Machine Learning Based Stock Prediction and Analysis

Document Type : Primary Research paper

Authors

1 Students Department of Computer Engineering, Jagadambha College of Engineering Technology Yavatmal

2 Assistant Professor Department of Computer Engineering, Jagadambha College of Engineering Technology Yavatmal

Abstract

India's stock market is extremely variable and indeterministic, which has a limitless number of aspects that regulate the directions and trends of the stock market; therefore, predicting the uptrend and downtrend is a complicated process. This paper presents advance method for stock price prediction and forecasting using companies financial performance on quarterly and yearly basis. This helps the investor to stay invest for Long term. There are many factors that influence stock price prediction, such as company fundamentals and internal (earning per share (EPS), dividend per share, and book values) and external factors (government rules and regulations, inflation, and other economic situations, such as gross domestic product (GDP), money supply, fluctuation in oil prices and environmental conditions). The proposed system has been implemented as a web app using Django and React. The React Web App displays all live prices and news received from the self-built Django Server via web scraping. Additionally, the Django server serves as a bridge between the React frontend and the machine learning algorithm built with Keras and further enhanced with scikit-learn.

Keywords

Int. J. of Aquatic Science
Volume 14, Issue 1
2023
Pages 81-85

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