G2TT
来源类型Discussion paper
规范类型论文
来源IDDP15717
DP15717 Model Complexity, Expectations, and Asset Prices
Pooya Molavi; Alireza Tahbaz-Salehi; Andrea Vedolin
发表日期2021-01-25
出版年2021
语种英语
摘要This paper analyzes how limits to the complexity of statistical models used by market participants can shape asset prices. We consider an economy in which agents can only entertain models with at most k factors, where k may be distinct from the true number of factors that drive the economy’s fundamentals. We first characterize the implications of the resulting departure from rational expectations for return dynamics and relate the extent of return predictability at various horizons to the number of factors in the agents’ models and the statistical properties of the underlying data-generating process. We then apply our framework to two applications in asset pricing: (i) violations of uncovered interest rate parity at different horizons and (ii) momentum and reversal in equity returns. We find that constraints on the complexity of agents’ models can generate return predictability patterns that are consistent with the data.
主题Financial Economics
关键词Model complexity Subjective expectations Asset pricing
URLhttps://cepr.org/publications/dp15717
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/544723
推荐引用方式
GB/T 7714
Pooya Molavi,Alireza Tahbaz-Salehi,Andrea Vedolin. DP15717 Model Complexity, Expectations, and Asset Prices. 2021.
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