Learning Under Ambiguity

Larry Epstein () and Martin Schneider ()

No 497, RCER Working Papers from University of Rochester - Center for Economic Research (RCER)

Abstract: This paper considers learning when the distinction between risk and ambiguity (Knightian uncertainty) matters. Working within the framework of recursive multiple-priors utility, the paper formulates a counterpart of the Bayesian model of learning about an uncertain parameter from conditionally i.i.d. signals. Ambiguous signals capture responses to information that cannot be captured by noisy signals. They induce nonmonotonic changes in agent confidence and prevent ambiguity from vanishing in the limit. In a dynamic portfolio choice model, learning about ambiguous returns leads to endogenous stock market participation costs that depend on past market performance. Hedging of ambiguity provides a new reason why the investment horizon matters for portfolio choice.

Keywords: ambiguity; learning; noisy signals; ambiguous signals; quality information; portfolio choice; portfolio diversification; Ellsberg Paradox (search for similar items in EconPapers)
JEL-codes: D81 D83 D9 G11 G12 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cbe
Date: 2002-10, Revised 2005-03
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Related works:
Working Paper: Learning Under Ambiguity (2006)
Journal Article: Learning Under Ambiguity (2007)
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Persistent link: http://EconPapers.repec.org/RePEc:roc:rocher:497

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