Tech Stocks Plunge as Leverage Unwinds
TREE NEWS reports: On November 6, the Nasdaq Composite fell 5.5% in a single day, the Philadelphia Semiconductor Index plunged 12%, and the S&P 500 dropped 4.4%. Goldman Sachs’ FICC and equities trading desk reported net selling of $3 billion in US cash equities, with information technology and communication services accounting for $2.2 billion. Cumulative net selling in tech has now reached $27 billion, surpassing the $21 billion technical selloff in July. Meanwhile, the VVIX, which measures volatility of volatility, saw its largest one-day move since the February 5, 2018 “Volmageddon” episode.
Rich Privorotsky, head of FICC and equities at Goldman Sachs, characterized the selloff as a liquidity crisis akin to 1998 rather than the bursting of the 2000 tech bubble. His core view: the AI growth engine remains intact; what the market is aggressively repricing is the financing and timing of buildouts, not underlying demand. If the analogy holds, historical episodes like this have ultimately proven to be buying opportunities.
Leverage Self-Reinforces, Not Valuation Re-rating
The mechanics point to forced deleveraging rather than fundamental-driven valuation reset. Privorotsky noted that forced liquidation of leveraged ETFs before the close amplified declines in semiconductors and the Nasdaq, compounded by negative gamma exposure from market makers creating a self-reinforcing liquidation loop. Flow data showed broad-based selling across multi-strategy funds, quant funds, long-only institutions, and retail—”everyone on the same side” is itself the problem. Rising correlations, momentum factor underperformance, and continued selling in residual leverage factors, while low-beta, defensive, and quality assets were bid, are consistent with a typical forced de-risking event.
The first two days post-election saw AI stocks underperform while cyclicals rallied on expectations of political centralization. The second day brought a sharp catch-down: if data center construction slows significantly, nominal growth expectations would be revised lower, putting the cyclical rally itself at risk of repricing.
1998 vs. 2000: Two Templates, Two Outcomes
Privorotsky compared the current selloff to two historical episodes, leaning toward the 1998 template. In 1998, the Russian default and LTCM crisis were external shocks, but US economic growth remained intact; once liquidity returned and the Fed eased, markets quickly recovered. Similarly, the AI growth logic may be intact, with the market repricing buildout financing and pace.
Unlike 2000, today’s tech leaders have real revenue, cash flow, and balance sheets. Delaying data center construction does not eliminate compute demand; constrained capacity may even improve the economics of existing assets. The discomfort similar to 2000 lies in the massive scale of spending and uncertain returns. The key question: is the market liquidating a sound growth story or discovering a flaw in its economic logic? Privorotsky leans toward the former but stresses that demand, utilization, and return data must remain solid.
Four AI Buildout Concerns, Market Focuses on the Wrong One
Goldman identified four market concerns driving the selloff: 1) insufficient capital for the scale of buildout; 2) insufficient revenue to justify investment; 3) insufficient power and permitting capacity to support compute expansion; 4) unsustainable overall spending trajectory. Privorotsky believes the market is most focused on the third—power and permitting—which is actually the least important. Supply constraints do not equal disappearing demand. The real question is whether revenue can ultimately justify the capital invested.
On the political front, Texas Governor-elect Gina Hinojosa’s stance is more moderate than the market interpreted. She stated: “We can achieve economic development while protecting Texans—these are not mutually exclusive,” and reiterated, “I don’t hate data centers.” Privorotsky sees this as a regulatory reset rather than ideological rejection, with actual spending likely better than current market discounts imply.
Technical Levels and Buy Point Prerequisites
Technically, the Nasdaq has broken below its 200-day moving average, while the S&P 500 is just above it; holding this support is crucial. The negative gamma environment means violent moves in either direction are possible. Privorotsky explicitly named TSMC and ASML as quality tech assets to favor amid uncertainty.
He listed three conditions to change the market narrative: political positive feedback for AI investment, stabilization in financing markets, and empirical evidence that underlying spending and demand remain intact. The falsification conditions are equally clear: if AI capex is materially delayed and revenue disproves the investment logic, the 1998 analogy fails and the 2000 template applies; if financing markets show refinancing failures first, the nature of the decline changes fundamentally.
Longer-term, Privorotsky cited historical data: since 1950, the S&P 500 has risen in all 19 instances in the 12 months following midterm elections—but he emphasized this is a 12-month observation, not a one-month prediction; short-term timing remains difficult. In energy, oil prices rebounded about 4% in a day; the market had been too optimistic about a quick easing of Iran tensions, and negotiations remain unresolved. The complex impact of energy shocks on rates, growth expectations, and risk appetite remains a key variable for stabilization.
Key Takeaways for Investors
- Leverage unwind, not fundamental collapse: The selloff appears driven by forced deleveraging and negative gamma, not a repricing of AI’s long-term demand. This distinction is critical for positioning.
- Quality bias: Favor high-quality tech with real cash flows and strong balance sheets (e.g., TSMC, ASML) over speculative AI plays.
- Watch the S&P 500’s 200-day moving average: Holding this support could signal a buying opportunity; a break could trigger further selling.
- Monitor financing markets and capex trends: If refinancing failures emerge or AI capex is materially delayed, the 1998 analogy breaks and a 2000-style bust becomes the base case.
- Long-term view: Historical post-midterm patterns are favorable over 12 months, but short-term volatility is likely to persist.
