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Time-series predictability in the disaster model

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  • François Gourio

    (Boston University, Department of Economics)

Abstract

This paper studies whether the Rietz–Barro “disaster” model, extended for a time-varying probability of disaster, can match the empirical evidence on predictability of stock returns. It is shown that when utility is CRRA, the model cannot replicate this evidence, regardless of parameter values. This motivates extending the disaster model to allow for Epstein–Zin utility. Analytical results show that when the probability of disaster is i.i.d., the model with Epstein–Zin utility can match the evidence on predictability qualitatively if the intertemporal elasticity of substitution is greater than unity. The case of a persistent probability of disaster is studied numerically, with partial success.

Suggested Citation

  • François Gourio, 2008. "Time-series predictability in the disaster model," Boston University - Department of Economics - Working Papers Series wp2008-016, Boston University - Department of Economics.
    • Handle: RePEc:bos:wpaper:wp2008-016
    as

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    References listed on IDEAS

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    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Mehra, Rajnish & Prescott, Edward C., 1985. "The equity premium: A puzzle," Journal of Monetary Economics, Elsevier, vol. 15(2), pages 145-161, March.
    3. Andrew Ang & Geert Bekaert, 2007. "Stock Return Predictability: Is it There?," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 651-707.
    4. John Y. Campbell & John Cochrane, 1999. "Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 107(2), pages 205-251, April.
    5. Campbell, John Y, 1996. "Understanding Risk and Return," Journal of Political Economy, University of Chicago Press, vol. 104(2), pages 298-345, April.
    6. Jessica A. Wachter, 2013. "Can Time-Varying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?," Journal of Finance, American Finance Association, vol. 68(3), pages 987-1035, June.
    7. Rietz, Thomas A., 1988. "The equity risk premium a solution," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 117-131, July.
    8. Xavier Gabaix, 2012. "Variable Rare Disasters: An Exactly Solved Framework for Ten Puzzles in Macro-Finance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(2), pages 645-700.
    9. Robert J. Barro, 2006. "Rare Disasters and Asset Markets in the Twentieth Century," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(3), pages 823-866.
    10. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    11. Longstaff, Francis A. & Piazzesi, Monika, 2004. "Corporate earnings and the equity premium," Journal of Financial Economics, Elsevier, vol. 74(3), pages 401-421, December.
    12. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, August.
    13. Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 2008. "The Myth of Long-Horizon Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1577-1605, July.
    14. Xavier Gabaix, 2007. "Linearity-Generating Processes: A Modelling Tool Yielding Closed Forms for Asset Prices," NBER Working Papers 13430, National Bureau of Economic Research, Inc.
    15. Francois Gourio, 2008. "Disasters and Recoveries," American Economic Review, American Economic Association, vol. 98(2), pages 68-73, May.
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    More about this item

    Keywords

    Rare events; Jumps; Disasters; Equity premium; Return predictability;
    All these keywords.

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • 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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