Building a Real-Time Financial Sentiment API: Handling Noise and LLM Hallucinations

Financial markets move faster than human cognition. A geopolitical headline can trigger automated oil liquidations within milliseconds. A single earnings report can wipe out a company’s valuation before a retail trader finishes reading the first paragraph. I set out to build a production-grade system that could automatically ingest unstructured global financial news feeds, parse the entities affected, determine the sentiment polarity, and expose the results as machine-readable market signals.