The Bubble No One Can Sell | Dan Rasmussen on the Private Equity Trap
What this covers
In this episode of Excess Returns, Justin and special guest host Kai Wu of Sparkline Capital are joined by Verdad’s Dan Rasmussen for a deep dive into the hidden risks lurking in private equity—and why they may be more dangerous than investors realize. Rasmussen, a long-time critic of the asset class, explains why the allure of illiquidity, stale pricing, and past outperformance has led to dangerous capital misallocations. Along the way, we explore the origins of the Yale model, the current liquidity crunch, volatility laundering, and whether small-cap value could be the better bet today. We also dig into bubbles, biotech, and whether AI will concentrate or diffuse economic power.
🔑 Topics covered:
* Why private equity may not be what investors think it is * The original logic of the Yale model—and how it’s broken today * Leverage, small company risk, and the illusion of low volatility * How private equity portfolios are “money traps” in disguise * Small-cap value as public market private equity * Why biotech could be the next overlooked opportunity * How innovation bubbles spark long-term progress * AI’s capital intensity and implications for Big Tech dominance * Behavioral risks in institutional vs. retail investing
📍 **Timestamps:** 00:00 – Why private equity could be a money trap 03:00 – The over-allocation to small, low-margin, highly levered companies 07:25 – Why private equity’s popularity may signal poor future returns 14:30 – The Yale Model’s origin story and how it morphed 19:25 – Collapse in private equity distributions 23:34 – Volatility laundering and misleading risk metrics 27:00 – What happens when private equity goes public 31:00 – Do lockups help investor behavior—or prevent learning? 35:10 – Could small-cap value be a better alternative to private equity? 42:00 – Why biotech is the most beaten-up corner of small caps 47:00 – Bubbles, innovation, and the role of speculative excess 51:00 – AI, capital intensity, and a return to economic gravity 54:00 – Will AI empower monopolies or smaller players?
Source description (no synthesized summary yet).
Dan Rasmussen argues that private equity has become massively overallocated by institutional investors despite representing small, highly leveraged, and low-quality companies, creating significant downside risk that will likely manifest as either a capital incineration event or a prolonged 'money trap' of depressed returns.
- Private equity's $2.5T market cap across 12,000 companies is only 5-6% the size of the S&P 500, yet endowments allocate 15-40% to it, representing massive overallocation relative to economic fundamentals
- PE-backed companies are small (avg $300M market cap), low-margin, and highly leveraged (50-60% debt), making them objectively riskier than public large-caps, yet PE distributions have collapsed from 30% to 10% of NAV despite record stock market highs, signaling exit channels are breaking
- Reported PE volatility is artificially suppressed through illiquidity and mark-to-fantasy, but London-listed PE funds reveal true volatility of 24% annualized with 30% NAV discounts, showing public market skepticism of PE valuations
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Investing is fundamentally a game of 'metaanalysis'—not about what you think is true, but about what you think relative to consensus, because efficient markets price consensus beliefs, so you can only make money by holding beliefs that differ from consensus and are correct.
“investing is not a game of analysis. It's a game of metaanalysis... the argument is that it's not what you think that matters, it's what you think relative to what everyone else thinks.”
It's possible that both the bullish narrative on tech/AI and the skeptical narrative are simultaneously true: tech innovations are genuinely transformational, but valuations may also be excessive and result in poor forward returns, creating a scenario where innovation thrives but investors suffer losses.
“both possible that that's true and that some of these areas are bubbles right that there's just too much capital that's not going to get paid off uh and and both of those things can be true and actually beneficial uh in the long run to the economy.”
Active small-cap equity managers have largely disappeared from the industry, and the natural buyer for private equity companies that go public via IPO would be active small-cap managers, but this constituency no longer exists in sufficient size to absorb PE exits.
“my sort of quip about the IPO market is the natural buyer um, for a private equity deal that goes public is an active small cap manager. >> Maybe an active midcap manager. And I sort of joke, have you met any active small cap managers, right? I mean, like there's just not enough of them to buy this stuff.”
In the 1980s, following the 1970s stagflation crisis where both stocks and bonds lost money, endowed institutions became desperate for diversification and adopted the 'Yale Model' pioneered by thinkers like Jim Bailey at Cambridge Associates and later David Swenson at Yale, which redirected capital into alternative assets like venture capital, private equity, and real estate.
“there was this huge sort of u uh uh huge question among these endowed institutions of like well gee that sucked right like we thought our stocks and our bonds were diversifying they both lost money. Um so these endowed institutions were desperate for something else to do. Um and so what they ended up doing is looking for quote unquote alternatives right?”
The idea that 'what the wise man does at first, the fool does at the end' suggests historical patterns in financial markets where good strategies eventually become crowded and break as everyone copies them.
“what the wise men does at first the fool does at the end or something. there's some I can't get quite get the quote”
The Yale Model of endowment investing, pioneered in the 1980s by David Swenson and others, was originally a rational response to the 1970s stagflation crisis that destroyed both stock and bond returns, and it did generate outperformance through venture capital and private equity in early decades when these markets were underpenetrated and inefficient (PE traded at 40% discounts to public comps), but this advantage has disappeared as trillions of capital have flowed in.
“the 70s happened where both bonds and equities lost money for a decade because of stagflation. Um, and so by 1980 there was this huge sort of u uh uh huge question among these endowed institutions of like well gee that sucked right like we thought our stocks and our bonds were diversifying they both lost money. Um so these endowed institutions were desperate for something else to do.”
Harvard's endowment suffered massive losses from a 20% allocation to commodities and emerging markets in the 2000s, which was the consensus 'alternative asset' at the time, demonstrating that institutional consensus about alternatives is often wrong and that fashionable alternative allocations regularly underperform.
“Harvard's endowment for example our alma mater uh thought this was a great alternative asset and put 20% of their portfolio in a combination of commodities and emerging markets and emerging market commodities that essentially was a negative return for 15 years and a huge drag on the portfolio.”
The volatility of private equity is misrepresented by NAV reporting, which shows 10% standard deviation annually similar to investment-grade bonds; but publicly listed private equity funds on the London Stock Exchange reveal the true volatility through market prices is about 24% annualized (similar to Russell 2000), with the gap between NAV and market price being the discount-to-NAV, which itself is highly volatile.
“the NAVs um the reported navs are just as volatile as other private equity navs, right? They're about 10% per year standard deviation. Um but the market price uh is 24%. And the delta is the discount to NAV. So turns out that people have various reasons uh for discounting more or less, right?”
Bubbles are a necessary part of innovation ecosystems—you need 'a thousand flowers to bloom' and 'speciation before selection'—meaning excessive speculation creates the capital availability and alternative funding sources that fuel new company formation, and most ventures fail but the winners (Amazon, Apple, Google) are transformational.
“you need to let a thousand flowers bloom, right? I mean that every innovation wave um you you need people uh you need speciation before you can have selection uh in evolutionary terms and uh and so what do you need to create a massive amount of new companies? you need a massive amount of speculation in risky ventures um to create that speciation”
A reasonable starting point for investing is to own passive index weights in all assets, then only take active bets where you believe there is a metaanalytic reason you are right—meaning a differentiated view not shared by consensus.
“first, right, start with efficient markets, right? Okay, own the passive weight, right? Be passive, right? That's sort of a good starting point. and then only take those active bets um where you believe that there's a metaanalytic reason that you're right.”
London-listed PE fund discounts to NAV have widened from approximately 95 cents on the dollar in 2021 to 70 cents on the dollar today, reflecting a marked shift in public market perception of PE valuations and timing with the decline in distributions.
“if you look at the um discounts to NAV at which these London listed private equity funds trade at um they've gone from 95 cents in the dollar in 2021 or so to like 70 cents in the dollar today.”
The buildup of risk is easy to see by looking at actual numbers, but the timing of when risk unwinds is impossible to predict—Dan's PE thesis is not controversial when examined rationally, but markets stay irrational longer than individuals can stay solvent, making the timing of PE's reckoning unknowable.
“I think it's easy to see buildups of risk. It's hard to call when they're going to end, right? Like I I actually don't think my like negative private equity thesis is like I don't know when you actually look at the numbers or like think through it rationally um it's not that controversial. I don't know, right? Like isn't it obvious to everyone that too much money is going into private markets, right? The only question is like when it's going to blow up”
Active small-cap mutual fund managers have largely disappeared or consolidated, eliminating the natural buyer base for PE-backed IPOs, which Rasmussen jokes is 'the cleanest way to see how broken the IPO exit channel is.'
“700 private equity funds closed and uh the other small cap active public equity manager said oh 700 funds closed god that's brutal for all the employees and uh and the guy said oh no no in private equity when you close a fund it means it launched because in the mutual fund world all he could think of was was, you know, closing fund closed, fund clo fund shut down, another fund shut down, right?”
Private equity backed companies represent approximately 12,000 companies with an aggregate market capitalization of about $2.4-2.5 trillion, making the sector roughly equal in size to the Russell 2000 (2,000 companies worth ~$2 trillion) but with dramatically smaller average company size ($300 million per PE company vs $2 billion per Russell 2000 constituent) and therefore massively smaller than the S&P 500 ($50 trillion across 500 companies).
“there are about 12,000 private equity back companies, so six times the number in the Russell 2000. Um, and they have an average market cap of about 300 million or so, which means they have an aggregate market cap about 2.5 trillion, 2.4, 2.5 trillion, right? So, let's call it about the same size as the Russell 2000”
Correlated beliefs—where everyone thinks the same thing and you agree—represent the worst-case investing scenario because not only is the belief fully priced in, but there is no risk premium for holding it, making it impossible to generate returns despite being right.
“in some sense, um the spectrum of beliefs on a given topic is indicative to you of the ability for you to make money, right? And if if there's what I call correlated beliefs where everybody thinks the same thing and you agree, you're really not going to make money, right? Like that's the worst case scenario because not only is what you believe priced in, but there's no sort of risk premium for believing it, right?”
If an institutional investor with 60% equity allocation allocates proportionally to market cap, they should have only 3.6% in private equity (60% × 6% PE weight), yet many pension funds hold 15%, college endowments hold 30%, and elite college endowments hold 40%, representing a massive overallocation relative to the size and quality of underlying businesses.
“I'm going to say that like 60% time 6% should be in private. So I should have about 3.6% weight in private markets. And but if I have a 15% weight or a 30% weight or god forbid a 40% weight, I am massively massively overallocated to these 12,000 companies.”
The M&A exit channel for PE is weak because private equity has concentrated about 40-50% of its deals in vertical software and vertical SAS companies, which lack strategic buyers among public companies—a public SaaS platform like Salesforce has no natural reason to acquire a vertical dealer SaaS, limiting the pool of potential strategic acquirers.
“I'd say one of the reasons it seems private equity is really focused a lot on sort of vertical software, a vertical SAS software, probably 40 50% of the deals and some something like that. Uh, and maybe there aren't a lot of public buyers who want to integrate like the auto dealer vertical SAS company or whatever and take that public. It just doesn't fit. Like why would Salesforce need to buy that?”
AI is a capital-intensive technology, unlike previous tech innovations (internet, search, cloud) that had high operating leverage and low capital requirements—AI has high capital intensity per query due to energy consumption, making it operationally similar to traditional utilities and cyclical industries with poor return profiles.
“I think what's interesting about AI is that it's the first tech innovation that's capital intensive. Okay. Well, since fiber, okay, sorry, we've got the second. That's the second. Um, uh, but we know how the fiber one ended. And I think that the AI one is a similar problem, right? So, um, uh, so is AI amazing? ... Um uh so the companies that are offering this service um uh the tech compan these big tech companies have gone from having about a third of the capital intensity of US industrial companies to three times the capital intensity of your typical US industrial company, right?”
The great irony of the Yale Model is that in 1980, investors who simply bought the S&P 500 and 30-year treasuries would have done fine and not needed alternatives at all—the call for alternatives was triggered by a specific point-in-time market anomaly (stagflation) rather than a permanent structural problem requiring permanent solution.
“the great irony of that is if in 1980 you just bought the S&P 500 and 30-year treasuries you you'd have been fine right you didn't need any alternatives then it just turned turned out there was sort of like this point in time.”
The shift to selling private equity exposure through 401k plans and retail ETFs is happening precisely when traditional fundraising and exit channels are declining sharply, suggesting PE is being pushed to retail markets at exactly the wrong time—when institutional momentum is reversing.
“it's not a surprise that amidst those traditional channels drying up, we're seeing this massive increase in 401k, add it to the 401k, sell it to retail. Um, uh, it's happening at precisely the time that traditional fundraising channels are declining, declining quite sharply.”
Institutional investors behave worse than retail investors: institutional investors change CIOs every 6 years, change portfolios every 3 years, and 'shoot the dead horse' (follow momentum), whereas retail Bogleheads/Vanguard investors set up auto-invest and forget their login—a more disciplined approach.
“institutional investors I've found to be quite fickle um uh for a whole variety of reasons they get a new CIO every six years who changes the portfolio um you know every 3 years they shoot the dead horse in the last three years etc etc um uh so I I'm not sure that I I sort of buy the the framing that um that institutional investors uh need this less than than retail investors ers.”
The US is currently experiencing a rare innovation era similar to Vienna in the 18th century for classical music or England in the early 19th century for steam engines—with developments in internet, mobile, cloud, and AI that are genuinely transformational, and figures like Elon Musk will be textbook historical figures.
“we're living in one of these rare times. We we really are. I I think you have to step back and say like this like Vienna for classical Vienna in the 18th century for classical music or or England in the early 19th century with the steam engine, right? That we're living in that for tech, right?”
When a narrative has been repeatedly profitable (tech optimism, 'buy the dip'), investors become conditioned to believe that strategy will always work, and risk accumulates in the system—skeptical voices arguing 'maybe this valuation is too high' get systematically ignored, creating dangerous buildup of mispriced risk.
“people get conditioned and this metaanalytic thinking, right, like the correlated beliefs harden because things have been paid off, right? It's paid off to be an optimist about new technology. It's paid off to buy the dip. um uh it's paid off to do all of these things which sort of in a rational view you'd sort of say I don't know like I don't know that that's a good idea um and I think that that builds up risk in the system.”
Hyperscaler AI companies are likely overspending on capex—paying enormous salaries to AI researchers based on the assumption that AGI will be built and any capex is worth it, creating the conditions for eventual disappointment when AGI predictions prove overly optimistic.
“look at the salaries Mark Zuckerberg is paying these AI, you know, researchers. Like, I don't know, it seems crazy to me. Like, I don't think anyone can be worth that much. Um, but I think when you think that, um, we're designing like artificial general intelligence, like any capital spending is worth it. Um, so if that's your philosophy, like, do you think these people are likely to be overspending on capex or under spending? Like probably overspending.”
US business cycles have become less volatile and are experiencing a 'dampening' effect, reducing the frequency of sector-specific crises and bankruptcies that historically created opportunities for value investors to profit from mean reversion, making value investing less effective as a general strategy.
“the US has experienced this sort of dampening of the business cycle that um that the US economy is just less volatile. Um, and to some extent what value does best with is like volatile cyclical times where like people are randomly panicked about carpet manufacturers and then carpet manufacturing is fine the next year and you make a lot of money”
Bubbles and excessive optimism are necessary drivers of innovation because they create massive capital availability that fuels 'speciation' (diversification) of new ventures, and though 99% of these ventures fail, the 1% that succeeds creates transformational value, making bubbles economically beneficial despite losses to marginal investors.
“you need to let a thousand flowers bloom, right? I mean that every innovation wave um you you need people uh you need speciation before you can have selection uh in evolutionary terms and uh and so what do you need to create a massive amount of new companies? you need a massive amount of speculation in risky ventures”
Investing is not a game of analysis, it's a game of metaanalysis—meaning success depends not on what you believe is true, but on what you believe relative to what everyone else believes, since consensus views are already priced into markets and offer no risk premium.
“it's not what you think that matters, it's what you think relative to what everyone else thinks. Right? If if you think AI is a really cool technology and therefore you're going to make a lot of money buying AI stocks, you know, you've missed one uh crucial part of the ingredient, which is that other people have also figured out that AI stocks are good.”
It's easy to know when you're in a bubble in real-time but hard to know when it will end; people who said the 1990s tech bubble was a bubble were right, but the timing of the crash was unpredictable and caused early pessimists to be wrong on timing.
“everyone who said that we were in a tech bubble in the '90s was right. They were installed too early. Um, and I think what's sort of interesting about this environment is you know, it's paid for the last 10 or 15 years to be a futurist, right?”
US small-cap energy stocks have been a 'wasteland' since the 2015 shale bust; shale and fracking companies are 'capital incineration machines' that require massive investment but never generate returns that justify the capital expenditure.
“energy had this tremendous boom into 2014 and 15. Uh and then sort of a bust, a crazy bust, and then no one's really been able to make money in small cap energy stocks since... they're you know, the stereotype is that they're capital incineration machines. They require a lot of investment to go and drill the wells and the the oil that comes back just never seems to quite justify it on a return basis.”
Alternative investments like commodities and emerging markets—promoted as diversifiers in the 2000s—have not necessarily worked out; for example, Harvard's endowment allocated 20% to commodities and emerging market combinations which delivered essentially zero returns over 15 years, demonstrating that alternative asset classes do not have a law guaranteeing success.
“in the 2000s, um uh one of the big uh alternative assets of course was commodities and emerging markets. Um and uh you know Harvard's endowment for example our alma mater uh thought this was a great alternative asset and put 20% of their portfolio in a combination of commodities and emerging markets and emerging market commodities that essentially was a negative return for 15 years and a huge drag on the portfolio.”
It is relatively easy to identify when you are in a speculative bubble (most observers in 1990s correctly identified tech bubble as a bubble), but it is extremely difficult to predict when the bubble will end or reverse, making timing bubble collapses nearly impossible.
“I think I think it's um uh it's it's easier to know when you're in one and hard to know when it's going to end you know I mean I think everyone who said that we were in a tech bubble in the '90s was right. They were installed too early.”
Perhaps the only alpha available in markets is in the next quarter's earnings, not in multi-year forecasts, which is why pod shops (quantitative traders focused on quarterly earnings) have been successful despite criticism from fundamental investors for being short-term focused.
“maybe next quarter's earnings is all anyone can predict. Like maybe that's where all the alpha is. Like maybe there's actually no alpha past a quarter. Yeah. Like I'm I'm not saying I necessarily believe that, but it's at least worth considering, right?”
Private equity has been the 'darling of investors' eyes' for the past decade, with surveys showing that 90% of institutional investors believe PE will outperform public equity, and the median expected outperformance is 200 basis points net of fees per year.
“private equity is uh is sort of the dar or has been until recently and we should talk about what's changed. It's it's sort of striking how much things have changed in the last few months. Um but um but private equity has been the darling of investors eyes uh for the past decade.”
It has paid off for the last 10-15 years to be a futurist (believing sci-fi fan narratives about technology) and a tech optimist—these investors have been correct, and skeptics have been systematically wrong—which has conditioned the market to believe that optimism is always rewarded and pessimism is always punished.
“it's paid for the last 10 or 15 years to be a futurist, right? Like if you grew up reading like popular science and basically like giving credence to every magazine cover and then like having the idea like I should bet money on all of this stuff like um, you've actually been a pretty good investor... conversely, the skeptics uh like uh me uh who have said, 'Hey, gee, you know, maybe we're maybe this valuations are too high... We've all been wrong, right?'”
The Magnificent Seven stocks (Nvidia, Microsoft, Apple, Google, etc.) now represent approximately 33% of S&P 500 market capitalization, up dramatically from more diversified historical levels, and these firms are the primary locations where AI is being developed and deployed.
“the magnificent 7, Nvidia, Microsoft, Apple, Google, so on so forth, right? Which have increased to, I want to say 33% or around one-third of the market cap of the entire index, right?”
The best opportunities for making money are things people are most pessimistic about, most capital-starved, or places where there is no capital and no attention despite lack of pessimism—opposite of the PE case, which is full of capital and enthusiasm.
“I want to look for my places that are going to be uh I'm the option to opportunity to make the most money are the things that people are most pessimistic about um or that are most capital starved um or both. Um or maybe even places that are really capital starved but actually no one's all that pessimistic about. They just don't even care.”
Biotech is currently experiencing massive technological advancement similar to Florence in the Renaissance or England during the industrial revolution—a transformational period in scientific research—yet biotech stocks are performing worse than small-cap energy or banks, trading like 'dog crap', representing one of the biggest pain points in small-cap equity markets.
“we're going through a period uh of biotechnological advances that probably is similar to Florence and the Renaissance, right? This is like a moment in history where we're making massive advancements in biotechnological research. We're learning so much about the science and yet these stocks are just dog crap, right? I mean like trading like worse than small cap energy or small cap banks.”
Depreciation schedules on AI hardware like Nvidia servers are critically important to profitability—if servers have 5-year lives, Nvidia is overvalued; if servers have 1-year lives, data center companies are doomed—and this uncertainty creates enormous valuation risk not priced appropriately.
“how fast do you think Nvidia servers depreciate is like an actually meaningful question now for a lot like those depreciation schedules really matter um to some of these companies income statements and to the fate of our equity markets right like and to the fate of Nvidia right like is Nvidia if these are like fiveyear depreciation lives and like Nvidia is probably pretty overvalued and if they have one year depreciative lives like a lot of these data center companies are screwed”
The private credit market faces enormous refinancing pressure as companies with payment-in-kind (PIK) debt default or are forced to restructure, particularly in a downturn scenario, which could force lenders to take writedowns similar to 2008.
“in a bankruptcy rate environment, right, I would expect 100% of the things that are picking today to go bankrupt and then some percent of the things they're not picking to, you know, have to pick and therefore go bankrupt as well”
Private equity is fundamentally investing in very small companies—the 12,000 PE-backed companies have an average market cap of about $300 million, making them roughly 10 times smaller than Russell 2000 constituents and tiny compared to S&P 500 companies which average $100 billion market cap.
“private equitybacked companies uh represent they're about 12,000 private equity back companies, so six times the number in the Russell 2000. Um, and they have an average market cap of about 300 million or so”
Historically, private equity deals traded at about a 40% discount to public equity market valuations, creating a large arbitrage opportunity over 20-year periods that early PE firms could exploit; venture similarly benefited from being the only formal capital source for tech entrepreneurs in the 1980s.
“in the early days in public private equity, you know, private firms were trading at about a 40% discount to the public equity market, right? huge gap um that could be arbitrageed and was over a 20-year period.”
Many PE-backed companies already pay interest in kind (PIK) rather than cash, adding debt instead of paying interest; in a bankruptcy environment, 100% of companies currently on PIK would go bankrupt plus some percentage of companies not yet on PIK, potentially making the actual bankruptcy rate higher than 25%.
“depending on the numbers you look at a pretty high percentage of private credit is already picking with payment in kind where they don't pay cash interest. they just add money to the debt. And so in a bankruptcy rate environment, right, I would expect 100% of the things that are picking today to go bankrupt and then some percent of the things they're not picking to, you know, have to pick and therefore go bankrupt as well.”
US small-cap banks lack attractive opportunities for growth and M&A activity; after the First Republic failure, the sector recovered but remains uninviting because small regional banks struggle to reach scale without consolidation, and consolidation is not occurring at the pace required.
“the banks, which um you know, all these small cap regional banks just don't seem all that exciting. And then they had that big blow up when First Republic went bust uh and then they kind of recovered, but it's just been not a very exciting place to be. And maybe that's because there's not enough M&A and you they haven't been able to reach scale or whatever.”
Valuing biotech companies requires abandoning traditional cash-flow-based metrics and instead focusing on intangible assets: patent quality, research quality, drug development pipeline quality, and people quality, since biotech firms have no tangible assets, minimal revenue, and no near-term profits.
“when you're talking about a biotech stock, they don't have assets and they don't have revenue and they don't have profit. So, you have to figure out a way to think about value beyond that. You know, what does value mean? And it has to be intangible value. It has to be the quality of the patents or the quality of the research, the quality of the drug and development or the quality of the people.”
The US economy has experienced a dampening of the business cycle—it is less volatile and subject to fewer bankruptcy waves—which reduces the random cyclical volatility (people panic about carpet manufacturers, then the industry recovers) that historically drove value investing returns.
“the US has experienced this sort of dampening of the business cycle that um that the US economy is just less volatile. Um, and to some extent what value does best with is like volatile cyclical times where like people are randomly panicked about carpet manufacturers and then carpet manufacturing is fine the next year and you make a lot of money”
Private equity distributions have collapsed from approximately 30% of NAV annually (historical average) to about 10% of NAV currently—the lowest level since 2008—despite the stock market reaching all-time highs, indicating either that PE assets are overvalued or that exit channels have broken down.
“typically private equity distributes about 30% of NAV a year. Um, but recently those distributions have dropped up down to about 10% of NAV. um which is the lowest since 2008. Um and if you haven't noticed, we're not exactly in a recession right now. We're in probably a stock market reaching all-time highs.”
US small-cap value has worked primarily as a cyclical early-recovery play—it performs well during the early stages of economic recovery when markets are rotating from growth—but is difficult or impossible to profit from outside those specific windows.
“value in the US um worked um from COVID until the release of batch GPT and other than that has not worked. So I think the other way to sort of look at um small cap value in the US or at least how it's traded recently is that it's almost entirely a sort of cyclical play like a early stage recovery play. It seems to certainly work in those times but it just feels like impossible to make money other than those moments.”
Private equity has been the 'darling of investor eyes' for the past decade, with surveys showing that 90%+ of institutional investors believe PE will outperform public equity by a median of 200 basis points per year net of fees—representing correlated bullish beliefs with no differentiated view.
“private equity has been the darling of investors eyes uh for the past decade. Um and if you look at um institutional investors um pension funds have about 15% of their money in private equity, college endowments 30%, elite college endowments 40%. Um so um you know the biggest the quote unquote most sophisticated investors uh love this um and if you do surveys of these people um uh they generally will answer on surveys that they believe almost 90 plus% of them believe private equity will outperform public equity. Um and uh generally the margin the sort of median margin is by 200 basis points net of fees per year.”
PE will resolve in one of two ways: either as a 'money trap' where capital trickles out over 20 years at much lower returns than expected, making investors unhappy with a slow bleed; or in a bankruptcy cycle where 25% of PE-backed companies go bankrupt in a 2008-like recession, causing capital incineration—though the exact outcome depends on macroeconomic conditions which are impossible to predict.
“It's a money trap, right? the money's gone in, it's just not going to come out, right? It's not it's going to trickle out... the question I think is um is there a bankruptcy cycle or not?... My guess would be 25%, right? So I I could see 25% of private equity back companies going bankrupt in a in a 2008 like scenario.”
Being a 'futurist' (crediting speculative long-term technology predictions, as one might from reading popular science magazines and betting on speculative innovations) has been a profitable investment strategy for the past 10-15 years, while skepticism about valuations or technology hype has been consistently wrong, creating path-dependent conditioning where investors assume speculation will continue to be rewarded.
“it's paid for the last 10 or 15 years to be a futurist, right? Like if you grew up reading like popular science and basically like giving credence to every magazine cover and then like having the idea like I should bet money on all of this stuff like um, you've actually been a pretty good investor. Like that's been a good outcome. Like sci-fi fans have been the winners here.”
Market concentration in the 'Magnificent 7' (Nvidia, Microsoft, Apple, Google, and others) now represent approximately 33% of total S&P 500 market cap, and this concentration means that the index's returns are entirely dependent on a small number of large-cap tech companies, creating vulnerability if tech valuations compress.
“if you're an investor in the S&P 500, you've done really well and a large part of the reason why you've done so well is because of the, you know, astounding performance of the magnificent 7, Nvidia, Microsoft, Apple, Google, so on so forth, right? Which have increased to, I want to say 33% or around one-third of the market cap of the entire index”
Private equity in 2011-2014 succeeded by buying small, illiquid, cheap, and leveraged companies; this strategy can be replicated in public markets by buying small-cap value stocks with similar financial leverage, eliminating the need for PE vehicles if you can achieve characteristic matching.
“private equity in the 80s and 90s was was was small cap value on steroids. It was leveraged small cap value. Um, and unsurprisingly, it did pretty well during a period where small cap and small cap value did well.”
The question of whether AI is a centralizing or decentralizing force is critical: will the three firms with sufficient capex to build AI models maintain permanent monopolies, or will AI become commoditized and benefits accrue to long-tail users and appliers rather than builders?
“the question becomes is AI a centralizing or decentralizing force. Is it going to be the case that you know the three firms that have enough capex to be able to build out these models will have monopolies that will kind of endure forever or is it the case that these things become commoditized and it's in fact going to be you know the long tale the users the appliers of these technologies that get the boost.”
PE volatility is artificially suppressed in reported NAVs due to illiquidity and mark-to-fantasy accounting, but publicly-listed PE funds on the London Stock Exchange (like Harbourvest funds) reveal that true PE volatility is approximately 24% annualized, driven by discounts to NAV that vary with investor sentiment, making PE roughly as volatile as the Russell 2000 (small-cap) index with a beta of ~1.6.
“They've had volatility that's just crazily high. And the NAVs um the reported navs are just as volatile as other private equity navs, right? They're about 10% per year standard deviation. Um but the market price uh is 24%. And the delta is the discount to NAV.”
The biotech sector is currently severely undervalued despite being in a period of extraordinary technological advancement ('like Florence in the Renaissance') because biotech companies have no near-term cash flows and can only be valued on intangible assets (patent quality, research quality, team quality, drug development pipeline), and investors and markets are unable or unwilling to properly value intangible assets.
“my sort of intuition is that we're going through a period uh of biotechnological advances that probably is similar to Florence and the Renaissance, right? This is like a moment in history where we're making massive advancements in biotechnological research. We're learning so much about the science and yet these stocks are just dog crap, right?”
Small-cap value has worked very well internationally and earned a premium to market benchmarks, but has been severely underperformant in the US, where small-cap and value stocks trade at their largest discount to large-cap and growth stocks in history.
“small cap and small small cap value has worked quite well internationally. It's earned a premium to the market. It's outperformed the market benchmarks. Um, and if you have been a small cap value investor internationally, you're generally quite happy and proud of yourself... if on the other hand uh you were a small cap value investor in the US um all of a sudden um you believe that you are the world's worst investor known to man... because the small caps are trading at the biggest discount relative to uh large caps ever in history”
The best opportunities for investors lie in places that are either (1) most capital-starved, (2) most pessimistic-about (in expectation), or (3) both—because these conditions signal mispricing and lack of competition for the opportunity.
“well, I want to look for my places that are going to be uh I'm the option to opportunity to make the most money are the things that people are most pessimistic about um or that are most capital starved um or both.”
Profit-focused investors should be skeptical about very long-term thinking in markets: if you cannot predict what will happen in 4-5 years, the actual advantage of thinking in 4-5 year horizons versus quarterly horizons may be illusory, and the alpha may actually exist in short-term predictability rather than long-term positioning.
“who the hell knows what's going to happen in four or five years? Like, what's the point of even thinking about four or five years? Like, I don't know. Like, I'm not sure that's a good investment idea. Like, I think you should be really laser focused on the things you can predict, which tend to be the things that are relatively short-term in nature.”
US small-cap value returns have been severely dragged down by concentrated exposure to three underperforming sectors: (1) energy (which peaked in 2014-15 then collapsed and has been a 'wasteland' as shale fracking companies appear to be 'capital incineration machines'), (2) regional banks (which have not reached sufficient scale through M&A and faced a major crisis with First Republic), and (3) biotech (which is down ~60% from peaks and is 'annihilated'), making US small-cap value a poor equity exposure unlike international small-cap value which is more diversified.
“in the US um the small cap market um is really you know it's almost it's four markets okay it's the bank market the biotech market um uh the energy market and then everything else um uh and uh and that's sort of the way the and then in the international markets it's almost all everything else there just aren't Aren't any biotechs? There aren't really that many banks.”
Lockups and illiquidity in private markets may create the perception of investor discipline, but they actually prevent learning; investors who receive feedback only every 10 years experience only 3 feedback cycles in a 30-year career versus investors with monthly reporting who experience 360 cycles; more feedback enables better learning.
“the idea that lockups are are helpful to people, I don't I don't think seems seems off base. But I also think in terms of learning, it's a challenge because, you know, we learn. The more feedback we get, the more we learn. Uh, the less feedback we get, the less we learn. And so, if you're getting your feedback on a 10-year cycle, you know, how much are you going to learn? You might have three cycles in your working life.”
We are returning to a world where scale and market dominance do not guarantee high returns or sustainable competitive advantage; in the last few years of hyperscaler dominance, simply owning the top 5 largest S&P 500 companies produced excellent returns, but for prior decades these same large-cap leaders earned low returns on capital and struggled to grow.
“for the last 10 years you'd have done really well with that brilliant strategy. Okay. Um but for the previous decades horribly because generally the story was like these scaled monopoly players actually ended up earning like really low returns on capital and having a really hard time growing.”
The question of whether AI will be a centralizing force (creating permanent monopolies for firms with sufficient capex) or a decentralizing force (commoditizing AI infrastructure for smaller competitors) is fundamental to understanding whether the Magnificent 7 concentration persists or reverses.
“the question becomes is AI a centralizing or decentralizing force. Is it going to be the case that you know the three firms that have enough capex to be able to build out these models will have monopolies that will kind of endure forever or is it the case that these things become commoditized and it's in fact going to be you know the long tale the users the appliers of these technologies that get the boost.”
AI is the first technology innovation since fiber to be highly capital-intensive, with big tech companies having shifted from 1/3 the capital intensity of traditional US industrial companies to 3x the capital intensity, creating risks where depreciation schedules (5-year vs 1-year Nvidia server lives) materially impact valuations and could result in massive losses if capex intensity proves unsustainable.
“what's interesting about AI is that it's the first tech innovation that's capital intensive. Okay. Well, since fiber, okay, sorry, we've got the second. Um, uh, but we know how the fiber one ended. And I think that the AI one is a similar problem”
Vanguard retail investors behave as long-term investors and do not exhibit the flightiness or reactionary behavior that institutional investors do, contradicting the narrative that retail investors need protective structures (like lockups) more than institutions.
“if you look at the Vanguard you know investors they're actually remarkably uh long-term in in nature um and actually institutional investors I've found to be quite fickle um uh for a whole variety of reasons they get a new CIO every six years who changes the portfolio”
AI queries incur massive marginal energy costs, making AI a worse business model than advertising-based or subscription-based software (like Salesforce), because Salesforce subscriptions have zero marginal cost and don't require capex recovery, while AI providers must spend significant capex and recoup it through per-query revenue.
“I'd rather sell Salesforce subscriptions than sell AI because the Salesforce subscription you don't have to recoup any capex. Um u and so I think that's the big danger to these hyperscalers.”
Learning and feedback loops in investing are more effective with frequent feedback (monthly returns) than with infrequent feedback (annual or longer cycles), because investors with more cycles in their career (more learning events) develop better intuition about what actually predicts returns.
“The more feedback we get, the more we learn. Uh, the less feedback we get, the less we learn. And so, if you're getting your feedback on a 10-year cycle, you know, how much are you going to learn? You might have three cycles in your working life. Uh, how much have you learned? Whereas, if you're investing on like monthly numbers, right? Like you're going to get a lot of cycles.”
The M&A market has been slow, limiting strategic buyer exits for PE companies, partly because PE firms focus heavily on 'vertical SaaS' software (40-50% of deals), which large public tech companies have little incentive to integrate, as it doesn't fit their platform strategy.
“the next exit path is strategics. Um so you just sell to some bigger company that's already public. Um and then for whatever reason, the M&A market has been pretty slow. Um, and I couldn't tell you exactly why. I mean, I'd say one of the reasons it seems private equity is really focused a lot on sort of vertical software, a vertical SAS software, probably 40 50% of the deals and some something like that. Uh, and maybe there aren't a lot of public buyers who want to integrate like the auto dealer vertical SAS company or whatever and take that public.”
The wise saying 'what the wise man does at the beginning, the fool does at the end' applies to the Yale Model: early allocators to alternatives (PE, VC) captured real arbitrage opportunities, but later allocators (current institutions) are chasing exhausted returns by copying the original strategy at the wrong time.
“What's that that wonderful uh that wonderful quote which I'm going to butcher which was what the wise men does at first the fool does at the end or something.”
PE distributions have collapsed from a historical ~30% of NAV per year to approximately 10% of NAV currently, which is the lowest level since 2008, despite the fact that stock markets are reaching all-time highs and the economy is not in recession, indicating severe distress in PE exit channels.
“So, so typically private equity distributes about 30% of NAV a year. Um, but recently those distributions have dropped up down to about 10% of NAV. um which is the lowest since 2008.”
Institutional investors including pension funds (15% allocation), college endowments (30% allocation), and elite college endowments (40% allocation) are massively overallocated to private equity relative to its actual market size, and this overallocation is unjustified given that PE companies are the smallest, lowest-margin, lowest-quality businesses with the highest debt loads.
“I should have about 3.6% weight in private markets. And but if I have a 15% weight or a 30% weight or god forbid a 40% weight, I am massively massively overallocated to these 12,000 companies.”
PE outcome will likely be a 'money trap' scenario rather than a dramatic crash, where capital is unable to exit at acceptable prices and investors receive depressed returns over a prolonged period (possibly 20+ years), rather than experiencing a sharp mark-down and reversal.
“I so I'd say on the first I think I think it's a uh it's a money trap, right? the money's gone in, it's just not going to come out, right? It's not it's going to trickle out and that and people are not going to be happy with that.”
AI, crypto, and biotech have historically been grouped together as major platform shifts, but biotech is currently not recovering while AI and crypto boom, which is anomalous because all three should respond similarly if they are viewed as equivalent platform shifts.
“AI is booming, crypto booming, biotech not so much. And it's kind of weird because you historically people have kind of put those three things kind of in the same category. These are kind of the major platform shifts in technology.”
The claim that it's 'obvious to everyone' that too much money is going into private markets is not actually controversial when examined logically, and the only real uncertainty is timing (when the problem manifests) rather than whether there is a problem.
“I don't know, right? Like isn't it obvious to everyone that too much money is going into private markets, right? The only question is like when it's going to blow up or if it's, you know, like of course it's going to blow up at some point.”
Sentiment has shifted dramatically regarding private equity over the past 7-8 months; while PE was previously considered the 'apple of investors' eyes' with institutional buyers excitedly discussing new fund commitments and co-invest deals, endowments and large investors now describe themselves as 'overallocated to PE'—language that represents a fundamental reassessment of PE's appeal.
“7 8 months ago private equity is still the apple of their eyes. They were all excited about what new funds they were getting into what co-invest deals they were underwriting. It was all they cared about all they wanted to talk about to the extent that like you had buddies that worked at these places that were doing like private equity deals on the side like buying a soccer team in Ireland and like you know like it was just like everyone wanted to do it. Um and uh and now all of a sudden uh everyone seems to have lost interest and you talk to them and say, 'Oh, you know, I think our allocation to private equity maybe a little overallocated right now'”
The current era of AI, mobile, cloud, and internet technological advancement is comparable to historical periods of transformational innovation like Vienna's 18th century classical music, or England's early 19th century steam engine revolution, with figures like Elon Musk destined to be remembered with the historical significance of Thomas Edison or Benjamin Franklin.
“we're living in one of these rare times. We we really are. I I think you have to step back and say like this like Vienna for classical Vienna in the 18th century for classical music or or England in the early 19th century with the steam engine, right? That we're living in that for tech”
In a recession scenario similar to 2008, a reasonable expected bankruptcy rate for small, heavily-leveraged PE-backed companies would be approximately 25%, as these companies have minimal buffer (they are already unprofitable or thin-margin), and many are in 'PIK' (payment-in-kind) structures where debt accrues rather than being serviced in cash.
“What's a reasonable bankruptcy rate to expect in like a real recession for really small companies like that that have a lot of debt? My guess would be 25%. It's like everything in our logical mind says that this stuff should be more volatile. And yet when you look at the uh um volatility of the navs, the volatility”
Institutional investor sentiment toward PE has shifted dramatically in the past 7-8 months from euphoria (where PE was 'the apple of their eyes' and all conversation focused on new PE fund commitments and co-invest deals) to concern, with endowments and large investors now openly discussing being 'overallocated' to PE—a statement Rasmussen has never heard from them before.
“it's coincided with I'd say sort of the headlines that we've seen of Yale selling a big stake in their private equity of stakes uh of other big GPS starting to sell out of private equity. Uh and I would say the the mood has shifted um quite precipitously um uh in talking to endowments and large investors where you know 7 8 months ago private equity is still the apple of their eyes. They were all excited about what new funds they were getting into what co-invest deals they were underwriting.”
Small-cap value in the US worked well from COVID through the release of ChatGPT (approximately 2020-2022), but has not worked since, and appears to only work during early-stage cyclical recoveries when cyclical stocks outperform, suggesting it has become a tactical cyclical play rather than a persistent value premium.
“value in the US um worked um from COVID until the release of batch GPT and other than that has not worked. So I think the other way to sort of look at um small cap value in the US or at least how it's traded recently is that it's almost entirely a sort of cyclical play like a early stage recovery play.”
Harvard College and Yale are alma maters of both Dan Rasmussen and Kyle, providing relevant institutional context for discussing endowment performance and allocation strategies.
“Harvard's endowment for example our alma mater”
Rasmussen's family (including his father) are long-term Vanguard/Boglehead investors who follow a strategy of passive index investing with automatic contributions and deliberately avoiding checking account balances, exemplifying disciplined long-term retail investor behavior.
“my dad is a longtime Boglehead Vanguard investor. And so all of all of his kids were all you know, we all have our Vanguard accounts...our sort of one of our sort of family mantras, just never check your account. Like the the best thing is if you forget your login, you know, like set up some auto invest and forget the login, right?”