Overview
This workflow automates the process of stock sentiment analysis by integrating real-time news data with advanced AI language models. It streamlines the collection, analysis, and storage of sentiment insights for multiple stock tickers.
Key Features
- Automated News Retrieval: Fetches the latest articles for each stock ticker using the EODHD News API.
- AI-Powered Sentiment Analysis: Utilizes Google Gemini via LangChain to analyze news sentiment for each ticker.
- Batch Processing: Efficiently processes multiple tickers in batches, handling invalid entries gracefully.
- Data Management: Reads tickers from and writes results to Google Sheets, ensuring seamless data flow.
- Custom Logic & Validation: Employs conditional logic and custom code nodes to validate tickers and format outputs.
Benefits
- Time Savings: Eliminates manual research and analysis, delivering rapid, consistent sentiment insights.
- Accuracy: Leverages state-of-the-art AI for nuanced sentiment evaluation.
- Scalability: Easily scales to analyze large lists of tickers with minimal user intervention.
- Centralized Reporting: Consolidates results in Google Sheets for easy access and further analysis.
Use Cases
- Investment Research: Supports analysts and investors in making informed decisions based on real-time sentiment.
- Market Monitoring: Enables financial teams to track sentiment trends across multiple stocks efficiently.
- Automated Alerts: Can be extended to trigger notifications based on sentiment thresholds.
Integrations
- Google Gemini (LangChain) for AI analysis
- EODHD News API for news data
- Google Sheets for data
