Network structures and the dynamics of takeover rumours: agent-based simulations of pre-announcement stock price drift

Abstract

Takeover targets often see their stock prices rise sharply before merger or acquisition announcements, mainly because information leaks and related rumours circulate among investors. Although this pattern is well-documented, the underlying process driving such pre-bid increases is still not fully understood. This thesis rebuilds the mechanism from the bottom up: an agent-based market in which an Ignorant–Spreader–Stifler rumour process propagates over a range of networks while heterogeneous value investors and trend followers trade on perceived mispricing and recent returns. Through Monte Carlo simulations, we find a strong link between the magnitude of the run-up and the efficiency of the network topology.