idea-generation-engine

Equity idea generation combines insider activity, short-squeeze setups, M&A signals, and sentiment-versus-fundamental divergence. The engine normalizes these candidates and categorizes them into long ideas, short ideas, and event-driven trades.

Validating competing theses uses structured multi-round debate or independent agent passes. This process compares the conflicting investment rationales and outputs a debate summary with cross-signal alignment before final ranking.

Multi-source signal fusion for event-driven trades merges M&A signals with sentiment-fundamental divergence. It normalizes the data to surface event-driven setups and outputs structured results for ranking.

Automating cross-signal alignment is supported through independent agent passes. The engine processes insider activity and short-squeeze setups to output a structured alignment summary without manual intervention.

Automated equity idea ranking requires inputs from multiple alpha modules. It uses signals like insider activity, short-squeeze setups, and sentiment-fundamental divergence to categorize and rank long, short, and event-driven candidates.