Excess Returns

Excess Returns
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Excess Returns is dedicated to making you a better long-term investor and making complex investing topics understandable. Join Jack Forehand, Justin Carbonneau and Matt Zeigler as they sit down with some of the most interesting names in finance to discuss topics like macroeconomics, value investing, factor investing, and more. Subscribe to learn along with us.

  1. 2D AGO

    The Truth No One Sees | 41 Great Investors Share Their Most Controversial Belief

    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

    1h 3m

  2. 4D AGO

    The Base Case is Wrong | Paul Eitelman on AI, Reacceleration and the Pause No One Sees

    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 alternatives Timestamps 00:00 Introduction and the Great Inflection Point outlook 03:00 Cycle, valuation, and sentiment investing framework 05:50 From economic resilience to potential reacceleration 07:00 AI as a transformational technology and historical parallels 09:20 Measuring returns on AI investment and productivity gains 11:00 The AI J-curve and timing of benefits 13:00 Capital intensity, leverage, and risks for big tech 15:00 Energy demand, labor markets, and AI risks 19:00 How Paul uses AI in his own research workflow 20:30 The case for economic reacceleration into 2026 21:40 Tariffs and their real economic impact 23:20 Immigration and labor supply effects 24:10 Uncertainty, confidence, and business decision-making 26:10 Financial conditions and household wealth 28:00 Fiscal stimulus and the One Big Beautiful Bill Act 29:20 Deregulation as a potential growth tailwind 30:40 Hard data versus soft data in the economy 34:10 Why recession forecasts failed 37:10 Recession risk outlook for 2026 40:30 Inflation dynamics and the Fed’s focus 43:50 Broadening market leadership beyond the Magnificent Seven 46:10 Investor sentiment, panic, and opportunity 49:00 Translating macro views into portfolio strategy 51:30 Real assets, alternatives, and diversification 54:30 Investing lessons, compounding, and staying invested

    57 min

  3. 6D AGO

    Nothing Has a Right to Exist in Your Portfolio | What the Last 15 Years Has Taught Us

    In the latest episode of Click Beta, Matt Zeigler, Dave Nadig and Cameron Dawson take a look back at 2025 and a look forward to 2026. Subscribe to Click Beta via the links below. Follow Click Beta: Spotify ⁠https://open.spotify.com/show/0u1fxie4C4vHXIJPUMhvUs⁠ Apple Podcasts ⁠https://podcasts.apple.com/ky/podcast/click-beta/id1793929457⁠ YouTube: ⁠https://www.youtube.com/excessreturns

    58 min

  4. DEC 21

    The Existential Spending Battle | Adrian Helfert on What You’re Missing in the AI Arms Race

    In this episode of Excess Returns, we sit down with Adrian Helfert of Westwood to discuss how investors should be thinking about portfolio construction in a market shaped by artificial intelligence, high levels of concentration, shifting interest rate dynamics, and evolving economic signals. The conversation covers how AI-driven capital spending is changing return profiles across markets, why traditional investing rules are breaking down, and how investors can balance growth, income, and risk in an uncertain environment. Adrian shares his framework for understanding return drivers, his views on market concentration and valuation, and how to think about diversification, macro risk, and income generation going forward. Main topics covered • How Westwood frames portfolio construction around capital appreciation, income, and event-driven returns • Why AI spending is both a major opportunity and a growing existential risk for large companies • The sustainability of market concentration and what it means for future returns • Whether higher interest rates really hurt growth stocks the way investors expect • How massive data center and AI capital expenditures could translate into productivity gains • The case for market broadening beyond the Magnificent Seven • Why traditional recession indicators have failed in recent cycles • How inflation, labor markets, and Federal Reserve policy interact today • Rethinking the classic 60/40 portfolio and the role of private markets • Using covered calls and active income strategies to manage risk and generate yield Timestamps 00:00 Introduction and near-term opportunities versus long-term risk 02:40 Capital appreciation, income, and event-driven investing framework 06:30 Have markets structurally changed to support higher returns 09:30 Intangible assets, AI, and margin expansion 10:20 The scale of AI and data center capital spending 13:00 Productivity gains and return on investment from AI 16:00 AI as both opportunity and risk for companies 19:30 Market concentration and diversification concerns 23:30 Will market leadership eventually broaden 25:30 Growth stocks, duration, and interest rates 29:30 International diversification and global investing 33:30 Why recession indicators have failed 39:00 Inflation outlook and Federal Reserve policy 46:00 Rethinking the 60/40 portfolio 53:00 Enhanced income strategies and covered calls 59:00 One investing belief most peers disagree with

    1h 1m

  5. DEC 19

    The Precarity Line | Ben Hunt and Adam Butler on the Broken Math of the American Dream

    In this special episode, Adam Butler and Ben Hunt join Matt Zeigler to unpack one of the most charged debates in markets and economics today: whether our official statistics still reflect lived reality. Building on Mike Green’s work and Adam Butler’s essay The Bureau of Missing Children, the conversation moves beyond the technical definition of poverty to a deeper idea of economic precarity, the growing gap between what we measure and what people actually experience. Together, they explore debt, housing, childcare, labor mobility, AI, and the erosion of meaning in economic language, while wrestling with what policy, community, and human-centered solutions might look like in a world that increasingly feels unstable. Main topics covered Why the debate should focus on precarity rather than poverty The disconnect between inflation statistics and lived experience How debt, housing, childcare, and education drive economic insecurity The idea of a participation budget for modern family formation Why labor mobility has broken down since the financial crisis How asset prices and credit intensify risk for households The role of grandparents and off-balance-sheet support in the economy Darwin’s wedge, positional goods, and rising costs of everyday life The impact of AI, technocracy, and anti-human incentives Centralized versus decentralized solutions to today’s economic challenges What it means to carry the fire and preserve human-centered values Timestamps 00:00 Introduction and the emotional roots of the precarity debate 02:00 Poverty versus precarity and what we are really measuring 06:30 Technocrats, narratives, and the limits of economic statistics 09:00 Personal experiences with precarity and debt 15:00 The Bureau of Missing Children and family formation economics 21:00 Modeling household income and participation budgets 25:50 Rising costs of childcare, housing, and everyday life 33:00 Darwin’s wedge and positional competition 36:45 Debt, housing, and labor immobility 40:00 Grandparents, unpaid care, and off-balance-sheet subsidies 46:30 How today differs from 40 or 50 years ago 49:40 Labor mobility as a lost engine of opportunity 55:00 Policy paths, mission-driven economics, and decentralization 01:11:00 Visionary leadership versus bottom-up solutions 01:15:50 Carrying the fire and preserving meaning 01:17:30 Where to follow Adam Butler and Ben Hunt

    1h 19m

  6. DEC 17

    The Alpha No Human Can Find | David Wright on Machine Learning's Hidden Edge

    In this episode of Excess Returns, we sit down with David Wright, Head of Quantitative Investing at Pictet Asset Management, for a deep and practical conversation about how artificial intelligence and machine learning are actually being used in real-world investment strategies. Rather than focusing on hype or black-box promises, David walks through how systematic investors combine human judgment, economic intuition, and machine learning models to forecast stock returns, construct portfolios, and manage risk. The discussion covers what AI can and cannot do in investing today, how machine learning differs from traditional factor models and large language models like ChatGPT, and why interpretability and robustness still matter. This episode is a must-watch for investors interested in quantitative investing, AI-driven ETFs, and the future of systematic portfolio construction. Main topics covered: What artificial intelligence and machine learning really mean in an investing context How machine learning models are trained to forecast relative stock returns The role of features, signals, and decision trees in quantitative investing Key differences between machine learning models and large language models like ChatGPT Why interpretability and stability matter more than hype in AI investing How human judgment and machine learning complement each other in portfolio management Data selection, feature engineering, and the trade-offs between traditional and alternative data Overfitting, data mining concerns, and how professional investors build guardrails Time horizons, rebalancing frequency, and transaction cost considerations How AI-driven strategies are implemented in diversified portfolios and ETFs The future of AI in investing and what it means for investors Timestamps: 00:00 Introduction and overview of AI and machine learning in investing 03:00 Defining artificial intelligence vs machine learning in finance 05:00 How machine learning models are trained using financial data 07:00 Machine learning vs ChatGPT and large language models for stock selection 09:45 Decision trees and how machine learning makes forecasts 12:00 Choosing data inputs: traditional data vs alternative data 14:40 The role of economic intuition and explainability in quant models 18:00 Time horizons and why machine learning works better at shorter horizons 22:00 Can machine learning improve traditional factor investing 24:00 Data mining, overfitting, and model robustness 26:00 What humans do better than AI and where machines excel 30:00 Feature importance, conditioning effects, and model structure 32:00 Model retraining, stability, and long-term persistence 36:00 The future of automation and human oversight in investing 40:00 Why ChatGPT-style models struggle with portfolio construction 45:00 Portfolio construction, diversification, and ETF implementation 51:00 Rebalancing, transaction costs, and practical execution 56:00 Surprising insights from machine learning models 59:00 Closing lessons on investing and avoiding overtrading

    1h 1m

  7. DEC 15

    The 100 Year Thinkers | Chris Mayer and Robert Hagstrom on the Dangers of Abstraction

    In this episode of our new show The 100 Year Thinkers, Robert Hagstrom, Chris Mayer, Bogumil Baranowki and Matt Zeigler explain how investors get trapped by labels, abstractions, and simplistic models, and why breaking free with better mental models, language, and long-term thinking is a real edge in markets. Subscribe on Spotify ⁠⁠https://open.spotify.com/show/5IsVVM27KWP6SUW6KN2ife⁠⁠ Subscribe on Apple Podcasts ⁠⁠https://podcasts.apple.com/us/podcast/the-100-year-thinkers-long-term-compounding-in-a-short-term-world/id1845466003⁠⁠ Subscribe on YouTube ⁠⁠https://youtube.com/@excessreturns⁠

    1h 13m

  8. DEC 13

    Magnet Above. Trap Door Below | Inside the Options Flows Driving Markets with Brent Kochuba

    Brent Kochuba takes a look behind the scenes at the options flows driving the market heading into the December options expiration and the end of 2025. Subscribe on Spotify ⁠https://open.spotify.com/show/4KR2YVJqk2lnVETMKDavJf⁠ Subscribe on Apple Podcasts ⁠https://podcasts.apple.com/us/podcast/the-opex-effect/id1711880009⁠ Subscribe on YouTube ⁠https://www.youtube.com/channel/UCPYvx_y92dvI1PSdiho0ALw

    1h 10m
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Excess Returns is dedicated to making you a better long-term investor and making complex investing topics understandable. Join Jack Forehand, Justin Carbonneau and Matt Zeigler as they sit down with some of the most interesting names in finance to discuss topics like macroeconomics, value investing, factor investing, and more. Subscribe to learn along with us.

Information

  • Creator
    Excess Returns
  • Years Active
    2019 - 2025
  • Episodes
    434
  • Rating
    Clean
  • Copyright
    © 905628
  • Show Website
    Excess Returns

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