Abstract
AbstractIn empirical equity asset pricing, the stochastic discount factor (SDF) is implicitly modeled as a linear function of equity factors and is influenced by the empirical properties of the factor returns. We investigate the pricing error introduced by a misspecified SDF which ignores each of the following established empirical phenomena: autocorrelation, dynamics of covariances, dynamics of correlations, and heavy tails for the conditional factor return distribution. We consider near-linear SDFs and nonlinear specifications characterized by a high degree of risk aversion. We find that assuming constant covariances or constant correlations can significantly overprice certain equity portfolios at all risk-aversion levels and that ignoring fat tails can lead to large pricing errors for some derivative assets for highly nonlinear SDFs.
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