Kian Zhong Siaw

This is my self-initiated Final Year Research Project and had been solely done. A lot of researchers and experts from different areas have proved that there is a high relationship between the news articles and the behavior of the stock market. In this project, the experiments which capture the impact of news articles on stock market have been successfully performed. The results have shown that there is strong information quotient in news articles which affect the stock market trend prediction. Data crawling techniques and MongoDb database are incorporate in the application architecture. News articles are aligned to the stock trends basic on the idea of Efficient Market Hypothesis. The possible combinations of phrases are formed by Part of Speech Tagging. The selection of meaningful words and phrases is based on statistics. Finally, the relationship between the news articles and direction of the stock trends are learned through machine learning. Different type of machine learning model and different parameter are executed to find the best prediction method. In particular, a market simulation using real-life data is conducted. The study shows that there is a high relationship between news articles and the direction of the stock trends. Furthermore, by monitoring this relationship, actionable decisions could be made.