Michael Burry on why he stopped managing his hedge fund: ‘I think the stock market could be in for a number of bad years.'

Michael Burry deregistered Scion Asset Management and says the U.S. equity market could face “a number of bad years,” citing heavy passive flows that he believes will pull down broad market values rather than leave pockets untouched. He said he replicated trades in his personal account, buying put options on Nvidia and Palantir, criticized Palantir’s stock-based compensation despite roughly $4 billion in revenue, and warned that AI-related capex announcements are currently inflating valuations ("$1 of capex -> $3 market cap" effect). Burry suggested out-of-favor healthcare names as potential buys but emphasized a defensive posture rather than betting against the U.S. overall.

Analysis

Market structure: Passive dominance (>50%+ of US equity AUM) and concentrated AI capex means downside will be highly correlated — winners: large legacy enterprise vendors (IBM) and fixed-income/FX safe-havens; losers: crowded high-multiple AI names (NVDA, PLTR) and tech-heavy ETFs. Pricing power shifts toward firms with recurring enterprise contracts and low equity dilution; supply–demand for liquidity is thin — a 10% equity drop will cascade via ETF creations/redemptions and options gamma. Cross-asset: expect Treasuries and USD to rally, VIX to jump >10-20 pts on a 15% drawdown, and cyclical commodities to lag.

Risk assessment: Tail risks include a fast options-gamma unwind, forced ETF redemptions, or an abrupt Fed pivot (policy surprise within 60 days) that triggers 15-30% equity drawdowns. Immediate (days): liquidity/gamma stress; short-term (weeks–3 months): earnings (NVDA) and CPI/Fed meetings will be catalytic; long-term (quarters): AI capex disappointment or real capex lag compresses multiples. Hidden dependencies: buybacks and margin leverage can amplify moves; government procurement timing (for PLTR) can be binary.

Trade implications: Implement targeted hedges and asymmetric shorts: establish 1–2% NAV equivalent short via 3–6 month NVDA put spreads (buy 10–15% OTM puts, sell 25–35% OTM to finance) and a 2–3% NAV long in 6–12 month PLTR puts (15–25% OTM). Pair trade: long IBM 2% NAV vs short PLTR 2% NAV (expect relative ER outperformance within 3–9 months). Rotate 3–5% into healthcare: buy XLV or large-cap defensives JNJ/MRK, and add 2–4% TLT and 1–2% GLD as tail hedges if S&P falls >8%.

Contrarian angles: Consensus underestimates NVDA’s structural moat and supply constraints (shorts risk a squeeze), and overestimates PLTR downside without contract losses — both create asymmetric outcomes. The market may be pricing a “data-transmission” rerun; if Q2–Q4 capex continues, AI names can rerate higher, so keep time-decayed option exposure small and staggered. Unintended consequences: crowded shortism could push dealers to widen spreads and increase implied vols — size positions to survive a 30% short-cover rally.

Key Decisions for Investors

• Establish a 1–2% NAV short position in NVDA via a 3–6 month put spread: buy 10–15% OTM puts and sell 25–35% OTM puts to cap cost; deploy if NVDA rallies >5% intraday or IV <50% to get cheaper entry, target payoff if NVDA drops >15% within 6 months.
• Buy 6–12 month PLTR puts equal to 2–3% NAV (15–25% OTM); if options are illiquid, short PLTR stock size 2% NAV. Monitor government contract announcements over next 90 days; trim if PLTR secures large multi-year deals.
• Initiate a pair trade: long IBM 2% NAV and short PLTR 2% NAV (expect relative outperformance in 3–9 months). Rebalance if IBM outperforms by >20% or PLTR reports material positive contract news.
• Rotate 3–5% NAV into healthcare defensives: buy XLV or split 2–3% JNJ and 1–2% MRK as durable cash-flow refuges. Add interest-rate tail hedge: purchase TLT equal to 2–4% NAV if S&P 500 declines >8% or VIX >30.
• Increase USD hedge (UUP) by 1–2% NAV and add 1% GLD as crash insurance if implied equity volatility rises >25% in 7 days; review positions around next CPI and NVDA earnings (both within 30–60 days) and adjust risk sizing accordingly.