Knowledge that Transforms

for providing analyst forecast data, available through the Institutional Brokers' Estimate System.These data have been provided as part of a broad academic program to encourage earnings expectation research.We also thank those companies, and the Securities and Exchange Commission, which generously provided copies of Form 20-Fs and Form 20-F filing dates for our research project.'cancelled out' in the averaging process that determines equilibrium prices" (Bamber and Cheon 1995, 418;Kim and Verrecchia 1991).Consequently, when investigating information content, price reaction and trading volume reaction may not yield identical results even for the same event (Bamber and Cheon 1995).Moreover,

We study market efficiency in an infinite-horizon model with a monopolistic insider. The insider can trade with a competitive market maker and noise traders, and observes privately the expected growth rate of asset dividends. In the absence of the insider, this information would be reflected in prices only after a long series of dividend observations. The insider chooses, however, to reveal the information very quickly, within a time converging to zero as the market approaches continuous trading. Although the market converges to strong-form efficiency, the insider's profits do not converge to zero.

The prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For example, for the persistence levels of dividend yields, the analytical correlation is 99% between the 1-and 2-year horizon estimators and 94% between the 1-and 5-year horizons, due to the combined effects of overlapping returns and the persistence of the predictive variable. Common sampling error across equations leads to ordinary least squares coefficient estimates and R2s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. The asymptotic theory is corroborated, and the analysis extended by extensive simulation evidence. We perform joint tests across horizons for a variety of explanatory variables, and provide an alternative view of the existing evidence.

This article develops and estimates a dynamic arbitrage-free model of the current forward curve as the sum of (i) an unconditional component, (ii) a maturity-specific component and (iii) a date-specific component. The model combines features of the Preferred Habitat model, the Expectations Hypothesis (ET) and affine yield curve models; it permits a class of low-parameter, multiple state variable dynamic models for the forward curve. We show how to construct alternative parametric examples of the three components from a sum of exponential functions, verify that the resulting forward curves satisfy the Heath-Jarrow-Morton (HJM) conditions, and derive the risk-neutral dynamics for the purpose of pricing interest rate derivatives. We select a model from alternative affine examples that are fitted to the Fama-Bliss Treasury data over an initial training period and use it to generate out-of-sample forecasts for forward rates and yields. For forecast horizons of 6 months or longer, the forecasts of this model significantly outperform those from common benchmark models.