Forecasting Singapore exchange stocks (commodities & transport) : combined analyses of fundamental, technical, and news techniques

• Main Author: Goh, Justin Junn Hau
• Other Authors: Wong Jia Yiing, Patricia
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/149581
• Institution: Nanyang Technological University

This report constitutes the knowledge, learning processes, and stocks analyses conducted by the writer for his final year project. Selection of profitable Singapore Exchange (SGX) transportation and commodity stocks proved to be ever more challenging and complicated due to the strong volatility in the market. Hence, many banking analysts and investors working in the financial hubs are finding new solutions and strategies to beat the market. In past research papers, there were inadequate analyses conducted solely on SGX stocks that showed efficacy in yielding high profit margins for investors. In this paper, three methods of analyses are carried out for the sector of transportation and commodity- fundamental analysis (FA), technical analysis (TA), and news analysis (NA). Grey Relational Analysis (GRA) theory and an adopted data envelopment analysis (DEA) model, i.e. Charnes, Cooper and Rhodes (CCR), are used to identify optimal financial efficiency of each stock, which is based on multi decision-making variables obtained from the balance sheets, income statement, and cash flow. A series of technical indicators are applied for further analysis of these stocks to simulate profit margins on Pinescript-TradingView. The effectiveness of each technical indicators is evaluated based on the writer’s interpretation to determine the probability of winnings with numerous back-testing between the year 2015 and 2019. These top ranked stocks would be further studied with the information of ex-dividend date, news headlines, and companies’ latest updates- i.e. announcements earnings.