Utilizing Graph Neural Networks for Identifying Similar Securities
Year: 2025
Type: article
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.
Author: Satyam Chauhan
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6911941350