Explainable Graph-Based Deep Learning Framework for Stock Price Forecasting and Systemic Risk Intelligence in the Philippine Stock Exchange

Authors

  • Almina S. Mualla, Jehana Muallam-Darkis, Alnahar A. Amirul, Aldaruhz T. Darkis

Keywords:

methods, companies, decisions

Abstract

The Philippine stock market is a sophisticated financial market where stock prices are determined not just by the performance of companies that are listed, but on the company's ties with other companies, industry sectors, and the wider economy. Given the significance of stock price forecasting, it has emerged as a pivotal field in financial analytics that can aid in investment decisions, portfolio management, and financial-risk assessment. Traditional methods have modeled financial assets mostly as individual time series; however, these methods can be challenged in describing the complex nature of financial markets. Specifically, information information received from one company could include predictive information for another company if the two companies are related based on industry, supply chain, market behavior, or financial relationships.

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Published

31.12.2023

How to Cite

Almina S. Mualla. (2023). Explainable Graph-Based Deep Learning Framework for Stock Price Forecasting and Systemic Risk Intelligence in the Philippine Stock Exchange. International Journal of Intelligent Systems and Applications in Engineering, 11(11s), 1163–1176. Retrieved from https://mail.ijisae.org/index.php/IJISAE/article/view/8502

Issue

Vol. 11 No. 11s (2023)

Section

Research Article

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