Predicting informed trading at merger announcements

Abstract

Purpose – This paper aims to propose a method of forecasting the level of informed trading at merger announcements by permitting liquidity traders to adjust their trading based upon signals from informed traders. Informed traders typically take advantage of their knowledge of forthcoming mergers by trading heavily at announcement. For cash mergers, they respond to a positive signal by purchasing stock, and for stock mergers, they respond to a negative signal by selling stock. In response, exchanges (market makers) set wider spreads (charge higher transaction fees) for informed buyers. Uninformed traders are subject to such excessive fees unless they can accurately predict the period during which such fees are charged. Design/methodology/approach – This paper proposes a technique by which uninformed traders may make predictions by creating a vector autoregressive framework that links informed and liquidity trading through price changes. Findings – For cash mergers, transaction fees remained excessive for days −1 to +1. For stock mergers, fees remained high on days −1 to +1, started declining on days 2 and 3, and vanished on days 4 and 5. Research limitations/implications – Most theoretical models of informed trading have viewed informed trading and liquidity trading as tangentially linked. This study finds a direct link between these two trading activities. Practical implications – Uninformed traders may wish to limit their trading until after day +1 for both types of mergers. Originality/value – This paper defines the time period during which transactions costs for traders are at the maximum level. Short sellers have more information about the direction of stock movements and may sell during days of informed selling set forth by this study and repurchase stock afterwards.