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. לפני 5 שע׳

    He Quantified 200 Years of Disruption | Kai Wu on Separating Software Survivors from Value Traps

    Kai Wu of Sparkline Capital joins Excess Returns to break down his latest research on AI disruption, software stocks, value traps, and intangible moats. We discuss why software valuations have collapsed, why traditional value investing can fail during technological disruption, and how investors can separate potential AI winners from companies whose business models may be permanently impaired. AI Disruption: Moats and Value Traps https://www.sparklinecapital.com/post/ai-disruption Kai Wu on X https://x.com/ckaiwu Sparkline Capital https://www.sparklinecapital.com/ Topics Covered: Why software stocks are trading at a historically unusual discount to the market How AI disruption can create both real opportunities and dangerous value traps Why Blockbuster, Borders, RadioShack and newspapers offer lessons for today’s software selloff How patent data and natural language processing can measure technological disruption Why disruption has helped explain the poor performance of traditional value investing Why value investing may still work in sectors insulated from technological change How intangible assets like brand, human capital, intellectual property and network effects can protect companies Why Walmart and The New York Times survived disruption while other incumbents did not How David Teece’s complementary assets framework applies to AI, software and moats Why AI adoption and intangible value together may help identify software survivors Why high dispersion in disruption-scare stocks creates a potential opportunity for stock pickers Timestamps: 00:00 Software stocks now trade at a historic discount 04:26 What makes a cheap stock a value trap 08:25 Measuring disruption using patents, filings and natural language processing 13:23 Is AI the biggest disruptive wave in history? 14:55 Why disruption keeps stacking on retailers 17:10 How technological change disrupted traditional value investing 21:20 Why value investors need to know when not to apply old metrics 25:06 Why more of the market is exposed to innovation than ever before 27:07 What Walmart and The New York Times teach about surviving disruption 32:40 The four intangible moats that can protect companies 35:02 Why intangible value works better in disrupted industries 38:50 Apple, Amazon, Macy’s and the difference between disruptors and value traps 42:58 Applying intangible value to beaten-down software stocks 47:05 Why AI adoption alone is not enough 48:23 How AI could improve margins for surviving software companies 50:09 Which industries are adopting AI fastest 52:14 The software sweet spot: AI adoption plus intangible moats 53:53 Why disruption-scare stocks have extreme return dispersion 57:40 What happens when intangible value is applied to high-disruption stocks 01:01:42 Why “code is not the moat” for many software companies

    שעה אחת ו-4 דקות

  2. לפני 3 ימים

    The Three Cracks in the AI Trade | Ben Hunt, Brent Kochuba and Aahan Menon on What Could Derail the Market's Biggest Bet

    In this episode of Last Call, we break down one of the most confusing market backdrops in years: AI-driven earnings optimism, rising oil and inflation risk, stretched options positioning, and the market impact of a potential SpaceX IPO. Jack Forehand and Matt Zeigler are joined by Aahan Menon, Ben Hunt, and Brent Kochuba to examine what macro data, political narratives, options flows, and index mechanics are saying about where markets could go next. Follow Last Call on Spotify⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠Follow Last Call on Apple Podcasts⁠ Topics Covered: Why markets are looking through war, oil shocks and valuation concerns How earnings estimates are driving sector performance in the AI trade Aahan Menon on growth, inflation, oil prices and macro regime signals Why demand destruction from higher energy prices can take longer than investors expect What a rising growth and rising inflation regime can mean for stocks, commodities and bonds Ben Hunt on World War AI and the collision between AI market optimism and political backlash Why opposition to AI data centers could become a major market and election issue Brent Kochuba on call buying, implied volatility and signs of options market froth Why CORE 1M and skew signals may be warning of a downside spasm How the SpaceX IPO could affect index flows, active managers and mega-cap stocks Timestamps:00:00 Intro: AI, inflation and options risk in one market05:40 Earnings estimates, AI optimism and why fundamentals still matter10:31 Aahan Menon on a difficult macro backdrop15:29 Why energy shocks and demand destruction take time20:24 Why inflation can persist even if the oil shock eases24:47 Ben Hunt on World War AI and the AI resource build-out30:00 AI CapEx as the pillar holding up market optimism34:00 The political backlash against AI data centers38:00 Why data center opposition matters for markets42:09 Why price action can distort the AI narrative47:48 CORE 1M, stretched call prices and downside spasm risk52:00 Why Nasdaq options are priced for upside crashes56:11 Index rules, human judgment and the SpaceX IPO01:00:34 The free float problem and rebalancing pressure01:05:22 Space data centers, valuation and the size of the AI opportunity

    שעה אחת ו-9 דקות

  3. לפני 5 ימים

    Cheap Is a Warning, Not a Thesis | Adam Parker on What This Market Is Really Pricing

    Adam Parker returns to Excess Returns to explain why the market may be trading more on future fundamentals than investors think, how AI is reshaping stock selection, and why traditional valuation signals may be less useful than they once were. We discuss AI revenue exposure, software vs. semiconductors, Mag Seven positioning, gross margins, estimate achievability, spinoffs, and Adam’s highest-conviction contrarian sector idea. Adam Parker on X https://x.com/Adam_Parker_Tri Trivariate Research https://trivariateresearch.com/ Trivector Research https://www.trivectorresearch.com Topics covered: Why “sell in May” and other calendar-based market rules often lack statistical support Why Adam thinks the stock market leads the economy, not the other way around How to think about whether today’s AI market is a bubble Why the market may be trading on 2030 or 2031 fundamentals When investors may start demanding returns on AI capital spending Why AI could create new jobs rather than simply destroy existing ones How large AI-related IPOs like SpaceX could affect index mechanics and portfolio flows Why gross margin expansion is one of Adam’s most important stock selection factors Why Adam remains cautious on software and prefers semiconductors over software How valuation, quality, and other traditional factors may have changed since COVID Why estimate achievability and incremental margins matter more than simple beats and misses How to think about the Mag Seven, Nvidia, and market concentration Why spinoffs may become more important in an AI-driven market Why healthcare is Adam’s highest-conviction contrarian sector idea Timestamps: 00:00 Why the market may be trading on future fundamentals 04:37 Is today’s stock market an AI bubble? 08:45 When AI capex needs to show real returns 13:00 How trillion-dollar IPOs could reshape index mechanics 19:00 Why gross margin expansion is such a powerful factor 23:00 Why software companies face AI-driven margin pressure 27:21 Where AI semiconductor exposure goes next 31:54 Why valuation does not work for stock picking 35:03 What has changed in markets since COVID 39:22 Estimate achievability and incremental margins 43:06 How to think about the Mag Seven and Nvidia 47:55 Why healthcare could be the biggest AI opportunity

    ‏50 דק׳

  4. 26 במאי

    He Built the Fund He'd Hold 30 Years | Eric Crittenden on What Investors Pick When Labels Come Off

    Eric Crittenden joins Matt Zeigler and Jason Buck for a deep dive into trend following and managed futures. They discuss why systematic macro trend investing works, how risk transfer creates a return premium, and how trend can fit inside a diversified all-weather portfolio. Standpoint Funds https://www.standpointfunds.com/ Topics covered: Why trend following can struggle during fast reversals and thrive after regime shifts How systematic investors manage whipsaws, drawdowns, and emotional pressure The trade-offs between short-term, medium-term, and long-term trend signals Why Eric prefers simple, durable systems over complex models and constant tinkering When it makes sense to remove a futures market from a systematic portfolio Why trend following may earn a risk transfer premium from hedgers and commercial users How copper producers, options markets, and insurance help explain trend following returns Why rising interest rates and short bond positions can benefit managed futures How trend following can pair with global equities in an all-weather portfolio Why smoothing a trend strategy can reduce its value when investors need convexity most The behavioral challenge of holding diversifiers that look wrong at the wrong time Why investors and advisors often want alternatives but struggle to stick with them Timestamps: 00:00 Why trend following opportunities appear under pressure 04:39 Pro-growth positioning before the whipsaw 09:32 Short-term vs long-term trend signals 13:46 The danger of tinkering with systematic strategies 18:43 What actually changes in a durable process 23:27 Rising rates, short bonds, and collateral yield 28:00 Copper hedging and why trend followers buy rising prices 32:00 Options, insurance, and risk transfer through time 36:28 Regime shifts and supply-demand imbalances 41:00 What investors choose when asset classes are anonymized 45:11 Building a portfolio for 30-year terminal wealth 50:06 Why portfolio construction is different than judging individual strategies 56:15 Why trend following and value investing require faith 01:00:42 Reducing errors vs chasing highlight-reel winners 01:05:36 Where to follow Eric and Standpoint

    שעה אחת ו-7 דקות

  5. 23 במאי

    Cliff Asness on Bubbles, Private Equity and His Research Greatest Hits

    Cliff Asness returns to Excess Returns for a greatest hits tour through some of his most important and entertaining investing ideas. We discuss bubble logic, today’s AI market comparisons, why volatility still matters as a risk measure, private equity “volatility laundering,” international diversification, market timing myths, pulling the goalie, and how machine learning is changing quantitative investing. Cliff Asness on X https://x.com/CliffordAsness AQR Capital Management https://www.aqr.com/ Papers Discussed Bubble Logic: Or, How to Learn to Stop Worrying and Love the Bull https://www.aqr.com/Insights/Research/Working-Paper/Bubble-Logic-Or-How-to-Learn-to-Stop-Worrying-and-Love-the-Bull Rubble Logic: What Did We Learn From the Great Stock Market Bubble? https://www.aqr.com/Insights/Research/Journal-Article/Rubble-Logic My Top 10 Peeves https://www.aqr.com/-/media/AQR/Documents/Insights/Journal-Article/My-Top-10-Peeves.pdf Volatility Laundering https://www.aqr.com/Insights/Perspectives/Volatility-Laundering I Did Not Predict What Is Going on in Privates https://www.aqr.com/Insights/Perspectives/I-Did-Not-Predict-What-is-Going-on-in-Privates (So) What If You Miss the Market's N Best Days? https://www.aqr.com/Insights/Perspectives/So-What-If-You-Miss-the-Markets-N-Best-Days International Diversification Works (Eventually) https://www.aqr.com/Insights/Research/Journal-Article/International-Diversification-Works-Eventually International Diversification - Still Not Crazy after All These Years https://www.aqr.com/Insights/Research/Journal-Article/International-Diversification-Still-Not-Crazy-after-All-These-Years Perhaps the Most Important Essay I Will Ever Co Author https://www.aqr.com/Insights/Perspectives/Perhaps-the-Most-Important-Essay-I-Will-Ever-Co-Author Main topics covered: How the dot-com bubble created its own internal logic Why Dow 36,000 and Cisco message boards captured bubble thinking What investors learned, and failed to learn, from the tech bubble How today’s AI market compares with the dot-com era Why long periods of underperformance make even good strategies hard to stick with Why Cliff still defends volatility as a useful risk measure Why “cash on the sidelines” is a misleading market narrative How private equity smoothing can make risk look lower than it really is Why the private markets debate is not a short-term prediction Why the “missing the best 10 days” argument against market timing is incomplete Why international diversification can still matter after decades of US outperformance What pulling the goalie can teach investors about risk, incentives and career risk How machine learning changes quant investing without eliminating economic intuition Timestamps: 00:00 Why certainty is dangerous in investing 04:58 Why Bubble Logic never became a book 10:18 Cisco, Yahoo message boards and bubble psychology 14:16 Rubble Logic and the lessons investors failed to learn 18:04 What today’s AI market has in common with the dot-com bubble 22:23 Why the long run can lie to investors 26:02 Volatility, permanent loss of capital and real risk control 30:19 Why there is no cash on the sidelines 34:00 Private equity, smoothing and volatility laundering 39:47 Why Cliff did not call the private markets downturn 43:19 The flaw in the missing the best 10 days argument 49:00 Why international diversification still works eventually 53:35 Why crashes are global but lost decades are local 57:30 Pulling the goalie and asymmetric risk 01:01:00 Why coaches and investors avoid optimal decisions 01:07:36 Machine learning, overfitting and economic intuition 01:10:50 Leverage, short selling and derivatives in quant portfolios 01:16:26 Where to follow Cliff Asness

    שעה אחת ו-19 דקות

  6. 21 במאי

    He Studied Every Bear Market Since 1929 | Ben Carlson on How the Worst Starting Point Still Made 8%

    Ben Carlson joins Excess Returns to discuss his new book Risk and Reward and the biggest lessons investors can learn from market history. We cover how to think about risk, inflation, market timing, bear markets, lost decades, diversification, compounding and why surviving volatility is the key to building long-term wealth. Ben's Book https://amzn.to/4dFHsQz Ben Carlson on X https://x.com/awealthofcs Ben's Blog https://awealthofcommonsense.com/ Main topics covered: Why risk is hard to define and always involves trade-offs How vivid risks like sharks and headlines distort investor decision-making Why doing nothing can be one of the hardest parts of investing How inflation should be viewed through personal finance, human capital and long-term investing Why stocks can be an inflation hedge even if they struggle during inflation spikes Why waiting for the market coast to clear often fails What the world’s worst market timer teaches about saving and staying invested How loss aversion shapes investor behavior What the Great Depression, bear markets and 30-year returns teach about long-term investing Why there is no perfect portfolio and the best strategy is one you can actually stick with Timestamps: 00:00 Ben Carlson on why risk and reward are attached 06:35 Doing nothing, action bias and better investing behavior 11:51 Inflation psychology and lessons from the 1970s 16:55 Why stocks can hedge inflation over the long run 21:07 Why waiting for the coast to clear is a market timing trap 26:30 Time horizons, loss aversion and portfolio behavior 31:49 Government rescue, left-tail risk and unintended consequences 35:54 Recessionary vs non-recessionary bear markets 42:09 Why the stock market and economy can diverge 47:24 Why compounding is about holding, not trading 51:37 Starting valuations, lost decades and future returns 55:40 Risk, reward and the biggest lesson for investors

    ‏57 דק׳

  7. 19 במאי

    Is AI Still in 1995? Gene Munster and Doug Clinton on the Next Phase of the AI Boom

    AI is moving from hype to real enterprise adoption, and Gene Munster and Doug Clinton join Excess Returns to explain what that means for investors, technology stocks, energy demand, jobs and the next phase of the AI trade. We discuss why AI may still be early in its bubble cycle, how frontier models like GPT, Claude, Gemini and Grok compare, why AI-powered investing is becoming more practical, and where the biggest second-order opportunities may emerge. Gene Munster on X https://x.com/munster_gene Doug Clinton on X https://x.com/dougclinton Deepwater Asset Management https://www.deepwatermgmt.com/ Intelligent Alpha https://www.intelligentalpha.co/ Main topics covered: • Why Doug Clinton still thinks AI could become a bigger bubble than dot-com • How Claude Code, Codex and frontier AI models are changing enterprise productivity • The job disruption risk for knowledge workers and why AI adoption may become a survival skill • Why the AI model race may not be winner-take-all • How Intelligent Alpha uses large language models to evaluate stocks and earnings expectations • Why GPT, Claude and DeepSeek perform differently across investing tasks • The AI infrastructure boom and why energy may be one of the most underappreciated bottlenecks • Hyperscaler CapEx, data centers and the investment case for continued AI spending • How major AI IPOs like SpaceX, Anthropic and OpenAI could affect public markets • Why space, orbital data centers and zero-gravity manufacturing could become real investment themes Timestamps: 00:00 AI, electricity and intelligence 04:33 Why new AI models changed the semiconductor trade 09:14 What AI means for knowledge worker jobs 14:03 Codex, Claude Code and Google’s AI challenge 18:50 OpenAI, Apple and the model capacity race 23:03 How many frontier AI models can survive? 27:18 Intelligent Alpha’s AI earnings benchmark 31:34 Why AI investors avoid emotional bias 35:33 Where to invest in the AI stack 39:00 Why AI energy demand is still underappreciated 43:43 How markets are judging hyperscaler AI spending 48:00 The investment opportunity in space 52:20 Final thoughts and closing

    ‏53 דק׳

  8. 16 במאי

    Jeremy Grantham on AI, Bubbles and Why Mean Reversion Lives On

    Jeremy Grantham joins Excess Returns to discuss The Making of a Permabear, mean reversion, market bubbles, AI, the Magnificent 7, and the long-term lessons investors can take from his career at GMO. We cover why he rejects the simple “permabear” label, how he thinks about valuation and bubbles, why AI may be both transformative and dangerous for investors, and why long-term thinking is so hard but so essential. The Making of a Permabear: The Perils of Long-term Investing in a Short-term World https://groveatlantic.com/book/the-making-of-a-permabear/ GMO https://www.gmo.com/americas/ Grantham Foundation https://granthamfoundation.org/ Topics covered: Why Jeremy Grantham thinks the “permabear” label misses the point The difference between being generally bearish and making a true “abandon ship” call Mean reversion, valuation cycles, and why history still matters for investors Why monopoly power helped reshape U.S. profit margins and market concentration How AI could turn today’s monopoly winners into brutal competitors Why new technology often becomes a cost of doing business rather than a permanent profit boost How Grantham defines bubbles using two-sigma market events Lessons from Japan, the dot-com bubble, the housing bubble, and the 2021 speculative peak Why institutional investors struggle to stick with value strategies during bubbles The role of purpose, climate risk, toxicity, and long-term thinking in Grantham’s later career The one lesson Grantham would teach ordinary investors about pessimism, realism, and time horizons Timestamps: 00:00 Jeremy Grantham on unpleasant news and long-term investing 04:18 Reinvesting when terrified in 2009 08:43 Why Grantham told investors to abandon ship in 2008 10:28 Mean reversion and why history matters 14:00 Monopoly power, the Mag 7, and rising market concentration 17:14 Why AI is important but impossible to forecast 20:21 AI as a cost of doing business 21:24 From monopoly profits to brutal AI competition 24:05 How investors should think about valuation mean reversion 27:00 Why high returns on capital should eventually attract competition 29:47 How Grantham defines a market bubble 33:00 Japan’s extreme bubble and GMO’s zero weight decision 34:19 The dot-com bubble and the pain of being early 38:00 Grantham’s bubble warning signal in 2021 41:35 Whether today’s market is showing classic bubble behavior 43:00 QuantumScape, meme stocks, and speculative excess 46:35 How ChatGPT interrupted the 2022 bear market 49:12 Investor behavior and the cost of underperforming in a bubble 55:00 Purpose, philanthropy, climate risk, and useful work 01:01:03 The one lesson Grantham would teach average investors

    שעה אחת ו-4 דקות
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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.

מידע

  • יוצרים
    Excess Returns
  • שנות פעילות
    2019 - 2026
  • פרקים
    514
  • סיווג
    תוכן בוטה
  • זכויות יוצרים
    © 905628
  • אתר התכנית
    Excess Returns

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