The goal of this project was to utilize a popular graphmachine learning framework, GraphSAGE, to predict mergers and acquisitions of enterprise companies . The results were promising, as the modelpredicted with 81.79% accuracy on a validation dataset . Given the abundance of data sources and algorithmic decision making within financial data science,graph-based machine learning offers a performant, yet non-traditional approach to generating alpha . The model was successful, as it predicted with an accuracy of 80% on a validated dataset .

Author(s) : Keenan Venuti

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Keywords : learning - data - mergers - graph - dataset -

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