Analysts’ recommendations and the market impact of the valuation methods

Abstract

Despite its importance, the informative value of the analysts’ valuation methods has not been thoroughly examined in the literature. Such an issue is relevant with regard to the concerns on analysts’ objectivity. We test whether investors’ reaction is jointly influenced by recommendations and target revisions and mainly by valuation method used because it summarizes the information considered to be relevant by the analysts. We analyse the market reaction to recommendation revisions with an event study methodology, calculating market-adjusted abnormal returns at the report release date. We run regressions to test the market impact of recommendations and target price revisions, as well as their interaction, and we then focus on testing several models to discern market reaction to distinct valuation methods. We show that market reaction is influenced by the valuation methods used in their reports. The majority of previous studies relying on commercial databases report the market reaction in relation to analysts’ recommendations, target prices or earnings forecasts, often overlooking the content of the reports and the methodology used therein. This is due to an information constraint of commercial databases, normally including only the above-mentioned synthetic variables. A notable exception is Asquith, Mikhail, and Au (2005) who find no relation between the market reaction and the valuation methods used by analysts. Compared to Asquith et al. (2005), our research uses a larger database and finds a different result. We show the market reacts differently to distinct valuation methods, without favouring the theoretically more correct ones based on discounting cash flows. We also find that the market reaction is larger when the analysts support their recommendation with more than one valuation method. Our research shows that the market pays attention to the content of the reports and analysts can be more influential when they use more valuation methodologies to cross-check their estimates.