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厚尾流动性需求、价格发现与限价订单簿风险

文章 arXiv papers · 作者: Umut Çetin et al.
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总结

本文研究在交易者可能掌握私人信息的序贯限价订单簿中，厚尾的非知情交易如何影响价格发现。流动性提供者可以看到汇总订单流，却无法直接区分知情订单与非知情流动性冲击。当非知情需求具有厚尾时，在比高斯假设下更深的订单簿位置，大额交易仍可能被合理地视为非知情交易。这会减缓价格冲击并拖慢学习过程，不过极端程度足够高的交易仍可能透露私人信息。

作者使用非线性不动点方程刻画均衡，并证明在尾部约束下均衡存在，同时给出后验一致性以及成本和订单流的渐近结果。作者还推导出尾部区域中知情需求最终占主导、订单簿具有单调性。对十档AAPL数据的实证分析报告了更远档位的交叉诊断结果，以及厚尾大额交易后持续存在的买卖价差。模型和证据聚焦于特定的信息与流动性环境；摘要并未证明相同模式适用于其他资产、交易场所或订单簿机制。

核心观点

  • 厚尾的非知情订单流可能使大额交易不再立即显露私人信息。
  • 其结果是在更广的深度范围内价格冲击更平缓，流动性提供者的学习速度更慢。
  • 随着尾部区域中知情需求占主导，极端交易仍可能变得具有信息含量。
  • 论文通过带有尾部约束的不动点方法确立均衡性质。
  • 十档AAPL数据显示了交叉诊断结果，以及厚尾大额交易后持续存在的价差。

标签

市场微观结构交易执行股票统计学
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# When large trades are not (automatically) news: liquidity tail risk and price discovery


# When large trades are not (automatically) news: liquidity tail risk and price discovery









We examine how heavy-tailed liquidity demand changes price discovery in a sequential limit order book with asymmetric information. In our setting, liquidity suppliers observe aggregate order flow, not its decomposition into informed demand and uninformed liquidity shocks. With heavy-tailed uninformed aggregated order flow, large trades remain plausibly uninformed over a wider range of depths, flattening price impact and slowing learning; sufficiently extreme trades can nevertheless become informative. We characterize equilibrium through a non-linear fixed point equation for the marginal-cost schedule; heavy-tailed uninformed aggregated order flow invalidates the monotonicity and compactness arguments available under Gaussianity. Therefore, we establish fixed-point existence within a tail-controlled class, prove posterior consistency for liquidity suppliers in the presence of endogenous dependent order flow, and derive tail asymptotics for marginal costs, informed demand, and aggregate order flow. Additionally, we obtain eventual informed-demand dominance and eventual monotonicity of the book in the far tails. Empirically, using 10-level AAPL data, we document farther-out crossover diagnostics and persistent bid-ask spreads following large heavy-tailed trades.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。