Shareholders wealth and mergers and acquisitions (M&AS)

Justice Kyei-Mensah; Chen Su; Nathan Lael Joseph

doi:10.21511/imfi.14(3).2017.02

Shareholders wealth and mergers and acquisitions (M&AS)

Justice Kyei-Mensah^*, Chen Su, Nathan Lael Joseph

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

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) fourfactor 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.

Original language	English
Pages (from-to)	15-24
Number of pages	10
Journal	Investment Management and Financial Innovations
Volume	14
Issue number	3
Early online date	4 Oct 2017
DOIs	https://doi.org/10.21511/imfi.14(3).2017.02
Publication status	Published - 4 Oct 2017

Bibliographical note

Keywords

Abnormal returns (ARs)
GJR-GARCH
Mergers and acquisitions (M&As)
Shareholders wealth

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10.21511/imfi.14(3).2017.02

Shareholders wealth and mergers and acquisitions
© The author(s) 2017. This publication is an open access article - This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Final published version, 404 KBLicence: CC BY-NC 3.0

Cite this

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title = "Shareholders wealth and mergers and acquisitions (M&AS)",

abstract = "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) fourfactor 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.",

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AU - Kyei-Mensah, Justice

AU - Su, Chen

AU - Joseph, Nathan Lael

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PY - 2017/10/4

Y1 - 2017/10/4

N2 - 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) fourfactor 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.

AB - 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) fourfactor 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.

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KW - GJR-GARCH

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Shareholders wealth and mergers and acquisitions (M&AS)

Abstract

Bibliographical note

Keywords

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