Utilizing Graph Neural Networks for Identifying Similar Securities

Author(s)	Satyam Chauhan
Country	United States
Abstract	Identifying similar securities is a critical task in financial analytics, influencing diversification, risk assessment, and portfolio management. This study presents a novel framework combining ChatGPT and Graph Neural Networks (GNNs) to enhance the analysis of structured and unstructured financial data. The integrated model leverages semantic embeddings and historical financial metrics for superior clustering accuracy, achieving significant improvements in normalized discounted cumulative gain and F1 scores. By capturing nuanced relationships, the proposed framework offers a robust solution for financial decision-making.
Keywords	ChatGPT, Financial Analytics, Graph Neural Networks, Securities Analysis, Textual Embeddings
Published In	Volume 6, Issue 2, February 2025
Published On	2025-02-21
Cite This	Utilizing Graph Neural Networks for Identifying Similar Securities - Satyam Chauhan - IJLRP Volume 6, Issue 2, February 2025. DOI 10.5281/zenodo.14905620
DOI	https://doi.org/10.5281/zenodo.14905620
Short DOI	https://doi.org/g85r7m

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