EARNINGS EXPECTATIONS, FIRM SIZE, AND THE INFORMATIVENESS OF STOCK PRICES

The notion that prices impound a wide array of information, including market expectations, has led to earnings forecast models conditioned on prices. Yet, presumably, analysts' forecasts capture both public information and certain private information not previously impounded in prices. Accordingly, price-based models are seemingly an inefficient, and less effective, source of expecta-tions. This article investigates this hypothesis using financial analysts', price-based, and naive forecasts. Results indicate that analysts' forecasts (1) are at least as accurate as price-based and naive models, and (2) yield better expectations for market tests relating returns and earnings. These inferences are robust across different information environments. The evidence suggests that analysts either possess private information or are more effective information processors, or both.     

A new coincident index of business cycles based on monthly and quarterly series

Popular monthly coincident indices of business cycles, e.g. the composite index and the Stock–Watson coincident index, have two shortcomings. First, they ignore information contained in quarterly indicators such as real GDP. Second, they lack economic interpretation; hence the heights of peaks and the depths of troughs depend on the choice of an index. This paper extends the Stock–Watson coincident index by applying maximum likelihood factor analysis to a mixed‐frequency series of quarterly real GDP and monthly coincident business cycle indicators. The resulting index is related to latent monthly real GDP. Copyright © 2002 John Wiley & Sons, Ltd.     

Do Gold Market Returns Have Long Memory?

This study examines the long memory behavior in gold returns during the post-Bretton Woods period using a new rescaled range technique. Unlike the conventional rescaled range analysis, the new rescaled range analysis is robust to short-term dependence and conditional heteroscedasticity found in the gold data. Statistical results suggest that the long memory behavior in gold returns is rather unstable. When only few observations corresponding to major political events in the Middle East, together with the Hunts event, in late 1979 are omitted, little evidence of long memory can be found.     

Are differences in firm size transitory or permanent?

An Erratum for this article has been published in Journal of Applied Econometrics 18(2) 2003, 249 Previous empirical work on corporate growth rates using cross‐section or short‐panel econometric techniques suggests that growth rates are random but that some degree of mean reversion exists. This means that size differences between firms are transitory. Another, more natural way to explore the long‐run distribution of firm sizes is to examine data on the growth of particular firms over long periods of time. Using a sample of 147 UK firms observed continually for more than 30 years, our conclusions are that growth rates are highly variable over time and that differences in growth rates between firms do not persist for very long. Further, firms show no tendency to converge to either a common size or to a pattern of stable size differences over time. These results are compared and contrasted with standard approaches that suggest that firms reach and maintain stable positions in a skewed size distribution. Copyright © 2002 John Wiley & Sons, Ltd.     

Bayesian MCMC Mapping of Quantitative Trait Loci in a Half-sib Design: a Graphical Model Perspective

Graphical models provide a powerful and flexible approach to the analysis of complex problems in genetics. While task-specific software may be extremely efficient for any particular analysis, it is often difficult to adapt to new computational challenges. By viewing these genetic applications in a more general framework, many problems can be handled by essentially the same software. This is advantageous in an area where fast methodological development is essential. Once a method has been fully developed and tested, problem-specific software may then be required. The aim of this paper is to illustrate the potential use of a graphical model approach to genetic analyses by taking a very simple and well-understood problem by way of example.