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Dynamic Asset Allocation with Ambiguous Return Predictability

  • Hui Chen

    ()

    (MIT Sloan School of Management)

  • Nengjiu Ju

    ()

    (Department of Finance, the Hong Kong University of Science and Technology)

  • Jianjun Miao

    ()

    (Department of Economics, Boston University)

We study an investor's optimal consumption and portfolio choice problem when he confronts with two possibly misspecified submodels of stock returns: one with IID returns and the other with predictability. We adopt a generalized recursive ambiguity model to accommodate the investor's aversion to model uncertainty. The investor deals with specification doubts by slanting his beliefs about submodels of returns pessimistically, causing his investment strategy to be more conservative than the Bayesian strategy. This effect is large for high and low values of the predictive variable. Unlike in the Bayesian framework, the hedging demand against model uncertainty may cause the investor's stock allocations to first decrease sharply and then increase with his prior probability of the IID model, even when the expected stock return under the IID model is lower than under the predictability model. Adopting suboptimal investment strategies by ignoring model uncertainty can lead to sizable welfare costs.

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Paper provided by Boston University - Department of Economics in its series Boston University - Department of Economics - Working Papers Series with number wp2009-015.

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Handle: RePEc:bos:wpaper:wp2009-015
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