Associating fundamental features with technical indicators for analyzing quarterly stock market trends using machine learning algorithms

Abstract

The stock market is the primary entity driving every major economy across the globe, with each investment designed to capitalize on profit while decreasing its associated risks. As a result of the stock market’s importance, there have been enumerable studies conducted with the goal of predicting the stock market through data analysis techniques including machine learning, neural networks, and time series analysis. This paper uses machine learning algorithms to perform stock market index classification using fundamental data while classifying the indices using technical indicators. The data were derived from Yahoo Finance on the top 100 indices in the NASDAQ stock market from January 2000 to December 2020.