Adverse Selection in Prediction Markets: Evidence from Kalshi

Abstract

Using 41.6 million trades, we measure adverse selection in prediction markets. Adapting Kyle’s λ and the Glosten-Harris decomposition, we show single-name markets exhibit greater informed price impact than broad-based markets. Despite this, effective spreads are only modestly wider, and market makers earn twice as much per contract. A frequency-magnitude decomposition resolves this puzzle: traders systematically overbet YES in markets that predominantly settle NO, generating a behavioral surplus that cross-subsidizes adverse selection. Adapting the VPIN toxicity metric, we find that one-sided order flow predicts maker losses in single-name markets but not broad-based markets. Our research suggests a new microstructure equilibrium concept for bilateral settlement markets.

Details

Author(s):
Publish Date:
April 21, 2026
Publication Title:
SSRN
Format:
Op-Ed or Opinion Piece
Citation(s):
  • Robert Bartlett, Adverse Selection in Prediction Markets: Evidence from Kalshi, SSRN (Apr. 21, 2026), https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6615739.
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