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.

If either economic incentives or psychological phenomena cause the bias in analysts' forecasts to persist long enough, it would be potentially discoverable and exploitable by investors. quot;Exploitationquot; in this context implies that investors, through examination of historical forecasting performance, can more or less reliably estimate the direction and extent of bias, and impute unbiased estimates for themselves, given analysts' forecasts. The absence of persistence in forecast errors would suggest that analysts' own behavior ultimately quot;self-correctsquot; within a time frame that eliminates the possibility that the patterns could be exploited by investors. We use two look-back methods that capture salient features of analysts' past forecasting behavior to form quintile portfolios that describe the range of analysts' forecasting behavior. Parametric and nonparametric tests are performed to determine whether the two portfolio formation methods provide predictive power with respect to subsequent forecast errors. The findings support a conclusion that analysts' behaviors in both optimistic and pessimistic extremes do not entirely self-correct, leaving open the possibility that investors may find historical forecast errors useful in making inferences about current forecasts.

This paper examines the accuracy of European analysts' forecasts of corporate earnings. The analysis is based on a large sample of individual forecasts of annual earnings for years ending in 1987 to 1992. The bias and accuracy of the analysts' forecasts in each country are contrasted and the results show that forecasts of Dutch and, to a lesser extent, UK and German firms' earnings are relatively accurate, and that forecasts of Austrian and Scandinavian firms' earnings are particularly poor. An analysis of the full sample and selected country specific sub-samples provide results that are consistent with optimistic forecasting and over- reaction to recent information when making forecasts, that forecasts based on the firm's share price and the market wide price earnings ratio have incremental predictive value beyond that of the analysts' forecasts, and revisions of forecasts made by analysts show a systematic tendency to reduce previously forecasted changes.

Analysts' earnings forecasts are influenced by their desire to win investment banking clients. We hypothesize that the equity bull market of the 1990s, along with the boom in investment banking business, exacerbated analysts' conflict of interest and their incentives to adjust strategically forecasts to avoid earnings disappointments. We document shifts in the distribution of earnings surprises, the market's response to surprises and forecast revisions, and in the predictability of non-negative surprises. Further confirmation is based on subsamples where conflicts of interest are more pronounced, including growth stocks and stocks with consecutive non-negative surprises; however shifts are less notable in international markets

We evaluate the extent to ...