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https://ssrn.com/abstract=2184254
 
 

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Implications of Return Predictability across Horizons for Asset Pricing Models


Carlo A. Favero


Bocconi University - Department of Finance; Centre for Economic Policy Research (CEPR)

Fulvio Ortu


Bocconi University - Department of Finance

Andrea Tamoni


London School of Economics & Political Science (LSE)

Haoxi Yang


Nankai University

November 13, 2016


Abstract:     
We use the evidence on predictability of returns at di fferent horizons to discriminate among competing asset pricing models. Speci fically, 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 satisfi es 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, satisfi es 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.

Number of Pages in PDF File: 61

Keywords: return predictability, predictors-based bound, asset pricing models

JEL Classification: G12, E21, E32, E44


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Date posted: December 4, 2012 ; Last revised: November 14, 2016

Suggested Citation

Favero, Carlo A. and Ortu, Fulvio and Tamoni, Andrea and Yang, Haoxi, Implications of Return Predictability across Horizons for Asset Pricing Models (November 13, 2016). Available at SSRN: https://ssrn.com/abstract=2184254 or http://dx.doi.org/10.2139/ssrn.2184254

Contact Information

Carlo A. Favero
Bocconi University - Department of Finance ( email )
Via Roentgen 1
Milano, MI 20136
Italy
HOME PAGE: http://www.igier.unibocconi.it\favero
Centre for Economic Policy Research (CEPR)
77 Bastwick Street
London, EC1V 3PZ
United Kingdom
Fulvio Ortu
Bocconi University - Department of Finance ( email )
Via Roentgen 1
Milano, MI 20136
Italy
Andrea Tamoni (Contact Author)
London School of Economics & Political Science (LSE) ( email )
Houghton Street
London, WC2A 2AE
United Kingdom
02079557303 (Phone)
Haoxi Yang
Nankai University ( email )
Tongyan Road 38
Tianjin, Tianjin 300350
China
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