Forecasting mergers and acquisitions failure based on partial-sigmoid neural network and feature selection.
Traditional forecasting methods in mergers and acquisitions (M&A) data have two limitations that significantly reduce forecasting accuracy: (1) the imbalance of data, that is, the failure cases of M&A are far fewer than the successful cases (82%/18% of our sample), and (2) both the bidder an...
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| Main Authors: | , |
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| Format: | article |
| Language: | EN |
| Published: |
Public Library of Science (PLoS)
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/e3da5f56e8ad4728ac17c186247e1f44 |
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