A recent issue of the Journal of Financial Economics (June/September 1978) is devoted to reporting anomalous evidence regarding market efficiency. This study may qualify under the same heading. Here we examine the market response to information about firms whose future is assessed as being extremely problematic.

Despite the proliferation of banking services, the basic commercial and industrial lending process remains the lifeblood of commercial banks and other banking institutions. The lending process is a relatively straightforward series of activities involving two principal parties whose association ranges from the initial loan request to the successful or unsuccessful repayment of the loan. Most students of banking would agree that the process is an interdependent one, but the exact dependencies are rarely articulated in a rigorous manner. One of the purposes of this paper is to investigate the association between at least two important aspects of the lending process, namely, the credit evaluation stage and the sequence of events that describes and quantifies the charge-off and subsequent recovery experience.

In a recent article in this Journal Joy and Tollefson [10] (hereafter J&T) critically analyzed discriminant analysis and its application to bankruptcy analysis. The authors make several interesting points and provide a useful discussion of the application of this statistical technique in finance. There are, however, three aspects of their presentation which need further elaboration. These relate to their discussions of (1) the difference between the stability of the discriminant model and its predictive ability, (2) the alternative methods of making inferences about the relative discriminatory power of variables, and (3) the reference statistics to use in assessing classification efficiency. In commenting on these points we will make use of the data from the Altman [1] study as did J&T.

The focus of our study concerns the information effect of newly reported data. Our time frame of reference is the period after the data become available. The information we analyze is generated by a multivariate model which utilizes publicly available data. We concentrate on an extremely poor performing group of companies where the new information indicates a change in status from a going concern to a potential bankruptcy; i.e., the firms possess characteristics similar, to other firms which were bankrupt in the past. Our sample, however, is comprised only of firms which, in fact, did not fail.

The purpose of this research is to develop a model for determining the credit worthiness of commercial loan applicants in a particular troubled industrial sector of France. The model is developed with the assistance of Banque de France, which serves tne central banking function in a banking environment that has become increasingly competitive in recent years. The research assesses the combined potential of traditional financial statement analysis with several relatively modern statistical procedures to aid the commercial loan officer.

This study is another attempt to analyze the behavior of common stock prices. In the last decade, and even before that, literature has spewed forth an abundant supply of studies in this area, from random walkers, to optimum portfolioers, to performance measurers. Terms such as risk and return, variance and covariance, and variability and volatility proliferate journal pages and our daily conversations.