Excess Returns

Professor Aswath Damodaran joins Kai Wu on The Intangible Economy to break down how to value SpaceX, AI companies, intangible assets, and the future of value investing.We discuss why big markets do not automatically create big value, how AI CapEx is changing the character of major technology companies, and why the best investment stories still have to connect to the numbers.Subscribe on Spotify⁠⁠⁠⁠Subscribe on AppleTopics covered:Valuing SpaceX after its IPO and why price matters even for great companiesHow Starlink, space launch, and xAI fit into SpaceX’s valuation storyWhy total addressable market can mislead investors in AI and other disruptive industriesThe problem with AI unit economics, data centers, power, water, and reinvestment needsWhy growth can destroy value when margins and returns on capital are weakHow intangible assets, R&D, future growth, and narratives should show up in valuationThe Big Market Delusion and how overconfidence drives boom and bust cyclesWhy AI CapEx is different from the dot-com boom and could create broader risksHow AI is changing the character of the Magnificent Seven and semiconductor companiesWhy value investing became rigid, ritualistic, and righteous, and how it can evolveTimestamps:00:00 Why great companies can still be bad investments01:03 Introducing Aswath Damodaran and The Intangible Economy01:49 SpaceX IPO, Starlink, xAI, and the challenge of valuing uncertainty05:31 Why Starlink became the core of SpaceX’s current revenue10:31 How Damodaran valued SpaceX across launch, connectivity, and AI14:07 Why AI’s huge market may still have difficult unit economics17:10 The tension between SpaceX competing in AI and renting data centers to competitors20:00 Why valuation should use distributions instead of false precision22:39 How stories and numbers work together in valuation26:45 Why investors confuse promises, potential, and businesses30:49 The Big Market Delusion and overconfidence in AI investing33:02 Why the AI CapEx boom is different from the dot-com bubble35:17 How AI infrastructure is changing the Magnificent Seven38:36 Nvidia, Micron, semiconductors, and the risk of peak cycle earnings41:00 Why the biggest AI market stories could be scary for society43:37 AI disruption, labor markets, and the speed of technological change46:30 Measuring which jobs and companies are most exposed to AI automation49:00 Why AI cost structure may look more like Spotify than software51:13 The unresolved business model questions for LLMs and AI agents52:29 Why traditional value investing lost its edge56:03 Passive investing, book value, and the blame game in value investing58:13 Why rigid value investing is vulnerable to AI disruption01:00:58 How value investing can adapt to intangible assets and uncertainty01:02:21 Why any company can be a good investment at the right price01:04:57 Why investing mistakes and track records are harder to judge than they look

In this episode of The OPEX Effect, Jack Forehand and Brent Kochuba break down the market structure impact of the SpaceX IPO, options expiration, dealer gamma, volatility, and the next major setup for the S&P 500 and Nasdaq. They discuss why SpaceX may trade more on flows than fundamentals, how call buying could create a gamma squeeze, and why June OPEX, VIX expiration, FOMC, oil, Iran headlines, and index inclusion could all collide at once.Subscribe to the OPEX Effect on Spotify⁠⁠⁠⁠Subscribe to the OPEX Effect on Apple PodcastsTopics covered:Why SpaceX is a flows game at the start of tradingHow the SpaceX IPO could affect liquidity across mega cap tech stocksWhy fundamentals may not matter when index flows and forced buying dominateThe role of Nasdaq, Russell, and S&P 500 index decisions in SpaceX tradingHow options could create a gamma squeeze in SpaceXWhy dealer hedging flows can push stocks higher or lowerWhat June options expiration could mean for the S&P 500Why VIX expiration and FOMC create a key market windowHow Core1M signaled the recent volatility spasmWhy expensive calls, not put buying, drove the recent market stressThe key S&P 500 levels Brent is watching into OPEXHow oil, rates, inflation, and Fed policy could affect market volatilityWhy Nasdaq options pricing is diverging from the S&P 500How SpaceX index inclusion could widen the gap between Nasdaq and the S&PWhat would make Brent add protection or look for another short-term market correctionTimestamps:00:00 Opening clips and the SpaceX flow setup05:27 Elon Musk net worth after the SpaceX IPO07:13 SpaceX, liquidity, Mag Seven selling, and index demand12:48 Why SpaceX may trade on flows before fundamentals17:59 What options trading could change for SpaceX22:05 How call buying can create a gamma squeeze28:24 Why June OPEX matters more than a normal expiration33:55 VIX expiration, FOMC, and market path dependency37:20 The Core1M signal and the recent volatility spasm41:22 The S&P 500 gamma map and key risk levels46:25 Why expensive calls drove the market stress50:14 Oil, rates, inflation, and the Fed setup57:03 The JPMorgan collar and the 6900 to 7000 support zone58:32 Nasdaq versus S&P 500 after the SpaceX IPO01:03:14 Brent’s summary, SpaceX gamma squeeze risk, and the next market setup

Mike Green joins Excess Returns to explain why passive investing, index construction, SpaceX, AI IPOs and mega-cap concentration may be changing how the stock market actually works. We discuss how passive flows can affect prices, why AI earnings may be more circular than investors think, what could break the current market narrative, and why the economy feels much weaker for many households than the headline data suggests.Michael Green Twitterhttps://x.com/profplum99Simplify Asset Managementhttps://www.simplify.us/Topics covered:Why the SpaceX IPO has turned passive investing into a mainstream market structure debateHow index committees and passive flows can influence individual stocksWhy low float, Nasdaq demand and passive buying could create unusual IPO dynamicsHow new AI-related equity issuance could change the supply-demand balance in the stock marketThe research behind passive flows, market impact and cap-weight concentrationWhy Mike thinks passive buying explains more of mega-cap outperformance than AI fundamentalsThe circular financing risk in AI, including Nvidia, CoreWeave, Google and AnthropicWhy buy-the-dip flows, ETFs, CTAs and vol control funds matter for market directionHow headline economic data can miss household stress, second jobs and lost purchasing powerWhat Mike is watching to see whether the AI trade and market narrative are starting to breakWhy AI may be hugely valuable to consumers before it creates major business productivity gainsHow companies may eventually redesign business models around AI rather than simply automate tasksWhy SpaceX wealth creation could seed the next generation of competitorsHow inflation, gasoline prices, low savings and a K-shaped economy are affecting consumersTimestamps:00:00 Passive indices, AI profits and why this market feels different04:07 Why SpaceX changed the passive investing debate08:01 The research behind passive flows and market impact12:16 Why Mike thinks passive flows explain mega-cap strength16:18 ETF flows, buy-the-dip behavior and bubble dynamics20:28 Why economic data can miss household stress25:13 Bubble warnings, CAPE and what investors may be ignoring29:17 AI as a consumer advice engine versus a productivity revolution33:29 How businesses may redesign themselves around AI37:51 Why IPO wealth may create the next generation of competitors42:06 Mike Green’s upcoming book on passive investing and market structure

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 Xhttps://x.com/munster_geneDoug Clinton on Xhttps://x.com/dougclintonDeepwater Asset Managementhttps://www.deepwatermgmt.com/Intelligent Alphahttps://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 themesTimestamps:00:00 AI, electricity and intelligence04:33 Why new AI models changed the semiconductor trade09:14 What AI means for knowledge worker jobs14:03 Codex, Claude Code and Google’s AI challenge18:50 OpenAI, Apple and the model capacity race23:03 How many frontier AI models can survive?27:18 Intelligent Alpha’s AI earnings benchmark31:34 Why AI investors avoid emotional bias35:33 Where to invest in the AI stack39:00 Why AI energy demand is still underappreciated43:43 How markets are judging hyperscaler AI spending48:00 The investment opportunity in space52:20 Final thoughts and closing

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 Xhttps://x.com/MarcRubyNet Interesthttps://www.netinterest.co/In this episode, we discuss:Why the Fed says private credit redemption risks are limited and manageableWhat Blue Owl’s redemption gates reveal about private credit liquidityHow post-2008 bank regulation pushed risk into private credit, hedge funds, trading firms, and exchangesWhy banks and private credit firms are both competitors and collaboratorsThe “layer cake” of leverage connecting banks, private credit, and borrowersHow HSBC’s loss tied to Atlas and MFS highlights hidden credit risksWhy insurance companies have become increasingly tied to private creditWhy rapid growth can be dangerous in financial businessesWhat bank earnings show about the gap between weak consumer confidence and resilient spendingWhy post-mortem reports from SVB, Credit Suisse, and other failures reveal what investors could not see in real timeHow Revolut became one of the most interesting fintech stories in global bankingWhy Marc calls this a potential golden age of arbitrageWhat Jane Street, public BDC discounts, private asset valuations, and geopolitical fragmentation tell us about market structureWhy investors may still be too anchored to the 2008 banking playbookWhere Marc sees risk and opportunity in financials, banks, Europe, and non-bank financial institutionsTimestamps:00:00 Private credit, hidden risks, and correlation spikes05:03 Why Blue Owl became a private credit warning sign10:20 How private credit grew after the 2008 financial crisis15:30 Banks and private credit as financial “frenemies”19:44 HSBC, Atlas, MFS, and the layer cake of leverage24:11 Apollo, Athene, insurance assets, and private credit incentives29:20 Why higher rates have not broken more of the financial system33:40 Bank earnings, consumer confidence, and resilient spending37:20 Why “I don’t know” can be a powerful signal from bank CEOs41:46 Revolut and the ambition to build a truly global bank47:38 Why growth can be dangerous in finance52:19 Private assets, public BDC discounts, and arbitrage opportunities56:34 What investors misunderstand about banks today59:31 How Marc would think about financials as a long-short investor

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.Subscribe on Spotify⁠⁠Subscribe on AppleTopics covered:How capital cycle theory applies to the AI data center boomWhy railway mania, autos, aircraft and the dot-com bubble offer lessons for todayWhy markets often fund major technology transitions but fail to identify the winnersThe prisoner’s dilemma driving hyperscaler AI spendingWhether AI demand can justify the supply being builtHow GPU depreciation and AI capital spending may affect reported earningsWhy hallucinations and reliability may limit the total addressable market for large language modelsThe case for looking at AI anti-bubbles instead of shorting the bubble directlyWhy China shows that strong GDP growth does not guarantee strong shareholder returnsHow intangible capital, SaaS valuations and human capital fit into capital cycle analysisWhether bubbles can be good for society while still being bad for investorsWhy the long-term interest rate cycle may have changedThe role of gold in a world of expensive stocks, rising debt and vulnerable bondsTimestamps:00:00 Edward Chancellor on capital cycles, bubbles and AI04:42 Why the railway mania became a classic overinvestment cycle09:00 Why markets fund technology booms but often miss the winners13:19 The prisoner’s dilemma behind AI spending17:30 Will AI demand justify the supply being built20:00 How capital spending can inflate profits before the bust25:08 The AI Hindenburg moment and the limits of large language models30:55 Why AI hype may exceed the proven technology35:55 Why the anti-bubble may matter more than shorting AI40:00 The energy transition bubble and the opportunity in overlooked assets45:08 China’s lesson on GDP growth and shareholder returns49:27 Big Booze, GLP-1s and the Lindy effect54:23 Can intangible capital have its own capital cycle59:54 SaaS valuations and the index creation warning signal01:04:10 Why bubbles can help society but hurt investors01:09:09 Why long-term rates may be in a new multi-decade cycle01:14:07 Why Edward Chancellor still sees a role for gold