What if a retail buying frenzy drives a parabolic melt-up?
A leveraged retail options/meme frenzy produces a parabolic melt-up — the trade is long the highest-gamma, highest-beta names (Solana, meme single-stocks) as dealer hedging chases price up, until it reflexively reverses. Rhymes with Jan-2021 (GME/AMC) and the 2024-25 crypto/retail melt-ups: vertical gains, then violent mean-reversion. Skeptical: melt-ups are unstable and end in capitulation (see scenario 1188); the durable lesson is to fade exhaustion, not chase. Roots (max risk_appetite + crypto_liquidity) are well-specified for a risk-on squeeze.
Every number ships with its receipt — the odds, the range, the precedents, and a public grade at Reality Check. The statistical machinery that produces it is proprietary.
The butterfly cascade
How this trigger trickles across markets, left → right — the root shock, its first‑order moves, then the ripple effects. Drag any node; tap a market for its real price history.
Resolution timeline — how this probability is moving
Our model's odds (electric blue) over time vs the market's (Polymarket, amber), from the past toward the 0–6 months horizon. Each dot is a real macro event that nudged the probability — green pushed it up, red pushed it down. Tap a dot for the source. Loading the probability audit trail…
What it would mean
If this plays out, it is a risk-on shock. A leveraged retail buying frenzy in single-stock options and meme names produces a parabolic melt-up detached from fundamentals. The trigger decomposes into signed root‑shocks — Crypto liquidity ▲ · Risk appetite ▲ — which propagate through our causal graph to the markets below.