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Sources of Entropy in Representative Agent Models

机译:代表性代理模型中的熵源

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摘要

We propose two data-based performance measures for asset pricing models and apply them to models with recursive utility and habits. Excess returns on risky securities are reflected in the pricing kernel's dispersion and riskless bond yields are reflected in its dynamics. We measure dispersion with entropy and dynamics with horizon dependence, the difference between entropy over several periods and one. We compare their magnitudes to estimates derived from asset returns. This exercise reveals tension between a model's ability to generate one-period entropy, which should be large, and horizon dependence, which should be small.
机译:我们为资产定价模型提出了两种基于数据的绩效指标,并将其应用于具有递归效用和习惯的模型。风险证券的超额收益反映在定价内核的离散度中,无风险债券收益率反映在定价动态中。我们用熵来衡量色散,用地平线依赖来衡量动力学,在几个周期内熵之间的差值是一个。我们将其幅度与资产收益估算值进行比较。这项练习揭示了模型产生一个周期的熵的能力(应该大)和视域依赖性(应该很小)之间的张力。

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