Justice Kyei-Mensah

We re-examine the abnormal returns (ARs) around merger announcements using a large sample of 8,945 announcements. We estimate the ARs using the Carhart (1997) four-factor model under the standard ordinary least square (OLS) method and the Glosten et al.’s (1993) asymmetric GARCH specification (hereafter, GJR-GARCH). Under the OLS method, acquirers do not generate significant cumulative ARs (CARs) in line with prior work. Our new results, however, show that under the GJR-GARCH estimation, acquirers generate positive and significant cumulative CARs. We attribute the gains to the use of the GJR-GARCH estimation method, as the GJR-GARCH method is more effective in capturing conditional volatility and asymmetry in the excess returns.

The paper examines market liquidity and size of 396 US firms engaged in mergers and acquisitions (M&A). The announcement-period returns are estimated using Carhart’s four-factor model and estimated using two regression specifications. The results suggest that the return continuation depends on the degree of liquidity and the firm size. The positive and significant cumulative abnormal returns (CARs) under both the specifications with exception to the acquiring firms are found. Under the generalized autoregressive conditional heteroskedasticity (GARCH) model due to Glosten et al. (1993), hereafter, GJR-GARCH, the pre-event CARs are significant and persistent in contrast to the estimation based on the ordinary least squares (OLS) regression. This suggests possible leakage of information prior to an event announcement and further lends support to the contract theory of information asymmetry and signalling. It is also found that the target firms exhibit positive and significant post-event CARs for the mid-cap stocks. Whereas, for the acquirer firms, the post-event CARs for the small trading volume stocks are positive and significant. The results are robust to bootstrapping simulations.