The identification of U.K. takeover targets using published historical cost accounting data Some empirical evidence comparing logit with linear discriminant analysis and raw financial ratios with industry-relative ratios

Paul Barnes*

*Corresponding author for this work

Research output: Contribution to journalArticle

41 Citations (Scopus)

Abstract

This study examines whether multivariate models using published financial data have predictive accuracy to successfully identify targets, thereby earning excess stock market returns. Although it was found that in the estimation period the important factors affecting the likelihood of a bid were stockholder profitability combined with poor sales growth, these variables were unable to successfully identify targets in the holdout sample. The empirical study also investigated whether the predictions are affected by the choice of statistical estimating technique and data form. It found that they were and that the choice depended upon the statistical assumptions of the models. The results also showed that raw financial ratios and IRRs based on the same underlying data generated significantly different forecasts using the same statistical technique.

Original languageEnglish
Pages (from-to)147-162
Number of pages16
JournalInternational Review of Financial Analysis
Volume9
Issue number2
Publication statusPublished - Jun 2000

Keywords

  • Acquisitions
  • Discriminant analysis
  • G34
  • Logit
  • Mergers
  • Prediction
  • Takeovers

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