Empirical Models of Analyst Forecasts PDF Download

Author: Youfei Xiao
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Languages : en
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Book Description
This dissertation is comprised of two studies on analyst forecasts. The first study provides empirical evidence about the objective function underlying analysts' choice of forecasts. Assumptions about sell-side analysts' objective function are critical to empirical researchers' understanding of their incentives and resulting behavior. In contrast to approaches used in previous papers which rely exclusively on statistical properties of forecasts, I compare theoretical models with alternate objective functions based on their ability to explain observed forecasts. A linear loss objective function which incorporates the effect future analysts' actions on analysts' deviation from peer forecasts is best rationalized by the data. I find that assumptions about the objective function have a substantial impact on the conclusions from empirical tests about analysts' incentives and behavior. The second study provides empirical estimates of uncertainty and disagreement about future earnings that underly analyst forecast dispersion. A parsimonious model which assumes that analysts' payoffs are jointly determined by forecast error and deviation from consensus reproduces many of the descriptive facts observed about forecast dispersion in the data. The strategic behavior that arises from the model distorts both the levels of forecast dispersion and the sensitivity of the measure with respect to cross-sectional variation in uncertainty. The estimated parameters perform better at predicting forecast dispersion out-of-sample than approaches based solely on regressions that use firm characteristics. Counterfactual simulations indicate that analysts' strategic incentives, together with the sequential forecast setting, plays a first-order role in determining forecast dispersion relative to the firm's information environment. The model-implied estimates of earnings uncertainty exhibit a substantially less negative association with future returns relative to the association generated by forecast dispersion. This finding partially reconciles the findings from previous studies with theories about the asset pricing implications of uncertainty and disagreement.