On the Use of Technical Analysis Indicators for Stock Market Price Movement Direction Prediction

Abstract

Technical indicators are algorithms that take financial time series data as input and predict price movement directions based on mathematical calculations. Technical analysts can predict the stock price trends by interpreting the results of different technical indicators. In this study, we investigate the prediction of price movement directions based on the use of technical indicators in learning algorithms. We explore the technical indicators that provide the most successful prediction when they are used together in learning algorithms. In this paper, we investigate the technical indicators that lead to the most successful price movement direction prediction. To do this, we explore all possible combinations of indicators with various machine learning algorithms. Here, a decision support system is proposed to predict price movement direction on financial time series data by using technical indicators in machine learning algorithms.