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Title: The use of financial ratios to predict acquisition targets : a study of UK mergers 1980-1986
Author: Al-Mwalla, Mona Mamdouh
ISNI:       0000 0001 3407 484X
Awarding Body: University of Glasgow
Current Institution: University of Glasgow
Date of Award: 1992
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Financial reporting should provide decision makers with useful information. One qualitative characteristic of useful information is its classificatory value. Prior studies in accounting, economics and finance provide evidence that balance sheet and income statement ratios can be utilised to classify economic events such as mergers and bankruptcy which are of interest to decision makers. This research examines the financial profile of U.K. firms acquired during the period 1980-1986. It also investigates whether the profile of financial characteristics of the observed firms provides a useful criterion for identifying those firms with a high probability of subsequently being acquired. The use of funds flow measures in the analysis contributes to the classification accuracy of the models when one year data was employed. Although this has been applied to bankruptcy predictions, its contribution has not been tested in any previous U.K. merger studies. The results for the univariate analysis indicate that the acquired firms during the period 1980-1986 have low profitability, high gearing ratios, low liquidity and low valuation ratios when compared with the non-acquired firms. The multivariate analysis indicates the usefulness of accounting information in merger classification when the most recent data is used. It also suggests the existence of different attributes that are important in the acquisition classification model. It provides a strong indication throughout the different stages of the analysis that the asset undervaluation hypothesis and the profitability hypothesis are the most important discriminators and not the size hypothesis as had previously been assumed.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: HG Finance