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.     

Daylight saving effect

Kamstra et al. [Kamstra, M.J., Kramer, L.A., Levi, M.D., 2000. Losing sleep at the market: the daylight saving anomaly. The American Economic Review 90, 1005–1011] argue that the mean weekend return following the changes in daylight saving time is less than the mean weekend return throughout the rest of the year. Opposing studies, such as Pinegar [Pinegar, J.M., 2002. Losing sleep at the market: comment. The American Economic Review 92, 1251–1256), reason that the observed results depend upon methodology. We extend the ongoing discussions by providing further evidence for equity markets and bond markets in Germany and across Europe. We further demonstrate that the daylight saving effect does not serve as a potential rationale for the weekend effect.     

中国负债知多少？

【美国《华尔街日报》7月23日】中国的隐性债务可能成为一大麻烦。     

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.     

Bank and Business Performance Measurement

Given the objective of maximizing the wealth of existing shareholders, this paper discusses some of the issues that arise in attempting to measure the performance of individual businesses within a bank. The paper describes two return measures – return on assets within a business and the return on the 'equity' of an individual business – and discusses the appropriate bench–marks. The paper ends with a discussion of the cost of unused allocated capital and the appropriate performance metric.
(J.E.L.: G30, G31).     

Pre-Harvest Price Expectations for Corn: The Information Content of USDA Reports and New Crop Futures

This article examines the puzzle of why futures prices continue to react to USDA crop reports despite the fact that reports appear to be no longer "newsworthy," that is, provide no better production estimates than private forecasts. The information value of reports is measured in terms of their influence on rational agents' harvest-time corn price expectations, which are uncovered using a Hamilton-type modeling approach. Results show that reports are still "newsworthy," as they would contribute to agents' price expectations if released a day early. Thus futures price reactions, which closely reflect price expectations, are rational and consistent with efficient markets hypothesis.     

Is your vision consistent?: A method for checking, based on scenario concepts

Common sense tells us that the future is an essential element in any strategy. In addition, there is a good deal of literature on scenario planning, which is an important tool in considering the future in terms of strategy. However, in many organizations there is serious resistance to the development of scenarios, and they are not broadly implemented by companies. But even organizations that do not rely heavily on the development of scenarios do, in fact, construct visions to guide their strategies. But it might be asked, what happens when this vision is not consistent with the future? To address this problem, the present article proposes a method for checking the content and consistency of an organization's vision of the future, no matter how it was conceived. The proposed method is grounded on theoretical concepts from the field of future studies, which are described in this article. This study was motivated by the search for developing new ways of improving and using scenario techniques as a method for making strategic decisions. The method was then tested on a company in the field of information technology in order to check its operational feasibility. The test showed that the proposed method is, in fact, operationally feasible and was capable of analyzing the vision of the company being studied, indicating both its shortcomings and points of inconsistency.     

Nonlinear dynamics and competing behavioral interpretations: Evidence from intra‐day FTSE‐100 index and futures data

Extant empirical research has reported nonlinear behavior within arbitrage relationships. In this article, the authors consider potential nonlinear dynamics within FTSE‐100 index and index‐futures. Such nonlinearity can be rationalized by the existence of transactions costs or through the interaction between informed and noise traders. They consider several empirical models designed to capture these alternative dynamics. Their empirical results provide evidence of a stationary basis term, and thus cointegration between index and index‐futures, and the presence of nonlinear dynamics within that relationship. The results further suggest that noise traders typically engage in momentum trading and are more prone to this behavior type when the underlying market is rising. Fundamental, or arbitrage, traders are characterized by heterogeneity, such that there is slow movement between regimes of behavior. In particular, fundamental traders act more quickly in response to small deviations from equilibrium, but are reluctant to act quickly in response to larger mispricings that are exposed to greater noise trader price risk. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:343–368, 2006     

Volatility clustering and the bid–ask spread: Exchange rate behavior in early Renaissance Florence

This paper investigates the nature and behavior of the domestic (local) currency market that existed in Florence (Italy) during the late 14th and early 15th centuries (a.k.a. the Early Renaissance). We find that the extant volatility and microstructure models developed for modern asset markets are able to describe the statistical volatility properties observed for the denaro-florin exchange rate. Volatility is clustered and is related to the bid–ask spread. This supports the notion that, although there are huge social, industrial and technological differences between capitalism then and now, individuals trading financial assets in an organized venue behave in a similar manner.