Geopolitics risk-off · 0–6 months
A what‑if from the future

What if a Chinese and Taiwanese warship collide mid-strait?

A median-line warship collision with fatalities is an escalation-spiral catalyst, not yet a fab event: VIX +12, Nasdaq -5, crypto-beta leads down on the unknown. Rhymes with the 2001 Hainan EP-3 incident, which roiled US-China sentiment but resolved diplomatically. The key tell is whether either side frames it as accident or attack. Forward angle: with both navies now far larger and operating closer, the collision baseline is higher than 2001, so fade-the-dip only after de-escalation signals.

12%
our model probability
over 0–6 months
prediction markets — the market's odds
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Anchored to measured history 12% · 90% range 4–20% · 40 dated precedents behind it — a wider range means thinner evidence

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…

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What it would mean

If this plays out, it is a risk-off shock. A PLA and Taiwanese warship collide near the median line, killing sailors and igniting an escalation spiral. The trigger decomposes into signed root‑shocks — Geopolitical risk ▲ · Risk appetite ▼ — which propagate through our causal graph to the markets below.

Methodology. Probability and impact are anchored to history and scored against what actually happens — wins and losses, in public, at Reality Check. Market odds live from Polymarket & Kalshi. By Vikas Singh, Quantitative Strategist. Updated 2026-08-13.