Learning and Asset Prices Under Ambiguous Information
在卢卡斯交换经济中研究学习与模糊信息对资产价格的影响，模型能匹配股权溢价、利率和股票收益波动率，并解释收益与波动率关系难以检测的原因。
In a Lucas exchange economy with standard power utility, we study asset prices under learning and ambiguous information. In contrast with models featuring only learning or ambiguity, our model is successful in matching the equity premium, the interest rate, and the volatility of stock returns under empirically reasonable parameters. Our closed-form formulas also show that a severe downward bias arises in the empirical relation between stock returns and return volatility. We quantify this bias in simulations and show that our model can explain why such a relation is difficult to detect in the data. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org., Oxford University Press.