Excess Returns

Subscribe to the OPEX Effect on Spotify⁠⁠⁠⁠Subscribe to the OPEX Effect on Apple PodcastsThis episode of The Opex Effect breaks down why markets have remained surprisingly resilient despite geopolitical chaos, an oil shock, and extreme headline risk. Brent Kochuba joins Jack Forehand to analyze what's really driving the market beneath the surface—from options flows and gamma positioning to the collapse in volatility and what it signals for the next move.They explore how the options market is shaping price action in ways most investors miss, why the VIX collapsed despite elevated risk, and what positioning tells us about the path forward as we head into earnings and the next major options expiration.Topics covered:Why markets have stayed near highs despite war, oil spikes, and macro uncertaintyThe “taco trade” and why investors expect bad news to reverse quicklyHow options flows and dealer hedging are influencing stock pricesWhy call options are historically cheap heading into earningsThe mechanics of gamma, delta hedging, and market maker positioningWhy options expiration (OpEx) can act as a turning point for marketsThe divergence between oil prices and equity volatilityWhat the collapse in the VIX reveals about investor positioningThe role of zero-DTE options in reinforcing short-term market rangesKey resistance levels forming from call selling and what they mean for upsideTimestamps:00:00 Why markets aren't reacting to geopolitical chaos04:18 The “taco trade” and shifting market expectations07:30 How options flows influence stock market movements11:10 Why OpEx can drive market turning points13:05 Volatility compression and the gamma-volatility relationship15:30 How large options positioning shapes market behavior18:05 Why positioning has shifted toward calls20:00 Why this OpEx may be less impactful than prior ones22:00 Market positioning into earnings and key drivers ahead24:10 Using gamma maps to identify support and resistance27:00 Revisiting the JP Morgan collar trade and March lows30:00 Correlation spikes and the oil-volatility relationship33:00 Why oil has stopped driving equity volatility34:30 The breakdown between oil and VIX correlation36:00 Why volatility may reprice higher after OpEx37:05 The oil curve and expectations for a short-term shock39:40 One of the largest VIX collapses ever41:00 How options positioning drove the volatility unwind43:00 Why selling volatility has become a dominant strategy45:00 The feedback loop between rising markets and falling volatilityFor more information on SpotGamma and Brent's work:https://spotgamma.comFollow Brent on Twitter:https://twitter.com/spotgamma

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

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

This episode of Excess Returns features Tony Wang of T. Rowe Price discussing how investors can identify “inevitabilities” in technology and position portfolios to benefit from long-term innovation trends. The conversation explores AI, semiconductors, and the evolving investment landscape, while also breaking down Tony's portfolio construction process and how he navigates cycles, valuation, and disruption risk.Tony explains why AI is fundamentally changing the cost of intelligence, how agentic systems could reshape software and labor markets, and why the current AI buildout may differ from past tech cycles. The discussion also dives into where we are in the AI cycle, how to think about the Mag 7, and what investors may be missing across the tech stack.T. Rowe Price Science and Technology Fundhttps://www.troweprice.com/financial-intermediary/us/en/investments/mutual-funds/us-products/science-and-technology-fund.htmlTopics CoveredWhat it means to invest in “inevitabilities” and separating signal from noise in marketsWhy AI and compute demand represent a structural shift similar to past tech wavesThe rise of agentic AI and how it could transform software and productivityWhether AI is underappreciated or already priced into marketsThe “multiple moons” idea and why AI may not be a winner-take-all marketHow AI could reshape the labor market, productivity, and economic growthThe AI CapEx debate and why this cycle may differ from the dot-com buildoutWhere we are in the AI cycle: training vs inferencing and deployment phaseThe impact of AI on software companies and the innovator's dilemmaHow semiconductors, memory, and infrastructure remain key bottlenecksThe changing nature of the Mag 7 and capital intensity in AITony's portfolio construction framework across compounders, emerging tech, and valueHow he generates ideas using S-curve adoption and economic bottlenecksPosition sizing, risk management, and balancing growth with drawdown controlSell discipline: valuation, fundamentals, and market signalsTimestamps00:00 Introduction and Tony Wang overview01:05 Investing in inevitabilities and long-term thinking03:00 Differentiating inevitability from hype and consensus04:45 AI inevitability and the rise of agentic systems07:00 Cost of intelligence and productivity implications08:00 Real-world examples of AI adoption (customer service, agents)09:00 Is AI underappreciated by markets?11:15 AI as a “space race with multiple moons”13:30 AI as the dominant driver of markets today15:00 AI's impact on jobs, productivity, and the economy18:30 Creativity, judgment, and the future of work20:45 Physical AI and robotics opportunity set22:30 AI CapEx debate vs the dot-com era25:30 Semiconductors vs software in the AI stack28:15 AI disruption risk for software companies31:00 Cyclicality in semiconductors and how AI changes it33:30 The evolving role of the Mag 7 in AI36:30 Competition, startups, and AI democratization38:00 Where we are in the AI cycle today40:00 Idea generation and S-curve adoption framework42:30 Case study: memory and AI bottlenecks44:45 Example position: optical networking and infrastructure46:40 Portfolio construction and position sizing49:00 Sell discipline and managing valuation risk

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

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

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

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

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

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

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

Subscribe to the 100 Year Thinkers of Spotify⁠⁠Subscribe to the 100 Year Thinkers of AppleIn this episode of our new show, 100 Year Thinkers, Robert Hagstrom and Chris Mayer explore how investors should think about base rates, extreme outcomes, and the realities of long-term wealth creation in markets. Applying the work of Michael Mauboussin, the conversation challenges conventional ideas like mean reversion and highlights why a small number of companies drive most stock market returns—and what that means for portfolio construction.This episode brings together Robert Hagstrom and Chris Mayer to explore how investors should think about base rates, extreme outcomes, and the realities of long-term wealth creation in markets. The conversation challenges conventional ideas like mean reversion and highlights why a small number of companies drive most stock market returns—and what that means for portfolio construction.Topics covered• Why markets are driven by extreme outcomes and power laws, not averages• The Best & Bessembinder research showing a handful of stocks create most wealth• Base rates vs outliers and when to trust historical probabilities• Why the 100 bagger framework focuses on studying winners, not predicting them• Portfolio construction as a way to capture asymmetric upside• Buffett's approach to consistency, durability, and long-term operating history• Inside view vs outside view and how narratives distort investing decisions• Why AI may be breaking traditional base rate assumptions in software and tech• The limits of mean reversion and why it can lead investors astray• Return on invested capital and how competition erodes excess returns over time• Identifying durable moats and why most advantages eventually get attacked• Winner-take-all dynamics and how they shape long-term investing outcomes• The twin engines of returns: earnings growth and multiple expansion• Return on incremental capital as a key driver of long-term compounding• Intangible assets and why accounting understates true business value• Amazon as a case study in misunderstood profitability and reinvestment• AI CapEx cycle and why current spending may not be sustainable long term• Why great businesses matter more than great management in long-term investingTimestamps00:00 Why extreme outcomes drive stock market returns01:00 Base rates vs studying 100 baggers03:00 Power laws and why markets are a game of outliers05:00 Just 46 companies created half of all market wealth07:00 Buffett on consistency and long-term operating history10:00 How to think about base rates in AI, energy, and macro cycles12:00 Does AI invalidate historical base rates?15:00 Inside view vs outside view in investment decision making19:00 Buffett's “certainty at a discount” framework23:00 How often investors should evaluate businesses vs prices29:00 Mean reversion myths and where it breaks down33:00 Return on invested capital and competitive pressure36:00 Moats, winner-take-all markets, and long-term dominance41:00 Twin engines of compounding: growth plus multiple expansion43:00 Return on incremental capital and forecasting future returns47:00 Intangibles and why accounting distorts real business value50:00 Amazon, CapEx cycles, and hidden profitability53:00 AI infrastructure buildout and the future of returns

Subscribe to the OPEX Effect on Spotify⁠⁠Subscribe to the OPEX Effect on Apple PodcastsThis episode breaks down the growing tension beneath the surface of today's markets, where volatility signals, options positioning, and macro risks like war and inflation are increasingly misaligned. Brent Kochuba and Jack Forehand explain why markets appear calm despite heavy hedging, and what that disconnect could mean for a potential volatility spike and downside move ahead.Brent Kochuba on Twitterhttps://twitter.com/SpotGammaSpotGamma Websitehttps://spotgamma.comTopics covered in this episode• Why volatility looks elevated beneath the surface even as markets remain relatively calm• The growing gap between implied volatility VIX and realized volatility and what it signals• How options expiration OPEX can create turning points in both price and volatility• Why current positioning is unusually put-heavy and what that means for downside risk• The role of market makers and hedging flows in driving market moves• How geopolitical risks like the Iran conflict are changing options behavior and hedging demand• Why correlation is spiking and what it says about investors moving from stock picking to asset allocation• The breakdown of traditional diversification including the 60/40 portfolio• How credit markets and liquidity risks could amplify equity volatility• The impact of zero DTE options and why traders are shifting to longer-duration hedges• The significance of the JP Morgan collar trade and key levels to watch into month-end• Why volatility spikes often follow periods of suppressed market movement• The potential for a sharp upside rally if geopolitical risks suddenly resolve• How options positioning can help both traders and long-term investors with timing decisionsTimestamps00:00 Volatility premium vs low market movement disconnect01:00 Why markets feel calm despite rising risks05:20 Explosion in options volume and impact of Monday Wednesday Friday expirations07:00 How market maker hedging flows drive price movements08:40 Dynamic hedging and why options impact evolves over time09:20 Why OPEX can trigger market turning points10:30 VIX expiration effects and short-term volatility suppression13:00 Negative gamma and how it amplifies market volatility14:10 Why hedging demand remains high despite OPEX clearing16:00 Jump risk scenario and potential VIX spike to 4017:10 Shift from zero DTE trading to longer-term hedging18:00 Put-heavy positioning across equities and indices20:40 Size and significance of the current OPEX event22:20 VIX spike dynamics around expiration23:40 JP Morgan collar trade and key SPX levels25:00 Why OPEX often marks short-term market lows or highs28:30 Review of prior OPEX signals and market setup30:00 Rising correlation and shift to asset allocation mindset32:00 Dispersion breakdown and implications for equities34:00 Software sector volatility and AI disruption narrative36:30 Using options signals for better timing decisions39:00 Correlation spike and risk-off behavior across markets41:30 Why investors are avoiding calls and piling into puts44:30 Cross-asset correlation breakdown and bond hedge failure48:00 Credit market risks and spillover into equities49:00 Extreme VIX vs realized volatility spread50:50 Why realized volatility remains unusually low52:30 Oil, inflation, and macro feedback loops

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

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

Follow Two Quants and a Financial Planner on Spotify⁠⁠Follow Two Quants and a Financial Planner on AppleIn this episode, we break down the most important insights from the week on Excess Returns,, with insights from Vitaliy Katsenelson, Jim Paulsen, and Joseph Shaposhnik. Markets today are being shaped by powerful crosscurrents including AI disruption, defense spending, macro policy shifts, and historically high valuations. In this episode, we highlight the biggest ideas from our conversations and explore what they mean for investors trying to navigate an uncertain world. Topics include the importance of humility in investing, the potential disruption of software by AI, the growing divergence within the economy, and why long-term structural trends like defense spending may create new opportunities.Topics Covered• Why humility may be the most important trait for investors in a rapidly changing world• How uncertainty around AI, geopolitics, and macro policy is widening the range of possible market outcomes• Why some investors are reducing exposure to software businesses amid AI disruption• The importance of management teams that can adapt and evolve in periods of technological change• Jim Paulsen's framework for understanding the “new era” economy versus the rest of the economy• Why a small portion of the economy may now be driving overall GDP growth• The idea that successful investing may be about being “least wrong” rather than perfectly right• How long-term structural trends like defense spending could create a multi-year investment tailwind• Why experienced investors focus on analyzing businesses rather than reacting to headlines• The potential deflationary impact of AI and how lower prices could shift spending across the economy• Why high market valuations may act as a headwind for future returns• The importance of deep research and preparation when unexpected events hit markets• Jim Paulsen's concept of “policy juice” and how fiscal and monetary policy drive bull markets• Whether a new wave of policy support could broaden the current market rally beyond mega-cap techTimestamps00:00 Introduction02:00 Why humility matters more than ever in investing08:50 AI disruption and the future of software businesses18:07 The growing gap between the “new era” economy and the rest of the economy25:00 Surviving first and being the least wrong as an investor31:43 The potential defense spending supercycle37:44 AI's deflationary impact and how innovation reshapes economies44:42 Why valuations act as a long-term headwind for stocks50:56 How investors should respond to geopolitical events56:49 Jim Paulsen on policy juice and the future of the bull market

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

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

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

In this episode of the Jim Paulsen Show, Jim joins Jack Forehand and Justin Carbonneau to break down the macro forces shaping today's markets and economy. Jim explains why the economy may be far weaker than headline GDP numbers suggest, how technology and AI investment are masking weakness in the broader economy, and why leadership in the stock market may be shifting. The conversation also explores the market implications of geopolitical conflict, the relationship between policy and market leadership, and how investors should think about AI's long-term economic impact.Topics covered in this episodeHow geopolitical events like the Iran conflict affect markets, volatility, oil prices, and investor sentimentWhy market reactions to geopolitical shocks often fade once the situation is “vetted” by investorsThe relationship between oil prices, the US dollar, and global financial marketsWhy Paulsen remains constructive on international stocks and emerging markets despite recent volatilityWhy energy and food now represent a much smaller share of consumer spending than in past inflation cyclesThe argument that inflation fears may be overstated given structural disinflationary forces in the economyHow AI and technological innovation can destroy some jobs while simultaneously creating new economic demandWhy technological progress often lowers costs and expands markets rather than simply eliminating workThe concept that the “new economy” driven by technology investment is now large enough to influence overall GDP growthPaulsen's analysis showing that roughly 11 percent of the economy tied to new-era investment is growing rapidly while the remaining 89 percent is barely growingWhy the broader economy may resemble a recession even while headline GDP remains positiveHow the dominance of large technology companies in indexes like the S&P 500 may be masking weakness in the broader marketThe historical “toggle” between technology leadership and broader market leadership in equity marketsWhy policy conditions like the yield curve and monetary easing often drive leadership shifts toward value, small caps, and cyclical stocksWhether the Federal Reserve could begin easing policy without a traditional recessionWhy policy support may eventually broaden the bull market beyond technology stocksTimestamps0:00 Jim Paulsen on geopolitical volatility, oil prices, and market reactions2:50 How investors should think about the Iran conflict and market implications10:50 The relationship between oil prices, the US dollar, and safe-haven flows12:20 Why Paulsen likes international and emerging market stocks14:30 Why higher oil prices may not lead to sustained inflation18:40 AI disruption and the economic debate around jobs and productivity23:00 How innovation historically creates new demand and economic growth29:40 Technology is the tail wagging the economic dog33:30 Why the “new economy” is growing far faster than the rest of the economy37:00 Evidence that most of the economy may already resemble a recession41:00 Profit growth disparity between technology and the rest of the economy45:40 Why the stock market can mask weakness in the broader economy46:30 The historical leadership toggle between tech and the broader market49:00 Valuation differences between technology and other sectors50:30 How policy conditions influence market leadership55:00 Signs that leadership may already be shifting beyond tech57:00 Could the Fed ease without a traditional recession59:00 What a policy shift could mean for the next phase of the bull market

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

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

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

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

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

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

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

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