论文标题
部分可观测时空混沌系统的无模型预测
Characteristics-driven returns in equilibrium
论文作者
论文摘要
我们将资产价格的均衡构建过程逆转，以获得取决于公司特征的回报，可能是线性的。一个关键要求是，代理必须有单独依赖公司特征和资产日志价格的需求。通过外源性（非因素驱动）供应以及特征线性需求结合的市场清除市场可产生所寻求的形式。所得线性表达式中的系数是对特征及其变化的净量骨料需求，并且两者都可以通过面板回归共同估算。基于资产定价异常的条件是得出的，并强调了特征之间联系的理论重要性。从经验上讲，当特征的数量很少时，价值和动量异常主要是由特定于公司特异性固定效应的驱动的，即潜在需求，这突出了低维模型的缺点。
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.
