On the Effectiveness of Technical Analysis, Time Series Analysis and Machine Learning Approaches in Forecasting Stock Markets Movement Direction

Wong, Jian Zhi (2020) On the Effectiveness of Technical Analysis, Time Series Analysis and Machine Learning Approaches in Forecasting Stock Markets Movement Direction. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

Stock market, also known as the equity market, is a financial market that enables public to buy and sell shares of publicly traded companies. It has always been a difficult task to forecast the exact future price of the stock market index. There are a lot of researches being conducted regarding about forecasting of the movement direction of the index. Hence, the purpose of this research is to find out the effectiveness, accuracy and usefulness of technical analysis, time series analysis and machine learning approaches to predict movement direction of stock market as whole. The effectiveness and accuracy were measured by evaluating the amount earned from daily trading and its winning percentage. Overall, daily breakout system and Aroon system, indicators in technical analysis, are more effective in performing daily trading compared to other indicators. Keywords: stock market movement direction, technical analysis, time series analysis, machine learning