Stock selection strategies via fundamental, technical and new analysis in SGX consumer stocks

Abstract

Stock market investment has been risky due to its volatility. Investors and analysts have adopted different types of strategies for stock picking and trading. Fundamental (FA), stock prediction, technical (TA) or news (NA) analysis are the most widely used strategies to identify the outperform stocks. In this paper, methodologies for FA, stock prediction with technical indicators, and NA were combined to investigate the effectiveness in stock investing. A ranking methodology on fundamental analysis includes the studies of quantitative and qualitative exploration for the businesses. Next, machine learning techniques such as random forests, support vector machines, and long-short term memory, were deployed with technical indicators featured. The insights of the stock trend were also analysed with the economy, politics, and company news. It was concluded that the combination of strategies was effective, as the news has shown a strong correlation with the stock movement.