We propose a general equilibrium model with multiple securities in which investors' risk preferences and expectations of dividend growth are time varying. While time varying risk preferences induce the standard positive relation between the dividend yield and expected returns, time varying expected dividend growth induces a negative relation between them. These o¤setting e¤ects reduce the ability of the dividend yield to forecast returns and eliminate its ability to forecast dividend growth, as observed in the data. The model links the predictability of returns to that of dividend growth, suggesting speci…c changes to standard linear predictive regressions for both. The model's predictions are con…rmed empirically.
We present evidence supporting the hypothesis that due to investor specialization and market segmentation, value-relevant information diffuses gradually in financial markets. Using the stock market as our setting, we find that (i) stocks that are in economically related supplier and customer industries cross-predict each other's returns, (ii) the magnitude of return cross-predictability declines with the number of informed investors in the market as proxied by the level of analyst coverage and institutional ownership, and (iii) changes in the stock holdings of institutional investors mirror the model trading behavior of informed investors. Copyright (c) 2010 the American Finance Association.
This paper provides evidence that analysts who have predicted earnings more accurately than the median analyst in the previous four quarters tend to be simultaneously less accurate and further from the consensus forecast in their subsequent earnings prediction. This phenomenon is economically and statistically meaningful. The results are robust to different estimation techniques and different control variables. Our findings are consistent with an attribution bias that leads analysts who have experienced a short-lived success to become overconfident in their ability to forecast future earnings.overconfidence, cognitive biases, analysts, earnings forecasts
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.