The “out-of-sample” performance of long run risk models |
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| Authors: | Wayne Ferson Suresh Nallareddy Biqin Xie |
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| Institution: | 1. Marshall School of Business, University of Southern California, Los Angeles, CA 90089, USA;2. Columbia Business School, Columbia University, New York, NY 10027, USA;3. Smeal College of Business, Pennsylvania State University, State College, PA 16802, USA;1. Federal Reserve Board, Division of Research and Statistics, Capital Markets MS-89, 20th & C street, Washington, DC 20551, United States;2. Naveen Jindal School of Management, University of Texas at Dallas, SM31, P.O.Box 830699, Richardson, TX 75083-0699, United States;1. Wharton School of the University of Pennsylvania, United States;2. NBER, United States;1. Saïd Business School, Oxford-Man Institute of Quantitative Finance, Park End Street, Oxford OX1 1HP, UK;2. CEPR, UK;1. Columbia Business School, Uris Hall 805, Broadway 3022, NYC, NY 10027, United States;2. Columbia Business School, Uris Hall 810, Broadway 3022, NYC, NY 10027, United States;3. Haas School of Business, University of California, Berkeley, 545 Student Services Building #1900, Berkeley, CA 94720-1900, United States;1. Carroll School of Management, Boston College, Chestnut Hill, MA 02467, USA;2. College of Business, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA;3. School of Business – Camden, Rutgers University, Camden, NJ 08102, USA |
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| Abstract: | This paper studies the ability of long-run risk models to explain out-of-sample asset returns during 1931–2009. The long-run risk models perform relatively well on the momentum effect.A cointegrated version of the model outperforms the classical, stationary version. Both the long-run and the short-run consumption shocks in the models are empirically important for the models' performance. The models' average pricing errors are especially small in the decades from the 1950s to the 1990s. When we restrict the risk premiums to identify structural parameters, this results in larger average pricing errors but often smaller error variances. The mean squared errors are not substantially better than those of the classical CAPM, except for Momentum. |
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