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Model Complexity, Expectations, and Asset Prices

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  • Vedolin, Andrea
  • Molavi, Pooya
  • Tahbaz-Salehi, Alireza

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.

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  • Vedolin, Andrea & Molavi, Pooya & Tahbaz-Salehi, Alireza, 2021. "Model Complexity, Expectations, and Asset Prices," CEPR Discussion Papers 15717, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:15717
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    1. Ignacio Esponda & Demian Pouzo, 2016. "Berk–Nash Equilibrium: A Framework for Modeling Agents With Misspecified Models," Econometrica, Econometric Society, vol. 84, pages 1093-1130, May.
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    3. Hirshleifer, David & Li, Jun & Yu, Jianfeng, 2015. "Asset pricing in production economies with extrapolative expectations," Journal of Monetary Economics, Elsevier, vol. 76(C), pages 87-106.
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    5. Stefan Nagel & Zhengyang Xu, 2022. "Asset Pricing with Fading Memory," The Review of Financial Studies, Society for Financial Studies, vol. 35(5), pages 2190-2245.
    6. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    7. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    8. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
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    Cited by:

    1. Engel, Charles & Kazakova, Katya & Wang, Mengqi & Xiang, Nan, 2022. "A reconsideration of the failure of uncovered interest parity for the U.S. dollar," Journal of International Economics, Elsevier, vol. 136(C).
    2. Granziera, Eleonora & Sihvonen, Markus, 2024. "Bonds, currencies and expectational errors," Journal of Economic Dynamics and Control, Elsevier, vol. 158(C).
    3. Bouaddi, Mohammed & Moutanabbir, Khouzeima, 2023. "Rational distorted beliefs investor; which risk matters?," Finance Research Letters, Elsevier, vol. 51(C).
    4. Matthes, Julian & Momsen, Katharina, 2024. "Preferences and Demand for Mental Models," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302412, Verein für Socialpolitik / German Economic Association.

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    More about this item

    Keywords

    Model complexity; Subjective expectations; Asset pricing;
    All these keywords.

    JEL classification:

    • G4 - Financial Economics - - Behavioral Finance
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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