alphasift

What problem does it solve?

AlphaSift automates discovery and ranking of A-share stock candidates by applying YAML-defined strategies and emitting structured candidate outputs for further analysis.

Core Features & Use Cases

• End-to-end stock discovery: screen the full market, apply deterministic hard filters, and generate ranked candidate lists.
• LLM-assisted ranking: optional cross-candidate reasoning, theses, catalysts, risks, and confidence for portfolio risk evaluation.
• Post-analysis integration: optional DSA or external HTTP analyzers, with T+N evaluation saved runs for later review.
• Industry/heat context: supports local industry maps and board heat scores to diversify candidate exposure.

Quick Start

Run alphasift quickstart to see a minimal end-to-end workflow.