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An Empirical Evaluation of the Long-Run Risks Model for Asset Prices

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  • Ravi Bansal
  • Dana Kiku
  • Amir Yaron

Abstract

We provide an empirical evaluation of the forward-looking long-run risks (LRR) model and highlight model differences with the backward-looking habit based asset pricing model. We feature three key results: (i) Consistent with the LRR model, there is considerable evidence in the data of time-varying expected consumption growth and volatility, (ii) The LRR model matches the key asset markets data features, (iii) In the data and in the LRR model accordingly, past consumption growth does not predict future asset prices, whereas lagged consumption in the habit model forecasts future price-dividend ratios with an R2 of over 40%. Overall, our evidence implies that the LRR model provides a coherent framework to analyze and interpret asset prices.

Suggested Citation

  • Ravi Bansal & Dana Kiku & Amir Yaron, 2009. "An Empirical Evaluation of the Long-Run Risks Model for Asset Prices," NBER Working Papers 15504, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:15504 Note: AP CF
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    References listed on IDEAS

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    Cited by:

    1. Turan G. Bali & Hao Zhou, 2011. "Risk, uncertainty, and expected returns," Finance and Economics Discussion Series 2011-45, Board of Governors of the Federal Reserve System (U.S.).
    2. Chen, Andrew Y., 2014. "Precautionary Volatility and Asset Prices," Finance and Economics Discussion Series 2014-59, Board of Governors of the Federal Reserve System (U.S.).
    3. Giovannetti, Bruno C., 2013. "Asset pricing under quantile utility maximization," Review of Financial Economics, Elsevier, vol. 22(4), pages 169-179.
    4. Ina Simonovska & Espen Henriksen, 2013. "Time-Varying Risk Premia and Capital Flows to Developing Countries," 2013 Meeting Papers 1258, Society for Economic Dynamics.
    5. Andreas Fuster & Benjamin Hebert & David Laibson, 2012. "Natural Expectations, Macroeconomic Dynamics, and Asset Pricing," NBER Macroeconomics Annual, University of Chicago Press, vol. 26(1), pages 1-48.
    6. Sebastian Di Tella & Pablo Kurlat, 2017. "Why are Banks Exposed to Monetary Policy?," NBER Working Papers 24076, National Bureau of Economic Research, Inc.
    7. David Backus & Mikhail Chernov & Stanley Zin, 2014. "Sources of Entropy in Representative Agent Models," Journal of Finance, American Finance Association, vol. 69(1), pages 51-99, February.
    8. Marianne Andries, 2012. "Consumption-based Asset Pricing Loss Aversion," 2012 Meeting Papers 571, Society for Economic Dynamics.
    9. Bednarek, Ziemowit, 2016. "Pure technology gaps and production predictability," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 39-50.
    10. Li, Minqiang, 2010. "Asset Pricing - A Brief Review," MPRA Paper 22379, University Library of Munich, Germany.
    11. Yu Chen & Thomas Cosimano & Alex Himonas & Peter Kelly, 2014. "An Analytic Approach for Stochastic Differential Utility for Endowment and Production Economies," Computational Economics, Springer;Society for Computational Economics, vol. 44(4), pages 397-443, December.
    12. Ravi Bansal & Dana Kiku & Amir Yaron, 2010. "Long Run Risks, the Macroeconomy, and Asset Prices," American Economic Review, American Economic Association, vol. 100(2), pages 542-546, May.
    13. Ludvigson, Sydney C., 2013. "Advances in Consumption-Based Asset Pricing: Empirical Tests," Handbook of the Economics of Finance, Elsevier.

    More about this item

    JEL classification:

    • E0 - Macroeconomics and Monetary Economics - - General
    • G0 - Financial Economics - - General
    • G1 - Financial Economics - - General Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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