edge-hint-extractor

Extracting trading edge hints from market data requires processing daily market observations and news reactions. The script analyzes this input to generate structured, actionable insights for trading strategy development and risk management.

Edge hint extraction in trading strategy development is the process of identifying actionable market insights from raw observations and news reactions. It transforms unstructured market data into structured hints to inform trading decisions and manage risk.

Yes, you can enhance market analysis hints through optional LLM ideation. By integrating an external LLM CLI or a pre-written hints file, the script augments extracted market observations with generated ideas for deeper trading insights.

Yes, automating news reaction analysis requires Python 3.9 or higher and the PyYAML library. These dependencies are necessary to run the scripts that process market observations and generate structured edge hints.

To generate trading insights from a pre-written hints file, run the extraction script with your market summary and news reactions data. The script processes these inputs to output structured edge hints for trading decisions.

Using an external LLM CLI for market observation analysis is optional and requires your own external setup. Without it, the script still processes market data and news reactions using your pre-written hints file to generate trading insights.