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Measuring time-varying economic fears with consumption-based stochastic discount factors

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  • Belén Nieto
  • Gonzalo Rubio

Abstract

This paper analyzes empirically the volatility of consumption-based stochastic discount factors as a measure of implicit economic fears by studying its relationship with future economic and stock market cycles. Time-varying economic fears seem to be well captured by the volatility of stochastic discount factors. In particular, the volatility of recursive utility-based stochastic discount factor with contemporaneous growth explains between 9 and 34 percent of future changes in industrial production at short and long horizons respectively. They also explain ex-ante uncertainty and risk aversion. However, future stock market cycles are better explained by a similar stochastic discount factor with long-run consumption growth. This specification of the stochastic discount factor presents higher volatility and lower pricing errors than the specification with contemporaneous consumption growth.

Suggested Citation

  • Belén Nieto & Gonzalo Rubio, 2007. "Measuring time-varying economic fears with consumption-based stochastic discount factors," Economics Working Papers 1029, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2007.
  • Handle: RePEc:upf:upfgen:1029
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    1. Amihud, Yakov & Hurvich, Clifford M., 2004. "Predictive Regressions: A Reduced-Bias Estimation Method," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(4), pages 813-841, December.
    2. Hansen, Lars Peter & Jagannathan, Ravi, 1991. "Implications of Security Market Data for Models of Dynamic Economies," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 225-262, April.
    3. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    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. Jonathan A. Parker & Christian Julliard, 2005. "Consumption Risk and the Cross Section of Expected Returns," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 185-222, February.
    7. Bakshi, Gurdip & Chen, Zhiwu & Hjalmarsson, Erik, 2005. "Volatility of the Stochastic Discount Factor, and the Distinction between Risk-Neutral and Objective Probability Measures," Working Papers in Economics 159, University of Gothenburg, Department of Economics.
    8. Li, Yuming, 2001. "Expected Returns and Habit Persistence," Review of Financial Studies, Society for Financial Studies, vol. 14(3), pages 861-899.
    9. Keller, Joachim & Glatzer, Ernst & Craig, Ben R. & Scheicher, Martin, 2003. "The Forecasting Performance of German Stock Option Densities," Discussion Paper Series 1: Economic Studies 2003,17, Deutsche Bundesbank.
    10. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
    11. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    12. Alessandro Beber & Michael W. Brandt, 2009. "Resolving Macroeconomic Uncertainty in Stock and Bond Markets," Review of Finance, European Finance Association, vol. 13(1), pages 1-45.
    13. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    14. Kang, Byung Jin & Kim, Tong Suk, 2006. "Option-implied risk preferences: An extension to wider classes of utility functions," Journal of Financial Markets, Elsevier, vol. 9(2), pages 180-198, May.
    15. Motohiro Yogo, 2006. "A Consumption‐Based Explanation of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 61(2), pages 539-580, April.
    16. Robert R. Bliss & Nikolaos Panigirtzoglou, 2004. "Option-Implied Risk Aversion Estimates," Journal of Finance, American Finance Association, vol. 59(1), pages 407-446, February.
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    More about this item

    Keywords

    Stochastic discount factor; economic fears; distance between probability measures; volatility of stochastic discount factor; consumption;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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