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Forecasting Stock Market Index using Artificial Intelligence

Sanskriti Harmukh, Mansi Mishra, Satyam Jain, Archit Chawda, Kauleshwar Prasad, Dinesh Kumar Bhawnani

Abstract


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 the 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.


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References


Stock Market Analysis and Prediction using Artificial Neural Networks, Tribhuvan University Institute of Engineering Himalaya College of Engineering, Code No: CT755

Tsai, K. H., & Wang, J. C. (2009). External technology sourcing and innovation performance in LMT sectors: An analysis based on the Taiwanese Technological Innovation Survey. Research Policy, 38(3), 518-526.

Patil, R. Time Series Analysis and Stock Price Forecasting using Machine Learning Techniques.

Introduction to Fundamentals of Time Series data and analysis by Eric (Director of Applications and Training at Aptech Systems, Inc.).

Azoff, E. M. (1994). Neural network time series forecasting of financial markets. John Wiley & Sons, Inc..

Ji, X., Wang, J., & Yan, Z. (2021). A stock price prediction method based on deep learning technology. International Journal of Crowd Science.

Vijh, M., Chandola, D., Tikkiwal, V. A., & Kumar, A. (2020). Stock closing price prediction using machine learning techniques. Procedia computer science, 167, 599-606.

Yetis, Y., Kaplan, H., & Jamshidi, M. (2014, August). Stock market prediction by using artificial neural network. In 2014 world automation congress (WAC) (pp. 718-722). IEEE.


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