Day-of-the-Week Effects in the Long-Run Performance of Initial Public Offerings

This study examines the influence of day-of-the-week patterns in security returns on long-run IPO underperformance. Comparisons are made between the IPOs in Ritter's [20] database, and a constructed set of matching firms based on SIC code and size, using NYSE, AMEX, and NASDAQ securities. It is found that virtually all of the IPO underperformance occurs on Mondays and Tuesdays and that the degree of underperformance significantly differs from other days. Thus, a common explanation may exist for the general day-of-the-week pattern in security returns and IPO long-run underperformance.     

Classification and aggregation: An application to industrial classification in cps data

In this paper we offer a method for deciding how to aggregate a set of elementary industries. The method is then applied to the problem of estimating a wage equation that allows for industry-specific effects. Our method explicitly formalizes the trade-off between goodness-of-fit and parsimony implicit in an aggregation problem. By varying the parameter of the assumed loss function, one obtains a whole sequence of aggregation levels. Further, the resulting sequence is consistent; that is, groupings formed at one level of aggregation will never be undone when one aggregates further.     

PROCYCLICAL RETAIL LABOUR PRODUCTIVITY*

The influence of lagged adjustment and consumer spending on retail labour productivity is investigated. Both influences result in a procyclical productivity pattern.     

Service Competitiveness – An Anglo-US Study

This article reports on the latest in a series of international comparisons of management practices and performance outcomes of industries in various countries. Here, it is the service industries in the UK and the US which come under the microscope. Among the companies surveyed, there were more world-class performers in the US than the UK, but also more low performers. The concluding part of the article is diagnostic – the authors also suggest measures which could improve performance.     

Pricing Options on an Asset with Bernoulli Jump-Diffusion Returns

The price movements of certain assets can be modeled by stochastic processes that combine continuous diffusion with discrete jumps. This paper compares values of options on assets with no jumps, jumps of fixed size, and jumps drawn from a lognormal distribution. It is shown that not only the magnitude but also the direction of the mispricing of the Black-Scholes model relative to jump models can vary with the distribution family of the jump component. This paper also discusses a methodology for the numerical valuation, via a backward induction algorithm, of American options on a jump-diffusion asset whose early exercise may be profitable. These cannot, in general, be accurately priced using analytic models. The procedure has the further advantage of being easily adaptable to nonanalytic, empirical distributions of period returns and to nonstationarity in the underlying diffusion process.