Predicting SP500 Price Through Machine Learning and Natural Language Processing

Abstract

Achieving better returns than the overall market has long been a subject of interest among researchers, politicians, and investors alike. Extensive literature and studies have attempted to identify financial market characteristics that can enhance the likelihood of accurately forecasting market movements. Some studies have focused on technical analysis of the financial market, such as analyzing macroeconomic factors that could affect market behavior, while others have explored the use of market social sentiments. These studies indicate that employing technical analysis and utilizing sentiment data from social media could lead to better investment decisions and returns. This paper aims to analyze technical analysis strategies in combination with social sentiment analysis to evaluate the feasibility of these investment strategies in achieving superior returns compared to the overall market.