event-driven

To convert sentiment signals into trading actions, you score sentiment-driven events using an LLM and blend them with technical indicators. This approach applies time-decayed aggregation to event data, producing a weighted, actionable trading signal.

Time-decayed aggregation for event-driven trading signals weights recent sentiment events more heavily than older ones. This mechanism produces a cohesive event signal that you can flexibly combine with your technical indicators.

Yes, you can use CSV files to ingest news and macro data for LLM sentiment scoring. The system utilizes a CSV-based event data layer to process earnings, macro, and policy events before applying LLM-based scoring prompts.

You blend event-driven signals with technical indicators by applying flexible weighting to tune their relative influence. This allows you to customize your quantitative trading strategy by combining time-decayed event scores with technical data.

The best way to score sentiment-driven events for quantitative trading is using an LLM to evaluate text from news and macro updates. This quantifies qualitative data, which is then aggregated with time decay to generate final trading signals.

Yes, this approach supports earnings, macro, policy, and sentiment events. It ingests these event types via CSV, applies LLM-based sentiment scoring, and integrates the results with technical indicators for comprehensive trading signals.