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AI Stock Analyzer leveraging the Modern Portfolio Theory and Black-Litterman model to make recommendations.

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SmartStock πŸ§ πŸ“ˆ

An AI-powered tool that is designed to provide recommendations on the stock market by utilizing a combination of traditional financial indicators and modern portfolio theory models. SmartStock leverages the power of Large Language Models (LLMs), particularly that of OpenAI, to analyze key performance indicators (KPIs) and provide actionable recommendations.

πŸ‘€ What does it do?

  • Calculates and visualizes popular KPIs like RSI, Bollinger Bands, and MACD for specific stocks,
  • Looks at the Price-to-Earnings (P/E) ratio to help you understand how a stock is valued,
  • Checks each stock’s Beta to show how risky or volatile it is compared to the overall market,
  • Uses GPT-4o to summarize the data and give you clear, easy-to-understand investment insights,
  • Helps you take steps toward an optimized portfolio by maximizing the Sharpe Ratio for better returns at a given level of risk,
  • Allows you to add your own views with the Black-Litterman model to create a more customized and balanced portfolio.

πŸ–₯️ Technologies Used

  • Python – Main programming language utilized
  • yfinance – To fetch historical stock data
  • PyPortfolioOpt – For portfolio optimization using MPT and Black-Litterman models
  • langchain-openai – To interact with OpenAI's language models
  • Matplotlib – To create visualizations
  • NumPy & Pandas – For data manipulation and analysis.

⚠️ Disclaimer

SmartStock is a research and educational tool. It uses AI-generated analysis, which could potentially include inaccuracies or outdated information. This project does not offer financial advice and should not be used to make investment decisions. Always consult a qualified financial advisor or professional before making any financial decisions or ventures.

πŸ“ Setup

  1. Clone the repository:

    git clone https://github.com/EKahyaoglu/SmartStock.git
    cd SmartStock
  2. Open the .ipynb notebook in your preferred environment:

    • Jupyter Notebook
    • JupyterLab
    • Google Colab
    • Visual Studio Code (VS Code)
  3. Replace api_key with your OpenAI API Key:

    api_key = "YOUR_API_KEY"

You can create an OpenAI API Key on https://platform.openai.com.

  1. Run the cells and start exploring your stock insights!

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AI Stock Analyzer leveraging the Modern Portfolio Theory and Black-Litterman model to make recommendations.

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