Forecasting Stock Market Index using Artificial Intelligence

Sanskriti Harmukh, Mansi Mishra, Satyam Jain, Archit Chawda, Kauleshwar Prasad, Dinesh Kumar Bhawnani
2022 Zenodo  
In this project, we attempt to implement the most popular Deep Learning technique for Time Series Forecasting since they allow for making reliable predictions on time series in many different problems. Instead of dealing with the data points collected randomly, we are using Time Series model to work upon a sequence of data points at a particular time interval. We are using three major modules to forecast the data, and they are Streamlit, Yahoo Finance, and Facebook Prophet. The user can select
more » ... he number of years according to their convenience for prediction. The data is collected by yfinance and plotted using a python library called Plotly. Each point on the graph represents the date and the opening and closing stock prices for the share market. Based on the historical data we used fbprophet to forecast the stock quotes for the near future. The concerning forecast components like trends and weekly and yearly variations are also plotted. It helps to analyse the prices at a closer range and study the records effectively. This project aims to ease the problem of trading that is faced by Financial Investors.
doi:10.5281/zenodo.6500420 fatcat:6rxbhpuzgfcdfjjz7kfeiv67di