收益偏差和分析师预测偏差

Joanna S. Wu, Zhaoyang Gu
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引用次数: 437

摘要

统计上最优的预测不一定是无偏的。如果分析师的目标是通过最小化平均绝对预测误差来提供最准确的预测,那么最优预测是中位数而不是平均收益。当收益分布偏斜时,中位数与平均值不同,观察到预测偏差。因此,分析师预测偏差可能是分析师努力提高预测准确性与收益分配偏差相结合的自然结果。我们发现,盈利偏度解释了分析师预测偏差在不同公司、不同财政季度和不同时间的显著差异。此外,市场似乎至少部分理解了由偏度引起的偏差,并进行了相应调整。我们的解释的一个显著特征是,我们不仅预测了盈利负偏的公司的乐观情绪,而且预测了盈利正偏的公司的悲观情绪,从而为分析师预测偏差提供了更连贯的解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Earnings Skewness and Analyst Forecast Bias
Statistically optimal forecasts need not be unbiased. If analysts' objective is to provide the most accurate forecast through minimizing the mean absolute forecast error, the optimal forecast is the median instead of the mean earnings. When earnings distribution is skewed, the median is different from the mean and forecast bias is observed. Thus, analyst forecast bias could be a natural result of analysts' effort to improve forecast accuracy combined with skewed distribution of earnings. We find that earnings skewness explains a significant amount of variation in analyst forecast bias across firms, across fiscal quarters and across time. Moreover, the market appears to understand at least part of the skewness-induced bias and adjusts accordingly. One salient feature of our explanation is that we predict not only forecast optimism for firms with negatively skewed earnings, but also pessimism for firms with positively skewed earnings, thus providing a more coherent explanation of analyst forecast bias.
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