AI 中文总结
研究美国赛事合约交易所Kalshi预测市场价格，发现校准非合约静态属性，临近到期有偏差，跨赛事连投系统性定价过高，两种偏差可校正，实际用价格作概率要考虑到期时间和产品类型。
AI 中文摘要
在学术研究和基于预测市场构建的衍生品中，预测市场价格常被视为概率。本文利用美国主要赛事合约交易所Kalshi上2300万笔让分胜负交易记录，揭示了这种解读存在的两个系统性问题。一是校准（报价与实际赛事频率的一致性）并非合约的静态属性，在合约有效期内参数会发生变化，临近到期时经验校准曲线呈阶梯状，符合持有亏损头寸交易者的保险需求行为。二是Kalshi上的跨赛事连投相对于同期单场价格的乘积系统性定价过高，且随着连投场次增加而加剧。这两种偏差都具有系统性，可通过计算进行校正。实际将预测市场价格用作概率时，需考虑到期时间和产品类型，而非仅依赖价格。
英文摘要
Prediction market prices are routinely interpreted as probabilities, both in academic work and in derivative products built atop these markets. We document two systematic ways this interpretation fails on Kalshi, a major U.S. event-contract exchange, using 23 million moneyline trades across major sport leagues. First, calibration, the agreement between quoted prices and realized event frequencies, is not a static property of a contract: fitting calibration models within time-to-expiry buckets, we find that parameters sit at their perfect-calibration reference values in the middle of a contract's life but depart sharply as expiry approaches. In the final ten minutes before settlement the empirical calibration curve becomes step-like, fitting a Prelec form with curvature parameter well above one, the opposite sign of the canonical lottery-choice fit, consistent with insurance-demand behavior by traders holding losing positions. Second, cross-game parlays on Kalshi are systematically overpriced relative to the product of their contemporaneous leg prices, with overpricing growing in leg count. This holds when the parlay legs are drawn from the TTE regime in which leg-level calibration is essentially perfect, indicating a separate, market-level markup at the parlay-pricing stage. Both deviations are systematic and therefore admit computational correction. Practical use of prediction-market prices as probabilities requires conditioning on time to expiry and on product type, not on price alone.
