Real-Time Financial Advisor App

deployed: https://financialadvisorapp.streamlit.app/

Overview

This Financial Advisor App is a Streamlit-based web application that provides users with real-time stock analysis, price predictions, and portfolio management tools. It's designed to assist users in making informed decisions about their investments by offering stock recommendations and portfolio insights.

Features

• User Authentication: Secure login and registration system
• Real-time Stock Data: Fetch and display current stock information
• Stock Price Visualization: Interactive candlestick charts for selected stocks
• Price Prediction: 30-day stock price forecast using LSTM neural networks
• Stock Recommendations: Buy/Sell/Hold recommendations based on current market trends
• Portfolio Management: Add stocks to your portfolio and track their performance
• Portfolio Analysis: View total value, profit/loss, and holdings distribution

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/financial-advisor-app.git
   cd financial-advisor-app
   

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
   

3. Install the required packages:

   pip install -r requirements.txt
   

Usage

1. Run the Streamlit app:

   streamlit run fin_advisor_app.py
   

2. Open a web browser and go to http://localhost:8501 (or the URL provided in the terminal).

3. Register for a new account or log in if you already have one.

4. Use the sidebar to navigate through different features of the app.

Dependencies

• streamlit
• yfinance
• pandas
• plotly
• scikit-learn
• tensorflow
• sqlalchemy

For a complete list of dependencies, see requirements.txt.

Database

The app uses SQLite as its database. The database file (financial_advisor.db) will be created in the same directory as the script when you run the app for the first time.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is open source and available under the MIT License.

Future Improvements

• Implement more advanced recommendation algorithms
• Add more technical indicators and fundamental analysis
• Incorporate news sentiment analysis for stocks
• Provide more detailed portfolio analytics and rebalancing suggestions
• Implement real-time price updates using websockets

Disclaimer

This app is for educational purposes only. It should not be considered as financial advice. Always do your own research and consult with a qualified financial advisor before making investment decisions.

License

This project is open source and available under the MIT License.