Financial News Analyzer

A Python-based financial news analysis tool that fetches real-time financial news and provides sentiment analysis, market impact assessment, and key insights extraction.

Features

• Real-time Financial News: Fetches latest financial news using the Currents API
• Smart Filtering: Automatically identifies and filters finance-related news
• Sentiment Analysis: Dual-mode sentiment analysis using:
  • OpenAI GPT-3.5 for advanced analysis
  • Rule-based fallback system for reliability
• Entity Extraction: Identifies key financial entities including:
  • Companies
  • Sectors
  • Financial instruments
• Metrics Analysis: Extracts and analyzes financial metrics from news content
• Comprehensive Reporting: Generates detailed analysis reports including:
  • Overall sentiment score
  • Market impact assessment
  • Confidence levels
  • Critical quotes
  • Market implications

Prerequisites

• Python 3.8+
• Currents API key
• OpenAI API key (optional, falls back to rule-based analysis if not provided)

Installation

1. Clone the repository:

git clone https://github.com/yourusername/financial-news-analyzer.git
cd financial-news-analyzer

2. Install required packages:

pip install -r requirements.txt

3. Create a .env file in the project root:

NEWS_API_KEY=your_currents_api_key
OPENAI_API_KEY=your_openai_api_key  # Optional

Usage

Run the analyzer:

python main.py

The program will:

1. Fetch the latest financial news
2. Filter for finance-related articles
3. Perform sentiment analysis
4. Generate detailed reports for each article

Project Structure

financial-news-analyzer/
├── config.py                 # Configuration settings
├── main.py                  # Main application entry point
├── models/
│   └── article.py          # Data models
├── services/
│   ├── news_service.py     # News fetching service
│   └── analysis/
│       ├── entity_extractor.py    # Entity extraction
│       ├── metrics_extractor.py   # Financial metrics extraction
│       └── sentiment_analyzer.py  # Sentiment analysis
└── utils/
    ├── date_utils.py       # Date handling utilities
    └── text_processor.py   # Text processing utilities

Configuration

Key configuration options in config.py:

• MAX_ARTICLES: Maximum number of articles to analyze
• SENTIMENT_THRESHOLD: Threshold values for sentiment classification
• OPENAI_MODEL: OpenAI model selection
• API configuration settings

Error Handling

The system includes robust error handling:

• Graceful fallback to rule-based analysis if OpenAI is unavailable
• Comprehensive logging for debugging
• Input validation and error reporting

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Currents API for financial news data
• OpenAI for advanced text analysis capabilities