Excess Returns

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