Impact of the Financial Crisis on the Performance of European Acquisitions

This study looks at the impact of the recent financial crisis on the short-term performance of European acquisitions. We use institutional theory and transaction cost economic theory to study whether bidders derive lower or higher returns from acquisitions announced after 2008. We investigate shareholders’ stock price reaction to 2245 deals which occurred during 2004–12 across 22 European Union countries. Our results from both univariate and multivariate analysis show that the deals announced in the post-crisis period, corresponding to the period of economic recession, generate higher returns to shareholders as compared to acquisitions announced in the pre-crisis period. We also test the relevance of the Economic and Monetary Union (EMU), that is, the Eurozone, to this value accrual during the recessionary period. We observe that non-EMU transactions obtain significantly higher gains vis-à-vis EMU transactions in the post-crisis years. Overall, announcement returns of European acquisitions have been affected by the financial crisis and the global recession; and companies that target countries with different currency regimes are likely to generate better returns from their acquisitions.

Multivariate Appoximations to Portfolio Return Distribution

This article proposes a three-step procedure to estimate portfolio return distributions under the multivariate Gram-Charlier (MGC) distribution. The method combines quasi maximum likelihood (QML) estimation for conditional means and variances and the method of moments (MM) estimation for the rest of the density parameters, including the correlation coefficients. The procedure involves consistent estimates even under density misspecification and solves the so-called ‘curse of dimensionality’ of multivariate modelling. Furthermore, the use of a MGC distribution represents a flexible and general approximation to the true distribution of portfolio returns and accounts for all its empirical regularities. An application of such procedure is performed for a portfolio composed of three European indices as an illustration. The MM estimation of the MGC (MGC-MM) is compared with the traditional maximum likelihood of both the MGC and multivariate Student’s t (benchmark) densities. A simulation on Value-at-Risk (VaR) performance for an equally weighted portfolio at 1% and 5% confidence indicates that the MGC-MM method provides reasonable approximations to the true empirical VaR. Therefore, the procedure seems to be a useful tool for risk managers and practitioners.