Uncertainty of M&As under asymmetric estimation
Journal of Business Research, ISSN: 0148-2963, Vol: 122, Page: 774-793
2021
- 4Citations
- 47Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Mergers and acquisitions (M&As) are often surrounded by uncertainty since they do not always deliver the anticipated results. The uncertainty ascribed to the outcomes of M&As is not a boundary concept, rather guides firms’ decision in favour of or against undertaking M&As. Typically, M&As suffer from estimation biases. Moreover, M&As are always treated synonymously as a single entity. Thus, evaluating M&A as a single event under traditional stationary specifications is not adequate for capturing the disaggregate effect of an individual event. This study examines announcement returns of both events individually under the asymmetric specification. Asymmetric specification captures the variance of uncertainty associated with the event outcome for each set of events. The findings further document acquirers (acquisition sample) register pre-announcement wealth loss, but not so with mergers. The cross-sectional analysis indicates that the announcement returns under asymmetric specification are associated with the deal characteristics of both sets of events, except deal premium.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S014829632030463X; http://dx.doi.org/10.1016/j.jbusres.2020.07.029; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85089152480&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S014829632030463X; https://dx.doi.org/10.1016/j.jbusres.2020.07.029
Elsevier BV
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