Are Analysts’ Loss Functions Asymmetric?

Recent research suggests that optimistically biased earnings forecasts issued by analysts are attributable to analysts minimizing symmetric, linear loss functions. We test an alternative explanation, namely that analysts have asymmetric loss functions. Theory predicts that if loss functions are asymmetric then forecast error bias depends on forecast error variance, but not necessarily on skewness. We find the ex ante forecast error variance is a significant determinant of forecast error and that, after controlling for variance, the sign of the coefficient on skewness is opposite to that found in prior research. Our results are thus consistent with financial analysts having asymmetric loss functions. Further analysis reveals that forecast bias varies systematically across characteristics that capture systematic variation in forecast error variance and skewness, i.e., book-to-market and market capitalization. Within portfolios formed on these bases, forecast error variance continues to play a dominant role in explaining forecast error.