AI Panic, Bitcoin Crash, Bubble Warnings… And the Opportunity Hiding Beneath the Fear
AI Panic, Bitcoin Crash, Bubble Warnings… And the Opportunity Hiding Beneath the Fear
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Note: AI-generated summary based on third-party content. Not financial advice. Read more.
Quick Insights

View recent pullbacks in the AI sector as buying opportunities, as the long-term trend is driven by strong fundamentals, not speculative hype. Despite its large run-up, consider NVIDIA (NVDA) a core holding poised to capture a significant share of the estimated $5 trillion global data center build-out. The extreme fear and recent 36% crash in Bitcoin (BTC) may present a significant buying opportunity for long-term believers as sentiment indicators reach historic lows. Look for undervalued opportunities in small and mid-cap stocks, which are forecasted to see nearly 60% EPS growth and may be poised for a major catch-up rally. A forward-looking theme is the physical infrastructure for AI, focusing on companies that control essential resources like power and land needed for data centers.

Detailed Analysis

Artificial Intelligence (AI) Sector

  • The speaker is extremely bullish on the AI sector for the long term, suggesting investors will be "climbing a wall of worry of AI for the next five years."
  • He strongly refutes the idea that AI is a bubble, arguing that current market corrections are fear-driven opportunities, not the start of a collapse.
  • The speaker contrasts the current environment with the dot-com bubble, noting that today's leading companies have massive revenue, high margins, and enormous cash flow, unlike the speculative companies of the late 90s.
    • He cites former Google CEO Eric Schmidt, who believes the "AI revolution is under hyped."
  • The core thesis is that AI is driving a fundamental shift in the economy, leading to higher profit margins and a "K-shaped economy" where AI-adopting companies thrive.
  • The speaker believes that any company that does not incorporate AI will eventually be out of business.

Takeaways

  • View pullbacks and "bubble fears" in the AI sector as potential buying opportunities rather than reasons to sell.
  • Focus on the fundamental facts of leading AI companies—such as revenue growth and profit margins—instead of getting caught up in negative sentiment.
  • The AI trend is considered a multi-year phenomenon. Investors should have a long-term perspective and not be shaken out by short-term volatility.

NVIDIA (NVDA)

  • The speaker describes NVIDIA as "cheap" despite its significant stock price appreciation.
  • He highlights the company's staggering financial performance as a core reason for his bullishness:
    • Q3 revenues hit a record $57 billion, a 62% year-over-year increase.
    • The speaker notes, "I've never seen a vertical chart like this go straight up, but people are trying to pick the top in it."
  • The long-term opportunity is framed around the global build-out of data centers, which is estimated to be a $5 trillion investment over the next five years.
    • NVIDIA is expected to capture 35% to 60% of this massive expenditure.
  • The speaker believes NVIDIA's competitive advantage, or "moat," is "almost impossible" to lose in the near future.

Takeaways

  • NVIDIA is presented as a core holding for the AI theme, with its valuation considered reasonable given its explosive growth.
  • Investors should focus on the company's continued execution (beating and raising revenue estimates) rather than trying to time a market top. The speaker suggests worrying only when revenue growth slows and margins begin to compress.

Bitcoin (BTC)

  • The speaker acknowledges the recent, painful "crash," with Bitcoin falling 36% from its highs in less than seven weeks.
  • He admits to being personally wrong on its price action this year and has taken significant losses on his holdings.
  • Despite the losses, his conviction remains high. He states he has "doubled down and tripled down" on his position during the sell-off.
  • He points to several indicators suggesting extreme fear and a potential bottoming process:
    • The Fear & Greed Index is at levels of extreme fear.
    • The Daily Sentiment Index (DSI) for Bitcoin futures is at an all-time low.
    • The Relative Strength Index (RSI), a momentum indicator, fell below 21, a level that has historically preceded bounces.
  • The speaker believes the crypto market is going through a "liquidation" but that it "won't be staying down long."

Takeaways

  • The extreme fear and sharp sell-off in Bitcoin are presented as a significant buying opportunity for long-term believers.
  • While acknowledging the high volatility and personal pain of the drawdown, the speaker's actions indicate a strong belief that the bottom is near and a sharp recovery could follow.
  • This is a high-risk asset. The speaker notes how quickly it can move in either direction, stating that just "two good weeks" could lead to it outperforming the S&P 500 for the year.

MicroStrategy (MSTR)

  • The speaker mentions owning MicroStrategy and has "taken a bath" on the position due to its high correlation with Bitcoin.
  • The stock's recent sharp decline is seen as part of a broader "liquidation" event that is shaking out retail investors from speculative assets.
  • Its price chart is shown to move almost "tick for tick" with other speculative investments and Bitcoin itself.

Takeaways

  • MicroStrategy is effectively a leveraged bet on the price of Bitcoin.
  • Investors should understand that owning MSTR comes with the same, if not amplified, volatility and risk as owning Bitcoin directly. The recent price action highlights this risk.

Small-Cap & Mid-Cap Stocks

  • The speaker is bullish on small and mid-cap stocks, noting they have been in a "bear market for three years" and are lagging the broader market.
  • A major catalyst is the forecast for earnings growth. Consensus estimates point to nearly 60% EPS growth for small-cap companies.
  • He uses Micron (MU) as an example of a stock that traded sideways for a long time before making a massive upward move, suggesting that well-positioned small caps could experience similar breakouts.

Takeaways

  • This is an area of the market that may be undervalued and poised for a significant catch-up rally.
  • Investors should "do their homework now" to identify promising small and mid-cap companies before a potential market rotation into this sector. The forecasted earnings recovery could be a powerful tailwind.

Investment Theme: Physical Infrastructure for AI

  • A new, forward-looking investment theme is introduced: "The next moat is control of land, power, water, and grid access."
  • The thesis is that the explosive growth of AI will create unprecedented demand for electricity and other physical resources needed to run data centers.
  • Companies that own or control this essential infrastructure will have immense pricing power.
  • The speaker suggests a scenario where AI "hyperscalers" (like Google, Amazon, Microsoft) could pay legacy industrial companies (e.g., aluminum, steel) to shut down their operations simply to use their electricity allocations.

Takeaways

  • This is a "picks and shovels" play on the AI revolution.
  • Investors should look beyond the chipmakers and software companies to identify opportunities in utilities, real estate (with land for data centers), water rights holders, and other companies that control the physical resources essential for AI's growth.

Other Mentioned Stocks

  • Palantir (PLTR), AMD (AMD), and Meta (META): These companies are cited as examples of strong, factual revenue growth (PLTR up 63%, META up 26%). Their performance is used as evidence to counter the "AI is a bubble" narrative by showing that real, profitable growth is occurring.
  • Micron (MU): Mentioned as a successful personal investment that demonstrates how a stock can break out of a long consolidation period and rally significantly (from under $100 to $240). This is used as an analogy for what could happen with small-cap stocks.
  • Eli Lilly (LLY): Mentioned briefly as another one of the speaker's "good buys." No further context was provided.

Takeaways

  • The strong financial results from a broad range of tech companies support the argument that the current technology boom is based on fundamentals, not just speculation.
  • The price action of stocks like Micron can serve as a model for how beaten-down sectors or stocks can perform once sentiment shifts and growth accelerates.
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Video Description
Thinking in Bets: Why the AI Bubble Fears Are Wrong—Again In this week's video, I tackle the latest wave of panic—S&P down just 3.5% from all-time highs while my portfolio is down 35%—and explain why this feels identical to every other correction we've climbed over the past two years. Despite economist covers, CoreWeave CDS fears, and institutional hand-wringing about AI credit stress, the data tells a different story: Nvidia just posted $57 billion in quarterly revenue (up 62%), S&P profit margins hit all-time highs, and earnings revisions remain elevated globally. The AI buildout isn't slowing—it's accelerating into physical infrastructure constraints that most investors still don't understand. The real shift: we're moving from GPU scarcity to power scarcity, from code-driven margin expansion to grid-driven capital rotation. Google's Gemini 3 launch underscores that AI capabilities continue advancing at pace, yet junk spreads remain tight, bank stocks are up 13% year-over-year, and leading economic indicators show none of the credit stress that precedes actual bubbles. Meanwhile, Bitcoin's 36% drawdown from recent highs has pushed sentiment to Liberation Day levels, creating what I view as a compelling asymmetric entry point heading into a year where PMI expansion, Fed rate cuts, and tokenization tailwinds converge. I walk through Annie Duke's Thinking in Bets framework as a mental model for navigating this volatility—every decision is a probabilistic wager on incomplete information, and right now the crowd is assigning far too much probability to bubble scenarios while ignoring structural drivers. Small-cap earnings growth is forecast near 60%, international equities show the largest relative growth differential in a decade, and the K-shaped economy continues separating AI-enabled winners from legacy laggards without triggering a traditional recession. This is exactly when alpha gets made. Timestamps (00:00–03:45) Market panic context: S&P down 3.5% feels like capitulation, retail fear at Liberation Day levels, why this drawdown (5.6% S&P, 8% NDX) pales versus historical corrections (03:45–08:20) Thinking in bets: Annie Duke's framework for decision-making under uncertainty, why emotions dominate when you believe you know things you don't (08:20–14:30) AI bubble fears debunked: Economist covers, CoreWeave CDS, Oracle credit stress—compared to dot-com (800% 5-year NDX gain vs. 95% today), junk spreads tight, bank stocks up 13% YoY vs. down 20% at prior peaks (14:30–21:15) The data that matters: Nvidia $57B revenue (+62%), Palantir +63% revenue growth, S&P profit margins at all-time highs, AI mentions across every S&P sector, DRAM prices rising (not falling) (21:15–28:40) Why this isn't 5G telecom: Hyperscalers are high-margin, low-leverage cash-flow machines vs. levered telcos; AI capex looks more like 1990s semiconductor boom or early AWS buildout (28:40–35:50) Recession that isn't: Leading indicators negative since 2022, PMI 20-month average in historical recession territory, temp jobs collapsing, yet S&P earnings climbing—K-shaped economy confirmed (35:50–42:10) Bitcoin drawdown: 36% from highs, fear/greed at 6, daily sentiment index at futures-era lows, RSI below 21—historical buying zone despite being down 9% YTD after back-to-back 100%+ years (42:10–48:55) Earnings revisions and PMI setup: 20-week moving average of revisions still elevated, international earnings growth accelerating faster than US, small-cap/mid-cap EPS growth near 60%—all pointing to 2025 PMI expansion (48:55–52:30) Investment takeaway: Craig Shapiro's insight on AI demand colliding with physical limits—hyperscalers can pay legacy industrials to go offline and use their grid allocations; the next moat is control of land, power, water, and grid access
About Jordi Visser
Jordi Visser

Jordi Visser

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