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The volatility of consumption-based stochastic discount factors and economic cycles

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  • Nieto, Belén
  • Rubio, Gonzalo
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    Abstract

    This paper aims to assess the macroeconomic and financial impact of economic uncertainty using information contained in the second moments of financial risk factors employed in the asset pricing literature. Specifically, we propose the volatility of consumption-based stochastic discount factors (SDFs) as a predictor of future economic and stock market cycles. We employ both contemporaneous and ultimate consumption risk specifications with durable and non-durable consumption. Alternative empirical tests show that this volatility has significant forecasting ability from 1985 to 2006. The degree of predictability tends to dominate that shown by standard predictor variables. We argue that the significant predictability of the volatility of consumption-based SDFs reported in this paper relies mainly on the joint effect of their components.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Banking & Finance.

    Volume (Year): 35 (2011)
    Issue (Month): 9 (September)
    Pages: 2197-2216

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    Handle: RePEc:eee:jbfina:v:35:y:2011:i:9:p:2197-2216

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    Web page: http://www.elsevier.com/locate/jbf

    Related research

    Keywords: Stochastic discount factor Economic cycles Volatility of stochastic discount factor Consumption Risk aversion;

    References

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    Cited by:
    1. Kang, Jangkoo & Kim, Tong Suk & Lee, Changjun & Min, Byoung-Kyu, 2011. "Macroeconomic risk and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3158-3173.
    2. Tim Bollerslev & Lai Xu & Hao Zhou, 2012. "Stock Return and Cash Flow Predictability: The Role of Volatility Risk," CREATES Research Papers 2012-51, School of Economics and Management, University of Aarhus.
    3. Nieto, Belén & Novales, Alfonso & Rubio, Gonzalo, 2014. "Variance swaps, non-normality and macroeconomic and financial risks," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 257-270.

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