The purpose of this project is to investigate the effect of several variables on the prediction of stock prices with emphasis on the analysis of the correlation between stock price and news media. Moreover, prediction of future stock movement using the Convolutional Neural Network model allows the User to choose a company from the S&P 500 and predict the price movement of a company's stock on the next trading move based on current sentiment (Vader) from GoogleNews articles related to such company.
Looking for executable orders using automated pre-programmed trading instructions accounting for variables such as VIX, Beta, price, sentiment, and volume?
You've come to the right place, we'll have your back using vix score volitality measurement to decide whether to buy, sell or hold on to your investment. In this project, we'll be comparing prices of the past three to four years. We will follow corporations and build a algorethmic robo advisor that can guide you with your investments... it'll research new media and past stock patterns to come up with the best decision for your stock invesment so you don't have to spend time following market trends. Our bot will be equiped for trading attempts that leverage the speed and computational resources of computers relative to human traders. According to a Wallstreet journal article, a study in 2019 showed that around 92% of trading in the Forex market was performed by trading algorithms rather than humans.