Scenario based merger & acquisition forecasting
While there is no doubt that M&A activity in the corporate sector follows wave-like patterns, there is no uniquely accepted definition of such a “merger wave” in a time series context. Count-data time series models are often employed to measure M&A activity and merger waves are then defined...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-12-01
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| Series: | Management şi Marketing |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/mmcks-2024-0026 |
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| Summary: | While there is no doubt that M&A activity in the corporate sector follows wave-like patterns, there is no uniquely accepted definition of such a “merger wave” in a time series context. Count-data time series models are often employed to measure M&A activity and merger waves are then defined as clusters of periods with an unusually high number of M&A deals retrospectively. However, the distribution of deals is usually not normal (Gaussian). More recently, different approaches that take into account the time-varying nature of M&A activity have been proposed, but still require the a-priori selection of parameters. We propose adapting the combination of the Local Parametric Approach and Multiplier Bootstrap to a count data setup in order to identify locally homogeneous intervals in the time series of M&A activity. This eliminates the need for manual parameter selection and allows for the generation of accurate forecasts without any manual input. |
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| ISSN: | 2069-8887 |