This study investigates the characteristics and attributes that private equity investors prefer when selecting target acquisitions. These characteristics are examined against a matched sample of firms subject to corporate acquisitions via tender/merger offer during 2000–2009, across seven countries: Australia, Canada, the United Kingdom, the USA, France, Germany and Sweden. We show that firm-specific characteristics are more influential in target selection than external or institutional variables. In particular, private equity targets exhibit lower stock volatility and long-term growth prospects, are larger, and have greater abnormal operating income relative to tender/merger offer target firms. Further, private equity bidders exhibit ‘home bias’, implying that familiarity motivates target selection. Institutional factors remain largely insignificant across all tests.

Exposure Draft 8 (ED 8) Operating Segments was introduced to replace the revised IAS 14 Segment Reporting and to align segment reporting requirements with their United States counterparts in SFAS 131. ED 8 proposed material changes in the identification, measurement and disclosure of corporate segment information. In response to the ED, there were 182 comment letters from various respondents including firms, professional associations, regulatory authorities and accounting firms. This paper investigates the influence of firm characteristics such as size, performance, and number of segments on firms’ lobbying position choices on ED 8. Results reveal that larger firms were more likely to lobby in favour of ED 8, and firms with two or fewer segments were more likely to lobby against ED 8. It also provides evidence that relatively profitable firms operating in an environment of low competition are less inclined to support ED 8.

This paper examines, within the Australian market, the extent to which legal insider trades are information driven, premised on a disconnect between the market's assessment of firm value, and that of more informed insiders. I address the notion that insiders, endowed with superior information about their firm, are contrarian, reflecting disagreement with the market's current perception of firm value, and also use this knowledge by trading in advance of future performance indicators not known to the market. I find that insiders, directors in particular, are contrarian traders; they buy when their firm is in the bottom tercile according to prior returns (losers), and sell if their firm is a prior winner. Further, this behaviour is exacerbated if the firm is a value (glamour) stock. Finally, I show that even after controlling for the aforementioned factors, directors engage in net buying prior to positive accounting performance changes in the subsequent and following 12 month periods.

Researchers commonly use industry classifications as a means of identifying peer companies to use as a performance benchmark. We describe the structure of commonly used sources of industry classification data available for Australian listed companies, both static and in time series. Next, we run a series of experiments matching firms according to GICS classification data presented in time series versus static data sources. Our results indicate that performance measures are better specified when matching on GICS data from a dynamic relative to a static source. The results of our power tests also underscore the importance of using dynamic industry data.

This study discusses the differences in company identification across sources of Australian data and raises important issues which should be considered prior to merging across databases. In particular, we show that the practice among accounting databases of overwriting prior identifiers used by a given company, with its most recent, results in failure to match data which actually exists. We suggest a method for reconciling these differences and show that our method results in a match rate of 97 percent with the Aspect company identification file, and 94 percent after missing accounting data is considered. This contrasts with a match rate of only 71 percent when performing a direct merge.