This study examines how the winsorization procedure affects the performance of regression‐based earnings forecasting models. I find that the impact is multifaceted and depends principally on three factors: the level of data errors in the tails, the characteristics of firms affected by the process, and the use of scaling. For a non‐GAAP earnings yield specification, where data input errors exist, winsorization changes the information set in a non‐systematic way and helps to improve the performance of regression‐based forecasts, especially when the least squares estimator is employed. However, for a non‐GAAP earnings per share specification, with fewer data input errors found in the tails of the distribution, winsorization has a particularly strong effect on very large companies, lowering the economic value of earnings predictions. I observe similar results for corresponding GAAP earnings specifications. Robust estimators, such as least absolute deviation, high breakdown‐point and Theil‐Sen, appear to be a more effective solution than winsorization. Their earnings forecasts consistently yield significant positive abnormal returns across non‐GAAP and GAAP earnings specifications.

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This paper investigates the informativeness and value relevance of analyst target prices in the context of mergers and acquisitions. Our results indicate that firms with high 12-month ahead target prices relative to current stock prices are more likely to become a takeover target and offer premium, and acquirers' announcement returns are positively associated with firms' target price premium. We also show that a long-short trading strategy formed on target prices and firms' takeover likelihood generates economically significant returns. Our results are robust to a battery of additional analysis, and the informativeness of target prices is not subsumed by other analyst forecast outputs such as earnings forecasts and recommendations. Overall, our findings suggest that analysts convey valuable information through target price forecasts, which are useful for participants in the corporate takeover markets.

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