The $2 Trillion Question | Tobias Carlisle on SpaceX, the AI Buildout, and the Rotation No One Sees
Tobias Carlisle argues that collectively, market valuation metrics are at their most overvalued point in the entire dataset — and the smart bet is now small and micro value stocks, not AI mega-caps.
Excess Returns
The $2 Trillion Question | Tobias Carlisle on SpaceX, the AI Buildout, and the Rotation No One Sees
Tobias Carlisle argues that collectively, market valuation metrics are at their most overvalued point in the entire dataset — and the smart bet is now small and micro value stocks, not AI mega-caps.
TL;DR
Tobias Carlisle, founder of Acquirers Funds, joins Excess Returns to make the case for a major rotation into small-cap and deep value stocks after a decade-long large-cap growth cycle. Market valuations are at their most stretched on record [1] — Tobias Carlisle "Most overvalued in dataset: Every major market valuation metric tracked by Advisor Perspectives is simultaneously at its most overvalued le…" 04:24 , AI capex may ultimately benefit consumers rather than investors [2] — Tobias Carlisle "The entire AI infrastructure buildout may end up enriching users rather than investors. Competition among AI providers makes commoditizatio…" 15:30 , and mega-IPOs like SpaceX signal potential cycle tops [3] — Tobias Carlisle "Three signals are converging that may mark the top of the AI boom: the SpaceX IPO is forcing the S&P 500 to absorb a massive new entrant, O…" 30:00 . The single most actionable takeaway: if you believe in mean reversion, the smart bet right now is small and micro value.
Tobias Carlisle joins Excess Returns to discuss why today's market may be setting up a major opportunity in value stocks, small caps and micro caps. Topics include stretched market valuations, AI capex, SpaceX and other massive IPOs, the risk of speculative growth assumptions, and how Tobias builds systematic deep value portfolios in ZIG and DEEP.
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Tobias Carlisle teases his core thesis — AI value may go to consumers, not creators — then is welcomed back to Excess Returns. Hosts introduce his ZIG and DEEP ETFs.
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Carlisle reviews 6-7 valuation metrics all at historic extremes. Overvaluation signals lower forward returns, not an immediate exit — the real opportunity is in cheap pockets like small and micro value. [1] — Tobias Carlisle "Most overvalued in dataset: Every major market valuation metric tracked by Advisor Perspectives is simultaneously at its most overvalued le…" 04:24
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Small caps have quietly outperformed Mag 7 over the last 12 months. Carlisle tracks equal-weight vs. cap-weight indexes and the S&P 100 vs. 500 as barometers of a leadership rotation. [1] — Tobias Carlisle "Small caps outperformed Mag 7 in 2025: Small caps have outperformed the Magnificent 7 over the last 12 months and year-to-date, a fact Carl…" 09:17
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Comparing AI to fiber optic and railway buildouts, Carlisle notes AI hardware lasts only 5-7 years vs. 25+ years for prior infrastructure. Gartner hype cycle dynamics are in play. [1] — Tobias Carlisle "AI hardware useful only 5–7 years: Unlike fiber optic cable or railways which last 25+ years, AI computing hardware depreciates and becomes…" 16:12
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Hosts debate whether AI profits accrue to companies or consumers. Carlisle says competition will commoditize models, eventually making AI just another cost of doing business for every company.
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Carlisle argues AI capex is more discretionary than it looks, citing Google raising $80B and Meta's metaverse pivot. The stock market — not consumers — is demanding compute investment. [1] — Tobias Carlisle "Even Google's raising money now. Like that just seems bonkers to me that Google would be out there raising $80 billion." 25:49
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Three of the largest IPOs ever are coming at once. Carlisle wonders if SpaceX marks the cycle top, noting a sharp small-value vs. large-growth swing on the day of its debut. [1] — Tobias Carlisle "Three signals are converging that may mark the top of the AI boom: the SpaceX IPO is forcing the S&P 500 to absorb a massive new entrant, O…" 30:00
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Mauboussin's base rate paper showed OpenAI's growth projections would be unprecedented; Anthropic's actual growth then obliterated those projections. Time Magazine's AI cover may signal a market top. [1] — Jack "Michael Mauboussin's base rate framework showed that OpenAI's growth projections would be unprecedented in corporate history. Then Anthropi…" 33:45
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Carlisle argues that large-cap tech companies keep breaking historical growth base rates, but speculation is rife. Individually and collectively, S&P 500 names are expensive.
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Kai Wu's research shows value has worked consistently in non-disrupted industries throughout the tech boom. Carlisle explains the earnings recession in small/micro from 2022-2025 and why it's bottoming. [1] — Tobias Carlisle "Small/micro earnings recession 2022–2025: US small, micro, and mid-cap companies experienced an earnings recession from 2022 through late 2…" 41:10
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Energy is at 3% of market cap vs. 12% historically. Carlisle sees energy as a contrarian play. The end of the war may re-ignite the small/international/value rotation that paused earlier this year.
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Energy is at 3% of market cap vs. 12% historically. Carlisle sees energy as a contrarian play. The end of the war may re-ignite the small/international/value rotation that paused earlier this year.
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Carlisle walks through his systematic process: financial statements first, Acquirer's Multiple for current price, 5-10 year lookback and projection, then equal weight across a range of quality tiers. [1] — Tobias Carlisle "The process is grounded entirely in financial statements: look at what a company earns on assets, its reinvestment rate, and its payout pol…" 51:00
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Carlisle walks through his systematic process: financial statements first, Acquirer's Multiple for current price, 5-10 year lookback and projection, then equal weight across a range of quality tiers. [1] — Tobias Carlisle "The process is grounded entirely in financial statements: look at what a company earns on assets, its reinvestment rate, and its payout pol…" 51:00
- Acquirer's Multiple
- A valuation metric developed by Tobias Carlisle that divides enterprise value (including debt, cash, and minority interests) by operating earnings, designed to identify undervalued takeover targets.
- Shiller PE (CAPE)
- Cyclically Adjusted Price-to-Earnings ratio: the stock market's price divided by 10-year average inflation-adjusted earnings, used to assess whether the overall market is over- or undervalued.
- Tobin's Q
- A valuation metric comparing the market value of a company or the entire market to the replacement cost of its assets; a ratio above 1 suggests overvaluation.
- Equal-weight index (RSP)
- A version of an index like the S&P 500 where every constituent stock is given the same portfolio weighting, regardless of its market capitalization; outperforms market-cap-weight when smaller stocks lead.
- Mean reversion
- The statistical tendency for extreme values — like high stock valuations or growth rates — to return toward their long-term historical average over time.
- Hyperscalers
- Very large technology companies (e.g. Google, Microsoft, Amazon, Meta) that operate massive cloud and computing infrastructure at global scale.
- CapEx (Capital Expenditure)
- Funds spent by a company to acquire, upgrade, or maintain physical assets like data centers, servers, or infrastructure; in the AI context, refers to the massive spending on computing hardware.
- Gartner Hype Cycle
- A framework by research firm Gartner that maps the maturity and adoption of technologies through phases: innovation trigger, peak of inflated expectations, trough of disillusionment, slope of enlightenment, and plateau of productivity.
- S-curve
- The characteristic growth pattern of new technologies or markets: slow initial adoption, rapid growth in the middle, then saturation as the market matures.
- DCF (Discounted Cash Flow)
- A valuation method that estimates the present value of a company by projecting its future cash flows and discounting them back to today at an appropriate rate.
- OEF
- The iShares S&P 100 ETF, which tracks the 100 largest US stocks; Carlisle uses the OEF/SPY ratio as a barometer for whether large- or mid-cap stocks are leading the market.
- GFC
- Global Financial Crisis; refers to the 2007–2009 financial crisis centered on US mortgage markets that caused a severe global recession and a roughly 57% drawdown in the S&P 500.
- Special purpose vehicle (SPV)
- A separate legal entity created by a company to isolate financial risk or carry debt off its main balance sheet, sometimes used by tech companies to fund large infrastructure projects.
- Foie gras (forced feeding)
- Carlisle uses this metaphor to describe how SpaceX will be force-fed into S&P 500 index funds, requiring passive funds to buy shares simply because of index inclusion rules.
- Timing luck
- The impact that the arbitrary choice of a rebalancing date has on returns; a concept popularized by Corey Hoffstein, describing how a portfolio rebalanced in March 2009 would have dramatically outperformed one rebalanced in September 2009.
- Terminal value
- In a DCF model, the estimated value of a company beyond the explicit forecast period, often representing the majority of total calculated value for high-growth companies.
- Hedonic treadmill
- The psychological tendency for people to return to a baseline level of satisfaction after positive or negative events; Carlisle uses it to describe how society quickly normalizes and stops being impressed by new technologies.
- Bifurcated market
- A market where two distinct groups of securities — e.g. large-cap growth and small-cap value — are moving in opposite directions, creating extreme performance divergence between them.
- Base rates
- Statistical reference points from historical data used to calibrate expectations; in investing, base rates describe how often companies of a certain size or type have achieved specific growth milestones.
- Parabolic
- Describing a price or earnings chart that accelerates upward at an increasing rate, resembling the curve of a parabola; often associated with unsustainable speculative moves.
Chapter 1 · 00:00
Why AI value may accrue to consumers
Tobias Carlisle teases his core thesis — AI value may go to consumers, not creators — then is welcomed back to Excess Returns. Hosts introduce his ZIG and DEEP ETFs.
Chapter 2 · 04:00
What extreme market valuations say about future returns
Carlisle reviews 6-7 valuation metrics all at historic extremes. Overvaluation signals lower forward returns, not an immediate exit — the real opportunity is in cheap pockets like small and micro value. [1] — Tobias Carlisle "Most overvalued in dataset: Every major market valuation metric tracked by Advisor Perspectives is simultaneously at its most overvalued le…" 04:24
Claims made here
All 6-7 major market valuation metrics tracked by Advisor Perspectives are simultaneously at their most overvalued level in the entire historical dataset.
Every major market valuation metric is simultaneously at its most overvalued in the historical dataset — but that doesn't mean you should exit the market. Overvaluation signals lower forward returns and volatility, not an immediate crash. The real opportunity is in the parts of the market that haven't been bid up.
Every major market valuation metric tracked by Advisor Perspectives is simultaneously at its most overvalued level in the entire historical dataset.
Chapter 3 · 08:22
Small caps, equal weight and the Mag Seven reversal
Small caps have quietly outperformed Mag 7 over the last 12 months. Carlisle tracks equal-weight vs. cap-weight indexes and the S&P 100 vs. 500 as barometers of a leadership rotation. [1] — Tobias Carlisle "Small caps outperformed Mag 7 in 2025: Small caps have outperformed the Magnificent 7 over the last 12 months and year-to-date, a fact Carl…" 09:17
Claims made here
Small caps have outperformed the Magnificent 7 both year-to-date and over the last 12 months.
The equal-weight S&P 500 (RSP) has outperformed the market-cap-weight S&P 500 for most of the period since at least 1990, except during notable large-cap growth booms.
The dot-com large-cap growth dominance period ran from approximately 2000 to 2015, followed by a value market, then another large-cap growth market from 2015 to the present.
The value-growth valuation spread is currently in the 95th percentile, meaning it has only been wider on 5% of historical occasions.
Small caps have outperformed the Magnificent 7 over both the last 12 months and year-to-date — a narrative violation almost nobody is talking about. Equal-weight indexes, small caps, and value are all signaling the same thing: a market leadership shift away from large-cap growth may already be in progress.
Small caps have outperformed the Magnificent 7 over the last 12 months and year-to-date, a fact Carlisle calls a narrative violation most investors don't know.
The current large-cap growth market dominance has persisted for over 10 years since 2015, preceding a potential extended value market cycle.
The spread between the most expensive and most undervalued stocks is in the 95th percentile, meaning it has only been wider on 5% of historical occasions.
Chapter 4 · 14:15
AI capex and lessons from past technology booms
Comparing AI to fiber optic and railway buildouts, Carlisle notes AI hardware lasts only 5-7 years vs. 25+ years for prior infrastructure. Gartner hype cycle dynamics are in play. [1] — Tobias Carlisle "AI hardware useful only 5–7 years: Unlike fiber optic cable or railways which last 25+ years, AI computing hardware depreciates and becomes…" 16:12
Claims made here
AI computing hardware has a useful life of approximately 5-7 years, compared to 25+ years for fiber optic cables and railways.
The entire AI infrastructure buildout may end up enriching users rather than investors. Competition among AI providers makes commoditization inevitable — most people will use cheaper, older models rather than pay for the cutting edge. The value creation is real, but investors may not capture it.
Fiber optic cables and railways last 25+ years. AI data center hardware becomes obsolete in 5 to 7 years. This changes the economics of the buildout entirely — the returns need to come faster, and the depreciation risk is far higher than in prior technology booms.
Unlike fiber optic cable or railways which last 25+ years, AI computing hardware depreciates and becomes obsolete in roughly 5 to 7 years.
Chapter 5 · 19:47
Who gets the profits from AI?
Hosts debate whether AI profits accrue to companies or consumers. Carlisle says competition will commoditize models, eventually making AI just another cost of doing business for every company.
Chapter 6 · 23:00
Cash flow, debt and the AI spending race
Carlisle argues AI capex is more discretionary than it looks, citing Google raising $80B and Meta's metaverse pivot. The stock market — not consumers — is demanding compute investment. [1] — Tobias Carlisle "Even Google's raising money now. Like that just seems bonkers to me that Google would be out there raising $80 billion." 25:49
Claims made here
Google is raising $80 billion in external capital to fund AI infrastructure, despite historically being one of the most cash-rich companies.
Meta spent approximately $12 billion on metaverse development before reversing course and abandoning the initiative.
The Mag 7's AI capital expenditure is more discretionary than it looks. Just like Zuckerberg pivoted away from the metaverse after spending $12 billion, these companies could pull back if investor sentiment shifts. The real demand signal is coming from stock markets, not from actual consumer need.
Even Google, a historically cash-rich company, is now raising $80 billion in capital to fund AI infrastructure, a shift Carlisle called 'bonkers.'
Meta spent approximately $12 billion on the metaverse before reversing course — Carlisle cites this as evidence that current AI CapEx is more discretionary than it appears.
Chapter 7 · 28:06
SpaceX, giant IPOs and market supply
Three of the largest IPOs ever are coming at once. Carlisle wonders if SpaceX marks the cycle top, noting a sharp small-value vs. large-growth swing on the day of its debut. [1] — Tobias Carlisle "Three signals are converging that may mark the top of the AI boom: the SpaceX IPO is forcing the S&P 500 to absorb a massive new entrant, O…" 30:00
Claims made here
On the day after SpaceX launched on the market, large-cap growth rallied approximately 3% while small value dropped approximately 2%, a 5% swing that erased half of small value's prior outperformance.
Three signals are converging that may mark the top of the AI boom: the SpaceX IPO is forcing the S&P 500 to absorb a massive new entrant, OpenAI and Anthropic seeking $80 billion are pulling liquidity from the market, and Time Magazine just put AI on the cover — the same indicator that called 'death of equities' in 1979.
Chapter 8 · 31:00
OpenAI, Anthropic and Mauboussin's base rates
Mauboussin's base rate paper showed OpenAI's growth projections would be unprecedented; Anthropic's actual growth then obliterated those projections. Time Magazine's AI cover may signal a market top. [1] — Jack "Michael Mauboussin's base rate framework showed that OpenAI's growth projections would be unprecedented in corporate history. Then Anthropi…" 33:45
Claims made here
Michael Mauboussin published a paper showing OpenAI's projected growth would be unprecedented in corporate history, and Anthropic's actual growth subsequently obliterated even those projections.
Amazon achieved approximately 80% revenue growth in a year when it was already generating around $100 billion in revenue during the pandemic.
SpaceX is valued at over $2 trillion, implying a price-to-sales multiple of 150 to 200 times, which requires unprecedented growth assumptions.
Michael Mauboussin's base rate framework showed that OpenAI's growth projections would be unprecedented in corporate history. Then Anthropic came along and obliterated those already-unprecedented projections. The tech giants keep breaking the models used to value them.
Chapter 9 · 35:17
Is buying the S&P 500 more speculative than investors realize?
Carlisle argues that large-cap tech companies keep breaking historical growth base rates, but speculation is rife. Individually and collectively, S&P 500 names are expensive.
Claims made here
Investor over-excitement during technology booms has occurred at least six identifiable times in history — the telegraph, railway, electronics, dot-com, and AI booms among them.
The pattern is the same every time: telegraph, railways, electronics, dot-com, and now AI. Investors get too excited, bid up picks-and-shovels sellers alongside the technology itself, and eventually everything returns to earth. The human behavioral response has never changed, even as the technology itself has transformed.
Carlisle traced the same investor over-excitement pattern through the telegraph boom, electronics boom, railway boom, dot-com boom, and now the AI boom — each ending with a crash.
Chapter 10 · 37:57
Value investing during disruptive technology cycles
Kai Wu's research shows value has worked consistently in non-disrupted industries throughout the tech boom. Carlisle explains the earnings recession in small/micro from 2022-2025 and why it's bottoming. [1] — Tobias Carlisle "Small/micro earnings recession 2022–2025: US small, micro, and mid-cap companies experienced an earnings recession from 2022 through late 2…" 41:10
Value investing has worked consistently in non-disrupted industries throughout the current tech boom — the underperformance is concentrated in disrupted sectors. The challenge is identifying disrupted industries in advance. For non-disrupted businesses trading at discounts, value metrics have been remarkably reliable.
US small, micro, and mid-cap companies experienced an earnings recession from 2022 through late 2024/early 2025, with earnings falling or trading sideways while large-cap earnings rose.
Energy stocks represent just 3% of market cap versus a 12% historical average. AI data centers will consume energy voraciously, and Carlisle thinks nuclear is the only long-term solution — though natural gas bridges the gap. Oil equities are doing the opposite of what everyone expects right now.
Chapter 11 · 44:11
War, energy prices and the broadening trade
Energy is at 3% of market cap vs. 12% historically. Carlisle sees energy as a contrarian play. The end of the war may re-ignite the small/international/value rotation that paused earlier this year.
Claims made here
Energy stocks currently represent approximately 3% of stock market capitalization versus a historical average of approximately 12%.
Energy currently represents only about 3% of stock market capitalization, well below its historical average of approximately 12%.
Chapter 13 · 47:50
How Tobias builds the ZIG and DEEP portfolios
Carlisle walks through his systematic process: financial statements first, Acquirer's Multiple for current price, 5-10 year lookback and projection, then equal weight across a range of quality tiers. [1] — Tobias Carlisle "The process is grounded entirely in financial statements: look at what a company earns on assets, its reinvestment rate, and its payout pol…" 51:00
Claims made here
China's top AI models were considered the best value option globally as of approximately one year prior to the recording, while US models led on raw capability.
Semiconductors as a group were trading at 55 times earnings, implying 75% of the sector's value is in terminal value beyond 10 years and requiring 16.5% annual growth for a decade.
Semiconductors as a group were trading at 55 times earnings, implying that 75% of the sector's value is in terminal value 10+ years out, requiring 16.5% annual growth for a decade.
The process is grounded entirely in financial statements: look at what a company earns on assets, its reinvestment rate, and its payout policy over 5-10 years. Combine with the Acquirer's Multiple (which includes balance sheet items) to find the best risk-adjusted opportunities. Equal weight everything because you can't know in advance which names will deliver.
Chapter 14 · 54:17
ETF rebalancing, timing luck and systematic value investing
Carlisle walks through his systematic process: financial statements first, Acquirer's Multiple for current price, 5-10 year lookback and projection, then equal weight across a range of quality tiers. [1] — Tobias Carlisle "The process is grounded entirely in financial statements: look at what a company earns on assets, its reinvestment rate, and its payout pol…" 51:00
Rebalancing monthly adds almost no extra return over quarterly, but annual rebalancing risks catastrophic timing luck — like having a September rebalance date in March 2009. Quarterly also captures a little momentum before cutting winners. It is the practical sweet spot for systematic value ETFs.
The Acquirer Fund ETF (ZIG) rebalances quarterly and Carlisle has the discretion to rebalance more frequently as an active fund, but chooses not to.
Rebalancing monthly adds little return versus quarterly, while annual rebalancing risks missing major bottoms like March 2009 by several months.
No indexed bits in this chapter.
Show stoppers
The entire AI infrastructure buildout may end up enriching users rather than investors. Competition among AI providers makes commoditization inevitable — most people will use cheaper, older models rather than pay for the cutting edge. The value creation is real, but investors may not capture it.
Three signals are converging that may mark the top of the AI boom: the SpaceX IPO is forcing the S&P 500 to absorb a massive new entrant, OpenAI and Anthropic seeking $80 billion are pulling liquidity from the market, and Time Magazine just put AI on the cover — the same indicator that called 'death of equities' in 1979.
Snapshots ()
Key Quotes ()
This episode
Cast
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Referenced for his base rate paper analyzing OpenAI's growth projections, which showed the projections would be unprecedented in corporate history.
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Mentioned as the researcher who popularized the concept of 'timing luck' in portfolio rebalancing, which Carlisle uses to justify quarterly over annual rebalancing.
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Discussed as the largest upcoming IPO in market history at a $2 trillion-plus valuation, with hosts and Carlisle debating whether it signals a market cycle top.
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The investment firm founded by Tobias Carlisle that operates the ZIG and DEEP value ETFs, discussed as the vehicle for his systematic deep value strategy.
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Discussed in the context of its planned IPO, Michael Mauboussin's base rate analysis of its growth projections, and its role as a driver of AI market speculation.
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Mentioned as seeking an $80 billion IPO valuation and discussed because its actual growth rates obliterated Mauboussin's already-unprecedented base rate projections for OpenAI.
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Used as an example of extreme large-cap valuation, cited at over 30x trailing earnings and 10x revenues despite potentially lower growth prospects than a decade ago.
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Cited as a historically cash-rich company now raising $80 billion in external capital for AI, which Carlisle called 'bonkers' and a sign of excessive discretionary AI spending.
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Discussed as an example of a company taking on debt for AI capex and previously having wasted $12 billion on the metaverse, suggesting AI spending could also be reversed.
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Discussed as the paradigmatic example of a company that broke historical base rate growth models, posting ~80% growth at $100 billion scale during the pandemic.
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Cited as an example of a non-tech company with a seemingly unjustifiable valuation multiple, trading at 30+ times PE despite being a traditional retailer.
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Mentioned alongside Walmart as a non-tech large company with a valuation multiple that Carlisle finds difficult to justify given its business model.
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Used as an example of a holding in Carlisle's portfolio — a busted growth story that screens cheap on financial metrics even though its consumer narrative has weakened.
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Mentioned as one of the Mag 7 hyperscalers that has broken historical base rate growth models and is at the center of the AI arms race.
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Cited as one of Carlisle's current portfolio holdings — a higher-quality company trading at a smaller discount, balancing the more cyclical deep value names in ZIG.
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Scott McNeely's famous critique of Sun Microsystems trading at 10x revenues is invoked by Carlisle to highlight Apple's similarly extreme current valuation.
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The benchmark index discussed throughout as increasingly concentrated in large-cap growth names and potentially overvalued, with passive index funds forced to absorb new mega-cap IPOs.
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Discussed as a near-peer AI competitor to the US, with Carlisle noting that during his visit a year prior, Chinese models were seen as the best-value AI option even if US models led on raw capability.
Stats
This episode
Claims & Sources
Factual claims made this episode, and whether a source was named.
All 6-7 major market valuation metrics tracked by Advisor Perspectives are simultaneously at their most overvalued level in the entire historical dataset.
Small caps have outperformed the Magnificent 7 both year-to-date and over the last 12 months.
The value-growth valuation spread is currently in the 95th percentile, meaning it has only been wider on 5% of historical occasions.
AI computing hardware has a useful life of approximately 5-7 years, compared to 25+ years for fiber optic cables and railways.
The dot-com large-cap growth dominance period ran from approximately 2000 to 2015, followed by a value market, then another large-cap growth market from 2015 to the present.
Google is raising $80 billion in external capital to fund AI infrastructure, despite historically being one of the most cash-rich companies.
Meta spent approximately $12 billion on metaverse development before reversing course and abandoning the initiative.
Michael Mauboussin published a paper showing OpenAI's projected growth would be unprecedented in corporate history, and Anthropic's actual growth subsequently obliterated even those projections.
Amazon achieved approximately 80% revenue growth in a year when it was already generating around $100 billion in revenue during the pandemic.
Semiconductors as a group were trading at 55 times earnings, implying 75% of the sector's value is in terminal value beyond 10 years and requiring 16.5% annual growth for a decade.
The equal-weight S&P 500 (RSP) has outperformed the market-cap-weight S&P 500 for most of the period since at least 1990, except during notable large-cap growth booms.
Energy stocks currently represent approximately 3% of stock market capitalization versus a historical average of approximately 12%.
Investor over-excitement during technology booms has occurred at least six identifiable times in history — the telegraph, railway, electronics, dot-com, and AI booms among them.
China's top AI models were considered the best value option globally as of approximately one year prior to the recording, while US models led on raw capability.
On the day after SpaceX launched on the market, large-cap growth rallied approximately 3% while small value dropped approximately 2%, a 5% swing that erased half of small value's prior outperformance.
