Visualising and Forecasting Stock Prices with Flask

Abstract

Abstract: Stock price forecasting and visualisation are critical tasks for investors and traders in financial markets. In this project, we have developed a web application that can visualise stock prices of the company in form of charts and predicts future stock prices using machine learning algorithms. The web application is built using Flask(python), a popular web framework, and integrates several APIs and libraries, including News API, Alpha Vantage API, Beautiful Soup (bs4), Pandas, Numpy, Plotly, and Scikit-learn. The application provides users with a basic overview of the company, current prices of the stock, news related to the company, and visualisations of historical stock prices in the form of charts. The historical stock prices are fetched using Alpha Vantage API, and the charts are generated using Plotly library. The web application also includes a predictive model built using Support Vector Regression (SVR) algorithm which forecasts the stock prices. This paper demonstrates the potential of machine learning algorithms and web technologies in the field of stock price forecasting and visualisation. The web application developed, provides users with valuable insights and information related to stock prices, and it can be used as a powerful tool in financial markets.