Essays on analyst growth forecasts and stock market valuations

Essay 1: stock market reactions to analysts' long-term growth forecast revisions and post-revision price adjustments. This study examines the information content of analysts' long-term growth forecasts (LTGF) in terms of market reactions to LTGF revisions and post-revision price drifting. We find the following results. First, on average, LTGF revisions trigger significant stock price changes in the days surrounding revisions after controlling for concurrent analyst information. Price reactions are stronger to revisions immediately following reporting/disclosure events (e.g., earnings announcements or management forecasts) and for firms with higher growth and/or profitability. Second, stock prices continue to adjust in the months following revisions, with the direction of adjustment depending on whether revisions are reinforced or contradicted by news in subsequent earnings announcements, management forecasts, or LTGF revisions, and the speed of adjustment depending on a firm's information environment (size and coverage) and analyst ability (prior forecast accuracy and experience). Furthermore, LTGF revisions affect the extent of market responses to subsequent earnings announcements, depending on whether or not revisions are in the same direction as the subsequent earnings news. Third, certain attributes of LTGF, issuing analysts, and the firm covered have ability to predict the direction of subsequent earnings news, and thus they help to predict the direction of post-revision price adjustment.;Essay 2: growth forecast errors and value premium: a test of errors-in-expectations explanation. Value stocks have historically outperformed growth stocks in major financial markets. Prior studies attribute this phenomenon to risk, measurement bias or mispricing (e.g., errors-in-expectations). Some studies use errors in short-term earning forecasts as proxies for expectation errors, but their results are not consistent with errors-in-expectations explanation for value premium. Based on analysts' growth forecasts and actual growth rates, this study constructs a measure (relative error of growth forecast, REGF) to test errors-in-expectations explanation for value premium. The results show optimistic (pessimistic) REGF for low (high) BM stocks/portfolios. Time-varying returns to BM strategy can be significantly explained by time-varying REGF differences between high BM and low BM portfolio. After controlling for REGF, portfolio returns to BM strategy no longer persistently exist. After including REGF in regression models, BM ratios' explanation power for future stock return decreases or even disappears. In 12 months before BM portfolio constructions, REGF of high BM portfolio increases and REGF of low BM portfolio decreases. In 36 months after BM portfolio constructions, the trend reverses. Overall, this study shows that growth forecasts are systematically more pessimistic (optimistic) for value (growth) stocks. This systematic bias can explain the excess return to value strategy. These results are consistent with errors-in-expectations explanation for value premium.