Business failure

About: Business failure is a research topic. Over the lifetime, 788 publications have been published within this topic receiving 26196 citations. The topic is also known as: flop.

Financial Ratios As Predictors Of Failure

Abstract: At the turn of the century, ratio analysis was in its embryonic state. It began with the development of a single ratio, the current ratio,' for a single purpose-the evaluation of credit-worthiness. Today ratio analysis involves the use of several ratios by a variety of users-including credit lenders, credit-rating agencies, investors, and management.2 In spite of the ubiquity of ratios, little effort has been directed toward the formal empirical verification of their usefulness. The usefulness of ratios can only be tested with regard to some particular purpose. The purpose chosen here was the prediction of failure, since ratios are currently in widespread use as predictors of failure. This is not the only possible use of ratios but is a starting point from which to build an empirical verification of ratio analysis. "Failure" is defined as the inability of a firm to pay its financial obligations as they mature. Operationally, a firm is said to have failed when any of the following events have occurred: bankruptcy, bond default, an overdrawn bank account, or nonpayment of a preferred stock dividend.3 A "financial ratio" is a quotient of two numbers, where both num-

Learning from Business Failure: Propositions of Grief Recovery for the Self-Employed

Abstract: In this paper I use the psychological literature on grief to explore the emotion of business failure, suggesting that the loss of a business from failure can cause the self-employed to feel grief—a negative emotional response interfering with the ability to learn from the events surrounding that loss. I discuss how a dual process of grief recovery maximizes the learning from business failure.

35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems

Abstract: Over the last 35 years, business failure prediction has become a major research domain within corporate finance. Numerous corporate failure prediction models have been developed, based on various modelling techniques. The most popular are the classic cross-sectional statistical methods, which have resulted in various ‘single-period’ or static models, especially multivariate discriminant models and logit models. To date, there has been no clear overview and discussion of the application of classic statistical methods to business failure prediction. Therefore, this paper extensively elaborates on the application of (1) univariate analysis, (2) risk index models, (3) multivariate discriminant analysis, and (4) conditional probability models in corporate failure prediction. In addition, because there is no clear and comprehensive analysis in the existing literature of the diverse problems related to the application of these methods to the topic of corporate failure prediction, this paper brings together all problem issues and enlarges upon each of them. It discusses all problems related to: (1) the classical paradigm (i.e. the arbitrary definition of failure, non-stationarity and data instability, sampling selectivity, and the choice of the optimisation criteria); (2) the neglect of the time dimension of failure; and (3) the application focus in failure prediction modelling. Further, the paper elaborates on a number of other problems related to the use of a linear classification rule, the use of annual account information, and neglect of the multidimensional nature of failure. This paper contributes towards a thorough understanding of the features of the classic statistical business failure prediction models and their related problems.