event-driven

To convert real-time news into event-driven trading signals, you can use an LLM-based scoring prompt to assess sentiment and output a standardized event CSV containing the date, event type, score, source, and summary for structured decision-making.

Time decay in signal aggregation is a mechanism that reduces the weight of older event signals over time. It blends these scores with technical indicators using weighted aggregation to produce a combined signal for backtesting and live trading.

You can build a trading strategy around earnings releases and macro announcements by scoring the impact of these events using a standardized prompt, generating an event CSV, and blending the resulting signals with technical indicators for consistent decision-making.

Yes, you can use sentiment analysis CSV files for live trading workflows. The generated event CSV follows a standardized schema and integrates with a signal engine that applies weighted aggregation to support both backtesting and live trading environments.

Event-driven signal generation can produce a standalone event CSV and sentiment score without external data, but the signal engine is designed to blend event scores with technical indicators using weighted aggregation to output a fully combined trading signal.