This project aims to develop a PoC solution for stock analysis and recommendation using financial data and OpenAI API to GPT model.

1. Data Collection
2. Data Preprocessing
3. Feature Selection
4. Integration with OpenAI API
5. Company Evaluation
6. Stock Recommendations
7. Output Presentation
8. Testing and Validation
9. Iterate and Refine

• Stock symbols list (USA)
• Collect the following data using Alpha Vantage API:
  • Stock price:
    • Daily, weekly, and monthly time series.
    • Adjusted close prices for splits and dividends.
  • Fundamental data:
    • Income statement (revenue, net income, etc.).
    • Balance sheet (total assets, total liabilities, etc.).
    • Cash flow statement (operating cash flow, investing cash flow, etc.).
    • Earnings data and estimates.
    • Dividends and stock splits history.

• Handle missing values.
• Convert data types.
• Normalize/scale data if required.

• Identify relevant factors:
  • Revenue growth.
  • Earnings growth.
  • Profit margin.
  • Return on equity.
  • Valuation ratios.

• Send preprocessed data as context/input.
• Include prompt for company evaluation.

• Parse OpenAI API responses.
• Implement scoring system or ranking method.

• Formulate prompts for recommendations.
• Provide context on Warren Buffett principles.

• Display recommended companies in a table/list.
• Include reasons for recommendations.

• Test PoC solution functionality.
• Validate recommendations against historical data/expert opinions.

• Improve solution based on feedback.
• Update data and adapt to market conditions.