Excess Returns

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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