Stock Market Prediction using FB Prophet Model

Abstract

The stock market has always been attracting people with its high returns but with it comes challenges and risks. A stock exchange market depicts savings and investments that are advantageous to increase the effectiveness of the national economy. The future stock returns have some predictive relationships with the publicly available information of present and historical stock market indices. FB PROPHET is a statistical model which is known to be efficient for time series forecasting, especially for short-term prediction. In this paper, we propose a model for forecasting the stock market trends based on the technical analysis using historical stock market data and the FB PROPHET model. This model will automate the process of predicting the direction of future stock price indices, thereby, helping the financial specialists choose better timing for purchasing and/or selling stocks. The results are shown in terms of the web application as frontend and using Python programming language. The obtained results reveal that the FB PROPHET model has a strong potential for short-term prediction of stock market trends.