Browsing by Author "Dludla, Sambulo Siyanda"

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    nformation Asymmetry and Merger Performance on the Johannesburg Stock Exchange
    (University of the Witwatersrand, Johannesburg, 2024) Dludla, Sambulo Siyanda; Chipeta, Chimwemwe
    This study examines the impact of information asymmetry on the long-term performance of mergers and acquisitions (M&A) on the Johannesburg Stock Exchange (JSE). The empirical test evaluates the 3-year period of share performance from 2001 to 2019. An event study methodology is utilized to evaluate the relationship between information asymmetry and M&A performance after the deal's completion. The study interrogates the relationship between information asymmetry through proxies and the M&A performance measures (BHAR & CAAR) and the relationship between the deal specific variables and the M&A performance measures. The results reveal several information asymmetry proxies (SPREAD, VOLATILITY, TRADED VOLUME, and TRADED VALUE) exhibit a statistically significant relationship with one or more M&A performance measures in the panel OLS fixed effects model. However, ANALYST COVERAGE was not statistically significant for M&A performance. This suggests that information asymmetry impacts M&A transactions on the JSE on the long run. Additionally, mixed results are observed in the Generalised Method of Moments (GMM) regression. When observing deal-specific variables, the panel OLS regression emphasises their significant relationship with M&A performance, particularly against the CAAR, rejecting the null hypotheses for cash, mixed, size, leverage, and value variables at a 1% or 5% level. Controlling for the financial industry, both panel OLS regression and GMM show a significant relationship between CAAR, which is consistent with Harford's (2005) concept of M&A waves and industry clustering. This emphasises the critical role of industry dynamics on M&A performance. The results suggest that management and investors need to be aware of the information asymmetry in the market when conducting and concluding an M&A transaction. Moreover, management and investors must be aware of the information asymmetry in the market in the long run post-merger.