从市场出清均衡推导特征收益
文章 arXiv papers · 作者: Guillaume Coqueret
总结
本文构建了一个模型，探讨公司特征如何在均衡中影响资产收益。模型假设投资者需求分别取决于公司特征和资产对数价格，而资产供给是外生的，不受因子驱动。当需求与特征呈线性关系时，市场出清会使收益也与这些特征呈线性关系。由此得到的系数代表经过缩放的总净需求及其变化，作者称可通过面板回归联合估计这些系数。
分析推导了将资产定价异象与特征之间关系联系起来的条件。报告的实证结果显示，当特征集合较小时，公司特定固定效应可以解释价值和动量异象的很大一部分。作者将这些效应解释为潜在的投资者需求，并认为低维模型可能遗漏重要结构。本文未说明数据集、回归细节或稳健性检验，因此无法根据这份说明进一步评估实证结论。均衡结果也取决于其对投资者需求和资产供给的假设。
核心观点
- 投资者需求分别依赖特征和对数价格，这一设定支撑了均衡推导。
- 基于特征的线性需求与外生供给共同导出与特征呈线性关系的收益。
- 模型系数代表经过缩放的总需求及其变化。
- 作者通过面板回归联合估计这些系数。
- 据报告，在特征较少时，公司特定固定效应可以解释价值和动量异象的很大一部分。
标签
全文
# Characteristics-driven returns in equilibrium # Characteristics-driven returns in equilibrium We reverse-engineer the equilibrium construction process of asset prices in order to obtain returns which depend on firm characteristics, possibly in a linear fashion. One key requirement is that agents must have demands that rely separately on firm characteristics and on the log-price of assets. Market clearing via exogenous (non-factor driven) supply, combined with linear demands in characteristics, yields the sought form. The coefficients in the resulting linear expressions are scaled net aggregate demands for characteristics, as well as their variations, and both can be jointly estimated via panel regressions. Conditions underpinning asset pricing anomalies are derived and underline the theoretical importance of the links between characteristics. Empirically, when the number of characteristics is small, the value and momentum anomalies are mostly driven by firm-specific fixed-effects, i.e., latent demands, which highlights the shortcomings of low-dimensional models.
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此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。