谁聚合信息？筛选、租金以及CLOB与AMM预测市场的共存

中文摘要 AI 辅助

预测市场股票与传统金融产品不同，在没有信息或外部效用的情况下，经典的德尔塔中性中央限价订单簿（CLOB）做市无法由无信息含量的噪声流来融资。来自一个主要预测市场CLOB平台的交易级证据表明，做市商的利润并非来自价差，而是来自持有定价偏低的一侧直至结算——这是行为性尾部需求而非经典随机噪声的经验特征。我们将这种尾部需求直接纳入模型，并研究同一事件上的LMSR和CLOB。在共同信号区间内的冲击前CLOB报价会被掠走；因此，竞争性报价将知情交易者筛选出订单簿。CLOB做市商通过持有定价偏低的一侧直至结算来赚取筛选租金，而知情流则流向LMSR。两种场所共存：CLOB提供了尾部需求租金边际，使LMSR能够收回其因知情流而遭受的部分损失，而AMM深度以由做市商侧可竞争性决定的符号移动CLOB溢价——在挂单可被削价时扩大溢价，在有承诺的做市商维持订单簿时压缩溢价。当结果数量为三个或更多时，二元账簿CLOB固定了转换价格，但使隐含信念不确定，而LMSR则连贯地为结果单纯形定价，并更有效地使用抵押品。

英文摘要

Prediction-market shares differ from traditional financial products in that, with no information or outside utility, classical delta-neutral Central Limit Order Book~(CLOB) market making cannot be financed by payoff-uninformative noise flow. Transaction-level evidence from a major prediction-market CLOB platform shows makers profiting not from spread but from carrying an under-priced side to settlement --- the empirical signature of behavioral tail demand rather than classical, randomized noise. We build this tail demand directly into the model and study an LMSR and a CLOB on the same event. A pre-shock CLOB quote inside the common-signal band is picked off; competitive quotes therefore screen informed traders out of the book. CLOB makers earn screening rent by carrying the under-priced side to resolution, while informed flow routes to the LMSR. The venues coexist: the CLOB supplies the tail-demand rent margin that lets the LMSR recover part of its loss to informed flow, and AMM depth moves the CLOB premium with a sign set by maker-side contestability---widening it where standing quotes can be undercut, compressing it where a committed maker carries the book. With three or more outcomes, binary-book CLOBs pin switch prices but leave implied beliefs indeterminate, whereas the LMSR prices the outcome simplex coherently and uses collateral more efficiently.

发表机构

• Gensyn AI
• The University of Tokyo（东京大学）

机构由 AI 辅助整理，请以论文原文为准。