CashTagNN: Exploiting the use of cashtags to predict stock market prices using convolutional networks

Research areas:ML-Assisted Systems
Systems & Workloads
Methods & Models
Problems & Goals

Abstract:

In this paper we discuss a system, CashTagNN, which uses the sentiment and subjectivity scores of tweets that include cashtags of two companies, Apple and Johnson and Johnson, to model stock market movement, and in particular predict opening and closing stock market prices. We demonstrate that by using only sentiment and subjectivity along with a neural network machine learning model we can predict the opening and closing prices of the two companies with high accuracy.