Everyone Feared Recession. His Data Said Otherwise | US Bank CIO Eric Freedman on What It Says Now

Kai Wu of Sparkline Capital joins Excess Returns to discuss his paper Surviving the AI CapEx Boom. In this episode, Kai breaks down the unprecedented level of investment in AI infrastructure, why today’s AI buildout mirrors past technology booms, and what it all means for investors. He explores the parallels between AI and historic bubbles, the implications of massive corporate CapEx spending, and where value might ultimately be captured as the cycle plays out.Topics covered:Why big tech’s CapEx spending has exploded and how much they’re investingThe trillions in revenue needed to justify AI infrastructure spendingHistorical parallels with the railroad and dot-com buildoutsWhy companies that invest heavily often underperformHow the Mag 7 are shifting from asset-light to asset-heavy businessesThe risks of “circular deals” and financial entanglement in AIWhy the AI race resembles a prisoner’s dilemmaWhich layers of the AI stack may capture long-term valueHow early adopters and infrastructure players differ in capital intensity and returnsWhere investors might find opportunity beyond the obvious AI namesTimestamps:00:00 Introduction and overview of AI CapEx boom03:00 Why Kai researched AI investment cycles05:00 Scale of big tech’s CapEx spending07:00 Revenue needed to justify AI infrastructure08:30 Market concentration and valuation risks11:30 Historical parallels: railroads, internet, and AI14:30 The capital cycle and overinvestment dynamics17:30 “This time is different?” and lessons from bubbles18:00 Factor investing and high-asset-growth underperformance21:00 Sector and firm-level CapEx trends22:30 Winner-take-all dynamics and competitive pressure26:00 How the Mag 7’s business model is changing30:00 Comparing tech CapEx to utilities34:00 The circular deal problem and financial risk37:30 The AI arms race as a prisoner’s dilemma40:30 Will AI be winner-take-all?43:30 Lessons from the railroad and dot-com eras47:00 Where the value is captured in infrastructure vs adoption48:00 Identifying early AI adopters and hidden beneficiaries50:30 Sector and geographic AI exposure54:00 Capital intensity and valuation differences between infrastructure and adopters

In this episode of Excess Returns, we speak with Nancy Davis, founder and CIO of Quadratic Capital Management and the mind behind the innovative fixed income ETFs IVOL and BNDD. Nancy shares her insights on how investors are unknowingly short volatility in their portfolios, the role of options and convexity in fixed income, and how her ETFs seek to hedge against inflation, interest rate shifts, and volatility in a unique way. We also discuss the bond market, inflation dynamics, and how investors can better understand and manage risks that are often hidden inside traditional portfolios.Main topics covered• How Nancy’s experience trading volatility at Goldman Sachs shaped her investment philosophy• Why most investors are short volatility without realizing it• Understanding convexity and prepayment risk in bond portfolios• The rise of passive investing and its impact on interest rate volatility• How IVOL provides exposure to interest rate volatility and inflation protection• The problem with relying on CPI as a measure of inflation• Why gold is an inconsistent inflation hedge• The yield curve as an alternative indicator of inflation expectations• Why interest rate volatility is historically cheap today• The relationship between bond volatility and stock volatility• How to think about IVOL and BNDD in a diversified portfolio• The long-term risks of shorting volatility and selling options for “income”Timestamps00:00 Introduction and overview of option selling in markets02:15 Nancy’s background at Goldman Sachs and lessons on volatility05:00 Understanding convexity and its importance in fixed income06:30 Why investors are short interest rate volatility without knowing it10:25 The hidden risks inside the bond market and the role of mortgages11:00 Why most investors are short inflation in real life13:00 Conventional vs. alternative inflation hedges17:00 Why CPI is an imperfect inflation measure18:00 How the yield curve reflects inflation expectations21:00 Historical yield curve data and current inversion25:00 Interest rate volatility after Silicon Valley Bank26:30 Relationship between bond and stock volatility28:00 Using IVOL in a portfolio31:00 Discussion on the national debt and interest rate risk32:00 BNDD ETF and how it complements IVOL33:30 Why inflation-protected bonds are underused in the US36:00 Closing questions – what Nancy believes most peers disagree with37:00 Why selling options is not income and the risks investors overlook

In this episode of Excess Returns, Meb Faber joins the show to discuss valuations, diversification, trend following, value investing, and the evolution of markets and investor behavior over the past two decades. Meb shares insights from his upcoming book, lessons from 400 years of market history, and how investors can position themselves for the next decade. The conversation covers everything from international investing and concentration risk to ETFs, managed futures, AI, and long-term discipline.Topics covered:The four historical periods of 15%+ annualized stock market returns and what followedWhy current U.S. valuations don’t necessarily mean an immediate crashHow global value stocks are now outperforming the S&P 500The role of international diversification and real assets in portfoliosTrend following and managed futures as the “premier diversifiers”The benefits of blending trend and valuation-based strategiesThe permanent portfolio and how managed futures enhance itConcentration risk in U.S. equities and what history teaches about market leadershipThe parallels (and limits) between today’s market and the dot-com bubbleAI’s potential role in investing and portfolio managementThe behavioral traps around performance chasing and when to sellLessons from launching and running ETFs and the 351 exchange structure for tax efficiencyThe future of markets, retail investors, and Meb’s upcoming book “Time Billionaires”Timestamps:00:00 Intro and market performance context04:00 Are U.S. valuations permanently higher?09:00 The spectrum of future returns and investor playbook12:00 International and value investing opportunities15:00 Trend following and managed futures19:00 The permanent portfolio and diversification25:00 Concentration risk and market structure28:00 AI’s impact on investing32:00 Comparing today’s market to the dot-com bubble37:00 The long-term case for value investing41:00 When to sell and investor behavior45:00 Lessons from running ETFs and industry evolution51:00 Understanding 351 exchanges and tax-efficient investing57:00 What’s changed most for investors over 20 years59:00 Meb’s new book “Time Billionaires” and closing thoughts

Eric Freedman, Chief Investment Officer at US Bank Wealth, joins Excess Returns to discuss markets, the economy and his investment process. Freedman shares his “control the controllables” investment framework, why he’s maintained a glass-half-full view on the U.S. economy, and how data—not emotion—drives portfolio decisions. The conversation covers macro trends, inflation, the Fed, AI, valuation, and how to stay disciplined as an investor.Topics covered:Data-driven investing and the “control the controllables” frameworkWhy the U.S. consumer remains resilientInflation outlook and how sticky prices impact portfoliosThe Fed’s next moves and what investors should watchGlobal diversification and the case for international stocksHow to think about inflation protection and real assetsThe diffusion of AI and separating winners from pretendersMarket concentration, valuations, and managing riskLife lessons from a CIO: discipline, process, and informed decision-makingTimestamps:00:00 Introduction03:00 Controlling the controllables06:00 Why Eric remains optimistic on the economy10:00 How portfolio decisions flow through US Bank15:00 Data-driven insights vs. gut feel18:00 Consumer strength and scorecard22:40 Inflation outlook and Fed challenges30:00 Bond market risk and the “Brazilian steakhouse” analogy34:00 Global competition and diversification38:00 Inflation protection and real assets41:30 The reality of AI and productivity47:00 Market concentration and the Mag 752:00 Valuations and long-term returns55:45 Lessons for investors

In this episode of Excess Returns, we welcome back Rick Ferri, founder of Ferri Investment Solutions and host of the Bogleheads on Investing podcast. Rick shares timeless insights on the evolution of an investor’s education, the pitfalls of complexity, and how to build portfolios that are simple, low-cost, and behaviorally sustainable. The discussion covers how investors can think about macro forecasts, indexing, factors, international diversification, and the right withdrawal rates in retirement.Topics covered:Why macro forecasting rarely works as a long-term investment strategyThe four stages of the index investor’s education: darkness, enlightenment, complexity, and simplicityHow financial advisors and Wall Street profit from unnecessary complexityThe case for international diversification and how to size it correctlyThe pros and cons of factor investing and why behavioral discipline matters more than factors themselvesWhy passive investing isn’t “too big” and why indexing works over timeHow to think about valuations and investor psychologyTips, gold, and how to think about inflation protectionRethinking the 4% withdrawal rule and why goals for heirs matter more than formulasThe one piece of advice Rick would give to young investors todayTimestamps:00:00 Introduction and the four stages of an index investor03:00 Why macro forecasting fails as an investment tool07:00 The evolution from complexity to simplicity13:00 Complexity as job security for advisors18:00 Should investors own international stocks?23:00 The behavioral challenge of factor investing32:00 Is passive investing too big?34:00 What to do (and not do) with market valuations37:00 Managing investor behavior through small adjustments39:00 Inflation, TIPS, and the role of gold46:00 Why indexing works and what makes it unbeatable49:00 The 4% rule and smarter withdrawal strategies57:00 Advice for young investors and what Rick wants his legacy to be

In this episode of Excess Returns, Matt Zeigler talks with macro strategist and author Remi Tetot, known as “The Mad King.” They explore how liquidity, policy, and narratives have reshaped markets over the last decade, why fundamentals have lost their grip, and how investors can adapt to a fractured global cycle. The conversation spans macro themes like fiscal dominance, housing, crypto, and AI — and ends with a deeper reflection on human capital, autonomy, and the behavioral side of markets.Topics covered:How liquidity replaced fundamentals as the market’s main driverWhy investors must adapt to desynchronized global cyclesThe impact of debt, fiscal dominance, and government policy on marketsHousing as the next driver of the business cycleHow AI, robotics, and quantum computing are shaping the next growth waveThe maturation of crypto and what comes after the “altcoin season”Why narratives now drive price and how to read them effectivelyThe risks and opportunities in trading liquidity and fiscal policyThe cognitive and behavioral shifts driving modern investingProtecting human capital in the age of AI and automationTimestamps:00:00 Liquidity and the end of fundamentals06:17 Three continents, three policies, one fractured world12:20 Housing as the next driver of the cycle16:39 Crypto’s evolution and fiscal dominance23:26 Portfolio positioning in a policy-driven market29:44 AI, human capital, and the risk to autonomy36:00 How narratives shape markets and investment themes52:00 Building a macro narrative and market framework58:00 Lessons for investors and closing thoughts

In this episode of Excess Returns, Larry Swedroe returns to discuss the biggest risks and opportunities facing investors today. From tariffs and immigration to AI and private credit, Larry shares evidence-based insights on how to think about markets without relying on forecasts. He explains why diversification is essential, how investors can “sin a little” with duration and valuation, and why only 4% of stocks drive the equity risk premium. The conversation blends timeless investing wisdom with today’s most important macro themes.Main topics covered:Why forecasts don’t work and what investors should do insteadThe real economic risks of tariffs and immigration restrictionsHow AI may (or may not) impact productivity and market winnersHow to build anti-fragile portfolios around macro risksWhen and how to “sin a little” on bond duration and valuationLessons from past tech booms and investor overconfidenceThe 4% of stocks that drive all long-term equity returnsThe risks of concentration in the S&P 500Hidden costs of passive investing and large index fundsWhen index and factor funds get too big to trade efficientlyValue investing, interest rates, and inflation relationshipsThe evidence on simple value strategies like Piotroski and Magic FormulaHow to think about growth exposure using quality and low volatilityThe opportunities and dangers of private credit and interval fundsWhy illiquidity premiums exist and how to capture them prudentlyBehavioral discipline, diversification, and long-term compounding lessonsTimestamps:00:00 Forecasting failures and market humility03:30 Why Larry doesn’t make macro predictions07:00 The real impact of tariffs and immigration on inflation and growth11:00 AI, productivity, and the question of who the real winners will be14:40 How to manage duration risk and “sin a little”18:00 Investor overconfidence and lessons from past tech booms21:00 Why only 4% of stocks explain all equity returns24:00 Market concentration and S&P 500 risk28:30 Why diversification still matters30:00 The hidden trading costs of index and factor funds38:00 How big fund size changes execution and exposure41:00 Is passive investing too big?42:30 Value vs growth and interest rate relationships45:00 Evidence on simple value strategies and Buffett’s alpha51:00 Factor diversification and one-over-N strategy54:00 Private credit: opportunity and risks58:00 Illiquidity premiums and fund structure concerns01:00:00 Behavioral discipline, patience, and staying diversified

Adam Parker, founder and CEO of Trivariate and Trivector Research, joins Excess Returns to discuss how fundamental, quantitative, and macro perspectives intersect to shape markets today. Parker shares his long-term bullish case for U.S. equities, why traditional valuation signals no longer work, the biggest risks he sees for investors, and how AI, inflation, and market structure are reshaping opportunities and risks in real time.Main topics covered:Why combining fundamental, quantitative, and macro analysis gives a clearer view of marketsThe case for the S&P 500 reaching 10,000 by 2030Structural reasons why market multiples may stay higher for longerThe key bear cases: hyperscaler CapEx risk, fiscal deficits, and AI-driven unemploymentComparing today’s market to the dot-com eraWhy traditional recession indicators have failedHow COVID changed the economic cycle and business synchronizationInflation, tariffs, and what the Fed is really watchingWhy valuation is a broken signal for stock pickingThe quant factors that matter most todayETF factor exposures and hidden risksHow to think about the 60/40 portfolio, diversification, and private marketsWhy U.S. innovation and margins make it the dominant equity marketKey lessons and philosophies for long-term investorsTimestamps:00:00 What really drives equity investing03:00 Adam Parker’s background and multi-lens approach05:00 Why he’s long-term bullish and sees S&P 10,00008:00 Structural margin expansion and AI productivity09:00 The three major bear cases14:00 How today compares to the 1990s tech bubble18:00 Why the economy has stayed resilient20:00 COVID’s impact on business cycles23:00 Market structure, inventory, and margins24:00 Inflation, tariffs, and Fed outlook29:00 Deficits and why timing macro risks is hard32:00 Large vs small cap dynamics37:00 Why valuation doesn’t work41:00 Key quant factors to watch43:00 ETF grading and hidden exposures46:00 The 60/40 portfolio and asset allocation51:00 U.S. vs Europe and innovation advantage55:00 Lessons for investors and closing thoughts

Ben Hunt returns to Excess Returns to break down the hidden risks building inside private credit and the parallels between today’s “alternative asset managers” and the shadow banking system that triggered the 2008 financial crisis. Using the Godfather’s Tessio as a metaphor for betrayal and broken trust, Ben explains how opacity, leverage, and narrative collapse can turn small defaults into systemic crises. He and Matt Zeigler explore what’s really happening beneath the surface of private markets, how common knowledge shifts shape investor behavior, and how Perscient Pro’s “storyboards” and “semantic signatures” help track the narratives driving markets in real time.Main topics coveredWhy Ben believes we’re at a “trust-breaking” moment similar to 2007The Godfather analogy and what frauds reveal about human behaviorHow private credit has evolved into today’s “shadow banking” systemFlow machines, hidden leverage, and why opacity is intentionalThe dangers of informational asymmetry between investors and lendersHow broken trust creates chain reactions in financial systemsThe link between narrative collapse and liquidity crisesCommon knowledge, crowd reactions, and market psychologyDoom loops between Wall Street and the real economyHow Perscient Pro tracks financial narratives using semantic signaturesWhy gold’s current rally is about safety, not debasementWhat investors should monitor next in credit, housing, and macro narrativesTimestamps0:00 Hidden leverage and the trust problem1:04 Introduction to Ben Hunt and Epsilon Theory2:12 The Tessio analogy – betrayal and the structure of fraud6:10 How private credit became today’s shadow banking system10:55 Flow machines and why opacity is intentional14:48 Trust breaks and the “funding stops first” dynamic18:35 The Biden “common knowledge” moment explained21:00 What happens when narratives collapse24:26 Apollo, asymmetric information, and shorting First Brands28:00 Hidden leverage and the domino effects of default33:40 The “doom loop” between Wall Street and the real economy39:10 Why Silicon Valley Bank was different44:18 What a “run on Wall Street” could look like48:00 Perscient Pro and tracking financial storyboards53:32 Semantic signatures and narrative detection57:10 Housing, inflation, and gold storyboards1:00:48 Where to follow Ben Hunt and learn more about Perscient Pro

In this episode of Excess Returns, Gene Munster and Doug Clinton of Deepwater Asset Management join Justin and Jack to explore the technological, economic, and investing implications of AI. They discuss why they believe we’re still in the early stages of a multi-year bull market driven by AI, how the technology is reshaping jobs and productivity, and what it means for investors. The conversation also covers how companies like Nvidia, Apple, Tesla, and Meta fit into this AI cycle, the energy demands of AI, and the future of AI-driven investing through Intelligent Alpha and its GPT ETF.Topics covered:• Why Gene and Doug believe AI represents a once-in-a-generation wealth creation opportunity• How AI may impact corporate profitability and hiring trends• The political and social dynamics slowing AI adoption• Doug’s “detective, people-pleaser, and tastemaker” framework for future human jobs• How Intelligent Alpha uses large language models to manage portfolios• The advantages of AI-driven investment models over humans• Economic and market implications of an AI productivity boom• The hardware-data-application structure of technological cycles• The role of energy, especially nuclear and solar, in supporting AI growth• The competitive race among model providers like OpenAI, Google, and Meta• Apple’s long-term AI positioning and potential comeback• Tesla’s valuation, autonomy vision, and the future of robotics• The inevitability and function of bubbles in breakthrough technologies• The rise of private markets and retail investor access to innovation• Future frontiers in quantum computing and biotechnologyTimestamps:00:00 Introduction and Deepwater’s AI thesis03:00 Why AI marks a multi-year bull market opportunity08:00 Political reality and limits of AI deployment11:00 The future of human work: detectives, people-pleasers, tastemakers16:00 Inside Intelligent Alpha and the GPT ETF19:00 Why AI can outperform human managers25:00 How AI affects productivity, margins, and employment26:00 Hardware, data, and application cycle in AI28:00 The energy constraint: nuclear, gas, and solar29:30 The model race: OpenAI, Google, Meta34:00 Apple’s role and long-term AI potential39:30 Tesla, autonomy, and long-term disruption44:00 Are bubbles necessary for technological revolutions?49:00 Private vs. public investing in innovation51:00 Beyond AI: quantum computing and life extension technologies54:45 Closing thoughts