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Bias in European Analysts' Earnings Forecasts

机译:欧洲分析师收益预测中的偏见

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Forecasting company earnings is a difficult and hazardous task. In an efficient market where analysts learn from past mistakes, there should be no persistent and systematic biases in consensus earnings accuracy. Previous research has already established how some (single) individual-company characteristics systematically influence forecast accuracy. So far, however, the effect on consensus earnings biases of a company's sector and country affiliation combined with a range of other fundamental characteristics has remained largely unexplored. Using data for 1993-2002, this article disentangles and quantifies for a broad universe of European stocks how the number of analysts following a stock, the dispersion of their forecasts, the volatility of earnings, the sector and country classification of the covered company, and its market capitalization influence the accuracy of the consensus earnings forecast.
机译:预测公司收益是一项艰巨而危险的任务。在一个高效的市场中,分析师可以从过去的错误中吸取教训,共识收益的准确性不应存在持久和系统的偏差。先前的研究已经确定了某些(单个)个人公司特征如何系统地影响预测准确性。但是,到目前为止,公司部门和国家/地区的隶属关系以及一系列其他基本特征对共识收益偏差的影响在很大程度上尚待探索。本文使用1993年至2002年的数据,对欧洲股票的广泛领域进行了梳理和量化,分析了跟随股票的分析师人数,其预测的离散程度,收益的波动性,所涵盖公司的行业和国家/地区分类,以及它的市值影响共识收益预测的准确性。

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