Value investing with machine learning: the South Asian market

• Main Author: Yu, Jiawei
• Other Authors: Wang Lipo
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Engineering
• Online Access: https://hdl.handle.net/10356/181605
• Institution: Nanyang Technological University

Stock investment has been one of the core issues in the financial market. South Asian markets are even more unpredictable. This study aims to find what kind of financial decisions investors should make based on a wide variety of financial data with the help of machine learning models in South Asian financial region. This is mainly on predicting stock prices of different companies using the historical data from 2014 to 2023 and using algorithms such as linear regression, SVM, random forest, and XGBoost. By analyzing the model performance, XGBoost model is found to be the most accurate for predicting future stock prices in this paper with RMSE of 0.64, R2 score of 0.80 and MAE of 0.47, and long-term investment decisions are made based on this model.