Brand transaction announcements and stock price volatility

Abstract

PurposeThis paper aims to investigate the potential relationship between the stock market announcement of a brand's buy and sell agreement, and the stock price trend.Design/methodology/approachThe research question was approached using a GARCH‐based statistical analysis on a sample of companies listed on the Mibtel (Italian stock exchange) that have a brand among their assets and have undertaken a purchase/sale from 2006 to 2008.FindingsAlthough the brand is believed to be an important value driver, the mere occurrence of a purchase/sale operation for this asset only occasionally leads to a reaction in the market; at any rate, the stock's volatility quite rarely depends solely on such an occurrence.Research limitations/implicationsThe statistical relevance of the analysis is limited by the observational data that it was possible to analyse. In particular, to give a positive conclusion about the influence of the brand's buy and sell agreements on a stock's return, it is necessary to have a time series of a greater number of firms. A larger availability of data might, in the future, allow a more detailed analysis and the opportunity to investigate the possible impacts of the event with relation to the business's characteristics – something that could not be carried out in this study because of the aforementioned problems.Practical implicationsResearchers and practitioners are now aware that the market does not always look upon the operations of a brand's buy and sell agreement as value‐relevant.Originality/valueThe originality of the present work lies in the fact that, to the best of one's knowledge, no other surveys were carried out on the chosen sample (i.e. the companies listed on the Italian stock market); that only a few international contributions posed the same research question; and most importantly, that the statistical methodology used can very well provide more reliable results than regression analysis, which is normally applied to such data.