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Long-Run Risk is the Worst-Case Scenario

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  • Ian Dew-Becker

    (Northwestern University)

  • Rhys Bidder

    (Federal Reserve Bank of San Francisco)

Abstract

We study an investor who is unsure of the dynamics of the economy. Not only are parameters unknown, but the investor does not even know what order model to estimate. She estimates her consumption process non-parametrically and prices assets using a pessimistic model that minimizes lifetime utility subject to a constraint on statistical plausibility. The equilibrium is exactly solvable and we show that the pricing model always includes long run risks. With a single free parameter determining risk preferences, the model generates high and volatile risk premia, excess volatility in stock returns, return predictability, interest rates that are uncorrelated with expected consumption growth, and investor expectations that are consistent with survey evidence. Risk aversion is equal to 4.8, there is no stochastic volatility or disasters, and the pricing model is statistically nearly indistinguishable from the true data-generating process. The analysis yields a general characterization of behavior under a very broad form of model uncertainty.

Suggested Citation

  • Ian Dew-Becker & Rhys Bidder, 2015. "Long-Run Risk is the Worst-Case Scenario," 2015 Meeting Papers 490, Society for Economic Dynamics.
  • Handle: RePEc:red:sed015:490
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    Cited by:

    1. Rhys Bidder & Ian Dew-Becker, 2016. "Long-Run Risk Is the Worst-Case Scenario," American Economic Review, American Economic Association, vol. 106(9), pages 2494-2527, September.
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    3. Jozef Barunik & Josef Kurka, 2021. "Frequency-Dependent Higher Moment Risks," Working Papers IES 2021/11, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2021.
    4. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    5. Bidder, R.M. & Smith, M.E., 2018. "Doubts and variability: A robust perspective on exotic consumption series," Journal of Economic Theory, Elsevier, vol. 175(C), pages 689-712.
    6. Cosmin L. Ilut & Martin Schneider, 2022. "Modeling Uncertainty as Ambiguity: a Review," NBER Working Papers 29915, National Bureau of Economic Research, Inc.
    7. Dew-Becker, Ian & Nathanson, Charles G., 2019. "Directed attention and nonparametric learning," Journal of Economic Theory, Elsevier, vol. 181(C), pages 461-496.
    8. Friberg, Richard & Seiler, Thomas, 2017. "Risk and ambiguity in 10-Ks: An examination of cash holding and derivatives use," Journal of Corporate Finance, Elsevier, vol. 45(C), pages 608-631.
    9. Yacine Aït-Sahalia & Felix Matthys & Emilio Osambela & Ronnie Sircar, 2021. "When Uncertainty and Volatility Are Disconnected: Implications for Asset Pricing and Portfolio Performance," Finance and Economics Discussion Series 2021-063, Board of Governors of the Federal Reserve System (U.S.).
    10. Hongye Guo & Jessica A. Wachter, 2019. ""Superstitious" Investors," NBER Working Papers 25603, National Bureau of Economic Research, Inc.
    11. Meyer-Gohde, Alexander, 2019. "Generalized entropy and model uncertainty," Journal of Economic Theory, Elsevier, vol. 183(C), pages 312-343.
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    13. Guihai Zhao, 2020. "Ambiguity, Nominal Bond Yields, and Real Bond Yields," American Economic Review: Insights, American Economic Association, vol. 2(2), pages 177-192, June.
    14. Szőke, Bálint, 2022. "Estimating robustness," Journal of Economic Theory, Elsevier, vol. 199(C).
    15. Alexander M. Chinco & Samuel M. Hartzmark & Abigail B. Sussman, 2020. "Necessary Evidence For A Risk Factor’s Relevance," NBER Working Papers 27227, National Bureau of Economic Research, Inc.
    16. Pohl, Walter & Schmedders, Karl & Wilms, Ole, 2021. "Asset pricing with heterogeneous agents and long-run risk," Journal of Financial Economics, Elsevier, vol. 140(3), pages 941-964.
    17. Hui Chen & Winston Wei Dou & Leonid Kogan, 2019. "Measuring “Dark Matter” in Asset Pricing Models," NBER Working Papers 26418, National Bureau of Economic Research, Inc.
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    More about this item

    JEL classification:

    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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