Benny & The Squirrel

About Benny & The Squirrel

Benny & The Squirrel is a twice weekly show about finance and markets. The show notes for members are hosted on Substack. www.bennysquirrel.tv (https://www.bennysquirrel.tv?utm_medium=podcast)

Publisher

Benny & The Squirrel

Category

business · business

Language

en

Explicit

No

First episode

30 Apr 2026

Latest episode

25 Oct 2026

Latest episodes

25 episodes in the feed.

1. 

   25 Oct 2026

   Assessing the AI Carnage

   Episode 98 and another unmissable Sunday Show! The AI trade is getting flushed. But is this the big one, or just another crowded-position unwind? We unpack the widening cracks in AI financing, why booming compute demand does not automatically mean booming revenue, and whether the S&P equal weight’s comeback signals a genuine market rotation. LLM Watch Pod Summary The AI Unwind in Numbers * The week’s equity weakness = a sharp reduction in crowded positioning, particularly around AI, rather than clear evidence of a broader market collapse. * This is probably not “the big one”. * Net leverage has been aggressively reduced, with positioning measures reaching the bottom percentiles * Similar to the deleveraging seen from late June into late July. * The damage within AI-related trades has been much more severe than the headline indices suggest * The central distinction is between a modest-looking index drawdown and a substantial collapse in individual speculative trades. AI financing: competition for capital becomes the constraint * Only a small number of players can compete effectively for credit-market funding. * Is access to financing is straightforward even for the largest companies? * Borrowers are having to pay more. * Beyond a certain point, a higher interest rate may not solve the problem because lenders hit capacity limits. * This creates a potential dividing line within AI: the ability to fund infrastructure may matter as much as the ability to generate demand for it. AI capex: compute demand is not external revenue (Minute 4) * Is the bullish argument that extraordinary demand for compute, including strong Hopper rental rates, is sufficient to justify AI investment. * Compute demand is not equivalent to revenue. * The relevant question is how much revenue must ultimately come from customers outside the AI industry to support the infrastructure spending. * Discussion of Paul Kedrosky’s AI capex revenue hurdle calculator (https://paulkedrosky.com/tools/revenue-hurdle/) * It translates AI capital expenditure into a required level of external revenue. * It then expresses that requirement relative to GDP, global software revenue and US white-collar salaries. * The purpose is to test whether the economic assumptions behind the investment cycle are plausible. * “Unlimited demand for compute” becomes less useful as an investment proposition unless it translates into real customer spending outside the sector. * Are credit markets are beginning to confront precisely this issue? AI usage versus spending (Minute 7) * Rapidly rising usage need not produce equally rapid growth in expenditure. * Better routing, system design and optimization can allow usage to grow geometrically while spending flattens or declines. * The key issue is whether customer spending will grow enough to justify the capital already committed. * The strategic motive for continued infrastructure investment. * Large operators may be trying to become indispensable, establish a toll-road position or price competitors out of the market. * In that scenario, the infrastructure owners could retain value even if the model developers face difficult economics. * Own the compute rather than be Anthropic or OpenAI but compute ownership only works if the owner can continue accessing capital markets. That narrows the investable universe substantially. * The hosts compare the possible outcome with a utility-like market in which a small number of dominant providers control access and capture the profits. What happened to Anthropic’s S-1? * Anthropic’s expected S-1 filing did not appear on Friday. * Delayed disclosure may help preserve the AI narrative. * Once detailed financial information becomes public, investors must assess the actual economics rather than an open-ended story. * Differentiation in private debt markets between OpenAI-backed and Anthropic-backed data-centre projects. * Some OpenAI-linked deals are reportedly not getting done. * Where financing is available, he has heard of differences of approximately 200 to 300 basis points. * He explicitly qualifies these observations as individual data points, not a comprehensive market survey. The sell-off spreads beyond direct AI beneficiaries (Minute 10) * The latest week’s weakness has extended further down the AI-related supply chain. * Copper miners fell nearly 10%. Iron ore miners were also coming under pressure. * The damage is moving from direct AI winners into second- and third-order beneficiaries. * Even traditional value investors are beginning to feel the effects. * He also sees increasing concern about slowing growth and a more stagflationary backdrop. * But do these apparently macro-driven moves simply just instead reflect the mechanics of crowded-position unwinds. Equal weight S&P versus Nasdaq (Minute 12) * The ratio has staged a striking rebound over past five weeks. * For it to extend, the semiconductors probably need to break down - but the weekly chart still in primary uptrend: * Betting against semiconductors means betting against currently booked revenue and earnings, not just a speculative narrative. * The hosts agree that “cheap” and “expensive” are difficult labels for highly cyclical businesses. * A bullish memory-stock thesis requires a clear view on: * The timing and scale of additional Chinese supply. * How that supply affects pricing. * Whether strong earnings can persist for another year or longer. * Very low multiples could produce attractive returns if current profitability lasts. * However, the thesis ultimately requires confidence in earnings further out, including 2028 and 2029. * The broader point is that the durability of earnings matters more than the apparent cheapness of a single year’s multiple. Industrials ‘20-for-20’ (Minute 18) * The traditional portfolio role for industrials is challenged in current pricing environment. * Industrials should ideally provide a steady base of compounding businesses. * Many now carry substantial premiums associated with AI infrastructure, electricity constraints or defence spending. * He revisits a hypothetical portfolio built from a 2006 starting point. * A portfolio extrapolating then-current narratives might have owned auto companies, handset manufacturers and GE. * A more successful hindsight portfolio could have included FANUC, Caterpillar and Schneider Electric. * The lesson is not simply to identify good businesses, but to distinguish business quality from the price paid. * Caterpillar is a classic case study - an “accidental bottleneck stock”. * He sees a similar pattern across industrial businesses connected with physical power constraints or the broader AI theme. * Defense stocks present a related problem. * Their thematic narratives are powerful. * That does not automatically make their starting valuations attractive for a portfolio assembled in 2026. Gold miner cash generation (Minute 23) * Popular narrative is that gold miners are “printing money” at $4,000 gold. * Some companies may be generating substantial cash. * That does not justify assuming the same economics across the sector or buying GDX indiscriminately. * Discussion of Respeculator (https://substack.com/profile/119464854-respeculator) research on ASX-listed gold miners. * The spread between gold prices and reported all-in sustaining costs can suggest margins of approximately $2,000 per ounce. * Yet those apparent margins are not consistently appearing as incremental cash on company balance sheets. * A major reason is spending classified as “growth capex”. * Some growth spending, including mine extensions needed to keep mills supplied, is economically necessary rather than genuinely optional. * He draws a direct comparison with AI accounting. * Ignoring model-training costs (‘EBTIT’) flatters the economics of AI labs. * Ignoring recurring mine-development requirements can similarly flatter the economics of gold producers. * The analytical requirement is to identify which companies actually convert high gold prices into cash after all necessary spending. If you act on anything provided in this newsletter, you agree to the terms in this disclaimer. Everything in this newsletter is for educational and entertainment purposes only and NOT investment advice. Nothing in this newsletter is an offer to sell or to buy any security. The author is not responsible for any financial loss you may incur by acting on any information provided in this newsletter. Before making any investment decisions, talk to a financial advisor. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.bennysquirrel.tv/subscribe (https://www.bennysquirrel.tv/subscribe?utm_medium=podcast&utm_campaign=CTA_2)

2. 

   23 Oct 2026

   Lost in The Bermuda Triangle

   In Episode 97, Benny & The Squirrel are joined by Nick Nemeth (https://substack.com/profile/130712974-nick-nemeth), author of Mispriced Assets (https://open.substack.com/pub/mispricedassets). Nick has spent fifteen months buried in 10,000 page statutory insurance filings, and what he found should worry anyone with an annuity, a life policy, or exposure to credit markets. The US life insurance industry runs a balance sheet the size of the entire American banking system, at roughly 16 to 17 times leverage, with capital that Nick describes as “completely fake”. A mere 5 percent write down on assets would wipe out the margin of error for most of the industry. And there no federal regulator with full sight of the system, and no obvious bailout big enough if it goes. Show Notes Insurance and the data problem * Why insurance? Nick calls it the most boring world - but the more you look, the more interesting it gets, for scary reasons. * Filings are enormous. About 680 insurers, and a single annual statutory filing can be nearly 10,000 pages. Mapping holdings across entities requires reading them or using LLMs. * The paywall problem. There is no EDGAR equivalent for insurance disclosures; the NAIC, the body meant to set guidelines, charges per filing (around 20 dollars each). SEC filings give you “really nothing”: you cannot see capital hardness or exposures. * Bad actors are pushing the risk spectrum. The highest yielding asset is private credit, so anyone pushing ROEs piles into it, and competitive pressure drags everyone else in. The $10 trillion balance sheet (Minute 3) * Scale. Asset side is about $10 trillion, liabilities of $9.6 trillion, once discounted. Functionally a balance sheet the size of the entire US banking system. True in force policies are way above $9.6 trillion. * Discount rate mechanics. Liabilities are PV’d back and the residual is equity. Contrary to what most assume, there is no standard risk free discount rate. Offshore reinsurance creates “toggles” to change the discount rate and flatter returns. Operators openly call it regulatory arbitrage. * The black Box. Aggregate in force policies and liabilities are visible, but average duration and granular data are not. Whatever sits in Bermuda, the Caymans or Barbados is legally beyond the reach of US regulators; the fact that Nick cannot answer basic questions after 15 months of reading NAIC filings is itself one of the problems. * Regulatory structure. No single federal regulator. Fifty one jurisdictions set their own rules, the NAIC is a quasi private standard setter “like the Federal Reserve except no law made it”, and individual state commissioners can grant “permitted practices”, essentially permission slips to break NAIC guidelines. * Nick’s view: the system is intelligently designed to have no oversight. Fed involvement is limited to SIFIs like AIG, MetLife, Prudential. Leverage, marks and capital quality (Minute 8) * Industry leverage is about 16 to 17 times. Huge dispersion: mutuals are generally better, listed companies worse, and private equity backed insurers worse again, with exceptions both ways. * Athene (Apollo’s life vehicle) has only 8 percent Level 1 assets (cash and treasuries). The rest is Level 2 and Level 3. Level 3 is an internal Excel model, but Nick has concerns about Level 2 as well: observed marks do not match market prices, and top of book liquidity is not the same as clearing prices. * Most insurers are in significant trouble if assets fall 5 percent, before even considering liabilities and hedging. * Mental model: an insurer is like a bank. Assets are mostly loans (plus equity repackaged as credit, including the newer “equity ABS”); liabilities are premiums instead of deposits. It is a spread business. * Leverage is simply assets over equity, defined the same way as for Lehman. The capital and surplus buffer between solvency and insolvency is “super soft, as in completely fake”, inflated via permitted practices and questionable or phony reinsurance. Insurers do go under, failures seem to be picking up, and when they fail there is always less capital than expected. * State guaranty funds cap protection at roughly 250k (300k in New York; California covers 80 percent up to 250k), on the total policy value, unlike FDIC deposit cover. A 1 million dollar annuity becomes a three quarters write down. * Runoff evidence. Insurers report surrenders running far above expectations as rates rose, despite policyholder inertia. The reputational run dynamic (the SVB, “60 Minutes asks if your insurer is safe” scenario) is unmodeled and could spike extraordinarily. With a 5 percent margin of error, a 15 percent write down on private credit puts some carriers close to the edge. What ‘Civilians’ Can Watch (Minute 25) * Equities will not tell you (passive flows distort prices). Watch the credit instead, for example Global Atlantic and similar insurer bonds, and subordinated issues. Practical advice: buy the 20 dollar statutory filing for your own insurer, run it through an AI, and check private credit exposure, leverage, and affiliated reinsurance out of Bermuda. * History says it can happen. Annuities existed in the city states of the 1500s and 1600s; insurers failed in the Depression, at the turn of the century, Executive Life failed in the 1990s high yield unwind, and failures are occurring now. What has never happened in our lifetime is a critical mass failure, and Nick predicts it will pick up a lot. * Complexity exceeds banking. Athene’s derivative book alone is a 3,000 page exhibit. Filings are only snapshots, and books can be dressed up for each reporting date. Regulators and commissioners do not have the answers either. Opacity has opened a window for extreme risk taking and, in some cases, fraud. * Tails hide in the shadows. Actuaries are smart, but almost nobody can jointly model asset correlations in a tail event and liability behavior under stress. People are predictable in normal times, not in crises: in 2008, policyholders surrendered even as the Fed cut rates, because they were broke. * Correlation is where it dies. Models assume stationary correlation, then in a tail everything goes to one while you need liquidity. That was the basis error behind CDOs, and it repeats in private credit and broadly syndicated loan CLOs, which are less diversified than believed (around 35 percent software exposure, heavy housing, real cyclicality). Outliers get excluded from the stats, which is exactly how things blow up. The endgame ( Minute 35) * The bailout question. Government could plug the hole, but Nick’s worry is that mispriced, consumer linked credit is everywhere, including the housing market, so a rescue could spiral beyond the sort of control seen in COVID. * The required number would exceed COVID (which exceeded World War II and dwarfed 2008), insurers are roughly 150 percent of the Fed’s balance sheet, and a credible response could mean 10 to 15 trillion dollars, expanding M2 by 25 to 33 percent in a year, with the bond market potentially revolting. * This is global. SocGen, BNP Paribas and Allianz carry similar private credit exposure, as does Asia. * Authorities always refuse the medicine, which takes gold toward $10,000/Oz. Gold works in both deflation and devaluation; deleveraging crashes are the time to buy it, as in late 2008 before the GFC structurally ended that November. Practical implication: shorting insurers caps you at 100 percent; the bigger money is on the other side of the trade. The New Subprime Crowd Wears Patagonia Vests (Minute 42) * Growth cannot bail the system out of a 6 percent deficit, leaving two paths: deleveraging through defaults or inflation. Private equity professionals are borrowing against carry and even their homes to meet capital calls and GP commitments of 2 to 5 percent per fund, with nothing returning, while funding Connecticut lifestyles on million dollar salaries. Asset rich on paper, cash poor. * The K shaped economy risk. If the top of the K stops feeling wealthy and stops spending, you get a recession that is extremely hard to fix. And this time the bailout politics are different: in 2008 people were in shock and Occupy came later; now everyone knows from day one who would be rescued (Apollo is the named example; Leon Black still owns 7 percent). Nick doubts the political appetite exists, raising the risk of a massive recession instead. * The historical analog is Japan, but Japan was Asia centric; this could be a global lost decade, with AI generating growth in pockets while everything else stagnates and most people do not work at Anthropic or OpenAI. * Europe and Japan are huge net creditors to the US. If they need to plug domestic holes, they will be forced sellers of US assets (the S&P and the Nasdaq). Nick’s New Real Estate Report (Minute 53) * Hyper levered housing: mortgage payments relative to median income are at the highest level ever, including 2006 and 2007. Commercial real estate, multifamily and US single family are all disasters, and Australia, the UK and especially Canada are as bad or worse. A global real estate problem stacked on top of the insurance problem. * Nick still tries to pick stocks (”there’s always a bull market somewhere”), but after a year of pulling threads and finding progressively scarier things, he is genuinely concerned about what comes next. The actionable takeaway at the personal level: save, cut spending, build a war chest. * An optimistic take to pair with the bearishness: an asset price reset would clear the forest, rebuild society on better footing, and put things back on track for his generation, because the current path without a crisis is off the rails. If you act on anything provided in this newsletter, you agree to the terms in this disclaimer. Everything in this newsletter is for educational and entertainment purposes only and NOT investment advice. Nothing in this newsletter is an offer to sell or to buy any security. The author is not responsible for any financial loss you may incur by acting on any information provided in this newsletter. Before making any investment decisions, talk to a financial advisor. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.bennysquirrel.tv/subscribe (https://www.bennysquirrel.tv/subscribe?utm_medium=podcast&utm_campaign=CTA_2)

3. 

   18 Oct 2026

   AI Panic

   For Episode 96 the show brings ‘Black Monday’ (we think not!) chatter, neocloud CDS blow outs, and Brent 2027 going vertical. We break down the first real pain at index level this year, why the AI unwind is a positioning flush and not the big one, the sovereign backstop question hanging over Anthropic / OpenAI and the data center complex, and where the smart money is actually hiding. All that, plus the Squirrel’s latest work on the ‘Twenty for Twenty’ portfolio (Global Industrials) and why BYD might be the world’s most impressive industrial company but a less impressive stock. Latest LLM / Token Chart Packs Show Notes The week that was, and the AI unwind * Key dynamics: a continued bid to bonds and growing concern about the AI narrative unwinding, centered primarily on neocloud balance sheets, a theme running since the Amish episode in March. * The hosts turned bearish in early June, calling the blow-off top in AI CapEx recipients. * SpaceX segment: the biggest unlock is coming; the market is being warmed up for a possible Tesla-SpaceX merger; SpaceX supply was talked about all summer but nobody is positioned. Shares went from around 210 down to near 100; the company has raised roughly $65bn in credit since listing (including a new $40bn package of $30bn IG plus $10bn term loan) plus around $110bn in equity. Elon has taken roughly $86bn in cash out of the market. Last week’s price action and positioning (Minute 5) * First real pain at index level after months of poor breadth: defensives caught a bid, staples up over 5 percent and utilities rallied. * We doubt this is the flush moment: it looks like an overcrowded trade unwinding on positioning and liquidity, with vol and implied correlation too low, a pattern seen repeatedly over the past fifteen years. * Midterm history suggests risk trades well afterwards; a Democrat result probably would not be great for stocks. * Growth-scare data points: Anthropic numbers came in “miss-ish,” average token price hit an all-time low, and rumors that the IPO timetable could slip again. A slipped $100bn Anthropic IPO at a $2tn pre-money valuation could paradoxically be bullish for year-end liquidity. * Triggers: the pulled Firmus IPO in Australia (long end of the curve bid from 5.70% to 5.40% since), plus UK neocloud Nscale having a major Microsoft contract pulled over the weekend. Amusing tweet: “if I were Jensen, I’d simply buy all my clients.” Positions, sovereign backstops and China (Minute 9) * 🐿️ is short Oracle and CoreWeave but nervous about NVIDIA acting as “the central bank of AI” and papering over the stress. * “Too big to fail” whispers about OpenAI are now circulating, an idea the show covered with Brandon Carl (guest on next week’s show) and in earlier episodes. * What sovereign intervention would actually mean: backstopping Wall Street’s data center credit at the monetary level rather than taking golden shares. OpenAI’s CFO floated a government backstop in Q4 2025 before walking it back on LinkedIn. * The circular dependency problem: OpenAI’s commitments underpin Oracle and cloud backlogs plus data center DDTLs; if OpenAI goes down, data centers, debt and collateral go down with it, a GFC-style chain. The flip side is adding huge liabilities to the sovereign just as debt refinancing costs are under scrutiny. * China keeps making tokens cheaper: the latest DeepSeek model offers near-frontier capability at roughly a 90 percent token-cost discount, so any US sovereign underwriting would be backing a disastrous forward P&L structure and would likely need to be twinned with protectionism. * Fortune 500 companies increasingly want to build their own AI on open-source models and their own hardware for data security; fraud risk is rising; large corporates are blocking agentic access to their APIs, and technically blocking agents is much harder than it sounds. Korea trigger and the IPO pipeline (Minute 21) * Korea looks like the proximate trigger, reacting to the Anthropic numbers. The SK Hynix ADR still trades at roughly a 50 percent premium to the Seoul listing, which cannot be arbitraged. Even international retail can buy locally, so there is no reason to pay the ADR premium. * OpenAI is definitely not coming public this year; Anthropic price talk is sliding from $2tn toward $1.5tn pre-money, and the view is they should just price at $1tn and get it out the door. * IPOs are momentum games: publicly talking down valuation before pricing is almost unprecedented (closest comp is Facebook’s 2012 “mobile problem”, but at a $100bn valuation, not $1.5 to $2tn). Too late to halve the target now, and the forward capital problem, roughly half a trillion to raise over four to six years, means they have to start big. Energy: the real hiding place (Minute 25) * Energy was again a good place to hide. The standout chart is December 2027 Brent: the market is reaching for long-dated contracts while large spec shorts (COT data) remain substantial. * Under the “China collar” theory, the move in long-dated crude underwrites the energy equities; the IXC global energy ETF chart looks strong. * Spike risk is higher now: Jesper Kohl’s point that Japan runs out of reserves by January; China is down an estimated 300 to 400m barrels; global reserves are being drawn. Transport costs now add $20 to 30 per barrel, yet China is still lifting cargoes, suggesting more right tail. * Demand is low volatility (COVID aside); supply is where the volatility sits. A double negative, soft demand against an even worse supply situation, could still push prices up. Rotation mechanics (Minute 30) * The AI trade is 40-plus percent of the S&P; neither host thinks it is truly rolling over yet, and if AI rolls over while the index holds via rotation, their non-AI longs benefit. * India outperformed the rest of Asia massively last week; Brazil is trading on its own election cycle with the runoff the following week. Both are read as positioning: popular funding shorts (staples, Infosys, TCS-type names) getting squeezed in a degrossing. * The “causal barbell”: implied correlation near zero with single-stock vol in the 99th percentile forces leveraged pods to degross when correlation rises, so shorts rip and longs get sold, but it does not cascade the way old crash analogies suggest. Twenty for Twenty - The Industrials (Minute 35) * Twenty for Twenty portfolio update: work began on industrials. * The key industrial question is the China scenario (the “panda in the room”) * BYD - arguably one of the most impressive industrial companies on the planet, but a great company is not necessarily a great stock. Deflationary technologies are hard to monetize compared with regulatory-capture industries and full-contact capitalist competition in Chinese industrials should never be underestimated. If you act on anything provided in this newsletter, you agree to the terms in this disclaimer. Everything in this newsletter is for educational and entertainment purposes only and NOT investment advice. Nothing in this newsletter is an offer to sell or to buy any security. The author is not responsible for any financial loss you may incur by acting on any information provided in this newsletter. Before making any investment decisions, talk to a financial advisor. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.bennysquirrel.tv/subscribe (https://www.bennysquirrel.tv/subscribe?utm_medium=podcast&utm_campaign=CTA_2)

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