The probability of conflict: How predictive markets reflect geopolitical realities
- Timothy Beggans
- Dec 4
- 2 min read
Predictive markets are increasingly shaping how analysts interpret geopolitical risk—often offering clearer, faster signals than traditional intelligence channels. Nowhere is this more evident than in markets tracking the probability of a Chinese invasion of Taiwan.
Platforms like Polymarket, Kalshi, Manifold, and Metaculus aggregate thousands of independent forecasts. While each uses different mechanisms, all point to the same broad takeaway: low near-term probability, but meaningful long-term risk. Traders have priced short-term invasion odds in the low single digits, but expectations rise steadily toward the late 2020s, reflecting structural tensions rather than immediate triggers.
Beijing’s Fourth Plenum reinforces this split outlook. Official policy remains unchanged—commitment to “peaceful reunification” paired with refusal to renounce force. Symbolic moves, such as establishing an annual “Commemoration Day of Taiwan’s Restoration,” tighten the ideological narrative but stop short of signaling imminent action.
The purge of senior PLA leaders, however, is the development markets responded to most. Removing commanders directly tied to Taiwan operations—ten full Central Committee members and four alternates—suggests a short-term disruption in operational readiness. Predictive markets picked this up quickly, with traders marking down invasion probabilities for the next 12–18 months.
But the longer horizon is where markets grow more cautious. Many see the purges as Xi consolidating control to build a more loyal, streamlined force capable of executing his strategic vision. That aligns with forecasts on Metaculus and Manifold showing elevated probabilities by 2027 and beyond, when analysts believe military modernization milestones converge with political symbolism.
In essence, predictive markets reflect a nuanced message: conflict is not imminent, but it is not drifting away either. They translate political signals, military reshuffling, and strategic intent into real-time probability curves—a data-driven map of geopolitical pressure.
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