No abstract

This paper assesses the importance of the role of prices as aggregators of private information in the S&P 500 futures market. We estimate primitive parameters of the Hellwig (1980) noisy rational expectations model, when both prices and terminal values are observable. The variance-covariance parameters governing futures prices and terminal values can be inverted to obtain estimates of the primitive parameters, including the precision of private information and the variance of liquidity motivated trades. We also estimate coefficients in the linear price conjecture, weights that agents place on different sources of information, and the informativeness of prices. We find that the variance of the error term in agents' private signals is several orders of magnitude larger than the variance of liquidity motivated trades. But in a large market prices are still so informative that the market as a whole appears to weight them more than prior beliefs.

Noise in prices, Measuring speculation, Herding not due to information, Momentum trading, Investor over-reaction, D83, D84, G12, G14,

We develop parametric estimates of the imitation-driven herding propensity of analysts and their earnings forecasts. By invoking rational expectations, we solve an explicit analyst optimization problem and estimate herding propensity using two measures: First, we estimate analysts' posterior beliefs using actual earnings plus a realization drawn from a mean-zero normal distribution. Second, we estimate herding propensity without seeding a random error, and allow for nonorthogonal information signals. In doing so, we avoid using the analyst's prior forecast as the proxy for his posterior beliefs, which is a traditional criticism in the literature. We find that more than 60 percent of analysts herd toward the prevailing consensus, and herding propensity is associated with various economic factors. We also validate our herding propensity measure by confirming its predictive power in explaining the cross-sectional variation in analysts' out-of-sample herding behavior and forecast accuracy. Finally, we find that forecasts adjusted for analysts' herding propensity are less biased than the raw forecasts. This adjustment formula can help researchers and investors obtain better proxies for analysts' unbiased earnings forecasts.Gr egarisme ou dissidence? Estimations relatives a la propension des analystes au ralliement dans la pr evision des r esultats R ESUM ELes auteurs elaborent des estimations param etriques de la propension au ralliement (gr egarisme) induite par l'imitation que manifestent les analystes et leurs pr evisions de r esultats. En recourant aux attentes rationnelles, ils r esolvent un probl eme explicite d'optimisation avec lequel doit composer l'analyste et estiment la propension au ralliement a l'aide de deux mesures : en premier lieu, ils estiment les opinions a posteriori des analystes en utilisant les r esultats r eels ainsi qu'une r ealisation tir ee d'une distribution normale a moyenne z ero; en second lieu, ils estiment la propension au ralliement sans introduire d'erreur al eatoire, en