We study a consumption-based asset pricing model with incomp
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We study a consumption-based asset pricing model with incomplete information
and α-stable shocks.Incomplete information leads to a non-Gaussian filtering problem.
Bayesian updating generates fluctuating confidence in the agents' estimate of the
persistent component of the dividends’ growth rate.This has the potential to generate
time variation in the volatility of model-implied returns,without relying on discrete shifts
in the drift rate of dividend growth rates.A test of the model using US consumption data indicates the implied returns display significant volatility persistence of a magnitude comparable to that in the data.
and α-stable shocks.Incomplete information leads to a non-Gaussian filtering problem.
Bayesian updating generates fluctuating confidence in the agents' estimate of the
persistent component of the dividends’ growth rate.This has the potential to generate
time variation in the volatility of model-implied returns,without relying on discrete shifts
in the drift rate of dividend growth rates.A test of the model using US consumption data indicates the implied returns display significant volatility persistence of a magnitude comparable to that in the data.
我们用不完整的信息与α-stable冲击研究了一种以消费型资产定价模式.不完整的信息导致一种非高斯过滤问题.而贝叶斯定理的更新对代理商评估持久稳固的股息增长率产生了不稳定的信心.这对在模式收益率产生时变性具有相当的潜在力,而不需要依赖于离散的个股增长率的变化.应用美国消费数据一次模拟测试,在与巨大数据中的收益比较中,收益率显示了突增的持续性.
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