Overview of Lots More With Charlie McElligott on This Week's SaaSpocalypse
This episode of Bloomberg’s Lots More features Charlie McElligott (Nomura), who explains why last week’s rapid market dislocations—plunging metals, a savage software sell‑off, and crypto weakness—were not the result of a single catalyst but of crowded, highly‑levered positioning interacting with market‑structure dynamics (options, levered ETFs, buybacks, and multi‑strategy flows). He ties micro (software/AI, private credit, VC/BDCs) and macro (dollar positioning, Fed messaging, credit supply) factors into a coherent narrative for why the unwind happened and how it could stop.
Key takeaways
- Crowded positioning + low realized volatility created large fragility: many trend trades accumulated because volatility had been low, and gross exposures hit multi‑year highs.
- The pullback was multi‑faceted: short‑dollar trades, concentrated AI/mega‑cap positioning, massive buyback activity (which suppressed vol), and stretched flows into metals and EM all reversed at once.
- Software (SaaS) and crypto (Bitcoin) behaved like a liquidity/valuation unwind rather than a simple macro hedging rotation—Bitcoin notably failed to act as a “debasement” hedge while gold and silver ran.
- Market structure amplified the sell‑off: options/skew, leveraged ETFs, multi‑strat low‑vol strategies with tight stops and big gross exposures, and CTAs/target‑vol dynamics all fed momentum in both directions.
- Credit is a key transmission channel: heavy issuance to fund buybacks and anticipated huge capital needs from AI players (e.g., OpenAI) could widen spreads; private credit / BDCs sitting on illiquid software loans add systemic-looking vulnerability.
- How the bleed stops: hedge monetization creating dealer delta buying, vol‑rollover, re‑entry by vol‑supply strategies and systematic buyers; that process can be quick but also fragile.
Topics discussed
- Market moves this week: gold/silver plunges, software sector collapse, Bitcoin drop (to ~60–66k), and broader equity dispersion.
- Positioning data: extreme gross exposures in risk parity/multi‑strat-like portfolios (99th–100th percentile on 5‑yr lookbacks), CTA/commodity exposures near 98th percentile.
- Buybacks as a vol suppressor: large tech/hyperscaler buybacks accounted for a huge share of S&P demand and reduced realized volatility; as buybacks fade, an important passive bid disappears.
- AI CapEx vs. balance sheet stress: AI spending burns cash and forces funding needs, creating demand in credit markets; tech firms used buybacks and leverage heavily.
- Options flow & skew: massive call demand in GLD/SLV while Bitcoin diverged; dealers’ gamma and option hedging matter materially for intraday/short‑term moves.
- Leveraged ETFs & retail behavior: large inflows into levered products (which are synthetic negative gamma) amplify moves—selling into declines, buying into rallies.
- Private credit / BDC and valuation risks: illiquid exposures to tech/software valuations can cause knock‑on effects in credit markets if growth covenants/marks break.
- Correlation vs. implied correlation: realized correlations rose (many sectors down) even as implied correlation readings remained low—creating confusion for hedgers.
Notable quotes / pithy insights
- “Grosses were too damn big.” — on multi‑strategy and gross leverage levels.
- Buybacks: “They are a vol suppressor… a passive bid under the market.”
- On Bitcoin vs. gold: “Bitcoin is trading like software… it’s trading like SaaS.”
- On market structure: “Anybody who’s on a VAR model is actually a momentum trader.”
Data points and market signals mentioned
- Gross exposures at 99th (risk parity) / 100th (GS prime brokerage equity hedge fund grosses) percentile vs. 5‑yr history.
- CTA/commodity exposures and net short dollar exposures were unusually high (commodities/metals 98th percentile; net equities exposure ~97th).
- Silver moved ~16% in one day—described as one of the wildest moves some traders have seen.
- Oracle raised $25bn (investment grade + converts) with ~$129bn demand — a one‑day relief moment for credit markets.
- OpenAI (and similar AI capex needs) potentially needing $100–200bn in coming months — a looming funding pressure.
Actionable implications / watchlist for traders and risk managers
- Monitor positioning and gross leverage metrics (multi‑strat gross, risk parity leverage, CTA exposures).
- Track short‑dollar positioning and FX flows—dollar stabilization can reverse many crowded trades.
- Watch buyback announcements and corporate cash trends as an indicator of the passive bid and vol suppression.
- Follow options skew and dealer gamma exposure (especially in GLD/SLV, mega‑caps, and major indices) for short‑term price dynamics.
- Keep an eye on credit supply and pricing: primary issuance in investment grade, tech convert/bond deals, and private credit valuations (BDCs).
- Compare implied correlation vs. realized correlation to detect hidden dispersion risk.
- Monitor Bitcoin vs. gold behavior to test “debasement” narratives—divergence can signal a liquidity/flow story rather than pure macro hedging.
How the market turn generally plays out (mechanics)
- Grosses and hedges are trimmed → dealers buy delta (from hedges being monetized) → short‑term rally can form.
- Retail/structured players re‑engage (zero‑DTE calls, income sellers) → adds skew/delta and can amplify moves.
- Vol supply and systematic strategies re‑enter when risk seems lower → markets stabilize or re‑test lows depending on flow intensity.
- Credit spread moves and funding needs remain an ongoing backstop / source of renewed stress.
Bottom line
This week’s “SaaSpocalypse” was less a single news shock and more the natural unwind of a decade of structural flows (buybacks, low‑vol allocation into multi‑strats, levered retail products, and option selling) meeting a concentrated thematic exposure to AI/software and related credit/funding risks. The reversal was exaggerated by market structure—tight stops, leverage, dealer hedging and momentum—so short‑term technical fixes (hedge monetization, dealer delta buying) can stop the immediate bleed, but the fundamental questions around tech valuations, private credit marks, and AI funding remain and will determine the medium‑term path.