Excess Returns

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

In 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

In this episode of Excess Returns, we sit down with Kevin Muir, author of The Macro Tourist, for a wide-ranging conversation on market sentiment, asset rotation, and the growing signals of stress beneath the surface of global markets. Kevin explains why extreme bullishness can be dangerous, why gold and commodities may be flashing warning signs, and how shifts in currencies, energy, and global capital flows could reshape portfolios in the years ahead. From hedging strategies to volatility, from AI-driven concentration to international diversification, this discussion focuses on how investors can think clearly in an environment where traditional relationships are breaking down.Topics covered:Why extreme bullish sentiment can be a warning sign for marketsThe meaning of “buying straw hats in the winter” and how to think about hedgingMarket breadth, small caps, and whether rotations are healthy or late cycleGold, silver, and what precious metals signal about financial stressCross-asset volatility and why correlations are changingEnergy markets, commodities, and the long-term impact of underinvestmentGlobal capital flows, foreign ownership of US assets, and currency riskThe US dollar, trade deficits, and implications for international investorsPortfolio construction lessons from bonds, commodities, and FXHow macro regime shifts can change risk management and diversificationTimestamps:00:00 Introduction and market sentiment overview03:00 Buying protection and the straw hat analogy07:00 Sentiment indicators and market confirmation12:00 Market rotations, small caps, and late-cycle risks18:00 Gold, silver, and precious metals as warning signals23:00 Bonds, currencies, and broken correlations29:00 Energy markets and commodity underinvestment37:00 Global capital flows and foreign ownership of US assets44:00 The US dollar, trade deficits, and FX volatility52:00 Macro regime shifts and portfolio construction lessons

In this episode of Excess Returns, we sit down with Victoria Greene of G Squared Private Wealth for a wide-ranging conversation on markets, macro risk, portfolio construction, and how investors should think about 2026 and beyond. Victoria brings a pragmatic, risk-aware framework to investing, blending top-down macro analysis with bottom-up fundamentals, technicals, and a strong focus on cash flow, diversification, and policy risk. We cover everything from the rise of what she calls a badger market, to AI capex, market concentration, inflation risk, and why policy error, not valuation, is what historically ends bull markets.Main topics covered• Why valuation is a poor market timing tool and what actually ends bull markets• The concept of a badger market and how investors should mentally prepare for volatility• Cash flow never lies and how Victoria evaluates business quality• Diversification in 2026 and why international, commodities, and value matter more now• Risks and opportunities in the labor market, AI-driven disruption, and productivity• The K-shaped economy and what it means for consumers and corporate earnings• 60/40 portfolios, alternatives, and where commodities fit today• AI investing from infrastructure to software and cybersecurity• Yield curve dynamics, inflation risk, and portfolio positioning• Active vs passive investing in a concentrated market• How policy decisions and election dynamics influence marketsTimestamps00:00 Intro and why valuation does not kill bull markets01:40 Investment philosophy and macro first portfolio construction06:00 Cash flow never lies explained07:40 Diversification beyond US large caps10:00 Market expectations and big tech earnings risk11:00 What is a badger market12:40 Is the 60 40 portfolio dead15:00 Why Victoria remains constructive on markets18:00 Politics, sentiment, and market noise21:00 Policy error vs valuation as the real risk26:40 The K-shaped economy and consumer health31:10 Hard data vs soft data disconnect34:10 Labor market risks and data reliability36:40 Yield curve steepening and inflation risk41:40 Portfolio positioning in a higher inflation world43:00 How to invest in AI beyond the Mag 747:20 Where we are in the AI cycle49:30 Active management challenges and opportunities53:00 Valuation, planning, and long-term return expectations

Follow Last Call on SpotifyFollow Last Call on Apple PodcastsJoin Jack Forehand and Matt Zeigler for the premiere episode of Last Call, a new monthly market wrap show where we go beyond the headlines to deliver actionable investment insights — and have a little fun along the way.Instead of focusing on index performance or short-term moves, we step back and connect the dots between macro instability, narrative shifts, options market signals, private credit risk, AI capital spending, and the changing nature of the Magnificent Seven.Featuring conversations with Brent Kochuba from SpotGamma, Ben Hunt from Perscient, Kai Wu from Sparkline Capital, and clips from our recent interviews with Liz Ann Sonders and Aswath Damodaran, the episode blends market structure, behavioral finance, valuation discipline, and long-term investing context to help investors understand what is really driving today's market environment — and how to think about it going forward.Main Topics:• Why this is not a traditional market recap and how Last Call is designed to be more useful for investors• Instability versus uncertainty — and why today's market feels different• Loss of trust in institutions, policy, and global systems and its impact on markets• What options market flows reveal about hidden market risks and sudden volatility• How private credit has reached bubble-like conditions and why narrative risk matters• The debate over retail and retirement account exposure to private credit• Why valuation discipline looks different when correlations rise across asset classes• Aswath Damodaran on trimming positions, raising cash, and the difficulty of finding uncorrelated assets• How the Magnificent Seven are changing from asset-light to asset-heavy businesses• AI capital expenditure, historical spending booms, and why infrastructure builders often underperform• Whether this AI cycle is truly different from railroads, telecom, and past technology boomsTimestamps00:00 — Intro and opening clips01:10 — What Last Call is and why this format exists04:30 — Instability versus uncertainty in today's market09:58 — Loss of trust, gold, and historical parallels13:18 — Brent Kochuba on options flows and hidden market stress25:17 — How options dislocations explain sudden market drops25:40 — Ben Hunt on private credit narrative risk28:00 — Why private credit exposure is everywhere32:32 — Retail access versus restrictions in private credit36:19 — What happens if the private credit bubble breaks39:28 — Aswath Damodaran on raising cash and trimming positions47:08 — The changing nature of the Magnificent Seven47:42 — Kai Wu on AI capex and asset-heavy tech50:48 — Why high capital spending often leads to underperformance56:01 — Historical parallels from railroads to the dot-com boom

In this episode of Excess Returns, we're joined again by Dan Rasmussen of Verdad Advisors for a wide-ranging conversation that challenges some of the most popular narratives in markets today. From private equity and private credit risks to AI-driven capital cycles and overlooked opportunities in biotech and international equities, Dan offers a deeply research-driven perspective on where investors may be misallocating capital and where future returns could emerge. Alongside Justin and special guest co-host Kai Wu, the discussion connects valuation, incentives, and innovation in a market environment shaped by concentration, leverage, and technological change.Main topics covered• Why private equity performance continues to disappoint and where the biggest structural risks are emerging• The growing stress in private credit and what rising bankruptcies signal for lower middle-market deals• Why democratizing private equity through 401ks, interval funds, and ETFs may create more problems than solutions• How AI CapEx is changing the economics of Big Tech and why asset-light models may be getting worse, not better• The case for diversifying away from U.S. concentration toward international markets and international small value• Why bubbles are often necessary for innovation and how to think about AI through that historical lens• How investors may be underestimating valuation and growth bankruptcy risk in the Mag 7• Why biotech is one of the hardest sectors to model and how Verdad rebuilt its framework from scratch• How intangible value, clinical trial data, specialist ownership, and peer momentum can improve biotech investing• What capital starvation, M&A dynamics, and global competition mean for biotech's future returnsTimestamps00:00 Introduction and market narratives02:20 Revisiting private equity risks and performance06:58 Private credit stress and bankruptcy signals10:58 Private equity in 401ks and interval fund risks14:52 Private assets in ETFs and liquidity concerns15:45 Why bubbles drive innovation and capital formation20:13 AI CapEx, Mag 7 concentration, and valuation risk25:24 International diversification and market leadership29:41 Why Verdad turned to biotech research37:13 Rebuilding biotech valuation and quality metrics44:26 Clinical trial data and peer momentum insights49:17 Portfolio construction and long-short biotech strategies51:00 Capital starvation, AI, and biotech's setup53:58 Research culture, humility, and evolving quant models

In this episode of our new show The 100 Year Thinkers, Chris Mayer and Robert Hagstrom explore how the words investors use quietly shape the decisions they make — often in destructive ways. From labels like “cheap,” “expensive,” and “compounder” to debates about valuation, concentration, and AI, the conversation digs into how language collapses uncertainty into false certainty. Drawing on general semantics, mental models, and decades of investing experience, they explain why confusing maps for reality leads investors astray — and how clearer thinking can change how you see markets, risk, and long-term returns.Topics discussed include:Why paying 30x earnings can be rational when return on invested capital stays highHow the word “is” smuggles hidden assumptions into investment decisionsThe difference between a company being a compounder and having compounded in the pastWhy valuation debates are really disagreements about time horizonThe “map vs. territory” problem in financial statements and market dataMarket concentration, index construction, and why benchmarks can mislead investorsHow language shapes narratives around value, growth, and riskAI investing, capital allocation, and separating durable businesses from hypeWhy many binary true-or-false questions are traps for investorsHow long-term investors think in decades, not quarters

In this episode of Excess Returns, we sit down with TG Macro founder Tony Greer to explore why markets are increasingly signaling a loss of faith in institutions and what that means for investors heading into 2026. Tony lays out a framework that connects inflation, central bank credibility, political risk, global regime change, and shifting consumer behavior into a coherent macro narrative. From gold and precious metals to miners, commodities, cyclicals, and the evolving role of AI, this conversation bridges big-picture macro themes with actionable market insights for both traders and long-term investors.Topics covered:• Why gold is rallying as trust in institutions erodes• Central banks, inflation, and the long-term consequences of monetary policy• The shift from a 60-40 portfolio to alternatives and real assets• Precious metals versus technology leadership in a changing market regime• Gold miners, industrial miners, and uranium as core themes• Consumer inflation, food prices, and purchasing power on Main Street• Big Food, Big Pharma, and the broader trust breakdown• Legal, political, and geopolitical risks shaping investor behavior• The end of globalization and the rise of domestic supply chains• Copper, energy, and natural resources in an economic recovery• AI, semiconductors, and signs of a leadership transition• Prediction markets and new tools for understanding market expectations• Financials, airlines, and overlooked cyclical opportunities• How to think about risk management when macro regimes changeTimestamps:00:00 Introduction and the collapse of trust in institutions02:00 Why gold is responding to credibility loss, not fear05:00 Central banks, inflation, and monetary excess08:20 Purchasing power and real-world inflation pressures11:00 Big Food, Big Pharma, and consumer awareness14:00 Healthcare, fraud, and institutional breakdown16:30 Legal system risk and political credibility18:30 Global factors, sanctions, and the shift away from globalization21:00 Precious metals, miners, and natural resource leadership25:00 The three mining themes driving performance29:00 Stocks and gold rising together in a new regime32:00 Gold market structure and long-term trend analysis36:00 Japan, global bond markets, and gold demand39:00 Investing versus trading precious metals43:00 Copper, supply chains, and tech partnerships47:00 AI leadership, capital rotation, and market risk51:00 Financials, airlines, and cyclical signals57:30 What would break the thesis and risk management signals

In this episode of Excess Returns, we sit down with Jan van Eck, CEO of VanEck, to discuss how long-term macro forces are shaping markets and investment opportunities. Jan shares how his firm thinks about government spending, monetary policy, and technology, why he believes investors have more visibility than they realize heading into 2026, and how trends like artificial intelligence, gold, and global asset allocation could redefine portfolios over the next decade and beyond.Topics covered in this episode includeHow VanEck uses fiscal policy, monetary policy, and technology as core macro pillarsWhy declining fiscal deficits may reduce long-term stress on marketsThe case for a less interventionist Federal Reserve and what it means for investorsWhy thinking in decades, not quarters, can lead to higher conviction investingArtificial intelligence as a transformative economic force and its impact on semiconductors, energy, and productivityThe AI capex buildout, compute shortages, and lessons from past infrastructure boomsGold's resurgence as a global store of value in a multipolar worldThe difference between owning physical gold and gold mining stocksRisks and opportunities in private credit and business development companiesWhy illiquid assets may not belong in daily liquidity vehicles like ETFsIndia's long-term growth potential and implications for global portfoliosHow family ownership influences VanEck's long-term investment approachBehavioral mistakes investors make and why long-term charts matterLessons Jan would teach the average investor based on decades of market experienceTimestamps00:00 Introduction and VanEck's macro framework02:25 Translating macro views into product development04:34 2026 outlook and why visibility may mean risk on06:00 Fiscal deficits, interest rates, and market stress07:00 The future of Federal Reserve intervention10:48 Long-term investing versus short-term predictions14:00 India, global growth, and asset allocation19:00 Artificial intelligence, compute demand, and semiconductors24:00 AI, jobs, and economic impact29:00 AI capex, market concentration, and historical analogies38:31 Private credit risks and liquidity considerations40:35 Illiquid assets and ETFs42:56 Gold, global currencies, and long-term trends47:26 Gold miners versus physical gold52:14 Contrarian opportunities and underloved markets52:47 Advantages of a family-owned investment firm56:06 Tokenization, blockchain, and market structure59:45 Investor psychology and long-term charts01:02:05 Lessons for the average investor

In this episode of Excess Returns, Redfin Chief Economist Daryl Fairweather joins Matt Zeigler to unpack what she calls the Great Housing Reset. Rather than a housing crash or correction, Fairweather argues the market is entering a multi year transition toward something more normal, where incomes gradually catch up to home prices and affordability improves at the margin. The conversation covers mortgage rates, supply constraints, regional housing dynamics, climate risk, policy tradeoffs, and how AI is reshaping real estate decisions for buyers, renters, and investors.Topics covered in this episode• Why the current housing market is a reset, not a crash or correction• How income growth outpacing home price growth could slowly improve affordability• Mortgage rate dynamics and why rates may stay near the low 6 percent range• The mortgage rate lock in effect and why inventory may take years to normalize• Regional housing trends including the Midwest, Northeast, Sunbelt, and tech hubs• The role of wages, rents, and affordability for Gen Z and first time homebuyers• Investor activity, rental markets, and the outlook for housing as an investment• Immigration, foreign buyers, and local market distortions• Multi generational living, ADUs, and creative housing solutions• Housing policy ideas that actually address supply constraints• Why demand side policies like 50 year mortgages miss the real problem• Climate risk, insurance costs, and total cost of home ownership• How AI and conversational search are changing the home buying process• The future of MLS consolidation and real estate market structure• Practical guidance for renters, buyers, and homeowners looking ahead to 2026Timestamps00:00 Introduction and the Great Housing Reset02:00 What a housing reset really means03:30 Income growth versus home price growth05:20 Mortgage rates and the outlook for borrowing costs08:40 Fed policy, bond markets, and mortgage rates10:40 Inventory shortages and the lock in effect12:30 Regional housing market winners and losers16:00 Affordability challenges for younger buyers19:00 Rental markets and investor dynamics21:20 Multi generational living and ADUs25:00 Housing policy and supply constraints29:30 Why 50 year mortgages do not solve affordability33:00 Geographic housing outlook by life stage39:30 Climate risk, insurance, and housing costs47:00 Energy efficiency and dense housing50:20 AI, real estate search, and market structure54:30 What to watch in the housing market through 202659:30 Book discussion and where to follow Daryl Fairweather

In this episode of Excess Returns, Rupert Mitchell returns to break down a rapidly shifting global macro landscape and explain how he is positioning across regions, assets, and market regimes. The conversation spans emerging markets, commodities, China, Latin America, US market leadership, and the risks building beneath familiar narratives. Rupert walks through the charts, frameworks, and portfolio construction decisions that underpin his current outlook, with a focus on duration, cash flows, and real assets in a changing cycle.Topics covered include:Why US equity leadership is showing signs of fatigue after a decade-plus runThe case for emerging markets as a multi-year relative tradeLatin America as a commodity-driven opportunity rather than a political betBrazil, Mexico, and Peru through the lens of fiscal policy and real assetsWhy India stands out as expensive within emerging marketsChina's equity market inflection and the role of domestic savings and fiscal supportThe difference between onshore A-shares and offshore Chinese equitiesWhy Rupert prefers lower-beta, dividend-oriented exposure in ChinaHow AI is being deployed differently in China versus the USThe risks facing enterprise software and long-duration growth assetsPortfolio construction, benchmarking, and managing drawdowns across cyclesHow Rupert thinks about hedging, trend following, and capital preservationTimestamps:00:00 Macro market backdrop and early warning signals01:00 Venezuela, oil, and why context matters more than headlines04:40 The chart of truth and US versus international equities07:00 Emerging markets relative performance and historical parallels10:00 Duration risk, valuation, and the shift toward real assets14:30 Mag 7 leadership, software weakness, and AI disruption18:00 India valuations and the role of flows and derivatives20:40 Latin America beyond politics: commodities and fiscal drivers26:00 Brazil, Mexico, and country-level positioning29:50 Benchmarking and why Latin America is a major overweight32:10 China's equity inflection and the ABC framework36:00 Fiscal policy, buybacks, and domestic savings in China41:00 Tencent versus Alibaba and managing drawdowns44:30 AI capex discipline in China versus the US46:00 Stock selection in China and second-derivative opportunities51:00 Portfolio construction, benchmarks, and risk management58:00 Blind Squirrel Macro, live shows, and ongoing research

In this episode of Excess Returns, we sit down with Gary Mishuris, Managing Partner and CIO of Silver Ring Value Partners, to explore how deep fundamental analysis, behavioral insight, and disciplined process come together in real-world investing. Gary shares formative lessons from his early career at Fidelity during the post-tech bubble period, including firsthand experiences learning from legends like Peter Lynch, and connects those lessons to how he evaluates value, quality, and mispricing today. The conversation spans a detailed case study on Warner Bros. Discovery, portfolio construction under uncertainty, selective use of options, and how artificial intelligence is reshaping the research process for long-term investors.Topics covered in this episode• Lessons from Peter Lynch and Fidelity on why “just cheap” does not work• The Silver Ring origin story and how early life experiences shaped a value investing mindset• Warner Bros. Discovery as a good business plus bad business mispricing case study• How hated stocks, spin-offs, and catalysts can unlock hidden value• Conviction, position sizing, and staying rational when the market disagrees• When and why options can be used in a value investing framework• Auctions, ego, and why prices can overshoot intrinsic value• The role of mental models like reflexivity, activation energy, and lollapalooza effects• How AI fits into an investment research process without replacing judgment• What average investors should understand about incentives and simplicityTimestamps00:00 Introduction and why “just cheap” does not work02:20 Early career at Fidelity and lessons from Peter Lynch07:40 The Silver Ring story and learning what real value means12:00 Warner Bros. Discovery and the good company bad company problem18:30 Conviction, mispricing, and maintaining discipline in hated stocks26:40 Using options selectively and managing portfolio-level risk34:10 Auctions, ego, and when price can detach from intrinsic value44:30 Entertainment, media disruption, and evergreen demand for content49:50 How AI is changing equity research and idea generation55:40 What AI can see that humans often miss01:00:30 One lesson for the average investor

In this episode of Excess Returns, we sit down with Mike Green of Simplify Asset Management for a deep dive into how passive investing has reshaped market structure, altered price discovery, and created new sources of systemic risk beneath the surface of today's equity markets. Mike explains why index funds are not as passive as most investors believe, how daily flows drive prices in increasingly inelastic markets, and why the growth of passive strategies may be pushing markets toward an unstable endpoint. The conversation also explores macro implications, AI-driven capital spending, demographic shifts, and what all of this means for investors navigating the years ahead.Topics coveredHow passive investing and ETF flows actively influence market pricesThe inelastic market hypothesis and why markets absorb flows differently than investors expectWhy index funds no longer fit the classic definition of passive investingThe growing share of passive ownership and what happens as it continues to risePotential market instability and the theoretical limits of passive dominanceHow demographics, retirement flows, and 401k defaults affect market structureCritiques of arguments downplaying the impact of passive investingWhy large-cap concentration keeps increasing despite slowing fundamentalsImplications for active management, stock selection, and liquidityThe role of AI, capital expenditures, and energy constraints in the macro outlookWhat rising electricity demand and infrastructure investment mean for the economyHousing market distortions, demographics, and long-term structural challengesTimestamps00:00 Introduction and why passive investing is not truly passive03:00 The inelastic market hypothesis explained06:00 Daily flows, index funds, and price impact08:20 How much of the market is now passive11:40 What happens if passive investing keeps growing14:20 Retirement flows and demographic effects on markets19:00 Responding to critiques of passive market impact23:00 Liquidity, concentration, and large-cap dominance27:00 Why market cap does not equal liquidity33:00 Active management under pressure38:00 Current market conditions and early-year rotations41:50 Economic growth, GDP, and underlying volatility43:30 AI capex, overinvestment, and market incentives47:00 Energy, electricity demand, and long-term constraints52:40 Housing, demographics, and policy challenges

This episode of Excess Returns features Gene Munster and Doug Clinton breaking down their 2026 technology and market predictions, with a deep focus on artificial intelligence, big tech, and where investors may be misreading the current cycle. The conversation explores how far along the AI bull market really is, what fundamentals still support it, and where the biggest opportunities and risks may emerge over the next several years. Munster and Clinton discuss market structure, capital spending, valuation, and technological inflection points across AI, software, hardware, and autonomous driving, offering a grounded but forward-looking framework for long-term investors.Main topics coveredWhy the AI bull market may still have multiple years left and how fundamentals support current valuationsNasdaq return expectations through 2026 and what earnings and multiples imply for investorsThe case for small-cap and non–Mag Seven tech outperforming as the AI cycle maturesHyperscaler AI capital spending and why CapEx growth could exceed current expectationsWhether AI pricing pressure leads to commoditization or expanding long-term value creationHow AI is changing the economics of infrastructure, platforms, and asset-heavy tech businessesApple's AI strategy, the future of Siri, and why expectations matter for valuationAlphabet, Amazon, and the evolving AI competition among the largest technology companiesEnergy constraints, data centers, nuclear power, and the infrastructure needed to support AI growthTesla, Waymo, and the realistic timeline for autonomous driving and robotaxi adoptionHow physical AI, autonomy, and robotics could reshape transportation and consumer behaviorTimestamps00:00 AI cycle outlook and why the bull market may still be early05:00 Nasdaq return expectations and earnings fundamentals10:30 Small-cap tech versus Mag Seven performance17:15 Hyperscaler AI CapEx and Nvidia's signals24:00 Infrastructure, pricing power, and AI commoditization debates32:30 Apple, Siri, and consumer AI assistants38:50 Alphabet, Amazon, and AI competition among mega-cap tech45:00 Energy, data centers, and nuclear power considerations48:10 Tesla, autonomy, and robotaxi timelines54:15 Waymo, market share, and the future of transportation

In this episode of Excess Returns, Professor Aswath Damodaran joins Matt Zeigler and Kai Wu for a wide-ranging conversation on valuation, portfolio construction, and how investors should think about risk, discipline, and opportunity in a market shaped by AI, market concentration, and rising uncertainty. Damodaran walks through how he builds and manages his own portfolio, why price matters more than story or quality, and how AI-driven capital spending could reshape margins and returns across the economy. The discussion blends practical investing frameworks with big-picture market insights, offering a clear look at how a valuation-driven investor navigates today's environment.Main topics covered• How Aswath Damodaran builds a stock portfolio, including diversification, position sizing, and turnover• Why investing is about buying at the right price, not buying great companies• Using valuation frameworks to invest in young, unprofitable, and fast-growing companies• How stories and narratives fit into valuation without replacing financial discipline• Watchlists, patience, and waiting for price rather than chasing popular stocks• Sell discipline, overvaluation triggers, and avoiding emotional attachment to winners• Using probability distributions and simulations instead of single-point estimates• How company lifecycles affect growth, margins, and capital allocation decisions• Why many companies struggle as they age and how management quality shows up late in the lifecycle• AI as a capital cycle and why massive AI investment may lower margins overall• Why AI is likely to create a bubble, even if it delivers long-term economic value• Winners and losers in the AI value chain, from infrastructure to applications• Risks from AI infrastructure spending, debt, and cross-ownership structures• Why private markets may not deliver better outcomes for individual investors• How Damodaran thinks about cash, diversification, and assets uncorrelated with equities• Reentering markets after selling and avoiding the trap of staying in cash too long• Time horizon, legacy investing, and managing wealth across generationsTimestamps00:00 Investing is about price, valuation, and early thoughts on AI and market risk01:54 Personal investing philosophy and why portfolios must be investor-specific03:00 Diversification, number of holdings, and managing downside risk05:00 Valuation frameworks and buying companies at the right price06:00 Stories versus numbers and avoiding the circle of competence trap08:20 Political risk and why some sectors are hard to value08:47 Watchlists, patience, and waiting for price to meet value11:43 When and why to sell stocks as a value investor12:00 Using probability distributions and simulations in valuation15:48 Sell discipline, fund flows, and separating skill from luck18:00 Company lifecycles, aging businesses, and management discipline23:18 Apple, Meta, and contrasting approaches to AI investment24:08 AI bubbles, winner-take-all dynamics, and capital cycles27:48 Infrastructure investing, debt risk, and societal spillovers32:20 Cross-ownership risks and AI ecosystem fragility35:00 AI's impact on profit margins and competition39:41 Where AI value may accrue over time44:38 AI tools, valuation bots, and the rise of investment scams49:17 Private markets, alternatives, and cost structures53:05 Cash, collectibles, and diversification beyond equities56:33 Reentering markets after selling and avoiding market timing traps58:35 Time horizon, legacy investing, and generational wealth

In this episode of Excess Returns, we welcome back Liz Ann Sonders to discuss the evolving market and economic landscape heading into 2026. The conversation focuses on why this cycle feels fundamentally different, how instability rather than uncertainty is shaping investor behavior, and what that means for inflation, the labor market, Federal Reserve policy, and equity markets. Liz Ann breaks down the growing bifurcation across the economy and markets, the shift away from the Great Moderation era, and how investors should think about diversification, earnings, valuations, and AI-driven capital spending in a more volatile and fragmented environment.Main topics covered• Why today's environment is better described as unstable rather than uncertain• The K-shaped economy and growing bifurcation across consumers, sectors, and markets• Inflation dynamics and why 2 percent may now be a floor rather than a ceiling• How deglobalization, supply chains, and tariffs are changing the inflation regime• The shifting relationship between stocks and bonds• Hard data versus soft data and what sentiment is really telling us• The labor market's headwinds and tailwinds, including immigration and hiring trends• AI's impact on productivity, jobs, and capital spending• The AI capex boom and how it differs from the late 1990s tech cycle• Earnings growth, valuation compression, and market broadening• Rolling recessions versus traditional economic downturns• Federal Reserve challenges under a conflicted dual mandate• Why factor-based investing matters more than sector or style callsTimestamps00:00 Introduction and why this cycle feels different02:00 Uncertainty versus instability in markets03:30 The K-shaped economy and market bifurcation07:00 Market broadening, small caps, and diversification09:00 Inflation measurement challenges and data reliability12:00 Why inflation may stay above 2 percent15:00 Stock and bond correlations across cycles17:30 Labor market crosscurrents and immigration effects20:45 AI, productivity, and entry-level job pressures24:30 Sentiment versus fundamentals in markets27:30 Retail trading, behavior, and market psychology31:00 Rolling recessions and post-pandemic distortions38:00 Technology, cyclicality, and sector rotation40:30 The Fed's policy dilemma and internal disagreements45:00 AI capital spending and comparisons to the dot-com era51:00 Earnings growth versus valuation expansion55:00 Factors, GARP, and portfolio positioning for 2026

This episode of Excess Returns features a wide ranging conversation with Grant Williams on what he calls the hundred year pivot. Grant explains why today's environment feels fundamentally different from the last several decades, why long held investing assumptions may no longer apply, and how declining trust in institutions, money, and markets is reshaping the global financial system. Drawing on history, macroeconomics, and decades of market experience, the discussion explores what this transition means for investors trying to navigate a world defined by uncertainty, volatility, and structural change.Main topics covered• What the hundred year pivot means and why it represents a once in a generation shift• The Fourth Turning framework and how it connects financial crises, politics, and social change• Why buy the dip worked for decades and why it may fail in the years ahead• The erosion of trust in institutions and its impact on markets and money• The financial crisis, sanctions, and the freezing of sovereign assets as turning points• The role of the dollar, gold, and central banks in a changing monetary system• Lessons from history including Bretton Woods and the Suez crisis• Why commodities and real assets matter in a world of deglobalization and reshoring• How artificial intelligence fits into the current investment cycle and capital allocation boom• Portfolio construction and behavioral challenges in a higher volatility environmentTimestamps00:00 The hundred year pivot and why this cycle is different01:30 Defining the Fourth Turning and historical cycles07:40 The financial crisis as the start of institutional breakdown11:00 Sanctions, sovereign assets, and the end of unquestioned trust in the dollar18:20 Historical parallels from Bretton Woods and the Suez crisis24:50 What could trigger a broader monetary reset28:50 Energy, geopolitics, and shifting global alliances35:00 Commodities, real assets, and rebuilding supply chains42:40 Artificial intelligence, capital cycles, and uncertainty52:30 Portfolio construction, behavior, and risk tolerance59:50 Where to follow Grant Williams and his work

In this episode of Excess Returns, we dive deep into one of the most pressing investing debates today: how to think about valuations, profit margins, and artificial intelligence in a market that feels both expensive and transformative. Sam Ro joins Matt Zeigler and Kai Wu for a wide-ranging conversation that explores whether traditional valuation tools still matter, how AI is reshaping corporate economics, and why history suggests investors should be cautious about bubble narratives even when enthusiasm runs high. From profit margins and capital intensity to the future of the Magnificent Seven, this episode focuses on how long-term investors can frame uncertainty without relying on false precision or short-term market calls.Timestamps00:00 Valuations, bubbles, and why timing markets is so hard01:41 Do valuations still matter for investors05:58 S&P 500 valuation levels versus history09:30 Profit margins and why mean reversion has not shown up yet14:39 Household finances, pricing power, and consumer resilience15:47 AI, productivity, and the limits of forecasting economic impact19:15 Valuations adjusted for structurally higher profit margins21:15 Tech multiples, growth expectations, and PEG ratios24:07 Are we in an AI bubble and why that question may not help29:14 Lessons from past bubbles and irrational exuberance30:14 How transformative AI could be compared to past innovations35:20 Massive AI capital spending and the risk of overbuild39:42 Who captures value in AI: builders versus users46:39 Revenue per worker and productivity trends48:00 Dispersion inside the Magnificent Seven51:34 Big tech shifting from asset-light to asset-heavy models59:53 Turnover among top companies over time01:01:10 Why Wall Street price targets miss the point01:04:30 Presidential cycles and market returns01:06:28 Fund manager surveys and why popular risks are often lagging indicatorsTopics coveredHow investors should think about valuations over long time horizonsWhy elevated profit margins may be more structural than cyclicalThe role of AI in productivity, earnings, and competitive dynamicsBubble psychology and lessons from the dot-com eraCapital intensity, overinvestment, and the risk of write-downsWhy AI infrastructure builders may not capture most of the valueWhat dispersion within the Magnificent Seven signals for marketsWhy broad diversification still matters in a rapidly changing market

In this episode of Excess Returns, Katie Stockton of Fairlead Strategies joins Matt Zeigler and Justin Carbonneau to walk through her technical outlook for markets as we head into 2026. The conversation focuses on trend analysis, momentum, volatility, and risk management across U.S. equities, sectors, international markets, and alternative assets. Rather than making predictions, Katie explains how she reacts to price, confirms signals, and uses a disciplined technical process to identify opportunities and manage downside risk in changing market environments.Main topics coveredMarket trend outlook for U.S. equities heading into 2026Why long-term trends remain constructive despite rising short-term risksHow to think about volatility, consolidation, and corrective phasesWhat loss of momentum in late 2025 signals for near-term positioningHow to use triangle formations, support, and resistance levelsUnderstanding DeMark indicators, MACD, and stochastic signalsLeadership shifts within large-cap technology and the Mag 7Growth versus value dynamics across market capsSmall caps, market breadth, and participation signalsSector rotation insights including technology, healthcare, financials, energy, utilities, and real estateHow sentiment indicators like fear and greed fit into a broader processGold, silver, and precious metals trends and volatilityBitcoin and crypto from a technical perspectiveThe U.S. dollar, yields, and global market implicationsInternational and emerging market opportunitiesHow the Fairlead Tactical Sector ETF is constructed and used in portfoliosWhere a tactical, risk-managed strategy can fit within asset allocationTimestamps00:00 Market setup and trend perspective for 202601:25 Long-term uptrend versus short-term risk04:16 Momentum loss and near-term caution06:00 Nasdaq 100 triangle and volatility setup07:45 Ichimoku clouds and trend confirmation11:01 Using consolidation and support levels13:05 Tech leadership and relative strength shifts18:30 Small caps, breadth, and market participation21:01 Growth versus value across market caps23:00 Market breadth and advance-decline signals24:13 Sentiment, fear and greed, and retests30:00 Breakouts, catalysts, and confirmation32:00 Sector rotation overview35:00 Energy, real estate, and rate-sensitive sectors39:10 Fairlead Tactical Sector ETF strategy45:00 International and emerging markets47:36 Gold, silver, and precious metals51:04 U.S. dollar and currency trends54:00 Bitcoin and crypto technical outlook57:12 Key indicators to watch going forward59:07 Long-term takeaways for investors

Subscribe to the Jim Paulsen Show on Apple Podcasts⁠⁠https://podcasts.apple.com/us/podcast/the-jim-paulsen-show/id1828054999⁠⁠Subscribe on Spotify⁠⁠https://open.spotify.com/show/3QaBDVGuBZ3cZfFZ4mqPFc⁠⁠In this episode of the Jim Paulsen Show, Jim Paulsen joins Jack Forehand and Justin Carbonneau to break down what the economy and markets may really be signaling beneath the headline numbers. Drawing from his recent outlook and long history studying market cycles, Jim explains why growth may be weaker than it appears, how policy lags are shaping the outlook, and why today's market looks very different from past late-cycle environments. The conversation explores the divide between the “new era” economy and the rest of the market, what that means for investors in 2026, and where opportunities may be emerging as monetary and fiscal policy begin to shift.Topics covered in this episode• Why headline GDP growth may be overstating the true strength of the economy• How trade distortions are affecting recent GDP data• The concept of a “no-shaped economy” and the divide between new era and old era businesses• Labor market signals that suggest economic sluggishness beneath the surface• Why this may be one of the most disliked bull markets in history• The role of policy lags and why easing could matter more than investors expect• How market concentration has shaped returns over the last several years• Warning signs emerging within the technology sector• The relationship between corporate cash levels, R&D spending, and tech leadership• Why market breadth and old era sectors may become more important going forward• Thoughts on bonds, stocks, commodities, gold, and portfolio positioning• Why international and emerging markets could benefit from a weaker dollar• How investors might think about diversification in an unusual market cycleTimestamps00:00 Introduction and key themes from Jim's outlook03:00 Why the economy may be weaker than GDP headlines suggest06:00 Labor market signals and recession-like dynamics12:00 Policy lags, the Fed, and why growth could soften further15:00 Market performance after multiple strong years18:00 The no-shaped economy and the split between new era and old era24:00 Strange market signals at all-time highs27:00 Valuations, sentiment, and why pessimism matters29:00 Fed easing expectations and consensus forecasts35:00 Warning signs for technology stocks42:00 Corporate cash, R&D spending, and tech leadership risks47:00 Portfolio construction and asset allocation thinking55:00 Final thoughts on opportunities and risks ahead

In this wide-ranging conversation, Gautam Baid joins Excess Returns to discuss the principles that shaped his investing philosophy, the lessons learned through bear markets, and why compounding, patience, and quality matter far more than forecasts or short-term performance. Drawing from his books The Joys of Compounding and The Making of a Value Investor, Baid shares a deeply reflective framework for long-term investing, portfolio construction, behavioral discipline, and global diversification, with insights spanning Indian and US markets, liquidity cycles, AI, and investor psychology.Main topics covered• The asymmetric power of compounding and why being wrong half the time can still lead to exceptional long-term returns• Why patience, temperament, and behavior matter more than analytical precision in investing• The role of journaling in improving decision-making and avoiding repeated behavioral mistakes• How investor sentiment reveals itself through IPO markets and portfolio quality late in bull cycles• Why long-term investing requires continuous monitoring rather than buy-and-forget complacency• Letting winners run, cutting losers, and understanding power-law outcomes in stock markets• Liquidity cycles and how they drive market returns in both India and the United States• How bear markets reshape investing philosophy toward resilience, quality, and diversification• When averaging down makes sense and when it is dangerous• The differences between Indian and US equity markets, valuations, and governance• Why home country bias can be a major risk for US-based investors• AI, productivity, profitability, and where future market winners may emerge beyond mega-cap tech• Why passion for investing matters more than money in sustaining long-term successTimestamps00:00 Introduction and the asymmetric nature of compounding01:00 Gautam Baid's investing background and books03:00 The importance of journaling and learning through bear markets06:00 Investor sentiment, IPOs, and late-cycle market behavior10:20 Long-term investing versus complacency and monitoring risk14:15 Convex upside, concave downside, and letting winners run18:30 Liquidity cycles and lessons from Stan Druckenmiller22:45 Identifying market bottoms and the anatomy of bull and bear markets28:00 Averaging down, quality, and risk management30:30 How bear markets change investor psychology and strategy33:00 Patience, management quality, and long-term optionality36:15 Mr. Market, price signals, and market intelligence39:00 The Federal Reserve, inflation, and asset price dynamics44:00 Understanding the Indian equity market and valuation structure46:45 Why global diversification matters for US investors50:30 AI, margins, and the future of value investing53:00 Passion, purpose, and the psychology of long-term investing54:30 The single most note investors should learn

In this episode of Excess Returns, Jack Forehand and Matt Zeigler dig into forecast season by reviewing and synthesizing insights from 22 major Wall Street and institutional market outlooks. Rather than treating year-end forecasts as precise predictions, the conversation uses them as a framework for understanding consensus views, hidden assumptions, and where the real risks and surprises for 2026 may lie. The discussion spans macroeconomic conditions, AI-driven growth, earnings expectations, valuation risks, and the growing divergence beneath headline market performance, helping investors think more clearly about the range of outcomes ahead.Main topics covered• Why year-end market forecasts are still useful despite being consistently wrong on exact targets• What consensus forecasts reveal about expectations for economic growth in 2026• The role of artificial intelligence in driving earnings, productivity, and capital spending• Reacceleration versus late-cycle slowdown and how forecasters are split on the outlook• Inflation expectations, interest rates, and the likelihood of fewer Fed cuts than expected• Fiscal policy, deficits, and the growing role of government stimulus• Energy constraints, data centers, and the physical limits of the AI buildout• Profit margin expansion versus revenue growth and why this matters for valuations• S&P 500 price targets, earnings assumptions, and where optimism and caution diverge• The dominance of the Magnificent Seven and the debate over market and earnings broadening• Risks beneath the surface, including margin compression, valuation resets, and sector rotation• What investors can learn by comparing the most bullish and most bearish forecastsTimestamps00:00 Forecast season and why reading outlooks still matters03:00 Why precise market targets are misleading but informative05:30 Using consensus forecasts to identify risks and surprises08:30 AI, economic reacceleration, and productivity expectations13:00 Recession risks, stagflation fears, and late-cycle dynamics17:00 Inflation outlook and why it may reemerge later in the year22:00 Fed policy, rate cuts, and rising internal dissent26:00 Fiscal stimulus, deficits, and long-term consequences28:00 AI infrastructure, energy constraints, and data centers35:00 AI diffusion and real-world productivity gains39:00 S&P 500 targets, earnings growth, and valuation assumptions43:00 Profit margins, mean reversion, and long-term risks47:00 Magnificent Seven earnings versus the rest of the market52:00 Market broadening, international stocks, and diversification56:00 Key takeaways for investors heading into 2026

In this special compilation episode of Excess Returns, we ask one revealing question to some of the most respected investors, strategists, and market thinkers in the industry:What is one belief you hold about investing that most of your peers would disagree with?The answers challenge conventional wisdom across macro, valuation, diversification, options, forecasting, AI, and investor behavior.Rather than consensus, this episode highlights how great investors think differently about risk, uncertainty, and long-term outcomes.00:06 Jim Grant – Why gold has been, is, and will remain money02:14 Andy Constan – Why quantitative easing is always pro-growth and inflationary03:36 Liz Ann Sonders – Why year-end market price targets are a useless exercise04:56 Richard Bernstein – Why the stock market is ownership, not a horse race06:33 David Giroux – Why macro investing does not create long-term alpha08:00 Meb Faber – Why dividend investing narratives are often misunderstood11:44 Sam Ro – When valuations actually matter and when they don't13:27 Jason Buck – Why belief systems in investing are often built on insecurity15:16 Mike Green – Why markets change when metrics become targets17:16 Jerry Parker – Why the Sharpe ratio fails for asymmetric return strategies19:15 Chris Mayer – Why trimming great businesses often hurts long-term returns21:14 Joseph Shaposhnik – Why a stock that has doubled may still be early24:27 Warren Pies – Why price and technicals are essential for managing risk25:33 Katie Stockton – Why technical analysis can stand on its own27:17 Jim Paulsen – Why policy makers matter less than cultural and economic forces28:41 Adam Parker – Why differentiated thinking is the only real edge versus the index30:29 Rupert Mitchell – Why copying great investors is a mistake31:18 Victor Haghani – Why asset allocation should be dynamic, not static33:09 Dan Rasmussen – Why historical growth tells you almost nothing about future growth33:45 Graeme Forster – Why you don't just need to be right 60% of the time35:40 Shannon Saccocia – Why investors should think more like futurists than historians36:21 Cem Karsan – Why options are not derivatives, but the true underlying40:31 Aahan Menon – Why tariffs and macro news matter less than investors think41:49 Andrew Beer – Why simple bets often outperform complex strategies44:09 Bogumil Baranowski – Why successful investing requires far less work than people believe45:55 Rick Ferri – Why advice fees and asset management fees should be separated46:57 Cameron Dawson – Why multidisciplinary thinking is essential for investors48:24 Mary Ann Bartels – Why blue chip dividend investing still has a place49:40 Travis Prentice – Why turnover depends entirely on the strategy50:24 Scott McBride – Why catalysts are overrated in value investing50:58 Jared Dillian – Why tariffs and protectionism make economies poorer53:35 Peter Atwater – Why shareholders are no longer the top corporate priority54:34 Ian Cassel – Why turnover myths persist in microcap investing55:31 Kris Sidial – Why trading psychology matters more than models56:17 Noel Smith – Why top hedge fund returns are not the upper limit57:09 Kai Wu – How AI will reshape investing jobs without replacing humans01:00:49 Tim Hayes – Why markets cannot be forecast reliably01:02:12 Doug Clinton – Why AI-powered asset management could be a multi-trillion-dollar industry

In this episode of Excess Returns, we sit down with Paul Eitelman, Global Chief Investment Strategist at Russell Investments, to unpack their 2026 outlook and the idea of a “Great Inflection Point” for markets and the economy. Paul explains why the U.S. economy may be shifting from resilience to reacceleration, how artificial intelligence is moving from hype to measurable returns, and why market leadership could finally broaden beyond the Magnificent Seven. The conversation blends macroeconomic analysis, behavioral finance, and real-world portfolio implications, offering investors a framework for thinking about growth, risk, and diversification as we head into 2026.Main topics covered• The cycle, valuation, and sentiment framework and how it shapes investment decisions• Why economic growth may reaccelerate in 2026 after navigating policy headwinds• Accelerating AI adoption and what early signs of ROI mean for productivity and profits• The J-curve of new technologies and where AI may sit today• Capital spending, leverage, and profitability risks among hyperscalers and large tech firms• Energy demand, labor market impacts, and other societal risks tied to AI• Tariffs, immigration, and uncertainty as fading or manageable economic headwinds• Financial conditions, fiscal stimulus, and deregulation as emerging tailwinds• The gap between hard economic data and weak consumer sentiment• Why recession forecasts have been wrong and how to think about recession risk going forward• Inflation dynamics, the Federal Reserve's priorities, and the outlook for rates• The case for market broadening beyond the Magnificent Seven• Global diversification, small caps, international equities, and emerging markets• Behavioral finance, investor sentiment, and staying invested through volatility• Portfolio construction implications, including real assets and alternativesTimestamps00:00 Introduction and the Great Inflection Point outlook03:00 Cycle, valuation, and sentiment investing framework05:50 From economic resilience to potential reacceleration07:00 AI as a transformational technology and historical parallels09:20 Measuring returns on AI investment and productivity gains11:00 The AI J-curve and timing of benefits13:00 Capital intensity, leverage, and risks for big tech15:00 Energy demand, labor markets, and AI risks19:00 How Paul uses AI in his own research workflow20:30 The case for economic reacceleration into 202621:40 Tariffs and their real economic impact23:20 Immigration and labor supply effects24:10 Uncertainty, confidence, and business decision-making26:10 Financial conditions and household wealth28:00 Fiscal stimulus and the One Big Beautiful Bill Act29:20 Deregulation as a potential growth tailwind30:40 Hard data versus soft data in the economy34:10 Why recession forecasts failed37:10 Recession risk outlook for 202640:30 Inflation dynamics and the Fed's focus43:50 Broadening market leadership beyond the Magnificent Seven46:10 Investor sentiment, panic, and opportunity49:00 Translating macro views into portfolio strategy51:30 Real assets, alternatives, and diversification54:30 Investing lessons, compounding, and staying invested

In the latest episode of Click Beta, Matt Zeigler, Dave Nadig and Cameron Dawson take a look back at 2025 and a look forward to 2026. Subscribe to Click Beta via the links below. Follow Click Beta:Spotify⁠https://open.spotify.com/show/0u1fxie4C4vHXIJPUMhvUs⁠Apple Podcasts⁠https://podcasts.apple.com/ky/podcast/click-beta/id1793929457⁠YouTube:⁠https://www.youtube.com/excessreturns

In this episode of Excess Returns, we sit down with Adrian Helfert of Westwood to discuss how investors should be thinking about portfolio construction in a market shaped by artificial intelligence, high levels of concentration, shifting interest rate dynamics, and evolving economic signals. The conversation covers how AI-driven capital spending is changing return profiles across markets, why traditional investing rules are breaking down, and how investors can balance growth, income, and risk in an uncertain environment. Adrian shares his framework for understanding return drivers, his views on market concentration and valuation, and how to think about diversification, macro risk, and income generation going forward.Main topics covered• How Westwood frames portfolio construction around capital appreciation, income, and event-driven returns• Why AI spending is both a major opportunity and a growing existential risk for large companies• The sustainability of market concentration and what it means for future returns• Whether higher interest rates really hurt growth stocks the way investors expect• How massive data center and AI capital expenditures could translate into productivity gains• The case for market broadening beyond the Magnificent Seven• Why traditional recession indicators have failed in recent cycles• How inflation, labor markets, and Federal Reserve policy interact today• Rethinking the classic 60/40 portfolio and the role of private markets• Using covered calls and active income strategies to manage risk and generate yieldTimestamps00:00 Introduction and near-term opportunities versus long-term risk02:40 Capital appreciation, income, and event-driven investing framework06:30 Have markets structurally changed to support higher returns09:30 Intangible assets, AI, and margin expansion10:20 The scale of AI and data center capital spending13:00 Productivity gains and return on investment from AI16:00 AI as both opportunity and risk for companies19:30 Market concentration and diversification concerns23:30 Will market leadership eventually broaden25:30 Growth stocks, duration, and interest rates29:30 International diversification and global investing33:30 Why recession indicators have failed39:00 Inflation outlook and Federal Reserve policy46:00 Rethinking the 60/40 portfolio53:00 Enhanced income strategies and covered calls59:00 One investing belief most peers disagree with

In this special episode, Adam Butler and Ben Hunt join Matt Zeigler to unpack one of the most charged debates in markets and economics today: whether our official statistics still reflect lived reality. Building on Mike Green's work and Adam Butler's essay The Bureau of Missing Children, the conversation moves beyond the technical definition of poverty to a deeper idea of economic precarity, the growing gap between what we measure and what people actually experience. Together, they explore debt, housing, childcare, labor mobility, AI, and the erosion of meaning in economic language, while wrestling with what policy, community, and human-centered solutions might look like in a world that increasingly feels unstable.Main topics coveredWhy the debate should focus on precarity rather than povertyThe disconnect between inflation statistics and lived experienceHow debt, housing, childcare, and education drive economic insecurityThe idea of a participation budget for modern family formationWhy labor mobility has broken down since the financial crisisHow asset prices and credit intensify risk for householdsThe role of grandparents and off-balance-sheet support in the economyDarwin's wedge, positional goods, and rising costs of everyday lifeThe impact of AI, technocracy, and anti-human incentivesCentralized versus decentralized solutions to today's economic challengesWhat it means to carry the fire and preserve human-centered valuesTimestamps00:00 Introduction and the emotional roots of the precarity debate02:00 Poverty versus precarity and what we are really measuring06:30 Technocrats, narratives, and the limits of economic statistics09:00 Personal experiences with precarity and debt15:00 The Bureau of Missing Children and family formation economics21:00 Modeling household income and participation budgets25:50 Rising costs of childcare, housing, and everyday life33:00 Darwin's wedge and positional competition36:45 Debt, housing, and labor immobility40:00 Grandparents, unpaid care, and off-balance-sheet subsidies46:30 How today differs from 40 or 50 years ago49:40 Labor mobility as a lost engine of opportunity55:00 Policy paths, mission-driven economics, and decentralization01:11:00 Visionary leadership versus bottom-up solutions01:15:50 Carrying the fire and preserving meaning01:17:30 Where to follow Adam Butler and Ben Hunt

In this episode of Excess Returns, we sit down with David Wright, Head of Quantitative Investing at Pictet Asset Management, for a deep and practical conversation about how artificial intelligence and machine learning are actually being used in real-world investment strategies. Rather than focusing on hype or black-box promises, David walks through how systematic investors combine human judgment, economic intuition, and machine learning models to forecast stock returns, construct portfolios, and manage risk. The discussion covers what AI can and cannot do in investing today, how machine learning differs from traditional factor models and large language models like ChatGPT, and why interpretability and robustness still matter. This episode is a must-watch for investors interested in quantitative investing, AI-driven ETFs, and the future of systematic portfolio construction.Main topics covered:What artificial intelligence and machine learning really mean in an investing contextHow machine learning models are trained to forecast relative stock returnsThe role of features, signals, and decision trees in quantitative investingKey differences between machine learning models and large language models like ChatGPTWhy interpretability and stability matter more than hype in AI investingHow human judgment and machine learning complement each other in portfolio managementData selection, feature engineering, and the trade-offs between traditional and alternative dataOverfitting, data mining concerns, and how professional investors build guardrailsTime horizons, rebalancing frequency, and transaction cost considerationsHow AI-driven strategies are implemented in diversified portfolios and ETFsThe future of AI in investing and what it means for investorsTimestamps:00:00 Introduction and overview of AI and machine learning in investing03:00 Defining artificial intelligence vs machine learning in finance05:00 How machine learning models are trained using financial data07:00 Machine learning vs ChatGPT and large language models for stock selection09:45 Decision trees and how machine learning makes forecasts12:00 Choosing data inputs: traditional data vs alternative data14:40 The role of economic intuition and explainability in quant models18:00 Time horizons and why machine learning works better at shorter horizons22:00 Can machine learning improve traditional factor investing24:00 Data mining, overfitting, and model robustness26:00 What humans do better than AI and where machines excel30:00 Feature importance, conditioning effects, and model structure32:00 Model retraining, stability, and long-term persistence36:00 The future of automation and human oversight in investing40:00 Why ChatGPT-style models struggle with portfolio construction45:00 Portfolio construction, diversification, and ETF implementation51:00 Rebalancing, transaction costs, and practical execution56:00 Surprising insights from machine learning models59:00 Closing lessons on investing and avoiding overtrading

In this episode of our new show The 100 Year Thinkers, Robert Hagstrom, Chris Mayer, Bogumil Baranowki and Matt Zeigler explain how investors get trapped by labels, abstractions, and simplistic models, and why breaking free with better mental models, language, and long-term thinking is a real edge in markets.Subscribe on Spotify⁠⁠https://open.spotify.com/show/5IsVVM27KWP6SUW6KN2ife⁠⁠Subscribe on Apple Podcasts⁠⁠https://podcasts.apple.com/us/podcast/the-100-year-thinkers-long-term-compounding-in-a-short-term-world/id1845466003⁠⁠Subscribe on YouTube⁠⁠https://youtube.com/@excessreturns⁠

Brent Kochuba takes a look behind the scenes at the options flows driving the market heading into the December options expiration and the end of 2025. Subscribe on Spotify⁠https://open.spotify.com/show/4KR2YVJqk2lnVETMKDavJf⁠Subscribe on Apple Podcasts⁠https://podcasts.apple.com/us/podcast/the-opex-effect/id1711880009⁠Subscribe on YouTube⁠https://www.youtube.com/channel/UCPYvx_y92dvI1PSdiho0ALw

Ed Yardeni returns to Excess Returns to break down the evolving market landscape, why he moved the Magnificent 7 to underweight, and how AI, productivity, interest rates, global markets, and sector leadership will shape the next stage of the Roaring 2020s. Ed explains why the economy has remained so resilient, what could finally trigger a true market broadening, and how investors should think about everything from tech competition to inflation, private credit risks, and Fed policy heading into 2026.Main topics covered• Why Ed reduced the Magnificent 7 and tech from overweight to market weight• How extreme sector concentration affects portfolio construction• The escalating competition inside AI and large-cap tech• The AI CapEx boom and how it changes earnings, margins, and valuation• Valuation considerations for tech leaders at this stage of the cycle• Whether the Mag 7 should be compared to past tech bubbles• How AI adoption may spread to the broader economy and boost productivity• Economic impact of AI on jobs, wages, and long-term inflation• Why the US economy avoided recession despite persistent warnings• Rolling recessions vs traditional recessions and how they shape markets• Private credit risks and whether they pose a systemic threat• Prospects for small caps, mid caps, financials, industrials, and healthcare• Why 2026 may finally bring true market broadening• The outlook for international investing and emerging markets• Ed's S&P 500 roadmap to 7,700 next year and 10,000 by 2029• Fed policy, rate cuts, inflation, bond vigilantes, and political pressure• Key risks investors should monitor heading into 2026Timestamps00:00 Mag 7 concentration and the case for rebalancing03:00 How Ed builds probability-based market scenarios04:30 Why the Roaring 2020s thesis still holds06:00 The no-show recession and economic resilience07:00 Why he moved the Mag 7 and tech to market weight09:30 How every company is becoming a technology company12:20 Knowing when a successful thesis has run its course13:30 The dominance of the US market and global diversification15:00 Why market weight, not overweight, for tech and the Mag 716:00 Tech competition, AI leapfrogging, and margin pressure18:30 The CapEx boom and valuation questions21:00 Comparing today's tech leaders to the 2000 era23:00 How AI could lift productivity across the entire economy25:00 Putting AI in historical context27:00 How new technologies solve constraints like energy and compute29:00 AI's long-term impact on productivity and growth30:00 Labor market disruption and job transition dynamics31:20 Will AI be deflationary over time?32:30 Technology, China, automation, and global deflation forces33:00 Ed's forecast for the S&P 500 through 202935:00 Why recession indicators failed this cycle37:00 How liquidity facilities prevent credit crunches39:00 Private credit risks and transparency challenges40:45 The potential for market broadening in 202642:20 Takeaways from the latest Fed meeting44:00 Should the Fed be cutting rates?45:00 Fed independence under political pressure47:00 Why bond vigilantes may return in 202648:00 International investing opportunities and ETFs49:30 Closing thoughts and key risks ahead

We are including this episode from our separate show Teach Me Like I'm Five in the Excess Returns feed. If you would like to continue receiving new episodes, subscribe using the links below.In the episode, we sit down with Business Breakdowns host Matt Reustle to discuss how he breaks down businesses and the common characteristics that the best businesses he has looked at share. Subscribe on Spotifyhttps://open.spotify.com/show/7zu6lFpPohoPKhcu0Er9kBSubscribe on Apple Podcastshttps://podcasts.apple.com/hr/podcast/teach-me-like-im-five-investing-concepts-made-simple/id1815975642

In this episode of Excess Returns, Graeme Forster of Orbis joins us to discuss two major research papers: Six Courageous Questions for 2026 and Sunrise on Venus. We explore how long-running global trends may be reversing, what that means for U.S. dominance, the future of international and emerging markets, the risks and opportunities created by AI and massive CapEx spending, the dollar's shifting role, and how investors should think about valuation, humility, and navigating a world where the economic “water” is changing. This conversation is packed with global macro insight, long-term investing lessons, and practical frameworks for building more resilient portfolios. Topics Covered:• Why long-term market “water” becomes invisible to investors• Self-reinforcing global cycles and how China's WTO entry reshaped the world• Signs the 25-year U.S. outperformance cycle may be breaking• How tariffs, political shifts, and corporate reforms change the global landscape• Why international and emerging markets may now offer better expected returns• Why U.S. large caps are not the entire story of American exceptionalism• How to think about valuation, margins, and discounted cash flow models across markets• The AI boom, bubbles, capital cycles, and asymmetric outcomes• How AI CapEx constraints influence winners and losers• The shifting role of the U.S. dollar and why market shocks may behave differently• Maslow's hierarchy, needs vs. wants, and the return of state-driven capital investment• Deglobalization, reshoring, and the national-security lens for investing• How to evaluate China and Taiwan inside emerging markets• Why humility is an investor's greatest edgeTimestamps:00:00 Introduction01:02 Why Orbis wrote Six Courageous Questions for 202603:44 The David Foster Wallace “water” analogy and investing06:12 How a 25-year self-reinforcing cycle powered U.S. outperformance10:12 Signs the cycle may be breaking12:00 Corporate reform and opportunity in Asia13:55 Why active share, benchmarking, and incentives distort investor behavior17:31 Decomposing S&P 500 returns: margins, valuations, fundamentals20:20 Expected returns inside and outside the U.S.22:34 Why international stocks offer richer opportunity sets24:25 Currency implications and weakening dollar dynamics26:18 American exceptionalism beyond the top 10 mega caps28:49 Where Orbis is finding value today30:25 Biotech, healthcare, and post-COVID dislocation31:05 How Orbis thinks about valuation in an intangible-heavy world32:09 Is AI a bubble or the beginning of something bigger?34:30 Game theory of AI CapEx and right-tail outcomes36:00 CapEx cycles, history, and who benefits38:00 Indirect AI beneficiaries and the SK Square example40:35 Maslow's hierarchy and the shift from wants to needs42:32 Deglobalization, national security, and domestic reinvestment44:00 Capital returning to home markets and strategic industries46:00 Can anything reverse these structural trends?48:00 Balancing bottom-up investing with macro awareness49:45 The deeper risk in emerging markets: owning vs. avoiding51:00 Valuation still matters for long-term returns52:29 Corporate behavior, dividends, and re-rating cycles53:52 How Orbis views China vs. bottom-up opportunity55:34 Why great investors must be right 90–95% of the time in decision quality58:00 One lesson Graeme would teach the average investor

James Grant, legendary founder of Grant's Interest Rate Observer, joins us for a wide-ranging conversation on cycles, interest rates, inflation, credit, the Federal Reserve, private markets, gold, and the future of investing. Grant brings five decades of historical perspective to today's market extremes, explaining why this era of ultra-low interest rates created distortions that will shape returns for years to come — and where patient investors may ultimately find opportunity.Topics Covered• The historical patterns that define major market cycles• Why interest rate cycles unfold over generations• What the 2021 bond market top tells us about the next decade• How inflation behaves like an underground coal fire• The shift from “capitalism without capital” to the “tangible twenties”• Geopolitical tension, military spending, and inflation risk• The Fed's role in shaping today's market distortions• The long-term consequences of QE and financial repression• Private credit, opaque marks, and the fragility beneath the surface• Rising risks inside life insurance balance sheets• Why credit cycles always go further than anyone expects• The challenge of finding long opportunities in today's market• Why liquidity and patience may be the biggest opportunities• Whether the classic 60/40 portfolio still works• Gold as money and why confidence in paper currencies is eroding• Jim Grant's one lesson for the average investorTimestamps00:00 Cycle extremes and market absurdities01:00 Interest rates over generations07:00 Defining major tops and bottoms12:30 Where we are in the current rate cycle14:00 Inflation, armed conflict, and tangible investment18:00 The “tangible twenties” and data center boom19:00 Coal fire inflation analogy20:00 Fed independence, politics, and monetary power25:00 The long shadow of the 2008 crisis30:00 QE, zero rates, and long-term consequences33:00 Housing affordability and locked-in rates34:00 Risks in private credit and opaque marks36:00 How far the credit cycle has progressed38:00 Japan, value investing, and long cycles43:00 Where opportunities exist today47:00 The future of the 60/40 portfolio49:00 Structural risks from low-rate distortions51:00 Freedom, politics, and economic consequences56:00 Gold as money58:00 What Jim Grant believes most investors disagree with59:30 The one lesson Jim Grant would teach the average investor

In this episode, we're joined again by Jim Paulsen to break down the key themes shaping markets and the economy heading into 2026. Jim explains why policymakers may be fighting the wrong battle, why real sustainable growth has quietly collapsed over the past 20 years, and how shifts in policy, demographics, productivity, inflation, and investor psychology all tie together. We also walk through Jim's latest charts from Paulsen Perspectives and explore what they mean for stocks, sectors, interest rates, the dollar, and leadership in the year ahead.Topics covered in this episode:• The state of inflation and why CPI and PPI may be sending a very different message• The 20-year collapse in real sustainable GDP growth• Why job creation, labor force growth, and productivity have all structurally weakened• The rise in unemployment duration and what it signals about lost “animal spirits”• How demographics, immigration policy, and cultural shifts are shaping growth• Productivity puzzles: innovation vs. distraction in a tech-driven economy• Why the real economic risk may be deflation, not inflation• How monetary policy, the yield curve, the dollar, and fiscal policy have remained contractionary• Tariffs as a hidden tax and their real impact on inflation• How an easing cycle could reshape market leadership in 2026• Jim's Total Policy Stimulus Index and what it reveals about small caps, cyclicals, value, and foreign stocks• The difference between today's tech cycle and the dot-com bubble• What a broadening market might look like if policy finally turns supportive• How international equities could respond to a weaker dollar• Why tech may underperform without collapsing• Jim's expectations for S&P 500 returns in 2026 and the potential for a more balanced leadership environmentTimestamps:00:00 Market setup and inflation overview02:00 Reviewing recent corrections and sector broadening04:00 Bond yields, easing expectations, and fear-based asset leadership06:00 Tech's relative performance beginning to fade07:00 GDP growth collapse over two decades09:00 Structural slowdown in job creation10:30 Labor force growth and aging demographics12:00 The doubling of unemployment duration14:00 Population trends, immigration, and slowing productivity17:00 The rise of de-risking and falling monetary velocity19:00 Trade deficits, globalization, and policy contraction22:00 Why inflation risk may be overstated26:00 CPI/PPI data versus the inflation narrative29:00 Money supply, real rates, and the longest yield curve inversion31:00 The strong dollar as a contractionary force34:00 International stock performance and currency impact35:00 Tax burden relative to slower growth37:00 Tariffs as taxes and their real economic effect39:00 What would it take to restore growth and optimism?42:00 The Total Policy Stimulus Index explained47:00 Policy's impact on equal-weight, small caps, cyclicals, and value52:00 How foreign stocks respond to policy and the dollar54:00 Tech valuations today vs. the dot-com era55:00 Fed response differences between now and 200057:00 Why today's tech cycle is structurally different59:00 What 2026 might look like for the S&P 50001:01:00 Why price targets are inherently unreliable01:01:45 Closing thoughts and sign-off

In this special episode of Excess Returns, we share the most important investing lessons from more than 50 of our top guests. After asking more than 200 investors, strategists, academics, and market thinkers the same closing question about the one lesson they would teach the average investor, we compiled the most powerful, timeless, and repeatable insights into a single episode. This collection highlights common themes around patience, discipline, humility, diversification, risk management, and long-term thinking, while revealing how great investors navigate markets, behavior, and uncertainty.Main topics covered:Why investing is about preserving and growing wealth, not getting richWhy neither get in nor get out is an investing strategyThe role of base rates in decision-makingThe dangers of performance chasingWhy you should look at your portfolio less oftenThe importance of independent thinking and avoiding envyTreating stocks as businesses, not trading sardinesDiversification across assets, strategies, and economic regimesThe behavioral traps that destroy wealthLiquidity, supply and demand, and how markets really functionThe value of patience, long-term thinking, and sticking to your planHow to build a resilient portfolio that survives different market environmentsWhy simplicity often beats complexityThe role of humility, self-awareness, and keeping emotions out of investingTimestamps:00:00 Investing is about preserving and growing wealth00:45 Why neither get in nor get out is a strategy01:16 How we arrived at the one-lesson question02:00 Finding a portfolio you can live with03:00 Avoiding envy and chasing 10-baggers04:00 Why watching markets too closely hurts results05:00 The Matt Levine rule of unbelievable returns06:00 The power of base rates08:00 Look at your portfolio as little as possible10:00 Treat your holdings like real businesses12:00 Be invested early and think independently14:00 Be kind to yourself and keep taking action15:58 Do not chase performance17:00 Treat every position like you put it on today18:31 Your portfolio is secondary to your life19:44 Buy when others are fearful20:00 Be Rip Van Winkle, not Nostradamus22:00 Navigate the noise and avoid the siren song23:38 The value of simplicity and studying history24:59 Patience and tuning out the noise26:00 True diversification and preparing for unknown regimes27:50 Stick to a strategy that fits your personality29:00 Diversify and be humble about what you know30:00 Most results come from the market, not manager skill32:38 Keep investing simple34:00 Focus on what is knowable35:00 Believe in long-term economic and market resilience37:00 Get out of your own way38:22 Build a philosophy you can stick to39:00 Misjudging probabilities and confidence40:46 Book your gains and contain your losses41:00 Diversification is protection against bad luck42:00 Supply, demand, and liquidity always matter45:00 Markets as a political utility46:00 Find something real if you want true alpha47:00 Write down your decisions48:32 Why 100 percent indexing is unrealistic for most50:00 Alpha through portfolio structure, not just stock picking52:00 Dividends and long-run investing53:56 Valuation, time horizons, and patience55:00 Embracing uncertainty and avoiding pigeonholing56:33 Rules-based processes57:35 Buy good businesses, not just cheap ones59:00 Think long term and save early01:01:00 Focus on the basics first01:02:00 Avoid catastrophic losses01:03:22 Evidence-based investing and avoiding resulting01:04:09 Know what you own and keep fees low01:05:00 Simple strategies often work best01:06:00 Compounding and emotional control01:07:00 Treat savings as savings, not lottery tickets01:07:50 Balance enjoying today with protecting tomorrow01:08:00 Stay invested and think long term01:08:41 Be humble, patient, and systematic01:09:00 Do your own work and build conviction

In this episode of Excess Returns, Matt sits down with Ben Hunt to break down his new Epsilon Theory essay, World War AI. They explore how the US government, markets, and Big Tech are rapidly shifting the AI narrative from productivity and progress toward a national security arms race with massive implications for energy, capital, jobs, inflation, and the broader economy. Ben explains why AI buildout is consuming enormous resources, how this echoes World War II scale mobilization, why consumers are already feeling the strain, and what policies could still steer the country toward a healthier economic path.Topics covered:• Why the AI narrative flipped from optimism to national security• How AI CapEx creates shortages of energy, capital, and investment elsewhere• The parallels between AI buildout and World War II economic mobilization• Why the promise of AI-driven productivity and leisure was never realistic• The coming squeeze on consumers through higher prices and reduced availability• Why energy bottlenecks and electricity scarcity may lead to rationing• The risk of stagflation and a shrinking job base as AI replaces human labor• The political paths this could take, from authoritarianism to backlash• Ben's three-policy plan: reshoring, energy expansion, and electricity caps• How investors should think about the boom-bust risk of hyperscale growth• Why awareness and public conversation are essential before the window closesTimestamps:00:00 AI narrative shift and the failure of the carrot01:20 Measuring narratives through Perscient Pro05:30 Why Ben wrote World War AI07:30 The carrot vs. the stick in AI storytelling11:00 Utility bills, consumer squeeze, and rising economic pressures12:30 World War II-level spending and debt dynamics15:30 Crowding out the consumer economy17:00 Interest rates, borrowing, and capital shortages20:00 Energy usage, electricity scarcity, and cost-push inflation24:00 Rationing risk and historical parallels26:00 Jobs, productivity, and AI's impact on labor31:00 The lack of new job creation in an AI-driven economy33:00 Why new-tech job optimism does not apply here38:00 Market skepticism and narrative extremes41:00 Political risk, backlash, and potential future paths42:20 The three policies: reshoring, energy buildout, electricity caps49:30 Investment implications and the boom-bust cycle55:00 How AI growth must be subordinated to broader economic goals57:00 Why connecting consumer pain to AI buildout is essential59:30 Early signs of state-level limits on data centers01:02:00 Where to follow Ben Hunt and the continuing story

In this episode of Excess Returns, we sit down with Louis-Vincent Gave of Gavekal Research for one of the most wide-ranging and eye-opening conversations we have ever hosted. Louis breaks down how China transformed its economy over the last seven years, why Western observers consistently misunderstand the country's growth model, and what this means for global markets, AI competition, supply chains, currencies, energy, demographics, and the next decade of investing. If you want a clearer picture of China, global macro dynamics, and the forces shaping markets today, this is essential viewing.Topics covered in this episode:• Why Western investors misread China's economy• China's response to the US semiconductor embargo• How China redirected all lending toward industry• The scale and speed of China's move up the value chain• China's EV dominance and the BYD vs. Tesla comparison• The new global deflation and reflation forces• Why China now looks like the US did in 2009• Energy, labor, and industrial competitiveness• China's open-source AI approach vs. America's closed systems• “Hunger Games” capitalism and the impact on investors• Where foreign investors consistently get China wrong• The RMB as the most mispriced major asset• How China's demographics shape policy and markets• Why fears of a Taiwan conflict are overblown• How Louis is positioning for China's next bull marketTimestamps:00:00 China's economic shock and the US semiconductor embargo02:00 What the West gets wrong about China04:00 Competition, local governments, and industrial incentives06:10 China's lending shift: real estate to industry08:00 China's rapid climb up the value chain10:00 BYD vs Tesla and China's engineering surge12:30 The global deflationary shock and US–China tensions15:00 From defense to offense: China's policy pivot17:00 China's reflation and emerging market implications18:20 Scarcity of energy, labor, and time21:00 China's cost advantages vs the US24:00 Comparing AI strategies: open vs closed systems28:00 “Hunger Games” capitalism in China31:30 Investing challenges and opportunities in China34:00 China's new high-tech niche champions37:00 Capital-light Chinese AI vs US capital intensity40:30 Rethinking US-China blocs and global alliances44:00 Why Europe will be torn apart by the next phase45:30 Will China outperform the US over the next decade?47:00 The massively undervalued RMB49:00 China's barbell investment setup50:00 China's demographic crisis and policy response53:00 Taiwan risk: myth vs reality58:00 How Louis could be wrong01:00:40 Louis's contrarian investing belief01:02:00 Louis's one lesson for investors

In this episode, we sit down with Sanctuary Wealth Chief Investment Strategist Mary Ann Bartels to break down her new 2026 outlook. We cover her long-term S&P 500 forecast, why she believes we are still early in a secular bull market, how technological innovation is fueling productivity and profitability, the risks she's watching in 2026, and the case for international stocks, gold, and diversification. Mary Ann also explains why skepticism suggests we are not yet in a true bubble, how valuations fit into today's market, and what investors should understand about cycles, inflation, and long-term compounding.Topics Covered• Secular bull markets and why the long-term trend still points higher• Whether today's market is following historic bubble patterns• AI, technology cycles, and the connection between innovation, productivity, and profits• Why skepticism means we are not yet near euphoria• The 2026 “reset” and how the presidential cycle could affect markets• Valuations, earnings trends, and interest-rate dynamics• Market concentration, structural changes, and the role of mega-caps• Growth vs value and why growth leadership may persist• Why international markets may be entering their own secular bull market• Inflation outlook, tariffs, and what the data now suggests• Private credit concerns and overall financial-system stability• Gold's surge, future targets, and its role as portfolio diversification• Portfolio construction, risk, and the importance of compounding for younger investorsTimestamps00:00 Market patterns, bubbles, and early-cycle dynamics01:00 Introduction02:00 Long-term S&P 500 outlook04:00 Historical bubble analogs and market psychology06:00 Skepticism vs optimism09:00 2026 reset and election-year dynamics13:00 Valuations and PE expansion17:00 Long-term valuation trends17:40 Innovation cycles and economic growth20:20 Productivity, AI CapEx, and profitability21:00 Technology adoption across industries22:20 Digitization and long-term tech layers22:30 Market concentration and structural changes25:00 Why corrections are more frequent27:20 Growth vs value31:00 International markets outlook36:00 Correlations, deglobalization, and opportunity38:40 Inflation short-term vs long-term40:30 Private credit and financial stability43:30 Gold outlook and targets45:40 Diversifying concentrated portfolios48:40 Crypto, private markets, and generational shifts49:20 Key risks for 202651:40 What most investors get wrong53:00 The one lesson for the average investor54:40 Closing