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Simple Forecasts and Paradigm Shifts

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  • HARRISON HONG
  • JEREMY C. STEIN
  • JIALIN YU

Abstract

We study the asset pricing implications of learning in an environment in which the true model of the world is a multivariate one, but agents update only over the class of simple univariate models. Thus, if a particular simple model does a poor job of forecasting over a period of time, it is discarded in favor of an alternative simple model. The theory yields a number of distinctive predictions for stock returns, generating forecastable variation in the magnitude of the value-glamour return differential, in volatility, and in the skewness of returns. We validate several of these predictions empirically. Copyright 2007 by The American Finance Association.

Suggested Citation

  • Harrison Hong & Jeremy C. Stein & Jialin Yu, 2007. "Simple Forecasts and Paradigm Shifts," Journal of Finance, American Finance Association, vol. 62(3), pages 1207-1242, June.
  • Handle: RePEc:bla:jfinan:v:62:y:2007:i:3:p:1207-1242
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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