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Graph neural network for merger and acquisition prediction
2021
Proceedings of the Second ACM International Conference on AI in Finance
This paper investigates the application of graph neural networks (GNN) in Mergers and Acquisitions (M&A) prediction, which aims to quantify the relationship between companies, their founders, and investors. M&A is a critical management strategy to decide if the company is to grow or downsize, and M&A prediction has been a challenging research topic in the past few decades. However, the traditional methods of predicting M&A probability are only based on the company's fundamentals, such as
doi:10.1145/3490354.3494368
fatcat:lb4khcz6jfbf7ixuo7jz6q3nh4