Safety First, Learning Under Ambiguity, and the Cross-Section of Stock Returns
Ariel Viale (),
Luis Garcia-Feijoo and
Review of Asset Pricing Studies, 2014, vol. 4, issue 1, 118-159
We examine the empirical implications of learning under ambiguity for the cross-section of stock returns. We introduce a theoretically-motivated ambiguity measure and find that ambiguity is priced in the cross-section of average stock returns. Ambiguity is not subsumed by state variables known to predict stock returns, nor by value, size, and momentum factors. In R-squared comparative tests, a model that takes ambiguity into account performs better than empirical implementations of the Bayesian learning model, the intertemporal CAPM, and the four-factor model of Fama and French (1993) and Carhart (1997).
JEL-codes: G12 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:oup:rasset:v:4:y:2014:i:1:p:118-159.
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