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Title: Predicting takeover targets in the UK
Author: Wang, Wei-kang
Awarding Body: Manchester Metropolitan University
Current Institution: University of Manchester
Date of Award: 1997
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The predictive ability criterion has often been considered of value for the evaluation of the usefulness of accounting information. The purpose of this study is to investigate the ability of publicly available accounting information to predict takeover targets. This will be accomplished by using publicly available accounting information to develop a financial profile of firms which are more likely to be acquired in subsequent time periods. This study employs Palepu's (1986) methodology which corrects for three statistical flaws in prior studies, but also amends two problems with that method. In the holdout sample, the classification procedure results in classifying 85 firms to be targets and 623 to be nontargets. Of the 85 firms predicted to be targets, 6 (7.06%) are in fact targets in 1995. Of the 623 firms predicted to be nontargets, 595 (95.51%) are in fact nontargets. This finding represents a 84.89% overall prediction accuracy rates (601 out of total 708 firms are correctly classified) which is better than 45.6% reported by Palepu (1986). In predicting takeover targets, Wansley, Roenfeldt, and Cooley (1983) and Palepu (1986) reached different conclusions concerning the ability to earn abnormal returns by investing in predicting takeover targets. The study re-examines whether cumulative abnormal returns (CARs) can be achieved by investing in the predicted targets of constructed takeover prediction models. The results clearly show that the predicted target portfolio cannot make profits throughout the 250 trading days of the hold-out sample. Further, the study considers applying the model to subset of data, based on size, in order to focus more attention on potentially neglected targets. The findings is that disaggregation by firm does not significantly improve the accuracy of predicted targets and that it is also 'impossible to earn significant positive abnormal returns by investing in firms identified as potential targets by the size models. A major refinement of the study is to investigate whether cash flow data has incremental information content in predicting takeover status using information taken from standard FRS 1 in 1992. The results suggest such cash-flow information is of little value in predicting takeovers. Two methods, a two by two contingency table and a McNemar test, are used to examine the predictive ability of prediction of takeover targets. The results are consistent. The findings are that Palepu's ratios encompass cash flow ratios, and that accrual accounting data provides greater discriminatory power than that of cash flows. When the cash flow ratios are combined with Palepu's ratios the result does not encompass Palepu's ratios alone in distinguishing between targets and nontargets. Neither can the cash flows improve the overall predictive accuracy of predicting takeover targets if it is to be used in combination with accrual accounting data. In summary, the findings are that cash flow ratios have no incremental information content in predicting takeover targets.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available