Convergence-Weighted Aggregation of Cross-Exchange Prediction Markets: A Dependency-Aware Index for Combining Prices Across Kalshi, Polymarket, Manifold, Metaculus, and Long-Tail Venues

Modern prediction-market venues increasingly host overlapping markets on identical world events. Naive aggregation methods treat each venue as a conditionally independent source given the resolution outcome; this assumption is violated by three documented mechanisms (cross-exchange copy-trading bots, shared news flow, arbitrageur compression). Adapts the Index of Convergence Multi-epistemic (ICM) framework to the prediction-market setting. Within Pi, the lead-lag primitive Pi_L is the load-bearing component for the empirical bias-reduction result. Synthetic experiments confirm bias-reduction direction under Mechanism I (copy-trading) but not under Mechanisms II (common factor) or III (arbitrage compression); result is regime-targeted rather than uniformly dominant. Strict cross-exchange backtest at V=2 listing venues degenerates ICM to equal-weighted naive mean. Reference implementation released open-source. Forward-looking evaluation across additional exchanges (Kalshi via authenticated API, plus Metaculus and long-tail venues) planned with rolling collection from May 2026.