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Learning About Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation

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  • Xia, Yihong

Abstract

This paper examines the effects of uncertainty about the predictability of stock returns on optimal dynamic portfolio choice in a continuous time setting with a long horizon. Uncertainty about the predictive relation affects the optimal portfolio choice through dynamic learning, and leads to a rich set of relations between the optimal portfolio choice and the investment horizon. There are also substantial market timing elements in the optimal hedge demands, which are caused by stochastic covariance and variance terms arising from dynamic learning. The opportunity cost of ignoring predictability or learning is found to be quite substantial.

Suggested Citation

  • Xia, Yihong, 2000. "Learning About Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation," University of California at Los Angeles, Anderson Graduate School of Management qt3167f8mz, Anderson Graduate School of Management, UCLA.
  • Handle: RePEc:cdl:anderf:qt3167f8mz
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    Cited by:

    1. Massa, Massimo & Simonov, Andrei, 2005. "Is learning a dimension of risk?," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2605-2632, October.
    2. Gollier Christian, 2004. "Optimal Dynamic Portfolio Risk with First-Order and Second-Order Predictability," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 4(1), pages 1-35, September.
    3. Alexandre Ziegler, 2001. "Dividend Growth Uncertainty and Stock Prices," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 137(IV), pages 579-598, December.
    4. Brennan, Michael J. & Xia, Yihong, 2000. "Dynamic Asset Allocation under Inflation," University of California at Los Angeles, Anderson Graduate School of Management qt8p95456t, Anderson Graduate School of Management, UCLA.
    5. Jianjun Miao, 2009. "Ambiguity, Risk and Portfolio Choice under Incomplete Information," Annals of Economics and Finance, Society for AEF, vol. 10(2), pages 257-279, November.

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