  This paper analyses the world web of mergers and acquisitions (M&As) using a
complex network approach. We use data of M&As to build a temporal sequence of
binary and weighted-directed networks for the period 1995-2010 and 224
countries (nodes) connected according to their M&As flows (links). We study
different geographical and temporal aspects of the international M&A network
(IMAN), building sequences of filtered sub-networks whose links belong to
specific intervals of distance or time. Given that M&As and trade are
complementary ways of reaching foreign markets, we perform our analysis using
statistics employed for the study of the international trade network (ITN),
highlighting the similarities and differences between the ITN and the IMAN. In
contrast to the ITN, the IMAN is a low density network characterized by a
persistent giant component with many external nodes and low reciprocity.
Clustering patterns are very heterogeneous and dynamic. High-income economies
are the main acquirers and are characterized by high connectivity, implying
that most countries are targets of a few acquirers. Like in the ITN,
geographical distance strongly impacts the structure of the IMAN: link-weights
and node degrees have a non-linear relation with distance, and an assortative
pattern is present at short distances.
