[论文] Across-Design Uncertainty in Short Pricing Panels: Evidence from Simul...

论文概要

研究领域: ML 作者: Pedro Cadahia Delgado 发布时间: 2026-08-21 arXiv: 2608.21334

中文摘要

短观测定价面板可能包含大量观测值，但仅提供少量不同的价格变动。本文在一个校准到稀疏定价机制的综合数据生成过程中研究了这一区别的影响。我们将条件于已实现价格轨迹的不确定性从相同定价过程生成的替代轨迹的估计误差变化中分离。在基线模拟中，后者占梯度提升规范估计误差方差的97.6%。面板内重采样程序使用一个已实现轨迹的信息，无法识别这一跨设计成分。三个结果组织了分析。首先，跨设计离散度很好地由经验关系sigma_hat ≈ 0.182 V^(-0.271)描述，其中V等于变动次数乘以幅度平方。其次，添加共享共同价格路径的区域减少了结果噪声，但未创建独立的价格轨迹；相反，对具有独立设计特定误差的单位取平均以标准平方根速率减少离散度。第三，跨独立定价单位估计的Paule-Mandel方差成分在均匀模拟中显著提高了经验覆盖率，从0.469提高到0.931。更广泛的含义是转向设计生成独立识别变异的数据生成过程，而非仅依赖固定的被动面板。

原文摘要

Short observational pricing panels can contain many observations while offering only a small number of distinct price movements. This paper studies the inferential consequences of that distinction in a synthetic data-generating process calibrated to a sparse pricing regime. We separate uncertainty conditional on a realised price trajectory from variation in estimation error across alternative trajectories generated by the same pricing process. In the baseline simulations, the latter component accounts for 97.6% of the variance of estimation error for the gradient-boosted specification. Within-panel resampling procedures use the information of one realised trajectory and do not identify this across-design component. Three results organise the analysis. First, across-design dispersion is wel...

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