Incomplete Information in a Long Run Risks Model of Asset Pricing
We study the effects of incorporating incomplete information in the recently developed long run risks model of asset pricing. Studying the effects of incomplete information in such a setting is tractable, especially in the homoskedastic case with no fluctuating economic uncertainty. The incomplete information model is solved using approximate analytical methods as in the complete information framework analyzed in the literature. Model implications on moments of endogenous variables of interest including rates of return are compared in the long run risks model with and without incomplete information.
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