Automatic Stock Market and Trading Algorithmic Improve using Machine Learning and Deep Learning Programming

Abstract

Our Invention Automatic Stock Market and Trading Algorithmic Improve using Machine Learning and Deep Learning Programming is a Stock market prediction regards the forecasting of the price of any given stock within the desired real-time-frame and has been a heavily researched topic over past years due to the difficulty of predicting time-series that are considered to be random walks. Whilst some use traditional Technical Analysis processes and methods such as the calculation and consideration of trends, more recently the problem has attracted the attention of Machine Learning, Deep Learning, and Artificial Intelligence approach. This Invention explores and compares the current Machine Learning, Deep learning approaches involved in predicting the direction and prices of selected stocks for a given real-time range, considering short, medium, and long-term investments. Using these models alongside Natural Language Processing of financial news to predict sudden, extreme fluctuations and Portfolio Optimisation to balance risk and expected return before trading, and the automated trading agent is designed, implemented, and evaluated against the index performance that the stocks are traded upon.