The Usefulness of Current Cost Information for Identifying Takeover Targets and Earning Above-Average Stock Returns

Abstract

Prior studies constructed takeover prediction models using financial variables that incorporated historical cost data. The studies report conflicting findings concerning the models' abilities to identify future takeover targets and to earn above-average returns by investing in shares of the targets. Other research has shown that financial ratios that incorporate asset replacement cost (i.e., current cost) data are useful for differentiating between takeover targets and nontargets; however, the ability to earn above-average returns was not examined.

This study combines the two tines of research by constructing a takeover prediction model in which predictor variables are constructed from current cost data. A model having similar variables was constructed from historical cost data. The models were estimated from takeovers occurring between 1981 and 1984, and the models separately identified takeover targets during the year 1985 based on a prediction sample. Stock returns were cumulated over the year 1985 for the two portfolios of predicted targets.

The results show that current cost data were useful for identifying future takeover targets and earning above-average stock returns. The current cost portfolio earned risk-adjusted returns that exceeded the returns of the entire prediction sample and the returns of the historical cost portfolio. Additionally, the models' explanatory power exceeds that which was reported for models in prior research.