价格错位、新闻引用与 Polymarket 上的认知杠杆

中文摘要 AI 辅助

预测市场的概率越来越多地出现在新闻报道中，但关于哪些市场变动会成为新闻，以及记者所引用的数字背后有多少交易资金，我们知之甚少。与民意调查不同，市场价格可以被任何愿意交易的人推动，因此制造一个作为新闻流传的数字的成本直接关系到信息环境。我们将1.737亿笔已签名的Polymarket交易与2024-2025年的新闻报道关联起来。从6,990篇提及预测市场平台的文章中，一个基于LLM并经人工验证的匹配器提取了1,582个引用市场赔率的句子，并将其中918个归因于其价格被引用的特定市场。然后，我们检测到44,976次价格错位，即由集中的单边交易支撑的至少五个百分点的变动，并询问市场在此之后是否被更频繁地引用。在错位发生后的几天内，市场的引用率比其匹配的基线高出约33%（对数引用率比率$\tau_{\mathrm{cite}}=0.283$，置换检验$p=0.001$），该结果对二元和泊松计数结果均稳健。然而，变动幅度并非引用的最强预测因子：显著性占主导地位（标准化$\beta=0.610$，而变动幅度的$\beta=0.159$）。最后，我们将给定价格变动背后的美元流量与观察到的引用率结合起来，形成我们称之为认知杠杆的指标，即推动市场变动五个点并使该变动被引用所需的美元金额。在各显著性五分位数中，该指标保持在约70万至100万美元之间，因为更便宜的市场被引用的可能性成比例地更低。隐含的威胁模型并非集中于可廉价变动的市场的长尾，而是集中于新闻编辑室视为信息基础设施的少数显著市场，在这些市场中，七位数的影响力价格处于对引用数字有重大利益的参与者的预算之内。我们发布了汇总的事件研究数据和验证材料。

英文摘要

Prediction-market probabilities increasingly appear in news coverage, yet little is known about which market movements become news or how much trading money sits behind the numbers journalists quote. Unlike a poll, a market price can be moved by anyone willing to trade, so the cost of manufacturing a number that circulates as news bears directly on the information environment. We link 173.7 million signed Polymarket trades to news coverage from 2024-2025. From 6,990 articles mentioning prediction-market venues, an LLM-based, human-validated matcher extracts 1,582 sentences quoting market odds and attributes 918 to the specific market whose price they cite. We then detect 44,976 price dislocations, movements of at least five percentage points backed by concentrated one-sided trading, and ask whether a market is cited more often afterward. In the days after a dislocation, a market's citation rate is about 33% higher than its matched baseline (log citation-rate ratio $τ_{\mathrm{cite}}=0.283$, permutation $p=0.001$), robust to binary and Poisson count outcomes. Yet move size is not the strongest predictor of citation: prominence dominates (standardized $β=0.610$ vs. $β=0.159$ for move size). Finally, we combine the dollar flow behind a given price change with observed citation rates into a metric we call epistemic leverage, the dollars needed to move a market five points and have the move cited. It stays near \$0.7-1.0 million across prominence quintiles, because cheaper-to-move markets are proportionally less likely to be cited. The implied threat model centers not on the long tail of cheaply moved markets but on the few prominent markets newsrooms treat as informational infrastructure, where a seven-figure price of influence sits within the budgets of actors with a large stake in the quoted number. We release aggregate event-study data and validation materials.

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17 pages, 3 figures