Excess Returns

This episode explores how massive structural shifts—AI, deglobalization, and the rise of passive investing—are reshaping markets and what that means for investors. Informed Momentum Company CIO Travis Prentice breaks down why 52 week highs don't mean what you think, the extreme dispersion beneath the surface of the market, why traditional definitions of risk may be flawed, and how investors should think about momentum, quality, and diversification in a rapidly changing environment.Papers and Resources Discussed:Risks Hiding in Plain Sighthttps://www.informedmomentum.com/risks-hiding-in-plain-sight-how-the-dominance-of-passive-investing-is-reshaping-market-risk/Is Quality Broken?https://www.informedmomentum.com/is-quality-broken-ai-driven-disruption-is-testing-standard-definitions-of-quality/Buy High, Sell Higherhttps://www.informedmomentum.com/buy-high-sell-higher/Topics Covered:The hidden divergence beneath index performance and why the market isn’t as stable as it looksWhy value and momentum are working together—and what that signals about market broadeningHow AI and deglobalization are driving a major regime shift in marketsWhy momentum investors ignore narratives and focus purely on what’s workingThe structural risks created by the rise of passive investing and index concentrationHow tracking error replaced real risk—and why that may be dangerousWhy quality stocks (especially software) are under pressure in the AI eraThe key insight behind 52-week highs as a powerful momentum signalWhy buying stocks near highs works despite investor intuitionHow momentum strategies adapt to changing leadership and market regimesThe importance of combining factors like value, momentum, and quality for long-term successTimestamps:00:00 Intro and major market shifts01:32 Market divergence beneath the surface03:00 Factor performance and broadening market trends05:13 Why market concentration hurts factor investing06:48 AI and deglobalization as structural drivers08:14 Does this environment change how you invest?11:02 Has the market sped up? Momentum implications14:00 Passive investing and hidden structural risks17:00 Tracking error vs real risk in portfolios19:00 AI as a potential change agent for markets21:09 How passive flows impact factor investing24:00 What defines “quality” in factor investing27:04 Why software and quality are under pressure29:13 AI disruption and changing expectations32:20 How to evaluate factor underperformance34:35 Comparing today’s market to the 1990s37:38 Buy high, sell higher: 52-week highs41:00 52-week highs vs traditional momentum43:20 Combining signals for better outcomes46:00 Why 52-week highs improve downside protection48:17 What momentum is picking up today50:21 Misconceptions about momentum and growth52:12 Timing and implementation of momentum54:18 Momentum reversals and market behavior57:17 Future research and improving momentum signals

This episode features Chris Bloomstran of Semper Augustus discussing market concentration, AI capital spending, Berkshire Hathaway, and the risks facing today’s equity investors. The conversation explores whether we are at a secular valuation plateau, how AI investment may reshape returns, and why passive investors may face more risk than they realize.Semper Augustus Investmentshttps://www.semperaugustus.comTopics covered:Why extreme market concentration in the Mag 7 may create long-term risksThe concept of a “secular plateau” vs a market peakHow AI capex could become a classic capital cycle with poor returnsWhy hyperscaler spending may not translate into shareholder profitsThe hidden risks of leverage both on and off balance sheetsWhy buy-and-hold investing is harder than it seems in practiceHow valuation discipline drives long-term investment outcomesBerkshire Hathaway’s cash position and what it signals about opportunityWhy capital allocation matters more than growth narrativesLessons from past bubbles including railroads, fiber, and the Nifty FiftyThe fragility of life and how it shapes investing prioritiesThe importance of independent thinking in the age of AITimestamps:00:00 Intro05:12 The “Both Sides Now” framework and AI theme09:03 Secular peak vs secular plateau in markets13:08 Leverage risks and balance sheet quality17:42 Why passive investors are more concentrated than they think21:12 The limits of long-term compounding and disruption risk25:06 Why valuation matters more than “forever stocks”29:10 Portfolio construction and return on capital differences33:18 AI capex boom and capital cycle parallels37:05 Why hyperscaler spending may not generate adequate returns41:12 The math problem behind AI investment returns45:10 Competition, redundancy, and pricing pressure in AI49:02 Is AI an existential risk for big tech?52:06 Berkshire Hathaway’s cash and Apple sales56:08 Capital allocation lessons from Coca-Cola vs Apple59:20 What Berkshire’s cash signals about future opportunities01:02:10 The fragility of life and investing priorities01:05:28 Final lessons for investors: reading, skepticism, and independent thinking

This episode features David Rosenberg, founder of Rosenberg Research, breaking down why today’s market may be driven more by valuation excess and investor behavior than fundamentals. He explains why the biggest risks right now are not obvious in headline data, and why the probability distribution for markets may be far more fragile than investors assume.Rosenberg walks through his framework for thinking in probabilities, how AI-driven productivity is distorting economic signals, why the equity market is now driving the economy, and what a “silent contraction” beneath the surface could mean for growth, inflation, and returns. He also outlines how he is positioning portfolios in response to these risks.Rosenberg Researchhttps://www.rosenbergresearch.comTopics CoveredWhy markets may be a “bubble in behavior,” not technologyThe equity risk premium at zero and what that implies for future returnsCAPE valuations and why long-term returns could be flat to negativeThe shift from economy driving markets to markets driving the economyThe “silent contraction” beneath strong GDP headlinesAI-driven productivity vs weakening labor marketsThe K-shaped economy across consumers, jobs, and capital spendingWhy the savings rate is the most important overlooked economic variableInflation outlook: why this shock may be disinflationary, not persistentPortfolio construction in a low-return, high-uncertainty environmentTimestamps00:00 Intro04:42 Cycle thinking vs “perma bear” label09:58 Learning probabilistic thinking and Plan B15:52 The “sixth mega bubble” and investor behavior20:36 Why valuations imply poor forward returns25:08 The “silent contraction” beneath headline data29:14 The savings rate and equity wealth effect33:12 Fiscal deficits and artificial economic support38:28 2027 outlook and shifting probabilities43:02 Why expectations matter more than recession calls45:40 Inflation shock vs wage-driven inflation49:22 Productivity boom and disinflation forces53:10 Why inflation may fall faster than expected55:04 Portfolio positioning and diversification strategy01:00:12 Tactical vs thematic investing framework01:03:10 Final thoughts on risk, probabilities, and markets

Brent Donnelly returns to Excess Returns to break down one of the most confusing market environments in years, where policy shocks, volatility, and positioning matter more than traditional fundamentals. He explains why markets can keep rising despite constant bad news, how traders should think about regime shifts, and what actually drives moves across equities, bonds, FX, and gold today.Brent also shares practical insights from his trading process, including risk management, journaling, and how to think about positioning and asymmetric opportunities. The conversation spans macro frameworks, behavioral pitfalls, and the evolving nature of market edges, offering a detailed look at how a professional trader navigates uncertainty.Spectra Marketshttps://www.spectramarkets.comTopics covered:Why stocks need a steady stream of bad news to go down and what drives ralliesThe impact of constant policy shocks on volatility, positioning, and mean reversionHow to distinguish structural trends from short-term trading opportunitiesThe “wall of worry” and why markets can ignore negative headlinesThe importance of Mag 7 earnings and concentration in today’s marketHow traders use reassessment triggers like the 200-day moving averageThe complexity of central bank reactions to oil shocks and inflationWhy bonds still matter as a recession hedge despite recent correlation breakdownsHow positioning—not fundamentals—drives moves in the U.S. dollarGold, silver, and Bitcoin through the lens of flows, retail behavior, and debasementThe role of overconfidence and risk management in trading successBrent’s journaling process and how writing clarifies thinkingHow to identify asymmetric trades using potential headline scenariosWhy edges in markets are temporary and require constant adaptationTimestamps:00:00 Intro02:05 Government policy shocks and market impact05:10 Volatility, shocks, and trading frameworks09:05 Why the economy remains resilient despite rate hikes13:05 Market concentration and the importance of big tech earnings16:05 The “steady stream of bad news” framework for stocks18:30 Using the 200-day moving average and pattern recognition22:10 Central banks, oil shocks, and inflation dynamics24:35 Stocks vs bonds and the 60/40 portfolio outlook26:05 Why dollar moves depend on positioning, not narratives30:55 Gold, silver, and the retail-driven momentum cycle34:05 The debasement trade and long-term gold thesis38:10 Rationality vs overconfidence in trading41:05 Risk management, journaling, and avoiding blowups46:00 Thinking in probabilities, positioning, and market expectations50:55 Journaling as a tool for clarity and discipline55:00 Why traders lose discipline when over-earning59:10 Brent’s new book and evolving trading frameworks01:03:30 Where to find Brent and closing thoughts

Liz Ann Sonders of Schwab joins Excess Returns to break down how war, an oil shock, and shifting market dynamics are reshaping the investing landscape. She explains why the surface-level strength in markets is misleading, what’s really happening beneath the index, and how investors should think about inflation, the Fed, AI, and the evolving role of retail traders.Follow Liz Ann on Twitterhttps://twitter.com/LizAnnSondersLiz Ann's Research and Commentaryhttps://www.schwab.com/learn/author/liz-ann-sondersTopics CoveredHow war and oil shocks are impacting markets, inflation, and Fed policyWhy the US being a “net energy exporter” doesn’t protect investorsThe hidden bear market beneath index-level resilienceRotation vs. correction and what it means for portfoliosThe rise of retail traders and the shift away from “dumb money”Why better or worse data matters more than good or bad dataThe K-shaped economy and its impact on consumption and marketsAI’s three phases and its real impact on jobs and productivityWhy this earnings season may be more important than usualThe shifting role of the Mag 7 and broader market participationWhy the bond market may be the true driver of equitiesRisks in credit markets and what investors should watchLabor market dynamics and challenges for younger workersHow investors and young professionals should think about AITimestamps00:00 Intro and current market environment04:05 Why the US isn’t immune to oil price shocks05:35 Lessons from past oil shocks and inflation07:22 Why markets seem resilient despite macro risks08:00 The hidden drawdowns beneath the index surface10:13 Rolling recessions and sector-level weakness10:37 Are investors conditioned to buy every dip12:58 What happens when the dip doesn’t get bought14:36 Valuations, corrections, and market structure15:12 Sentiment analysis in a new market regime18:50 Retail investors outperforming institutions20:08 Better or worse vs good or bad economic data23:00 How markets anticipate economic turning points25:22 Understanding the K-shaped economy28:00 Wealth effects and risks from equity declines29:09 AI as a transformative force vs macro risks30:00 The three phases of AI development33:04 Why this earnings season matters more34:00 Earnings revisions and sector concentration36:00 The future of Mag 7 leadership vs the rest of the market38:00 Contribution vs performance in index returns40:00 Sector sensitivity to inflation and supply chains42:00 Fundamentals vs speculation in small caps44:21 The Fed’s dilemma in an oil shock environment48:00 Why the bond market is driving equities50:05 Credit markets and systemic risk signals53:26 Lessons from past bond market dislocations54:19 Labor market challenges and younger workers57:00 Career advice in the age of AI59:26 How Liz Ann uses AI in her research process01:01:00 Closing thoughts and where to follow Liz Ann

This episode features Jim Grant of Grant’s Interest Rate Observer on inflation, war, monetary policy, and the long arc of credit cycles. Grant explains why inflation is ultimately driven by monetary debasement and why war, fiscal policy, and central bank actions may be setting the stage for a more persistent inflationary regime than markets expect.We explore how today’s environment compares to past inflationary periods, the hidden risks in credit markets and public debt, and what history teaches us about AI investment booms, oil shocks, and monetary disruption. Grant also discusses trust in financial systems, the role of gold, and why markets are always harder in real time than they appear in hindsight.Grant’s Interest Rate Observerhttps://www.grantspub.com/Topics Covered:Why war is inherently inflationary and how it strains the productive economyThe difference between measured economic stability and underlying systemic risksHow inflation shifted from a wartime phenomenon to a permanent feature of modern monetary policyThe Fed’s 2% inflation target as a structural form of currency debasementLessons from the 1970s inflation and oil shocks vs. today’s environmentWhy inflation is a ratchet that erodes purchasing power over timeThe importance of trust in credit markets and growing risks in private credit structuresPublic debt, Treasury market dynamics, and early signs of strain in government financingHistorical parallels between AI investment and past technological booms like the internetThe role of gold as a hedge against (and investment in) monetary instabilityThe durability of the US dollar despite long-term structural concernsWhy investing is always difficult in the present—even when it looks obvious in hindsightTimestamps:00:00 Intro and Jim Grant on the true causes of inflation04:04 Why war drives sustained inflation and current geopolitical risks08:00 Historical perspective on inflation before the 1970s12:00 Oil shocks, Volcker, and lessons from past inflation cycles16:00 Why inflation never reverses and purchasing power declines20:00 Trust in markets and the foundation of credit systems24:00 Private credit risks and the modern credit cycle28:00 Public debt, Treasury markets, and fiscal sustainability concerns32:00 Treasury auctions, yields, and early warning signs in bonds35:25 AI capex boom and lessons from past technological bubbles38:17 Air conditioning, internet bubbles, and delayed economic payoffs40:00 The Fed, Treasury, and hidden financial interdependence44:14 Asset allocation, gold, and monetary disruption48:44 The dollar’s strength and global dominance53:41 Why investing is always difficult in real time59:00 Advice on markets, newsletters, and enduring uncertainty

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

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

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

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