Dynamic Asset Allocation with Ambiguous Return Predictability

Hui Chen (), Nengjiu Ju and Jianjun Miao

No wp2009-015, Boston University - Department of Economics - Working Papers Series from Boston University - Department of Economics

Abstract: 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.

Keywords: generalized recursive ambiguity utility; ambiguity aversion; model uncertainty; learning; portfolio choice; robustness; return predictability (search for similar items in EconPapers)
JEL-codes: D81 D83 E21 G11 (search for similar items in EconPapers)
Pages: 46
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Citations: View citations in EconPapers (11)

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Journal Article: Dynamic Asset Allocation with Ambiguous Return Predictability (2014)
Working Paper: Dynamic Asset Allocation with Ambiguous Return Predictability (2009)
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