Automated Stock Sentiment Analysis Using Google Gemini & EODHD News Integration

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