identifying the right layer of the AI ecosystem may matter more than simply betting on the theme itself, and why balance sheets, durability, and capital allocation remain critical even in the most exciting growth environments.Hype vs High Convictionhttps://www.gmo.com/americas/research-library/hype-vs-high-conviction_insights/Topics Covered:Why AI may be the most important investment decision todayThe four-layer AI stack: applications, LLMs, hyperscalers, and infrastructureWhy investors confuse secular trends with investable opportunitiesFollowing the money through the AI value chainThe hidden risks of investing lower in the stackWhy today’s tech leaders differ from the dot-com eraGrowth vs maintenance capex and what it means for AI economicsWhy software may be more resilient than markets thinkHow GMO defines “quality” and why it matters in volatile marketsPortfolio construction: where GMO is investing (and avoiding) in AITimestamps:00:00 Intro and framing the AI investment debate00:00:55 Tom Hancock background and focus on quality investing00:02:00 What investors are getting wrong about AI00:03:23 Breaking down the four layers of the AI ecosystem00:06:45 Applications vs infrastructure: where value may accrue00:08:45 Why predicting AI winners is still difficult00:11:00 Following the cash flows through the AI stack00:13:00 Why AI funding is more stable than past tech bubbles00:16:00 Big Tech strategy differences and capital allocation decisions00:17:34 Are today’s tech companies higher quality than in 1999?00:19:00 Growth vs maintenance capex and implications for Nvidia and others00:22:00 Depreciation, chip lifecycles, and hidden risks in capex assumptions00:24:00 Capital intensity vs quality: when heavy investment is a feature00:27:00 Why incumbents may benefit most from AI00:28:30 Risks in the LLM layer and potential commoditization00:30:10 Software disruption fears: overdone or justified?00:34:06 Defining “quality” in investing00:36:00 Balance sheets vs return on capital00:38:32 Why GMO sold Oracle and the risks of leverage00:40:18 What happens if AI spending slows down00:41:35 Where the biggest risks are in the AI stack00:44:26 Where GMO is positioned vs the S&P 50000:48:00 How new ideas enter a quality portfolio00:51:00 Sell discipline and portfolio turnover00:53:00 International vs US quality investing

This episode of Excess Returns features Jim Paulsen breaking down the current macro environment through a series of powerful indicators, including oil, interest rates, consumer behavior, and market sentiment. The discussion explores whether today’s environment signals a slowing economy—or the early stages of a new bull market hidden beneath the surface.Subscribe to the Jim Paulsen Show on Spotify⁠⁠Subscribe to the Jim Paulsen Show on Apple PodcastsJim 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 Substackhttps://paulsenperspectives.substack.comTopics CoveredWhy the recent oil spike hasn’t impacted inflation and interest rates as expectedSlowing economic growth vs. recession risk and what the Fed might do nextThe Walmart vs luxury retail indicator and what it signals about the economyPrivate credit risks and how they differ from traditional credit crisesWhy many indicators point to a new bull market rather than a bearThe role of sentiment, volatility, and uncertainty in driving market returnsMarket rotation from mega-cap “new era” stocks to broader market leadershipCorporate profits divergence and the opportunity in the rest of the economyLiquidity, cash levels, and positioning as potential fuel for marketsProductivity trends and whether AI-driven gains are real or overstatedTimestamps00:00 Intro and current macro backdrop01:05 Oil spike and limited impact on yields and inflation04:45 Growth outlook and why recession may still be avoided07:10 Fed policy and the stagflation question10:15 Walmart vs luxury retail indicator explained13:40 Private credit stress vs traditional credit cycles17:00 Why this isn’t 2008 and how balance sheets differ19:50 Private credit risks and market spillover effects22:15 Bear market fears vs signs of a new bull23:45 Consumer confidence and its impact on returns25:05 Oil spikes historically as buy signals26:15 VIX, volatility, and market bottoms27:05 Yield curve steepening and market implications28:05 Sentiment indicators and what they really reflect30:00 Market rotation and broadening beyond mega caps32:45 Passing the baton from tech to broader markets35:15 Corporate profits divergence and future potential37:00 Policy uncertainty and why it can be bullish42:05 Liquidity, cash levels, and risk allocation43:20 Options positioning and put-call signals44:05 Gold vs commodities and risk appetite45:10 Consumer credit contraction and market signals46:20 Polymarket recession probabilities as sentiment47:30 Economic sentiment collapse and contrarian signals48:10 Interest rate expectations and positioning49:05 Unemployment trends and historical market bottoms50:25 Productivity trends and AI impact on the economy

This episode of Excess Returns features Tony Wang of T. Rowe Price discussing how investors can identify “inevitabilities” in technology and position portfolios to benefit from long-term innovation trends. The conversation explores AI, semiconductors, and the evolving investment landscape, while also breaking down Tony’s portfolio construction process and how he navigates cycles, valuation, and disruption risk.Tony explains why AI is fundamentally changing the cost of intelligence, how agentic systems could reshape software and labor markets, and why the current AI buildout may differ from past tech cycles. The discussion also dives into where we are in the AI cycle, how to think about the Mag 7, and what investors may be missing across the tech stack.T. Rowe Price Science and Technology Fundhttps://www.troweprice.com/financial-intermediary/us/en/investments/mutual-funds/us-products/science-and-technology-fund.htmlTopics CoveredWhat it means to invest in “inevitabilities” and separating signal from noise in marketsWhy AI and compute demand represent a structural shift similar to past tech wavesThe rise of agentic AI and how it could transform software and productivityWhether AI is underappreciated or already priced into marketsThe “multiple moons” idea and why AI may not be a winner-take-all marketHow AI could reshape the labor market, productivity, and economic growthThe AI CapEx debate and why this cycle may differ from the dot-com buildoutWhere we are in the AI cycle: training vs inferencing and deployment phaseThe impact of AI on software companies and the innovator’s dilemmaHow semiconductors, memory, and infrastructure remain key bottlenecksThe changing nature of the Mag 7 and capital intensity in AITony’s portfolio construction framework across compounders, emerging tech, and valueHow he generates ideas using S-curve adoption and economic bottlenecksPosition sizing, risk management, and balancing growth with drawdown controlSell discipline: valuation, fundamentals, and market signalsTimestamps00:00 Introduction and Tony Wang overview01:05 Investing in inevitabilities and long-term thinking03:00 Differentiating inevitability from hype and consensus04:45 AI inevitability and the rise of agentic systems07:00 Cost of intelligence and productivity implications08:00 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 today15:00 AI’s impact on jobs, productivity, and the economy18:30 Creativity, judgment, and the future of work20:45 Physical AI and robotics opportunity set22:30 AI CapEx debate vs the dot-com era25:30 Semiconductors vs software in the AI stack28:15 AI disruption risk for software companies31:00 Cyclicality in semiconductors and how AI changes it33:30 The evolving role of the Mag 7 in AI36:30 Competition, startups, and AI democratization38:00 Where we are in the AI cycle today40:00 Idea generation and S-curve adoption framework42:30 Case study: memory and AI bottlenecks44:45 Example position: optical networking and infrastructure46:40 Portfolio construction and position sizing49:00 Sell discipline and managing valuation risk

This episode explores the growing signs of a shift beneath the surface of the market, as technical indicators point to weakening momentum in equities and a potential change in leadership. Katie Stockton joins the show to break down what recent signals in the S&P 500, oil, gold, and sector rotation are telling us about where markets may be headed next.We cover the implications of a new monthly MACD sell signal, the importance of market breadth and leadership, and how investors can interpret shifting trends across asset classes using a disciplined technical framework.More on Katie's Strategieshttps://www.fairleadstrategies.com/Topics Covered:Why a new monthly MACD sell signal may signal a longer, choppier market phaseThe difference between fast corrections and slow grind bear phasesKey S&P 500 support levels and what a breakdown could mean for downside riskHow technical indicators help filter noise in headline-driven marketsThe breakout in crude oil and what it signals about a potential new cycleWhether sharp price moves are sustainable or likely to reverseUnderstanding overbought and oversold conditions across different timeframesWhy mega-cap weakness is critical to overall market directionThe shift from growth to value and what it means for investorsSector rotation trends and where leadership is emerging in 2025What gold’s recent run and emerging weakness signal for safe haven assetsHow a systematic, technical approach can help manage drawdowns and re-entry timingTimestamps:00:00 Intro04:18 S&P 500 momentum deterioration and MACD sell signal08:09 Key support levels and downside scenarios for equities12:53 Crude oil breakout and implications for a new cycle16:01 What overbought and oversold really mean in practice20:04 Mega-cap weakness and shifting market leadership24:41 Concentration risk in investor portfolios27:52 Value vs growth rotation and cycle dynamics32:13 Market breadth and confirmation signals36:19 Moving averages, death cross, and trend interpretation39:56 Inside the TAC ETF and sector rotation strategy44:04 Gold trends and why consolidation may be next47:00 Key signals to watch going forward

In this inaugural episode of our new show, The Intangible Economy with Kai Wu, we explore how AI, intangible assets, and unprecedented capital investment are reshaping the future of markets. Michael Mauboussin joins Kai to break down why today’s AI expectations may be historically unmatched—and what that means for investors trying to assess risk, returns, and who ultimately captures value.Subscribe on SpotifySubscribe on AppleThe 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 Futurehttps://www.morganstanley.com/im/en-us/institutional-investor/insights/consilient-observer/bayes-and-base-rates.htmlThe Impact of Intangibles on Base Rateshttps://www.morganstanley.com/im/publication/insights/articles/article_theimpactofintangiblesonbaserates.pdfMeasuring the Moat: Assessing the Magnitude and Sustainability of Value Creationhttps://www.morganstanley.com/im/publication/insights/articles/article_measuringthemoat.pdfOne Job: Expectations and the Role of Intangible Investmentshttps://www.morganstanley.com/im/publication/insights/articles/article_onejob.pdfCapitalism Without Capital: The Rise of the Intangible Economyhttps://books.google.com/books/about/Capitalism_without_Capital.html?id=J3SYDwAAQBAJA Better Estimate of Internally Generated Intangible Capitalhttps://pubsonline.informs.org/doi/10.1287/mnsc.2022.01703Underestimating the Red Queen: Measuring Growth and Maintenance Investmentshttps://www.morganstanley.com/im/publication/insights/articles/article_underestimatingtheredqueen.pdfExplaining the Recent Failure of Value Investinghttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=3442539Guest Links:Michael Mauboussin TwitterTopics Covered:Why OpenAI’s projected growth would be unprecedented in market historyHow base rates provide a reality check on AI expectationsThe role of diffusion models and adoption curves in forecasting technologyWhy massive capital investment in AI may follow past boom-bust cyclesLessons from large-scale infrastructure projects and why timelines breakHow intangible assets change the distribution of business outcomesThe rise of “fat tails” and why more companies now massively win or failWho captures value in AI across the stack from chips to applicationsWhy competition may drive AI profits toward consumers, not producersHow accounting distorts intangible investment and misleads investorsTimestamps:00:00 Intro and OpenAI growth expectations vs historical base rates04:32 Why no company has ever achieved 100%+ sustained growth at scale08:47 Lessons from megaprojects and AI infrastructure buildouts13:18 Intangible assets and why outcomes now have fatter tails18:36 Why big tech is growing faster than historical precedents23:52 Where value accrues in AI and why consumers may benefit most28:21 Barriers to entry in AI including capital, talent, and scale32:47 The risk of overinvestment and historical parallels to past bubbles37:26 Game theory and competitive signaling in AI capital spending41:58 Why investment returns—not “asset light” narratives—drive value46:12 How accounting fails to capture intangible investment properly50:44 Breaking down SG&A into maintenance vs investment spending55:03 Why understanding reinvestment and ROI is the core investing skill59:18 Final thoughts on uncertainty, expectations, and base rates in AI

This episode of Excess Returns features Aahan Menon of Prometheus Research breaking down the growing risk of an inflation shock driven by energy markets and what it means for investors. The discussion explores how a potential shift toward stagflation could challenge traditional stock and bond portfolios and why commodities, trend following, and systematic frameworks may be better suited for the current environment.Prometheus Researchhttps://www.prometheus-research.comAahan Menon Twitterhttps://x.com/@AahanPrometheusWhy the current inflation shock may be one of the most significant in recent historyHow oil prices and geopolitical conflict are reshaping macro expectationsThe growing risk of a stagflationary environment and what it means for portfoliosWhy traditional 60/40 portfolios may struggle in sustained inflation regimesHow expected returns differ across equities, bonds, commodities, and FXWhy commodities and energy markets offer the most attractive opportunities todayThe role of backwardation and supply shocks in driving commodity returnsWhy consensus earnings expectations may be too optimistic relative to macro realityHow inflation flows through the economy from energy to consumer demandThe Fed’s dilemma between inflation control and economic slowdownA simple rule for when to own treasuries based on inflation trendsWhy correlations across asset classes are breaking down in crisis environmentsHow systematic investors manage risk when markets are driven by news and geopoliticsThe case for trend following as a core portfolio strategyHow Aahan’s free trend system works across stocks, bonds, gold, and BitcoinThe behavioral advantages of systematic investing during volatile marketsRisks of trend following including whipsaws and false signalsHow portfolio construction is evolving to include crisis protection and energy overlays00:00 Inflation shock and why equities and bonds may struggle01:03 Setting up the macro backdrop before the oil shock03:12 Labor market slowdown vs strong GDP divergence04:45 Consumer spending driven by de-saving05:35 Oil-driven inflation shock as a recession catalyst07:32 Preparing for stagflation vs disinflationary growth09:18 Why commodities outperform in inflation regimes10:45 Expected returns framework across asset classes12:05 Why commodities and FX offer the best opportunities14:05 How commodity carry and backwardation work16:42 Trend following and commodities as pro-cyclical exposures17:43 Ranking expected returns: energy, FX, bonds, equities18:51 Challenges of systematic investing in news-driven markets20:15 Extreme correlations and oil dominating asset pricing23:47 Earnings expectations vs macro reality gap28:30 Why the Fed faces an impossible policy tradeoff30:00 Real-time CPI estimates and inflation pressure32:00 A rule for when to own treasuries based on CPI37:30 Stock-bond correlation regime shifts39:34 How the trend following system works45:10 Benefits and limitations of trend strategies

This episode explores Harris “Kuppy” Kupperman’s framework for “inflection investing” and how he identifies asymmetric opportunities across global markets. The conversation dives into why he believes U.S. equities are structurally challenged, where he sees better opportunities globally, and how macro, politics, and capital flows drive major investing inflections.Inflection investing and identifying asymmetric opportunitiesHow macro and politics create winners and losers in marketsThe Argentina case study and why the stock exchange may outperform the countryHow to structure trades with limited downside and multi-bagger upsideTime horizon advantages versus short-term Wall Street thinkingPortfolio construction, capital allocation, and when to sell positionsManaging risk, leverage, and liquidity during crises and warsBuilding a “shopping list” during market dislocationsCountry ETFs vs individual securities in global investingWhy Kuppy prefers international markets over the U.S.The structural imbalances in the U.S. economy and stock marketWhy AI may lead to profitless growth and economic disruptionThe impact of AI on jobs, margins, and economic demandHow inflation distorts economic data and investor perceptionFinding opportunities in “left for dead” markets like BrazilThe role of elections and policy shifts in market inflectionsHow to think probabilistically about investmentsAvoiding unforced errors and emotional decision-makingThe importance of long-term thinking in volatile marketsPsychology and discipline in global macro investingHarris Kupperman Twitterhttps://twitter.com/HedgeyeKuppyPraetorian Capital Websitehttps://praetorian-capital.comTimestamps00:00 Why the U.S. stock market is structurally overvalued01:14 What “inflection investing” means02:54 Top-down vs bottom-up investing framework04:31 Using politics to identify winning trades05:00 Argentina trade setup and execution06:20 Why the Argentine stock exchange is the best play08:00 Earnings inflection and multiple expansion potential10:37 Time horizon and holding period strategy13:00 When to exit positions and recycle capital18:41 How and when to raise cash19:41 De-grossing the portfolio during crises23:14 Real-time decision making during war scenarios27:00 Building a shopping list during dislocations29:32 ETF vs individual stock decision process33:22 Why the U.S. is less attractive than global markets38:17 The problem with AI-driven “growth”43:31 Monitoring vs acting across global opportunities48:14 The psychology of long-term investing and edge

This episode of our new market wrap show Last Call breaks down the biggest market drivers right now through three distinct lenses: macro, narrative, and flows. With an oil shock driven by geopolitical conflict, rising volatility, and conflicting economic signals, the discussion focuses on what actually matters beneath the surface and how investors should think about positioning in an environment where nothing is clearly priced in.Follow Last Call on Spotify⁠⁠⁠⁠⁠⁠Follow Last Call on Apple Podcasts⁠Jack 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 Twitterhttps://x.com/dampedspringBen Hunt Twitterhttps://x.com/EpsilonTheoryBrent Kochuba Twitterhttps://x.com/spotgammaEric Pachman Twitterhttps://x.com/epachmanTopics covered:How oil supply shocks impact GDP, inflation, and consumer spendingWhy higher oil prices act as a tax on the economy and shift growth dynamicsThe difference between supply shocks and demand shocks in energy marketsWhy central banks may be unable to respond to an oil-driven slowdownThe “common knowledge” framework and how narratives reshape marketsWhy the Strait of Hormuz has become the key global economic bottleneckOil exporters vs importers and how that divide is driving asset performanceWhy energy equities may outperform in a prolonged geopolitical conflictHow volatility is being driven by oil prices and geopolitical riskThe relationship between VIX and oil during crisis periodsWhy $100 oil could trigger a major volatility spike and equity selloffThe JP Morgan collar trade and how options positioning can pin marketsHow dealer hedging flows influence short-term price actionWhy markets may appear disconnected from negative newsThe limits of predicting what is “priced in” during uncertain environmentsWhy diversification matters more when macro visibility is lowHow unemployment data can mislead by excluding people leaving the workforceThe difference between unemployment rate and labor force participationStructural decline in rural economies and the migration to urban centersHow labor force trends explain the divergence in economic experiences across the USTimestamps:00:00 Oil shock as a GDP tax on consumers00:16 Strait of Hormuz as global economic chokepoint00:29 Why $100 oil could send VIX to 5000:39 Why unemployment rate may be misleading01:07 What Last Call is and how the episode is structured02:28 Macro, narrative, and flows framework for markets03:44 How oil supply shocks impact growth and inflation06:00 Why higher oil prices reduce discretionary spending07:00 Oil’s impact on inflation and central bank policy09:39 Scenario analysis for oil prices and market outcomes12:28 Is the oil shock priced into markets?16:00 Why oil vs assets may be mispriced20:00 Ben Hunt on the “common knowledge” market shift25:00 Why the Strait of Hormuz changes everything29:00 Portfolio implications: long energy vs global equities33:00 Brent Kochuba on oil, VIX, and market volatility linkage36:00 Why $100 oil is the key risk threshold for equities40:00 JP Morgan collar trade and market pinning dynamics44:00 Why options flows can override macro narratives short term52:00 Eric Pachman on unemployment vs labor force reality59:00 Structural decline in labor force across US counties

In this episode of Excess Returns, we sit down with Larry Swedroe to break down one of the most debated topics in markets today: private credit. Larry walks through what private credit actually is, why it has grown so rapidly since 2008, and where he believes the biggest misconceptions and risks are for investors.We dig into the structure of the market, how liquidity and credit risk really work beneath the surface, and why the media narrative around private credit may be overstating systemic risks. We also explore how investors should think about diversification, illiquidity premiums, and the potential impact of AI on credit markets and software lending.Larry Swedroe Twitterhttps://twitter.com/larryswedroeLarry Swedroe Substackhttps://larryswedroe.substack.comTopics coveredWhat private credit is and how it evolved after the 2008 financial crisisWhy private credit is not a single asset class and how risk varies across structuresThe three key risks in private credit: credit risk, liquidity risk, and concentration riskHow illiquidity premiums work and why they can be a major source of returnDifferences between private credit funds, BDCs, and open architecture platformsWhy diversification is critical and how concentration risk can be hiddenHow rising interest rates are impacting defaults and underwriting standardsMedia misconceptions around defaults, losses, and valuation marks in private creditThe real systemic risk of private credit vs the banking systemHow liquidity actually works in interval funds and stress scenariosWhat happens in a recession and how private credit compares to equities and high yield bondsThe role of software lending and how AI disruption could impact credit portfoliosHow to evaluate private credit managers including scale, underwriting, and leverageThe importance of credit culture and avoiding “reach for yield” behaviorWhether private credit should be accessible to retail investors and the risks involvedThe concept of earning “beta” in private credit vs trying to pick winning managersAI’s growing role in investment research and the risks of overfitting and false signalsTimestamps00:00 Why private credit is less risky than banks for systemic stability01:12 Introduction and episode overview03:00 What private credit is and how it grew after 200805:21 Who provides capital to private credit funds07:11 Why private credit is not a monolithic asset class08:00 The three key risks in private credit09:00 Illiquidity premium and why it can be a “near free lunch”12:00 Credit risk and importance of senior secured lending16:00 Concentration risk and why diversification matters18:11 Are defaults rising and what the data actually shows21:00 Media narratives vs actual credit losses23:50 Could private credit cause a financial crisis25:50 How to analyze portfolios and why most investors can’t28:44 Should investors think about indexing private credit30:12 Can private credit work for retail investors32:26 Mass redemption risk and liquidity stress scenarios36:00 Sources of liquidity inside private credit funds41:37 Software lending and AI disruption risk47:00 Private equity valuations and spillover into credit risk49:43 Key checklist for evaluating private credit investments56:30 How AI is changing financial research and investing

This episode of Excess Returns features Bob Elliott discussing the growing fragility in the global economy as an oil shock collides with a shift from an income-driven to a savings-driven system.The conversation explores why markets may be mispricing the economic impact of higher oil prices, how inflation and growth dynamics could unfold, and what this means for investors navigating an increasingly volatile macro environment.Bob also breaks down how to think about global macro investing today, including why traditional portfolios may be poorly positioned for a wider range of outcomes, how macro managers are adapting to shifting conditions, and how AI-driven productivity gains could impact economic growth, labor, and markets.Bob Elliott on Twitterhttps://twitter.com/BobEUnlimitedUnlimited Funds websitehttps://www.unlimitedfunds.comTopics coveredThe shift from an income-driven economy to a savings-driven economy and why it creates fragilityWhy an oil shock acts as both an inflation driver and a tax on real consumer spendingHow higher gas prices mechanically reduce discretionary spending and economic growthWhy markets may be underpricing the economic impact of the current oil shockThe link between oil prices, inflation expectations, and real demand destructionHow global markets respond to shocks through deleveraging and volatility spikesWhy gold and other winning trades can fall during risk-off environmentsThe sequencing of inflation first and growth slowdown later in shock-driven cyclesHow central banks are likely to respond to a stagflationary shockLessons from 2022 and 2008 for understanding today’s macro environmentWhy stocks and bonds may both be mispriced in the current regimeThe difference between consumer surplus and true productivity gains from AIWhy AI-driven job losses and economic growth cannot coexist without major dissavingThe most likely path for AI as a productivity enhancer rather than a job destroyerHow to think about measuring productivity in a technology-driven economyThe role of second- and third-order effects in macro investingHow global macro strategies identify mispricings across asset classesThe concept of using the “wisdom of the crowd” from hedge fund positioningWhy macro strategies can perform in both rising and falling marketsHow macro fits into a portfolio as a diversifier versus long-only assetsWhy the future investment environment may require broader strategy diversificationTimestamps00:00 Oil shock meets a savings-driven economy01:00 Framing the macro environment: oil, inflation, and growth02:12 What a savings-driven economy means for market fragility04:46 Why household income vs spending divergence matters07:00 First principles of an oil shock and demand inelasticity08:00 How oil price spikes flow through to inflation13:00 Global market reactions and emerging market dynamics14:00 Deleveraging and volatility driving asset price reversals15:44 Why gold declines during macro stress events17:17 Institutional positioning and ETF flows in gold17:34 Inflation first, growth slowdown later: sequencing the impact19:24 Is the economic damage already done22:00 How macro investors operate in low-conviction environments29:19 What the Fed should do versus what it will do31:00 Comparing today’s environment to 2022 inflation dynamics33:00 Why markets are pricing in almost nothing34:00 AI and the link between labor, income, and spending37:11 Productivity vs consumer surplus in AI adoption40:00 Why better tools don’t necessarily mean higher productivitys46:00 How global macro strategies are constructed48:00 Using hedge fund positioning as a signal56:00 Why the opportunity set for macro may be expanding

Subscribe to the 100 Year Thinkers of Spotify⁠⁠Subscribe to the 100 Year Thinkers of AppleIn 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 investingTimestamps00:00 Why extreme outcomes drive stock market returns01:00 Base rates vs studying 100 baggers03:00 Power laws and why markets are a game of outliers05:00 Just 46 companies created half of all market wealth07:00 Buffett on consistency and long-term operating history10:00 How to think about base rates in AI, energy, and macro cycles12:00 Does AI invalidate historical base rates?15:00 Inside view vs outside view in investment decision making19:00 Buffett’s “certainty at a discount” framework23:00 How often investors should evaluate businesses vs prices29:00 Mean reversion myths and where it breaks down33:00 Return on invested capital and competitive pressure36:00 Moats, winner-take-all markets, and long-term dominance41:00 Twin engines of compounding: growth plus multiple expansion43:00 Return on incremental capital and forecasting future returns47:00 Intangibles and why accounting distorts real business value50:00 Amazon, CapEx cycles, and hidden profitability53:00 AI infrastructure buildout and the future of returns

Subscribe to the OPEX Effect on Spotify⁠⁠Subscribe to the OPEX Effect on Apple PodcastsThis 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 Twitterhttps://twitter.com/SpotGammaSpotGamma Websitehttps://spotgamma.comTopics 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 decisionsTimestamps00:00 Volatility premium vs low market movement disconnect01:00 Why markets feel calm despite rising risks05:20 Explosion in options volume and impact of Monday Wednesday Friday expirations07:00 How market maker hedging flows drive price movements08:40 Dynamic hedging and why options impact evolves over time09:20 Why OPEX can trigger market turning points10:30 VIX expiration effects and short-term volatility suppression13:00 Negative gamma and how it amplifies market volatility14:10 Why hedging demand remains high despite OPEX clearing16:00 Jump risk scenario and potential VIX spike to 4017:10 Shift from zero DTE trading to longer-term hedging18:00 Put-heavy positioning across equities and indices20:40 Size and significance of the current OPEX event22:20 VIX spike dynamics around expiration23:40 JP Morgan collar trade and key SPX levels25:00 Why OPEX often marks short-term market lows or highs28:30 Review of prior OPEX signals and market setup30:00 Rising correlation and shift to asset allocation mindset32:00 Dispersion breakdown and implications for equities34:00 Software sector volatility and AI disruption narrative36:30 Using options signals for better timing decisions39:00 Correlation spike and risk-off behavior across markets41:30 Why investors are avoiding calls and piling into puts44:30 Cross-asset correlation breakdown and bond hedge failure48:00 Credit market risks and spillover into equities49:00 Extreme VIX vs realized volatility spread50:50 Why realized volatility remains unusually low52:30 Oil, inflation, and macro feedback loops

In this episode, Jared Dillian joins Excess Returns to break down why markets consistently misprice major regime shifts, geopolitical risks, and inflation shocks—and what that means for investors today. The conversation explores how changing correlations, Fed policy constraints, commodities, and portfolio construction are reshaping the investing playbook in 2026.Jared Dillian Twitterhttps://twitter.com/DailyDirtNapDaily Dirt Naphttps://www.dailydirtnap.comTopics CoveredWhy markets fail to price low-frequency, high-impact events like war and geopolitical shocksThe concept of regime change and why investors struggle to adapt to new market environmentsThe breakdown of the 60/40 portfolio and stock-bond correlation in an inflationary regimeCommodities bull market dynamics and why energy, agriculture, and hard assets may outperformThe role of options and “long gamma” positioning in uncertain macro environmentsBitcoin as a liquidity trade vs. store of value and how sentiment drives crypto cyclesFed policy, oil prices, and why central banks follow the “path of least embarrassment”Inflation psychology, consumer behavior, and risks of 1970s-style market conditionsPolitical bias in investing and how ideology shapes portfolio decisionsRisks in private equity and private credit, including valuation marks and liquidity issuesThe Awesome Portfolio framework and why diversification across asset classes reduces drawdownsAI, productivity shifts, and how technological change impacts markets and labor trendsTimestamps00:00 Why markets misprice geopolitical risk and regime change02:00 Ukraine, Iran, and delayed market reactions to obvious risks05:00 Overreaction cycles and the Peloton example06:00 What it means to be long gamma in investing09:00 Oil volatility and asymmetric risk opportunities10:00 Regime change explained through stock-bond correlation breakdown12:00 Non-stationarity and why investing rules constantly change14:00 Why most investors fail to adapt to new regimes17:00 Position sizing, risk management, and staying “small”19:00 Commodities bull market and broad participation across assets20:30 Bitcoin as a liquidity sponge and sentiment-driven asset22:00 Fed policy, inflation, and the path of least embarrassment25:00 Oil-driven inflation vs demand destruction dynamics27:00 Inflation psychology and real-time indicators29:00 Are we entering a 1970s-style macro regime31:00 How political views shape investment strategies35:00 Learning from past mistakes and adapting to new trends37:00 Private equity and private credit valuation risks40:00 Liquidity cycles and refinancing risk in credit markets43:00 The Awesome Portfolio explained46:00 Behavior, drawdowns, and why diversification works49:00 Real estate allocation and portfolio construction51:00 Labor trends, productivity, and changing work dynamics54:00 AI productivity boom vs social media drag57:00 The dangers of consensus thinking and unpopular views

Biotech is one of the few areas in investing where specialized knowledge may still generate persistent alpha. In this episode of Excess Returns, D.A. Wallach, venture capitalist and co-founder of Time BioVentures, joins us to explain how biotech investing works, why development-stage drug companies behave like portfolios of options, and why specialist investors play such a large role in this market. We also explore the cycles that have driven biotech performance, the impact of interest rates and capital flows, and how AI and global competition may reshape the industry in the years ahead.D.A. Wallach – Twitterhttps://x.com/DAWallachTopics 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 adaptableTimestamps00:00 Why biotech investing requires specialized knowledge01:40 Is biotech one of the last places for persistent active alpha?02:45 The “bag of options” model for valuing biotech companies05:00 Drug development phases and probabilities of success07:00 Using base rates to estimate clinical trial success09:20 Estimating total addressable markets for new drugs11:10 Why rising interest rates hurt biotech valuations13:00 Capital flows and why biotech underperformed in recent years15:30 The biotech boom and bust around the COVID pandemic18:00 How AI and tech compete with biotech for investor capital22:20 The role of specialist biotech hedge funds24:00 How pharmaceutical acquisitions drive biotech returns25:20 How biotech venture capital differs from tech VC30:50 Why biotech investors must evaluate complex scientific data34:20 Where AI may improve drug discovery and R&D productivity42:00 Portfolio construction and diversification in biotech venture investing44:30 Volatility, valuation marks, and private market pricing48:00 Managing risk across different drug technologies and disease areas49:30 Why China is becoming important for clinical trials53:00 Why biotech investing must be viewed as a global industry54:30 The importance of flexibility between value and growth investing58:50 Will investing become more systematic and quantitative over time

Follow Two Quants and a Financial Planner on Spotify⁠⁠Follow Two Quants and a Financial Planner on AppleIn 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 techTimestamps00:00 Introduction02:00 Why humility matters more than ever in investing08:50 AI disruption and the future of software businesses18:07 The growing gap between the “new era” economy and the rest of the economy25:00 Surviving first and being the least wrong as an investor31:43 The potential defense spending supercycle37:44 AI’s deflationary impact and how innovation reshapes economies44:42 Why valuations act as a long-term headwind for stocks50:56 How investors should respond to geopolitical events56:49 Jim Paulsen on policy juice and the future of the bull market

On this episode of Excess Returns, Matt Zeigler and Bogumil Baranowski speak with Rainwater Equity ETF portfolio manager Joseph Shaposhnik about how long-term investors should think about markets in an era defined by geopolitical shocks, AI disruption, and unprecedented capital investment cycles. The conversation explores how disciplined investors can stay focused on durable businesses and long-term free cash flow rather than reacting to short-term headlines. Joseph explains how his team evaluates companies during major events, why the AI boom may create both massive disruption and opportunity, and where he believes the most attractive investment opportunities exist today.Topics covered in this episode• Why most macro headlines and geopolitical events rarely have lasting impacts on great businesses• How long-term investors should analyze conflicts and market shocks without overreacting• The defense spending supercycle and why aerospace and defense may benefit from rising geopolitical tensions• How Joseph evaluates the AI investment cycle across semiconductors, software, and hyperscalers• Why semiconductor companies may offer a lower-risk way to benefit from AI growth• The risks created by massive AI infrastructure CapEx and concentration around specific AI models• Why some software companies may face significant disruption from AI tools and LLMs• How AI could reshape business models that rely on packaging public or commoditized data• The potential rotation from the Magnificent Seven to the other 493 companies in the S&P 500• Why capital intensity may change the long-term attractiveness of some technology companies• The role of management quality and capital allocation in navigating technological disruption• Fragile vs anti-fragile business models in an AI-driven economy• Where AI may create unexpected winners across industrial and traditional industries• Why long-term investors should still prioritize durable cash flow compounding businessesTimestamps00:00 Introduction and why most headlines have limited long-term impact on businesses02:00 How experienced investors think about geopolitical shocks and market headlines04:00 Defense spending tailwinds and the aerospace and defense supercycle06:45 How investors should react when major market news breaks11:10 How Joseph evaluates the AI boom and which companies benefit most14:15 The case for opportunities outside the Magnificent Seven17:15 How rising AI CapEx is changing the economics of major tech companies21:25 Why hyperscalers face increasing concentration risk23:00 Why semiconductor suppliers may be the best positioned AI investments27:15 Why Joseph reduced exposure to software companies33:00 The importance of learning organizations and adaptive management teams37:00 AI, labor markets, and whether high-income jobs face disruption41:00 Fragile vs anti-fragile companies in the age of AI46:00 Where AI could create unexpected business winners52:00 How great management teams adapt during technological disruption57:00 How AI may accelerate entrepreneurship and innovation59:00 Why investors should remain focused on sustainable cash flow01:02:00 What the next generation of long-term compounders may look like

In this episode of Excess Returns, Matt Zeigler and Bogumil Baranowski speak with Vitaliy Katsenelson, CEO of Investment Management Associates and author of Soul in the Game. The conversation explores how value investing is evolving in a world shaped by artificial intelligence, rapidly changing economic dynamics, and historically high market valuations. Vitaliy discusses why humility and diversification are increasingly important for investors today, how to balance quality and valuation when selecting stocks, and what he has learned about selling decisions, portfolio construction, and long-term investing discipline. The discussion also moves beyond markets into deeper ideas about passion, creativity, and why investing, like art, is ultimately a creative pursuit driven by curiosity and lifelong learning.Topics covered in this episodeWhy high stock market valuations may create a headwind for future returnsThe math behind long-term stock market returns and the role of earnings growth versus valuation changesWhether the dominance of mega-cap technology companies represents a structural shift in marketsWhy AI investment could lead to both massive innovation and large amounts of wasted capitalThe importance of humility in investing during periods of rapid technological and economic changeWhy Vitaliy increased the number of stocks in his portfolio due to greater uncertaintyHow investors can think about what will not change in a rapidly evolving worldThe evolution from statistical value investing to focusing on business quality and managementWhy cheap stocks are often expensive and how narrative bias can trap value investorsThe importance of evaluating management integrity and avoiding companies with questionable leadershipHow Vitaliy thinks about selling decisions and recognizing when an investment thesis is brokenWhy many investors make their biggest mistakes by selling winners too earlyThe concept of being a value buyer but a growth holder when fundamentals improveWhy updating valuation models as businesses improve is critical to capturing long-term upsideLessons learned from great investors and the importance of surrounding yourself with thoughtful peersThe idea of building a personal operating system for investing and lifePassion, patience, and process as the three pillars of long-term investment successWhy investing is fundamentally a creative pursuit similar to art and musicThe deeper motivations behind investing and why for many great investors it is not ultimately about moneyTimestamps0:00 Vitaliy on humility and why the range of outcomes in investing is expanding2:00 The math behind long-term stock market returns4:00 Why high valuations can become a headwind for future returns6:00 Big tech growth and whether large companies now have structural advantages8:00 AI investment and the risk of massive capital misallocation10:30 Learning AI and why investors must adapt to rapid technological change14:00 Why humility leads to diversification and larger portfolios20:00 The evolution from cheap stocks to quality investing25:30 Selling discipline and recognizing when a thesis is broken34:30 Letting winners run and avoiding the mistake of selling too early42:00 Learning from other great investors and building your own framework44:30 Passion, patience, and process in investing52:00 Why great investors are motivated by more than money1:01:40 The connection between investing, creativity, and classical music

Follow Two Quants and a Financial Planner on SpotifyFollow Two Quants and a Financial Planner on AppleIn 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 episodeHow to evaluate expert opinions during major market events and filter signal from noiseAndy Constan’s framework for judging credibility based on experience and confidenceWhy charts showing markets rising after wars are often misleading data miningThe difference between believing in AI technology and believing AI stocks are good investmentsHow AI could both replace and augment human work through the task based structure of jobsRob Arnott’s definition of a market bubble using implausible growth assumptionsWhy many technology leaders ultimately fail to justify the expectations priced into their stocksThe difference between software companies whose moat is code and those with durable intangible advantagesHow brand, switching costs, distribution and network effects protect enterprise software companiesWhy AI may be one of the most disruptive technologies in history and what that means for marketsMeb Faber on the myth that the easy money has already been made in international and value stocksThe behavioral challenge of holding unpopular strategies through long periods of underperformanceRob Arnott on why small cap value could outperform large cap growth over the next decadeBen Hunt on the point in every credit cycle when lenders say no moreHow rising costs of capital can trigger boom bust credit cyclesRupert Mitchell on why global equity markets often follow government fiscal spendingThe growing role of international fiscal policy and capital flows in global market leadershipTimestamps00:00 Introduction and the idea behind the weekly Excess Returns recap show03:00 Andy Constan on how to evaluate experts and filter market commentary11:40 Why charts showing markets rising after wars can be misleading17:00 Kai Wu on AI technology versus AI investments and the future of work25:37 Rob Arnott on how to define a market bubble using valuation assumptions29:35 Kai Wu on software moats, intangible assets and enterprise software durability35:31 Rob Arnott on how disruptive AI could be for the global economy39:54 Meb Faber on why the easy money has never been made in markets43:57 Rob Arnott on small cap value versus large cap growth opportunities48:39 Ben Hunt on credit cycles and the moment lenders pull back55:56 Rupert Mitchell on fiscal spending and global equity market performance

Subscribe to the Jim Paulsen Show on SpotifySubscribe to the Jim Paulsen Show on Apple PodcastsIn 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 episodeHow geopolitical events like the Iran conflict affect markets, volatility, oil prices, and investor sentimentWhy market reactions to geopolitical shocks often fade once the situation is “vetted” by investorsThe relationship between oil prices, the US dollar, and global financial marketsWhy Paulsen remains constructive on international stocks and emerging markets despite recent volatilityWhy energy and food now represent a much smaller share of consumer spending than in past inflation cyclesThe argument that inflation fears may be overstated given structural disinflationary forces in the economyHow AI and technological innovation can destroy some jobs while simultaneously creating new economic demandWhy technological progress often lowers costs and expands markets rather than simply eliminating workThe concept that the “new economy” driven by technology investment is now large enough to influence overall GDP growthPaulsen’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 growingWhy the broader economy may resemble a recession even while headline GDP remains positiveHow the dominance of large technology companies in indexes like the S&P 500 may be masking weakness in the broader marketThe historical “toggle” between technology leadership and broader market leadership in equity marketsWhy policy conditions like the yield curve and monetary easing often drive leadership shifts toward value, small caps, and cyclical stocksWhether the Federal Reserve could begin easing policy without a traditional recessionWhy policy support may eventually broaden the bull market beyond technology stocksTimestamps0:00 Jim Paulsen on geopolitical volatility, oil prices, and market reactions2:50 How investors should think about the Iran conflict and market implications10:50 The relationship between oil prices, the US dollar, and safe-haven flows12:20 Why Paulsen likes international and emerging market stocks14:30 Why higher oil prices may not lead to sustained inflation18:40 AI disruption and the economic debate around jobs and productivity23:00 How innovation historically creates new demand and economic growth29:40 Technology is the tail wagging the economic dog33:30 Why the “new economy” is growing far faster than the rest of the economy37:00 Evidence that most of the economy may already resemble a recession41:00 Profit growth disparity between technology and the rest of the economy45:40 Why the stock market can mask weakness in the broader economy46:30 The historical leadership toggle between tech and the broader market49:00 Valuation differences between technology and other sectors50:30 How policy conditions influence market leadership55:00 Signs that leadership may already be shifting beyond tech57:00 Could the Fed ease without a traditional recession59:00 What a policy shift could mean for the next phase of the bull market

Rob Arnott returns to Excess Returns to discuss the biggest questions facing investors today, including the impact of geopolitical conflict, the valuation gap between U.S. and international markets, the long-term investment implications of artificial intelligence, and why extreme spreads between growth and value may present major opportunities. Arnott, founder of Research Affiliates and pioneer of fundamental indexing, explains why AI itself is not necessarily a bubble but many AI stocks may be priced for implausible growth. He also discusses why small cap and value stocks may offer some of the most compelling long-term opportunities in decades, how market narratives drive valuations, and why diversification beyond the U.S. could be critical for investors. Throughout the conversation, Arnott draws on decades of market history to explain how bubbles form, why profit margins tend to mean revert, and how investors should think about positioning portfolios for the next market cycle.Topics covered in this episode:• Why Rob Arnott believes AI is real but many AI stocks may be in a bubble• How market narratives can push valuations far beyond fundamentals• Why U.S. stocks trade at roughly twice the valuation multiples of international markets• The widening valuation gap between growth and value stocks• Why small cap stocks may be one of the most attractive opportunities today• The massive capital spending required to build the AI ecosystem• How technological revolutions historically destroy jobs but create new opportunities• Why investors should learn to use AI tools to remain competitive• The definition of a market bubble based on implausible growth expectations• Lessons from the dot-com bubble and the history of dominant technology companies• Why profit margins tend to mean revert over time• The long-term outlook for international stocks and diversification• How fundamental indexing works and why it can create rebalancing alpha• The concept of the “Trifecta” approach combining value, core indexing, and growth• The risks of conglomerate premiums and the diversification discount• Why the largest companies in the market rarely remain dominant over long periods• How investors should think about balancing growth exposure with cheaper opportunitiesTimestamps:00:00 AI vs AI Stocks: Why Arnott Sees a Bubble00:01 Introduction to Rob Arnott and Research Affiliates02:13 The Iran Conflict and How War Impacts Markets06:41 U.S. Valuations vs International Opportunities08:50 The Extreme Spread Between Growth and Value10:00 The Small Cap Opportunity and Index Effects13:08 The Citrini AI Paper and Long-Term Technology Shifts14:09 How Technological Revolutions Destroy and Create Jobs16:00 How AI Is Already Changing Investment Research20:00 Why AI Tools Are Still Losing Money23:40 How Investors Should Think About AI Exposure25:21 Arnott’s Definition of a Market Bubble27:41 Lessons from the Dot-Com Bubble28:34 Profit Margins and Mean Reversion30:34 Technology Moats and Competitive Disruption32:12 Will Mean Reversion Still Work in Markets?36:02 The Case for International Stocks41:39 The Trifecta: A New Framework for Indexing51:15 Why Expensive Slow-Growth Companies Underperform56:25 Conglomerate Premiums and Mega Cap Tech57:00 The Long-Term Case for Value and Small Caps01:00:00 Why Market Leaders Rarely Stay on Top

In this episode of Excess Returns, we welcome back Andy Constan of Damped Spring Advisors for a wide-ranging discussion on geopolitical risk, AI and productivity, capital flows, credit markets, fiscal policy, and the shift from US to international equities. Andy walks through the framework he uses to evaluate uncertainty, from wars and geopolitical shocks to the long-term implications of artificial intelligence, and explains why capital markets and funding conditions may matter more than bold narratives. We also explore growth, inflation, Fed policy, and the structural case for global diversification in today’s macro environment.Main topics coveredA practical framework for analyzing geopolitical shocks, including red flags, green flags, and how to evaluate information quality during times of uncertaintyHow markets are pricing the current conflict with Iran across oil, equities, bonds, gold, and volatilityWhy historical market performance after wars may offer limited predictive value due to small sample sizesHow to think about AI from a macro perspective, including GDP growth versus GDP share and who ultimately captures the gainsThe capital markets implications of massive AI-related capex and whether equity and credit markets can fund current spending plansGrowth, inflation, and the Fed: how fiscal stimulus, wealth effects, QT, and labor market trends are shaping the current macro backdropWhy Andy has shifted away from US assets toward international markets, including the role of bond yields and global risk parityA critical look at the Trump accounts proposal and the broader issue of fiscal deficits and capital allocationThe key risks Andy is watching over the next three to six months, especially around credit markets and funding conditionsTimestamps00:00 Introduction and overview of discussion topics01:01 Framework for evaluating geopolitical shocks and information quality11:46 Market reaction to the Iran conflict and asset pricing implications23:00 Why historical war data may not be reliable for market forecasting27:03 How to analyze AI’s impact on productivity and economic growth37:00 AI capex, credit markets, and funding risks42:24 Growth, inflation, and Fed policy in the current cycle49:20 The case for international equities over US markets56:20 Trump accounts, fiscal policy, and capital allocation01:02:23 What Andy is watching most closely in the months ahead

In this episode, Jack Forehand and Kai Wu break down the viral “AI doom loop” article that sparked debate across Wall Street, Silicon Valley, and even the Federal Reserve. They walk through the core thesis that artificial intelligence could trigger a non-cyclical economic disruption, separating signal from noise and exploring what it could mean for software stocks, labor markets, productivity, wealth inequality, and long-term investing. Rather than reacting emotionally, they analyze the mechanics step by step, asking whether AI is more likely to replace workers or amplify them, how fast adoption can realistically happen, and what investors should be watching right now.Main topics covered:The core thesis behind the AI doom loop scenario and why it went viralIs AI a substitute for human labor or a productivity multiplierPeople times productivity as a framework for understanding economic growthWhy we are not yet seeing major AI disruption in labor or productivity dataSoftware stocks, margin compression, and the risk to SaaS business modelsThe Jevons Paradox and whether lower costs could expand demand instead of destroy itWhy incumbents with strong intangible moats may survive AI disruptionThe difference between technological capability and real world adoption speedCompute, energy, and token costs as natural limits on AI expansionThe feedback loop argument and whether AI could cause a demand shockCreative destruction and the difficulty of forecasting new job creationAI, high income knowledge workers, and the risk to consumer spendingWealth inequality, capital versus labor, and policy responses like UBIWhy investors can be bullish on AI technology but cautious on marketsHow to think about short term disruption versus long term abundanceTimestamps:00:00 Introduction and the AI doom loop thesis02:15 Why the article triggered a market reaction06:00 People times productivity and economic growth09:00 AI and disruption in software stocks15:00 Jevons Paradox and expanding total demand19:00 AI agents, frictionless commerce, and price competition26:00 Adoption speed versus technology speed28:00 Compute constraints and natural governors on AI growth31:00 The non cyclical disruption feedback loop33:00 Creative destruction and new job formation38:00 General purpose technology and broad economic exposure44:00 Replacement versus augmentation of workers48:00 Token costs, enterprise AI spending, and labor tradeoffs51:00 High income job risk and inequality concerns

Follow Last Call on Spotify⁠⁠Follow Last Call on Apple PodcastsIn this episode of Last Call, Jack Forehand and Matt Zeigler look past the headlines to unpack what really moved markets this month. From the viral AI end of times scenario that sparked responses from Citadel, Fed Governor Waller, and Jeremy Siegel, to the growing stress in private credit and the rotation out of US mega cap stocks, this is a different kind of market wrap. Instead of recapping what the S and P 500 did, we explore what investors are actually doing with their money, how narratives shape positioning, and what the data says about whether this time is different.Featuring Brent Kochuba of SpotGamma, Ben Hunt of Epsilon Theory, Rupert Mitchell of Blind Squirrel Macro, and Meb Faber of The Idea Farm, this episode dives into AI, software stocks, options flows, credit cycles, global equity markets, gold, and the power of base rates in investing.Main topics covered:The viral AI bear case scenario and why a fictional narrative moved real marketsHow investors should think in probabilities, bull cases, base cases, and bear casesWhat options pricing and put call ratios reveal about real fear versus social media fearThe state of software stocks and whether extreme bearishness may have marked a short term bottomPrivate credit stress, rising default risks, and why every credit cycle ends when lenders say no moreAn on the ground anecdote from San Francisco illustrating how refinancing risk is playing out in real timeThe rotation from US mega caps into international stocks and why fiscal spending matters for equity marketsGold and gold miners as potential beneficiaries of global liquidity and currency shiftsWhy base rates matter when evaluating explosive AI revenue forecastsHistorical lessons from the Nifty Fifty, Japan’s bubble, the dot com era, and other periods when investors believed this time is differentPortfolio construction tools including diversification, rebalancing, and trend following in bubble environmentsTimestamps:00:00 Introduction and the AI end of times narrative02:16 Why investors are responding to fiction and what we can learn from it08:00 Brent Kochuba on options flows and software stock positioning13:00 Has extreme bearishness in software marked a bottom19:55 Ben Hunt on private credit and the boom bust cycle27:00 A San Francisco refinancing story and when lenders say no33:08 Rupert Mitchell on global markets, fiscal spending, and gold44:22 Meb Faber on base rates, bubbles, and this time is different01:00:16 How to track AI’s real world impact in corporate dataIf you enjoy deep dives into investing, AI, market structure, credit cycles, global equities, and evidence based portfolio construction, be sure to subscribe to Excess Returns for more conversations like this.

In this episode of Excess Returns, we sit down with Cullen Roche to discuss his new book Your Perfect Portfolio and the deeper principles behind building a portfolio that actually fits your life. Rather than starting with asset allocation models or return forecasts, Cullen reframes investing around risk, time horizons, and lifetime consumption. We explore how to think about stocks, bonds, factor investing, international diversification, private assets, inflation hedges, and more through the lens of financial planning and asset liability matching. This is a practical, wide ranging conversation about portfolio construction, behavioral risk, and how investors can align their investments with real world goals.Main topics covered:Why you are a saver, not an investor, and why that distinction mattersDefining risk as uncertainty of lifetime consumptionThe temporal conundrum and matching investments to time horizonsHuman capital as your most important asset and how it impacts portfolio riskThe pros and cons of a 100 percent stock allocationRethinking the 60 40 portfolio after inflation and rising ratesInternational diversification and valuation differences between US and global marketsFactor investing as a time horizon tool rather than an alpha strategyThe forward cap portfolio and skating to where the market cap puck is goingInflation protection strategies including stocks, TIPS, gold, and the permanent portfolioRisk parity and the tradeoff between diversification and returnCountercyclical rebalancing and managing behavioral riskPrivate equity, venture capital, and the illiquidity premiumDefined duration investing and asset liability matching for individual investorsThe real impact of inflation, taxes, and fees on long term returnsTimestamps:00:00 Risk as lifetime consumption and asset liability matching01:03 Introduction to Your Perfect Portfolio05:25 You are a saver, not an investor08:24 Defining risk and uncertainty of lifetime consumption10:15 The temporal conundrum and time horizons12:38 Using past performance and forecasting responsibly15:00 Human capital and portfolio construction17:12 The case for a 100 percent stock allocation19:50 Rethinking the 60 40 portfolio24:00 Adding international diversification29:43 Factor investing across time horizons35:00 The forward cap portfolio concept38:27 Inflation hedges and the permanent portfolio42:27 Risk parity explained44:49 Countercyclical rebalancing47:17 Private assets and illiquidity51:25 Defined duration strategy and Discipline Funds ETFs56:00 Real returns after inflation, taxes, and feesIf you are interested in portfolio construction, asset allocation, financial planning, factor investing, inflation protection, or building a long term investment strategy that matches your goals, this conversation offers a thoughtful framework for thinking differently about risk and returns.

In this episode of Excess Returns, we sit down with Matt Russell of Business Breakdowns to explore how AI is actually being used in investing today. We go beyond the hype and break down practical use cases for AI in portfolio management, stock research, due diligence, monitoring, and idea generation. From deep research models and agentic AI to prompt engineering and workflow design, this conversation walks through how professional investors can use AI tools to increase productivity, improve decision-making, and reduce blind spots without losing their edge. If you are an asset manager, analyst, allocator, or DIY investor wondering how AI will impact investing and stock picking, this episode offers a clear, practical roadmap.Main topics covered:The evolution from early large language models to deep research and agentic AI for investorsLLMs vs agent-based AI and why the distinction matters for investment researchHow AI fits into an investor’s workflow, from due diligence to portfolio monitoringUsing AI to monitor KPIs, earnings calls, and cross-industry signals in real timeHow AI can help kill bad ideas faster and surface deal breakers earlyPrompt engineering for investors, including mindset framing, audience targeting, and output designBuilding mental models into AI systems to reflect your investment philosophyAI tech stacks for investors, including writing tools, deep research models, and browser-based AIIteration, experimentation, and standardized testing of prompts across model upgradesThe impact of AI on alpha generation, active management, and generalist vs specialist investorsOrganizational adoption strategies for investment firms considering AICustomization, agentic workflows, and what AI in investing could look like five years from nowTimestamps:00:00 How AI tools increase investor productivity01:16 Why early ChatGPT was a head fake for investors03:07 The inflection point with deep research and agentic AI05:00 LLMs vs agents explained in plain English07:01 Where AI fits inside an investment workflow09:28 Replacing manual earnings transcript work11:40 Real-time monitoring and AI alerts19:24 Using AI to kill bad investment ideas faster22:01 Trust but verify, hallucinations and safeguards25:29 Matt’s AI tech stack for investing30:00 Prompt engineering breakthroughs33:00 Standardized experimentation across new AI models36:07 Building idea generation prompts step by step40:15 Using AI as an editor and critical reviewer43:50 Does AI compress investor skill differences46:10 How funds should adopt AI internally50:40 Fear of falling behind in asset management53:05 Generalists vs specialists in an AI world55:18 AI and the pursuit of alpha57:00 Customization, agents and the future of investing01:01:10 Coding agents and building tools with AI

Subscribe to Two Quants and a Financial Planner on SpotifySubscribe to Two Quants and a Financial Planner on AppleIn this episode, we explore one of the most important but overlooked questions in investing: what is the purpose of your portfolio? Through a series of powerful clips and reflections from Aswath Damodaran, Meb Faber, Ben Hunt, Cullen Roche, Corey Hoffstein, Daniel Crosby, Larry Swedroe, and Wes Gray, we examine how goals like financial freedom, funded contentment, liability driven investing, retirement planning, and multi generational wealth shape the way we invest. This conversation goes beyond beating the market and focuses on preserving and growing wealth, reducing financial stress, aligning money with meaning, and defining what a life well lived truly looks like.Topics covered include:Why the end game of investing matters more than beating the marketPreserving and growing wealth vs trying to get richFreedom as the ultimate goal of financial independenceFunded contentment and what it means to live a life well livedLiability driven investing and matching assets to future needsThe difference between getting rich and staying richNeeds vs desires and understanding marginal utility of wealthRetirement planning and redefining success beyond a numberMulti generational wealth and thinking beyond your own lifetimeThe psychological impact of growing up with or without moneyFinancial freedom, stress reduction, and peace of mindTactical financial goals vs long term purpose driven investingEducation, legacy, and investing in the next generationWhy once you win the game you may not need to keep playingTimestamps:00:00 Aswath Damodaran on preserving and growing wealth10:04 Meb Faber on freedom, contentment, and the hedonic treadmill22:36 Ben Hunt on funded contentment and finding your pack28:23 Cullen Roche on risk as uncertainty of consumption33:25 Corey Hoffstein on liability driven investing and not worrying about money41:50 Daniel Crosby on financial freedom and living life on your own terms47:33 Larry Swedroe on needs vs desires and staying rich55:54 Wes Gray on big blue arrows, tactical goals, and peace of mind

Subscribe to the 100 Year Thinkers of SpotifySubscribe to the 100 Year Thinkers of AppleIn this episode of the 100 Year Thinkers, Matt Zeigler and Bogumil Baranowski continue their conversation with Robert Hagstrom and Chris Mayer, diving deeper into general semantics and what it means for investors navigating AI enthusiasm, market volatility, benchmark obsession, and the gamification of markets. From Warren Buffett’s cathedral versus casino metaphor to the risks hiding in so-called “safe” consumer staples stocks, this discussion explores how language, expectations, and mistaken certainty shape investment decisions. If you want to think more clearly about markets, technology, valuation, and your own reactions as an investor, this episode offers a powerful mental framework.Topics CoveredWhat general semantics is and how language influences how investors thinkIFD disease idealism frustration demoralization and how unrealistic expectations impact marketsAI hype, capital spending, and the prisoner’s dilemma facing major tech companiesWarren Buffett’s cathedral versus casino metaphor and what it means for investors todayWhy beating the S and P 500 may not be the right benchmark for successThe gamification of markets, retail trading growth, and the shift from long-term investing to speculationTerminal value risk in software stocks amid AI disruptionWhy low volatility “warm fuzzy” stocks like consumer staples may be more dangerous than they appearExpectations investing, confidence versus overconfidence, and avoiding mistaken certaintyThe map is not the territory and how to avoid confusing models with realityEverything is connected to everything else markets as biological systems rather than mechanical systemsDelayed gratification, compounding, and why wealth is built later in the investment journeyTimestamps00:00 Cathedral versus casino capitalism and the market metaphor02:00 What is general semantics and why it matters for investors03:00 IFD disease unrealistic expectations and AI hype06:40 Outperformance, Bill Miller, and unrealistic return expectations09:00 Are market benchmarks the right way to measure success12:00 What if stock market indexes did not exist14:00 Public versus private markets and myopic loss aversion18:40 Compounding, volatility, and delayed gratification21:00 AI valuations, strategic capital spending, and economic returns24:20 The AI adoption cycle frustration and demoralization30:40 The man in overalls story and delaying reactions33:30 Warren Buffett cathedral versus casino metaphor revisited35:00 Gamification of markets passive flows and species shift in investing39:00 When to sit still versus when to act in volatile markets43:00 Mistaken certainty and the biggest risks in today’s market45:00 The hidden risk in consumer staples and low volatility stocks47:20 Expectations investing confidence versus overconfidence49:40 Everything is connected markets as living systems53:00 What success really means beyond beating an index56:20 The map is not the territory final lessons for investors

In this episode of Excess Returns, Jason Hsu returns for a wide-ranging conversation on China’s economy, the global AI race, emerging markets, factor investing, and what the next phase of globalization could mean for U.S. investors. We explore how China’s fiercely competitive domestic capitalism contrasts with common Western narratives, why AI could reshape professional services the way globalization reshaped manufacturing, and how investors should think about portfolio allocation in a shifting G2 world.This discussion covers China manufacturing dominance, Chinese EV competition, U.S. vs. China AI strategy, emerging markets investing, factor investing in inefficient markets, and how machine learning is changing quantitative portfolio management.Main topics coveredWhy U.S. investors misunderstand China’s economic system and the role of competition inside its domestic marketHow China became the world’s manufacturing powerhouse and what that means for tariffs and trade warsThe Chinese government’s role as a venture-style capital allocator rather than a central plannerThe real estate reset in China and the shift toward technology, AI, and advanced manufacturingAI as the next wave of globalization and its impact on professional services and labor marketsWhether the U.S. vs. China AI competition is truly winner-take-allCapital expenditure intensity in the U.S. vs. capital efficiency and open-source innovation in ChinaU.S. exceptionalism, G2 geopolitics, and portfolio diversification beyond a U.S.-centric allocationWhy emerging markets ex-China may differ from China tech exposureThe case for separating China from emerging markets in asset allocationThe concept of China as an alpha reservoir due to retail-driven market inefficienciesWhy traditional value and factor strategies have struggled in the U.S. but still work in ChinaHow machine learning and AI are changing quantitative investing and factor constructionThe launch of CNQQ and accessing large-cap China technology exposureTimestamps00:00 China as the world’s factory and the role of fierce internal competition01:02 Why U.S. investors misunderstand China’s economy03:48 Is China capitalist despite the Communist Party label05:33 The government as a VC-style investor rather than central planner07:45 China EV competition and manufacturing dominance09:23 Tariffs, trade leverage, and manufacturing monopoly dynamics12:18 China’s bear market and valuation opportunity13:59 The real estate reset and shift toward productive capital16:00 AI as the next wave of globalization18:01 Labor force participation and economic disruption from AI19:46 Jobs that may survive in an AI-dominated world22:00 Is U.S. vs. China AI a winner-take-all battle24:13 Chip restrictions and long-term innovation incentives26:54 Capital efficiency in China vs. heavy AI capex in the U.S.29:27 Rebalancing away from U.S.-centric portfolios31:18 The end of U.S. exceptionalism and the move toward a G2 world34:00 How endowments approach U.S., developed, and emerging markets36:35 CNQQ and accessing China large-cap technology40:45 China as the great alpha reservoir45:49 The future of factor investing in efficient vs. inefficient markets49:06 Machine learning, factor decay, and next-generation quant strategies55:17 Can AI replace active portfolio managersIf you enjoy deep conversations on global markets, AI investing, China technology, emerging markets, and quantitative strategies, make sure to subscribe to Excess Returns for more interviews with leading investors and thinkers.

Subscribe to Click Beta on SpotifySubscribe to Click Beta on Apple PodcastsIn this episode of Click Beta, Matt Zeigler sits down with Cameron Dawson of NewEdge Wealth and Dave Nadig of ETF.com for a wide-ranging conversation on markets, macro data, positioning, tokenization, AI productivity, and the narratives driving investor behavior. The discussion dives into consensus forecasts, the K-shaped economy, international equity performance, dollar positioning, AI capex, and whether the biggest market moves are driven by fundamentals or liquidity shifts. Along the way, they explore tokenization in financial markets, stablecoins, Fed balance sheet dynamics, and how AI is quietly reshaping productivity for small businesses and individuals. This episode is a deep dive into stock market trends, economic data distortions, asset allocation shifts, and the structural forces shaping the investing landscape in 2026.Main topics covered:• Why consensus forecasts are average and why that creates risks for investors• Cyclical reacceleration narrative versus liquidity-driven market rotation• The K-shaped economy and distortions in US jobs data• Healthcare hiring versus cyclical employment weakness• AI capex spending and who actually benefits• Energy, industrials, and staples outperformance versus tech concentration• International equities versus US stocks and valuation percentiles• US dollar positioning extremes and contrarian signals• Positioning versus narrative and where market surprises hide• Tokenization, decentralized finance, and DTCC proposals• Stablecoins, collateral efficiency, and capital reuse in markets• Fed balance sheet, leverage ratios, and financial system risk• AI productivity gains in small and mid-sized businesses• The future of work, automation, and economic dispersionTimestamps:00:00 Cameron on cyclical reacceleration and market expectations03:00 Consensus forecasts and average return assumptions06:00 K-shaped economy and distorted jobs data10:00 AI capex and disconnect between perception and reality12:30 Liquidity shifts and market rotation beyond mega caps14:00 International equity valuations and performance gap16:50 Dollar positioning and contrarian signals18:20 Positioning versus narrative in stock performance20:00 Tokenization and ETF market plumbing22:00 Stablecoins and capital efficiency24:00 Atomic settlement versus traditional clearing27:00 Fed balance sheet and leverage ratio debate30:00 Recessions, market resets, and social impact39:00 Cultural distribution, media fragmentation, and market narratives47:00 AI productivity, small business impact, and economic implicationsFor more episodes from the Excess Returns network, including macro investing, asset allocation, ETFs, and AI-driven market insights, visit excessreturnspod.com

Subscribe to the OPEX Effect on SpotifySubscribe to the OPEX Effect on Apple PodcastsIn this episode of The Opex Effect, Jack and Brent break down the growing impact of options markets on stocks, volatility, and sector rotation. While the major indexes appear calm, massive moves beneath the surface tell a very different story. From software stocks and AI disruption to gold, silver, bonds, and the Nasdaq, they analyze how dealer hedging flows, gamma positioning, implied volatility, and options expiration cycles may be shaping market behavior more than headlines suggest. If you want to understand why markets can feel wildly volatile yet go nowhere, and how options positioning can influence short term price action, this episode provides a deep dive into the mechanics driving today’s market environment.Main Topics CoveredWhy the market feels like the wildest calm market of all timeMassive single stock volatility versus muted index performanceSoftware stock weakness, AI disruption, and the so called SaaS apocalypseThe surge in options volume and the rise of zero DTE in major stocksHow dealer hedging, delta, gamma, and volatility flows impact equitiesThe historical tendency for markets to flip direction after options expirationRealized volatility versus intraday volatility and what is being hiddenBeneath the surface rotation into value, small caps, energy, and defenseGold and silver volatility spikes and what options volume signaled at the topRising demand for puts and what skew is telling us about downside riskCorrelation spikes, VIX behavior, and the risk of a volatility expansionHow positioning can create rapid market spasms in single stocks like Nvidia and TeslaWhy this environment may represent a staging area for a larger moveTimestamps00:00 Violently going nowhere and hidden volatility01:01 The wildest calm market of all time04:00 Introduction to The Opex Effect and options driven flows05:29 The growth of options trading and zero DTE impact11:00 Dealer hedging, delta, and how options move stocks13:42 Why options expiration can trigger regime changes16:22 Intraday volatility versus close to close volatility20:18 Extreme rotation beneath the surface21:00 Measuring expiration size with the lobster claw rating25:00 Single stock positioning and March expiration risk27:35 Core one month correlation warning signals33:00 Rising put demand and what skew reveals36:45 Asset rotation in bonds, gold, bitcoin, and tech43:06 Correlation spikes and crash risk setup46:40 The quickening of volatility and single stock spasms

In this episode of Excess Returns, we sit down with Neil Howe, author of The Fourth Turning Is Here and co-creator of the Fourth Turning generational framework, along with Ben Hunt of Epsilon Theory, to discuss where we are in the current cycle and what it means for markets, inflation, AI, capital flows, and America’s long-term economic outlook. From the debasement trade and rising gold prices to global capital crowding out and the structural forces shaping productivity and growth, this conversation connects generational theory with real-world investing decisions. If you’re thinking about inflation, deficits, AI capital spending, global diversification, or how to position defensively and offensively in a shifting macro regime, this discussion provides a powerful framework for navigating what may be a historic transition period.Topics CoveredThe Fourth Turning framework and where we are in the current crisis cycleWhy inflation is not a problem but a policy solution in major crisesThe collapse in US national savings and long-term deficit risksCapital flows, the debasement trade, and the future of the US dollarGold, commodities, and real assets in a regime shiftGlobal diversification and opportunities outside the United StatesAI capital spending, productivity gains, and the risk of overinvestmentCrowding out effects from government deficits and AI hyper scalingTrust, geopolitics, and the long-term implications for global marketsHealthcare, demographics, and structural investment themesDefensive and offensive positioning in a Fourth Turning environmentTimestamps00:00 Inflation as a solution and the generational crisis framework04:00 Explaining the Fourth Turning and historical crisis cycles12:55 Narratives, generational archetypes, and market behavior22:24 Is the Fourth Turning pessimistic or optimistic34:00 Inflation, gold, and the debasement trade40:00 Global capital flows and the reversal of US inflows50:00 AI capital spending and the K shaped capital markets55:09 Crowding out, deficits, and slow growth risks01:02:23 Defensive and offensive investment positioning01:09:31 Final thoughts on diversification, gold, and financials

In this episode of Excess Returns, we sit down with Pete Hecht of AQR to break down portable alpha, capital efficient portfolio construction, and how investors can combine equity beta with truly diversifying sources of alpha. We cover how portable alpha works in practice, how it solves the funding problem for alternative strategies, and why implementation details like leverage, liquidity, and financing costs matter more than most investors realize. If you’re interested in diversification, long short investing, managed futures, equity market neutral strategies, or improving total returns without giving up equity exposure, this discussion provides a practical and detailed framework.Main Topics CoveredWhat portable alpha actually is and how it differs from traditional stock bond alternative portfoliosHow portable alpha combines equity beta exposure with unconstrained long short alphaThe funding problem with alternatives and how portable alpha solves itTurnkey implementation versus separating alpha managers and beta overlaysThe role of equity market neutral, managed futures, and multi strategy approachesWhy private equity and private credit are poor candidates for portable alphaLong short leverage versus long only leverage and how to think about riskTarget volatility, risk models, and stress testing leveraged portfoliosFinancing costs in futures markets and how higher interest rates affect strategiesHow to evaluate portable alpha using excess returns, tracking error, and tail riskTax aware implementation and after tax returnsWhy mutual funds are not obsolete for active long short strategiesThe importance of asking whether a view is already priced into valuationsTimestamps00:00 Why you cannot eat a risk adjusted return02:12 Defining portable alpha and the problem it solves03:55 Portable alpha versus traditional balanced portfolios06:54 The funding problem with diversifying alternatives09:00 How portable alpha works in practice13:05 What types of alpha strategies work best16:35 Managed futures and crisis alpha19:49 Simplicity versus complexity in implementation21:46 Why private equity and private credit do not work in portable alpha24:15 Understanding leverage and risk management29:18 Target volatility and portfolio construction34:52 Stress testing and lessons from COVID and 202235:01 Risks and financing costs of portable alpha38:50 Interest rates and leveraged strategies39:07 Identifying hidden beta and volatility laundering46:08 Introducing AQR Fusion Funds50:25 Evaluating performance versus the benchmark53:17 Tax efficiency in long short mutual funds57:29 Is your view already priced in

In this episode of Excess Returns, Kai Wu of Sparkline Capital returns to discuss his latest research on AI adoption, ROI, and what it all means for investors.Building on his prior work on the AI CapEx boom, Kai tackles the trillion dollar question at the center of today’s market: Is AI generating real, measurable economic returns across the broader economy, or are we still in an infrastructure-driven bubble?Using a systematic analysis of earnings calls, patent data, and adoption trends, Kai lays out a framework for identifying which companies are truly benefiting from artificial intelligence and how investors can position portfolios accordingly.Find the Full Paper Here:https://etf.sparklinecapital.com/Main topics covered:Satya Nadella’s AI bubble framework and why broad economic diffusion mattersThe AI adoption S-curve and where we are in the technology diffusion cycleA new AI ROI taxonomy based on earnings call analysis and quantified economic gainsReal-world AI productivity, revenue, and cost-saving examples across industriesInfrastructure vs early adopters vs laggards and how companies were categorizedAI-driven outperformance and excess returns across different adopter groupsValuation dispersion between AI infrastructure stocks and AI early adoptersThe risk of overcapacity and lessons from railroads and the dot-com telecom boomCompetition among large language models and the durability of AI moatsS&P 500 exposure to AI infrastructure and hidden concentration riskThe case for AI early adopters as a middle ground between growth and valueIntangible value investing and the concept of AI yieldTimestamps:00:00:00 The trillion dollar question and what “real ROI” means00:03:19 Nadella’s bubble framework: diffusion vs a narrow CapEx trade00:06:08 The classic tech diffusion S-curve and where AI is on it00:32:25 Why infrastructure is being rewarded even if the ROI story is different00:33:04 The key chart: adoption vs valuation shows “basically no relationship”00:38:00 Why early adopters and laggards should separate00:38:26 The “25% ROI” example and how it could show up later in fundamentals00:39:03 Railroads and fiber: builders go bankrupt, users capture the value00:39:45 Telecom index fell 95% and never recovered (dot-com bust parallel)00:40:00 The application layer captures profits; infrastructure becomes a utility00:41:00 The punchline: transformative tech, but builders can still be bad investments00:42:57 Overcapacity question: where are we on the line?00:43:17 The buildout: another $5 trillion of data centers “or whatever the number is”00:44:00 If there’s no ROI, companies cancel orders00:45:01 Moat and LLM competition discussion begins00:49:00 The big one: adding infrastructure names gets the S&P to 46% AI infrastructure00:50:00 “Alternative indices” swing you to laggard risk00:51:00 The “false choice” and the “middle ground” framing (early adopters)

In this episode of Excess Returns, we sit down with Bloomberg Opinion columnist Nir Kaissar for a wide-ranging conversation on markets, AI, interest rates, private credit, small caps, and the risks investors may be underestimating. Nir shares his unexpected predictions for 2026, challenges the consensus on Fed rate cuts, explains why high profitability may be putting a floor under valuations, and offers a thoughtful framework for thinking about AI, concentration risk, and the future of public versus private markets. This is a deep dive into today’s most important investing debates, grounded in history and focused on what may come next.Topics CoveredNir’s unexpected predictions for 2026 and why mass adoption of autonomous vehicles may arrive faster than investors expectWhy the consensus on lower interest rates in 2026 may be wrong and what the two year Treasury yield is signalingThe impact of tariffs, affordability pressures, and corporate margins on inflationWhy high corporate profitability may support elevated stock market valuations even if returns slowThe role of earnings growth in driving S&P 500 returns and why 2015 to 2024 may not repeatIs AI more like 1995 or 1999 in the internet cycle and what that means for long term investorsThe convergence of big tech companies around AI and the risks of a more zero sum competitive landscapeWhy companies staying private longer could hurt retail investors and distort public market indicesConcentration risk in the S&P 500 and what it means for long term portfolio constructionOpportunities and risks in small cap stocks, including the importance of quality screensThe growth of private credit markets and the hidden risks investors may not seeWhy Treasuries may still be the cleanest shirt in the laundry during a crisisLessons from 20 years of running strategies and what Nir has changed his mind aboutTimestamps00:00 Nir’s 2026 predictions and the rise of Waymo05:00 Interest rates, Trump, and the outlook for Fed policy08:40 Tariffs, inflation, and corporate margins12:00 Valuations, profitability, and future S&P 500 returns16:00 AI compared to the internet era and long term investing lessons19:00 Public versus private markets and regulatory concerns32:00 Concentration risk and the Magnificent Seven39:00 Small caps, quality screens, and value opportunities47:00 Private credit risks and default cycles54:30 Nir’s investment philosophy and 20 year lessons

David Giroux, CIO of T. Rowe Price and manager of the Capital Appreciation strategy, joins Excess Returns for a wide ranging discussion on market valuation, AI investing, Mag 6 dynamics, utilities, healthcare, fixed income, and how to think independently in volatile markets. David shares his framework for exploiting structural market inefficiencies, why market drawdowns can create opportunity, how he evaluates the S&P 500 at the micro level, and what investors are getting wrong about AI, profit margins, and the current cycle.Main topics covered in this episode• Exploiting structural market inefficiencies in GARP stocks, high yield, and double B credit• Why market drawdowns often lower forward risk and increase expected returns• Strategic equity allocation during periods of fear and volatility• Rethinking S&P 500 valuation through 500 company bottom up analysis• The changing composition of the index and its impact on profit margins• Where the most overvalued and undervalued areas of the market may be today• AI investing framework including Nvidia, AMD, cloud providers, and software risk• How AI could reshape margins, labor productivity, and enterprise software• Differences between today and the dotcom bubble• Overweight positioning in utilities and healthcare and the thesis behind each• Fixed income positioning including the belly of the Treasury curve and fiscal risk• Commodities, gold, and fiscal sustainability• Lessons for portfolio managers on independent thinking and making high conviction betsTimestamps00:00 Market drawdowns and forward returns02:09 Exploiting structural market inefficiencies06:28 Strategic equity allocation during selloffs11:22 Is the market expensive and how to value the S&P 50015:00 Profit margins and index composition17:13 Where valuation excess exists outside the Mag 620:38 How to think about AI and enterprise adoption27:18 AI disruption risk across sectors39:20 AI versus the dotcom bubble42:30 Apple versus Meta and capital allocation46:53 Overweight utilities and healthcare52:57 Fixed income opportunities and risks57:32 Commodities, gold, and fiscal concerns01:00:15 Lessons for new portfolio managers