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Excess Returns

Excess Returns
Excess Returns
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506 episoder

  • Excess Returns

    Financial Risk Has Quietly Left the Banks | Marc Rubinstein on What That Means for Markets

    15.05.2026 | 1 t. 3 min.
    Marc Rubinstein joins Excess Returns to explain what private credit, bank earnings, insurance balance sheets, fintech growth, and arbitrage firms reveal about the modern financial system. The conversation covers why private credit risks may not be systemic in the traditional banking-crisis sense, but still matter for investors because of redemption gates, hidden leverage, opaque structures, incentive conflicts, and correlations that can spike when markets are under stress.
    Marc Rubinstein on X
    https://x.com/MarcRuby
    Net Interest
    https://www.netinterest.co/
    In this episode, we discuss:
    Why the Fed says private credit redemption risks are limited and manageable

    What Blue Owl’s redemption gates reveal about private credit liquidity

    How post-2008 bank regulation pushed risk into private credit, hedge funds, trading firms, and exchanges

    Why banks and private credit firms are both competitors and collaborators

    The “layer cake” of leverage connecting banks, private credit, and borrowers

    How HSBC’s loss tied to Atlas and MFS highlights hidden credit risks

    Why insurance companies have become increasingly tied to private credit

    Why rapid growth can be dangerous in financial businesses

    What bank earnings show about the gap between weak consumer confidence and resilient spending

    Why post-mortem reports from SVB, Credit Suisse, and other failures reveal what investors could not see in real time

    How Revolut became one of the most interesting fintech stories in global banking

    Why Marc calls this a potential golden age of arbitrage

    What Jane Street, public BDC discounts, private asset valuations, and geopolitical fragmentation tell us about market structure

    Why investors may still be too anchored to the 2008 banking playbook

    Where Marc sees risk and opportunity in financials, banks, Europe, and non-bank financial institutions

    Timestamps:
    00:00 Private credit, hidden risks, and correlation spikes
    05:03 Why Blue Owl became a private credit warning sign
    10:20 How private credit grew after the 2008 financial crisis
    15:30 Banks and private credit as financial “frenemies”
    19:44 HSBC, Atlas, MFS, and the layer cake of leverage
    24:11 Apollo, Athene, insurance assets, and private credit incentives
    29:20 Why higher rates have not broken more of the financial system
    33:40 Bank earnings, consumer confidence, and resilient spending
    37:20 Why “I don’t know” can be a powerful signal from bank CEOs
    41:46 Revolut and the ambition to build a truly global bank
    47:38 Why growth can be dangerous in finance
    52:19 Private assets, public BDC discounts, and arbitrage opportunities
    56:34 What investors misunderstand about banks today
    59:31 How Marc would think about financials as a long-short investor
  • Excess Returns

    Lessons from Investing Through Bubble Regimes with Andy Constan

    14.05.2026 | 1 t. 4 min.
    First Principles with Andy Constan launches with a deep dive into market bubbles, AI, semiconductor stocks, and the financial conditions that can turn powerful technological change into a dangerous investment regime. Andy explains how bubbles form, why they are almost impossible to time, how today’s AI boom compares to past episodes like 1987, the dot-com bubble, housing, and the bond bubble, and what investors should watch as expectations, financing, and FOMO build.
    Andy Constan on X
    https://x.com/dampedspring
    Damped Spring Advisors
    https://dampedspring.com/
    Topics covered:
    Why bubbles are easy to identify in hindsight but nearly impossible to define in real time

    The difference between an expensive market and a true bubble regime

    How new technologies, easy money, regulation, and exogenous shocks can create bubble conditions

    Why AI may rhyme with the internet boom without being an exact repeat

    The role of ChatGPT, Microsoft’s OpenAI investment, and semiconductor earnings expectations

    What the 1987 crash, Japan, housing, bonds, and dot-com bubble can teach investors today

    Why human nature, FOMO, and “keeping up with the Joneses” make bubbles so powerful

    How the late-1990s Fed response to Long-Term Capital Management helped fuel the final phase of the tech bubble

    Why tech’s current size in the economy and market may limit how far the AI boom can grow

    How AI capex, hyperscaler spending, buybacks, debt issuance, and IPO supply could determine what happens next

    Timestamps:
    00:00 Intro and the challenge of identifying bubbles
    04:32 Expensive markets vs true bubble regimes
    09:57 The five bubble episodes Andy compares to today
    14:35 Root conditions, escalation events, and the peaking phase
    19:20 Why the 1987 crash may also have been a bubble
    24:25 The late-1990s setup and the Netscape Navigator moment
    28:00 Crisis analogs, easy financial conditions, and today’s AI parallels
    32:20 Long-Term Capital Management and rocket fuel for the tech bubble
    36:11 Why tech’s market share matters more today than in the 1990s
    43:18 Policy mistakes, subsidies, and how governments feed bubbles
    47:42 Semiconductor earnings expectations and valuation risk
    53:45 The AI capex chain and where the money has to come from
    58:42 IPOs, corporate debt, and the financing risk behind the AI boom
    01:02:27 What investors should do differently in a bubble regime
  • Excess Returns

    He Wrote the Book on Bubbles | Edward Chancellor on If AI is Different

    12.05.2026 | 1 t. 17 min.
    Edward Chancellor joins Kai Wu on the latest episode of the Intangible Economy to discuss what financial history and capital cycle theory can teach investors about today’s AI boom. They explore why transformative technologies can still produce terrible investor returns, how overinvestment develops, where anti-bubbles may be forming, and what past episodes like the railway mania, the dot-com bubble, China’s investment boom and the post-2008 interest rate regime suggest about the risks and opportunities today.
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    Topics covered:
    How capital cycle theory applies to the AI data center boom

    Why railway mania, autos, aircraft and the dot-com bubble offer lessons for today

    Why markets often fund major technology transitions but fail to identify the winners

    The prisoner’s dilemma driving hyperscaler AI spending

    Whether AI demand can justify the supply being built

    How GPU depreciation and AI capital spending may affect reported earnings

    Why hallucinations and reliability may limit the total addressable market for large language models

    The case for looking at AI anti-bubbles instead of shorting the bubble directly

    Why China shows that strong GDP growth does not guarantee strong shareholder returns

    How intangible capital, SaaS valuations and human capital fit into capital cycle analysis

    Whether bubbles can be good for society while still being bad for investors

    Why the long-term interest rate cycle may have changed

    The role of gold in a world of expensive stocks, rising debt and vulnerable bonds

    Timestamps:
    00:00 Edward Chancellor on capital cycles, bubbles and AI
    04:42 Why the railway mania became a classic overinvestment cycle
    09:00 Why markets fund technology booms but often miss the winners
    13:19 The prisoner’s dilemma behind AI spending
    17:30 Will AI demand justify the supply being built
    20:00 How capital spending can inflate profits before the bust
    25:08 The AI Hindenburg moment and the limits of large language models
    30:55 Why AI hype may exceed the proven technology
    35:55 Why the anti-bubble may matter more than shorting AI
    40:00 The energy transition bubble and the opportunity in overlooked assets
    45:08 China’s lesson on GDP growth and shareholder returns
    49:27 Big Booze, GLP-1s and the Lindy effect
    54:23 Can intangible capital have its own capital cycle
    59:54 SaaS valuations and the index creation warning signal
    01:04:10 Why bubbles can help society but hurt investors
    01:09:09 Why long-term rates may be in a new multi-decade cycle
    01:14:07 Why Edward Chancellor still sees a role for gold
  • Excess Returns

    We Asked an Options Expert Why This Melt Up Hasn’t Broken — and Which Signal Could End It

    10.05.2026 | 1 t. 7 min.
    Brent Kochuba of SpotGamma joins Jack Forehand for the May 2026 OPEX Effect to break down what options positioning is saying after a massive AI and semiconductor-led market rally. They discuss SPX call volume, zero DTE options, dealer gamma, VIX expiration, NVIDIA earnings, oil risk, AI CapEx, and why options flows may help explain both the market’s recent melt-up and the potential for a volatility shift after OPEX.
    Guest Links
    Brent Kochuba on X
    https://x.com/spotgamma
    SpotGamma
    https://spotgamma.com/
    Topics Covered
    Why the market has ignored oil shocks and geopolitical risk while AI earnings dominate investor attention

    How AI CapEx, semiconductors and mega-cap tech have driven a powerful melt-up in stocks

    Why options volume and zero DTE trading are increasingly important for all investors

    How dealer hedging, delta and gamma can affect stock market moves

    Why options expiration can create short-term turning points in markets and volatility

    What the May OPEX setup says about call-heavy positioning in the S&P 500

    Why single-stock options activity in NVIDIA, Tesla, Apple, Amazon and AI-related names matters

    How record SPX call volume is being driven by short-dated options flows

    Why Brent is watching VIX expiration, NVIDIA earnings and May 19 to May 20 for volatility expansion

    What oil, VIX, correlation and dispersion are signaling about market risk

    Timestamps
    00:00 Intro: SPX call volume, call-heavy positioning and transient options flows
    00:57 Are we in melt-up mode?
    05:29 AI, UFOs and how fast market narratives are changing
    09:00 Why options flows matter more for everyday investors
    13:39 Could SpaceX become the next huge options market?
    16:00 How dealer hedging, delta and gamma move through the market
    20:44 Why OPEX can become a turning point for stocks and volatility
    23:22 Why May OPEX is so call heavy
    28:07 The market rally into May expiration
    33:00 AI rebranding, meme behavior and downside headline risk
    36:07 Reviewing last month’s oil and volatility setup
    40:17 How the war flipped market leadership back to tech
    44:13 Dealer gamma support in the S&P 500
    49:19 Single-stock gamma in NVIDIA, Tesla, Apple and Amazon
    51:06 Record SPX call volume and the role of zero DTE
    54:55 Semiconductor, AI and memory call volume
    57:50 From bearish positioning to peak-bull dispersion
    59:22 Oil, the S&P 500 and changing correlations
    01:03:06 COR1M, dispersion risk and when Brent considers hedging
    01:04:57 Brent’s key takeaways for May OPEX and volatility expansion
  • Excess Returns

    We Asked a $4.5B Quant Manager Why the S&P 500 Is Just 46 Stocks — and Why Small Caps Aren't Dead

    08.05.2026 | 1 t. 2 min.
    Elena Khoziaeva, Co-Chief Investment Officer and Portfolio Manager at Bridgeway Capital Management, joins Excess Returns to discuss factor investing, small caps, value investing, market concentration, intangibles, passive investing, market neutral strategies, and the role of AI in quantitative investment research.
    We cover how Bridgeway combines disciplined quantitative models with human judgment, why the S&P 500 may be less diversified than investors think, and how investors can think about diversification when mega-cap growth stocks dominate market returns.
    Bridgeway Capital Management
    https://bridgeway.com/
    I Know What You Did Last Summer
    https://bridgeway.com/perspectives/i-know-what-you-did-last-summer/
    How Many Stocks Are Effectively in the S&P 500?
    https://bridgeway.com/perspectives/how-many-stocks-are-effectively-in-the-sp500/
    Topics Covered
    Why quantitative investing still needs human judgment and skepticism

    The difference between smart beta and true multi-factor portfolio construction

    How Bridgeway combines value, quality, sentiment and risk controls

    Why the size premium may depend on how small-cap stocks are defined

    Why recently fallen large caps and IPOs can distort small-cap research

    How the small-cap universe has changed as companies stay private longer

    How intangible assets affect traditional value and quality metrics

    Why value can work in bursts and why timing factor rotations is so difficult

    How concentrated the S&P 500 has become using the HHI framework

    Why passive investing may create opportunities for active small-cap managers

    How market neutral strategies can help investors manage equity market volatility

    How AI can help with data, text analysis and trading without replacing investment judgment

    Timestamps
    00:00 Why fewer than 50 stocks are driving S&P 500 returns
    01:04 Bridgeway’s evidence-based investing approach
    02:59 Why quantitative models need human judgment
    07:52 Smart beta vs multi-factor investing
    11:32 How Bridgeway builds multi-factor portfolios
    16:08 Rethinking the size premium
    20:31 Has the small-cap universe gotten worse?
    23:49 How intangibles change value investing
    28:05 Does value still work?
    30:09 Why value returns can be episodic
    33:11 Why factor investors need patience
    35:22 How concentrated is the S&P 500?
    40:29 Factor strategies as portfolio diversifiers
    41:41 Passive investing and market structure
    44:27 Managing volatility with market neutral strategies
    49:40 How systematic managers update their models
    55:02 How Bridgeway is using AI
    01:00:03 Elena’s biggest lesson for investors
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Om Excess Returns
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.
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