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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.

fin_assistance_app

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.