Stock liquidity, firm size and return persistence around mergers and acquisitions announcement

  • 121 Views
  • 5 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

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.

view full abstract hide full abstract
    • Table 1. Bootstrapping simulations of average cumulative measures for target and acquirer firms around merger announcements
    • Table 2. ARs and CARs measure for target and acquirer firms around mergers announcements using the four-factor CAPM under the OLS estimation method and the GJR-GARCH estimation method
    • Table 3. Cumulative ARs measures around mergers announcements group by market capitalization value for target and acquirer firms
    • Table 4. Cumulative ARs measures around merger announcements group by trading volume for target and acquirer firms
    • Table A1. Descriptive statistics of explanatory variables