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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.
Earmia, Jalal Y.
Earmia, Jalal Y.
Publication Date
2009-09-08T14:17:55Z
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The University of Bradford theses are licenced under a Creative Commons Licence.
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Institution
University of Bradford
Department
Post-graduate School of Industrial Technology
Awarded
1991
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Abstract
This 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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Type
Thesis
Qualification name
PhD