Investing for the Long Run When Returns are Predictable

49 Pages Posted: 4 Jan 2000

See all articles by Nicholas Barberis

Nicholas Barberis

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

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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.

JEL Classification: G1

Suggested Citation

Barberis, Nicholas and Barberis, Nicholas, Investing for the Long Run When Returns are Predictable. Available at SSRN: or

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