by Dr. Chris Kacher
After the scorching run in AI infrastructure names — AVGO, MRVL, LITE, CRWV, NBIS, HPE, PANW, and the usual suspects — the setup for a meaningful pullback made sense. We recently saw AVGO gap down hard on a “not excited enough” guidance print, and broader futures have been wobbly on oil/geopolitics. This isn’t doom-and-gloom; it’s the kind of risk-off digestion we track daily with pocket pivots, buyable gap ups, and liquidity signals. Here’s the realistic bear case for how AI stocks could drop 20-40%+ in a correction.
### 1. Valuation & Expectation Reset (The “Priced for Perfection” Trap)
AI names are trading at extreme multiples because the narrative is “insatiable demand forever.” One soft guide, one missed whisper number, or even just no upward revision (see AVGO’s latest) and the multiple contracts fast.
We’ve seen this movie: hyperscalers are guiding massive AI revenue, but if capex ROI doesn’t show up quickly enough, sentiment flips. Dan Niles and others have flagged 30-50% downside in early 2027 on exactly this. AVGO vs MRVL is the perfect example — AVGO has more cushion and diversification, but MRVL is higher-beta and more exposed if custom ASIC ramps disappoint. A broader rotation out of crowded AI trades would hit the entire basket hard.
### 2. Power & Infrastructure Bottleneck Bites Harder
This is the big one we’ve been watching in the AI infrastructure theme. The shift from “compute bottleneck” to “power bottleneck” is real and accelerating. Data center delays, grid constraints, transformer backlogs (5+ years in some cases), and massive energy shortfalls could cap the ramp.
Hyperscalers are throwing hundreds of billions at capex (projected $500-700B+ in 2026), but if half the planned 2026 projects get delayed or canceled due to power access, revenue growth narratives take a hit. Optics/networking names (LITE, etc.) and custom chip plays feel it first. This isn’t theoretical — it’s already showing up in unfulfilled backlogs and slower buildouts. Prolonged delays = lower near-term multiples.
### 3. Liquidity Tightening & Higher Yields (QE Megatrend Risk)
Our core QE Liquidity focus is critical here. Rising oil from geopolitics, stickier inflation, and any pause or reversal in Fed easing pushes bond yields higher. Growth stocks with long-duration cash flows get punished hardest.
Global liquidity signals matter — China tightening moves, any QT undertow, or simply risk-off flows out of tech into defensives can trigger sharp de-risking. We’ve seen it recently: futures weakness + AVGO reaction = classic liquidity-driven move. If reserves tighten or capex funding gets expensive, the leveraged AI buildout slows, and stocks gap down.
### 4. Capex Digestion & ROI Reality Check
Big Tech is spending like crazy, but markets will demand proof that this translates into real earnings acceleration, not just more hype. If monetization lags (AI fatigue, token costs exploding, or enterprises slowing spend), we get the classic “digestion phase.”
Vanguard, Panmure, and others have modeled scenarios where AI capex underdelivers → tech hardware down 35%+, broader S&P correction 15-30%. Add in any macro shock (recession scare, higher rates) and it compounds.
### 5. Technical & Sentiment Triggers We Watch Daily
- Failed pocket pivots or buyable gap-ups on key names.
- Distribution days piling up after record highs.
- Rotation out of mega-cap AI into value/energy (already hints in recent action).
**Bottom Line for Our Framework**
A drop doesn’t mean the secular AI theme is dead — far from it. But after parabolic moves, healthy (or not-so-healthy) 20-40%+ corrections in leading, high alpha names are normal and create the next entry.
Watch power/infrastructure updates, liquidity dashboards, and earnings reactions closely.
Near-term (next 1–3 months): **Liquidity tightening is more likely to create downside pressure or volatility** than a straight shot to new highs. AI remains a powerful structural tailwind for longer-term upside (2026 H2 and beyond), but it won’t fully override short-term macro friction right away.
Kevin Warsh (new Fed Chair) has been consistent:
- **Long-term bullish on supply-side deflation**: He views AI as a major **disinflationary productivity force** (echoing the 1990s Greenspan era). Higher productivity lets the economy grow without pushing up prices, eventually creating room for lower rates.
- **Short-term cautious/hawkish**: Recent data (hot May jobs +172k, CPI at +4.2% YoY driven by energy, sticky core at +2.9% YoY, plus oil/geopolitical risks) means he’s likely to prioritize data-dependence. His first FOMC meeting (June 16–17) is expected to **remove any easing bias**, hold rates steady (current ~3.50–3.75% range), and signal a more neutral stance. He has also favored gradual balance-sheet normalization (QT-like pressure), which can tighten liquidity.
### Global Liquidity Outlook
Liquidity has been a mixed-to-tightening story lately:
- Fed balance sheet normalization and higher-for-longer rates (or even hikes) drain reserves.
- Geopolitical factors (Iran conflict, oil spike) add friction via higher energy costs and risk aversion.
- Global liquidity proxies (e.g., cross-border flows, bank lending, China easing offsets) show some support but are not strongly expansionary right now.
Tighter liquidity + hawkish Fed tone + elevated oil/inflation risks typically pressure risk assets (equities, especially high-valuation growth/AI names). This aligns with the recent pullbacks. Expect volatility, possible tests of support levels, and rotation away from crowded AI/tech if liquidity feels scarce.
### AI Bull Case: Path to New Highs?
AI remains a **major structural positive**:
- Hyperscaler capex is still rising strongly (guidance lifts into 2026+).
- Productivity gains are real and broadening beyond pure tech.
- Earnings growth for AI-exposed companies continues to support valuations in a base case.
Many major banks (J.P. Morgan, Morgan Stanley, etc.) remain constructive on equities for the rest of 2026, forecasting double-digit gains driven by AI investment and earnings. If Warsh’s long-term thesis plays out and data cools (or oil eases), liquidity could stabilize or improve later in the year, fueling a rally to new highs.
**Most probable path**: **Liquidity tightness creates headwinds first** (next few months), leading to choppy or downside-biased markets. AI provides a floor and eventual upside catalyst once the Fed’s tone or data improves. A clean “shoot to new highs” right now is less likely without relief on oil/inflation or clearer Fed easing signals.
**Key risks to watch**:
- June 16–17 FOMC dot plot and Warsh’s tone.
- Oil prices and Iran developments (big liquidity/inflation wildcard).
- Actual AI earnings/capex delivery vs. hype.