Super Learner for Predicting Stock Market Trends: A Case Study of Jakarta Islamic Index Stock Exchange

Predicting stock market trend is one of the challenging tasks over the years. It has diverse influencing’s factors which cause stock market trend is very dynamic and has high volatility. Forecasting model, which is a prevalent method to predict the stock market trend, has several difficulties with its characteristics. Although forecasting model is efficient, sometimes it has high forecasting error. Formulating forecasting problem into a classification problem might be considered an alternative approach to predict stock market trend. Several kinds of research have shown that machine learning is a suitable method for predicting stock market trend as a classification problem. This paper discusses applying one of powerful machine learning method, which is called Super learner, to predict stock market trends. Besides, this research employs several technical indicators as predictor variables. Results show that the Super Learner model is useful for predicting both the short-term and long-term trend.