Excess 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

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

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

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

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

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

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

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

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

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

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

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

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