What is AnalystRSS?
AnalystRSS is a Python utility that evaluates the prediction accuracy of financial analysts by comparing their price targets to actual stock performance. It identifies the top analysts based on historical performance and generates an RSS feed with their latest reports. The feed is updated every 12 hours and can be served via an HTTP server, so you can easily integrate it with your favorite RSS reader.
Key Features:
In the world of finance, there's an abundance of analyst opinions, but it's challenging to track who consistently makes accurate predictions. I built AnalystRSS to bring transparency to analyst performance and help investors make more informed decisions by spotlighting analysts with a proven track record.
How Does It Work?
The project is open-source and available on GitHub:
GitHub Repository Link
Installation and usage instructions are provided in the README.
Requirements:
I would love to get your feedback! Whether it's suggestions, bug reports, or contributions, feel free to open an issue or submit a pull request on GitHub.
AnalystRSS is a Python utility that evaluates the prediction accuracy of financial analysts by comparing their price targets to actual stock performance. It identifies the top analysts based on historical performance and generates an RSS feed with their latest reports. The feed is updated every 12 hours and can be served via an HTTP server, so you can easily integrate it with your favorite RSS reader.
Key Features:
- Analyst Accuracy Analysis: Compares analyst price targets to real stock prices over a specified time horizon.
- Top Analyst Identification: Ranks analysts based on accuracy and the volume of their predictions.
- RSS Feed Generation: Creates an RSS feed featuring the latest reports from top analysts.
- Built-in HTTP Server: Serves the RSS feed locally for easy access.
- Automated Scheduling: Updates analyst accuracy data weekly and refreshes the RSS feed every 12 hours.
- Multi-threaded Data Fetching: Efficiently gathers data using multi-threading.
- API Rate Limiting: Complies with API usage policies to prevent overloading services.
- Detailed Logging: Keeps track of processes for monitoring and debugging.
In the world of finance, there's an abundance of analyst opinions, but it's challenging to track who consistently makes accurate predictions. I built AnalystRSS to bring transparency to analyst performance and help investors make more informed decisions by spotlighting analysts with a proven track record.
How Does It Work?
- Symbol Input: You provide a list of stock symbols you're interested in.
- Data Collection: The tool fetches historical analyst price targets and stock prices.
- Performance Analysis: It evaluates each analyst's predictions against actual stock performance over your specified time horizon.
- Top Analysts Selection: Identifies and ranks the top analysts based on accuracy and prediction volume.
- RSS Feed Creation: Generates an RSS feed with the latest reports from these top analysts.
- HTTP Serving: An optional built-in server lets you access the RSS feed locally.
The project is open-source and available on GitHub:
GitHub Repository Link
Installation and usage instructions are provided in the README.
Requirements:
- Python 3.7 or higher
- API key from Financial Modeling Prep
I would love to get your feedback! Whether it's suggestions, bug reports, or contributions, feel free to open an issue or submit a pull request on GitHub.
