The financial performance of small and medium sized companies: A model based on accountancy data is developed to predict the financial performance of small and medium sized companies.
AuthorEarmia, Jalal Y.
Rights© 1991 Earmia, J. Y. This work is licensed under a Creative Commons Attribution-Non-Commercial-Share-Alike License (http://creativecommons.org/licenses/by-nc-nd/2.0/uk).
InstitutionUniversity of Bradford
DepartmentPost-graduate School of Industrial Technology
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AbstractThis study is concerned with developing a model to identify small-medium U.K. companies at risk of financial failure up to five years in advance. The importance of small companies in an economy, the impact of their failures, and the lack of failure research with respect to . this population, provided justification for this study. The research was undertaken in two stages. The first stage included a detailed description and discussion of the nature and role of small business in the UK economy, heir relevance, problems and Government involvement in this sector, together with literature review and assessment of past research relevant to this study. The second stage was involved with construction of the models using multiple discriminant analysis, applied to published accountancy data for two groups of failed and nonfailed companies. The later stage was performed in three parts : (1) evaluating five discriminant models for each of five years prior to failure; (2) testing the performance of each of the .five models over time on data not used . in their construction; (3) testing the discriminant models on a validation sample. The purpose was to establish the "best" discriminant model. "Best" was determined according to classification ability of the model and interpretation of variables. Finally a model comprising seven financial ratios measuring four aspects of a company's financial profile, such as profitability, gearing, capital turnover and liquidity was chosen. The model has shown to be a valid tool for predicting companies' health up to five years in advance.
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