Model Complexity, Expectations, and Asset Prices

Pooya Molavi, Alireza Tahbaz-Salehi and Andrea Vedolin

No 28408, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: D84 F31 G12 G4 (search for similar items in EconPapers)
Date: 2021-01
New Economics Papers: this item is included in nep-ore
Note: AP
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Citations: View citations in EconPapers (5)

Published as Pooya Molavi & Alireza Tahbaz-Salehi & Andrea Vedolin, 2024. "Model Complexity, Expectations, and Asset Prices," Review of Economic Studies, vol 91(4), pages 2462-2507.

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Working Paper: Model Complexity, Expectations, and Asset Prices (2021)
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