/Stock-Market-Prediction-and-Sentiment-Analysis-Web-App

Primary LanguagePython

Stock Market Prediction and Sentiment Analysis Web App.

This repository contains a full-stack application designed to predict stock market trends and analyze sentiment from financial news. It integrates various technologies including Flask, React, MongoDB, and machine learning algorithms.

Overview

The application serves as a tool for investors and financial analysts to gauge market sentiment and predict future stock prices using historical data and news sentiment analysis. It leverages advanced machine learning models to provide insights and visualizations that aid in making informed investment decisions.

Features

  • Stock Prediction: Utilizes ARIMA, and Linear Regression models to forecast future stock prices based on historical data.
  • Sentiment Analysis: Analyzes the sentiment of financial news articles related to specific stocks using NLP techniques to determine market sentiment.
  • Interactive Dashboard: A React-based frontend that displays predictions, sentiment analysis results, and historical data charts.
  • Data Management: Backend API built with Flask to handle data processing and serve the frontend.
  • User History: Keeps track of user history based on email id, and shows their search history during current search.

Tech Stack

  • Frontend: React, Chart.js
  • Backend: Flask
  • Database: MongoDB
  • Machine Learning: Python, Pandas, Scikit-learn, Keras
  • APIs: NewsAPI for fetching recent news articles

Getting Started

Prerequisites

  • Node.js
  • Python 3.x
  • MongoDB
  • Flask

Installation

  1. Clone the repository

    git clone https://github.com/gsai29/Stock-Market-Prediction-and-Sentiment-Analysis-Web-App.git
cd stock-market-prediction-and-sentiment-analysis

  2. Install Python dependencies

     pip install -r requirements.txt

  3. Set up the React application

    Navigate to the React application directory:

     cd my-react-app

    Install Node.js dependencies and build the application:

     npm install
 npm run build

    Navigate back to the main directory:

     cd ..

  4. Start the application

    Run the Flask application which also serves the React frontend:

     python application.py

Live Link

The project is deployed on AWS Elastic Beanstalk. Feel free to check it out - http://stock-env.eba-yb8tcmkf.us-west-2.elasticbeanstalk.com/ .