Stocks Recommendation Using Stock Price Prediction and Sentiment Analysis

Overview

This project aims to provide stock recommendations by combining stock price prediction with sentiment analysis. Focusing on SP 500 companies, it leverages historical data, tweets, and financial news sentiments.

Key Features

• Predictive analysis of stock prices using ARIMA and LSTM models.
• Sentiment analysis using VADER on social media and news data.
• Web-based platform for insightful stock investment decisions.

Technologies

• Machine Learning: ARIMA, LSTM
• Natural Language Processing: VADER Sentiment Analysis
• Data Sources: SP 500 company stocks, Twitter, Financial News
• Frontend with Angular

Installation and Running

First, ensure that you have Node.js and the Angular CLI installed. Then, you can proceed with the following steps:

1. Open a Terminal or Command Prompt and navigate to your project's directory.
2. Install Dependencies: Run npm install to install the necessary packages and dependencies defined in your project's package.json file.
3. Start the Development Server: Execute ng serve to start the local development server. This command will compile your application and host it locally.
4. Access the Application: By default, the Angular application runs on http://localhost:4200. Open this URL in a web browser to view your application.

If you encounter any issues, ensure that your Angular CLI is up to date and that your project's configuration files are correctly set up.

Future Scope

Plans to enhance the model for safer investment recommendations and expanding market analysis scope.

For more detailed insights, refer to our full project documentation.