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Implications of Return Predictability across Horizons for Asset Pricing Models

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  • Favero, Carlo A.
  • Ortu, Fulvio
  • Tamoni, Andrea
  • Yang, Haoxi

Abstract

We use the evidence on predictability of returns at diff erent horizons to discriminate among competing asset pricing models. Specifically, we employ predictors-based variance bounds, i.e. bounds on the variance of the Stochastic Discount Factors (SDFs) that price a given set of returns conditional on the information contained in a vector of return predictors. We show that return predictability delivers variance bounds that are much tighter than the classical, unconditional Hansen and Jagannathan (1991) bounds. We use the predictors-based bounds to discriminate among three leading classes of asset pricing models: rare disasters, long-run risks and external habit. We find that the rare disasters model of Nakamura, Steinsson, Barro, and Ursua (2013) is the best performer since it satisfies rather comfortably the predictors-based bounds at all horizons. As for long-run risks, while the classical version of Bansal and Yaron (2004) is the model most challenged by the introduction of conditioning information since it struggles to meet the bounds at all horizons, the more general version of Schorfheide, Song, and Yaron (2016), which accounts for multiple volatility components, satisfies the 1- and 5-year bounds as long as the set of test assets includes only equities and T-Bills. The Campbell and Cochrane (1999) habit model lies somehow in the middle: it performs quite well at our longest 5-year horizon while it struggles at the 1-year horizon. Finally, when the set of test assets is augmented with Treasury Bonds, the only model that is able to satisfy the predictors-based bounds is the rare disasters model

Suggested Citation

  • Favero, Carlo A. & Ortu, Fulvio & Tamoni, Andrea & Yang, Haoxi, 2016. "Implications of Return Predictability across Horizons for Asset Pricing Models," CEPR Discussion Papers 11645, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:11645
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    References listed on IDEAS

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    Cited by:

    1. Raymond Kan & Cesare Robotti, 2016. "The Exact Distribution of the Hansen–Jagannathan Bound," Management Science, INFORMS, vol. 62(7), pages 1915-1943, July.

    More about this item

    Keywords

    asset pricing models; predictors-based bound; return predictability;

    JEL classification:

    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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