Speaker · Updated
Tobias Carlisle: latest market views
Acquirers Funds / The Acquirers Podcast
Summary
Tobias Carlisle is a deep value investor, founder of Acquirers Funds and Acquirers Multiple, host of The Acquirers Podcast, and author of 'Deep Value', 'Quantitative Value' and 'The Acquirer's Multiple'.
Chorus has 35 views from Tobias Carlisle across 6 episodes on The Acquirers Podcast since October 1, 2026. Their latest calls: bearish on Tesla and Micron Technology.
Where they stand
Their latest bullish or bearish call on each company.
- TeslaBearish ·
- Micron TechnologyBearish ·
What they talk about most
- US stock market outlook · 6
- AI: overall outlook · 3
- AI infrastructure & data centers · 2
- Market sentiment, positioning & volatility · 2
- US housing · 2
- US Treasuries & yields · 2
- AI & jobs · 1
- Enterprise AI adoption & AI software · 1
- Frontier AI labs & model race · 1
- Nuclear energy · 1
- Robotics & autonomous vehicles · 1
- Software & SaaS · 1
The latest views
Newest first. Every quote is checked against the episode's transcript.
AI infrastructure & data centers
AI compute firms are WeWork-like lessors that sublease capacity, and one struggled to list.
Carlisle compares AI compute firms to WeWork: they do not own their data-center locations, they lease them and sublease to smaller players. He says an Australian compute firm chasing a huge valuation could not get it done in Australia and now faces problems. He implies this model is fragile and that the valuations are stretched.
“They don't own the location. They just lease it, and then they sublease to smaller players... That's what these compute firms do.”at 3:29
The Acquirers Podcast: Why Buffett Would Be Short the “AI Horses” Right Now ·
AI will be a huge winner, but picking which AI companies win is very hard.
Carlisle says the AI improvement over the last twelve months is astonishing and will be a game changer. But he argues the question of which businesses profit from it is much harder than whether AI matters. His Buffett analogy: you can be sure the car will win without knowing which car company will win. He thinks picking the AI winners is a very tough ask.
“I think AI is gonna be a huge winner, but picking AI companies that are going to be the winners is a very tough ask.”at 3:49
The Acquirers Podcast: Why Buffett Would Be Short the “AI Horses” Right Now ·
We may already be in the AI singularity, with recursive self-improvement near.
Carlisle applies I.J. Good's and Vinge's definition of the singularity: a machine that makes a smarter machine, which recursively accelerates. He cites OpenAI and Anthropic saying they are doing this already or are very close, this year or imminently, so the machine will improve the model. He points to OpenAI solving long-standing math problems in unexpected ways and to progress in decoding the genome as evidence of accelerating breakthroughs. He hedges that the change may be absorbed like past technologies such as electricity.
“I think we're getting close to this point where we may already be in the singularity right now where these things are happening.”at 9:18
The Acquirers Podcast: Why Buffett Would Be Short the “AI Horses” Right Now ·
Market sentiment, positioning & volatility
A speculative AI mania is driving selling of non-AI stocks that are not actually threatened by AI.
Carlisle says there is a little bit of a mania going on. Other stocks are being sold off, not because AI will hurt them but because they have not gone up as much and are less interesting to speculators. Speculators fund purchases of AI stocks by shorting or not buying other parts of the market. He sees this as an opportunity for value and small and mid-cap investors.
“We've got this little bit of a mania going on, and these other stocks are being sold off.”at 17:45
The Acquirers Podcast: Why Buffett Would Be Short the “AI Horses” Right Now ·
US home prices must reset lower because mortgage activity is at a 25-year low.
Carlisle cites mortgage originations falling to the lowest level in at least 25 years, below the 2008-09 lows. He attributes it to high rates or high house prices. Mortgage rates are in the high sevens, and house payments are about twice what they were five years ago, but prices have not corrected to match. This creates a transaction freeze with knock-on effects, such as no household formation and fewer appliance purchases.
“House prices have to reset a little bit lower.”at 22:31
The Acquirers Podcast: Why Buffett Would Be Short the “AI Horses” Right Now ·
Mid and small caps trade near record-low relative valuations versus an AI-heavy index.
Carlisle tracks the S&P MidCap 400 (MDY), a profitable-company index, and the Russell 1000 stocks below the top 200. Both are at about their lowest relative levels in the data. Mid and small caps are a tiny share of the index because it is heavily weighted to AI megacaps, so the rest of the market is undervalued relative to the top. He says these companies are priced on very modest assumptions, and that it always takes a year or so, eighteen months, for value to work through.
“I've had a look at that MDY, which is the mid cap 400... They're both at about as low as they've been in the data, on a relative basis.”at 27:53
The Acquirers Podcast: Why Buffett Would Be Short the “AI Horses” Right Now ·
Enterprise AI adoption & AI software
AI-driven backtesting data-mines results that fail out of sample, so findings rarely persist.
Carlisle gave Claude his backtest data and software. It ran 916,000 backtests across 1,217 parameter sets in one afternoon, where he would normally run dozens. He describes this as a data mine. He follows his own rule of optimising on the first half of the data and testing on the second, and finds it very hard to find anything that persists from one set to the next. What optimises in the first half usually fails in the second. He argues that the AI's speed of search makes overfitting easier, not the discovery of real edges.
“And it's very hard to find anything that persists from one set to the next.”at 4:05
The 10-3 yield curve inversion recession signal has stopped working, and un-inversion has not helped.
Carlisle says the 10-3 inversion had a strong track record, with a near-perfect hit rate through 2022 to 2024. It then failed to call the downturn that followed. He says the curve un-inverted about a year before the conversation, with a sideways market since then. He concludes that un-inversion has not behaved like a recession signal, and that stretching the definition to keep it alive is getting hard.
“But the uninversion doesn't seem to work.”at 10:55
Valuation is not a useful timing tool, though expensive markets imply lower future returns and more volatility.
Carlisle says his backtesting across CAPE, Tobin's Q and Buffett's market-cap-to-GNP ratio all point to the same answer: the market is expensive relative to its trend. He argues that an expensive market implies lower returns and some volatility ahead. He is equally clear that valuation does not work for timing. He also notes CAPE has calculation problems when earnings have run far ahead, but that the rough answer holds. His reading is that the market is expensive, but valuation will not tell you when to act.
“Valuation is not a useful timing tool at all. Valuation doesn't work as a timing tool... Is not a timing tool.”at 11:33
The 60/40 portfolio's bond hedge has worked only about 20 years and failed in 2022.
Carlisle explains the 60/40 logic. Bonds rally when equities fall, so rebalancing buys more stock at the bottom. That only works when stocks and bonds are negatively correlated. He says that held for a short window, about 20 years, while most of the time they have been positively correlated. In 2022 bonds sold off alongside stocks, so the hedge failed and the portfolio did not recover as expected.
“6040 has only worked for twenty years. There's a short period of time where bonds and equities were uncorrelated. Most of the time, they've been pretty correlated.”at 15:30
Market sentiment, positioning & volatility
Moving-average trend rules whipsaw, have no good parameter, and are an expensive diversifier at best.
Carlisle tested moving averages, including the 50-day, 200-day and crossovers. He found no choice of average that solves the problem. A rule can ride a market to its peak and then exit at the very top. Markets often fall back to their moving average before rallying, which causes whipsaws and overtrading that get worse at higher checking frequency. He calls moving averages trend strategies that work sometimes and cost money. They might earn a place as one uncorrelated stream, but they do not solve the problem. He also says CTA track records are flattered by survivorship bias, since failed funds drop out of the data.
“And so moving averages are trend strategies. ... It works sometimes and doesn't work other times, and it's expensive.”at 20:11
AI is already solving math problems and decoding the genome, which will be a big boost to medicine and aging.
Carlisle cites present-day evidence that AI is solving math problems and decoding the human genome. He argues this will be incredible for medicine and, perhaps, for aging. He ties the math breakthroughs to models from Anthropic or OpenAI, and notes mathematicians thought the solutions were 'alien' connections a human would not have made. He hedges on the aging benefit with 'maybe'.
“We're already seeing, like, it's solving math problems. It's decoding the human genome. So that's gonna be incredible for medicine and for aging maybe.”at 36:12
OpenAI and Anthropic are already building AI that builds smarter AI, so we're in the singularity now.
Carlisle argues the singularity is defined by machines that make smarter machines. He says OpenAI and Anthropic are doing this now or will do so this year, so 'we're living in the singularity right now.' He frames this as a present-tense fact, with the timing set by 'this year'.
“OpenAI and Anthropic are making the machines that make the machines smarter. They're either doing that now or that's... They're gonna be doing that this year.”at 41:18
TeslaBearish
Tesla's self-driving is still about ten years away despite Musk's earlier timelines.
Carlisle notes Musk has said for five to ten years that autonomy was near. He concludes that, from the outside, Tesla is still roughly ten years away from self-driving. He contrasts this with Waymo, which he asks about and treats as further along.
“Musk saying it's five years ago, ten years ago. Clearly, it's still ten ish years away for Tesla.”at 42:19
Robotics & autonomous vehicles
Humanoid robots are getting close, though they are not in homes yet and cost is unclear.
Carlisle points to robot Olympics and a robot fighting league as evidence humanoid robots are advancing quickly. He notes they are not yet in the home and that the cost of one is unknown, but he judges them 'close'. This comes from observed demonstrations rather than hard data.
“It's getting close... they're not in the home yet, and who knows how much one of these things actually cost, but they're close.”at 43:56
AI infrastructure & data centers
AI bottlenecks like power, compute and data center space are solvable and just take time.
Carlisle lists the possible constraints on AI as power, computing power and data center space. He argues each is a solvable problem that is not especially hard to fix, though it takes some time. He treats these bottlenecks as temporary rather than binding.
“you gotta think that all of those problems are solvable problems that they're not that difficult to solve. They just take a little bit of time.”at 46:14
AI can rebuild existing software from its binary, so consumers will stop paying for it.
Carlisle describes AI decompiling a binary into source code and rebuilding a working version of Microsoft Word from what it can see. If AI can rebuild any software for free, he asks what people will pay for. He concludes 'all software is cracked' and that the value goes to consumers as surplus rather than to software vendors.
“Or you can just put Word, Microsoft Word, and it'll give you a functioning version of Word built backwards from what it can see. But I've already got Word.”at 47:51
Robots plus superintelligent AI could leave humans with little work to do.
Carlisle reasons that a robot could do all physical labor while a superintelligent machine does the thinking work, with no mistakes and around-the-clock availability. He asks what humans would then do, and his only answer is 'make more humans'. He treats the outcome as a speculative question rather than a confident forecast.
“If you've got a robot that can do all the physical labor and you've got this ultra intelligent machine that it's smarter than you are... What's the human day? What are we doing?”at 48:23
Nuclear power never became too cheap to meter because nuclear is too expensive to build.
Carlisle recalls a 1950s prediction that nuclear would make energy too cheap to meter, and says it has not happened. He offers his own explanation that nuclear is too expensive to build, though he says he has not checked this. The view is a tentative explanation rather than a researched conclusion.
“because we haven't got nuclear. It's too expensive to build nuclear.”at 49:31
Another market crash is highly likely, regardless of whether valuations or AI are the cause.
Carlisle cites history showing a crash roughly every seven years, which makes another crash highly likely. He says the crash does not need to be explained by overvaluation or AI, since markets simply tend to crash. The crash risk is therefore a structural feature of markets rather than a call about current AI valuations.
“There's a crash about once every seven years. We're highly likely to get another crash. It's got nothing to do with the market being overvalued or AI.”at 53:06
Rising long-term rates hurt small, micro and cyclical value stocks, which have more debt and shorter maturities.
Long-run rates keep rising, and this hits small, micro and value cyclical companies. Their debt is not as well termed out and they carry more of it. Their businesses are more cyclical, so they feel the pain first and fall fastest. They also recover first and fastest, which makes them the market's bellwethers.
“long run rates seem just keep... Seem to be just continually jacking up, and that increase impacts the businesses of small and micro and value cyclical stocks because they've got... Their debt's not as well termed out.”at 3:02
The Acquirers Podcast: MGM and VICI: Finding Value in the Las Vegas Selloff | Value Options Podcast ·
Oil near $100 adds a cost to most businesses, weighing on small value cyclicals.
Energy is a cost for most businesses that move goods, and it shows up as an additional cost. Oil is back around $100, which is close enough to that level to matter. This has made small value cyclicals a tougher area this year.
“The other thing is energy, is just another cost for most businesses moving stuff around, and that shows up as a... Just an additional cost. And energy oils, it's back to a $100.”at 3:38
The Acquirers Podcast: MGM and VICI: Finding Value in the Las Vegas Selloff | Value Options Podcast ·
Market gains are concentrated in about ten AI-capex names, so breadth is unhealthy.
Outside the largest ten companies, which are mostly AI or AI capex beneficiaries such as hyperscalers and semiconductor firms, most stocks are underperforming. Anyone holding the S&P 500 is underperforming those names. Everything else is lagging a handful of stocks, which is not a healthy market. He says this may be justified, but he thinks it is an unhealthy setup.
“that's anything that's not the biggest 10 companies in the market... Sort of AI or AI CapEx beneficiaries... If you're holding the S and P 500, you're underperforming those names. ... not a super healthy market.”at 4:04
The Acquirers Podcast: MGM and VICI: Finding Value in the Las Vegas Selloff | Value Options Podcast ·
Highly profitable stocks trade at 11x book, well above the 2000 peak of 7x, so they look stretched.
Profitability has been one of the best predictors of returns. The profitability factor peaked at about 7x book value in 2000 and now sits at about 11x book. Book value is an imperfect measure, especially for capital-intensive firms. Still, Tobias says that puts the group well past the 2000 peak. Getting it right requires being correct on the business and the forward growth, and analysts have been consistently too optimistic.
“11 times book value is is pretty stretched. You gotta be right on the business. You gotta be right on the forward growth, and analysts seem to be very optimistic about that, but I think they've been pretty consistently wrong.”at 5:29
The Acquirers Podcast: MGM and VICI: Finding Value in the Las Vegas Selloff | Value Options Podcast ·
Micron TechnologyBearish
Micron's low P/E looks misleading because its cyclical earnings need normalizing before it can be called cheap.
Micron has traditionally been very cyclical and often appears on deep value screens because its earnings are high relative to a low market valuation. Once those cyclical earnings are normalized, the stock may not be cheap. Tobias does not think the nature of the business has changed much. The cycle may just run longer, although he admits he does not know whether demand is now secular.
“You gotta normalize those earnings... Traditionally, they've been very cyclical... I don't think that nature's changed that much.”at 8:33
The Acquirers Podcast: MGM and VICI: Finding Value in the Las Vegas Selloff | Value Options Podcast ·
AI firms are ahead of themselves short term, as dot-com firms were, before real adoption takes a decade.
The dot-com era was clearly game-changing, but the market got ahead of itself and then collapsed. The internet then took ten or fifteen years to become properly integrated into business. Good businesses emerged from the dot-com wreckage over the last five years or so. Tobias thinks the same will happen with AI companies, which are a little ahead of themselves in the short term.
“the analogy is the early two thousands... where the .com was clearly game changing for everybody... we did get a little bit ahead of ourselves... it really took ten or fifteen years... I think they're a little bit ahead of themselves”at 12:01
The Acquirers Podcast: MGM and VICI: Finding Value in the Las Vegas Selloff | Value Options Podcast ·
Chinese AI, led by DeepSeek, was only a little behind the American frontier.
On a trip to China about eighteen months ago, VCs there said American AI was ahead. OpenAI's American version was ahead of everything else, but DeepSeek, the free Chinese version, was just behind. Tobias notes that this is old technology, but says the field was leapfrogging at the time.
“The American version of OpenAI was ahead of everything else. But DeepSeek, which is the free Chinese version, was sort of just behind it.”at 21:53
The Acquirers Podcast: MGM and VICI: Finding Value in the Las Vegas Selloff | Value Options Podcast ·
Most users will settle for cheaper older AI models, so AI makers will struggle to earn much.
Most people may only need an older, cheaper model that delivers 90-95% of the performance. Only a handful of users will need bleeding-edge models and pay for them. That is great for consumers but hard for AI businesses to earn much money from. Tobias compares the sector to hard drive makers leapfrogging each other, which makes it uninvestable unless you know exactly what you are doing.
“Can they do it with a cheaper version that's just like a a generation or two behind that's, like, gives you 95 or 90% of the performance? ... Great for a consumer, hard for a business to make a whole lot of money with that.”at 22:12
The Acquirers Podcast: MGM and VICI: Finding Value in the Las Vegas Selloff | Value Options Podcast ·
Market cycles now turn faster, so today's dislocations should normalize within about eighteen months.
Tobias thinks cycles are turning faster than ever. Eighteen months is a long time in today's market. He expects that many of the current distortions will have reverted to normal by then. Markets swing faster to the extremes, but they also swing faster back to the median.
“Think that the cycles are turning faster than they have ever before... Eighteen months is, like, a really long time in the market now.”at 29:34
The Acquirers Podcast: MGM and VICI: Finding Value in the Las Vegas Selloff | Value Options Podcast ·
US housing is still short of supply, with high prices but very low transaction volumes.
Tobias cites two charts. One shows annual new home building below what it should have been since 2016, so the US is still short of housing. The other shows many more sellers than buyers, and housing transactions back at GFC lows. Mortgage rates are back near long-run levels, so prices are high but volumes are low. He says this means the data should be taken with a grain of salt.
“Nothing's going through with long run mortgage rates back to, like, basically, close to the long run. So prices are high, but volumes are low.”at 40:40
The Acquirers Podcast: Korea’s Hidden Value: Activism, AI & Golfzon | Ryan Albert ·
5 older views from Tobias Carlisle are on the episode pages, and all of them are a question away in your AI with Chorus.
Shows
- The Acquirers Podcast · 6 episodes
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