Tom Lee: Why the AI bloodbath and crypto selloff are nearly over

Key takeaways

• Fundstrat co-founder Tom Lee believes the AI "scare trade" is approaching an end and sees Mag 7 stocks and crypto moving toward near-term bottoms.
• Nvidia (NVDA) delivered solid results, yet market reaction has been muted and there was no immediate rally on Thursday.
• Nvidia CEO Jensen Huang said “markets got it wrong” on the software selloff, a concise market view that traders are weighing.

Market context

Markets tied to the AI narrative and high-growth technology sectors experienced a difficult stretch this month. Stocks widely associated with AI demand and adoption have underperformed relative to broader indices, and cryptocurrencies have declined in tandem with risk-off flows. The combination of profit-taking, software-sector weakness, and rotation into non-AI areas has driven short-term volatility.

Fundstrat's co-founder frames the current environment as an AI scare trade that is winding down rather than a structural reversal of the AI investment thesis. Describing the current phase as "nearly" over signals a shift in sentiment more than an absolute end to volatility.

Nvidia's earnings and market response

Nvidia (NVDA) reported results characterized in market commentary as solid. Despite the company's performance, the immediate market reaction was limited: applause has been described as a "smattering," and there was no clear rally in the AI-oriented cohort on the subsequent trading day (Thursday). That muted response indicates investors remain cautious, pricing in near-term uncertainty even as fundamentals hold up.

Nvidia CEO Jensen Huang’s succinct statement, “markets got it wrong,” highlights management’s view that the market overshot in adjusting valuations on software and related segments. This leadership perspective can influence sentiment, but it does not erase near-term technical and liquidity-driven pressure.

Why Tom Lee sees a turning point

Tom Lee’s assessment that the AI scare trade and crypto selloff are close to a bottom rests on several observable dynamics:

• Sentiment extremes: When positioning and headlines emphasize downside risk for AI-linked names and crypto, contrarian signals often appear for professional traders and institutional allocators.
• Corporate resilience: Large-cap AI-related companies delivering strong results can stabilize investor expectations even when broader market flows remain unsettled.
• Sector divergence: When the market differentiates between durable AI winners and weaker names, capital can reallocate toward higher-quality AI exposures rather than exiting the theme entirely.

Framing the move as "nearly over" is deliberately cautious: it recognizes that technical rebounds and renewed investor participation typically follow a phase where fundamentals reassert themselves and headline-driven selling abates.

What institutional traders and analysts should watch

• Earnings and guidance: Follow upcoming quarterly updates from AI-focused hardware and software vendors to gauge revenue sustainability and demand trends.
• Volatility and liquidity metrics: Spikes in implied volatility and widening bid-ask spreads can prolong corrections even when fundamentals improve.
• Mag 7 behavior: Monitor the price action of the Mag 7 as a group—the behavior of these large-cap leaders often sets tone for broader AI-related flows.
• Crypto risk appetite: Observe stablecoin flows, futures open interest, and large-wallet activity for signs of capitulation or renewed accumulation.

Practical signals of a durable bottom

• Consistent follow-through in buying across multiple market sessions rather than a single-day bounce.
• Rotation into quality: capital moving back into large-cap, cash-flow-positive AI leaders rather than purely speculative names.
• Reduced headline-driven selling: fewer aggressive liquidation events tied to margin calls or forced selling.

Risks and counterpoints

• Rebound risk: Labeling a scare trade "nearly" over does not preclude fresh downside if macro data or liquidity conditions deteriorate.
• Dispersion within the AI theme: Not all AI-exposed companies will recover equally; idiosyncratic execution risk remains significant.
• Crypto correlation: Continued correlation between equity risk-on/risk-off moves and crypto assets means a broader market shock could drag both lower again.

Actionable implications for professional traders and institutional investors

• Reassess position sizing: If conviction in specific AI winners remains intact, consider phased re-entry rather than full allocation at once.
• Use volatility to your advantage: Structured trades or options strategies can capture asymmetric risk-reward when implied volatility is elevated.
• Maintain liquidity buffers: Preserving dry powder enables participation in selective rebounds and prevents forced exits during renewed stress.

Bottom line

The market is at an inflection where sentiment-driven selling has created opportunities for differentiated exposure to AI leaders and selectively for crypto. Tom Lee’s view—that the AI scare trade and crypto selloff are almost over—frames the current phase as a potential turning point rather than a confirmed recovery. Investors should combine disciplined risk management with close monitoring of earnings, liquidity, and group-level behavior to determine whether the expected stabilization becomes sustainable.