Stock market prediction using artificial intelligence

Abstract

Nowadays, Artificial Intelligence (AI) is revolutionizing the way of people work and the future development of various fields. With its capacity to process and analyze enormous amounts of data at a speed and precision beyond what humans are capable of, artificial intelligence (AI) has emerged as a major driving force in the field of finance. This project aims to explore the application of three AI-based models, linear regression, support vector machine (SVM), and long short-term memory (LSTM), for predicting stock market prices. The datasets used in this project consists of daily historical prices for the company of DBS, APPLE and TESLA. R-squared (R2) and loss function were used to evaluate the accuracy of each AI model in this project. The results got from each AI model show how well AI-based model can make prediction for non-linear and complicated data in financial markets.