(untitled) (Trinity Journal of Management, IT & Media (TJMITM), 2022)
Investors who trade stocks must have access to timely information to make wise decisions. The decision-making process is influenced by a variety of elements because a stock exchange trades various stocks. Additionally, stock price behaviour is unpredictable and challenging to forecast. These factors make stock price forecasting both a crucial and difficult procedure. Finding the prediction model with the lowest error rate and highest forecast accuracy becomes the focus of this research. This article summarises studies on machine learning methods and algorithms used to increase stock price prediction precision.