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Investing for the Long Run when Returns are Predictable

Nicholas Barberis

Yale School of Management; National Bureau of Economic Research (NBER)

We examine how the evidence of predictability in asset returns affects optimal portfolio choice for investors with long horizons. Particular attention is paid to estimation risk, or uncertainty about the true values of model parameters. We find that even after incorporating parameter uncertainty, there is enough predictability in returns to make investors allocate substantially more to stocks, the longer their horizon. Moreover, the weak statistical significance of the evidence for predictability makes it important to take estimation risk into account; a long-horizon investor who ignores it may over-allocate to stocks by a sizeable amount.

Number of Pages in PDF File: 49

JEL Classification: G1

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Date posted: January 4, 2000  

Suggested Citation

Barberis, Nicholas, Investing for the Long Run when Returns are Predictable. Available at SSRN: https://ssrn.com/abstract=185376 or http://dx.doi.org/10.2139/ssrn.185376

Contact Information

Nicholas Barberis (Contact Author)
Yale School of Management ( email )
135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States
203-436-0777 (Phone)

National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
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References:  30
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