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Volatility Bounds, Size, and Real Activity Prediction

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  • Belén Nieto
  • Gonzalo Rubio

Abstract

This article shows how to extract future real activity information from optimally combined size-sorted portfolios. In particular, we analyze the capacity of the size-based model-free Hansen–Jagannathan volatility bound to predict future economic growth. We find that the volatility bound is a powerful in-sample and out-of-sample predictor of future industrial production growth. The asymmetric sensitivities of small and large companies through the business cycle explain our findings. Alternative volatility bounds estimated with sorting procedures based on book-to-market, momentum, or dividend yield do not show these asymmetric sensitivities or forecasting capacity of output growth.

Suggested Citation

  • Belén Nieto & Gonzalo Rubio, 2014. "Volatility Bounds, Size, and Real Activity Prediction," Review of Finance, European Finance Association, vol. 18(1), pages 373-415.
    • Handle: RePEc:oup:revfin:v:18:y:2014:i:1:p:373-415.
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    File URL: http://hdl.handle.net/10.1093/rof/rft003
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    Cited by:

    1. González-Urteaga, Ana & Rubio, Gonzalo, 2021. "The quality premium with leverage and liquidity constraints," International Review of Financial Analysis, Elsevier, vol. 75(C).
    2. A. Ronald Gallant & George Tauchen, 2021. "Cash Flows Discounted Using a Model-Free SDF Extracted under a Yield Curve Prior," JRFM, MDPI, vol. 14(3), pages 1-15, March.
    3. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).

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